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f7fe5cc57b8dc3dbda90bbec12570fac6442abf1 | 778,605 | py | Python | test/unit/test_cloudant_v1.py | IBM/cloudant-python-sdk | e5c6dfb7a0b932025e3249dece60658e390a4e8d | [
"Apache-2.0"
] | 19 | 2020-11-10T13:50:54.000Z | 2022-03-28T03:35:53.000Z | test/unit/test_cloudant_v1.py | IBM/cloudant-python-sdk | e5c6dfb7a0b932025e3249dece60658e390a4e8d | [
"Apache-2.0"
] | 129 | 2020-08-19T14:20:18.000Z | 2022-03-31T07:39:30.000Z | test/unit/test_cloudant_v1.py | IBM/cloudant-python-sdk | e5c6dfb7a0b932025e3249dece60658e390a4e8d | [
"Apache-2.0"
] | 5 | 2020-06-29T15:25:41.000Z | 2021-08-16T23:33:35.000Z | # -*- coding: utf-8 -*-
# (C) Copyright IBM Corp. 2021.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Unit Tests for CloudantV1
"""
from datetime import datetime, timezone
from ibm_cloud_sdk_core.authenticators.no_auth_authenticator import NoAuthAuthenticator
from ibm_cloud_sdk_core.utils import datetime_to_string, string_to_datetime
import base64
import inspect
import io
import json
import os
import pytest
import re
import requests
import requests.models
import responses
import tempfile
import urllib
import gzip
from ibmcloudant.cloudant_v1 import *
_service = CloudantV1(
authenticator=NoAuthAuthenticator()
)
_base_url = 'http://localhost:5984'
_service.set_service_url(_base_url)
##############################################################################
# Start of Service: Server
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetServerInformation():
"""
Test Class for get_server_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_server_information_all_params(self):
"""
get_server_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/')
mock_response = '{"couchdb": "couchdb", "features": ["features"], "vendor": {"name": "name", "variant": "variant", "version": "version"}, "version": "version", "features_flags": ["features_flags"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_server_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_server_information_all_params_with_retries(self):
# Enable retries and run test_get_server_information_all_params.
_service.enable_retries()
self.test_get_server_information_all_params()
# Disable retries and run test_get_server_information_all_params.
_service.disable_retries()
self.test_get_server_information_all_params()
class TestGetMembershipInformation():
"""
Test Class for get_membership_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_membership_information_all_params(self):
"""
get_membership_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_membership')
mock_response = '{"all_nodes": ["all_nodes"], "cluster_nodes": ["cluster_nodes"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_membership_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_membership_information_all_params_with_retries(self):
# Enable retries and run test_get_membership_information_all_params.
_service.enable_retries()
self.test_get_membership_information_all_params()
# Disable retries and run test_get_membership_information_all_params.
_service.disable_retries()
self.test_get_membership_information_all_params()
class TestGetUuids():
"""
Test Class for get_uuids
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_uuids_all_params(self):
"""
get_uuids()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_uuids')
mock_response = '{"uuids": ["uuids"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
count = 1
# Invoke method
response = _service.get_uuids(
count=count,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'count={}'.format(count) in query_string
def test_get_uuids_all_params_with_retries(self):
# Enable retries and run test_get_uuids_all_params.
_service.enable_retries()
self.test_get_uuids_all_params()
# Disable retries and run test_get_uuids_all_params.
_service.disable_retries()
self.test_get_uuids_all_params()
@responses.activate
def test_get_uuids_required_params(self):
"""
test_get_uuids_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_uuids')
mock_response = '{"uuids": ["uuids"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_uuids()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_uuids_required_params_with_retries(self):
# Enable retries and run test_get_uuids_required_params.
_service.enable_retries()
self.test_get_uuids_required_params()
# Disable retries and run test_get_uuids_required_params.
_service.disable_retries()
self.test_get_uuids_required_params()
class TestGetCapacityThroughputInformation():
"""
Test Class for get_capacity_throughput_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_capacity_throughput_information_all_params(self):
"""
get_capacity_throughput_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_capacity_throughput_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_capacity_throughput_information_all_params_with_retries(self):
# Enable retries and run test_get_capacity_throughput_information_all_params.
_service.enable_retries()
self.test_get_capacity_throughput_information_all_params()
# Disable retries and run test_get_capacity_throughput_information_all_params.
_service.disable_retries()
self.test_get_capacity_throughput_information_all_params()
class TestPutCapacityThroughputConfiguration():
"""
Test Class for put_capacity_throughput_configuration
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_capacity_throughput_configuration_all_params(self):
"""
put_capacity_throughput_configuration()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
blocks = 0
# Invoke method
response = _service.put_capacity_throughput_configuration(
blocks,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['blocks'] == 0
def test_put_capacity_throughput_configuration_all_params_with_retries(self):
# Enable retries and run test_put_capacity_throughput_configuration_all_params.
_service.enable_retries()
self.test_put_capacity_throughput_configuration_all_params()
# Disable retries and run test_put_capacity_throughput_configuration_all_params.
_service.disable_retries()
self.test_put_capacity_throughput_configuration_all_params()
@responses.activate
def test_put_capacity_throughput_configuration_value_error(self):
"""
test_put_capacity_throughput_configuration_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
blocks = 0
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"blocks": blocks,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_capacity_throughput_configuration(**req_copy)
def test_put_capacity_throughput_configuration_value_error_with_retries(self):
# Enable retries and run test_put_capacity_throughput_configuration_value_error.
_service.enable_retries()
self.test_put_capacity_throughput_configuration_value_error()
# Disable retries and run test_put_capacity_throughput_configuration_value_error.
_service.disable_retries()
self.test_put_capacity_throughput_configuration_value_error()
# endregion
##############################################################################
# End of Service: Server
##############################################################################
##############################################################################
# Start of Service: Changes
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetDbUpdates():
"""
Test Class for get_db_updates
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_db_updates_all_params(self):
"""
get_db_updates()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_db_updates')
mock_response = '{"last_seq": "last_seq", "results": [{"account": "account", "db_name": "db_name", "seq": "seq", "type": "created"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
feed = 'normal'
heartbeat = 0
timeout = 0
since = '0'
# Invoke method
response = _service.get_db_updates(
feed=feed,
heartbeat=heartbeat,
timeout=timeout,
since=since,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'feed={}'.format(feed) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'since={}'.format(since) in query_string
def test_get_db_updates_all_params_with_retries(self):
# Enable retries and run test_get_db_updates_all_params.
_service.enable_retries()
self.test_get_db_updates_all_params()
# Disable retries and run test_get_db_updates_all_params.
_service.disable_retries()
self.test_get_db_updates_all_params()
@responses.activate
def test_get_db_updates_required_params(self):
"""
test_get_db_updates_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_db_updates')
mock_response = '{"last_seq": "last_seq", "results": [{"account": "account", "db_name": "db_name", "seq": "seq", "type": "created"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_db_updates()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_db_updates_required_params_with_retries(self):
# Enable retries and run test_get_db_updates_required_params.
_service.enable_retries()
self.test_get_db_updates_required_params()
# Disable retries and run test_get_db_updates_required_params.
_service.disable_retries()
self.test_get_db_updates_required_params()
class TestPostChanges():
"""
Test Class for post_changes
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_changes_all_params(self):
"""
post_changes()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
last_event_id = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
feed = 'normal'
filter = 'testString'
heartbeat = 0
include_docs = False
limit = 0
seq_interval = 1
since = '0'
style = 'main_only'
timeout = 0
view = 'testString'
# Invoke method
response = _service.post_changes(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
last_event_id=last_event_id,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
feed=feed,
filter=filter,
heartbeat=heartbeat,
include_docs=include_docs,
limit=limit,
seq_interval=seq_interval,
since=since,
style=style,
timeout=timeout,
view=view,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'descending={}'.format('true' if descending else 'false') in query_string
assert 'feed={}'.format(feed) in query_string
assert 'filter={}'.format(filter) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'limit={}'.format(limit) in query_string
assert 'seq_interval={}'.format(seq_interval) in query_string
assert 'since={}'.format(since) in query_string
assert 'style={}'.format(style) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'view={}'.format(view) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['testString']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
def test_post_changes_all_params_with_retries(self):
# Enable retries and run test_post_changes_all_params.
_service.enable_retries()
self.test_post_changes_all_params()
# Disable retries and run test_post_changes_all_params.
_service.disable_retries()
self.test_post_changes_all_params()
@responses.activate
def test_post_changes_required_params(self):
"""
test_post_changes_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
# Invoke method
response = _service.post_changes(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['testString']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
def test_post_changes_required_params_with_retries(self):
# Enable retries and run test_post_changes_required_params.
_service.enable_retries()
self.test_post_changes_required_params()
# Disable retries and run test_post_changes_required_params.
_service.disable_retries()
self.test_post_changes_required_params()
@responses.activate
def test_post_changes_value_error(self):
"""
test_post_changes_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_changes(**req_copy)
def test_post_changes_value_error_with_retries(self):
# Enable retries and run test_post_changes_value_error.
_service.enable_retries()
self.test_post_changes_value_error()
# Disable retries and run test_post_changes_value_error.
_service.disable_retries()
self.test_post_changes_value_error()
class TestPostChangesAsStream():
"""
Test Class for post_changes_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_changes_as_stream_all_params(self):
"""
post_changes_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
last_event_id = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
feed = 'normal'
filter = 'testString'
heartbeat = 0
include_docs = False
limit = 0
seq_interval = 1
since = '0'
style = 'main_only'
timeout = 0
view = 'testString'
# Invoke method
response = _service.post_changes_as_stream(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
last_event_id=last_event_id,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
feed=feed,
filter=filter,
heartbeat=heartbeat,
include_docs=include_docs,
limit=limit,
seq_interval=seq_interval,
since=since,
style=style,
timeout=timeout,
view=view,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'descending={}'.format('true' if descending else 'false') in query_string
assert 'feed={}'.format(feed) in query_string
assert 'filter={}'.format(filter) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'limit={}'.format(limit) in query_string
assert 'seq_interval={}'.format(seq_interval) in query_string
assert 'since={}'.format(since) in query_string
assert 'style={}'.format(style) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'view={}'.format(view) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['0007741142412418284']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_changes_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_changes_as_stream_all_params.
_service.enable_retries()
self.test_post_changes_as_stream_all_params()
# Disable retries and run test_post_changes_as_stream_all_params.
_service.disable_retries()
self.test_post_changes_as_stream_all_params()
@responses.activate
def test_post_changes_as_stream_required_params(self):
"""
test_post_changes_as_stream_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
# Invoke method
response = _service.post_changes_as_stream(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['0007741142412418284']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_changes_as_stream_required_params_with_retries(self):
# Enable retries and run test_post_changes_as_stream_required_params.
_service.enable_retries()
self.test_post_changes_as_stream_required_params()
# Disable retries and run test_post_changes_as_stream_required_params.
_service.disable_retries()
self.test_post_changes_as_stream_required_params()
@responses.activate
def test_post_changes_as_stream_value_error(self):
"""
test_post_changes_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_changes_as_stream(**req_copy)
def test_post_changes_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_changes_as_stream_value_error.
_service.enable_retries()
self.test_post_changes_as_stream_value_error()
# Disable retries and run test_post_changes_as_stream_value_error.
_service.disable_retries()
self.test_post_changes_as_stream_value_error()
# endregion
##############################################################################
# End of Service: Changes
##############################################################################
##############################################################################
# Start of Service: Databases
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadDatabase():
"""
Test Class for head_database
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_database_all_params(self):
"""
head_database()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.head_database(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_database_all_params_with_retries(self):
# Enable retries and run test_head_database_all_params.
_service.enable_retries()
self.test_head_database_all_params()
# Disable retries and run test_head_database_all_params.
_service.disable_retries()
self.test_head_database_all_params()
@responses.activate
def test_head_database_value_error(self):
"""
test_head_database_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_database(**req_copy)
def test_head_database_value_error_with_retries(self):
# Enable retries and run test_head_database_value_error.
_service.enable_retries()
self.test_head_database_value_error()
# Disable retries and run test_head_database_value_error.
_service.disable_retries()
self.test_head_database_value_error()
class TestGetAllDbs():
"""
Test Class for get_all_dbs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_all_dbs_all_params(self):
"""
get_all_dbs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_all_dbs')
mock_response = '["operation_response"]'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
descending = False
endkey = 'testString'
limit = 0
skip = 0
startkey = 'testString'
# Invoke method
response = _service.get_all_dbs(
descending=descending,
endkey=endkey,
limit=limit,
skip=skip,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'descending={}'.format('true' if descending else 'false') in query_string
assert 'endkey={}'.format(endkey) in query_string
assert 'limit={}'.format(limit) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'startkey={}'.format(startkey) in query_string
def test_get_all_dbs_all_params_with_retries(self):
# Enable retries and run test_get_all_dbs_all_params.
_service.enable_retries()
self.test_get_all_dbs_all_params()
# Disable retries and run test_get_all_dbs_all_params.
_service.disable_retries()
self.test_get_all_dbs_all_params()
@responses.activate
def test_get_all_dbs_required_params(self):
"""
test_get_all_dbs_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_all_dbs')
mock_response = '["operation_response"]'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_all_dbs()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_all_dbs_required_params_with_retries(self):
# Enable retries and run test_get_all_dbs_required_params.
_service.enable_retries()
self.test_get_all_dbs_required_params()
# Disable retries and run test_get_all_dbs_required_params.
_service.disable_retries()
self.test_get_all_dbs_required_params()
class TestPostDbsInfo():
"""
Test Class for post_dbs_info
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_dbs_info_all_params(self):
"""
post_dbs_info()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_dbs_info')
mock_response = '[{"error": "error", "info": {"cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}, "key": "key"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
keys = ['testString']
# Invoke method
response = _service.post_dbs_info(
keys,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['keys'] == ['testString']
def test_post_dbs_info_all_params_with_retries(self):
# Enable retries and run test_post_dbs_info_all_params.
_service.enable_retries()
self.test_post_dbs_info_all_params()
# Disable retries and run test_post_dbs_info_all_params.
_service.disable_retries()
self.test_post_dbs_info_all_params()
@responses.activate
def test_post_dbs_info_value_error(self):
"""
test_post_dbs_info_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_dbs_info')
mock_response = '[{"error": "error", "info": {"cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}, "key": "key"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
keys = ['testString']
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"keys": keys,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_dbs_info(**req_copy)
def test_post_dbs_info_value_error_with_retries(self):
# Enable retries and run test_post_dbs_info_value_error.
_service.enable_retries()
self.test_post_dbs_info_value_error()
# Disable retries and run test_post_dbs_info_value_error.
_service.disable_retries()
self.test_post_dbs_info_value_error()
class TestDeleteDatabase():
"""
Test Class for delete_database
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_database_all_params(self):
"""
delete_database()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.delete_database(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_database_all_params_with_retries(self):
# Enable retries and run test_delete_database_all_params.
_service.enable_retries()
self.test_delete_database_all_params()
# Disable retries and run test_delete_database_all_params.
_service.disable_retries()
self.test_delete_database_all_params()
@responses.activate
def test_delete_database_value_error(self):
"""
test_delete_database_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_database(**req_copy)
def test_delete_database_value_error_with_retries(self):
# Enable retries and run test_delete_database_value_error.
_service.enable_retries()
self.test_delete_database_value_error()
# Disable retries and run test_delete_database_value_error.
_service.disable_retries()
self.test_delete_database_value_error()
class TestGetDatabaseInformation():
"""
Test Class for get_database_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_database_information_all_params(self):
"""
get_database_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_database_information(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_database_information_all_params_with_retries(self):
# Enable retries and run test_get_database_information_all_params.
_service.enable_retries()
self.test_get_database_information_all_params()
# Disable retries and run test_get_database_information_all_params.
_service.disable_retries()
self.test_get_database_information_all_params()
@responses.activate
def test_get_database_information_value_error(self):
"""
test_get_database_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_database_information(**req_copy)
def test_get_database_information_value_error_with_retries(self):
# Enable retries and run test_get_database_information_value_error.
_service.enable_retries()
self.test_get_database_information_value_error()
# Disable retries and run test_get_database_information_value_error.
_service.disable_retries()
self.test_get_database_information_value_error()
class TestPutDatabase():
"""
Test Class for put_database
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_database_all_params(self):
"""
put_database()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
partitioned = False
q = 1
# Invoke method
response = _service.put_database(
db,
partitioned=partitioned,
q=q,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'partitioned={}'.format('true' if partitioned else 'false') in query_string
assert 'q={}'.format(q) in query_string
def test_put_database_all_params_with_retries(self):
# Enable retries and run test_put_database_all_params.
_service.enable_retries()
self.test_put_database_all_params()
# Disable retries and run test_put_database_all_params.
_service.disable_retries()
self.test_put_database_all_params()
@responses.activate
def test_put_database_required_params(self):
"""
test_put_database_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.put_database(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
def test_put_database_required_params_with_retries(self):
# Enable retries and run test_put_database_required_params.
_service.enable_retries()
self.test_put_database_required_params()
# Disable retries and run test_put_database_required_params.
_service.disable_retries()
self.test_put_database_required_params()
@responses.activate
def test_put_database_value_error(self):
"""
test_put_database_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_database(**req_copy)
def test_put_database_value_error_with_retries(self):
# Enable retries and run test_put_database_value_error.
_service.enable_retries()
self.test_put_database_value_error()
# Disable retries and run test_put_database_value_error.
_service.disable_retries()
self.test_put_database_value_error()
# endregion
##############################################################################
# End of Service: Databases
##############################################################################
##############################################################################
# Start of Service: Documents
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadDocument():
"""
Test Class for head_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_document_all_params(self):
"""
head_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
latest = False
rev = 'testString'
# Invoke method
response = _service.head_document(
db,
doc_id,
if_none_match=if_none_match,
latest=latest,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
def test_head_document_all_params_with_retries(self):
# Enable retries and run test_head_document_all_params.
_service.enable_retries()
self.test_head_document_all_params()
# Disable retries and run test_head_document_all_params.
_service.disable_retries()
self.test_head_document_all_params()
@responses.activate
def test_head_document_required_params(self):
"""
test_head_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.head_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_document_required_params_with_retries(self):
# Enable retries and run test_head_document_required_params.
_service.enable_retries()
self.test_head_document_required_params()
# Disable retries and run test_head_document_required_params.
_service.disable_retries()
self.test_head_document_required_params()
@responses.activate
def test_head_document_value_error(self):
"""
test_head_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_document(**req_copy)
def test_head_document_value_error_with_retries(self):
# Enable retries and run test_head_document_value_error.
_service.enable_retries()
self.test_head_document_value_error()
# Disable retries and run test_head_document_value_error.
_service.disable_retries()
self.test_head_document_value_error()
class TestPostDocument():
"""
Test Class for post_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_document_all_params(self):
"""
post_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
document = document_model
content_type = 'application/json'
batch = 'ok'
# Invoke method
response = _service.post_document(
db,
document,
content_type=content_type,
batch=batch,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_post_document_all_params_with_retries(self):
# Enable retries and run test_post_document_all_params.
_service.enable_retries()
self.test_post_document_all_params()
# Disable retries and run test_post_document_all_params.
_service.disable_retries()
self.test_post_document_all_params()
@responses.activate
def test_post_document_required_params(self):
"""
test_post_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
document = document_model
# Invoke method
response = _service.post_document(
db,
document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_post_document_required_params_with_retries(self):
# Enable retries and run test_post_document_required_params.
_service.enable_retries()
self.test_post_document_required_params()
# Disable retries and run test_post_document_required_params.
_service.disable_retries()
self.test_post_document_required_params()
@responses.activate
def test_post_document_value_error(self):
"""
test_post_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
document = document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"document": document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_document(**req_copy)
def test_post_document_value_error_with_retries(self):
# Enable retries and run test_post_document_value_error.
_service.enable_retries()
self.test_post_document_value_error()
# Disable retries and run test_post_document_value_error.
_service.disable_retries()
self.test_post_document_value_error()
class TestPostAllDocs():
"""
Test Class for post_all_docs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_all_params(self):
"""
post_all_docs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = 'testString'
# Invoke method
response = _service.post_all_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == 'testString'
def test_post_all_docs_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_all_params.
_service.enable_retries()
self.test_post_all_docs_all_params()
# Disable retries and run test_post_all_docs_all_params.
_service.disable_retries()
self.test_post_all_docs_all_params()
@responses.activate
def test_post_all_docs_value_error(self):
"""
test_post_all_docs_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs(**req_copy)
def test_post_all_docs_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_value_error.
_service.enable_retries()
self.test_post_all_docs_value_error()
# Disable retries and run test_post_all_docs_value_error.
_service.disable_retries()
self.test_post_all_docs_value_error()
class TestPostAllDocsAsStream():
"""
Test Class for post_all_docs_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_as_stream_all_params(self):
"""
post_all_docs_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Invoke method
response = _service.post_all_docs_as_stream(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_all_docs_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_as_stream_all_params.
_service.enable_retries()
self.test_post_all_docs_as_stream_all_params()
# Disable retries and run test_post_all_docs_as_stream_all_params.
_service.disable_retries()
self.test_post_all_docs_as_stream_all_params()
@responses.activate
def test_post_all_docs_as_stream_value_error(self):
"""
test_post_all_docs_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_as_stream(**req_copy)
def test_post_all_docs_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_as_stream_value_error.
_service.enable_retries()
self.test_post_all_docs_as_stream_value_error()
# Disable retries and run test_post_all_docs_as_stream_value_error.
_service.disable_retries()
self.test_post_all_docs_as_stream_value_error()
class TestPostAllDocsQueries():
"""
Test Class for post_all_docs_queries
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_queries_all_params(self):
"""
post_all_docs_queries()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['testString']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Invoke method
response = _service.post_all_docs_queries(
db,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_all_docs_queries_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_queries_all_params.
_service.enable_retries()
self.test_post_all_docs_queries_all_params()
# Disable retries and run test_post_all_docs_queries_all_params.
_service.disable_retries()
self.test_post_all_docs_queries_all_params()
@responses.activate
def test_post_all_docs_queries_value_error(self):
"""
test_post_all_docs_queries_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['testString']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_queries(**req_copy)
def test_post_all_docs_queries_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_queries_value_error.
_service.enable_retries()
self.test_post_all_docs_queries_value_error()
# Disable retries and run test_post_all_docs_queries_value_error.
_service.disable_retries()
self.test_post_all_docs_queries_value_error()
class TestPostAllDocsQueriesAsStream():
"""
Test Class for post_all_docs_queries_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_queries_as_stream_all_params(self):
"""
post_all_docs_queries_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Invoke method
response = _service.post_all_docs_queries_as_stream(
db,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_all_docs_queries_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_queries_as_stream_all_params.
_service.enable_retries()
self.test_post_all_docs_queries_as_stream_all_params()
# Disable retries and run test_post_all_docs_queries_as_stream_all_params.
_service.disable_retries()
self.test_post_all_docs_queries_as_stream_all_params()
@responses.activate
def test_post_all_docs_queries_as_stream_value_error(self):
"""
test_post_all_docs_queries_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_queries_as_stream(**req_copy)
def test_post_all_docs_queries_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_queries_as_stream_value_error.
_service.enable_retries()
self.test_post_all_docs_queries_as_stream_value_error()
# Disable retries and run test_post_all_docs_queries_as_stream_value_error.
_service.disable_retries()
self.test_post_all_docs_queries_as_stream_value_error()
class TestPostBulkDocs():
"""
Test Class for post_bulk_docs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_docs_all_params(self):
"""
post_bulk_docs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_docs')
mock_response = '[{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a dict representation of a BulkDocs model
bulk_docs_model = {}
bulk_docs_model['docs'] = [document_model]
bulk_docs_model['new_edits'] = True
# Set up parameter values
db = 'testString'
bulk_docs = bulk_docs_model
# Invoke method
response = _service.post_bulk_docs(
db,
bulk_docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == bulk_docs
def test_post_bulk_docs_all_params_with_retries(self):
# Enable retries and run test_post_bulk_docs_all_params.
_service.enable_retries()
self.test_post_bulk_docs_all_params()
# Disable retries and run test_post_bulk_docs_all_params.
_service.disable_retries()
self.test_post_bulk_docs_all_params()
@responses.activate
def test_post_bulk_docs_value_error(self):
"""
test_post_bulk_docs_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_docs')
mock_response = '[{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a dict representation of a BulkDocs model
bulk_docs_model = {}
bulk_docs_model['docs'] = [document_model]
bulk_docs_model['new_edits'] = True
# Set up parameter values
db = 'testString'
bulk_docs = bulk_docs_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"bulk_docs": bulk_docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_docs(**req_copy)
def test_post_bulk_docs_value_error_with_retries(self):
# Enable retries and run test_post_bulk_docs_value_error.
_service.enable_retries()
self.test_post_bulk_docs_value_error()
# Disable retries and run test_post_bulk_docs_value_error.
_service.disable_retries()
self.test_post_bulk_docs_value_error()
class TestPostBulkGet():
"""
Test Class for post_bulk_get
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_all_params(self):
"""
post_bulk_get()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_all_params.
_service.enable_retries()
self.test_post_bulk_get_all_params()
# Disable retries and run test_post_bulk_get_all_params.
_service.disable_retries()
self.test_post_bulk_get_all_params()
@responses.activate
def test_post_bulk_get_required_params(self):
"""
test_post_bulk_get_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_required_params.
_service.enable_retries()
self.test_post_bulk_get_required_params()
# Disable retries and run test_post_bulk_get_required_params.
_service.disable_retries()
self.test_post_bulk_get_required_params()
@responses.activate
def test_post_bulk_get_value_error(self):
"""
test_post_bulk_get_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get(**req_copy)
def test_post_bulk_get_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_value_error.
_service.enable_retries()
self.test_post_bulk_get_value_error()
# Disable retries and run test_post_bulk_get_value_error.
_service.disable_retries()
self.test_post_bulk_get_value_error()
class TestPostBulkGetAsMixed():
"""
Test Class for post_bulk_get_as_mixed
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_mixed_all_params(self):
"""
post_bulk_get_as_mixed()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get_as_mixed(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_mixed_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_all_params.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_all_params()
# Disable retries and run test_post_bulk_get_as_mixed_all_params.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_all_params()
@responses.activate
def test_post_bulk_get_as_mixed_required_params(self):
"""
test_post_bulk_get_as_mixed_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get_as_mixed(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_mixed_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_required_params.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_required_params()
# Disable retries and run test_post_bulk_get_as_mixed_required_params.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_required_params()
@responses.activate
def test_post_bulk_get_as_mixed_value_error(self):
"""
test_post_bulk_get_as_mixed_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_mixed(**req_copy)
def test_post_bulk_get_as_mixed_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_value_error.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_value_error()
# Disable retries and run test_post_bulk_get_as_mixed_value_error.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_value_error()
class TestPostBulkGetAsRelated():
"""
Test Class for post_bulk_get_as_related
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_related_all_params(self):
"""
post_bulk_get_as_related()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get_as_related(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_related_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_related_all_params.
_service.enable_retries()
self.test_post_bulk_get_as_related_all_params()
# Disable retries and run test_post_bulk_get_as_related_all_params.
_service.disable_retries()
self.test_post_bulk_get_as_related_all_params()
@responses.activate
def test_post_bulk_get_as_related_required_params(self):
"""
test_post_bulk_get_as_related_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get_as_related(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_related_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_related_required_params.
_service.enable_retries()
self.test_post_bulk_get_as_related_required_params()
# Disable retries and run test_post_bulk_get_as_related_required_params.
_service.disable_retries()
self.test_post_bulk_get_as_related_required_params()
@responses.activate
def test_post_bulk_get_as_related_value_error(self):
"""
test_post_bulk_get_as_related_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_related(**req_copy)
def test_post_bulk_get_as_related_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_as_related_value_error.
_service.enable_retries()
self.test_post_bulk_get_as_related_value_error()
# Disable retries and run test_post_bulk_get_as_related_value_error.
_service.disable_retries()
self.test_post_bulk_get_as_related_value_error()
class TestPostBulkGetAsStream():
"""
Test Class for post_bulk_get_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_stream_all_params(self):
"""
post_bulk_get_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get_as_stream(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_bulk_get_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_all_params.
_service.enable_retries()
self.test_post_bulk_get_as_stream_all_params()
# Disable retries and run test_post_bulk_get_as_stream_all_params.
_service.disable_retries()
self.test_post_bulk_get_as_stream_all_params()
@responses.activate
def test_post_bulk_get_as_stream_required_params(self):
"""
test_post_bulk_get_as_stream_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get_as_stream(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_bulk_get_as_stream_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_required_params.
_service.enable_retries()
self.test_post_bulk_get_as_stream_required_params()
# Disable retries and run test_post_bulk_get_as_stream_required_params.
_service.disable_retries()
self.test_post_bulk_get_as_stream_required_params()
@responses.activate
def test_post_bulk_get_as_stream_value_error(self):
"""
test_post_bulk_get_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_stream(**req_copy)
def test_post_bulk_get_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_value_error.
_service.enable_retries()
self.test_post_bulk_get_as_stream_value_error()
# Disable retries and run test_post_bulk_get_as_stream_value_error.
_service.disable_retries()
self.test_post_bulk_get_as_stream_value_error()
class TestDeleteDocument():
"""
Test Class for delete_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_document_all_params(self):
"""
delete_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
# Invoke method
response = _service.delete_document(
db,
doc_id,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_document_all_params_with_retries(self):
# Enable retries and run test_delete_document_all_params.
_service.enable_retries()
self.test_delete_document_all_params()
# Disable retries and run test_delete_document_all_params.
_service.disable_retries()
self.test_delete_document_all_params()
@responses.activate
def test_delete_document_required_params(self):
"""
test_delete_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.delete_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_document_required_params_with_retries(self):
# Enable retries and run test_delete_document_required_params.
_service.enable_retries()
self.test_delete_document_required_params()
# Disable retries and run test_delete_document_required_params.
_service.disable_retries()
self.test_delete_document_required_params()
@responses.activate
def test_delete_document_value_error(self):
"""
test_delete_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_document(**req_copy)
def test_delete_document_value_error_with_retries(self):
# Enable retries and run test_delete_document_value_error.
_service.enable_retries()
self.test_delete_document_value_error()
# Disable retries and run test_delete_document_value_error.
_service.disable_retries()
self.test_delete_document_value_error()
class TestGetDocument():
"""
Test Class for get_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_all_params(self):
"""
get_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_all_params_with_retries(self):
# Enable retries and run test_get_document_all_params.
_service.enable_retries()
self.test_get_document_all_params()
# Disable retries and run test_get_document_all_params.
_service.disable_retries()
self.test_get_document_all_params()
@responses.activate
def test_get_document_required_params(self):
"""
test_get_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_required_params_with_retries(self):
# Enable retries and run test_get_document_required_params.
_service.enable_retries()
self.test_get_document_required_params()
# Disable retries and run test_get_document_required_params.
_service.disable_retries()
self.test_get_document_required_params()
@responses.activate
def test_get_document_value_error(self):
"""
test_get_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document(**req_copy)
def test_get_document_value_error_with_retries(self):
# Enable retries and run test_get_document_value_error.
_service.enable_retries()
self.test_get_document_value_error()
# Disable retries and run test_get_document_value_error.
_service.disable_retries()
self.test_get_document_value_error()
class TestGetDocumentAsMixed():
"""
Test Class for get_document_as_mixed
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_mixed_all_params(self):
"""
get_document_as_mixed()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document_as_mixed(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_as_mixed_all_params_with_retries(self):
# Enable retries and run test_get_document_as_mixed_all_params.
_service.enable_retries()
self.test_get_document_as_mixed_all_params()
# Disable retries and run test_get_document_as_mixed_all_params.
_service.disable_retries()
self.test_get_document_as_mixed_all_params()
@responses.activate
def test_get_document_as_mixed_required_params(self):
"""
test_get_document_as_mixed_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document_as_mixed(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_as_mixed_required_params_with_retries(self):
# Enable retries and run test_get_document_as_mixed_required_params.
_service.enable_retries()
self.test_get_document_as_mixed_required_params()
# Disable retries and run test_get_document_as_mixed_required_params.
_service.disable_retries()
self.test_get_document_as_mixed_required_params()
@responses.activate
def test_get_document_as_mixed_value_error(self):
"""
test_get_document_as_mixed_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_mixed(**req_copy)
def test_get_document_as_mixed_value_error_with_retries(self):
# Enable retries and run test_get_document_as_mixed_value_error.
_service.enable_retries()
self.test_get_document_as_mixed_value_error()
# Disable retries and run test_get_document_as_mixed_value_error.
_service.disable_retries()
self.test_get_document_as_mixed_value_error()
class TestGetDocumentAsRelated():
"""
Test Class for get_document_as_related
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_related_all_params(self):
"""
get_document_as_related()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document_as_related(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_as_related_all_params_with_retries(self):
# Enable retries and run test_get_document_as_related_all_params.
_service.enable_retries()
self.test_get_document_as_related_all_params()
# Disable retries and run test_get_document_as_related_all_params.
_service.disable_retries()
self.test_get_document_as_related_all_params()
@responses.activate
def test_get_document_as_related_required_params(self):
"""
test_get_document_as_related_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document_as_related(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_as_related_required_params_with_retries(self):
# Enable retries and run test_get_document_as_related_required_params.
_service.enable_retries()
self.test_get_document_as_related_required_params()
# Disable retries and run test_get_document_as_related_required_params.
_service.disable_retries()
self.test_get_document_as_related_required_params()
@responses.activate
def test_get_document_as_related_value_error(self):
"""
test_get_document_as_related_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_related(**req_copy)
def test_get_document_as_related_value_error_with_retries(self):
# Enable retries and run test_get_document_as_related_value_error.
_service.enable_retries()
self.test_get_document_as_related_value_error()
# Disable retries and run test_get_document_as_related_value_error.
_service.disable_retries()
self.test_get_document_as_related_value_error()
class TestGetDocumentAsStream():
"""
Test Class for get_document_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_stream_all_params(self):
"""
get_document_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document_as_stream(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_document_as_stream_all_params_with_retries(self):
# Enable retries and run test_get_document_as_stream_all_params.
_service.enable_retries()
self.test_get_document_as_stream_all_params()
# Disable retries and run test_get_document_as_stream_all_params.
_service.disable_retries()
self.test_get_document_as_stream_all_params()
@responses.activate
def test_get_document_as_stream_required_params(self):
"""
test_get_document_as_stream_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document_as_stream(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_document_as_stream_required_params_with_retries(self):
# Enable retries and run test_get_document_as_stream_required_params.
_service.enable_retries()
self.test_get_document_as_stream_required_params()
# Disable retries and run test_get_document_as_stream_required_params.
_service.disable_retries()
self.test_get_document_as_stream_required_params()
@responses.activate
def test_get_document_as_stream_value_error(self):
"""
test_get_document_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_stream(**req_copy)
def test_get_document_as_stream_value_error_with_retries(self):
# Enable retries and run test_get_document_as_stream_value_error.
_service.enable_retries()
self.test_get_document_as_stream_value_error()
# Disable retries and run test_get_document_as_stream_value_error.
_service.disable_retries()
self.test_get_document_as_stream_value_error()
class TestPutDocument():
"""
Test Class for put_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_document_all_params(self):
"""
put_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
content_type = 'application/json'
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_document(
db,
doc_id,
document,
content_type=content_type,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_document_all_params_with_retries(self):
# Enable retries and run test_put_document_all_params.
_service.enable_retries()
self.test_put_document_all_params()
# Disable retries and run test_put_document_all_params.
_service.disable_retries()
self.test_put_document_all_params()
@responses.activate
def test_put_document_required_params(self):
"""
test_put_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Invoke method
response = _service.put_document(
db,
doc_id,
document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_document_required_params_with_retries(self):
# Enable retries and run test_put_document_required_params.
_service.enable_retries()
self.test_put_document_required_params()
# Disable retries and run test_put_document_required_params.
_service.disable_retries()
self.test_put_document_required_params()
@responses.activate
def test_put_document_value_error(self):
"""
test_put_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"document": document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_document(**req_copy)
def test_put_document_value_error_with_retries(self):
# Enable retries and run test_put_document_value_error.
_service.enable_retries()
self.test_put_document_value_error()
# Disable retries and run test_put_document_value_error.
_service.disable_retries()
self.test_put_document_value_error()
# endregion
##############################################################################
# End of Service: Documents
##############################################################################
##############################################################################
# Start of Service: DesignDocuments
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadDesignDocument():
"""
Test Class for head_design_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_design_document_all_params(self):
"""
head_design_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
if_none_match = 'testString'
# Invoke method
response = _service.head_design_document(
db,
ddoc,
if_none_match=if_none_match,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_design_document_all_params_with_retries(self):
# Enable retries and run test_head_design_document_all_params.
_service.enable_retries()
self.test_head_design_document_all_params()
# Disable retries and run test_head_design_document_all_params.
_service.disable_retries()
self.test_head_design_document_all_params()
@responses.activate
def test_head_design_document_required_params(self):
"""
test_head_design_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Invoke method
response = _service.head_design_document(
db,
ddoc,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_design_document_required_params_with_retries(self):
# Enable retries and run test_head_design_document_required_params.
_service.enable_retries()
self.test_head_design_document_required_params()
# Disable retries and run test_head_design_document_required_params.
_service.disable_retries()
self.test_head_design_document_required_params()
@responses.activate
def test_head_design_document_value_error(self):
"""
test_head_design_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_design_document(**req_copy)
def test_head_design_document_value_error_with_retries(self):
# Enable retries and run test_head_design_document_value_error.
_service.enable_retries()
self.test_head_design_document_value_error()
# Disable retries and run test_head_design_document_value_error.
_service.disable_retries()
self.test_head_design_document_value_error()
class TestDeleteDesignDocument():
"""
Test Class for delete_design_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_design_document_all_params(self):
"""
delete_design_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
# Invoke method
response = _service.delete_design_document(
db,
ddoc,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_design_document_all_params_with_retries(self):
# Enable retries and run test_delete_design_document_all_params.
_service.enable_retries()
self.test_delete_design_document_all_params()
# Disable retries and run test_delete_design_document_all_params.
_service.disable_retries()
self.test_delete_design_document_all_params()
@responses.activate
def test_delete_design_document_required_params(self):
"""
test_delete_design_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Invoke method
response = _service.delete_design_document(
db,
ddoc,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_design_document_required_params_with_retries(self):
# Enable retries and run test_delete_design_document_required_params.
_service.enable_retries()
self.test_delete_design_document_required_params()
# Disable retries and run test_delete_design_document_required_params.
_service.disable_retries()
self.test_delete_design_document_required_params()
@responses.activate
def test_delete_design_document_value_error(self):
"""
test_delete_design_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_design_document(**req_copy)
def test_delete_design_document_value_error_with_retries(self):
# Enable retries and run test_delete_design_document_value_error.
_service.enable_retries()
self.test_delete_design_document_value_error()
# Disable retries and run test_delete_design_document_value_error.
_service.disable_retries()
self.test_delete_design_document_value_error()
class TestGetDesignDocument():
"""
Test Class for get_design_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_design_document_all_params(self):
"""
get_design_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_design_document(
db,
ddoc,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_design_document_all_params_with_retries(self):
# Enable retries and run test_get_design_document_all_params.
_service.enable_retries()
self.test_get_design_document_all_params()
# Disable retries and run test_get_design_document_all_params.
_service.disable_retries()
self.test_get_design_document_all_params()
@responses.activate
def test_get_design_document_required_params(self):
"""
test_get_design_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Invoke method
response = _service.get_design_document(
db,
ddoc,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_design_document_required_params_with_retries(self):
# Enable retries and run test_get_design_document_required_params.
_service.enable_retries()
self.test_get_design_document_required_params()
# Disable retries and run test_get_design_document_required_params.
_service.disable_retries()
self.test_get_design_document_required_params()
@responses.activate
def test_get_design_document_value_error(self):
"""
test_get_design_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_design_document(**req_copy)
def test_get_design_document_value_error_with_retries(self):
# Enable retries and run test_get_design_document_value_error.
_service.enable_retries()
self.test_get_design_document_value_error()
# Disable retries and run test_get_design_document_value_error.
_service.disable_retries()
self.test_get_design_document_value_error()
class TestPutDesignDocument():
"""
Test Class for put_design_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_design_document_all_params(self):
"""
put_design_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_design_document(
db,
ddoc,
design_document,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == design_document
def test_put_design_document_all_params_with_retries(self):
# Enable retries and run test_put_design_document_all_params.
_service.enable_retries()
self.test_put_design_document_all_params()
# Disable retries and run test_put_design_document_all_params.
_service.disable_retries()
self.test_put_design_document_all_params()
@responses.activate
def test_put_design_document_required_params(self):
"""
test_put_design_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
# Invoke method
response = _service.put_design_document(
db,
ddoc,
design_document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == design_document
def test_put_design_document_required_params_with_retries(self):
# Enable retries and run test_put_design_document_required_params.
_service.enable_retries()
self.test_put_design_document_required_params()
# Disable retries and run test_put_design_document_required_params.
_service.disable_retries()
self.test_put_design_document_required_params()
@responses.activate
def test_put_design_document_value_error(self):
"""
test_put_design_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"design_document": design_document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_design_document(**req_copy)
def test_put_design_document_value_error_with_retries(self):
# Enable retries and run test_put_design_document_value_error.
_service.enable_retries()
self.test_put_design_document_value_error()
# Disable retries and run test_put_design_document_value_error.
_service.disable_retries()
self.test_put_design_document_value_error()
class TestGetDesignDocumentInformation():
"""
Test Class for get_design_document_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_design_document_information_all_params(self):
"""
get_design_document_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_info')
mock_response = '{"name": "name", "view_index": {"compact_running": false, "language": "language", "signature": "signature", "sizes": {"active": 6, "external": 8, "file": 4}, "updater_running": false, "waiting_clients": 0, "waiting_commit": true}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Invoke method
response = _service.get_design_document_information(
db,
ddoc,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_design_document_information_all_params_with_retries(self):
# Enable retries and run test_get_design_document_information_all_params.
_service.enable_retries()
self.test_get_design_document_information_all_params()
# Disable retries and run test_get_design_document_information_all_params.
_service.disable_retries()
self.test_get_design_document_information_all_params()
@responses.activate
def test_get_design_document_information_value_error(self):
"""
test_get_design_document_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_info')
mock_response = '{"name": "name", "view_index": {"compact_running": false, "language": "language", "signature": "signature", "sizes": {"active": 6, "external": 8, "file": 4}, "updater_running": false, "waiting_clients": 0, "waiting_commit": true}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_design_document_information(**req_copy)
def test_get_design_document_information_value_error_with_retries(self):
# Enable retries and run test_get_design_document_information_value_error.
_service.enable_retries()
self.test_get_design_document_information_value_error()
# Disable retries and run test_get_design_document_information_value_error.
_service.disable_retries()
self.test_get_design_document_information_value_error()
class TestPostDesignDocs():
"""
Test Class for post_design_docs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_design_docs_all_params(self):
"""
post_design_docs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
accept = 'application/json'
# Invoke method
response = _service.post_design_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
accept=accept,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
def test_post_design_docs_all_params_with_retries(self):
# Enable retries and run test_post_design_docs_all_params.
_service.enable_retries()
self.test_post_design_docs_all_params()
# Disable retries and run test_post_design_docs_all_params.
_service.disable_retries()
self.test_post_design_docs_all_params()
@responses.activate
def test_post_design_docs_required_params(self):
"""
test_post_design_docs_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Invoke method
response = _service.post_design_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
def test_post_design_docs_required_params_with_retries(self):
# Enable retries and run test_post_design_docs_required_params.
_service.enable_retries()
self.test_post_design_docs_required_params()
# Disable retries and run test_post_design_docs_required_params.
_service.disable_retries()
self.test_post_design_docs_required_params()
@responses.activate
def test_post_design_docs_value_error(self):
"""
test_post_design_docs_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_design_docs(**req_copy)
def test_post_design_docs_value_error_with_retries(self):
# Enable retries and run test_post_design_docs_value_error.
_service.enable_retries()
self.test_post_design_docs_value_error()
# Disable retries and run test_post_design_docs_value_error.
_service.disable_retries()
self.test_post_design_docs_value_error()
class TestPostDesignDocsQueries():
"""
Test Class for post_design_docs_queries
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_design_docs_queries_all_params(self):
"""
post_design_docs_queries()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
accept = 'application/json'
# Invoke method
response = _service.post_design_docs_queries(
db,
queries,
accept=accept,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_design_docs_queries_all_params_with_retries(self):
# Enable retries and run test_post_design_docs_queries_all_params.
_service.enable_retries()
self.test_post_design_docs_queries_all_params()
# Disable retries and run test_post_design_docs_queries_all_params.
_service.disable_retries()
self.test_post_design_docs_queries_all_params()
@responses.activate
def test_post_design_docs_queries_required_params(self):
"""
test_post_design_docs_queries_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Invoke method
response = _service.post_design_docs_queries(
db,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_design_docs_queries_required_params_with_retries(self):
# Enable retries and run test_post_design_docs_queries_required_params.
_service.enable_retries()
self.test_post_design_docs_queries_required_params()
# Disable retries and run test_post_design_docs_queries_required_params.
_service.disable_retries()
self.test_post_design_docs_queries_required_params()
@responses.activate
def test_post_design_docs_queries_value_error(self):
"""
test_post_design_docs_queries_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_design_docs_queries(**req_copy)
def test_post_design_docs_queries_value_error_with_retries(self):
# Enable retries and run test_post_design_docs_queries_value_error.
_service.enable_retries()
self.test_post_design_docs_queries_value_error()
# Disable retries and run test_post_design_docs_queries_value_error.
_service.disable_retries()
self.test_post_design_docs_queries_value_error()
# endregion
##############################################################################
# End of Service: DesignDocuments
##############################################################################
##############################################################################
# Start of Service: Views
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostView():
"""
Test Class for post_view
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_all_params(self):
"""
post_view()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['testString']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Invoke method
response = _service.post_view(
db,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
def test_post_view_all_params_with_retries(self):
# Enable retries and run test_post_view_all_params.
_service.enable_retries()
self.test_post_view_all_params()
# Disable retries and run test_post_view_all_params.
_service.disable_retries()
self.test_post_view_all_params()
@responses.activate
def test_post_view_value_error(self):
"""
test_post_view_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['testString']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view(**req_copy)
def test_post_view_value_error_with_retries(self):
# Enable retries and run test_post_view_value_error.
_service.enable_retries()
self.test_post_view_value_error()
# Disable retries and run test_post_view_value_error.
_service.disable_retries()
self.test_post_view_value_error()
class TestPostViewAsStream():
"""
Test Class for post_view_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_as_stream_all_params(self):
"""
post_view_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Invoke method
response = _service.post_view_as_stream(
db,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == True
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['examplekey']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_view_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_view_as_stream_all_params.
_service.enable_retries()
self.test_post_view_as_stream_all_params()
# Disable retries and run test_post_view_as_stream_all_params.
_service.disable_retries()
self.test_post_view_as_stream_all_params()
@responses.activate
def test_post_view_as_stream_value_error(self):
"""
test_post_view_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_as_stream(**req_copy)
def test_post_view_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_view_as_stream_value_error.
_service.enable_retries()
self.test_post_view_as_stream_value_error()
# Disable retries and run test_post_view_as_stream_value_error.
_service.disable_retries()
self.test_post_view_as_stream_value_error()
class TestPostViewQueries():
"""
Test Class for post_view_queries
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_queries_all_params(self):
"""
post_view_queries()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"results": [{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = False
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 0
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Invoke method
response = _service.post_view_queries(
db,
ddoc,
view,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [view_query_model]
def test_post_view_queries_all_params_with_retries(self):
# Enable retries and run test_post_view_queries_all_params.
_service.enable_retries()
self.test_post_view_queries_all_params()
# Disable retries and run test_post_view_queries_all_params.
_service.disable_retries()
self.test_post_view_queries_all_params()
@responses.activate
def test_post_view_queries_value_error(self):
"""
test_post_view_queries_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"results": [{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = False
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 0
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_queries(**req_copy)
def test_post_view_queries_value_error_with_retries(self):
# Enable retries and run test_post_view_queries_value_error.
_service.enable_retries()
self.test_post_view_queries_value_error()
# Disable retries and run test_post_view_queries_value_error.
_service.disable_retries()
self.test_post_view_queries_value_error()
class TestPostViewQueriesAsStream():
"""
Test Class for post_view_queries_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_queries_as_stream_all_params(self):
"""
post_view_queries_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = True
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 5
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Invoke method
response = _service.post_view_queries_as_stream(
db,
ddoc,
view,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [view_query_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_view_queries_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_view_queries_as_stream_all_params.
_service.enable_retries()
self.test_post_view_queries_as_stream_all_params()
# Disable retries and run test_post_view_queries_as_stream_all_params.
_service.disable_retries()
self.test_post_view_queries_as_stream_all_params()
@responses.activate
def test_post_view_queries_as_stream_value_error(self):
"""
test_post_view_queries_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = True
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 5
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_queries_as_stream(**req_copy)
def test_post_view_queries_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_view_queries_as_stream_value_error.
_service.enable_retries()
self.test_post_view_queries_as_stream_value_error()
# Disable retries and run test_post_view_queries_as_stream_value_error.
_service.disable_retries()
self.test_post_view_queries_as_stream_value_error()
# endregion
##############################################################################
# End of Service: Views
##############################################################################
##############################################################################
# Start of Service: PartitionedDatabases
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetPartitionInformation():
"""
Test Class for get_partition_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_partition_information_all_params(self):
"""
get_partition_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString')
mock_response = '{"db_name": "db_name", "doc_count": 0, "doc_del_count": 0, "partition": "partition", "partitioned_indexes": {"count": 0, "indexes": {"search": 0, "view": 0}, "limit": 0}, "sizes": {"active": 0, "external": 0}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
# Invoke method
response = _service.get_partition_information(
db,
partition_key,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_partition_information_all_params_with_retries(self):
# Enable retries and run test_get_partition_information_all_params.
_service.enable_retries()
self.test_get_partition_information_all_params()
# Disable retries and run test_get_partition_information_all_params.
_service.disable_retries()
self.test_get_partition_information_all_params()
@responses.activate
def test_get_partition_information_value_error(self):
"""
test_get_partition_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString')
mock_response = '{"db_name": "db_name", "doc_count": 0, "doc_del_count": 0, "partition": "partition", "partitioned_indexes": {"count": 0, "indexes": {"search": 0, "view": 0}, "limit": 0}, "sizes": {"active": 0, "external": 0}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_partition_information(**req_copy)
def test_get_partition_information_value_error_with_retries(self):
# Enable retries and run test_get_partition_information_value_error.
_service.enable_retries()
self.test_get_partition_information_value_error()
# Disable retries and run test_get_partition_information_value_error.
_service.disable_retries()
self.test_get_partition_information_value_error()
class TestPostPartitionAllDocs():
"""
Test Class for post_partition_all_docs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_all_docs_all_params(self):
"""
post_partition_all_docs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Invoke method
response = _service.post_partition_all_docs(
db,
partition_key,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
def test_post_partition_all_docs_all_params_with_retries(self):
# Enable retries and run test_post_partition_all_docs_all_params.
_service.enable_retries()
self.test_post_partition_all_docs_all_params()
# Disable retries and run test_post_partition_all_docs_all_params.
_service.disable_retries()
self.test_post_partition_all_docs_all_params()
@responses.activate
def test_post_partition_all_docs_value_error(self):
"""
test_post_partition_all_docs_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_all_docs(**req_copy)
def test_post_partition_all_docs_value_error_with_retries(self):
# Enable retries and run test_post_partition_all_docs_value_error.
_service.enable_retries()
self.test_post_partition_all_docs_value_error()
# Disable retries and run test_post_partition_all_docs_value_error.
_service.disable_retries()
self.test_post_partition_all_docs_value_error()
class TestPostPartitionAllDocsAsStream():
"""
Test Class for post_partition_all_docs_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_all_docs_as_stream_all_params(self):
"""
post_partition_all_docs_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Invoke method
response = _service.post_partition_all_docs_as_stream(
db,
partition_key,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_all_docs_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_all_docs_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_all_docs_as_stream_all_params()
# Disable retries and run test_post_partition_all_docs_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_all_docs_as_stream_all_params()
@responses.activate
def test_post_partition_all_docs_as_stream_value_error(self):
"""
test_post_partition_all_docs_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_all_docs_as_stream(**req_copy)
def test_post_partition_all_docs_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_all_docs_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_all_docs_as_stream_value_error()
# Disable retries and run test_post_partition_all_docs_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_all_docs_as_stream_value_error()
class TestPostPartitionSearch():
"""
Test Class for post_partition_search
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_search_all_params(self):
"""
post_partition_search()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
# Invoke method
response = _service.post_partition_search(
db,
partition_key,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
def test_post_partition_search_all_params_with_retries(self):
# Enable retries and run test_post_partition_search_all_params.
_service.enable_retries()
self.test_post_partition_search_all_params()
# Disable retries and run test_post_partition_search_all_params.
_service.disable_retries()
self.test_post_partition_search_all_params()
@responses.activate
def test_post_partition_search_value_error(self):
"""
test_post_partition_search_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_search(**req_copy)
def test_post_partition_search_value_error_with_retries(self):
# Enable retries and run test_post_partition_search_value_error.
_service.enable_retries()
self.test_post_partition_search_value_error()
# Disable retries and run test_post_partition_search_value_error.
_service.disable_retries()
self.test_post_partition_search_value_error()
class TestPostPartitionSearchAsStream():
"""
Test Class for post_partition_search_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_search_as_stream_all_params(self):
"""
post_partition_search_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
# Invoke method
response = _service.post_partition_search_as_stream(
db,
partition_key,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 3
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_search_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_search_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_search_as_stream_all_params()
# Disable retries and run test_post_partition_search_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_search_as_stream_all_params()
@responses.activate
def test_post_partition_search_as_stream_value_error(self):
"""
test_post_partition_search_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_search_as_stream(**req_copy)
def test_post_partition_search_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_search_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_search_as_stream_value_error()
# Disable retries and run test_post_partition_search_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_search_as_stream_value_error()
class TestPostPartitionView():
"""
Test Class for post_partition_view
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_view_all_params(self):
"""
post_partition_view()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Invoke method
response = _service.post_partition_view(
db,
partition_key,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == True
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['examplekey']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
def test_post_partition_view_all_params_with_retries(self):
# Enable retries and run test_post_partition_view_all_params.
_service.enable_retries()
self.test_post_partition_view_all_params()
# Disable retries and run test_post_partition_view_all_params.
_service.disable_retries()
self.test_post_partition_view_all_params()
@responses.activate
def test_post_partition_view_value_error(self):
"""
test_post_partition_view_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_view(**req_copy)
def test_post_partition_view_value_error_with_retries(self):
# Enable retries and run test_post_partition_view_value_error.
_service.enable_retries()
self.test_post_partition_view_value_error()
# Disable retries and run test_post_partition_view_value_error.
_service.disable_retries()
self.test_post_partition_view_value_error()
class TestPostPartitionViewAsStream():
"""
Test Class for post_partition_view_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_view_as_stream_all_params(self):
"""
post_partition_view_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Invoke method
response = _service.post_partition_view_as_stream(
db,
partition_key,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == True
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['examplekey']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_view_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_view_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_view_as_stream_all_params()
# Disable retries and run test_post_partition_view_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_view_as_stream_all_params()
@responses.activate
def test_post_partition_view_as_stream_value_error(self):
"""
test_post_partition_view_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_view_as_stream(**req_copy)
def test_post_partition_view_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_view_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_view_as_stream_value_error()
# Disable retries and run test_post_partition_view_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_view_as_stream_value_error()
class TestPostPartitionFind():
"""
Test Class for post_partition_find
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_find_all_params(self):
"""
post_partition_find()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Invoke method
response = _service.post_partition_find(
db,
partition_key,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
def test_post_partition_find_all_params_with_retries(self):
# Enable retries and run test_post_partition_find_all_params.
_service.enable_retries()
self.test_post_partition_find_all_params()
# Disable retries and run test_post_partition_find_all_params.
_service.disable_retries()
self.test_post_partition_find_all_params()
@responses.activate
def test_post_partition_find_value_error(self):
"""
test_post_partition_find_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_find(**req_copy)
def test_post_partition_find_value_error_with_retries(self):
# Enable retries and run test_post_partition_find_value_error.
_service.enable_retries()
self.test_post_partition_find_value_error()
# Disable retries and run test_post_partition_find_value_error.
_service.disable_retries()
self.test_post_partition_find_value_error()
class TestPostPartitionFindAsStream():
"""
Test Class for post_partition_find_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_find_as_stream_all_params(self):
"""
post_partition_find_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['productid', 'name', 'description']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Invoke method
response = _service.post_partition_find_as_stream(
db,
partition_key,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['productid', 'name', 'description']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_find_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_find_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_find_as_stream_all_params()
# Disable retries and run test_post_partition_find_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_find_as_stream_all_params()
@responses.activate
def test_post_partition_find_as_stream_value_error(self):
"""
test_post_partition_find_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['productid', 'name', 'description']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_find_as_stream(**req_copy)
def test_post_partition_find_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_find_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_find_as_stream_value_error()
# Disable retries and run test_post_partition_find_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_find_as_stream_value_error()
# endregion
##############################################################################
# End of Service: PartitionedDatabases
##############################################################################
##############################################################################
# Start of Service: Queries
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostExplain():
"""
Test Class for post_explain
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_explain_all_params(self):
"""
post_explain()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_explain')
mock_response = '{"dbname": "dbname", "fields": ["fields"], "index": {"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}, "limit": 0, "opts": {"mapKey": "anyValue"}, "range": {"end_key": ["anyValue"], "start_key": ["anyValue"]}, "selector": {"mapKey": "anyValue"}, "skip": 0}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Invoke method
response = _service.post_explain(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
def test_post_explain_all_params_with_retries(self):
# Enable retries and run test_post_explain_all_params.
_service.enable_retries()
self.test_post_explain_all_params()
# Disable retries and run test_post_explain_all_params.
_service.disable_retries()
self.test_post_explain_all_params()
@responses.activate
def test_post_explain_value_error(self):
"""
test_post_explain_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_explain')
mock_response = '{"dbname": "dbname", "fields": ["fields"], "index": {"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}, "limit": 0, "opts": {"mapKey": "anyValue"}, "range": {"end_key": ["anyValue"], "start_key": ["anyValue"]}, "selector": {"mapKey": "anyValue"}, "skip": 0}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_explain(**req_copy)
def test_post_explain_value_error_with_retries(self):
# Enable retries and run test_post_explain_value_error.
_service.enable_retries()
self.test_post_explain_value_error()
# Disable retries and run test_post_explain_value_error.
_service.disable_retries()
self.test_post_explain_value_error()
class TestPostFind():
"""
Test Class for post_find
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_find_all_params(self):
"""
post_find()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Invoke method
response = _service.post_find(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['_id', 'type', 'name', 'email']
assert req_body['limit'] == 3
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
def test_post_find_all_params_with_retries(self):
# Enable retries and run test_post_find_all_params.
_service.enable_retries()
self.test_post_find_all_params()
# Disable retries and run test_post_find_all_params.
_service.disable_retries()
self.test_post_find_all_params()
@responses.activate
def test_post_find_value_error(self):
"""
test_post_find_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_find(**req_copy)
def test_post_find_value_error_with_retries(self):
# Enable retries and run test_post_find_value_error.
_service.enable_retries()
self.test_post_find_value_error()
# Disable retries and run test_post_find_value_error.
_service.disable_retries()
self.test_post_find_value_error()
class TestPostFindAsStream():
"""
Test Class for post_find_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_find_as_stream_all_params(self):
"""
post_find_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Invoke method
response = _service.post_find_as_stream(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['_id', 'type', 'name', 'email']
assert req_body['limit'] == 3
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_find_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_find_as_stream_all_params.
_service.enable_retries()
self.test_post_find_as_stream_all_params()
# Disable retries and run test_post_find_as_stream_all_params.
_service.disable_retries()
self.test_post_find_as_stream_all_params()
@responses.activate
def test_post_find_as_stream_value_error(self):
"""
test_post_find_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_find_as_stream(**req_copy)
def test_post_find_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_find_as_stream_value_error.
_service.enable_retries()
self.test_post_find_as_stream_value_error()
# Disable retries and run test_post_find_as_stream_value_error.
_service.disable_retries()
self.test_post_find_as_stream_value_error()
class TestGetIndexesInformation():
"""
Test Class for get_indexes_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_indexes_information_all_params(self):
"""
get_indexes_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"total_rows": 0, "indexes": [{"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_indexes_information(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_indexes_information_all_params_with_retries(self):
# Enable retries and run test_get_indexes_information_all_params.
_service.enable_retries()
self.test_get_indexes_information_all_params()
# Disable retries and run test_get_indexes_information_all_params.
_service.disable_retries()
self.test_get_indexes_information_all_params()
@responses.activate
def test_get_indexes_information_value_error(self):
"""
test_get_indexes_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"total_rows": 0, "indexes": [{"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_indexes_information(**req_copy)
def test_get_indexes_information_value_error_with_retries(self):
# Enable retries and run test_get_indexes_information_value_error.
_service.enable_retries()
self.test_get_indexes_information_value_error()
# Disable retries and run test_get_indexes_information_value_error.
_service.disable_retries()
self.test_get_indexes_information_value_error()
class TestPostIndex():
"""
Test Class for post_index
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_index_all_params(self):
"""
post_index()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"id": "id", "name": "name", "result": "created"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a IndexTextOperatorDefaultField model
index_text_operator_default_field_model = {}
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
# Construct a dict representation of a IndexField model
index_field_model = {}
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
# Construct a dict representation of a IndexDefinition model
index_definition_model = {}
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
# Set up parameter values
db = 'testString'
index = index_definition_model
ddoc = 'testString'
def_ = index_definition_model
name = 'testString'
partitioned = True
type = 'json'
# Invoke method
response = _service.post_index(
db,
index,
ddoc=ddoc,
def_=def_,
name=name,
partitioned=partitioned,
type=type,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['index'] == index_definition_model
assert req_body['ddoc'] == 'testString'
assert req_body['def'] == index_definition_model
assert req_body['name'] == 'testString'
assert req_body['partitioned'] == True
assert req_body['type'] == 'json'
def test_post_index_all_params_with_retries(self):
# Enable retries and run test_post_index_all_params.
_service.enable_retries()
self.test_post_index_all_params()
# Disable retries and run test_post_index_all_params.
_service.disable_retries()
self.test_post_index_all_params()
@responses.activate
def test_post_index_value_error(self):
"""
test_post_index_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"id": "id", "name": "name", "result": "created"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a IndexTextOperatorDefaultField model
index_text_operator_default_field_model = {}
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
# Construct a dict representation of a IndexField model
index_field_model = {}
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
# Construct a dict representation of a IndexDefinition model
index_definition_model = {}
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
# Set up parameter values
db = 'testString'
index = index_definition_model
ddoc = 'testString'
def_ = index_definition_model
name = 'testString'
partitioned = True
type = 'json'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_index(**req_copy)
def test_post_index_value_error_with_retries(self):
# Enable retries and run test_post_index_value_error.
_service.enable_retries()
self.test_post_index_value_error()
# Disable retries and run test_post_index_value_error.
_service.disable_retries()
self.test_post_index_value_error()
class TestDeleteIndex():
"""
Test Class for delete_index
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_index_all_params(self):
"""
delete_index()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index/_design/testString/json/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
type = 'json'
index = 'testString'
# Invoke method
response = _service.delete_index(
db,
ddoc,
type,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_index_all_params_with_retries(self):
# Enable retries and run test_delete_index_all_params.
_service.enable_retries()
self.test_delete_index_all_params()
# Disable retries and run test_delete_index_all_params.
_service.disable_retries()
self.test_delete_index_all_params()
@responses.activate
def test_delete_index_value_error(self):
"""
test_delete_index_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index/_design/testString/json/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
type = 'json'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"type": type,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_index(**req_copy)
def test_delete_index_value_error_with_retries(self):
# Enable retries and run test_delete_index_value_error.
_service.enable_retries()
self.test_delete_index_value_error()
# Disable retries and run test_delete_index_value_error.
_service.disable_retries()
self.test_delete_index_value_error()
# endregion
##############################################################################
# End of Service: Queries
##############################################################################
##############################################################################
# Start of Service: Searches
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostSearchAnalyze():
"""
Test Class for post_search_analyze
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_analyze_all_params(self):
"""
post_search_analyze()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_search_analyze')
mock_response = '{"tokens": ["tokens"]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
analyzer = 'arabic'
text = 'testString'
# Invoke method
response = _service.post_search_analyze(
analyzer,
text,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['analyzer'] == 'arabic'
assert req_body['text'] == 'testString'
def test_post_search_analyze_all_params_with_retries(self):
# Enable retries and run test_post_search_analyze_all_params.
_service.enable_retries()
self.test_post_search_analyze_all_params()
# Disable retries and run test_post_search_analyze_all_params.
_service.disable_retries()
self.test_post_search_analyze_all_params()
@responses.activate
def test_post_search_analyze_value_error(self):
"""
test_post_search_analyze_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_search_analyze')
mock_response = '{"tokens": ["tokens"]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
analyzer = 'arabic'
text = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"analyzer": analyzer,
"text": text,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search_analyze(**req_copy)
def test_post_search_analyze_value_error_with_retries(self):
# Enable retries and run test_post_search_analyze_value_error.
_service.enable_retries()
self.test_post_search_analyze_value_error()
# Disable retries and run test_post_search_analyze_value_error.
_service.disable_retries()
self.test_post_search_analyze_value_error()
class TestPostSearch():
"""
Test Class for post_search
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_all_params(self):
"""
post_search()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Invoke method
response = _service.post_search(
db,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
counts=counts,
drilldown=drilldown,
group_field=group_field,
group_limit=group_limit,
group_sort=group_sort,
ranges=ranges,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
assert req_body['counts'] == ['testString']
assert req_body['drilldown'] == [['testString']]
assert req_body['group_field'] == 'testString'
assert req_body['group_limit'] == 1
assert req_body['group_sort'] == ['testString']
assert req_body['ranges'] == {}
def test_post_search_all_params_with_retries(self):
# Enable retries and run test_post_search_all_params.
_service.enable_retries()
self.test_post_search_all_params()
# Disable retries and run test_post_search_all_params.
_service.disable_retries()
self.test_post_search_all_params()
@responses.activate
def test_post_search_value_error(self):
"""
test_post_search_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search(**req_copy)
def test_post_search_value_error_with_retries(self):
# Enable retries and run test_post_search_value_error.
_service.enable_retries()
self.test_post_search_value_error()
# Disable retries and run test_post_search_value_error.
_service.disable_retries()
self.test_post_search_value_error()
class TestPostSearchAsStream():
"""
Test Class for post_search_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_as_stream_all_params(self):
"""
post_search_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Invoke method
response = _service.post_search_as_stream(
db,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
counts=counts,
drilldown=drilldown,
group_field=group_field,
group_limit=group_limit,
group_sort=group_sort,
ranges=ranges,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 3
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
assert req_body['counts'] == ['testString']
assert req_body['drilldown'] == [['testString']]
assert req_body['group_field'] == 'testString'
assert req_body['group_limit'] == 1
assert req_body['group_sort'] == ['testString']
assert req_body['ranges'] == {}
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_search_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_search_as_stream_all_params.
_service.enable_retries()
self.test_post_search_as_stream_all_params()
# Disable retries and run test_post_search_as_stream_all_params.
_service.disable_retries()
self.test_post_search_as_stream_all_params()
@responses.activate
def test_post_search_as_stream_value_error(self):
"""
test_post_search_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search_as_stream(**req_copy)
def test_post_search_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_search_as_stream_value_error.
_service.enable_retries()
self.test_post_search_as_stream_value_error()
# Disable retries and run test_post_search_as_stream_value_error.
_service.disable_retries()
self.test_post_search_as_stream_value_error()
class TestGetSearchInfo():
"""
Test Class for get_search_info
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_search_info_all_params(self):
"""
get_search_info()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search_info/testString')
mock_response = '{"name": "name", "search_index": {"committed_seq": 13, "disk_size": 0, "doc_count": 0, "doc_del_count": 0, "pending_seq": 11}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_search_info(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_search_info_all_params_with_retries(self):
# Enable retries and run test_get_search_info_all_params.
_service.enable_retries()
self.test_get_search_info_all_params()
# Disable retries and run test_get_search_info_all_params.
_service.disable_retries()
self.test_get_search_info_all_params()
@responses.activate
def test_get_search_info_value_error(self):
"""
test_get_search_info_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search_info/testString')
mock_response = '{"name": "name", "search_index": {"committed_seq": 13, "disk_size": 0, "doc_count": 0, "doc_del_count": 0, "pending_seq": 11}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_search_info(**req_copy)
def test_get_search_info_value_error_with_retries(self):
# Enable retries and run test_get_search_info_value_error.
_service.enable_retries()
self.test_get_search_info_value_error()
# Disable retries and run test_get_search_info_value_error.
_service.disable_retries()
self.test_get_search_info_value_error()
# endregion
##############################################################################
# End of Service: Searches
##############################################################################
##############################################################################
# Start of Service: Geospatial
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetGeo():
"""
Test Class for get_geo
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_all_params(self):
"""
get_geo()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
bbox = 'testString'
bookmark = 'testString'
format = 'view'
g = 'testString'
include_docs = False
lat = -90
limit = 0
lon = -180
nearest = False
radius = 0
rangex = 0
rangey = 0
relation = 'intersects'
skip = 0
stale = 'ok'
# Invoke method
response = _service.get_geo(
db,
ddoc,
index,
bbox=bbox,
bookmark=bookmark,
format=format,
g=g,
include_docs=include_docs,
lat=lat,
limit=limit,
lon=lon,
nearest=nearest,
radius=radius,
rangex=rangex,
rangey=rangey,
relation=relation,
skip=skip,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'bbox={}'.format(bbox) in query_string
assert 'bookmark={}'.format(bookmark) in query_string
assert 'format={}'.format(format) in query_string
assert 'g={}'.format(g) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'lat={}'.format(lat) in query_string
assert 'limit={}'.format(limit) in query_string
assert 'lon={}'.format(lon) in query_string
assert 'nearest={}'.format('true' if nearest else 'false') in query_string
assert 'radius={}'.format(radius) in query_string
assert 'rangex={}'.format(rangex) in query_string
assert 'rangey={}'.format(rangey) in query_string
assert 'relation={}'.format(relation) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'stale={}'.format(stale) in query_string
def test_get_geo_all_params_with_retries(self):
# Enable retries and run test_get_geo_all_params.
_service.enable_retries()
self.test_get_geo_all_params()
# Disable retries and run test_get_geo_all_params.
_service.disable_retries()
self.test_get_geo_all_params()
@responses.activate
def test_get_geo_required_params(self):
"""
test_get_geo_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_geo(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_geo_required_params_with_retries(self):
# Enable retries and run test_get_geo_required_params.
_service.enable_retries()
self.test_get_geo_required_params()
# Disable retries and run test_get_geo_required_params.
_service.disable_retries()
self.test_get_geo_required_params()
@responses.activate
def test_get_geo_value_error(self):
"""
test_get_geo_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo(**req_copy)
def test_get_geo_value_error_with_retries(self):
# Enable retries and run test_get_geo_value_error.
_service.enable_retries()
self.test_get_geo_value_error()
# Disable retries and run test_get_geo_value_error.
_service.disable_retries()
self.test_get_geo_value_error()
class TestGetGeoAsStream():
"""
Test Class for get_geo_as_stream
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_as_stream_all_params(self):
"""
get_geo_as_stream()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
bbox = 'testString'
bookmark = 'testString'
format = 'view'
g = 'testString'
include_docs = False
lat = -90
limit = 0
lon = -180
nearest = False
radius = 0
rangex = 0
rangey = 0
relation = 'intersects'
skip = 0
stale = 'ok'
# Invoke method
response = _service.get_geo_as_stream(
db,
ddoc,
index,
bbox=bbox,
bookmark=bookmark,
format=format,
g=g,
include_docs=include_docs,
lat=lat,
limit=limit,
lon=lon,
nearest=nearest,
radius=radius,
rangex=rangex,
rangey=rangey,
relation=relation,
skip=skip,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'bbox={}'.format(bbox) in query_string
assert 'bookmark={}'.format(bookmark) in query_string
assert 'format={}'.format(format) in query_string
assert 'g={}'.format(g) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'lat={}'.format(lat) in query_string
assert 'limit={}'.format(limit) in query_string
assert 'lon={}'.format(lon) in query_string
assert 'nearest={}'.format('true' if nearest else 'false') in query_string
assert 'radius={}'.format(radius) in query_string
assert 'rangex={}'.format(rangex) in query_string
assert 'rangey={}'.format(rangey) in query_string
assert 'relation={}'.format(relation) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'stale={}'.format(stale) in query_string
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_geo_as_stream_all_params_with_retries(self):
# Enable retries and run test_get_geo_as_stream_all_params.
_service.enable_retries()
self.test_get_geo_as_stream_all_params()
# Disable retries and run test_get_geo_as_stream_all_params.
_service.disable_retries()
self.test_get_geo_as_stream_all_params()
@responses.activate
def test_get_geo_as_stream_required_params(self):
"""
test_get_geo_as_stream_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_geo_as_stream(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_geo_as_stream_required_params_with_retries(self):
# Enable retries and run test_get_geo_as_stream_required_params.
_service.enable_retries()
self.test_get_geo_as_stream_required_params()
# Disable retries and run test_get_geo_as_stream_required_params.
_service.disable_retries()
self.test_get_geo_as_stream_required_params()
@responses.activate
def test_get_geo_as_stream_value_error(self):
"""
test_get_geo_as_stream_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo_as_stream(**req_copy)
def test_get_geo_as_stream_value_error_with_retries(self):
# Enable retries and run test_get_geo_as_stream_value_error.
_service.enable_retries()
self.test_get_geo_as_stream_value_error()
# Disable retries and run test_get_geo_as_stream_value_error.
_service.disable_retries()
self.test_get_geo_as_stream_value_error()
class TestPostGeoCleanup():
"""
Test Class for post_geo_cleanup
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_geo_cleanup_all_params(self):
"""
post_geo_cleanup()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_geo_cleanup')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=202)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.post_geo_cleanup(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 202
def test_post_geo_cleanup_all_params_with_retries(self):
# Enable retries and run test_post_geo_cleanup_all_params.
_service.enable_retries()
self.test_post_geo_cleanup_all_params()
# Disable retries and run test_post_geo_cleanup_all_params.
_service.disable_retries()
self.test_post_geo_cleanup_all_params()
@responses.activate
def test_post_geo_cleanup_value_error(self):
"""
test_post_geo_cleanup_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_geo_cleanup')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=202)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_geo_cleanup(**req_copy)
def test_post_geo_cleanup_value_error_with_retries(self):
# Enable retries and run test_post_geo_cleanup_value_error.
_service.enable_retries()
self.test_post_geo_cleanup_value_error()
# Disable retries and run test_post_geo_cleanup_value_error.
_service.disable_retries()
self.test_post_geo_cleanup_value_error()
class TestGetGeoIndexInformation():
"""
Test Class for get_geo_index_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_index_information_all_params(self):
"""
get_geo_index_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo_info/testString')
mock_response = '{"geo_index": {"data_size": 0, "disk_size": 0, "doc_count": 0}, "name": "name"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_geo_index_information(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_geo_index_information_all_params_with_retries(self):
# Enable retries and run test_get_geo_index_information_all_params.
_service.enable_retries()
self.test_get_geo_index_information_all_params()
# Disable retries and run test_get_geo_index_information_all_params.
_service.disable_retries()
self.test_get_geo_index_information_all_params()
@responses.activate
def test_get_geo_index_information_value_error(self):
"""
test_get_geo_index_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo_info/testString')
mock_response = '{"geo_index": {"data_size": 0, "disk_size": 0, "doc_count": 0}, "name": "name"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo_index_information(**req_copy)
def test_get_geo_index_information_value_error_with_retries(self):
# Enable retries and run test_get_geo_index_information_value_error.
_service.enable_retries()
self.test_get_geo_index_information_value_error()
# Disable retries and run test_get_geo_index_information_value_error.
_service.disable_retries()
self.test_get_geo_index_information_value_error()
# endregion
##############################################################################
# End of Service: Geospatial
##############################################################################
##############################################################################
# Start of Service: Replication
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadReplicationDocument():
"""
Test Class for head_replication_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_replication_document_all_params(self):
"""
head_replication_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
if_none_match = 'testString'
# Invoke method
response = _service.head_replication_document(
doc_id,
if_none_match=if_none_match,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_replication_document_all_params_with_retries(self):
# Enable retries and run test_head_replication_document_all_params.
_service.enable_retries()
self.test_head_replication_document_all_params()
# Disable retries and run test_head_replication_document_all_params.
_service.disable_retries()
self.test_head_replication_document_all_params()
@responses.activate
def test_head_replication_document_required_params(self):
"""
test_head_replication_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.head_replication_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_replication_document_required_params_with_retries(self):
# Enable retries and run test_head_replication_document_required_params.
_service.enable_retries()
self.test_head_replication_document_required_params()
# Disable retries and run test_head_replication_document_required_params.
_service.disable_retries()
self.test_head_replication_document_required_params()
@responses.activate
def test_head_replication_document_value_error(self):
"""
test_head_replication_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_replication_document(**req_copy)
def test_head_replication_document_value_error_with_retries(self):
# Enable retries and run test_head_replication_document_value_error.
_service.enable_retries()
self.test_head_replication_document_value_error()
# Disable retries and run test_head_replication_document_value_error.
_service.disable_retries()
self.test_head_replication_document_value_error()
class TestHeadSchedulerDocument():
"""
Test Class for head_scheduler_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_scheduler_document_all_params(self):
"""
head_scheduler_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.head_scheduler_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_scheduler_document_all_params_with_retries(self):
# Enable retries and run test_head_scheduler_document_all_params.
_service.enable_retries()
self.test_head_scheduler_document_all_params()
# Disable retries and run test_head_scheduler_document_all_params.
_service.disable_retries()
self.test_head_scheduler_document_all_params()
@responses.activate
def test_head_scheduler_document_value_error(self):
"""
test_head_scheduler_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_scheduler_document(**req_copy)
def test_head_scheduler_document_value_error_with_retries(self):
# Enable retries and run test_head_scheduler_document_value_error.
_service.enable_retries()
self.test_head_scheduler_document_value_error()
# Disable retries and run test_head_scheduler_document_value_error.
_service.disable_retries()
self.test_head_scheduler_document_value_error()
class TestHeadSchedulerJob():
"""
Test Class for head_scheduler_job
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_scheduler_job_all_params(self):
"""
head_scheduler_job()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
job_id = 'testString'
# Invoke method
response = _service.head_scheduler_job(
job_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_scheduler_job_all_params_with_retries(self):
# Enable retries and run test_head_scheduler_job_all_params.
_service.enable_retries()
self.test_head_scheduler_job_all_params()
# Disable retries and run test_head_scheduler_job_all_params.
_service.disable_retries()
self.test_head_scheduler_job_all_params()
@responses.activate
def test_head_scheduler_job_value_error(self):
"""
test_head_scheduler_job_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
job_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"job_id": job_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_scheduler_job(**req_copy)
def test_head_scheduler_job_value_error_with_retries(self):
# Enable retries and run test_head_scheduler_job_value_error.
_service.enable_retries()
self.test_head_scheduler_job_value_error()
# Disable retries and run test_head_scheduler_job_value_error.
_service.disable_retries()
self.test_head_scheduler_job_value_error()
class TestDeleteReplicationDocument():
"""
Test Class for delete_replication_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_replication_document_all_params(self):
"""
delete_replication_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
# Invoke method
response = _service.delete_replication_document(
doc_id,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_replication_document_all_params_with_retries(self):
# Enable retries and run test_delete_replication_document_all_params.
_service.enable_retries()
self.test_delete_replication_document_all_params()
# Disable retries and run test_delete_replication_document_all_params.
_service.disable_retries()
self.test_delete_replication_document_all_params()
@responses.activate
def test_delete_replication_document_required_params(self):
"""
test_delete_replication_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.delete_replication_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
def test_delete_replication_document_required_params_with_retries(self):
# Enable retries and run test_delete_replication_document_required_params.
_service.enable_retries()
self.test_delete_replication_document_required_params()
# Disable retries and run test_delete_replication_document_required_params.
_service.disable_retries()
self.test_delete_replication_document_required_params()
@responses.activate
def test_delete_replication_document_value_error(self):
"""
test_delete_replication_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_replication_document(**req_copy)
def test_delete_replication_document_value_error_with_retries(self):
# Enable retries and run test_delete_replication_document_value_error.
_service.enable_retries()
self.test_delete_replication_document_value_error()
# Disable retries and run test_delete_replication_document_value_error.
_service.disable_retries()
self.test_delete_replication_document_value_error()
class TestGetReplicationDocument():
"""
Test Class for get_replication_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_replication_document_all_params(self):
"""
get_replication_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_replication_document(
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_replication_document_all_params_with_retries(self):
# Enable retries and run test_get_replication_document_all_params.
_service.enable_retries()
self.test_get_replication_document_all_params()
# Disable retries and run test_get_replication_document_all_params.
_service.disable_retries()
self.test_get_replication_document_all_params()
@responses.activate
def test_get_replication_document_required_params(self):
"""
test_get_replication_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.get_replication_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_replication_document_required_params_with_retries(self):
# Enable retries and run test_get_replication_document_required_params.
_service.enable_retries()
self.test_get_replication_document_required_params()
# Disable retries and run test_get_replication_document_required_params.
_service.disable_retries()
self.test_get_replication_document_required_params()
@responses.activate
def test_get_replication_document_value_error(self):
"""
test_get_replication_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_replication_document(**req_copy)
def test_get_replication_document_value_error_with_retries(self):
# Enable retries and run test_get_replication_document_value_error.
_service.enable_retries()
self.test_get_replication_document_value_error()
# Disable retries and run test_get_replication_document_value_error.
_service.disable_retries()
self.test_get_replication_document_value_error()
class TestPutReplicationDocument():
"""
Test Class for put_replication_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_replication_document_all_params(self):
"""
put_replication_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_replication_document(
doc_id,
replication_document,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == replication_document
def test_put_replication_document_all_params_with_retries(self):
# Enable retries and run test_put_replication_document_all_params.
_service.enable_retries()
self.test_put_replication_document_all_params()
# Disable retries and run test_put_replication_document_all_params.
_service.disable_retries()
self.test_put_replication_document_all_params()
@responses.activate
def test_put_replication_document_required_params(self):
"""
test_put_replication_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
# Invoke method
response = _service.put_replication_document(
doc_id,
replication_document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == replication_document
def test_put_replication_document_required_params_with_retries(self):
# Enable retries and run test_put_replication_document_required_params.
_service.enable_retries()
self.test_put_replication_document_required_params()
# Disable retries and run test_put_replication_document_required_params.
_service.disable_retries()
self.test_put_replication_document_required_params()
@responses.activate
def test_put_replication_document_value_error(self):
"""
test_put_replication_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
"replication_document": replication_document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_replication_document(**req_copy)
def test_put_replication_document_value_error_with_retries(self):
# Enable retries and run test_put_replication_document_value_error.
_service.enable_retries()
self.test_put_replication_document_value_error()
# Disable retries and run test_put_replication_document_value_error.
_service.disable_retries()
self.test_put_replication_document_value_error()
class TestGetSchedulerDocs():
"""
Test Class for get_scheduler_docs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_docs_all_params(self):
"""
get_scheduler_docs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs')
mock_response = '{"total_rows": 0, "docs": [{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
limit = 0
skip = 0
states = ['initializing']
# Invoke method
response = _service.get_scheduler_docs(
limit=limit,
skip=skip,
states=states,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'limit={}'.format(limit) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'states={}'.format(','.join(states)) in query_string
def test_get_scheduler_docs_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_docs_all_params.
_service.enable_retries()
self.test_get_scheduler_docs_all_params()
# Disable retries and run test_get_scheduler_docs_all_params.
_service.disable_retries()
self.test_get_scheduler_docs_all_params()
@responses.activate
def test_get_scheduler_docs_required_params(self):
"""
test_get_scheduler_docs_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs')
mock_response = '{"total_rows": 0, "docs": [{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_scheduler_docs()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_docs_required_params_with_retries(self):
# Enable retries and run test_get_scheduler_docs_required_params.
_service.enable_retries()
self.test_get_scheduler_docs_required_params()
# Disable retries and run test_get_scheduler_docs_required_params.
_service.disable_retries()
self.test_get_scheduler_docs_required_params()
class TestGetSchedulerDocument():
"""
Test Class for get_scheduler_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_document_all_params(self):
"""
get_scheduler_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.get_scheduler_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_document_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_document_all_params.
_service.enable_retries()
self.test_get_scheduler_document_all_params()
# Disable retries and run test_get_scheduler_document_all_params.
_service.disable_retries()
self.test_get_scheduler_document_all_params()
@responses.activate
def test_get_scheduler_document_value_error(self):
"""
test_get_scheduler_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_scheduler_document(**req_copy)
def test_get_scheduler_document_value_error_with_retries(self):
# Enable retries and run test_get_scheduler_document_value_error.
_service.enable_retries()
self.test_get_scheduler_document_value_error()
# Disable retries and run test_get_scheduler_document_value_error.
_service.disable_retries()
self.test_get_scheduler_document_value_error()
class TestGetSchedulerJobs():
"""
Test Class for get_scheduler_jobs
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_jobs_all_params(self):
"""
get_scheduler_jobs()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs')
mock_response = '{"total_rows": 0, "jobs": [{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
limit = 0
skip = 0
# Invoke method
response = _service.get_scheduler_jobs(
limit=limit,
skip=skip,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'limit={}'.format(limit) in query_string
assert 'skip={}'.format(skip) in query_string
def test_get_scheduler_jobs_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_jobs_all_params.
_service.enable_retries()
self.test_get_scheduler_jobs_all_params()
# Disable retries and run test_get_scheduler_jobs_all_params.
_service.disable_retries()
self.test_get_scheduler_jobs_all_params()
@responses.activate
def test_get_scheduler_jobs_required_params(self):
"""
test_get_scheduler_jobs_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs')
mock_response = '{"total_rows": 0, "jobs": [{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_scheduler_jobs()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_jobs_required_params_with_retries(self):
# Enable retries and run test_get_scheduler_jobs_required_params.
_service.enable_retries()
self.test_get_scheduler_jobs_required_params()
# Disable retries and run test_get_scheduler_jobs_required_params.
_service.disable_retries()
self.test_get_scheduler_jobs_required_params()
class TestGetSchedulerJob():
"""
Test Class for get_scheduler_job
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_job_all_params(self):
"""
get_scheduler_job()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
job_id = 'testString'
# Invoke method
response = _service.get_scheduler_job(
job_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_job_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_job_all_params.
_service.enable_retries()
self.test_get_scheduler_job_all_params()
# Disable retries and run test_get_scheduler_job_all_params.
_service.disable_retries()
self.test_get_scheduler_job_all_params()
@responses.activate
def test_get_scheduler_job_value_error(self):
"""
test_get_scheduler_job_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
job_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"job_id": job_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_scheduler_job(**req_copy)
def test_get_scheduler_job_value_error_with_retries(self):
# Enable retries and run test_get_scheduler_job_value_error.
_service.enable_retries()
self.test_get_scheduler_job_value_error()
# Disable retries and run test_get_scheduler_job_value_error.
_service.disable_retries()
self.test_get_scheduler_job_value_error()
# endregion
##############################################################################
# End of Service: Replication
##############################################################################
##############################################################################
# Start of Service: Authentication
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetSessionInformation():
"""
Test Class for get_session_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_session_information_all_params(self):
"""
get_session_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_session')
mock_response = '{"ok": true, "info": {"authenticated": "authenticated", "authentication_db": "authentication_db", "authentication_handlers": ["authentication_handlers"]}, "userCtx": {"db": "db", "name": "name", "roles": ["_reader"]}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_session_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_session_information_all_params_with_retries(self):
# Enable retries and run test_get_session_information_all_params.
_service.enable_retries()
self.test_get_session_information_all_params()
# Disable retries and run test_get_session_information_all_params.
_service.disable_retries()
self.test_get_session_information_all_params()
# endregion
##############################################################################
# End of Service: Authentication
##############################################################################
##############################################################################
# Start of Service: Authorization
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetSecurity():
"""
Test Class for get_security
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_security_all_params(self):
"""
get_security()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_security')
mock_response = '{"admins": {"names": ["names"], "roles": ["roles"]}, "members": {"names": ["names"], "roles": ["roles"]}, "cloudant": {"mapKey": ["_reader"]}, "couchdb_auth_only": false}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_security(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_security_all_params_with_retries(self):
# Enable retries and run test_get_security_all_params.
_service.enable_retries()
self.test_get_security_all_params()
# Disable retries and run test_get_security_all_params.
_service.disable_retries()
self.test_get_security_all_params()
@responses.activate
def test_get_security_value_error(self):
"""
test_get_security_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_security')
mock_response = '{"admins": {"names": ["names"], "roles": ["roles"]}, "members": {"names": ["names"], "roles": ["roles"]}, "cloudant": {"mapKey": ["_reader"]}, "couchdb_auth_only": false}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_security(**req_copy)
def test_get_security_value_error_with_retries(self):
# Enable retries and run test_get_security_value_error.
_service.enable_retries()
self.test_get_security_value_error()
# Disable retries and run test_get_security_value_error.
_service.disable_retries()
self.test_get_security_value_error()
class TestPutSecurity():
"""
Test Class for put_security
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_security_all_params(self):
"""
put_security()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_security')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a SecurityObject model
security_object_model = {}
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Set up parameter values
db = 'testString'
admins = security_object_model
members = security_object_model
cloudant = {}
couchdb_auth_only = True
# Invoke method
response = _service.put_security(
db,
admins=admins,
members=members,
cloudant=cloudant,
couchdb_auth_only=couchdb_auth_only,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['admins'] == security_object_model
assert req_body['members'] == security_object_model
assert req_body['cloudant'] == {}
assert req_body['couchdb_auth_only'] == True
def test_put_security_all_params_with_retries(self):
# Enable retries and run test_put_security_all_params.
_service.enable_retries()
self.test_put_security_all_params()
# Disable retries and run test_put_security_all_params.
_service.disable_retries()
self.test_put_security_all_params()
@responses.activate
def test_put_security_value_error(self):
"""
test_put_security_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_security')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a SecurityObject model
security_object_model = {}
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Set up parameter values
db = 'testString'
admins = security_object_model
members = security_object_model
cloudant = {}
couchdb_auth_only = True
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_security(**req_copy)
def test_put_security_value_error_with_retries(self):
# Enable retries and run test_put_security_value_error.
_service.enable_retries()
self.test_put_security_value_error()
# Disable retries and run test_put_security_value_error.
_service.disable_retries()
self.test_put_security_value_error()
class TestPostApiKeys():
"""
Test Class for post_api_keys
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_api_keys_all_params(self):
"""
post_api_keys()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/api_keys')
mock_response = '{"ok": true, "key": "key", "password": "password"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Invoke method
response = _service.post_api_keys()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
def test_post_api_keys_all_params_with_retries(self):
# Enable retries and run test_post_api_keys_all_params.
_service.enable_retries()
self.test_post_api_keys_all_params()
# Disable retries and run test_post_api_keys_all_params.
_service.disable_retries()
self.test_post_api_keys_all_params()
class TestPutCloudantSecurityConfiguration():
"""
Test Class for put_cloudant_security_configuration
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_cloudant_security_configuration_all_params(self):
"""
put_cloudant_security_configuration()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/db/testString/_security')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a SecurityObject model
security_object_model = {}
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Set up parameter values
db = 'testString'
cloudant = {}
admins = security_object_model
members = security_object_model
couchdb_auth_only = True
# Invoke method
response = _service.put_cloudant_security_configuration(
db,
cloudant,
admins=admins,
members=members,
couchdb_auth_only=couchdb_auth_only,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['cloudant'] == {}
assert req_body['admins'] == security_object_model
assert req_body['members'] == security_object_model
assert req_body['couchdb_auth_only'] == True
def test_put_cloudant_security_configuration_all_params_with_retries(self):
# Enable retries and run test_put_cloudant_security_configuration_all_params.
_service.enable_retries()
self.test_put_cloudant_security_configuration_all_params()
# Disable retries and run test_put_cloudant_security_configuration_all_params.
_service.disable_retries()
self.test_put_cloudant_security_configuration_all_params()
@responses.activate
def test_put_cloudant_security_configuration_value_error(self):
"""
test_put_cloudant_security_configuration_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/db/testString/_security')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a SecurityObject model
security_object_model = {}
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Set up parameter values
db = 'testString'
cloudant = {}
admins = security_object_model
members = security_object_model
couchdb_auth_only = True
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"cloudant": cloudant,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_cloudant_security_configuration(**req_copy)
def test_put_cloudant_security_configuration_value_error_with_retries(self):
# Enable retries and run test_put_cloudant_security_configuration_value_error.
_service.enable_retries()
self.test_put_cloudant_security_configuration_value_error()
# Disable retries and run test_put_cloudant_security_configuration_value_error.
_service.disable_retries()
self.test_put_cloudant_security_configuration_value_error()
# endregion
##############################################################################
# End of Service: Authorization
##############################################################################
##############################################################################
# Start of Service: CORS
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetCorsInformation():
"""
Test Class for get_cors_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_cors_information_all_params(self):
"""
get_cors_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/config/cors')
mock_response = '{"allow_credentials": true, "enable_cors": true, "origins": ["origins"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_cors_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_cors_information_all_params_with_retries(self):
# Enable retries and run test_get_cors_information_all_params.
_service.enable_retries()
self.test_get_cors_information_all_params()
# Disable retries and run test_get_cors_information_all_params.
_service.disable_retries()
self.test_get_cors_information_all_params()
class TestPutCorsConfiguration():
"""
Test Class for put_cors_configuration
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_cors_configuration_all_params(self):
"""
put_cors_configuration()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/config/cors')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
origins = ['testString']
allow_credentials = True
enable_cors = True
# Invoke method
response = _service.put_cors_configuration(
origins,
allow_credentials=allow_credentials,
enable_cors=enable_cors,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['origins'] == ['testString']
assert req_body['allow_credentials'] == True
assert req_body['enable_cors'] == True
def test_put_cors_configuration_all_params_with_retries(self):
# Enable retries and run test_put_cors_configuration_all_params.
_service.enable_retries()
self.test_put_cors_configuration_all_params()
# Disable retries and run test_put_cors_configuration_all_params.
_service.disable_retries()
self.test_put_cors_configuration_all_params()
@responses.activate
def test_put_cors_configuration_value_error(self):
"""
test_put_cors_configuration_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/config/cors')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
origins = ['testString']
allow_credentials = True
enable_cors = True
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"origins": origins,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_cors_configuration(**req_copy)
def test_put_cors_configuration_value_error_with_retries(self):
# Enable retries and run test_put_cors_configuration_value_error.
_service.enable_retries()
self.test_put_cors_configuration_value_error()
# Disable retries and run test_put_cors_configuration_value_error.
_service.disable_retries()
self.test_put_cors_configuration_value_error()
# endregion
##############################################################################
# End of Service: CORS
##############################################################################
##############################################################################
# Start of Service: Attachments
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadAttachment():
"""
Test Class for head_attachment
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_attachment_all_params(self):
"""
head_attachment()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
if_match = 'testString'
if_none_match = 'testString'
rev = 'testString'
# Invoke method
response = _service.head_attachment(
db,
doc_id,
attachment_name,
if_match=if_match,
if_none_match=if_none_match,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'rev={}'.format(rev) in query_string
def test_head_attachment_all_params_with_retries(self):
# Enable retries and run test_head_attachment_all_params.
_service.enable_retries()
self.test_head_attachment_all_params()
# Disable retries and run test_head_attachment_all_params.
_service.disable_retries()
self.test_head_attachment_all_params()
@responses.activate
def test_head_attachment_required_params(self):
"""
test_head_attachment_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Invoke method
response = _service.head_attachment(
db,
doc_id,
attachment_name,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_attachment_required_params_with_retries(self):
# Enable retries and run test_head_attachment_required_params.
_service.enable_retries()
self.test_head_attachment_required_params()
# Disable retries and run test_head_attachment_required_params.
_service.disable_retries()
self.test_head_attachment_required_params()
@responses.activate
def test_head_attachment_value_error(self):
"""
test_head_attachment_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"attachment_name": attachment_name,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_attachment(**req_copy)
def test_head_attachment_value_error_with_retries(self):
# Enable retries and run test_head_attachment_value_error.
_service.enable_retries()
self.test_head_attachment_value_error()
# Disable retries and run test_head_attachment_value_error.
_service.disable_retries()
self.test_head_attachment_value_error()
class TestDeleteAttachment():
"""
Test Class for delete_attachment
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_attachment_all_params(self):
"""
delete_attachment()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
if_match = 'testString'
rev = 'testString'
batch = 'ok'
# Invoke method
response = _service.delete_attachment(
db,
doc_id,
attachment_name,
if_match=if_match,
rev=rev,
batch=batch,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'rev={}'.format(rev) in query_string
assert 'batch={}'.format(batch) in query_string
def test_delete_attachment_all_params_with_retries(self):
# Enable retries and run test_delete_attachment_all_params.
_service.enable_retries()
self.test_delete_attachment_all_params()
# Disable retries and run test_delete_attachment_all_params.
_service.disable_retries()
self.test_delete_attachment_all_params()
@responses.activate
def test_delete_attachment_required_params(self):
"""
test_delete_attachment_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Invoke method
response = _service.delete_attachment(
db,
doc_id,
attachment_name,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
def test_delete_attachment_required_params_with_retries(self):
# Enable retries and run test_delete_attachment_required_params.
_service.enable_retries()
self.test_delete_attachment_required_params()
# Disable retries and run test_delete_attachment_required_params.
_service.disable_retries()
self.test_delete_attachment_required_params()
@responses.activate
def test_delete_attachment_value_error(self):
"""
test_delete_attachment_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"attachment_name": attachment_name,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_attachment(**req_copy)
def test_delete_attachment_value_error_with_retries(self):
# Enable retries and run test_delete_attachment_value_error.
_service.enable_retries()
self.test_delete_attachment_value_error()
# Disable retries and run test_delete_attachment_value_error.
_service.disable_retries()
self.test_delete_attachment_value_error()
class TestGetAttachment():
"""
Test Class for get_attachment
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_attachment_all_params(self):
"""
get_attachment()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='*/*',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
if_match = 'testString'
if_none_match = 'testString'
range = 'testString'
rev = 'testString'
# Invoke method
response = _service.get_attachment(
db,
doc_id,
attachment_name,
if_match=if_match,
if_none_match=if_none_match,
range=range,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'rev={}'.format(rev) in query_string
def test_get_attachment_all_params_with_retries(self):
# Enable retries and run test_get_attachment_all_params.
_service.enable_retries()
self.test_get_attachment_all_params()
# Disable retries and run test_get_attachment_all_params.
_service.disable_retries()
self.test_get_attachment_all_params()
@responses.activate
def test_get_attachment_required_params(self):
"""
test_get_attachment_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='*/*',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Invoke method
response = _service.get_attachment(
db,
doc_id,
attachment_name,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_attachment_required_params_with_retries(self):
# Enable retries and run test_get_attachment_required_params.
_service.enable_retries()
self.test_get_attachment_required_params()
# Disable retries and run test_get_attachment_required_params.
_service.disable_retries()
self.test_get_attachment_required_params()
@responses.activate
def test_get_attachment_value_error(self):
"""
test_get_attachment_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='*/*',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"attachment_name": attachment_name,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_attachment(**req_copy)
def test_get_attachment_value_error_with_retries(self):
# Enable retries and run test_get_attachment_value_error.
_service.enable_retries()
self.test_get_attachment_value_error()
# Disable retries and run test_get_attachment_value_error.
_service.disable_retries()
self.test_get_attachment_value_error()
class TestPutAttachment():
"""
Test Class for put_attachment
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_attachment_all_params(self):
"""
put_attachment()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
attachment = io.BytesIO(b'This is a mock file.').getvalue()
content_type = 'application/octet-stream'
if_match = 'testString'
rev = 'testString'
# Invoke method
response = _service.put_attachment(
db,
doc_id,
attachment_name,
attachment,
content_type,
if_match=if_match,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_attachment_all_params_with_retries(self):
# Enable retries and run test_put_attachment_all_params.
_service.enable_retries()
self.test_put_attachment_all_params()
# Disable retries and run test_put_attachment_all_params.
_service.disable_retries()
self.test_put_attachment_all_params()
@responses.activate
def test_put_attachment_required_params(self):
"""
test_put_attachment_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
attachment = io.BytesIO(b'This is a mock file.').getvalue()
content_type = 'application/octet-stream'
# Invoke method
response = _service.put_attachment(
db,
doc_id,
attachment_name,
attachment,
content_type,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_attachment_required_params_with_retries(self):
# Enable retries and run test_put_attachment_required_params.
_service.enable_retries()
self.test_put_attachment_required_params()
# Disable retries and run test_put_attachment_required_params.
_service.disable_retries()
self.test_put_attachment_required_params()
@responses.activate
def test_put_attachment_value_error(self):
"""
test_put_attachment_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
attachment_name = 'testString'
attachment = io.BytesIO(b'This is a mock file.').getvalue()
content_type = 'application/octet-stream'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"attachment_name": attachment_name,
"attachment": attachment,
"content_type": content_type,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_attachment(**req_copy)
def test_put_attachment_value_error_with_retries(self):
# Enable retries and run test_put_attachment_value_error.
_service.enable_retries()
self.test_put_attachment_value_error()
# Disable retries and run test_put_attachment_value_error.
_service.disable_retries()
self.test_put_attachment_value_error()
# endregion
##############################################################################
# End of Service: Attachments
##############################################################################
##############################################################################
# Start of Service: LocalDocuments
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadLocalDocument():
"""
Test Class for head_local_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_local_document_all_params(self):
"""
head_local_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
# Invoke method
response = _service.head_local_document(
db,
doc_id,
if_none_match=if_none_match,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_local_document_all_params_with_retries(self):
# Enable retries and run test_head_local_document_all_params.
_service.enable_retries()
self.test_head_local_document_all_params()
# Disable retries and run test_head_local_document_all_params.
_service.disable_retries()
self.test_head_local_document_all_params()
@responses.activate
def test_head_local_document_required_params(self):
"""
test_head_local_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.head_local_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_local_document_required_params_with_retries(self):
# Enable retries and run test_head_local_document_required_params.
_service.enable_retries()
self.test_head_local_document_required_params()
# Disable retries and run test_head_local_document_required_params.
_service.disable_retries()
self.test_head_local_document_required_params()
@responses.activate
def test_head_local_document_value_error(self):
"""
test_head_local_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_local_document(**req_copy)
def test_head_local_document_value_error_with_retries(self):
# Enable retries and run test_head_local_document_value_error.
_service.enable_retries()
self.test_head_local_document_value_error()
# Disable retries and run test_head_local_document_value_error.
_service.disable_retries()
self.test_head_local_document_value_error()
class TestDeleteLocalDocument():
"""
Test Class for delete_local_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_local_document_all_params(self):
"""
delete_local_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
batch = 'ok'
# Invoke method
response = _service.delete_local_document(
db,
doc_id,
batch=batch,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
def test_delete_local_document_all_params_with_retries(self):
# Enable retries and run test_delete_local_document_all_params.
_service.enable_retries()
self.test_delete_local_document_all_params()
# Disable retries and run test_delete_local_document_all_params.
_service.disable_retries()
self.test_delete_local_document_all_params()
@responses.activate
def test_delete_local_document_required_params(self):
"""
test_delete_local_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.delete_local_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_local_document_required_params_with_retries(self):
# Enable retries and run test_delete_local_document_required_params.
_service.enable_retries()
self.test_delete_local_document_required_params()
# Disable retries and run test_delete_local_document_required_params.
_service.disable_retries()
self.test_delete_local_document_required_params()
@responses.activate
def test_delete_local_document_value_error(self):
"""
test_delete_local_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_local_document(**req_copy)
def test_delete_local_document_value_error_with_retries(self):
# Enable retries and run test_delete_local_document_value_error.
_service.enable_retries()
self.test_delete_local_document_value_error()
# Disable retries and run test_delete_local_document_value_error.
_service.disable_retries()
self.test_delete_local_document_value_error()
class TestGetLocalDocument():
"""
Test Class for get_local_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_local_document_all_params(self):
"""
get_local_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
accept = 'application/json'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
local_seq = False
# Invoke method
response = _service.get_local_document(
db,
doc_id,
accept=accept,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
local_seq=local_seq,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
def test_get_local_document_all_params_with_retries(self):
# Enable retries and run test_get_local_document_all_params.
_service.enable_retries()
self.test_get_local_document_all_params()
# Disable retries and run test_get_local_document_all_params.
_service.disable_retries()
self.test_get_local_document_all_params()
@responses.activate
def test_get_local_document_required_params(self):
"""
test_get_local_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_local_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_local_document_required_params_with_retries(self):
# Enable retries and run test_get_local_document_required_params.
_service.enable_retries()
self.test_get_local_document_required_params()
# Disable retries and run test_get_local_document_required_params.
_service.disable_retries()
self.test_get_local_document_required_params()
@responses.activate
def test_get_local_document_value_error(self):
"""
test_get_local_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_local_document(**req_copy)
def test_get_local_document_value_error_with_retries(self):
# Enable retries and run test_get_local_document_value_error.
_service.enable_retries()
self.test_get_local_document_value_error()
# Disable retries and run test_get_local_document_value_error.
_service.disable_retries()
self.test_get_local_document_value_error()
class TestPutLocalDocument():
"""
Test Class for put_local_document
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_local_document_all_params(self):
"""
put_local_document()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
content_type = 'application/json'
batch = 'ok'
# Invoke method
response = _service.put_local_document(
db,
doc_id,
document,
content_type=content_type,
batch=batch,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_local_document_all_params_with_retries(self):
# Enable retries and run test_put_local_document_all_params.
_service.enable_retries()
self.test_put_local_document_all_params()
# Disable retries and run test_put_local_document_all_params.
_service.disable_retries()
self.test_put_local_document_all_params()
@responses.activate
def test_put_local_document_required_params(self):
"""
test_put_local_document_required_params()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Invoke method
response = _service.put_local_document(
db,
doc_id,
document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_local_document_required_params_with_retries(self):
# Enable retries and run test_put_local_document_required_params.
_service.enable_retries()
self.test_put_local_document_required_params()
# Disable retries and run test_put_local_document_required_params.
_service.disable_retries()
self.test_put_local_document_required_params()
@responses.activate
def test_put_local_document_value_error(self):
"""
test_put_local_document_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"document": document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_local_document(**req_copy)
def test_put_local_document_value_error_with_retries(self):
# Enable retries and run test_put_local_document_value_error.
_service.enable_retries()
self.test_put_local_document_value_error()
# Disable retries and run test_put_local_document_value_error.
_service.disable_retries()
self.test_put_local_document_value_error()
# endregion
##############################################################################
# End of Service: LocalDocuments
##############################################################################
##############################################################################
# Start of Service: DatabaseDetails
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostRevsDiff():
"""
Test Class for post_revs_diff
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_revs_diff_all_params(self):
"""
post_revs_diff()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_revs_diff')
mock_response = '{"mapKey": {"missing": ["missing"], "possible_ancestors": ["possible_ancestors"]}}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
document_revisions = {}
# Invoke method
response = _service.post_revs_diff(
db,
document_revisions,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == document_revisions
def test_post_revs_diff_all_params_with_retries(self):
# Enable retries and run test_post_revs_diff_all_params.
_service.enable_retries()
self.test_post_revs_diff_all_params()
# Disable retries and run test_post_revs_diff_all_params.
_service.disable_retries()
self.test_post_revs_diff_all_params()
@responses.activate
def test_post_revs_diff_value_error(self):
"""
test_post_revs_diff_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_revs_diff')
mock_response = '{"mapKey": {"missing": ["missing"], "possible_ancestors": ["possible_ancestors"]}}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
document_revisions = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"document_revisions": document_revisions,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_revs_diff(**req_copy)
def test_post_revs_diff_value_error_with_retries(self):
# Enable retries and run test_post_revs_diff_value_error.
_service.enable_retries()
self.test_post_revs_diff_value_error()
# Disable retries and run test_post_revs_diff_value_error.
_service.disable_retries()
self.test_post_revs_diff_value_error()
class TestGetShardsInformation():
"""
Test Class for get_shards_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_shards_information_all_params(self):
"""
get_shards_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_shards')
mock_response = '{"shards": {"mapKey": ["inner"]}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_shards_information(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_shards_information_all_params_with_retries(self):
# Enable retries and run test_get_shards_information_all_params.
_service.enable_retries()
self.test_get_shards_information_all_params()
# Disable retries and run test_get_shards_information_all_params.
_service.disable_retries()
self.test_get_shards_information_all_params()
@responses.activate
def test_get_shards_information_value_error(self):
"""
test_get_shards_information_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_shards')
mock_response = '{"shards": {"mapKey": ["inner"]}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_shards_information(**req_copy)
def test_get_shards_information_value_error_with_retries(self):
# Enable retries and run test_get_shards_information_value_error.
_service.enable_retries()
self.test_get_shards_information_value_error()
# Disable retries and run test_get_shards_information_value_error.
_service.disable_retries()
self.test_get_shards_information_value_error()
class TestGetDocumentShardsInfo():
"""
Test Class for get_document_shards_info
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_shards_info_all_params(self):
"""
get_document_shards_info()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_shards/testString')
mock_response = '{"nodes": ["nodes"], "range": "range"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document_shards_info(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_shards_info_all_params_with_retries(self):
# Enable retries and run test_get_document_shards_info_all_params.
_service.enable_retries()
self.test_get_document_shards_info_all_params()
# Disable retries and run test_get_document_shards_info_all_params.
_service.disable_retries()
self.test_get_document_shards_info_all_params()
@responses.activate
def test_get_document_shards_info_value_error(self):
"""
test_get_document_shards_info_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_shards/testString')
mock_response = '{"nodes": ["nodes"], "range": "range"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_shards_info(**req_copy)
def test_get_document_shards_info_value_error_with_retries(self):
# Enable retries and run test_get_document_shards_info_value_error.
_service.enable_retries()
self.test_get_document_shards_info_value_error()
# Disable retries and run test_get_document_shards_info_value_error.
_service.disable_retries()
self.test_get_document_shards_info_value_error()
# endregion
##############################################################################
# End of Service: DatabaseDetails
##############################################################################
##############################################################################
# Start of Service: Monitoring
##############################################################################
# region
class TestNewInstance():
"""
Test Class for new_instance
"""
def test_new_instance(self):
"""
new_instance()
"""
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
"""
new_instance_without_authenticator()
"""
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadUpInformation():
"""
Test Class for head_up_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_up_information_all_params(self):
"""
head_up_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_up')
responses.add(responses.HEAD,
url,
status=200)
# Invoke method
response = _service.head_up_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_up_information_all_params_with_retries(self):
# Enable retries and run test_head_up_information_all_params.
_service.enable_retries()
self.test_head_up_information_all_params()
# Disable retries and run test_head_up_information_all_params.
_service.disable_retries()
self.test_head_up_information_all_params()
class TestGetActiveTasks():
"""
Test Class for get_active_tasks
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_active_tasks_all_params(self):
"""
get_active_tasks()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_active_tasks')
mock_response = '[{"changes_done": 0, "database": "database", "node": "node", "pid": "pid", "progress": 0, "started_on": 0, "status": "status", "task": "task", "total_changes": 0, "type": "type", "updated_on": 0}]'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_active_tasks()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_active_tasks_all_params_with_retries(self):
# Enable retries and run test_get_active_tasks_all_params.
_service.enable_retries()
self.test_get_active_tasks_all_params()
# Disable retries and run test_get_active_tasks_all_params.
_service.disable_retries()
self.test_get_active_tasks_all_params()
class TestGetUpInformation():
"""
Test Class for get_up_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_up_information_all_params(self):
"""
get_up_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_up')
mock_response = '{"seeds": {"anyKey": "anyValue"}, "status": "maintenance_mode"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_up_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_up_information_all_params_with_retries(self):
# Enable retries and run test_get_up_information_all_params.
_service.enable_retries()
self.test_get_up_information_all_params()
# Disable retries and run test_get_up_information_all_params.
_service.disable_retries()
self.test_get_up_information_all_params()
class TestGetActivityTrackerEvents():
"""
Test Class for get_activity_tracker_events
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_activity_tracker_events_all_params(self):
"""
get_activity_tracker_events()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"types": ["management"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_activity_tracker_events()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_activity_tracker_events_all_params_with_retries(self):
# Enable retries and run test_get_activity_tracker_events_all_params.
_service.enable_retries()
self.test_get_activity_tracker_events_all_params()
# Disable retries and run test_get_activity_tracker_events_all_params.
_service.disable_retries()
self.test_get_activity_tracker_events_all_params()
class TestPostActivityTrackerEvents():
"""
Test Class for post_activity_tracker_events
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_activity_tracker_events_all_params(self):
"""
post_activity_tracker_events()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
types = ['management']
# Invoke method
response = _service.post_activity_tracker_events(
types,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['types'] == ['management']
def test_post_activity_tracker_events_all_params_with_retries(self):
# Enable retries and run test_post_activity_tracker_events_all_params.
_service.enable_retries()
self.test_post_activity_tracker_events_all_params()
# Disable retries and run test_post_activity_tracker_events_all_params.
_service.disable_retries()
self.test_post_activity_tracker_events_all_params()
@responses.activate
def test_post_activity_tracker_events_value_error(self):
"""
test_post_activity_tracker_events_value_error()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
types = ['management']
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"types": types,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_activity_tracker_events(**req_copy)
def test_post_activity_tracker_events_value_error_with_retries(self):
# Enable retries and run test_post_activity_tracker_events_value_error.
_service.enable_retries()
self.test_post_activity_tracker_events_value_error()
# Disable retries and run test_post_activity_tracker_events_value_error.
_service.disable_retries()
self.test_post_activity_tracker_events_value_error()
class TestGetCurrentThroughputInformation():
"""
Test Class for get_current_throughput_information
"""
def preprocess_url(self, request_url: str):
"""
Preprocess the request URL to ensure the mock response will be found.
"""
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_current_throughput_information_all_params(self):
"""
get_current_throughput_information()
"""
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/current/throughput')
mock_response = '{"throughput": {"query": 0, "read": 0, "write": 0}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_current_throughput_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_current_throughput_information_all_params_with_retries(self):
# Enable retries and run test_get_current_throughput_information_all_params.
_service.enable_retries()
self.test_get_current_throughput_information_all_params()
# Disable retries and run test_get_current_throughput_information_all_params.
_service.disable_retries()
self.test_get_current_throughput_information_all_params()
# endregion
##############################################################################
# End of Service: Monitoring
##############################################################################
##############################################################################
# Start of Model Tests
##############################################################################
# region
class TestModel_ActiveTask():
"""
Test Class for ActiveTask
"""
def test_active_task_serialization(self):
"""
Test serialization/deserialization for ActiveTask
"""
# Construct a json representation of a ActiveTask model
active_task_model_json = {}
active_task_model_json['changes_done'] = 0
active_task_model_json['database'] = 'testString'
active_task_model_json['node'] = 'testString'
active_task_model_json['pid'] = 'testString'
active_task_model_json['progress'] = 0
active_task_model_json['started_on'] = 0
active_task_model_json['status'] = 'testString'
active_task_model_json['task'] = 'testString'
active_task_model_json['total_changes'] = 0
active_task_model_json['type'] = 'testString'
active_task_model_json['updated_on'] = 0
# Construct a model instance of ActiveTask by calling from_dict on the json representation
active_task_model = ActiveTask.from_dict(active_task_model_json)
assert active_task_model != False
# Construct a model instance of ActiveTask by calling from_dict on the json representation
active_task_model_dict = ActiveTask.from_dict(active_task_model_json).__dict__
active_task_model2 = ActiveTask(**active_task_model_dict)
# Verify the model instances are equivalent
assert active_task_model == active_task_model2
# Convert model instance back to dict and verify no loss of data
active_task_model_json2 = active_task_model.to_dict()
assert active_task_model_json2 == active_task_model_json
class TestModel_ActivityTrackerEvents():
"""
Test Class for ActivityTrackerEvents
"""
def test_activity_tracker_events_serialization(self):
"""
Test serialization/deserialization for ActivityTrackerEvents
"""
# Construct a json representation of a ActivityTrackerEvents model
activity_tracker_events_model_json = {}
activity_tracker_events_model_json['types'] = ['management']
# Construct a model instance of ActivityTrackerEvents by calling from_dict on the json representation
activity_tracker_events_model = ActivityTrackerEvents.from_dict(activity_tracker_events_model_json)
assert activity_tracker_events_model != False
# Construct a model instance of ActivityTrackerEvents by calling from_dict on the json representation
activity_tracker_events_model_dict = ActivityTrackerEvents.from_dict(activity_tracker_events_model_json).__dict__
activity_tracker_events_model2 = ActivityTrackerEvents(**activity_tracker_events_model_dict)
# Verify the model instances are equivalent
assert activity_tracker_events_model == activity_tracker_events_model2
# Convert model instance back to dict and verify no loss of data
activity_tracker_events_model_json2 = activity_tracker_events_model.to_dict()
assert activity_tracker_events_model_json2 == activity_tracker_events_model_json
class TestModel_AllDocsQueriesResult():
"""
Test Class for AllDocsQueriesResult
"""
def test_all_docs_queries_result_serialization(self):
"""
Test serialization/deserialization for AllDocsQueriesResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
docs_result_row_model = {} # DocsResultRow
docs_result_row_model['caused_by'] = 'testString'
docs_result_row_model['error'] = 'testString'
docs_result_row_model['reason'] = 'testString'
docs_result_row_model['doc'] = document_model
docs_result_row_model['id'] = 'testString'
docs_result_row_model['key'] = 'testString'
docs_result_row_model['value'] = docs_result_row_value_model
all_docs_result_model = {} # AllDocsResult
all_docs_result_model['total_rows'] = 0
all_docs_result_model['rows'] = [docs_result_row_model]
all_docs_result_model['update_seq'] = 'testString'
# Construct a json representation of a AllDocsQueriesResult model
all_docs_queries_result_model_json = {}
all_docs_queries_result_model_json['results'] = [all_docs_result_model]
# Construct a model instance of AllDocsQueriesResult by calling from_dict on the json representation
all_docs_queries_result_model = AllDocsQueriesResult.from_dict(all_docs_queries_result_model_json)
assert all_docs_queries_result_model != False
# Construct a model instance of AllDocsQueriesResult by calling from_dict on the json representation
all_docs_queries_result_model_dict = AllDocsQueriesResult.from_dict(all_docs_queries_result_model_json).__dict__
all_docs_queries_result_model2 = AllDocsQueriesResult(**all_docs_queries_result_model_dict)
# Verify the model instances are equivalent
assert all_docs_queries_result_model == all_docs_queries_result_model2
# Convert model instance back to dict and verify no loss of data
all_docs_queries_result_model_json2 = all_docs_queries_result_model.to_dict()
assert all_docs_queries_result_model_json2 == all_docs_queries_result_model_json
class TestModel_AllDocsQuery():
"""
Test Class for AllDocsQuery
"""
def test_all_docs_query_serialization(self):
"""
Test serialization/deserialization for AllDocsQuery
"""
# Construct a json representation of a AllDocsQuery model
all_docs_query_model_json = {}
all_docs_query_model_json['att_encoding_info'] = False
all_docs_query_model_json['attachments'] = False
all_docs_query_model_json['conflicts'] = False
all_docs_query_model_json['descending'] = False
all_docs_query_model_json['include_docs'] = False
all_docs_query_model_json['inclusive_end'] = True
all_docs_query_model_json['limit'] = 0
all_docs_query_model_json['skip'] = 0
all_docs_query_model_json['update_seq'] = False
all_docs_query_model_json['endkey'] = 'testString'
all_docs_query_model_json['key'] = 'testString'
all_docs_query_model_json['keys'] = ['testString']
all_docs_query_model_json['startkey'] = 'testString'
# Construct a model instance of AllDocsQuery by calling from_dict on the json representation
all_docs_query_model = AllDocsQuery.from_dict(all_docs_query_model_json)
assert all_docs_query_model != False
# Construct a model instance of AllDocsQuery by calling from_dict on the json representation
all_docs_query_model_dict = AllDocsQuery.from_dict(all_docs_query_model_json).__dict__
all_docs_query_model2 = AllDocsQuery(**all_docs_query_model_dict)
# Verify the model instances are equivalent
assert all_docs_query_model == all_docs_query_model2
# Convert model instance back to dict and verify no loss of data
all_docs_query_model_json2 = all_docs_query_model.to_dict()
assert all_docs_query_model_json2 == all_docs_query_model_json
class TestModel_AllDocsResult():
"""
Test Class for AllDocsResult
"""
def test_all_docs_result_serialization(self):
"""
Test serialization/deserialization for AllDocsResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
docs_result_row_model = {} # DocsResultRow
docs_result_row_model['caused_by'] = 'testString'
docs_result_row_model['error'] = 'testString'
docs_result_row_model['reason'] = 'testString'
docs_result_row_model['doc'] = document_model
docs_result_row_model['id'] = 'testString'
docs_result_row_model['key'] = 'testString'
docs_result_row_model['value'] = docs_result_row_value_model
# Construct a json representation of a AllDocsResult model
all_docs_result_model_json = {}
all_docs_result_model_json['total_rows'] = 0
all_docs_result_model_json['rows'] = [docs_result_row_model]
all_docs_result_model_json['update_seq'] = 'testString'
# Construct a model instance of AllDocsResult by calling from_dict on the json representation
all_docs_result_model = AllDocsResult.from_dict(all_docs_result_model_json)
assert all_docs_result_model != False
# Construct a model instance of AllDocsResult by calling from_dict on the json representation
all_docs_result_model_dict = AllDocsResult.from_dict(all_docs_result_model_json).__dict__
all_docs_result_model2 = AllDocsResult(**all_docs_result_model_dict)
# Verify the model instances are equivalent
assert all_docs_result_model == all_docs_result_model2
# Convert model instance back to dict and verify no loss of data
all_docs_result_model_json2 = all_docs_result_model.to_dict()
assert all_docs_result_model_json2 == all_docs_result_model_json
class TestModel_Analyzer():
"""
Test Class for Analyzer
"""
def test_analyzer_serialization(self):
"""
Test serialization/deserialization for Analyzer
"""
# Construct a json representation of a Analyzer model
analyzer_model_json = {}
analyzer_model_json['name'] = 'classic'
analyzer_model_json['stopwords'] = ['testString']
# Construct a model instance of Analyzer by calling from_dict on the json representation
analyzer_model = Analyzer.from_dict(analyzer_model_json)
assert analyzer_model != False
# Construct a model instance of Analyzer by calling from_dict on the json representation
analyzer_model_dict = Analyzer.from_dict(analyzer_model_json).__dict__
analyzer_model2 = Analyzer(**analyzer_model_dict)
# Verify the model instances are equivalent
assert analyzer_model == analyzer_model2
# Convert model instance back to dict and verify no loss of data
analyzer_model_json2 = analyzer_model.to_dict()
assert analyzer_model_json2 == analyzer_model_json
class TestModel_AnalyzerConfiguration():
"""
Test Class for AnalyzerConfiguration
"""
def test_analyzer_configuration_serialization(self):
"""
Test serialization/deserialization for AnalyzerConfiguration
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a json representation of a AnalyzerConfiguration model
analyzer_configuration_model_json = {}
analyzer_configuration_model_json['name'] = 'classic'
analyzer_configuration_model_json['stopwords'] = ['testString']
analyzer_configuration_model_json['fields'] = {}
# Construct a model instance of AnalyzerConfiguration by calling from_dict on the json representation
analyzer_configuration_model = AnalyzerConfiguration.from_dict(analyzer_configuration_model_json)
assert analyzer_configuration_model != False
# Construct a model instance of AnalyzerConfiguration by calling from_dict on the json representation
analyzer_configuration_model_dict = AnalyzerConfiguration.from_dict(analyzer_configuration_model_json).__dict__
analyzer_configuration_model2 = AnalyzerConfiguration(**analyzer_configuration_model_dict)
# Verify the model instances are equivalent
assert analyzer_configuration_model == analyzer_configuration_model2
# Convert model instance back to dict and verify no loss of data
analyzer_configuration_model_json2 = analyzer_configuration_model.to_dict()
assert analyzer_configuration_model_json2 == analyzer_configuration_model_json
class TestModel_ApiKeysResult():
"""
Test Class for ApiKeysResult
"""
def test_api_keys_result_serialization(self):
"""
Test serialization/deserialization for ApiKeysResult
"""
# Construct a json representation of a ApiKeysResult model
api_keys_result_model_json = {}
api_keys_result_model_json['ok'] = True
api_keys_result_model_json['key'] = 'testString'
api_keys_result_model_json['password'] = 'testString'
# Construct a model instance of ApiKeysResult by calling from_dict on the json representation
api_keys_result_model = ApiKeysResult.from_dict(api_keys_result_model_json)
assert api_keys_result_model != False
# Construct a model instance of ApiKeysResult by calling from_dict on the json representation
api_keys_result_model_dict = ApiKeysResult.from_dict(api_keys_result_model_json).__dict__
api_keys_result_model2 = ApiKeysResult(**api_keys_result_model_dict)
# Verify the model instances are equivalent
assert api_keys_result_model == api_keys_result_model2
# Convert model instance back to dict and verify no loss of data
api_keys_result_model_json2 = api_keys_result_model.to_dict()
assert api_keys_result_model_json2 == api_keys_result_model_json
class TestModel_Attachment():
"""
Test Class for Attachment
"""
def test_attachment_serialization(self):
"""
Test serialization/deserialization for Attachment
"""
# Construct a json representation of a Attachment model
attachment_model_json = {}
attachment_model_json['content_type'] = 'testString'
attachment_model_json['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model_json['digest'] = 'testString'
attachment_model_json['encoded_length'] = 0
attachment_model_json['encoding'] = 'testString'
attachment_model_json['follows'] = True
attachment_model_json['length'] = 0
attachment_model_json['revpos'] = 1
attachment_model_json['stub'] = True
# Construct a model instance of Attachment by calling from_dict on the json representation
attachment_model = Attachment.from_dict(attachment_model_json)
assert attachment_model != False
# Construct a model instance of Attachment by calling from_dict on the json representation
attachment_model_dict = Attachment.from_dict(attachment_model_json).__dict__
attachment_model2 = Attachment(**attachment_model_dict)
# Verify the model instances are equivalent
assert attachment_model == attachment_model2
# Convert model instance back to dict and verify no loss of data
attachment_model_json2 = attachment_model.to_dict()
assert attachment_model_json2 == attachment_model_json
class TestModel_BulkDocs():
"""
Test Class for BulkDocs
"""
def test_bulk_docs_serialization(self):
"""
Test serialization/deserialization for BulkDocs
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a BulkDocs model
bulk_docs_model_json = {}
bulk_docs_model_json['docs'] = [document_model]
bulk_docs_model_json['new_edits'] = True
# Construct a model instance of BulkDocs by calling from_dict on the json representation
bulk_docs_model = BulkDocs.from_dict(bulk_docs_model_json)
assert bulk_docs_model != False
# Construct a model instance of BulkDocs by calling from_dict on the json representation
bulk_docs_model_dict = BulkDocs.from_dict(bulk_docs_model_json).__dict__
bulk_docs_model2 = BulkDocs(**bulk_docs_model_dict)
# Verify the model instances are equivalent
assert bulk_docs_model == bulk_docs_model2
# Convert model instance back to dict and verify no loss of data
bulk_docs_model_json2 = bulk_docs_model.to_dict()
assert bulk_docs_model_json2 == bulk_docs_model_json
class TestModel_BulkGetQueryDocument():
"""
Test Class for BulkGetQueryDocument
"""
def test_bulk_get_query_document_serialization(self):
"""
Test serialization/deserialization for BulkGetQueryDocument
"""
# Construct a json representation of a BulkGetQueryDocument model
bulk_get_query_document_model_json = {}
bulk_get_query_document_model_json['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model_json['id'] = 'testString'
bulk_get_query_document_model_json['rev'] = 'testString'
# Construct a model instance of BulkGetQueryDocument by calling from_dict on the json representation
bulk_get_query_document_model = BulkGetQueryDocument.from_dict(bulk_get_query_document_model_json)
assert bulk_get_query_document_model != False
# Construct a model instance of BulkGetQueryDocument by calling from_dict on the json representation
bulk_get_query_document_model_dict = BulkGetQueryDocument.from_dict(bulk_get_query_document_model_json).__dict__
bulk_get_query_document_model2 = BulkGetQueryDocument(**bulk_get_query_document_model_dict)
# Verify the model instances are equivalent
assert bulk_get_query_document_model == bulk_get_query_document_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_query_document_model_json2 = bulk_get_query_document_model.to_dict()
assert bulk_get_query_document_model_json2 == bulk_get_query_document_model_json
class TestModel_BulkGetResult():
"""
Test Class for BulkGetResult
"""
def test_bulk_get_result_serialization(self):
"""
Test serialization/deserialization for BulkGetResult
"""
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
bulk_get_result_document_model = {} # BulkGetResultDocument
bulk_get_result_document_model['error'] = document_result_model
bulk_get_result_document_model['ok'] = document_model
bulk_get_result_item_model = {} # BulkGetResultItem
bulk_get_result_item_model['docs'] = [bulk_get_result_document_model]
bulk_get_result_item_model['id'] = 'testString'
# Construct a json representation of a BulkGetResult model
bulk_get_result_model_json = {}
bulk_get_result_model_json['results'] = [bulk_get_result_item_model]
# Construct a model instance of BulkGetResult by calling from_dict on the json representation
bulk_get_result_model = BulkGetResult.from_dict(bulk_get_result_model_json)
assert bulk_get_result_model != False
# Construct a model instance of BulkGetResult by calling from_dict on the json representation
bulk_get_result_model_dict = BulkGetResult.from_dict(bulk_get_result_model_json).__dict__
bulk_get_result_model2 = BulkGetResult(**bulk_get_result_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_model == bulk_get_result_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_model_json2 = bulk_get_result_model.to_dict()
assert bulk_get_result_model_json2 == bulk_get_result_model_json
class TestModel_BulkGetResultDocument():
"""
Test Class for BulkGetResultDocument
"""
def test_bulk_get_result_document_serialization(self):
"""
Test serialization/deserialization for BulkGetResultDocument
"""
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a BulkGetResultDocument model
bulk_get_result_document_model_json = {}
bulk_get_result_document_model_json['error'] = document_result_model
bulk_get_result_document_model_json['ok'] = document_model
# Construct a model instance of BulkGetResultDocument by calling from_dict on the json representation
bulk_get_result_document_model = BulkGetResultDocument.from_dict(bulk_get_result_document_model_json)
assert bulk_get_result_document_model != False
# Construct a model instance of BulkGetResultDocument by calling from_dict on the json representation
bulk_get_result_document_model_dict = BulkGetResultDocument.from_dict(bulk_get_result_document_model_json).__dict__
bulk_get_result_document_model2 = BulkGetResultDocument(**bulk_get_result_document_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_document_model == bulk_get_result_document_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_document_model_json2 = bulk_get_result_document_model.to_dict()
assert bulk_get_result_document_model_json2 == bulk_get_result_document_model_json
class TestModel_BulkGetResultItem():
"""
Test Class for BulkGetResultItem
"""
def test_bulk_get_result_item_serialization(self):
"""
Test serialization/deserialization for BulkGetResultItem
"""
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
bulk_get_result_document_model = {} # BulkGetResultDocument
bulk_get_result_document_model['error'] = document_result_model
bulk_get_result_document_model['ok'] = document_model
# Construct a json representation of a BulkGetResultItem model
bulk_get_result_item_model_json = {}
bulk_get_result_item_model_json['docs'] = [bulk_get_result_document_model]
bulk_get_result_item_model_json['id'] = 'testString'
# Construct a model instance of BulkGetResultItem by calling from_dict on the json representation
bulk_get_result_item_model = BulkGetResultItem.from_dict(bulk_get_result_item_model_json)
assert bulk_get_result_item_model != False
# Construct a model instance of BulkGetResultItem by calling from_dict on the json representation
bulk_get_result_item_model_dict = BulkGetResultItem.from_dict(bulk_get_result_item_model_json).__dict__
bulk_get_result_item_model2 = BulkGetResultItem(**bulk_get_result_item_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_item_model == bulk_get_result_item_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_item_model_json2 = bulk_get_result_item_model.to_dict()
assert bulk_get_result_item_model_json2 == bulk_get_result_item_model_json
class TestModel_CapacityThroughputInformation():
"""
Test Class for CapacityThroughputInformation
"""
def test_capacity_throughput_information_serialization(self):
"""
Test serialization/deserialization for CapacityThroughputInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
capacity_throughput_information_current_model = {} # CapacityThroughputInformationCurrent
capacity_throughput_information_current_model['throughput'] = throughput_information_model
capacity_throughput_information_target_model = {} # CapacityThroughputInformationTarget
capacity_throughput_information_target_model['throughput'] = throughput_information_model
# Construct a json representation of a CapacityThroughputInformation model
capacity_throughput_information_model_json = {}
capacity_throughput_information_model_json['current'] = capacity_throughput_information_current_model
capacity_throughput_information_model_json['target'] = capacity_throughput_information_target_model
# Construct a model instance of CapacityThroughputInformation by calling from_dict on the json representation
capacity_throughput_information_model = CapacityThroughputInformation.from_dict(capacity_throughput_information_model_json)
assert capacity_throughput_information_model != False
# Construct a model instance of CapacityThroughputInformation by calling from_dict on the json representation
capacity_throughput_information_model_dict = CapacityThroughputInformation.from_dict(capacity_throughput_information_model_json).__dict__
capacity_throughput_information_model2 = CapacityThroughputInformation(**capacity_throughput_information_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_model == capacity_throughput_information_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_model_json2 = capacity_throughput_information_model.to_dict()
assert capacity_throughput_information_model_json2 == capacity_throughput_information_model_json
class TestModel_CapacityThroughputInformationCurrent():
"""
Test Class for CapacityThroughputInformationCurrent
"""
def test_capacity_throughput_information_current_serialization(self):
"""
Test serialization/deserialization for CapacityThroughputInformationCurrent
"""
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
# Construct a json representation of a CapacityThroughputInformationCurrent model
capacity_throughput_information_current_model_json = {}
capacity_throughput_information_current_model_json['throughput'] = throughput_information_model
# Construct a model instance of CapacityThroughputInformationCurrent by calling from_dict on the json representation
capacity_throughput_information_current_model = CapacityThroughputInformationCurrent.from_dict(capacity_throughput_information_current_model_json)
assert capacity_throughput_information_current_model != False
# Construct a model instance of CapacityThroughputInformationCurrent by calling from_dict on the json representation
capacity_throughput_information_current_model_dict = CapacityThroughputInformationCurrent.from_dict(capacity_throughput_information_current_model_json).__dict__
capacity_throughput_information_current_model2 = CapacityThroughputInformationCurrent(**capacity_throughput_information_current_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_current_model == capacity_throughput_information_current_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_current_model_json2 = capacity_throughput_information_current_model.to_dict()
assert capacity_throughput_information_current_model_json2 == capacity_throughput_information_current_model_json
class TestModel_CapacityThroughputInformationTarget():
"""
Test Class for CapacityThroughputInformationTarget
"""
def test_capacity_throughput_information_target_serialization(self):
"""
Test serialization/deserialization for CapacityThroughputInformationTarget
"""
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
# Construct a json representation of a CapacityThroughputInformationTarget model
capacity_throughput_information_target_model_json = {}
capacity_throughput_information_target_model_json['throughput'] = throughput_information_model
# Construct a model instance of CapacityThroughputInformationTarget by calling from_dict on the json representation
capacity_throughput_information_target_model = CapacityThroughputInformationTarget.from_dict(capacity_throughput_information_target_model_json)
assert capacity_throughput_information_target_model != False
# Construct a model instance of CapacityThroughputInformationTarget by calling from_dict on the json representation
capacity_throughput_information_target_model_dict = CapacityThroughputInformationTarget.from_dict(capacity_throughput_information_target_model_json).__dict__
capacity_throughput_information_target_model2 = CapacityThroughputInformationTarget(**capacity_throughput_information_target_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_target_model == capacity_throughput_information_target_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_target_model_json2 = capacity_throughput_information_target_model.to_dict()
assert capacity_throughput_information_target_model_json2 == capacity_throughput_information_target_model_json
class TestModel_Change():
"""
Test Class for Change
"""
def test_change_serialization(self):
"""
Test serialization/deserialization for Change
"""
# Construct a json representation of a Change model
change_model_json = {}
change_model_json['rev'] = 'testString'
# Construct a model instance of Change by calling from_dict on the json representation
change_model = Change.from_dict(change_model_json)
assert change_model != False
# Construct a model instance of Change by calling from_dict on the json representation
change_model_dict = Change.from_dict(change_model_json).__dict__
change_model2 = Change(**change_model_dict)
# Verify the model instances are equivalent
assert change_model == change_model2
# Convert model instance back to dict and verify no loss of data
change_model_json2 = change_model.to_dict()
assert change_model_json2 == change_model_json
class TestModel_ChangesResult():
"""
Test Class for ChangesResult
"""
def test_changes_result_serialization(self):
"""
Test serialization/deserialization for ChangesResult
"""
# Construct dict forms of any model objects needed in order to build this model.
change_model = {} # Change
change_model['rev'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
changes_result_item_model = {} # ChangesResultItem
changes_result_item_model['changes'] = [change_model]
changes_result_item_model['deleted'] = True
changes_result_item_model['doc'] = document_model
changes_result_item_model['id'] = 'testString'
changes_result_item_model['seq'] = 'testString'
# Construct a json representation of a ChangesResult model
changes_result_model_json = {}
changes_result_model_json['last_seq'] = 'testString'
changes_result_model_json['pending'] = 26
changes_result_model_json['results'] = [changes_result_item_model]
# Construct a model instance of ChangesResult by calling from_dict on the json representation
changes_result_model = ChangesResult.from_dict(changes_result_model_json)
assert changes_result_model != False
# Construct a model instance of ChangesResult by calling from_dict on the json representation
changes_result_model_dict = ChangesResult.from_dict(changes_result_model_json).__dict__
changes_result_model2 = ChangesResult(**changes_result_model_dict)
# Verify the model instances are equivalent
assert changes_result_model == changes_result_model2
# Convert model instance back to dict and verify no loss of data
changes_result_model_json2 = changes_result_model.to_dict()
assert changes_result_model_json2 == changes_result_model_json
class TestModel_ChangesResultItem():
"""
Test Class for ChangesResultItem
"""
def test_changes_result_item_serialization(self):
"""
Test serialization/deserialization for ChangesResultItem
"""
# Construct dict forms of any model objects needed in order to build this model.
change_model = {} # Change
change_model['rev'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a ChangesResultItem model
changes_result_item_model_json = {}
changes_result_item_model_json['changes'] = [change_model]
changes_result_item_model_json['deleted'] = True
changes_result_item_model_json['doc'] = document_model
changes_result_item_model_json['id'] = 'testString'
changes_result_item_model_json['seq'] = 'testString'
# Construct a model instance of ChangesResultItem by calling from_dict on the json representation
changes_result_item_model = ChangesResultItem.from_dict(changes_result_item_model_json)
assert changes_result_item_model != False
# Construct a model instance of ChangesResultItem by calling from_dict on the json representation
changes_result_item_model_dict = ChangesResultItem.from_dict(changes_result_item_model_json).__dict__
changes_result_item_model2 = ChangesResultItem(**changes_result_item_model_dict)
# Verify the model instances are equivalent
assert changes_result_item_model == changes_result_item_model2
# Convert model instance back to dict and verify no loss of data
changes_result_item_model_json2 = changes_result_item_model.to_dict()
assert changes_result_item_model_json2 == changes_result_item_model_json
class TestModel_ContentInformationSizes():
"""
Test Class for ContentInformationSizes
"""
def test_content_information_sizes_serialization(self):
"""
Test serialization/deserialization for ContentInformationSizes
"""
# Construct a json representation of a ContentInformationSizes model
content_information_sizes_model_json = {}
content_information_sizes_model_json['active'] = 26
content_information_sizes_model_json['external'] = 26
content_information_sizes_model_json['file'] = 26
# Construct a model instance of ContentInformationSizes by calling from_dict on the json representation
content_information_sizes_model = ContentInformationSizes.from_dict(content_information_sizes_model_json)
assert content_information_sizes_model != False
# Construct a model instance of ContentInformationSizes by calling from_dict on the json representation
content_information_sizes_model_dict = ContentInformationSizes.from_dict(content_information_sizes_model_json).__dict__
content_information_sizes_model2 = ContentInformationSizes(**content_information_sizes_model_dict)
# Verify the model instances are equivalent
assert content_information_sizes_model == content_information_sizes_model2
# Convert model instance back to dict and verify no loss of data
content_information_sizes_model_json2 = content_information_sizes_model.to_dict()
assert content_information_sizes_model_json2 == content_information_sizes_model_json
class TestModel_CorsInformation():
"""
Test Class for CorsInformation
"""
def test_cors_information_serialization(self):
"""
Test serialization/deserialization for CorsInformation
"""
# Construct a json representation of a CorsInformation model
cors_information_model_json = {}
cors_information_model_json['allow_credentials'] = True
cors_information_model_json['enable_cors'] = True
cors_information_model_json['origins'] = ['testString']
# Construct a model instance of CorsInformation by calling from_dict on the json representation
cors_information_model = CorsInformation.from_dict(cors_information_model_json)
assert cors_information_model != False
# Construct a model instance of CorsInformation by calling from_dict on the json representation
cors_information_model_dict = CorsInformation.from_dict(cors_information_model_json).__dict__
cors_information_model2 = CorsInformation(**cors_information_model_dict)
# Verify the model instances are equivalent
assert cors_information_model == cors_information_model2
# Convert model instance back to dict and verify no loss of data
cors_information_model_json2 = cors_information_model.to_dict()
assert cors_information_model_json2 == cors_information_model_json
class TestModel_CurrentThroughputInformation():
"""
Test Class for CurrentThroughputInformation
"""
def test_current_throughput_information_serialization(self):
"""
Test serialization/deserialization for CurrentThroughputInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
current_throughput_information_throughput_model = {} # CurrentThroughputInformationThroughput
current_throughput_information_throughput_model['query'] = 0
current_throughput_information_throughput_model['read'] = 0
current_throughput_information_throughput_model['write'] = 0
# Construct a json representation of a CurrentThroughputInformation model
current_throughput_information_model_json = {}
current_throughput_information_model_json['throughput'] = current_throughput_information_throughput_model
# Construct a model instance of CurrentThroughputInformation by calling from_dict on the json representation
current_throughput_information_model = CurrentThroughputInformation.from_dict(current_throughput_information_model_json)
assert current_throughput_information_model != False
# Construct a model instance of CurrentThroughputInformation by calling from_dict on the json representation
current_throughput_information_model_dict = CurrentThroughputInformation.from_dict(current_throughput_information_model_json).__dict__
current_throughput_information_model2 = CurrentThroughputInformation(**current_throughput_information_model_dict)
# Verify the model instances are equivalent
assert current_throughput_information_model == current_throughput_information_model2
# Convert model instance back to dict and verify no loss of data
current_throughput_information_model_json2 = current_throughput_information_model.to_dict()
assert current_throughput_information_model_json2 == current_throughput_information_model_json
class TestModel_CurrentThroughputInformationThroughput():
"""
Test Class for CurrentThroughputInformationThroughput
"""
def test_current_throughput_information_throughput_serialization(self):
"""
Test serialization/deserialization for CurrentThroughputInformationThroughput
"""
# Construct a json representation of a CurrentThroughputInformationThroughput model
current_throughput_information_throughput_model_json = {}
current_throughput_information_throughput_model_json['query'] = 0
current_throughput_information_throughput_model_json['read'] = 0
current_throughput_information_throughput_model_json['write'] = 0
# Construct a model instance of CurrentThroughputInformationThroughput by calling from_dict on the json representation
current_throughput_information_throughput_model = CurrentThroughputInformationThroughput.from_dict(current_throughput_information_throughput_model_json)
assert current_throughput_information_throughput_model != False
# Construct a model instance of CurrentThroughputInformationThroughput by calling from_dict on the json representation
current_throughput_information_throughput_model_dict = CurrentThroughputInformationThroughput.from_dict(current_throughput_information_throughput_model_json).__dict__
current_throughput_information_throughput_model2 = CurrentThroughputInformationThroughput(**current_throughput_information_throughput_model_dict)
# Verify the model instances are equivalent
assert current_throughput_information_throughput_model == current_throughput_information_throughput_model2
# Convert model instance back to dict and verify no loss of data
current_throughput_information_throughput_model_json2 = current_throughput_information_throughput_model.to_dict()
assert current_throughput_information_throughput_model_json2 == current_throughput_information_throughput_model_json
class TestModel_DatabaseInformation():
"""
Test Class for DatabaseInformation
"""
def test_database_information_serialization(self):
"""
Test serialization/deserialization for DatabaseInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
database_information_cluster_model = {} # DatabaseInformationCluster
database_information_cluster_model['n'] = 1
database_information_cluster_model['q'] = 1
database_information_cluster_model['r'] = 1
database_information_cluster_model['w'] = 1
database_information_props_model = {} # DatabaseInformationProps
database_information_props_model['partitioned'] = True
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
# Construct a json representation of a DatabaseInformation model
database_information_model_json = {}
database_information_model_json['cluster'] = database_information_cluster_model
database_information_model_json['committed_update_seq'] = 'testString'
database_information_model_json['compact_running'] = True
database_information_model_json['compacted_seq'] = 'testString'
database_information_model_json['db_name'] = 'testString'
database_information_model_json['disk_format_version'] = 26
database_information_model_json['doc_count'] = 0
database_information_model_json['doc_del_count'] = 0
database_information_model_json['engine'] = 'testString'
database_information_model_json['props'] = database_information_props_model
database_information_model_json['sizes'] = content_information_sizes_model
database_information_model_json['update_seq'] = 'testString'
database_information_model_json['uuid'] = 'testString'
# Construct a model instance of DatabaseInformation by calling from_dict on the json representation
database_information_model = DatabaseInformation.from_dict(database_information_model_json)
assert database_information_model != False
# Construct a model instance of DatabaseInformation by calling from_dict on the json representation
database_information_model_dict = DatabaseInformation.from_dict(database_information_model_json).__dict__
database_information_model2 = DatabaseInformation(**database_information_model_dict)
# Verify the model instances are equivalent
assert database_information_model == database_information_model2
# Convert model instance back to dict and verify no loss of data
database_information_model_json2 = database_information_model.to_dict()
assert database_information_model_json2 == database_information_model_json
class TestModel_DatabaseInformationCluster():
"""
Test Class for DatabaseInformationCluster
"""
def test_database_information_cluster_serialization(self):
"""
Test serialization/deserialization for DatabaseInformationCluster
"""
# Construct a json representation of a DatabaseInformationCluster model
database_information_cluster_model_json = {}
database_information_cluster_model_json['n'] = 1
database_information_cluster_model_json['q'] = 1
database_information_cluster_model_json['r'] = 1
database_information_cluster_model_json['w'] = 1
# Construct a model instance of DatabaseInformationCluster by calling from_dict on the json representation
database_information_cluster_model = DatabaseInformationCluster.from_dict(database_information_cluster_model_json)
assert database_information_cluster_model != False
# Construct a model instance of DatabaseInformationCluster by calling from_dict on the json representation
database_information_cluster_model_dict = DatabaseInformationCluster.from_dict(database_information_cluster_model_json).__dict__
database_information_cluster_model2 = DatabaseInformationCluster(**database_information_cluster_model_dict)
# Verify the model instances are equivalent
assert database_information_cluster_model == database_information_cluster_model2
# Convert model instance back to dict and verify no loss of data
database_information_cluster_model_json2 = database_information_cluster_model.to_dict()
assert database_information_cluster_model_json2 == database_information_cluster_model_json
class TestModel_DatabaseInformationProps():
"""
Test Class for DatabaseInformationProps
"""
def test_database_information_props_serialization(self):
"""
Test serialization/deserialization for DatabaseInformationProps
"""
# Construct a json representation of a DatabaseInformationProps model
database_information_props_model_json = {}
database_information_props_model_json['partitioned'] = True
# Construct a model instance of DatabaseInformationProps by calling from_dict on the json representation
database_information_props_model = DatabaseInformationProps.from_dict(database_information_props_model_json)
assert database_information_props_model != False
# Construct a model instance of DatabaseInformationProps by calling from_dict on the json representation
database_information_props_model_dict = DatabaseInformationProps.from_dict(database_information_props_model_json).__dict__
database_information_props_model2 = DatabaseInformationProps(**database_information_props_model_dict)
# Verify the model instances are equivalent
assert database_information_props_model == database_information_props_model2
# Convert model instance back to dict and verify no loss of data
database_information_props_model_json2 = database_information_props_model.to_dict()
assert database_information_props_model_json2 == database_information_props_model_json
class TestModel_DbEvent():
"""
Test Class for DbEvent
"""
def test_db_event_serialization(self):
"""
Test serialization/deserialization for DbEvent
"""
# Construct a json representation of a DbEvent model
db_event_model_json = {}
db_event_model_json['account'] = 'testString'
db_event_model_json['db_name'] = 'testString'
db_event_model_json['seq'] = 'testString'
db_event_model_json['type'] = 'created'
# Construct a model instance of DbEvent by calling from_dict on the json representation
db_event_model = DbEvent.from_dict(db_event_model_json)
assert db_event_model != False
# Construct a model instance of DbEvent by calling from_dict on the json representation
db_event_model_dict = DbEvent.from_dict(db_event_model_json).__dict__
db_event_model2 = DbEvent(**db_event_model_dict)
# Verify the model instances are equivalent
assert db_event_model == db_event_model2
# Convert model instance back to dict and verify no loss of data
db_event_model_json2 = db_event_model.to_dict()
assert db_event_model_json2 == db_event_model_json
class TestModel_DbUpdates():
"""
Test Class for DbUpdates
"""
def test_db_updates_serialization(self):
"""
Test serialization/deserialization for DbUpdates
"""
# Construct dict forms of any model objects needed in order to build this model.
db_event_model = {} # DbEvent
db_event_model['account'] = 'testString'
db_event_model['db_name'] = 'testString'
db_event_model['seq'] = 'testString'
db_event_model['type'] = 'created'
# Construct a json representation of a DbUpdates model
db_updates_model_json = {}
db_updates_model_json['last_seq'] = 'testString'
db_updates_model_json['results'] = [db_event_model]
# Construct a model instance of DbUpdates by calling from_dict on the json representation
db_updates_model = DbUpdates.from_dict(db_updates_model_json)
assert db_updates_model != False
# Construct a model instance of DbUpdates by calling from_dict on the json representation
db_updates_model_dict = DbUpdates.from_dict(db_updates_model_json).__dict__
db_updates_model2 = DbUpdates(**db_updates_model_dict)
# Verify the model instances are equivalent
assert db_updates_model == db_updates_model2
# Convert model instance back to dict and verify no loss of data
db_updates_model_json2 = db_updates_model.to_dict()
assert db_updates_model_json2 == db_updates_model_json
class TestModel_DbsInfoResult():
"""
Test Class for DbsInfoResult
"""
def test_dbs_info_result_serialization(self):
"""
Test serialization/deserialization for DbsInfoResult
"""
# Construct dict forms of any model objects needed in order to build this model.
database_information_cluster_model = {} # DatabaseInformationCluster
database_information_cluster_model['n'] = 1
database_information_cluster_model['q'] = 1
database_information_cluster_model['r'] = 1
database_information_cluster_model['w'] = 1
database_information_props_model = {} # DatabaseInformationProps
database_information_props_model['partitioned'] = True
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
database_information_model = {} # DatabaseInformation
database_information_model['cluster'] = database_information_cluster_model
database_information_model['committed_update_seq'] = 'testString'
database_information_model['compact_running'] = True
database_information_model['compacted_seq'] = 'testString'
database_information_model['db_name'] = 'testString'
database_information_model['disk_format_version'] = 26
database_information_model['doc_count'] = 0
database_information_model['doc_del_count'] = 0
database_information_model['engine'] = 'testString'
database_information_model['props'] = database_information_props_model
database_information_model['sizes'] = content_information_sizes_model
database_information_model['update_seq'] = 'testString'
database_information_model['uuid'] = 'testString'
# Construct a json representation of a DbsInfoResult model
dbs_info_result_model_json = {}
dbs_info_result_model_json['error'] = 'testString'
dbs_info_result_model_json['info'] = database_information_model
dbs_info_result_model_json['key'] = 'testString'
# Construct a model instance of DbsInfoResult by calling from_dict on the json representation
dbs_info_result_model = DbsInfoResult.from_dict(dbs_info_result_model_json)
assert dbs_info_result_model != False
# Construct a model instance of DbsInfoResult by calling from_dict on the json representation
dbs_info_result_model_dict = DbsInfoResult.from_dict(dbs_info_result_model_json).__dict__
dbs_info_result_model2 = DbsInfoResult(**dbs_info_result_model_dict)
# Verify the model instances are equivalent
assert dbs_info_result_model == dbs_info_result_model2
# Convert model instance back to dict and verify no loss of data
dbs_info_result_model_json2 = dbs_info_result_model.to_dict()
assert dbs_info_result_model_json2 == dbs_info_result_model_json
class TestModel_DesignDocument():
"""
Test Class for DesignDocument
"""
def test_design_document_serialization(self):
"""
Test serialization/deserialization for DesignDocument
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
analyzer_configuration_model = {} # AnalyzerConfiguration
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
search_index_definition_model = {} # SearchIndexDefinition
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
design_document_options_model = {} # DesignDocumentOptions
design_document_options_model['partitioned'] = True
design_document_views_map_reduce_model = {} # DesignDocumentViewsMapReduce
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
geo_index_definition_model = {} # GeoIndexDefinition
geo_index_definition_model['index'] = 'testString'
# Construct a json representation of a DesignDocument model
design_document_model_json = {}
design_document_model_json['_attachments'] = {}
design_document_model_json['_conflicts'] = ['testString']
design_document_model_json['_deleted'] = True
design_document_model_json['_deleted_conflicts'] = ['testString']
design_document_model_json['_id'] = 'testString'
design_document_model_json['_local_seq'] = 'testString'
design_document_model_json['_rev'] = 'testString'
design_document_model_json['_revisions'] = revisions_model
design_document_model_json['_revs_info'] = [document_revision_status_model]
design_document_model_json['autoupdate'] = True
design_document_model_json['filters'] = {}
design_document_model_json['indexes'] = {}
design_document_model_json['language'] = 'javascript'
design_document_model_json['options'] = design_document_options_model
design_document_model_json['validate_doc_update'] = 'testString'
design_document_model_json['views'] = {}
design_document_model_json['st_indexes'] = {}
design_document_model_json['foo'] = 'testString'
# Construct a model instance of DesignDocument by calling from_dict on the json representation
design_document_model = DesignDocument.from_dict(design_document_model_json)
assert design_document_model != False
# Construct a model instance of DesignDocument by calling from_dict on the json representation
design_document_model_dict = DesignDocument.from_dict(design_document_model_json).__dict__
design_document_model2 = DesignDocument(**design_document_model_dict)
# Verify the model instances are equivalent
assert design_document_model == design_document_model2
# Convert model instance back to dict and verify no loss of data
design_document_model_json2 = design_document_model.to_dict()
assert design_document_model_json2 == design_document_model_json
# Test get_properties and set_properties methods.
design_document_model.set_properties({})
actual_dict = design_document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
design_document_model.set_properties(expected_dict)
actual_dict = design_document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_DesignDocumentInformation():
"""
Test Class for DesignDocumentInformation
"""
def test_design_document_information_serialization(self):
"""
Test serialization/deserialization for DesignDocumentInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
design_document_view_index_model = {} # DesignDocumentViewIndex
design_document_view_index_model['compact_running'] = True
design_document_view_index_model['language'] = 'testString'
design_document_view_index_model['signature'] = 'testString'
design_document_view_index_model['sizes'] = content_information_sizes_model
design_document_view_index_model['updater_running'] = True
design_document_view_index_model['waiting_clients'] = 0
design_document_view_index_model['waiting_commit'] = True
# Construct a json representation of a DesignDocumentInformation model
design_document_information_model_json = {}
design_document_information_model_json['name'] = 'testString'
design_document_information_model_json['view_index'] = design_document_view_index_model
# Construct a model instance of DesignDocumentInformation by calling from_dict on the json representation
design_document_information_model = DesignDocumentInformation.from_dict(design_document_information_model_json)
assert design_document_information_model != False
# Construct a model instance of DesignDocumentInformation by calling from_dict on the json representation
design_document_information_model_dict = DesignDocumentInformation.from_dict(design_document_information_model_json).__dict__
design_document_information_model2 = DesignDocumentInformation(**design_document_information_model_dict)
# Verify the model instances are equivalent
assert design_document_information_model == design_document_information_model2
# Convert model instance back to dict and verify no loss of data
design_document_information_model_json2 = design_document_information_model.to_dict()
assert design_document_information_model_json2 == design_document_information_model_json
class TestModel_DesignDocumentOptions():
"""
Test Class for DesignDocumentOptions
"""
def test_design_document_options_serialization(self):
"""
Test serialization/deserialization for DesignDocumentOptions
"""
# Construct a json representation of a DesignDocumentOptions model
design_document_options_model_json = {}
design_document_options_model_json['partitioned'] = True
# Construct a model instance of DesignDocumentOptions by calling from_dict on the json representation
design_document_options_model = DesignDocumentOptions.from_dict(design_document_options_model_json)
assert design_document_options_model != False
# Construct a model instance of DesignDocumentOptions by calling from_dict on the json representation
design_document_options_model_dict = DesignDocumentOptions.from_dict(design_document_options_model_json).__dict__
design_document_options_model2 = DesignDocumentOptions(**design_document_options_model_dict)
# Verify the model instances are equivalent
assert design_document_options_model == design_document_options_model2
# Convert model instance back to dict and verify no loss of data
design_document_options_model_json2 = design_document_options_model.to_dict()
assert design_document_options_model_json2 == design_document_options_model_json
class TestModel_DesignDocumentViewIndex():
"""
Test Class for DesignDocumentViewIndex
"""
def test_design_document_view_index_serialization(self):
"""
Test serialization/deserialization for DesignDocumentViewIndex
"""
# Construct dict forms of any model objects needed in order to build this model.
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
# Construct a json representation of a DesignDocumentViewIndex model
design_document_view_index_model_json = {}
design_document_view_index_model_json['compact_running'] = True
design_document_view_index_model_json['language'] = 'testString'
design_document_view_index_model_json['signature'] = 'testString'
design_document_view_index_model_json['sizes'] = content_information_sizes_model
design_document_view_index_model_json['updater_running'] = True
design_document_view_index_model_json['waiting_clients'] = 0
design_document_view_index_model_json['waiting_commit'] = True
# Construct a model instance of DesignDocumentViewIndex by calling from_dict on the json representation
design_document_view_index_model = DesignDocumentViewIndex.from_dict(design_document_view_index_model_json)
assert design_document_view_index_model != False
# Construct a model instance of DesignDocumentViewIndex by calling from_dict on the json representation
design_document_view_index_model_dict = DesignDocumentViewIndex.from_dict(design_document_view_index_model_json).__dict__
design_document_view_index_model2 = DesignDocumentViewIndex(**design_document_view_index_model_dict)
# Verify the model instances are equivalent
assert design_document_view_index_model == design_document_view_index_model2
# Convert model instance back to dict and verify no loss of data
design_document_view_index_model_json2 = design_document_view_index_model.to_dict()
assert design_document_view_index_model_json2 == design_document_view_index_model_json
class TestModel_DesignDocumentViewsMapReduce():
"""
Test Class for DesignDocumentViewsMapReduce
"""
def test_design_document_views_map_reduce_serialization(self):
"""
Test serialization/deserialization for DesignDocumentViewsMapReduce
"""
# Construct a json representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model_json = {}
design_document_views_map_reduce_model_json['map'] = 'testString'
design_document_views_map_reduce_model_json['reduce'] = 'testString'
# Construct a model instance of DesignDocumentViewsMapReduce by calling from_dict on the json representation
design_document_views_map_reduce_model = DesignDocumentViewsMapReduce.from_dict(design_document_views_map_reduce_model_json)
assert design_document_views_map_reduce_model != False
# Construct a model instance of DesignDocumentViewsMapReduce by calling from_dict on the json representation
design_document_views_map_reduce_model_dict = DesignDocumentViewsMapReduce.from_dict(design_document_views_map_reduce_model_json).__dict__
design_document_views_map_reduce_model2 = DesignDocumentViewsMapReduce(**design_document_views_map_reduce_model_dict)
# Verify the model instances are equivalent
assert design_document_views_map_reduce_model == design_document_views_map_reduce_model2
# Convert model instance back to dict and verify no loss of data
design_document_views_map_reduce_model_json2 = design_document_views_map_reduce_model.to_dict()
assert design_document_views_map_reduce_model_json2 == design_document_views_map_reduce_model_json
class TestModel_DocsResultRow():
"""
Test Class for DocsResultRow
"""
def test_docs_result_row_serialization(self):
"""
Test serialization/deserialization for DocsResultRow
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
# Construct a json representation of a DocsResultRow model
docs_result_row_model_json = {}
docs_result_row_model_json['caused_by'] = 'testString'
docs_result_row_model_json['error'] = 'testString'
docs_result_row_model_json['reason'] = 'testString'
docs_result_row_model_json['doc'] = document_model
docs_result_row_model_json['id'] = 'testString'
docs_result_row_model_json['key'] = 'testString'
docs_result_row_model_json['value'] = docs_result_row_value_model
# Construct a model instance of DocsResultRow by calling from_dict on the json representation
docs_result_row_model = DocsResultRow.from_dict(docs_result_row_model_json)
assert docs_result_row_model != False
# Construct a model instance of DocsResultRow by calling from_dict on the json representation
docs_result_row_model_dict = DocsResultRow.from_dict(docs_result_row_model_json).__dict__
docs_result_row_model2 = DocsResultRow(**docs_result_row_model_dict)
# Verify the model instances are equivalent
assert docs_result_row_model == docs_result_row_model2
# Convert model instance back to dict and verify no loss of data
docs_result_row_model_json2 = docs_result_row_model.to_dict()
assert docs_result_row_model_json2 == docs_result_row_model_json
class TestModel_DocsResultRowValue():
"""
Test Class for DocsResultRowValue
"""
def test_docs_result_row_value_serialization(self):
"""
Test serialization/deserialization for DocsResultRowValue
"""
# Construct a json representation of a DocsResultRowValue model
docs_result_row_value_model_json = {}
docs_result_row_value_model_json['rev'] = 'testString'
# Construct a model instance of DocsResultRowValue by calling from_dict on the json representation
docs_result_row_value_model = DocsResultRowValue.from_dict(docs_result_row_value_model_json)
assert docs_result_row_value_model != False
# Construct a model instance of DocsResultRowValue by calling from_dict on the json representation
docs_result_row_value_model_dict = DocsResultRowValue.from_dict(docs_result_row_value_model_json).__dict__
docs_result_row_value_model2 = DocsResultRowValue(**docs_result_row_value_model_dict)
# Verify the model instances are equivalent
assert docs_result_row_value_model == docs_result_row_value_model2
# Convert model instance back to dict and verify no loss of data
docs_result_row_value_model_json2 = docs_result_row_value_model.to_dict()
assert docs_result_row_value_model_json2 == docs_result_row_value_model_json
class TestModel_Document():
"""
Test Class for Document
"""
def test_document_serialization(self):
"""
Test serialization/deserialization for Document
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a json representation of a Document model
document_model_json = {}
document_model_json['_attachments'] = {}
document_model_json['_conflicts'] = ['testString']
document_model_json['_deleted'] = True
document_model_json['_deleted_conflicts'] = ['testString']
document_model_json['_id'] = 'testString'
document_model_json['_local_seq'] = 'testString'
document_model_json['_rev'] = 'testString'
document_model_json['_revisions'] = revisions_model
document_model_json['_revs_info'] = [document_revision_status_model]
document_model_json['foo'] = 'testString'
# Construct a model instance of Document by calling from_dict on the json representation
document_model = Document.from_dict(document_model_json)
assert document_model != False
# Construct a model instance of Document by calling from_dict on the json representation
document_model_dict = Document.from_dict(document_model_json).__dict__
document_model2 = Document(**document_model_dict)
# Verify the model instances are equivalent
assert document_model == document_model2
# Convert model instance back to dict and verify no loss of data
document_model_json2 = document_model.to_dict()
assert document_model_json2 == document_model_json
# Test get_properties and set_properties methods.
document_model.set_properties({})
actual_dict = document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
document_model.set_properties(expected_dict)
actual_dict = document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_DocumentResult():
"""
Test Class for DocumentResult
"""
def test_document_result_serialization(self):
"""
Test serialization/deserialization for DocumentResult
"""
# Construct a json representation of a DocumentResult model
document_result_model_json = {}
document_result_model_json['id'] = 'testString'
document_result_model_json['rev'] = 'testString'
document_result_model_json['ok'] = True
document_result_model_json['caused_by'] = 'testString'
document_result_model_json['error'] = 'testString'
document_result_model_json['reason'] = 'testString'
# Construct a model instance of DocumentResult by calling from_dict on the json representation
document_result_model = DocumentResult.from_dict(document_result_model_json)
assert document_result_model != False
# Construct a model instance of DocumentResult by calling from_dict on the json representation
document_result_model_dict = DocumentResult.from_dict(document_result_model_json).__dict__
document_result_model2 = DocumentResult(**document_result_model_dict)
# Verify the model instances are equivalent
assert document_result_model == document_result_model2
# Convert model instance back to dict and verify no loss of data
document_result_model_json2 = document_result_model.to_dict()
assert document_result_model_json2 == document_result_model_json
class TestModel_DocumentRevisionStatus():
"""
Test Class for DocumentRevisionStatus
"""
def test_document_revision_status_serialization(self):
"""
Test serialization/deserialization for DocumentRevisionStatus
"""
# Construct a json representation of a DocumentRevisionStatus model
document_revision_status_model_json = {}
document_revision_status_model_json['rev'] = 'testString'
document_revision_status_model_json['status'] = 'available'
# Construct a model instance of DocumentRevisionStatus by calling from_dict on the json representation
document_revision_status_model = DocumentRevisionStatus.from_dict(document_revision_status_model_json)
assert document_revision_status_model != False
# Construct a model instance of DocumentRevisionStatus by calling from_dict on the json representation
document_revision_status_model_dict = DocumentRevisionStatus.from_dict(document_revision_status_model_json).__dict__
document_revision_status_model2 = DocumentRevisionStatus(**document_revision_status_model_dict)
# Verify the model instances are equivalent
assert document_revision_status_model == document_revision_status_model2
# Convert model instance back to dict and verify no loss of data
document_revision_status_model_json2 = document_revision_status_model.to_dict()
assert document_revision_status_model_json2 == document_revision_status_model_json
class TestModel_DocumentShardInfo():
"""
Test Class for DocumentShardInfo
"""
def test_document_shard_info_serialization(self):
"""
Test serialization/deserialization for DocumentShardInfo
"""
# Construct a json representation of a DocumentShardInfo model
document_shard_info_model_json = {}
document_shard_info_model_json['nodes'] = ['testString']
document_shard_info_model_json['range'] = 'testString'
# Construct a model instance of DocumentShardInfo by calling from_dict on the json representation
document_shard_info_model = DocumentShardInfo.from_dict(document_shard_info_model_json)
assert document_shard_info_model != False
# Construct a model instance of DocumentShardInfo by calling from_dict on the json representation
document_shard_info_model_dict = DocumentShardInfo.from_dict(document_shard_info_model_json).__dict__
document_shard_info_model2 = DocumentShardInfo(**document_shard_info_model_dict)
# Verify the model instances are equivalent
assert document_shard_info_model == document_shard_info_model2
# Convert model instance back to dict and verify no loss of data
document_shard_info_model_json2 = document_shard_info_model.to_dict()
assert document_shard_info_model_json2 == document_shard_info_model_json
class TestModel_ExecutionStats():
"""
Test Class for ExecutionStats
"""
def test_execution_stats_serialization(self):
"""
Test serialization/deserialization for ExecutionStats
"""
# Construct a json representation of a ExecutionStats model
execution_stats_model_json = {}
execution_stats_model_json['execution_time_ms'] = 72.5
execution_stats_model_json['results_returned'] = 0
execution_stats_model_json['total_docs_examined'] = 0
execution_stats_model_json['total_keys_examined'] = 0
execution_stats_model_json['total_quorum_docs_examined'] = 0
# Construct a model instance of ExecutionStats by calling from_dict on the json representation
execution_stats_model = ExecutionStats.from_dict(execution_stats_model_json)
assert execution_stats_model != False
# Construct a model instance of ExecutionStats by calling from_dict on the json representation
execution_stats_model_dict = ExecutionStats.from_dict(execution_stats_model_json).__dict__
execution_stats_model2 = ExecutionStats(**execution_stats_model_dict)
# Verify the model instances are equivalent
assert execution_stats_model == execution_stats_model2
# Convert model instance back to dict and verify no loss of data
execution_stats_model_json2 = execution_stats_model.to_dict()
assert execution_stats_model_json2 == execution_stats_model_json
class TestModel_ExplainResult():
"""
Test Class for ExplainResult
"""
def test_explain_result_serialization(self):
"""
Test serialization/deserialization for ExplainResult
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
index_information_model = {} # IndexInformation
index_information_model['ddoc'] = 'testString'
index_information_model['def'] = index_definition_model
index_information_model['name'] = 'testString'
index_information_model['type'] = 'json'
explain_result_range_model = {} # ExplainResultRange
explain_result_range_model['end_key'] = ['testString']
explain_result_range_model['start_key'] = ['testString']
# Construct a json representation of a ExplainResult model
explain_result_model_json = {}
explain_result_model_json['dbname'] = 'testString'
explain_result_model_json['fields'] = ['testString']
explain_result_model_json['index'] = index_information_model
explain_result_model_json['limit'] = 0
explain_result_model_json['opts'] = {}
explain_result_model_json['range'] = explain_result_range_model
explain_result_model_json['selector'] = {}
explain_result_model_json['skip'] = 0
# Construct a model instance of ExplainResult by calling from_dict on the json representation
explain_result_model = ExplainResult.from_dict(explain_result_model_json)
assert explain_result_model != False
# Construct a model instance of ExplainResult by calling from_dict on the json representation
explain_result_model_dict = ExplainResult.from_dict(explain_result_model_json).__dict__
explain_result_model2 = ExplainResult(**explain_result_model_dict)
# Verify the model instances are equivalent
assert explain_result_model == explain_result_model2
# Convert model instance back to dict and verify no loss of data
explain_result_model_json2 = explain_result_model.to_dict()
assert explain_result_model_json2 == explain_result_model_json
class TestModel_ExplainResultRange():
"""
Test Class for ExplainResultRange
"""
def test_explain_result_range_serialization(self):
"""
Test serialization/deserialization for ExplainResultRange
"""
# Construct a json representation of a ExplainResultRange model
explain_result_range_model_json = {}
explain_result_range_model_json['end_key'] = ['testString']
explain_result_range_model_json['start_key'] = ['testString']
# Construct a model instance of ExplainResultRange by calling from_dict on the json representation
explain_result_range_model = ExplainResultRange.from_dict(explain_result_range_model_json)
assert explain_result_range_model != False
# Construct a model instance of ExplainResultRange by calling from_dict on the json representation
explain_result_range_model_dict = ExplainResultRange.from_dict(explain_result_range_model_json).__dict__
explain_result_range_model2 = ExplainResultRange(**explain_result_range_model_dict)
# Verify the model instances are equivalent
assert explain_result_range_model == explain_result_range_model2
# Convert model instance back to dict and verify no loss of data
explain_result_range_model_json2 = explain_result_range_model.to_dict()
assert explain_result_range_model_json2 == explain_result_range_model_json
class TestModel_FindResult():
"""
Test Class for FindResult
"""
def test_find_result_serialization(self):
"""
Test serialization/deserialization for FindResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
execution_stats_model = {} # ExecutionStats
execution_stats_model['execution_time_ms'] = 72.5
execution_stats_model['results_returned'] = 0
execution_stats_model['total_docs_examined'] = 0
execution_stats_model['total_keys_examined'] = 0
execution_stats_model['total_quorum_docs_examined'] = 0
# Construct a json representation of a FindResult model
find_result_model_json = {}
find_result_model_json['bookmark'] = 'testString'
find_result_model_json['docs'] = [document_model]
find_result_model_json['execution_stats'] = execution_stats_model
find_result_model_json['warning'] = 'testString'
# Construct a model instance of FindResult by calling from_dict on the json representation
find_result_model = FindResult.from_dict(find_result_model_json)
assert find_result_model != False
# Construct a model instance of FindResult by calling from_dict on the json representation
find_result_model_dict = FindResult.from_dict(find_result_model_json).__dict__
find_result_model2 = FindResult(**find_result_model_dict)
# Verify the model instances are equivalent
assert find_result_model == find_result_model2
# Convert model instance back to dict and verify no loss of data
find_result_model_json2 = find_result_model.to_dict()
assert find_result_model_json2 == find_result_model_json
class TestModel_GeoIndexDefinition():
"""
Test Class for GeoIndexDefinition
"""
def test_geo_index_definition_serialization(self):
"""
Test serialization/deserialization for GeoIndexDefinition
"""
# Construct a json representation of a GeoIndexDefinition model
geo_index_definition_model_json = {}
geo_index_definition_model_json['index'] = 'testString'
# Construct a model instance of GeoIndexDefinition by calling from_dict on the json representation
geo_index_definition_model = GeoIndexDefinition.from_dict(geo_index_definition_model_json)
assert geo_index_definition_model != False
# Construct a model instance of GeoIndexDefinition by calling from_dict on the json representation
geo_index_definition_model_dict = GeoIndexDefinition.from_dict(geo_index_definition_model_json).__dict__
geo_index_definition_model2 = GeoIndexDefinition(**geo_index_definition_model_dict)
# Verify the model instances are equivalent
assert geo_index_definition_model == geo_index_definition_model2
# Convert model instance back to dict and verify no loss of data
geo_index_definition_model_json2 = geo_index_definition_model.to_dict()
assert geo_index_definition_model_json2 == geo_index_definition_model_json
class TestModel_GeoIndexInformation():
"""
Test Class for GeoIndexInformation
"""
def test_geo_index_information_serialization(self):
"""
Test serialization/deserialization for GeoIndexInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
geo_index_stats_model = {} # GeoIndexStats
geo_index_stats_model['data_size'] = 0
geo_index_stats_model['disk_size'] = 0
geo_index_stats_model['doc_count'] = 0
# Construct a json representation of a GeoIndexInformation model
geo_index_information_model_json = {}
geo_index_information_model_json['geo_index'] = geo_index_stats_model
geo_index_information_model_json['name'] = 'testString'
# Construct a model instance of GeoIndexInformation by calling from_dict on the json representation
geo_index_information_model = GeoIndexInformation.from_dict(geo_index_information_model_json)
assert geo_index_information_model != False
# Construct a model instance of GeoIndexInformation by calling from_dict on the json representation
geo_index_information_model_dict = GeoIndexInformation.from_dict(geo_index_information_model_json).__dict__
geo_index_information_model2 = GeoIndexInformation(**geo_index_information_model_dict)
# Verify the model instances are equivalent
assert geo_index_information_model == geo_index_information_model2
# Convert model instance back to dict and verify no loss of data
geo_index_information_model_json2 = geo_index_information_model.to_dict()
assert geo_index_information_model_json2 == geo_index_information_model_json
class TestModel_GeoIndexStats():
"""
Test Class for GeoIndexStats
"""
def test_geo_index_stats_serialization(self):
"""
Test serialization/deserialization for GeoIndexStats
"""
# Construct a json representation of a GeoIndexStats model
geo_index_stats_model_json = {}
geo_index_stats_model_json['data_size'] = 0
geo_index_stats_model_json['disk_size'] = 0
geo_index_stats_model_json['doc_count'] = 0
# Construct a model instance of GeoIndexStats by calling from_dict on the json representation
geo_index_stats_model = GeoIndexStats.from_dict(geo_index_stats_model_json)
assert geo_index_stats_model != False
# Construct a model instance of GeoIndexStats by calling from_dict on the json representation
geo_index_stats_model_dict = GeoIndexStats.from_dict(geo_index_stats_model_json).__dict__
geo_index_stats_model2 = GeoIndexStats(**geo_index_stats_model_dict)
# Verify the model instances are equivalent
assert geo_index_stats_model == geo_index_stats_model2
# Convert model instance back to dict and verify no loss of data
geo_index_stats_model_json2 = geo_index_stats_model.to_dict()
assert geo_index_stats_model_json2 == geo_index_stats_model_json
class TestModel_GeoJsonFeature():
"""
Test Class for GeoJsonFeature
"""
def test_geo_json_feature_serialization(self):
"""
Test serialization/deserialization for GeoJsonFeature
"""
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_object_model = {} # GeoJsonGeometry
geo_json_geometry_object_model['type'] = 'Point'
geo_json_geometry_object_model['coordinates'] = ['testString']
# Construct a json representation of a GeoJsonFeature model
geo_json_feature_model_json = {}
geo_json_feature_model_json['_id'] = 'testString'
geo_json_feature_model_json['_rev'] = 'testString'
geo_json_feature_model_json['bbox'] = [72.5]
geo_json_feature_model_json['geometry'] = geo_json_geometry_object_model
geo_json_feature_model_json['properties'] = {}
geo_json_feature_model_json['type'] = 'Feature'
geo_json_feature_model_json['foo'] = 'testString'
# Construct a model instance of GeoJsonFeature by calling from_dict on the json representation
geo_json_feature_model = GeoJsonFeature.from_dict(geo_json_feature_model_json)
assert geo_json_feature_model != False
# Construct a model instance of GeoJsonFeature by calling from_dict on the json representation
geo_json_feature_model_dict = GeoJsonFeature.from_dict(geo_json_feature_model_json).__dict__
geo_json_feature_model2 = GeoJsonFeature(**geo_json_feature_model_dict)
# Verify the model instances are equivalent
assert geo_json_feature_model == geo_json_feature_model2
# Convert model instance back to dict and verify no loss of data
geo_json_feature_model_json2 = geo_json_feature_model.to_dict()
assert geo_json_feature_model_json2 == geo_json_feature_model_json
# Test get_properties and set_properties methods.
geo_json_feature_model.set_properties({})
actual_dict = geo_json_feature_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
geo_json_feature_model.set_properties(expected_dict)
actual_dict = geo_json_feature_model.get_properties()
assert actual_dict == expected_dict
class TestModel_GeoResult():
"""
Test Class for GeoResult
"""
def test_geo_result_serialization(self):
"""
Test serialization/deserialization for GeoResult
"""
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_object_model = {} # GeoJsonGeometry
geo_json_geometry_object_model['type'] = 'Point'
geo_json_geometry_object_model['coordinates'] = ['testString']
geo_json_feature_model = {} # GeoJsonFeature
geo_json_feature_model['_id'] = 'testString'
geo_json_feature_model['_rev'] = 'testString'
geo_json_feature_model['bbox'] = [72.5]
geo_json_feature_model['geometry'] = geo_json_geometry_object_model
geo_json_feature_model['properties'] = {}
geo_json_feature_model['type'] = 'Feature'
geo_json_feature_model['foo'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
geo_result_row_model = {} # GeoResultRow
geo_result_row_model['doc'] = document_model
geo_result_row_model['geometry'] = geo_json_geometry_model
geo_result_row_model['id'] = 'testString'
geo_result_row_model['rev'] = 'testString'
# Construct a json representation of a GeoResult model
geo_result_model_json = {}
geo_result_model_json['bookmark'] = 'testString'
geo_result_model_json['features'] = [geo_json_feature_model]
geo_result_model_json['rows'] = [geo_result_row_model]
geo_result_model_json['type'] = 'FeatureCollection'
# Construct a model instance of GeoResult by calling from_dict on the json representation
geo_result_model = GeoResult.from_dict(geo_result_model_json)
assert geo_result_model != False
# Construct a model instance of GeoResult by calling from_dict on the json representation
geo_result_model_dict = GeoResult.from_dict(geo_result_model_json).__dict__
geo_result_model2 = GeoResult(**geo_result_model_dict)
# Verify the model instances are equivalent
assert geo_result_model == geo_result_model2
# Convert model instance back to dict and verify no loss of data
geo_result_model_json2 = geo_result_model.to_dict()
assert geo_result_model_json2 == geo_result_model_json
class TestModel_GeoResultRow():
"""
Test Class for GeoResultRow
"""
def test_geo_result_row_serialization(self):
"""
Test serialization/deserialization for GeoResultRow
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
# Construct a json representation of a GeoResultRow model
geo_result_row_model_json = {}
geo_result_row_model_json['doc'] = document_model
geo_result_row_model_json['geometry'] = geo_json_geometry_model
geo_result_row_model_json['id'] = 'testString'
geo_result_row_model_json['rev'] = 'testString'
# Construct a model instance of GeoResultRow by calling from_dict on the json representation
geo_result_row_model = GeoResultRow.from_dict(geo_result_row_model_json)
assert geo_result_row_model != False
# Construct a model instance of GeoResultRow by calling from_dict on the json representation
geo_result_row_model_dict = GeoResultRow.from_dict(geo_result_row_model_json).__dict__
geo_result_row_model2 = GeoResultRow(**geo_result_row_model_dict)
# Verify the model instances are equivalent
assert geo_result_row_model == geo_result_row_model2
# Convert model instance back to dict and verify no loss of data
geo_result_row_model_json2 = geo_result_row_model.to_dict()
assert geo_result_row_model_json2 == geo_result_row_model_json
class TestModel_IndexDefinition():
"""
Test Class for IndexDefinition
"""
def test_index_definition_serialization(self):
"""
Test serialization/deserialization for IndexDefinition
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
# Construct a json representation of a IndexDefinition model
index_definition_model_json = {}
index_definition_model_json['default_analyzer'] = analyzer_model
index_definition_model_json['default_field'] = index_text_operator_default_field_model
index_definition_model_json['fields'] = [index_field_model]
index_definition_model_json['index_array_lengths'] = True
index_definition_model_json['partial_filter_selector'] = {}
# Construct a model instance of IndexDefinition by calling from_dict on the json representation
index_definition_model = IndexDefinition.from_dict(index_definition_model_json)
assert index_definition_model != False
# Construct a model instance of IndexDefinition by calling from_dict on the json representation
index_definition_model_dict = IndexDefinition.from_dict(index_definition_model_json).__dict__
index_definition_model2 = IndexDefinition(**index_definition_model_dict)
# Verify the model instances are equivalent
assert index_definition_model == index_definition_model2
# Convert model instance back to dict and verify no loss of data
index_definition_model_json2 = index_definition_model.to_dict()
assert index_definition_model_json2 == index_definition_model_json
class TestModel_IndexField():
"""
Test Class for IndexField
"""
def test_index_field_serialization(self):
"""
Test serialization/deserialization for IndexField
"""
# Construct a json representation of a IndexField model
index_field_model_json = {}
index_field_model_json['name'] = 'testString'
index_field_model_json['type'] = 'boolean'
index_field_model_json['foo'] = 'asc'
# Construct a model instance of IndexField by calling from_dict on the json representation
index_field_model = IndexField.from_dict(index_field_model_json)
assert index_field_model != False
# Construct a model instance of IndexField by calling from_dict on the json representation
index_field_model_dict = IndexField.from_dict(index_field_model_json).__dict__
index_field_model2 = IndexField(**index_field_model_dict)
# Verify the model instances are equivalent
assert index_field_model == index_field_model2
# Convert model instance back to dict and verify no loss of data
index_field_model_json2 = index_field_model.to_dict()
assert index_field_model_json2 == index_field_model_json
# Test get_properties and set_properties methods.
index_field_model.set_properties({})
actual_dict = index_field_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'asc'}
index_field_model.set_properties(expected_dict)
actual_dict = index_field_model.get_properties()
assert actual_dict == expected_dict
class TestModel_IndexInformation():
"""
Test Class for IndexInformation
"""
def test_index_information_serialization(self):
"""
Test serialization/deserialization for IndexInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
# Construct a json representation of a IndexInformation model
index_information_model_json = {}
index_information_model_json['ddoc'] = 'testString'
index_information_model_json['def'] = index_definition_model
index_information_model_json['name'] = 'testString'
index_information_model_json['type'] = 'json'
# Construct a model instance of IndexInformation by calling from_dict on the json representation
index_information_model = IndexInformation.from_dict(index_information_model_json)
assert index_information_model != False
# Construct a model instance of IndexInformation by calling from_dict on the json representation
index_information_model_dict = IndexInformation.from_dict(index_information_model_json).__dict__
index_information_model2 = IndexInformation(**index_information_model_dict)
# Verify the model instances are equivalent
assert index_information_model == index_information_model2
# Convert model instance back to dict and verify no loss of data
index_information_model_json2 = index_information_model.to_dict()
assert index_information_model_json2 == index_information_model_json
class TestModel_IndexResult():
"""
Test Class for IndexResult
"""
def test_index_result_serialization(self):
"""
Test serialization/deserialization for IndexResult
"""
# Construct a json representation of a IndexResult model
index_result_model_json = {}
index_result_model_json['id'] = 'testString'
index_result_model_json['name'] = 'testString'
index_result_model_json['result'] = 'created'
# Construct a model instance of IndexResult by calling from_dict on the json representation
index_result_model = IndexResult.from_dict(index_result_model_json)
assert index_result_model != False
# Construct a model instance of IndexResult by calling from_dict on the json representation
index_result_model_dict = IndexResult.from_dict(index_result_model_json).__dict__
index_result_model2 = IndexResult(**index_result_model_dict)
# Verify the model instances are equivalent
assert index_result_model == index_result_model2
# Convert model instance back to dict and verify no loss of data
index_result_model_json2 = index_result_model.to_dict()
assert index_result_model_json2 == index_result_model_json
class TestModel_IndexTextOperatorDefaultField():
"""
Test Class for IndexTextOperatorDefaultField
"""
def test_index_text_operator_default_field_serialization(self):
"""
Test serialization/deserialization for IndexTextOperatorDefaultField
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a json representation of a IndexTextOperatorDefaultField model
index_text_operator_default_field_model_json = {}
index_text_operator_default_field_model_json['analyzer'] = analyzer_model
index_text_operator_default_field_model_json['enabled'] = True
# Construct a model instance of IndexTextOperatorDefaultField by calling from_dict on the json representation
index_text_operator_default_field_model = IndexTextOperatorDefaultField.from_dict(index_text_operator_default_field_model_json)
assert index_text_operator_default_field_model != False
# Construct a model instance of IndexTextOperatorDefaultField by calling from_dict on the json representation
index_text_operator_default_field_model_dict = IndexTextOperatorDefaultField.from_dict(index_text_operator_default_field_model_json).__dict__
index_text_operator_default_field_model2 = IndexTextOperatorDefaultField(**index_text_operator_default_field_model_dict)
# Verify the model instances are equivalent
assert index_text_operator_default_field_model == index_text_operator_default_field_model2
# Convert model instance back to dict and verify no loss of data
index_text_operator_default_field_model_json2 = index_text_operator_default_field_model.to_dict()
assert index_text_operator_default_field_model_json2 == index_text_operator_default_field_model_json
class TestModel_IndexesInformation():
"""
Test Class for IndexesInformation
"""
def test_indexes_information_serialization(self):
"""
Test serialization/deserialization for IndexesInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
index_information_model = {} # IndexInformation
index_information_model['ddoc'] = 'testString'
index_information_model['def'] = index_definition_model
index_information_model['name'] = 'testString'
index_information_model['type'] = 'json'
# Construct a json representation of a IndexesInformation model
indexes_information_model_json = {}
indexes_information_model_json['total_rows'] = 0
indexes_information_model_json['indexes'] = [index_information_model]
# Construct a model instance of IndexesInformation by calling from_dict on the json representation
indexes_information_model = IndexesInformation.from_dict(indexes_information_model_json)
assert indexes_information_model != False
# Construct a model instance of IndexesInformation by calling from_dict on the json representation
indexes_information_model_dict = IndexesInformation.from_dict(indexes_information_model_json).__dict__
indexes_information_model2 = IndexesInformation(**indexes_information_model_dict)
# Verify the model instances are equivalent
assert indexes_information_model == indexes_information_model2
# Convert model instance back to dict and verify no loss of data
indexes_information_model_json2 = indexes_information_model.to_dict()
assert indexes_information_model_json2 == indexes_information_model_json
class TestModel_MembershipInformation():
"""
Test Class for MembershipInformation
"""
def test_membership_information_serialization(self):
"""
Test serialization/deserialization for MembershipInformation
"""
# Construct a json representation of a MembershipInformation model
membership_information_model_json = {}
membership_information_model_json['all_nodes'] = ['testString']
membership_information_model_json['cluster_nodes'] = ['testString']
# Construct a model instance of MembershipInformation by calling from_dict on the json representation
membership_information_model = MembershipInformation.from_dict(membership_information_model_json)
assert membership_information_model != False
# Construct a model instance of MembershipInformation by calling from_dict on the json representation
membership_information_model_dict = MembershipInformation.from_dict(membership_information_model_json).__dict__
membership_information_model2 = MembershipInformation(**membership_information_model_dict)
# Verify the model instances are equivalent
assert membership_information_model == membership_information_model2
# Convert model instance back to dict and verify no loss of data
membership_information_model_json2 = membership_information_model.to_dict()
assert membership_information_model_json2 == membership_information_model_json
class TestModel_Ok():
"""
Test Class for Ok
"""
def test_ok_serialization(self):
"""
Test serialization/deserialization for Ok
"""
# Construct a json representation of a Ok model
ok_model_json = {}
ok_model_json['ok'] = True
# Construct a model instance of Ok by calling from_dict on the json representation
ok_model = Ok.from_dict(ok_model_json)
assert ok_model != False
# Construct a model instance of Ok by calling from_dict on the json representation
ok_model_dict = Ok.from_dict(ok_model_json).__dict__
ok_model2 = Ok(**ok_model_dict)
# Verify the model instances are equivalent
assert ok_model == ok_model2
# Convert model instance back to dict and verify no loss of data
ok_model_json2 = ok_model.to_dict()
assert ok_model_json2 == ok_model_json
class TestModel_PartitionInformation():
"""
Test Class for PartitionInformation
"""
def test_partition_information_serialization(self):
"""
Test serialization/deserialization for PartitionInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
partition_information_indexes_indexes_model = {} # PartitionInformationIndexesIndexes
partition_information_indexes_indexes_model['search'] = 0
partition_information_indexes_indexes_model['view'] = 0
partition_information_indexes_model = {} # PartitionInformationIndexes
partition_information_indexes_model['count'] = 0
partition_information_indexes_model['indexes'] = partition_information_indexes_indexes_model
partition_information_indexes_model['limit'] = 0
partition_information_sizes_model = {} # PartitionInformationSizes
partition_information_sizes_model['active'] = 0
partition_information_sizes_model['external'] = 0
# Construct a json representation of a PartitionInformation model
partition_information_model_json = {}
partition_information_model_json['db_name'] = 'testString'
partition_information_model_json['doc_count'] = 0
partition_information_model_json['doc_del_count'] = 0
partition_information_model_json['partition'] = 'testString'
partition_information_model_json['partitioned_indexes'] = partition_information_indexes_model
partition_information_model_json['sizes'] = partition_information_sizes_model
# Construct a model instance of PartitionInformation by calling from_dict on the json representation
partition_information_model = PartitionInformation.from_dict(partition_information_model_json)
assert partition_information_model != False
# Construct a model instance of PartitionInformation by calling from_dict on the json representation
partition_information_model_dict = PartitionInformation.from_dict(partition_information_model_json).__dict__
partition_information_model2 = PartitionInformation(**partition_information_model_dict)
# Verify the model instances are equivalent
assert partition_information_model == partition_information_model2
# Convert model instance back to dict and verify no loss of data
partition_information_model_json2 = partition_information_model.to_dict()
assert partition_information_model_json2 == partition_information_model_json
class TestModel_PartitionInformationIndexes():
"""
Test Class for PartitionInformationIndexes
"""
def test_partition_information_indexes_serialization(self):
"""
Test serialization/deserialization for PartitionInformationIndexes
"""
# Construct dict forms of any model objects needed in order to build this model.
partition_information_indexes_indexes_model = {} # PartitionInformationIndexesIndexes
partition_information_indexes_indexes_model['search'] = 0
partition_information_indexes_indexes_model['view'] = 0
# Construct a json representation of a PartitionInformationIndexes model
partition_information_indexes_model_json = {}
partition_information_indexes_model_json['count'] = 0
partition_information_indexes_model_json['indexes'] = partition_information_indexes_indexes_model
partition_information_indexes_model_json['limit'] = 0
# Construct a model instance of PartitionInformationIndexes by calling from_dict on the json representation
partition_information_indexes_model = PartitionInformationIndexes.from_dict(partition_information_indexes_model_json)
assert partition_information_indexes_model != False
# Construct a model instance of PartitionInformationIndexes by calling from_dict on the json representation
partition_information_indexes_model_dict = PartitionInformationIndexes.from_dict(partition_information_indexes_model_json).__dict__
partition_information_indexes_model2 = PartitionInformationIndexes(**partition_information_indexes_model_dict)
# Verify the model instances are equivalent
assert partition_information_indexes_model == partition_information_indexes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_indexes_model_json2 = partition_information_indexes_model.to_dict()
assert partition_information_indexes_model_json2 == partition_information_indexes_model_json
class TestModel_PartitionInformationIndexesIndexes():
"""
Test Class for PartitionInformationIndexesIndexes
"""
def test_partition_information_indexes_indexes_serialization(self):
"""
Test serialization/deserialization for PartitionInformationIndexesIndexes
"""
# Construct a json representation of a PartitionInformationIndexesIndexes model
partition_information_indexes_indexes_model_json = {}
partition_information_indexes_indexes_model_json['search'] = 0
partition_information_indexes_indexes_model_json['view'] = 0
# Construct a model instance of PartitionInformationIndexesIndexes by calling from_dict on the json representation
partition_information_indexes_indexes_model = PartitionInformationIndexesIndexes.from_dict(partition_information_indexes_indexes_model_json)
assert partition_information_indexes_indexes_model != False
# Construct a model instance of PartitionInformationIndexesIndexes by calling from_dict on the json representation
partition_information_indexes_indexes_model_dict = PartitionInformationIndexesIndexes.from_dict(partition_information_indexes_indexes_model_json).__dict__
partition_information_indexes_indexes_model2 = PartitionInformationIndexesIndexes(**partition_information_indexes_indexes_model_dict)
# Verify the model instances are equivalent
assert partition_information_indexes_indexes_model == partition_information_indexes_indexes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_indexes_indexes_model_json2 = partition_information_indexes_indexes_model.to_dict()
assert partition_information_indexes_indexes_model_json2 == partition_information_indexes_indexes_model_json
class TestModel_PartitionInformationSizes():
"""
Test Class for PartitionInformationSizes
"""
def test_partition_information_sizes_serialization(self):
"""
Test serialization/deserialization for PartitionInformationSizes
"""
# Construct a json representation of a PartitionInformationSizes model
partition_information_sizes_model_json = {}
partition_information_sizes_model_json['active'] = 0
partition_information_sizes_model_json['external'] = 0
# Construct a model instance of PartitionInformationSizes by calling from_dict on the json representation
partition_information_sizes_model = PartitionInformationSizes.from_dict(partition_information_sizes_model_json)
assert partition_information_sizes_model != False
# Construct a model instance of PartitionInformationSizes by calling from_dict on the json representation
partition_information_sizes_model_dict = PartitionInformationSizes.from_dict(partition_information_sizes_model_json).__dict__
partition_information_sizes_model2 = PartitionInformationSizes(**partition_information_sizes_model_dict)
# Verify the model instances are equivalent
assert partition_information_sizes_model == partition_information_sizes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_sizes_model_json2 = partition_information_sizes_model.to_dict()
assert partition_information_sizes_model_json2 == partition_information_sizes_model_json
class TestModel_ReplicationCreateTargetParameters():
"""
Test Class for ReplicationCreateTargetParameters
"""
def test_replication_create_target_parameters_serialization(self):
"""
Test serialization/deserialization for ReplicationCreateTargetParameters
"""
# Construct a json representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model_json = {}
replication_create_target_parameters_model_json['n'] = 1
replication_create_target_parameters_model_json['partitioned'] = False
replication_create_target_parameters_model_json['q'] = 1
# Construct a model instance of ReplicationCreateTargetParameters by calling from_dict on the json representation
replication_create_target_parameters_model = ReplicationCreateTargetParameters.from_dict(replication_create_target_parameters_model_json)
assert replication_create_target_parameters_model != False
# Construct a model instance of ReplicationCreateTargetParameters by calling from_dict on the json representation
replication_create_target_parameters_model_dict = ReplicationCreateTargetParameters.from_dict(replication_create_target_parameters_model_json).__dict__
replication_create_target_parameters_model2 = ReplicationCreateTargetParameters(**replication_create_target_parameters_model_dict)
# Verify the model instances are equivalent
assert replication_create_target_parameters_model == replication_create_target_parameters_model2
# Convert model instance back to dict and verify no loss of data
replication_create_target_parameters_model_json2 = replication_create_target_parameters_model.to_dict()
assert replication_create_target_parameters_model_json2 == replication_create_target_parameters_model_json
class TestModel_ReplicationDatabase():
"""
Test Class for ReplicationDatabase
"""
def test_replication_database_serialization(self):
"""
Test serialization/deserialization for ReplicationDatabase
"""
# Construct dict forms of any model objects needed in order to build this model.
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
replication_database_auth_model = {} # ReplicationDatabaseAuth
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a json representation of a ReplicationDatabase model
replication_database_model_json = {}
replication_database_model_json['auth'] = replication_database_auth_model
replication_database_model_json['headers'] = {}
replication_database_model_json['url'] = 'testString'
# Construct a model instance of ReplicationDatabase by calling from_dict on the json representation
replication_database_model = ReplicationDatabase.from_dict(replication_database_model_json)
assert replication_database_model != False
# Construct a model instance of ReplicationDatabase by calling from_dict on the json representation
replication_database_model_dict = ReplicationDatabase.from_dict(replication_database_model_json).__dict__
replication_database_model2 = ReplicationDatabase(**replication_database_model_dict)
# Verify the model instances are equivalent
assert replication_database_model == replication_database_model2
# Convert model instance back to dict and verify no loss of data
replication_database_model_json2 = replication_database_model.to_dict()
assert replication_database_model_json2 == replication_database_model_json
class TestModel_ReplicationDatabaseAuth():
"""
Test Class for ReplicationDatabaseAuth
"""
def test_replication_database_auth_serialization(self):
"""
Test serialization/deserialization for ReplicationDatabaseAuth
"""
# Construct dict forms of any model objects needed in order to build this model.
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a json representation of a ReplicationDatabaseAuth model
replication_database_auth_model_json = {}
replication_database_auth_model_json['basic'] = replication_database_auth_basic_model
replication_database_auth_model_json['iam'] = replication_database_auth_iam_model
# Construct a model instance of ReplicationDatabaseAuth by calling from_dict on the json representation
replication_database_auth_model = ReplicationDatabaseAuth.from_dict(replication_database_auth_model_json)
assert replication_database_auth_model != False
# Construct a model instance of ReplicationDatabaseAuth by calling from_dict on the json representation
replication_database_auth_model_dict = ReplicationDatabaseAuth.from_dict(replication_database_auth_model_json).__dict__
replication_database_auth_model2 = ReplicationDatabaseAuth(**replication_database_auth_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_model == replication_database_auth_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_model_json2 = replication_database_auth_model.to_dict()
assert replication_database_auth_model_json2 == replication_database_auth_model_json
class TestModel_ReplicationDatabaseAuthBasic():
"""
Test Class for ReplicationDatabaseAuthBasic
"""
def test_replication_database_auth_basic_serialization(self):
"""
Test serialization/deserialization for ReplicationDatabaseAuthBasic
"""
# Construct a json representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model_json = {}
replication_database_auth_basic_model_json['password'] = 'testString'
replication_database_auth_basic_model_json['username'] = 'testString'
# Construct a model instance of ReplicationDatabaseAuthBasic by calling from_dict on the json representation
replication_database_auth_basic_model = ReplicationDatabaseAuthBasic.from_dict(replication_database_auth_basic_model_json)
assert replication_database_auth_basic_model != False
# Construct a model instance of ReplicationDatabaseAuthBasic by calling from_dict on the json representation
replication_database_auth_basic_model_dict = ReplicationDatabaseAuthBasic.from_dict(replication_database_auth_basic_model_json).__dict__
replication_database_auth_basic_model2 = ReplicationDatabaseAuthBasic(**replication_database_auth_basic_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_basic_model == replication_database_auth_basic_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_basic_model_json2 = replication_database_auth_basic_model.to_dict()
assert replication_database_auth_basic_model_json2 == replication_database_auth_basic_model_json
class TestModel_ReplicationDatabaseAuthIam():
"""
Test Class for ReplicationDatabaseAuthIam
"""
def test_replication_database_auth_iam_serialization(self):
"""
Test serialization/deserialization for ReplicationDatabaseAuthIam
"""
# Construct a json representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model_json = {}
replication_database_auth_iam_model_json['api_key'] = 'testString'
# Construct a model instance of ReplicationDatabaseAuthIam by calling from_dict on the json representation
replication_database_auth_iam_model = ReplicationDatabaseAuthIam.from_dict(replication_database_auth_iam_model_json)
assert replication_database_auth_iam_model != False
# Construct a model instance of ReplicationDatabaseAuthIam by calling from_dict on the json representation
replication_database_auth_iam_model_dict = ReplicationDatabaseAuthIam.from_dict(replication_database_auth_iam_model_json).__dict__
replication_database_auth_iam_model2 = ReplicationDatabaseAuthIam(**replication_database_auth_iam_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_iam_model == replication_database_auth_iam_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_iam_model_json2 = replication_database_auth_iam_model.to_dict()
assert replication_database_auth_iam_model_json2 == replication_database_auth_iam_model_json
class TestModel_ReplicationDocument():
"""
Test Class for ReplicationDocument
"""
def test_replication_document_serialization(self):
"""
Test serialization/deserialization for ReplicationDocument
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
replication_create_target_parameters_model = {} # ReplicationCreateTargetParameters
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
replication_database_auth_model = {} # ReplicationDatabaseAuth
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
replication_database_model = {} # ReplicationDatabase
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
user_context_model = {} # UserContext
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a json representation of a ReplicationDocument model
replication_document_model_json = {}
replication_document_model_json['_attachments'] = {}
replication_document_model_json['_conflicts'] = ['testString']
replication_document_model_json['_deleted'] = True
replication_document_model_json['_deleted_conflicts'] = ['testString']
replication_document_model_json['_id'] = 'testString'
replication_document_model_json['_local_seq'] = 'testString'
replication_document_model_json['_rev'] = 'testString'
replication_document_model_json['_revisions'] = revisions_model
replication_document_model_json['_revs_info'] = [document_revision_status_model]
replication_document_model_json['cancel'] = True
replication_document_model_json['checkpoint_interval'] = 0
replication_document_model_json['connection_timeout'] = 0
replication_document_model_json['continuous'] = False
replication_document_model_json['create_target'] = False
replication_document_model_json['create_target_params'] = replication_create_target_parameters_model
replication_document_model_json['doc_ids'] = ['testString']
replication_document_model_json['filter'] = 'testString'
replication_document_model_json['http_connections'] = 1
replication_document_model_json['query_params'] = {}
replication_document_model_json['retries_per_request'] = 0
replication_document_model_json['selector'] = {}
replication_document_model_json['since_seq'] = 'testString'
replication_document_model_json['socket_options'] = 'testString'
replication_document_model_json['source'] = replication_database_model
replication_document_model_json['source_proxy'] = 'testString'
replication_document_model_json['target'] = replication_database_model
replication_document_model_json['target_proxy'] = 'testString'
replication_document_model_json['use_checkpoints'] = True
replication_document_model_json['user_ctx'] = user_context_model
replication_document_model_json['worker_batch_size'] = 1
replication_document_model_json['worker_processes'] = 1
replication_document_model_json['foo'] = 'testString'
# Construct a model instance of ReplicationDocument by calling from_dict on the json representation
replication_document_model = ReplicationDocument.from_dict(replication_document_model_json)
assert replication_document_model != False
# Construct a model instance of ReplicationDocument by calling from_dict on the json representation
replication_document_model_dict = ReplicationDocument.from_dict(replication_document_model_json).__dict__
replication_document_model2 = ReplicationDocument(**replication_document_model_dict)
# Verify the model instances are equivalent
assert replication_document_model == replication_document_model2
# Convert model instance back to dict and verify no loss of data
replication_document_model_json2 = replication_document_model.to_dict()
assert replication_document_model_json2 == replication_document_model_json
# Test get_properties and set_properties methods.
replication_document_model.set_properties({})
actual_dict = replication_document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
replication_document_model.set_properties(expected_dict)
actual_dict = replication_document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_Revisions():
"""
Test Class for Revisions
"""
def test_revisions_serialization(self):
"""
Test serialization/deserialization for Revisions
"""
# Construct a json representation of a Revisions model
revisions_model_json = {}
revisions_model_json['ids'] = ['testString']
revisions_model_json['start'] = 1
# Construct a model instance of Revisions by calling from_dict on the json representation
revisions_model = Revisions.from_dict(revisions_model_json)
assert revisions_model != False
# Construct a model instance of Revisions by calling from_dict on the json representation
revisions_model_dict = Revisions.from_dict(revisions_model_json).__dict__
revisions_model2 = Revisions(**revisions_model_dict)
# Verify the model instances are equivalent
assert revisions_model == revisions_model2
# Convert model instance back to dict and verify no loss of data
revisions_model_json2 = revisions_model.to_dict()
assert revisions_model_json2 == revisions_model_json
class TestModel_RevsDiff():
"""
Test Class for RevsDiff
"""
def test_revs_diff_serialization(self):
"""
Test serialization/deserialization for RevsDiff
"""
# Construct a json representation of a RevsDiff model
revs_diff_model_json = {}
revs_diff_model_json['missing'] = ['testString']
revs_diff_model_json['possible_ancestors'] = ['testString']
# Construct a model instance of RevsDiff by calling from_dict on the json representation
revs_diff_model = RevsDiff.from_dict(revs_diff_model_json)
assert revs_diff_model != False
# Construct a model instance of RevsDiff by calling from_dict on the json representation
revs_diff_model_dict = RevsDiff.from_dict(revs_diff_model_json).__dict__
revs_diff_model2 = RevsDiff(**revs_diff_model_dict)
# Verify the model instances are equivalent
assert revs_diff_model == revs_diff_model2
# Convert model instance back to dict and verify no loss of data
revs_diff_model_json2 = revs_diff_model.to_dict()
assert revs_diff_model_json2 == revs_diff_model_json
class TestModel_SchedulerDocsResult():
"""
Test Class for SchedulerDocsResult
"""
def test_scheduler_docs_result_serialization(self):
"""
Test serialization/deserialization for SchedulerDocsResult
"""
# Construct dict forms of any model objects needed in order to build this model.
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
scheduler_document_model = {} # SchedulerDocument
scheduler_document_model['database'] = 'testString'
scheduler_document_model['doc_id'] = 'testString'
scheduler_document_model['error_count'] = 0
scheduler_document_model['id'] = 'testString'
scheduler_document_model['info'] = scheduler_info_model
scheduler_document_model['last_updated'] = "2019-01-01T12:00:00Z"
scheduler_document_model['node'] = 'testString'
scheduler_document_model['source'] = 'testString'
scheduler_document_model['source_proxy'] = 'testString'
scheduler_document_model['start_time'] = "2019-01-01T12:00:00Z"
scheduler_document_model['state'] = 'initializing'
scheduler_document_model['target'] = 'testString'
scheduler_document_model['target_proxy'] = 'testString'
# Construct a json representation of a SchedulerDocsResult model
scheduler_docs_result_model_json = {}
scheduler_docs_result_model_json['total_rows'] = 0
scheduler_docs_result_model_json['docs'] = [scheduler_document_model]
# Construct a model instance of SchedulerDocsResult by calling from_dict on the json representation
scheduler_docs_result_model = SchedulerDocsResult.from_dict(scheduler_docs_result_model_json)
assert scheduler_docs_result_model != False
# Construct a model instance of SchedulerDocsResult by calling from_dict on the json representation
scheduler_docs_result_model_dict = SchedulerDocsResult.from_dict(scheduler_docs_result_model_json).__dict__
scheduler_docs_result_model2 = SchedulerDocsResult(**scheduler_docs_result_model_dict)
# Verify the model instances are equivalent
assert scheduler_docs_result_model == scheduler_docs_result_model2
# Convert model instance back to dict and verify no loss of data
scheduler_docs_result_model_json2 = scheduler_docs_result_model.to_dict()
assert scheduler_docs_result_model_json2 == scheduler_docs_result_model_json
class TestModel_SchedulerDocument():
"""
Test Class for SchedulerDocument
"""
def test_scheduler_document_serialization(self):
"""
Test serialization/deserialization for SchedulerDocument
"""
# Construct dict forms of any model objects needed in order to build this model.
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
# Construct a json representation of a SchedulerDocument model
scheduler_document_model_json = {}
scheduler_document_model_json['database'] = 'testString'
scheduler_document_model_json['doc_id'] = 'testString'
scheduler_document_model_json['error_count'] = 0
scheduler_document_model_json['id'] = 'testString'
scheduler_document_model_json['info'] = scheduler_info_model
scheduler_document_model_json['last_updated'] = "2019-01-01T12:00:00Z"
scheduler_document_model_json['node'] = 'testString'
scheduler_document_model_json['source'] = 'testString'
scheduler_document_model_json['source_proxy'] = 'testString'
scheduler_document_model_json['start_time'] = "2019-01-01T12:00:00Z"
scheduler_document_model_json['state'] = 'initializing'
scheduler_document_model_json['target'] = 'testString'
scheduler_document_model_json['target_proxy'] = 'testString'
# Construct a model instance of SchedulerDocument by calling from_dict on the json representation
scheduler_document_model = SchedulerDocument.from_dict(scheduler_document_model_json)
assert scheduler_document_model != False
# Construct a model instance of SchedulerDocument by calling from_dict on the json representation
scheduler_document_model_dict = SchedulerDocument.from_dict(scheduler_document_model_json).__dict__
scheduler_document_model2 = SchedulerDocument(**scheduler_document_model_dict)
# Verify the model instances are equivalent
assert scheduler_document_model == scheduler_document_model2
# Convert model instance back to dict and verify no loss of data
scheduler_document_model_json2 = scheduler_document_model.to_dict()
assert scheduler_document_model_json2 == scheduler_document_model_json
class TestModel_SchedulerInfo():
"""
Test Class for SchedulerInfo
"""
def test_scheduler_info_serialization(self):
"""
Test serialization/deserialization for SchedulerInfo
"""
# Construct a json representation of a SchedulerInfo model
scheduler_info_model_json = {}
scheduler_info_model_json['changes_pending'] = 0
scheduler_info_model_json['checkpointed_source_seq'] = 'testString'
scheduler_info_model_json['doc_write_failures'] = 0
scheduler_info_model_json['docs_read'] = 0
scheduler_info_model_json['docs_written'] = 0
scheduler_info_model_json['error'] = 'testString'
scheduler_info_model_json['missing_revisions_found'] = 0
scheduler_info_model_json['revisions_checked'] = 0
scheduler_info_model_json['source_seq'] = 'testString'
scheduler_info_model_json['through_seq'] = 'testString'
# Construct a model instance of SchedulerInfo by calling from_dict on the json representation
scheduler_info_model = SchedulerInfo.from_dict(scheduler_info_model_json)
assert scheduler_info_model != False
# Construct a model instance of SchedulerInfo by calling from_dict on the json representation
scheduler_info_model_dict = SchedulerInfo.from_dict(scheduler_info_model_json).__dict__
scheduler_info_model2 = SchedulerInfo(**scheduler_info_model_dict)
# Verify the model instances are equivalent
assert scheduler_info_model == scheduler_info_model2
# Convert model instance back to dict and verify no loss of data
scheduler_info_model_json2 = scheduler_info_model.to_dict()
assert scheduler_info_model_json2 == scheduler_info_model_json
class TestModel_SchedulerJob():
"""
Test Class for SchedulerJob
"""
def test_scheduler_job_serialization(self):
"""
Test serialization/deserialization for SchedulerJob
"""
# Construct dict forms of any model objects needed in order to build this model.
scheduler_job_event_model = {} # SchedulerJobEvent
scheduler_job_event_model['reason'] = 'testString'
scheduler_job_event_model['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model['type'] = 'testString'
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
# Construct a json representation of a SchedulerJob model
scheduler_job_model_json = {}
scheduler_job_model_json['database'] = 'testString'
scheduler_job_model_json['doc_id'] = 'testString'
scheduler_job_model_json['history'] = [scheduler_job_event_model]
scheduler_job_model_json['id'] = 'testString'
scheduler_job_model_json['info'] = scheduler_info_model
scheduler_job_model_json['node'] = 'testString'
scheduler_job_model_json['pid'] = 'testString'
scheduler_job_model_json['source'] = 'testString'
scheduler_job_model_json['start_time'] = "2019-01-01T12:00:00Z"
scheduler_job_model_json['target'] = 'testString'
scheduler_job_model_json['user'] = 'testString'
# Construct a model instance of SchedulerJob by calling from_dict on the json representation
scheduler_job_model = SchedulerJob.from_dict(scheduler_job_model_json)
assert scheduler_job_model != False
# Construct a model instance of SchedulerJob by calling from_dict on the json representation
scheduler_job_model_dict = SchedulerJob.from_dict(scheduler_job_model_json).__dict__
scheduler_job_model2 = SchedulerJob(**scheduler_job_model_dict)
# Verify the model instances are equivalent
assert scheduler_job_model == scheduler_job_model2
# Convert model instance back to dict and verify no loss of data
scheduler_job_model_json2 = scheduler_job_model.to_dict()
assert scheduler_job_model_json2 == scheduler_job_model_json
class TestModel_SchedulerJobEvent():
"""
Test Class for SchedulerJobEvent
"""
def test_scheduler_job_event_serialization(self):
"""
Test serialization/deserialization for SchedulerJobEvent
"""
# Construct a json representation of a SchedulerJobEvent model
scheduler_job_event_model_json = {}
scheduler_job_event_model_json['reason'] = 'testString'
scheduler_job_event_model_json['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model_json['type'] = 'testString'
# Construct a model instance of SchedulerJobEvent by calling from_dict on the json representation
scheduler_job_event_model = SchedulerJobEvent.from_dict(scheduler_job_event_model_json)
assert scheduler_job_event_model != False
# Construct a model instance of SchedulerJobEvent by calling from_dict on the json representation
scheduler_job_event_model_dict = SchedulerJobEvent.from_dict(scheduler_job_event_model_json).__dict__
scheduler_job_event_model2 = SchedulerJobEvent(**scheduler_job_event_model_dict)
# Verify the model instances are equivalent
assert scheduler_job_event_model == scheduler_job_event_model2
# Convert model instance back to dict and verify no loss of data
scheduler_job_event_model_json2 = scheduler_job_event_model.to_dict()
assert scheduler_job_event_model_json2 == scheduler_job_event_model_json
class TestModel_SchedulerJobsResult():
"""
Test Class for SchedulerJobsResult
"""
def test_scheduler_jobs_result_serialization(self):
"""
Test serialization/deserialization for SchedulerJobsResult
"""
# Construct dict forms of any model objects needed in order to build this model.
scheduler_job_event_model = {} # SchedulerJobEvent
scheduler_job_event_model['reason'] = 'testString'
scheduler_job_event_model['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model['type'] = 'testString'
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
scheduler_job_model = {} # SchedulerJob
scheduler_job_model['database'] = 'testString'
scheduler_job_model['doc_id'] = 'testString'
scheduler_job_model['history'] = [scheduler_job_event_model]
scheduler_job_model['id'] = 'testString'
scheduler_job_model['info'] = scheduler_info_model
scheduler_job_model['node'] = 'testString'
scheduler_job_model['pid'] = 'testString'
scheduler_job_model['source'] = 'testString'
scheduler_job_model['start_time'] = "2019-01-01T12:00:00Z"
scheduler_job_model['target'] = 'testString'
scheduler_job_model['user'] = 'testString'
# Construct a json representation of a SchedulerJobsResult model
scheduler_jobs_result_model_json = {}
scheduler_jobs_result_model_json['total_rows'] = 0
scheduler_jobs_result_model_json['jobs'] = [scheduler_job_model]
# Construct a model instance of SchedulerJobsResult by calling from_dict on the json representation
scheduler_jobs_result_model = SchedulerJobsResult.from_dict(scheduler_jobs_result_model_json)
assert scheduler_jobs_result_model != False
# Construct a model instance of SchedulerJobsResult by calling from_dict on the json representation
scheduler_jobs_result_model_dict = SchedulerJobsResult.from_dict(scheduler_jobs_result_model_json).__dict__
scheduler_jobs_result_model2 = SchedulerJobsResult(**scheduler_jobs_result_model_dict)
# Verify the model instances are equivalent
assert scheduler_jobs_result_model == scheduler_jobs_result_model2
# Convert model instance back to dict and verify no loss of data
scheduler_jobs_result_model_json2 = scheduler_jobs_result_model.to_dict()
assert scheduler_jobs_result_model_json2 == scheduler_jobs_result_model_json
class TestModel_SearchAnalyzeResult():
"""
Test Class for SearchAnalyzeResult
"""
def test_search_analyze_result_serialization(self):
"""
Test serialization/deserialization for SearchAnalyzeResult
"""
# Construct a json representation of a SearchAnalyzeResult model
search_analyze_result_model_json = {}
search_analyze_result_model_json['tokens'] = ['testString']
# Construct a model instance of SearchAnalyzeResult by calling from_dict on the json representation
search_analyze_result_model = SearchAnalyzeResult.from_dict(search_analyze_result_model_json)
assert search_analyze_result_model != False
# Construct a model instance of SearchAnalyzeResult by calling from_dict on the json representation
search_analyze_result_model_dict = SearchAnalyzeResult.from_dict(search_analyze_result_model_json).__dict__
search_analyze_result_model2 = SearchAnalyzeResult(**search_analyze_result_model_dict)
# Verify the model instances are equivalent
assert search_analyze_result_model == search_analyze_result_model2
# Convert model instance back to dict and verify no loss of data
search_analyze_result_model_json2 = search_analyze_result_model.to_dict()
assert search_analyze_result_model_json2 == search_analyze_result_model_json
class TestModel_SearchIndexDefinition():
"""
Test Class for SearchIndexDefinition
"""
def test_search_index_definition_serialization(self):
"""
Test serialization/deserialization for SearchIndexDefinition
"""
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
analyzer_configuration_model = {} # AnalyzerConfiguration
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a json representation of a SearchIndexDefinition model
search_index_definition_model_json = {}
search_index_definition_model_json['analyzer'] = analyzer_configuration_model
search_index_definition_model_json['index'] = 'testString'
# Construct a model instance of SearchIndexDefinition by calling from_dict on the json representation
search_index_definition_model = SearchIndexDefinition.from_dict(search_index_definition_model_json)
assert search_index_definition_model != False
# Construct a model instance of SearchIndexDefinition by calling from_dict on the json representation
search_index_definition_model_dict = SearchIndexDefinition.from_dict(search_index_definition_model_json).__dict__
search_index_definition_model2 = SearchIndexDefinition(**search_index_definition_model_dict)
# Verify the model instances are equivalent
assert search_index_definition_model == search_index_definition_model2
# Convert model instance back to dict and verify no loss of data
search_index_definition_model_json2 = search_index_definition_model.to_dict()
assert search_index_definition_model_json2 == search_index_definition_model_json
class TestModel_SearchIndexInfo():
"""
Test Class for SearchIndexInfo
"""
def test_search_index_info_serialization(self):
"""
Test serialization/deserialization for SearchIndexInfo
"""
# Construct a json representation of a SearchIndexInfo model
search_index_info_model_json = {}
search_index_info_model_json['committed_seq'] = 26
search_index_info_model_json['disk_size'] = 0
search_index_info_model_json['doc_count'] = 0
search_index_info_model_json['doc_del_count'] = 0
search_index_info_model_json['pending_seq'] = 26
# Construct a model instance of SearchIndexInfo by calling from_dict on the json representation
search_index_info_model = SearchIndexInfo.from_dict(search_index_info_model_json)
assert search_index_info_model != False
# Construct a model instance of SearchIndexInfo by calling from_dict on the json representation
search_index_info_model_dict = SearchIndexInfo.from_dict(search_index_info_model_json).__dict__
search_index_info_model2 = SearchIndexInfo(**search_index_info_model_dict)
# Verify the model instances are equivalent
assert search_index_info_model == search_index_info_model2
# Convert model instance back to dict and verify no loss of data
search_index_info_model_json2 = search_index_info_model.to_dict()
assert search_index_info_model_json2 == search_index_info_model_json
class TestModel_SearchInfoResult():
"""
Test Class for SearchInfoResult
"""
def test_search_info_result_serialization(self):
"""
Test serialization/deserialization for SearchInfoResult
"""
# Construct dict forms of any model objects needed in order to build this model.
search_index_info_model = {} # SearchIndexInfo
search_index_info_model['committed_seq'] = 26
search_index_info_model['disk_size'] = 0
search_index_info_model['doc_count'] = 0
search_index_info_model['doc_del_count'] = 0
search_index_info_model['pending_seq'] = 26
# Construct a json representation of a SearchInfoResult model
search_info_result_model_json = {}
search_info_result_model_json['name'] = 'testString'
search_info_result_model_json['search_index'] = search_index_info_model
# Construct a model instance of SearchInfoResult by calling from_dict on the json representation
search_info_result_model = SearchInfoResult.from_dict(search_info_result_model_json)
assert search_info_result_model != False
# Construct a model instance of SearchInfoResult by calling from_dict on the json representation
search_info_result_model_dict = SearchInfoResult.from_dict(search_info_result_model_json).__dict__
search_info_result_model2 = SearchInfoResult(**search_info_result_model_dict)
# Verify the model instances are equivalent
assert search_info_result_model == search_info_result_model2
# Convert model instance back to dict and verify no loss of data
search_info_result_model_json2 = search_info_result_model.to_dict()
assert search_info_result_model_json2 == search_info_result_model_json
class TestModel_SearchResult():
"""
Test Class for SearchResult
"""
def test_search_result_serialization(self):
"""
Test serialization/deserialization for SearchResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
search_result_row_model = {} # SearchResultRow
search_result_row_model['doc'] = document_model
search_result_row_model['fields'] = {}
search_result_row_model['highlights'] = {}
search_result_row_model['id'] = 'testString'
search_result_properties_model = {} # SearchResultProperties
search_result_properties_model['total_rows'] = 0
search_result_properties_model['bookmark'] = 'testString'
search_result_properties_model['by'] = 'testString'
search_result_properties_model['counts'] = {}
search_result_properties_model['ranges'] = {}
search_result_properties_model['rows'] = [search_result_row_model]
# Construct a json representation of a SearchResult model
search_result_model_json = {}
search_result_model_json['total_rows'] = 0
search_result_model_json['bookmark'] = 'testString'
search_result_model_json['by'] = 'testString'
search_result_model_json['counts'] = {}
search_result_model_json['ranges'] = {}
search_result_model_json['rows'] = [search_result_row_model]
search_result_model_json['groups'] = [search_result_properties_model]
# Construct a model instance of SearchResult by calling from_dict on the json representation
search_result_model = SearchResult.from_dict(search_result_model_json)
assert search_result_model != False
# Construct a model instance of SearchResult by calling from_dict on the json representation
search_result_model_dict = SearchResult.from_dict(search_result_model_json).__dict__
search_result_model2 = SearchResult(**search_result_model_dict)
# Verify the model instances are equivalent
assert search_result_model == search_result_model2
# Convert model instance back to dict and verify no loss of data
search_result_model_json2 = search_result_model.to_dict()
assert search_result_model_json2 == search_result_model_json
class TestModel_SearchResultProperties():
"""
Test Class for SearchResultProperties
"""
def test_search_result_properties_serialization(self):
"""
Test serialization/deserialization for SearchResultProperties
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
search_result_row_model = {} # SearchResultRow
search_result_row_model['doc'] = document_model
search_result_row_model['fields'] = {}
search_result_row_model['highlights'] = {}
search_result_row_model['id'] = 'testString'
# Construct a json representation of a SearchResultProperties model
search_result_properties_model_json = {}
search_result_properties_model_json['total_rows'] = 0
search_result_properties_model_json['bookmark'] = 'testString'
search_result_properties_model_json['by'] = 'testString'
search_result_properties_model_json['counts'] = {}
search_result_properties_model_json['ranges'] = {}
search_result_properties_model_json['rows'] = [search_result_row_model]
# Construct a model instance of SearchResultProperties by calling from_dict on the json representation
search_result_properties_model = SearchResultProperties.from_dict(search_result_properties_model_json)
assert search_result_properties_model != False
# Construct a model instance of SearchResultProperties by calling from_dict on the json representation
search_result_properties_model_dict = SearchResultProperties.from_dict(search_result_properties_model_json).__dict__
search_result_properties_model2 = SearchResultProperties(**search_result_properties_model_dict)
# Verify the model instances are equivalent
assert search_result_properties_model == search_result_properties_model2
# Convert model instance back to dict and verify no loss of data
search_result_properties_model_json2 = search_result_properties_model.to_dict()
assert search_result_properties_model_json2 == search_result_properties_model_json
class TestModel_SearchResultRow():
"""
Test Class for SearchResultRow
"""
def test_search_result_row_serialization(self):
"""
Test serialization/deserialization for SearchResultRow
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a SearchResultRow model
search_result_row_model_json = {}
search_result_row_model_json['doc'] = document_model
search_result_row_model_json['fields'] = {}
search_result_row_model_json['highlights'] = {}
search_result_row_model_json['id'] = 'testString'
# Construct a model instance of SearchResultRow by calling from_dict on the json representation
search_result_row_model = SearchResultRow.from_dict(search_result_row_model_json)
assert search_result_row_model != False
# Construct a model instance of SearchResultRow by calling from_dict on the json representation
search_result_row_model_dict = SearchResultRow.from_dict(search_result_row_model_json).__dict__
search_result_row_model2 = SearchResultRow(**search_result_row_model_dict)
# Verify the model instances are equivalent
assert search_result_row_model == search_result_row_model2
# Convert model instance back to dict and verify no loss of data
search_result_row_model_json2 = search_result_row_model.to_dict()
assert search_result_row_model_json2 == search_result_row_model_json
class TestModel_Security():
"""
Test Class for Security
"""
def test_security_serialization(self):
"""
Test serialization/deserialization for Security
"""
# Construct dict forms of any model objects needed in order to build this model.
security_object_model = {} # SecurityObject
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Construct a json representation of a Security model
security_model_json = {}
security_model_json['admins'] = security_object_model
security_model_json['members'] = security_object_model
security_model_json['cloudant'] = {}
security_model_json['couchdb_auth_only'] = True
# Construct a model instance of Security by calling from_dict on the json representation
security_model = Security.from_dict(security_model_json)
assert security_model != False
# Construct a model instance of Security by calling from_dict on the json representation
security_model_dict = Security.from_dict(security_model_json).__dict__
security_model2 = Security(**security_model_dict)
# Verify the model instances are equivalent
assert security_model == security_model2
# Convert model instance back to dict and verify no loss of data
security_model_json2 = security_model.to_dict()
assert security_model_json2 == security_model_json
class TestModel_SecurityObject():
"""
Test Class for SecurityObject
"""
def test_security_object_serialization(self):
"""
Test serialization/deserialization for SecurityObject
"""
# Construct a json representation of a SecurityObject model
security_object_model_json = {}
security_object_model_json['names'] = ['testString']
security_object_model_json['roles'] = ['testString']
# Construct a model instance of SecurityObject by calling from_dict on the json representation
security_object_model = SecurityObject.from_dict(security_object_model_json)
assert security_object_model != False
# Construct a model instance of SecurityObject by calling from_dict on the json representation
security_object_model_dict = SecurityObject.from_dict(security_object_model_json).__dict__
security_object_model2 = SecurityObject(**security_object_model_dict)
# Verify the model instances are equivalent
assert security_object_model == security_object_model2
# Convert model instance back to dict and verify no loss of data
security_object_model_json2 = security_object_model.to_dict()
assert security_object_model_json2 == security_object_model_json
class TestModel_ServerInformation():
"""
Test Class for ServerInformation
"""
def test_server_information_serialization(self):
"""
Test serialization/deserialization for ServerInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
server_vendor_model = {} # ServerVendor
server_vendor_model['name'] = 'testString'
server_vendor_model['variant'] = 'testString'
server_vendor_model['version'] = 'testString'
# Construct a json representation of a ServerInformation model
server_information_model_json = {}
server_information_model_json['couchdb'] = 'testString'
server_information_model_json['features'] = ['testString']
server_information_model_json['vendor'] = server_vendor_model
server_information_model_json['version'] = 'testString'
server_information_model_json['features_flags'] = ['testString']
# Construct a model instance of ServerInformation by calling from_dict on the json representation
server_information_model = ServerInformation.from_dict(server_information_model_json)
assert server_information_model != False
# Construct a model instance of ServerInformation by calling from_dict on the json representation
server_information_model_dict = ServerInformation.from_dict(server_information_model_json).__dict__
server_information_model2 = ServerInformation(**server_information_model_dict)
# Verify the model instances are equivalent
assert server_information_model == server_information_model2
# Convert model instance back to dict and verify no loss of data
server_information_model_json2 = server_information_model.to_dict()
assert server_information_model_json2 == server_information_model_json
class TestModel_ServerVendor():
"""
Test Class for ServerVendor
"""
def test_server_vendor_serialization(self):
"""
Test serialization/deserialization for ServerVendor
"""
# Construct a json representation of a ServerVendor model
server_vendor_model_json = {}
server_vendor_model_json['name'] = 'testString'
server_vendor_model_json['variant'] = 'testString'
server_vendor_model_json['version'] = 'testString'
# Construct a model instance of ServerVendor by calling from_dict on the json representation
server_vendor_model = ServerVendor.from_dict(server_vendor_model_json)
assert server_vendor_model != False
# Construct a model instance of ServerVendor by calling from_dict on the json representation
server_vendor_model_dict = ServerVendor.from_dict(server_vendor_model_json).__dict__
server_vendor_model2 = ServerVendor(**server_vendor_model_dict)
# Verify the model instances are equivalent
assert server_vendor_model == server_vendor_model2
# Convert model instance back to dict and verify no loss of data
server_vendor_model_json2 = server_vendor_model.to_dict()
assert server_vendor_model_json2 == server_vendor_model_json
class TestModel_SessionAuthentication():
"""
Test Class for SessionAuthentication
"""
def test_session_authentication_serialization(self):
"""
Test serialization/deserialization for SessionAuthentication
"""
# Construct a json representation of a SessionAuthentication model
session_authentication_model_json = {}
session_authentication_model_json['authenticated'] = 'testString'
session_authentication_model_json['authentication_db'] = 'testString'
session_authentication_model_json['authentication_handlers'] = ['testString']
# Construct a model instance of SessionAuthentication by calling from_dict on the json representation
session_authentication_model = SessionAuthentication.from_dict(session_authentication_model_json)
assert session_authentication_model != False
# Construct a model instance of SessionAuthentication by calling from_dict on the json representation
session_authentication_model_dict = SessionAuthentication.from_dict(session_authentication_model_json).__dict__
session_authentication_model2 = SessionAuthentication(**session_authentication_model_dict)
# Verify the model instances are equivalent
assert session_authentication_model == session_authentication_model2
# Convert model instance back to dict and verify no loss of data
session_authentication_model_json2 = session_authentication_model.to_dict()
assert session_authentication_model_json2 == session_authentication_model_json
class TestModel_SessionInformation():
"""
Test Class for SessionInformation
"""
def test_session_information_serialization(self):
"""
Test serialization/deserialization for SessionInformation
"""
# Construct dict forms of any model objects needed in order to build this model.
session_authentication_model = {} # SessionAuthentication
session_authentication_model['authenticated'] = 'testString'
session_authentication_model['authentication_db'] = 'testString'
session_authentication_model['authentication_handlers'] = ['testString']
user_context_model = {} # UserContext
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a json representation of a SessionInformation model
session_information_model_json = {}
session_information_model_json['ok'] = True
session_information_model_json['info'] = session_authentication_model
session_information_model_json['userCtx'] = user_context_model
# Construct a model instance of SessionInformation by calling from_dict on the json representation
session_information_model = SessionInformation.from_dict(session_information_model_json)
assert session_information_model != False
# Construct a model instance of SessionInformation by calling from_dict on the json representation
session_information_model_dict = SessionInformation.from_dict(session_information_model_json).__dict__
session_information_model2 = SessionInformation(**session_information_model_dict)
# Verify the model instances are equivalent
assert session_information_model == session_information_model2
# Convert model instance back to dict and verify no loss of data
session_information_model_json2 = session_information_model.to_dict()
assert session_information_model_json2 == session_information_model_json
class TestModel_ShardsInformation():
"""
Test Class for ShardsInformation
"""
def test_shards_information_serialization(self):
"""
Test serialization/deserialization for ShardsInformation
"""
# Construct a json representation of a ShardsInformation model
shards_information_model_json = {}
shards_information_model_json['shards'] = {}
# Construct a model instance of ShardsInformation by calling from_dict on the json representation
shards_information_model = ShardsInformation.from_dict(shards_information_model_json)
assert shards_information_model != False
# Construct a model instance of ShardsInformation by calling from_dict on the json representation
shards_information_model_dict = ShardsInformation.from_dict(shards_information_model_json).__dict__
shards_information_model2 = ShardsInformation(**shards_information_model_dict)
# Verify the model instances are equivalent
assert shards_information_model == shards_information_model2
# Convert model instance back to dict and verify no loss of data
shards_information_model_json2 = shards_information_model.to_dict()
assert shards_information_model_json2 == shards_information_model_json
class TestModel_ThroughputInformation():
"""
Test Class for ThroughputInformation
"""
def test_throughput_information_serialization(self):
"""
Test serialization/deserialization for ThroughputInformation
"""
# Construct a json representation of a ThroughputInformation model
throughput_information_model_json = {}
throughput_information_model_json['blocks'] = 0
throughput_information_model_json['query'] = 0
throughput_information_model_json['read'] = 0
throughput_information_model_json['write'] = 0
# Construct a model instance of ThroughputInformation by calling from_dict on the json representation
throughput_information_model = ThroughputInformation.from_dict(throughput_information_model_json)
assert throughput_information_model != False
# Construct a model instance of ThroughputInformation by calling from_dict on the json representation
throughput_information_model_dict = ThroughputInformation.from_dict(throughput_information_model_json).__dict__
throughput_information_model2 = ThroughputInformation(**throughput_information_model_dict)
# Verify the model instances are equivalent
assert throughput_information_model == throughput_information_model2
# Convert model instance back to dict and verify no loss of data
throughput_information_model_json2 = throughput_information_model.to_dict()
assert throughput_information_model_json2 == throughput_information_model_json
class TestModel_UpInformation():
"""
Test Class for UpInformation
"""
def test_up_information_serialization(self):
"""
Test serialization/deserialization for UpInformation
"""
# Construct a json representation of a UpInformation model
up_information_model_json = {}
up_information_model_json['seeds'] = { 'foo': 'bar' }
up_information_model_json['status'] = 'maintenance_mode'
# Construct a model instance of UpInformation by calling from_dict on the json representation
up_information_model = UpInformation.from_dict(up_information_model_json)
assert up_information_model != False
# Construct a model instance of UpInformation by calling from_dict on the json representation
up_information_model_dict = UpInformation.from_dict(up_information_model_json).__dict__
up_information_model2 = UpInformation(**up_information_model_dict)
# Verify the model instances are equivalent
assert up_information_model == up_information_model2
# Convert model instance back to dict and verify no loss of data
up_information_model_json2 = up_information_model.to_dict()
assert up_information_model_json2 == up_information_model_json
class TestModel_UserContext():
"""
Test Class for UserContext
"""
def test_user_context_serialization(self):
"""
Test serialization/deserialization for UserContext
"""
# Construct a json representation of a UserContext model
user_context_model_json = {}
user_context_model_json['db'] = 'testString'
user_context_model_json['name'] = 'testString'
user_context_model_json['roles'] = ['_reader']
# Construct a model instance of UserContext by calling from_dict on the json representation
user_context_model = UserContext.from_dict(user_context_model_json)
assert user_context_model != False
# Construct a model instance of UserContext by calling from_dict on the json representation
user_context_model_dict = UserContext.from_dict(user_context_model_json).__dict__
user_context_model2 = UserContext(**user_context_model_dict)
# Verify the model instances are equivalent
assert user_context_model == user_context_model2
# Convert model instance back to dict and verify no loss of data
user_context_model_json2 = user_context_model.to_dict()
assert user_context_model_json2 == user_context_model_json
class TestModel_UuidsResult():
"""
Test Class for UuidsResult
"""
def test_uuids_result_serialization(self):
"""
Test serialization/deserialization for UuidsResult
"""
# Construct a json representation of a UuidsResult model
uuids_result_model_json = {}
uuids_result_model_json['uuids'] = ['testString']
# Construct a model instance of UuidsResult by calling from_dict on the json representation
uuids_result_model = UuidsResult.from_dict(uuids_result_model_json)
assert uuids_result_model != False
# Construct a model instance of UuidsResult by calling from_dict on the json representation
uuids_result_model_dict = UuidsResult.from_dict(uuids_result_model_json).__dict__
uuids_result_model2 = UuidsResult(**uuids_result_model_dict)
# Verify the model instances are equivalent
assert uuids_result_model == uuids_result_model2
# Convert model instance back to dict and verify no loss of data
uuids_result_model_json2 = uuids_result_model.to_dict()
assert uuids_result_model_json2 == uuids_result_model_json
class TestModel_ViewQueriesResult():
"""
Test Class for ViewQueriesResult
"""
def test_view_queries_result_serialization(self):
"""
Test serialization/deserialization for ViewQueriesResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
view_result_row_model = {} # ViewResultRow
view_result_row_model['caused_by'] = 'testString'
view_result_row_model['error'] = 'testString'
view_result_row_model['reason'] = 'testString'
view_result_row_model['doc'] = document_model
view_result_row_model['id'] = 'testString'
view_result_row_model['key'] = 'testString'
view_result_row_model['value'] = 'testString'
view_result_model = {} # ViewResult
view_result_model['total_rows'] = 0
view_result_model['update_seq'] = 'testString'
view_result_model['rows'] = [view_result_row_model]
# Construct a json representation of a ViewQueriesResult model
view_queries_result_model_json = {}
view_queries_result_model_json['results'] = [view_result_model]
# Construct a model instance of ViewQueriesResult by calling from_dict on the json representation
view_queries_result_model = ViewQueriesResult.from_dict(view_queries_result_model_json)
assert view_queries_result_model != False
# Construct a model instance of ViewQueriesResult by calling from_dict on the json representation
view_queries_result_model_dict = ViewQueriesResult.from_dict(view_queries_result_model_json).__dict__
view_queries_result_model2 = ViewQueriesResult(**view_queries_result_model_dict)
# Verify the model instances are equivalent
assert view_queries_result_model == view_queries_result_model2
# Convert model instance back to dict and verify no loss of data
view_queries_result_model_json2 = view_queries_result_model.to_dict()
assert view_queries_result_model_json2 == view_queries_result_model_json
class TestModel_ViewQuery():
"""
Test Class for ViewQuery
"""
def test_view_query_serialization(self):
"""
Test serialization/deserialization for ViewQuery
"""
# Construct a json representation of a ViewQuery model
view_query_model_json = {}
view_query_model_json['att_encoding_info'] = False
view_query_model_json['attachments'] = False
view_query_model_json['conflicts'] = False
view_query_model_json['descending'] = False
view_query_model_json['include_docs'] = False
view_query_model_json['inclusive_end'] = True
view_query_model_json['limit'] = 0
view_query_model_json['skip'] = 0
view_query_model_json['update_seq'] = False
view_query_model_json['endkey'] = 'testString'
view_query_model_json['endkey_docid'] = 'testString'
view_query_model_json['group'] = False
view_query_model_json['group_level'] = 1
view_query_model_json['key'] = 'testString'
view_query_model_json['keys'] = ['testString']
view_query_model_json['reduce'] = True
view_query_model_json['stable'] = False
view_query_model_json['startkey'] = 'testString'
view_query_model_json['startkey_docid'] = 'testString'
view_query_model_json['update'] = 'true'
# Construct a model instance of ViewQuery by calling from_dict on the json representation
view_query_model = ViewQuery.from_dict(view_query_model_json)
assert view_query_model != False
# Construct a model instance of ViewQuery by calling from_dict on the json representation
view_query_model_dict = ViewQuery.from_dict(view_query_model_json).__dict__
view_query_model2 = ViewQuery(**view_query_model_dict)
# Verify the model instances are equivalent
assert view_query_model == view_query_model2
# Convert model instance back to dict and verify no loss of data
view_query_model_json2 = view_query_model.to_dict()
assert view_query_model_json2 == view_query_model_json
class TestModel_ViewResult():
"""
Test Class for ViewResult
"""
def test_view_result_serialization(self):
"""
Test serialization/deserialization for ViewResult
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
view_result_row_model = {} # ViewResultRow
view_result_row_model['caused_by'] = 'testString'
view_result_row_model['error'] = 'testString'
view_result_row_model['reason'] = 'testString'
view_result_row_model['doc'] = document_model
view_result_row_model['id'] = 'testString'
view_result_row_model['key'] = 'testString'
view_result_row_model['value'] = 'testString'
# Construct a json representation of a ViewResult model
view_result_model_json = {}
view_result_model_json['total_rows'] = 0
view_result_model_json['update_seq'] = 'testString'
view_result_model_json['rows'] = [view_result_row_model]
# Construct a model instance of ViewResult by calling from_dict on the json representation
view_result_model = ViewResult.from_dict(view_result_model_json)
assert view_result_model != False
# Construct a model instance of ViewResult by calling from_dict on the json representation
view_result_model_dict = ViewResult.from_dict(view_result_model_json).__dict__
view_result_model2 = ViewResult(**view_result_model_dict)
# Verify the model instances are equivalent
assert view_result_model == view_result_model2
# Convert model instance back to dict and verify no loss of data
view_result_model_json2 = view_result_model.to_dict()
assert view_result_model_json2 == view_result_model_json
class TestModel_ViewResultRow():
"""
Test Class for ViewResultRow
"""
def test_view_result_row_serialization(self):
"""
Test serialization/deserialization for ViewResultRow
"""
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a ViewResultRow model
view_result_row_model_json = {}
view_result_row_model_json['caused_by'] = 'testString'
view_result_row_model_json['error'] = 'testString'
view_result_row_model_json['reason'] = 'testString'
view_result_row_model_json['doc'] = document_model
view_result_row_model_json['id'] = 'testString'
view_result_row_model_json['key'] = 'testString'
view_result_row_model_json['value'] = 'testString'
# Construct a model instance of ViewResultRow by calling from_dict on the json representation
view_result_row_model = ViewResultRow.from_dict(view_result_row_model_json)
assert view_result_row_model != False
# Construct a model instance of ViewResultRow by calling from_dict on the json representation
view_result_row_model_dict = ViewResultRow.from_dict(view_result_row_model_json).__dict__
view_result_row_model2 = ViewResultRow(**view_result_row_model_dict)
# Verify the model instances are equivalent
assert view_result_row_model == view_result_row_model2
# Convert model instance back to dict and verify no loss of data
view_result_row_model_json2 = view_result_row_model.to_dict()
assert view_result_row_model_json2 == view_result_row_model_json
class TestModel_GeoJsonGeometry():
"""
Test Class for GeoJsonGeometry
"""
def test_geo_json_geometry_serialization(self):
"""
Test serialization/deserialization for GeoJsonGeometry
"""
# Construct a json representation of a GeoJsonGeometry model
geo_json_geometry_model_json = {}
geo_json_geometry_model_json['type'] = 'Point'
geo_json_geometry_model_json['coordinates'] = ['testString']
# Construct a model instance of GeoJsonGeometry by calling from_dict on the json representation
geo_json_geometry_model = GeoJsonGeometry.from_dict(geo_json_geometry_model_json)
assert geo_json_geometry_model != False
# Construct a model instance of GeoJsonGeometry by calling from_dict on the json representation
geo_json_geometry_model_dict = GeoJsonGeometry.from_dict(geo_json_geometry_model_json).__dict__
geo_json_geometry_model2 = GeoJsonGeometry(**geo_json_geometry_model_dict)
# Verify the model instances are equivalent
assert geo_json_geometry_model == geo_json_geometry_model2
# Convert model instance back to dict and verify no loss of data
geo_json_geometry_model_json2 = geo_json_geometry_model.to_dict()
assert geo_json_geometry_model_json2 == geo_json_geometry_model_json
class TestModel_GeoJsonGeometryCollection():
"""
Test Class for GeoJsonGeometryCollection
"""
def test_geo_json_geometry_collection_serialization(self):
"""
Test serialization/deserialization for GeoJsonGeometryCollection
"""
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
# Construct a json representation of a GeoJsonGeometryCollection model
geo_json_geometry_collection_model_json = {}
geo_json_geometry_collection_model_json['type'] = 'Point'
geo_json_geometry_collection_model_json['geometries'] = [geo_json_geometry_model]
# Construct a model instance of GeoJsonGeometryCollection by calling from_dict on the json representation
geo_json_geometry_collection_model = GeoJsonGeometryCollection.from_dict(geo_json_geometry_collection_model_json)
assert geo_json_geometry_collection_model != False
# Construct a model instance of GeoJsonGeometryCollection by calling from_dict on the json representation
geo_json_geometry_collection_model_dict = GeoJsonGeometryCollection.from_dict(geo_json_geometry_collection_model_json).__dict__
geo_json_geometry_collection_model2 = GeoJsonGeometryCollection(**geo_json_geometry_collection_model_dict)
# Verify the model instances are equivalent
assert geo_json_geometry_collection_model == geo_json_geometry_collection_model2
# Convert model instance back to dict and verify no loss of data
geo_json_geometry_collection_model_json2 = geo_json_geometry_collection_model.to_dict()
assert geo_json_geometry_collection_model_json2 == geo_json_geometry_collection_model_json
# endregion
##############################################################################
# End of Model Tests
##############################################################################
| 41.556629 | 1,470 | 0.647074 |
from datetime import datetime, timezone
from ibm_cloud_sdk_core.authenticators.no_auth_authenticator import NoAuthAuthenticator
from ibm_cloud_sdk_core.utils import datetime_to_string, string_to_datetime
import base64
import inspect
import io
import json
import os
import pytest
import re
import requests
import requests.models
import responses
import tempfile
import urllib
import gzip
from ibmcloudant.cloudant_v1 import *
_service = CloudantV1(
authenticator=NoAuthAuthenticator()
)
_base_url = 'http://localhost:5984'
_service.set_service_url(_base_url)
y encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_capacity_throughput_information_all_params(self):
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_capacity_throughput_information()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_capacity_throughput_information_all_params_with_retries(self):
_service.enable_retries()
self.test_get_capacity_throughput_information_all_params()
_service.disable_retries()
self.test_get_capacity_throughput_information_all_params()
class TestPutCapacityThroughputConfiguration():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_capacity_throughput_configuration_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
blocks = 0
# Invoke method
response = _service.put_capacity_throughput_configuration(
blocks,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['blocks'] == 0
def test_put_capacity_throughput_configuration_all_params_with_retries(self):
# Enable retries and run test_put_capacity_throughput_configuration_all_params.
_service.enable_retries()
self.test_put_capacity_throughput_configuration_all_params()
# Disable retries and run test_put_capacity_throughput_configuration_all_params.
_service.disable_retries()
self.test_put_capacity_throughput_configuration_all_params()
@responses.activate
def test_put_capacity_throughput_configuration_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/capacity/throughput')
mock_response = '{"current": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}, "target": {"throughput": {"blocks": 0, "query": 0, "read": 0, "write": 0}}}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
blocks = 0
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"blocks": blocks,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_capacity_throughput_configuration(**req_copy)
def test_put_capacity_throughput_configuration_value_error_with_retries(self):
# Enable retries and run test_put_capacity_throughput_configuration_value_error.
_service.enable_retries()
self.test_put_capacity_throughput_configuration_value_error()
# Disable retries and run test_put_capacity_throughput_configuration_value_error.
_service.disable_retries()
self.test_put_capacity_throughput_configuration_value_error()
# endregion
##############################################################################
# End of Service: Server
##############################################################################
##############################################################################
# Start of Service: Changes
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetDbUpdates():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_db_updates_all_params(self):
url = self.preprocess_url(_base_url + '/_db_updates')
mock_response = '{"last_seq": "last_seq", "results": [{"account": "account", "db_name": "db_name", "seq": "seq", "type": "created"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
feed = 'normal'
heartbeat = 0
timeout = 0
since = '0'
response = _service.get_db_updates(
feed=feed,
heartbeat=heartbeat,
timeout=timeout,
since=since,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'feed={}'.format(feed) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'since={}'.format(since) in query_string
def test_get_db_updates_all_params_with_retries(self):
_service.enable_retries()
self.test_get_db_updates_all_params()
_service.disable_retries()
self.test_get_db_updates_all_params()
@responses.activate
def test_get_db_updates_required_params(self):
url = self.preprocess_url(_base_url + '/_db_updates')
mock_response = '{"last_seq": "last_seq", "results": [{"account": "account", "db_name": "db_name", "seq": "seq", "type": "created"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_db_updates()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_db_updates_required_params_with_retries(self):
_service.enable_retries()
self.test_get_db_updates_required_params()
_service.disable_retries()
self.test_get_db_updates_required_params()
class TestPostChanges():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_changes_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
last_event_id = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
feed = 'normal'
filter = 'testString'
heartbeat = 0
include_docs = False
limit = 0
seq_interval = 1
since = '0'
style = 'main_only'
timeout = 0
view = 'testString'
# Invoke method
response = _service.post_changes(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
last_event_id=last_event_id,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
feed=feed,
filter=filter,
heartbeat=heartbeat,
include_docs=include_docs,
limit=limit,
seq_interval=seq_interval,
since=since,
style=style,
timeout=timeout,
view=view,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'descending={}'.format('true' if descending else 'false') in query_string
assert 'feed={}'.format(feed) in query_string
assert 'filter={}'.format(filter) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'limit={}'.format(limit) in query_string
assert 'seq_interval={}'.format(seq_interval) in query_string
assert 'since={}'.format(since) in query_string
assert 'style={}'.format(style) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'view={}'.format(view) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['testString']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
def test_post_changes_all_params_with_retries(self):
# Enable retries and run test_post_changes_all_params.
_service.enable_retries()
self.test_post_changes_all_params()
# Disable retries and run test_post_changes_all_params.
_service.disable_retries()
self.test_post_changes_all_params()
@responses.activate
def test_post_changes_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
# Invoke method
response = _service.post_changes(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['testString']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
def test_post_changes_required_params_with_retries(self):
# Enable retries and run test_post_changes_required_params.
_service.enable_retries()
self.test_post_changes_required_params()
# Disable retries and run test_post_changes_required_params.
_service.disable_retries()
self.test_post_changes_required_params()
@responses.activate
def test_post_changes_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"last_seq": "last_seq", "pending": 7, "results": [{"changes": [{"rev": "rev"}], "deleted": false, "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "seq": "seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_ids = ['testString']
fields = ['testString']
selector = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_changes(**req_copy)
def test_post_changes_value_error_with_retries(self):
# Enable retries and run test_post_changes_value_error.
_service.enable_retries()
self.test_post_changes_value_error()
# Disable retries and run test_post_changes_value_error.
_service.disable_retries()
self.test_post_changes_value_error()
class TestPostChangesAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_changes_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
last_event_id = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
feed = 'normal'
filter = 'testString'
heartbeat = 0
include_docs = False
limit = 0
seq_interval = 1
since = '0'
style = 'main_only'
timeout = 0
view = 'testString'
response = _service.post_changes_as_stream(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
last_event_id=last_event_id,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
feed=feed,
filter=filter,
heartbeat=heartbeat,
include_docs=include_docs,
limit=limit,
seq_interval=seq_interval,
since=since,
style=style,
timeout=timeout,
view=view,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'descending={}'.format('true' if descending else 'false') in query_string
assert 'feed={}'.format(feed) in query_string
assert 'filter={}'.format(filter) in query_string
assert 'heartbeat={}'.format(heartbeat) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'limit={}'.format(limit) in query_string
assert 'seq_interval={}'.format(seq_interval) in query_string
assert 'since={}'.format(since) in query_string
assert 'style={}'.format(style) in query_string
assert 'timeout={}'.format(timeout) in query_string
assert 'view={}'.format(view) in query_string
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['0007741142412418284']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_changes_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_changes_as_stream_all_params()
_service.disable_retries()
self.test_post_changes_as_stream_all_params()
@responses.activate
def test_post_changes_as_stream_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
response = _service.post_changes_as_stream(
db,
doc_ids=doc_ids,
fields=fields,
selector=selector,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['doc_ids'] == ['0007741142412418284']
assert req_body['fields'] == ['testString']
assert req_body['selector'] == {}
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_changes_as_stream_required_params_with_retries(self):
_service.enable_retries()
self.test_post_changes_as_stream_required_params()
_service.disable_retries()
self.test_post_changes_as_stream_required_params()
@responses.activate
def test_post_changes_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_changes')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_ids = ['0007741142412418284']
fields = ['testString']
selector = {}
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_changes_as_stream(**req_copy)
def test_post_changes_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_changes_as_stream_value_error()
_service.disable_retries()
self.test_post_changes_as_stream_value_error()
cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_database_information(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_database_information_all_params_with_retries(self):
# Enable retries and run test_get_database_information_all_params.
_service.enable_retries()
self.test_get_database_information_all_params()
# Disable retries and run test_get_database_information_all_params.
_service.disable_retries()
self.test_get_database_information_all_params()
@responses.activate
def test_get_database_information_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"cluster": {"n": 1, "q": 1, "r": 1, "w": 1}, "committed_update_seq": "committed_update_seq", "compact_running": false, "compacted_seq": "compacted_seq", "db_name": "db_name", "disk_format_version": 19, "doc_count": 0, "doc_del_count": 0, "engine": "engine", "props": {"partitioned": false}, "sizes": {"active": 6, "external": 8, "file": 4}, "update_seq": "update_seq", "uuid": "uuid"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_database_information(**req_copy)
def test_get_database_information_value_error_with_retries(self):
# Enable retries and run test_get_database_information_value_error.
_service.enable_retries()
self.test_get_database_information_value_error()
# Disable retries and run test_get_database_information_value_error.
_service.disable_retries()
self.test_get_database_information_value_error()
class TestPutDatabase():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_database_all_params(self):
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
db = 'testString'
partitioned = False
q = 1
response = _service.put_database(
db,
partitioned=partitioned,
q=q,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 201
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'partitioned={}'.format('true' if partitioned else 'false') in query_string
assert 'q={}'.format(q) in query_string
def test_put_database_all_params_with_retries(self):
_service.enable_retries()
self.test_put_database_all_params()
_service.disable_retries()
self.test_put_database_all_params()
@responses.activate
def test_put_database_required_params(self):
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
db = 'testString'
response = _service.put_database(
db,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 201
def test_put_database_required_params_with_retries(self):
_service.enable_retries()
self.test_put_database_required_params()
_service.disable_retries()
self.test_put_database_required_params()
@responses.activate
def test_put_database_value_error(self):
url = self.preprocess_url(_base_url + '/testString')
mock_response = '{"ok": true}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
db = 'testString'
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_database(**req_copy)
def test_put_database_value_error_with_retries(self):
_service.enable_retries()
self.test_put_database_value_error()
_service.disable_retries()
self.test_put_database_value_error()
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_document(**req_copy)
def test_post_document_value_error_with_retries(self):
_service.enable_retries()
self.test_post_document_value_error()
_service.disable_retries()
self.test_post_document_value_error()
class TestPostAllDocs():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = 'testString'
# Invoke method
response = _service.post_all_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == 'testString'
def test_post_all_docs_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_all_params.
_service.enable_retries()
self.test_post_all_docs_all_params()
# Disable retries and run test_post_all_docs_all_params.
_service.disable_retries()
self.test_post_all_docs_all_params()
@responses.activate
def test_post_all_docs_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 0
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs(**req_copy)
def test_post_all_docs_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_value_error.
_service.enable_retries()
self.test_post_all_docs_value_error()
# Disable retries and run test_post_all_docs_value_error.
_service.disable_retries()
self.test_post_all_docs_value_error()
class TestPostAllDocsAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
response = _service.post_all_docs_as_stream(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_all_docs_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_all_docs_as_stream_all_params()
_service.disable_retries()
self.test_post_all_docs_as_stream_all_params()
@responses.activate
def test_post_all_docs_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_as_stream(**req_copy)
def test_post_all_docs_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_all_docs_as_stream_value_error()
_service.disable_retries()
self.test_post_all_docs_as_stream_value_error()
class TestPostAllDocsQueries():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_queries_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['testString']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Invoke method
response = _service.post_all_docs_queries(
db,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_all_docs_queries_all_params_with_retries(self):
# Enable retries and run test_post_all_docs_queries_all_params.
_service.enable_retries()
self.test_post_all_docs_queries_all_params()
# Disable retries and run test_post_all_docs_queries_all_params.
_service.disable_retries()
self.test_post_all_docs_queries_all_params()
@responses.activate
def test_post_all_docs_queries_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a AllDocsQuery model
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['testString']
all_docs_query_model['startkey'] = 'testString'
# Set up parameter values
db = 'testString'
queries = [all_docs_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_queries(**req_copy)
def test_post_all_docs_queries_value_error_with_retries(self):
# Enable retries and run test_post_all_docs_queries_value_error.
_service.enable_retries()
self.test_post_all_docs_queries_value_error()
# Disable retries and run test_post_all_docs_queries_value_error.
_service.disable_retries()
self.test_post_all_docs_queries_value_error()
class TestPostAllDocsQueriesAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_all_docs_queries_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
db = 'testString'
queries = [all_docs_query_model]
response = _service.post_all_docs_queries_as_stream(
db,
queries,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_all_docs_queries_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_all_docs_queries_as_stream_all_params()
_service.disable_retries()
self.test_post_all_docs_queries_as_stream_all_params()
@responses.activate
def test_post_all_docs_queries_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_all_docs/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
db = 'testString'
queries = [all_docs_query_model]
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_all_docs_queries_as_stream(**req_copy)
def test_post_all_docs_queries_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_all_docs_queries_as_stream_value_error()
_service.disable_retries()
self.test_post_all_docs_queries_as_stream_value_error()
class TestPostBulkDocs():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_docs_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_docs')
mock_response = '[{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a dict representation of a BulkDocs model
bulk_docs_model = {}
bulk_docs_model['docs'] = [document_model]
bulk_docs_model['new_edits'] = True
# Set up parameter values
db = 'testString'
bulk_docs = bulk_docs_model
# Invoke method
response = _service.post_bulk_docs(
db,
bulk_docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == bulk_docs
def test_post_bulk_docs_all_params_with_retries(self):
# Enable retries and run test_post_bulk_docs_all_params.
_service.enable_retries()
self.test_post_bulk_docs_all_params()
# Disable retries and run test_post_bulk_docs_all_params.
_service.disable_retries()
self.test_post_bulk_docs_all_params()
@responses.activate
def test_post_bulk_docs_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_docs')
mock_response = '[{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}]'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a dict representation of a BulkDocs model
bulk_docs_model = {}
bulk_docs_model['docs'] = [document_model]
bulk_docs_model['new_edits'] = True
# Set up parameter values
db = 'testString'
bulk_docs = bulk_docs_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"bulk_docs": bulk_docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_docs(**req_copy)
def test_post_bulk_docs_value_error_with_retries(self):
# Enable retries and run test_post_bulk_docs_value_error.
_service.enable_retries()
self.test_post_bulk_docs_value_error()
# Disable retries and run test_post_bulk_docs_value_error.
_service.disable_retries()
self.test_post_bulk_docs_value_error()
class TestPostBulkGet():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
response = _service.post_bulk_get(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_all_params_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_all_params()
_service.disable_retries()
self.test_post_bulk_get_all_params()
@responses.activate
def test_post_bulk_get_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
db = 'testString'
docs = [bulk_get_query_document_model]
response = _service.post_bulk_get(
db,
docs,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_required_params_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_required_params()
_service.disable_retries()
self.test_post_bulk_get_required_params()
@responses.activate
def test_post_bulk_get_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"results": [{"docs": [{"error": {"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}, "ok": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}}], "id": "id"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'testString'
bulk_get_query_document_model['rev'] = 'testString'
db = 'testString'
docs = [bulk_get_query_document_model]
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get(**req_copy)
def test_post_bulk_get_value_error_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_value_error()
_service.disable_retries()
self.test_post_bulk_get_value_error()
class TestPostBulkGetAsMixed():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_mixed_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get_as_mixed(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_mixed_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_all_params.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_all_params()
# Disable retries and run test_post_bulk_get_as_mixed_all_params.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_all_params()
@responses.activate
def test_post_bulk_get_as_mixed_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get_as_mixed(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_mixed_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_required_params.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_required_params()
# Disable retries and run test_post_bulk_get_as_mixed_required_params.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_required_params()
@responses.activate
def test_post_bulk_get_as_mixed_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_mixed(**req_copy)
def test_post_bulk_get_as_mixed_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_as_mixed_value_error.
_service.enable_retries()
self.test_post_bulk_get_as_mixed_value_error()
# Disable retries and run test_post_bulk_get_as_mixed_value_error.
_service.disable_retries()
self.test_post_bulk_get_as_mixed_value_error()
class TestPostBulkGetAsRelated():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_related_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
response = _service.post_bulk_get_as_related(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_related_all_params_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_as_related_all_params()
_service.disable_retries()
self.test_post_bulk_get_as_related_all_params()
@responses.activate
def test_post_bulk_get_as_related_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
db = 'testString'
docs = [bulk_get_query_document_model]
response = _service.post_bulk_get_as_related(
db,
docs,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
def test_post_bulk_get_as_related_required_params_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_as_related_required_params()
_service.disable_retries()
self.test_post_bulk_get_as_related_required_params()
@responses.activate
def test_post_bulk_get_as_related_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = 'This is a mock binary response.'
responses.add(responses.POST,
url,
body=mock_response,
content_type='multipart/related',
status=200)
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
db = 'testString'
docs = [bulk_get_query_document_model]
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_related(**req_copy)
def test_post_bulk_get_as_related_value_error_with_retries(self):
_service.enable_retries()
self.test_post_bulk_get_as_related_value_error()
_service.disable_retries()
self.test_post_bulk_get_as_related_value_error()
class TestPostBulkGetAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_bulk_get_as_stream_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
attachments = False
att_encoding_info = False
latest = False
revs = False
# Invoke method
response = _service.post_bulk_get_as_stream(
db,
docs,
attachments=attachments,
att_encoding_info=att_encoding_info,
latest=latest,
revs=revs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_bulk_get_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_all_params.
_service.enable_retries()
self.test_post_bulk_get_as_stream_all_params()
# Disable retries and run test_post_bulk_get_as_stream_all_params.
_service.disable_retries()
self.test_post_bulk_get_as_stream_all_params()
@responses.activate
def test_post_bulk_get_as_stream_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Invoke method
response = _service.post_bulk_get_as_stream(
db,
docs,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['docs'] == [bulk_get_query_document_model]
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_bulk_get_as_stream_required_params_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_required_params.
_service.enable_retries()
self.test_post_bulk_get_as_stream_required_params()
# Disable retries and run test_post_bulk_get_as_stream_required_params.
_service.disable_retries()
self.test_post_bulk_get_as_stream_required_params()
@responses.activate
def test_post_bulk_get_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_bulk_get')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a BulkGetQueryDocument model
bulk_get_query_document_model = {}
bulk_get_query_document_model['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model['id'] = 'order00067'
bulk_get_query_document_model['rev'] = '3-917fa2381192822767f010b95b45325b'
# Set up parameter values
db = 'testString'
docs = [bulk_get_query_document_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"docs": docs,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_bulk_get_as_stream(**req_copy)
def test_post_bulk_get_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_bulk_get_as_stream_value_error.
_service.enable_retries()
self.test_post_bulk_get_as_stream_value_error()
# Disable retries and run test_post_bulk_get_as_stream_value_error.
_service.disable_retries()
self.test_post_bulk_get_as_stream_value_error()
class TestDeleteDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_document_all_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
response = _service.delete_document(
db,
doc_id,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_document_all_params_with_retries(self):
_service.enable_retries()
self.test_delete_document_all_params()
_service.disable_retries()
self.test_delete_document_all_params()
@responses.activate
def test_delete_document_required_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
response = _service.delete_document(
db,
doc_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_document_required_params_with_retries(self):
_service.enable_retries()
self.test_delete_document_required_params()
_service.disable_retries()
self.test_delete_document_required_params()
@responses.activate
def test_delete_document_value_error(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_document(**req_copy)
def test_delete_document_value_error_with_retries(self):
_service.enable_retries()
self.test_delete_document_value_error()
_service.disable_retries()
self.test_delete_document_value_error()
class TestGetDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_all_params_with_retries(self):
# Enable retries and run test_get_document_all_params.
_service.enable_retries()
self.test_get_document_all_params()
# Disable retries and run test_get_document_all_params.
_service.disable_retries()
self.test_get_document_all_params()
@responses.activate
def test_get_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_required_params_with_retries(self):
# Enable retries and run test_get_document_required_params.
_service.enable_retries()
self.test_get_document_required_params()
# Disable retries and run test_get_document_required_params.
_service.disable_retries()
self.test_get_document_required_params()
@responses.activate
def test_get_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document(**req_copy)
def test_get_document_value_error_with_retries(self):
# Enable retries and run test_get_document_value_error.
_service.enable_retries()
self.test_get_document_value_error()
# Disable retries and run test_get_document_value_error.
_service.disable_retries()
self.test_get_document_value_error()
class TestGetDocumentAsMixed():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_mixed_all_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
response = _service.get_document_as_mixed(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_as_mixed_all_params_with_retries(self):
_service.enable_retries()
self.test_get_document_as_mixed_all_params()
_service.disable_retries()
self.test_get_document_as_mixed_all_params()
@responses.activate
def test_get_document_as_mixed_required_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
db = 'testString'
doc_id = 'testString'
response = _service.get_document_as_mixed(
db,
doc_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_as_mixed_required_params_with_retries(self):
_service.enable_retries()
self.test_get_document_as_mixed_required_params()
_service.disable_retries()
self.test_get_document_as_mixed_required_params()
@responses.activate
def test_get_document_as_mixed_value_error(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/mixed',
status=200)
db = 'testString'
doc_id = 'testString'
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_mixed(**req_copy)
def test_get_document_as_mixed_value_error_with_retries(self):
_service.enable_retries()
self.test_get_document_as_mixed_value_error()
_service.disable_retries()
self.test_get_document_as_mixed_value_error()
class TestGetDocumentAsRelated():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_related_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
# Invoke method
response = _service.get_document_as_related(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_document_as_related_all_params_with_retries(self):
# Enable retries and run test_get_document_as_related_all_params.
_service.enable_retries()
self.test_get_document_as_related_all_params()
# Disable retries and run test_get_document_as_related_all_params.
_service.disable_retries()
self.test_get_document_as_related_all_params()
@responses.activate
def test_get_document_as_related_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Invoke method
response = _service.get_document_as_related(
db,
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_document_as_related_required_params_with_retries(self):
# Enable retries and run test_get_document_as_related_required_params.
_service.enable_retries()
self.test_get_document_as_related_required_params()
# Disable retries and run test_get_document_as_related_required_params.
_service.disable_retries()
self.test_get_document_as_related_required_params()
@responses.activate
def test_get_document_as_related_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = 'This is a mock binary response.'
responses.add(responses.GET,
url,
body=mock_response,
content_type='multipart/related',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_related(**req_copy)
def test_get_document_as_related_value_error_with_retries(self):
# Enable retries and run test_get_document_as_related_value_error.
_service.enable_retries()
self.test_get_document_as_related_value_error()
# Disable retries and run test_get_document_as_related_value_error.
_service.disable_retries()
self.test_get_document_as_related_value_error()
class TestGetDocumentAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_document_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
response = _service.get_document_as_stream(
db,
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_document_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_get_document_as_stream_all_params()
_service.disable_retries()
self.test_get_document_as_stream_all_params()
@responses.activate
def test_get_document_as_stream_required_params(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
response = _service.get_document_as_stream(
db,
doc_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_document_as_stream_required_params_with_retries(self):
_service.enable_retries()
self.test_get_document_as_stream_required_params()
_service.disable_retries()
self.test_get_document_as_stream_required_params()
@responses.activate
def test_get_document_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
doc_id = 'testString'
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_document_as_stream(**req_copy)
def test_get_document_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_get_document_as_stream_value_error()
_service.disable_retries()
self.test_get_document_as_stream_value_error()
class TestPutDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
content_type = 'application/json'
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_document(
db,
doc_id,
document,
content_type=content_type,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_document_all_params_with_retries(self):
# Enable retries and run test_put_document_all_params.
_service.enable_retries()
self.test_put_document_all_params()
# Disable retries and run test_put_document_all_params.
_service.disable_retries()
self.test_put_document_all_params()
@responses.activate
def test_put_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Invoke method
response = _service.put_document(
db,
doc_id,
document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
def test_put_document_required_params_with_retries(self):
# Enable retries and run test_put_document_required_params.
_service.enable_retries()
self.test_put_document_required_params()
# Disable retries and run test_put_document_required_params.
_service.disable_retries()
self.test_put_document_required_params()
@responses.activate
def test_put_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Document model
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
# Set up parameter values
db = 'testString'
doc_id = 'testString'
document = document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
"document": document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_document(**req_copy)
def test_put_document_value_error_with_retries(self):
# Enable retries and run test_put_document_value_error.
_service.enable_retries()
self.test_put_document_value_error()
# Disable retries and run test_put_document_value_error.
_service.disable_retries()
self.test_put_document_value_error()
# endregion
##############################################################################
# End of Service: Documents
##############################################################################
##############################################################################
# Start of Service: DesignDocuments
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadDesignDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_design_document_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
db = 'testString'
ddoc = 'testString'
if_none_match = 'testString'
response = _service.head_design_document(
db,
ddoc,
if_none_match=if_none_match,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_design_document_all_params_with_retries(self):
_service.enable_retries()
self.test_head_design_document_all_params()
_service.disable_retries()
self.test_head_design_document_all_params()
@responses.activate
def test_head_design_document_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
db = 'testString'
ddoc = 'testString'
response = _service.head_design_document(
db,
ddoc,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_design_document_required_params_with_retries(self):
_service.enable_retries()
self.test_head_design_document_required_params()
_service.disable_retries()
self.test_head_design_document_required_params()
@responses.activate
def test_head_design_document_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
responses.add(responses.HEAD,
url,
status=200)
db = 'testString'
ddoc = 'testString'
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_design_document(**req_copy)
def test_head_design_document_value_error_with_retries(self):
_service.enable_retries()
self.test_head_design_document_value_error()
_service.disable_retries()
self.test_head_design_document_value_error()
class TestDeleteDesignDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_design_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
# Invoke method
response = _service.delete_design_document(
db,
ddoc,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_design_document_all_params_with_retries(self):
# Enable retries and run test_delete_design_document_all_params.
_service.enable_retries()
self.test_delete_design_document_all_params()
# Disable retries and run test_delete_design_document_all_params.
_service.disable_retries()
self.test_delete_design_document_all_params()
@responses.activate
def test_delete_design_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Invoke method
response = _service.delete_design_document(
db,
ddoc,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_design_document_required_params_with_retries(self):
# Enable retries and run test_delete_design_document_required_params.
_service.enable_retries()
self.test_delete_design_document_required_params()
# Disable retries and run test_delete_design_document_required_params.
_service.disable_retries()
self.test_delete_design_document_required_params()
@responses.activate
def test_delete_design_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_design_document(**req_copy)
def test_delete_design_document_value_error_with_retries(self):
# Enable retries and run test_delete_design_document_value_error.
_service.enable_retries()
self.test_delete_design_document_value_error()
# Disable retries and run test_delete_design_document_value_error.
_service.disable_retries()
self.test_delete_design_document_value_error()
class TestGetDesignDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_design_document_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
response = _service.get_design_document(
db,
ddoc,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_design_document_all_params_with_retries(self):
_service.enable_retries()
self.test_get_design_document_all_params()
_service.disable_retries()
self.test_get_design_document_all_params()
@responses.activate
def test_get_design_document_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
response = _service.get_design_document(
db,
ddoc,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_design_document_required_params_with_retries(self):
_service.enable_retries()
self.test_get_design_document_required_params()
_service.disable_retries()
self.test_get_design_document_required_params()
@responses.activate
def test_get_design_document_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "autoupdate": true, "filters": {"mapKey": "inner"}, "indexes": {"mapKey": {"analyzer": {"name": "classic", "stopwords": ["stopwords"], "fields": {"mapKey": {"name": "classic", "stopwords": ["stopwords"]}}}, "index": "index"}}, "language": "javascript", "options": {"partitioned": false}, "validate_doc_update": "validate_doc_update", "views": {"mapKey": {"map": "map", "reduce": "reduce"}}, "st_indexes": {"mapKey": {"index": "index"}}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_design_document(**req_copy)
def test_get_design_document_value_error_with_retries(self):
_service.enable_retries()
self.test_get_design_document_value_error()
_service.disable_retries()
self.test_get_design_document_value_error()
class TestPutDesignDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_design_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_design_document(
db,
ddoc,
design_document,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == design_document
def test_put_design_document_all_params_with_retries(self):
# Enable retries and run test_put_design_document_all_params.
_service.enable_retries()
self.test_put_design_document_all_params()
# Disable retries and run test_put_design_document_all_params.
_service.disable_retries()
self.test_put_design_document_all_params()
@responses.activate
def test_put_design_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
# Invoke method
response = _service.put_design_document(
db,
ddoc,
design_document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == design_document
def test_put_design_document_required_params_with_retries(self):
# Enable retries and run test_put_design_document_required_params.
_service.enable_retries()
self.test_put_design_document_required_params()
# Disable retries and run test_put_design_document_required_params.
_service.disable_retries()
self.test_put_design_document_required_params()
@responses.activate
def test_put_design_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a Analyzer model
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a dict representation of a AnalyzerConfiguration model
analyzer_configuration_model = {}
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a dict representation of a SearchIndexDefinition model
search_index_definition_model = {}
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocumentOptions model
design_document_options_model = {}
design_document_options_model['partitioned'] = True
# Construct a dict representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model = {}
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
# Construct a dict representation of a GeoIndexDefinition model
geo_index_definition_model = {}
geo_index_definition_model['index'] = 'testString'
# Construct a dict representation of a DesignDocument model
design_document_model = {}
design_document_model['_attachments'] = {}
design_document_model['_conflicts'] = ['testString']
design_document_model['_deleted'] = True
design_document_model['_deleted_conflicts'] = ['testString']
design_document_model['_id'] = 'testString'
design_document_model['_local_seq'] = 'testString'
design_document_model['_rev'] = 'testString'
design_document_model['_revisions'] = revisions_model
design_document_model['_revs_info'] = [document_revision_status_model]
design_document_model['autoupdate'] = True
design_document_model['filters'] = {}
design_document_model['indexes'] = {}
design_document_model['language'] = 'javascript'
design_document_model['options'] = design_document_options_model
design_document_model['validate_doc_update'] = 'testString'
design_document_model['views'] = {}
design_document_model['st_indexes'] = {}
design_document_model['foo'] = 'testString'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
design_document = design_document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"design_document": design_document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_design_document(**req_copy)
def test_put_design_document_value_error_with_retries(self):
# Enable retries and run test_put_design_document_value_error.
_service.enable_retries()
self.test_put_design_document_value_error()
# Disable retries and run test_put_design_document_value_error.
_service.disable_retries()
self.test_put_design_document_value_error()
class TestGetDesignDocumentInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_design_document_information_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_info')
mock_response = '{"name": "name", "view_index": {"compact_running": false, "language": "language", "signature": "signature", "sizes": {"active": 6, "external": 8, "file": 4}, "updater_running": false, "waiting_clients": 0, "waiting_commit": true}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
response = _service.get_design_document_information(
db,
ddoc,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_design_document_information_all_params_with_retries(self):
_service.enable_retries()
self.test_get_design_document_information_all_params()
_service.disable_retries()
self.test_get_design_document_information_all_params()
@responses.activate
def test_get_design_document_information_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_info')
mock_response = '{"name": "name", "view_index": {"compact_running": false, "language": "language", "signature": "signature", "sizes": {"active": 6, "external": 8, "file": 4}, "updater_running": false, "waiting_clients": 0, "waiting_commit": true}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
req_param_dict = {
"db": db,
"ddoc": ddoc,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_design_document_information(**req_copy)
def test_get_design_document_information_value_error_with_retries(self):
_service.enable_retries()
self.test_get_design_document_information_value_error()
_service.disable_retries()
self.test_get_design_document_information_value_error()
class TestPostDesignDocs():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_design_docs_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
accept = 'application/json'
# Invoke method
response = _service.post_design_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
accept=accept,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
def test_post_design_docs_all_params_with_retries(self):
# Enable retries and run test_post_design_docs_all_params.
_service.enable_retries()
self.test_post_design_docs_all_params()
# Disable retries and run test_post_design_docs_all_params.
_service.disable_retries()
self.test_post_design_docs_all_params()
@responses.activate
def test_post_design_docs_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Invoke method
response = _service.post_design_docs(
db,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
key=key,
keys=keys,
startkey=startkey,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
def test_post_design_docs_required_params_with_retries(self):
# Enable retries and run test_post_design_docs_required_params.
_service.enable_retries()
self.test_post_design_docs_required_params()
# Disable retries and run test_post_design_docs_required_params.
_service.disable_retries()
self.test_post_design_docs_required_params()
@responses.activate
def test_post_design_docs_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design_docs')
mock_response = '{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_design_docs(**req_copy)
def test_post_design_docs_value_error_with_retries(self):
# Enable retries and run test_post_design_docs_value_error.
_service.enable_retries()
self.test_post_design_docs_value_error()
# Disable retries and run test_post_design_docs_value_error.
_service.disable_retries()
self.test_post_design_docs_value_error()
class TestPostDesignDocsQueries():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_design_docs_queries_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
db = 'testString'
queries = [all_docs_query_model]
accept = 'application/json'
response = _service.post_design_docs_queries(
db,
queries,
accept=accept,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_design_docs_queries_all_params_with_retries(self):
_service.enable_retries()
self.test_post_design_docs_queries_all_params()
_service.disable_retries()
self.test_post_design_docs_queries_all_params()
@responses.activate
def test_post_design_docs_queries_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
db = 'testString'
queries = [all_docs_query_model]
response = _service.post_design_docs_queries(
db,
queries,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [all_docs_query_model]
def test_post_design_docs_queries_required_params_with_retries(self):
_service.enable_retries()
self.test_post_design_docs_queries_required_params()
_service.disable_retries()
self.test_post_design_docs_queries_required_params()
@responses.activate
def test_post_design_docs_queries_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design_docs/queries')
mock_response = '{"results": [{"total_rows": 0, "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "key", "value": {"rev": "rev"}}], "update_seq": "update_seq"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
all_docs_query_model = {}
all_docs_query_model['att_encoding_info'] = False
all_docs_query_model['attachments'] = False
all_docs_query_model['conflicts'] = False
all_docs_query_model['descending'] = False
all_docs_query_model['include_docs'] = False
all_docs_query_model['inclusive_end'] = True
all_docs_query_model['limit'] = 0
all_docs_query_model['skip'] = 0
all_docs_query_model['update_seq'] = False
all_docs_query_model['endkey'] = 'testString'
all_docs_query_model['key'] = 'testString'
all_docs_query_model['keys'] = ['small-appliances:1000042', 'small-appliances:1000043']
all_docs_query_model['startkey'] = 'testString'
db = 'testString'
queries = [all_docs_query_model]
req_param_dict = {
"db": db,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_design_docs_queries(**req_copy)
def test_post_design_docs_queries_value_error_with_retries(self):
_service.enable_retries()
self.test_post_design_docs_queries_value_error()
_service.disable_retries()
self.test_post_design_docs_queries_value_error()
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_as_stream(**req_copy)
def test_post_view_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_view_as_stream_value_error()
_service.disable_retries()
self.test_post_view_as_stream_value_error()
class TestPostViewQueries():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_queries_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"results": [{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = False
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 0
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Invoke method
response = _service.post_view_queries(
db,
ddoc,
view,
queries,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [view_query_model]
def test_post_view_queries_all_params_with_retries(self):
# Enable retries and run test_post_view_queries_all_params.
_service.enable_retries()
self.test_post_view_queries_all_params()
# Disable retries and run test_post_view_queries_all_params.
_service.disable_retries()
self.test_post_view_queries_all_params()
@responses.activate
def test_post_view_queries_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"results": [{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Construct a dict representation of a ViewQuery model
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = False
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 0
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
# Set up parameter values
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_queries(**req_copy)
def test_post_view_queries_value_error_with_retries(self):
# Enable retries and run test_post_view_queries_value_error.
_service.enable_retries()
self.test_post_view_queries_value_error()
# Disable retries and run test_post_view_queries_value_error.
_service.disable_retries()
self.test_post_view_queries_value_error()
class TestPostViewQueriesAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_view_queries_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = True
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 5
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
response = _service.post_view_queries_as_stream(
db,
ddoc,
view,
queries,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['queries'] == [view_query_model]
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_view_queries_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_view_queries_as_stream_all_params()
_service.disable_retries()
self.test_post_view_queries_as_stream_all_params()
@responses.activate
def test_post_view_queries_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_view/testString/queries')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
view_query_model = {}
view_query_model['att_encoding_info'] = False
view_query_model['attachments'] = False
view_query_model['conflicts'] = False
view_query_model['descending'] = False
view_query_model['include_docs'] = True
view_query_model['inclusive_end'] = True
view_query_model['limit'] = 5
view_query_model['skip'] = 0
view_query_model['update_seq'] = False
view_query_model['endkey'] = 'testString'
view_query_model['endkey_docid'] = 'testString'
view_query_model['group'] = False
view_query_model['group_level'] = 1
view_query_model['key'] = 'testString'
view_query_model['keys'] = ['testString']
view_query_model['reduce'] = True
view_query_model['stable'] = False
view_query_model['startkey'] = 'testString'
view_query_model['startkey_docid'] = 'testString'
view_query_model['update'] = 'true'
db = 'testString'
ddoc = 'testString'
view = 'testString'
queries = [view_query_model]
req_param_dict = {
"db": db,
"ddoc": ddoc,
"view": view,
"queries": queries,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_view_queries_as_stream(**req_copy)
def test_post_view_queries_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_view_queries_as_stream_value_error()
_service.disable_retries()
self.test_post_view_queries_as_stream_value_error()
req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == False
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['testString']
assert req_body['startkey'] == '0007741142412418284'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_all_docs_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_all_docs_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_all_docs_as_stream_all_params()
# Disable retries and run test_post_partition_all_docs_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_all_docs_as_stream_all_params()
@responses.activate
def test_post_partition_all_docs_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_all_docs')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = False
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
key = 'testString'
keys = ['testString']
startkey = '0007741142412418284'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_all_docs_as_stream(**req_copy)
def test_post_partition_all_docs_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_all_docs_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_all_docs_as_stream_value_error()
# Disable retries and run test_post_partition_all_docs_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_all_docs_as_stream_value_error()
class TestPostPartitionSearch():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_search_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
response = _service.post_partition_search(
db,
partition_key,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
def test_post_partition_search_all_params_with_retries(self):
_service.enable_retries()
self.test_post_partition_search_all_params()
_service.disable_retries()
self.test_post_partition_search_all_params()
@responses.activate
def test_post_partition_search_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_search(**req_copy)
def test_post_partition_search_value_error_with_retries(self):
_service.enable_retries()
self.test_post_partition_search_value_error()
_service.disable_retries()
self.test_post_partition_search_value_error()
class TestPostPartitionSearchAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_search_as_stream_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
# Invoke method
response = _service.post_partition_search_as_stream(
db,
partition_key,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 3
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_search_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_search_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_search_as_stream_all_params()
# Disable retries and run test_post_partition_search_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_search_as_stream_all_params()
@responses.activate
def test_post_partition_search_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_search_as_stream(**req_copy)
def test_post_partition_search_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_search_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_search_as_stream_value_error()
# Disable retries and run test_post_partition_search_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_search_as_stream_value_error()
class TestPostPartitionView():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_view_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
response = _service.post_partition_view(
db,
partition_key,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == True
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['examplekey']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
def test_post_partition_view_all_params_with_retries(self):
_service.enable_retries()
self.test_post_partition_view_all_params()
_service.disable_retries()
self.test_post_partition_view_all_params()
@responses.activate
def test_post_partition_view_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"total_rows": 0, "update_seq": "update_seq", "rows": [{"caused_by": "caused_by", "error": "error", "reason": "reason", "doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "id": "id", "key": "anyValue", "value": "anyValue"}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_view(**req_copy)
def test_post_partition_view_value_error_with_retries(self):
_service.enable_retries()
self.test_post_partition_view_value_error()
_service.disable_retries()
self.test_post_partition_view_value_error()
class TestPostPartitionViewAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_view_as_stream_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Invoke method
response = _service.post_partition_view_as_stream(
db,
partition_key,
ddoc,
view,
att_encoding_info=att_encoding_info,
attachments=attachments,
conflicts=conflicts,
descending=descending,
include_docs=include_docs,
inclusive_end=inclusive_end,
limit=limit,
skip=skip,
update_seq=update_seq,
endkey=endkey,
endkey_docid=endkey_docid,
group=group,
group_level=group_level,
key=key,
keys=keys,
reduce=reduce,
stable=stable,
startkey=startkey,
startkey_docid=startkey_docid,
update=update,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['att_encoding_info'] == False
assert req_body['attachments'] == False
assert req_body['conflicts'] == False
assert req_body['descending'] == False
assert req_body['include_docs'] == True
assert req_body['inclusive_end'] == True
assert req_body['limit'] == 10
assert req_body['skip'] == 0
assert req_body['update_seq'] == False
assert req_body['endkey'] == 'testString'
assert req_body['endkey_docid'] == 'testString'
assert req_body['group'] == False
assert req_body['group_level'] == 1
assert req_body['key'] == 'testString'
assert req_body['keys'] == ['examplekey']
assert req_body['reduce'] == True
assert req_body['stable'] == False
assert req_body['startkey'] == 'testString'
assert req_body['startkey_docid'] == 'testString'
assert req_body['update'] == 'true'
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_view_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_view_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_view_as_stream_all_params()
# Disable retries and run test_post_partition_view_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_view_as_stream_all_params()
@responses.activate
def test_post_partition_view_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_design/testString/_view/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
ddoc = 'testString'
view = 'testString'
att_encoding_info = False
attachments = False
conflicts = False
descending = False
include_docs = True
inclusive_end = True
limit = 10
skip = 0
update_seq = False
endkey = 'testString'
endkey_docid = 'testString'
group = False
group_level = 1
key = 'testString'
keys = ['examplekey']
reduce = True
stable = False
startkey = 'testString'
startkey_docid = 'testString'
update = 'true'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"ddoc": ddoc,
"view": view,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_view_as_stream(**req_copy)
def test_post_partition_view_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_view_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_view_as_stream_value_error()
# Disable retries and run test_post_partition_view_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_view_as_stream_value_error()
class TestPostPartitionFind():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_find_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
response = _service.post_partition_find(
db,
partition_key,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
def test_post_partition_find_all_params_with_retries(self):
_service.enable_retries()
self.test_post_partition_find_all_params()
_service.disable_retries()
self.test_post_partition_find_all_params()
@responses.activate
def test_post_partition_find_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
req_param_dict = {
"db": db,
"partition_key": partition_key,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_find(**req_copy)
def test_post_partition_find_value_error_with_retries(self):
_service.enable_retries()
self.test_post_partition_find_value_error()
_service.disable_retries()
self.test_post_partition_find_value_error()
class TestPostPartitionFindAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_partition_find_as_stream_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['productid', 'name', 'description']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Invoke method
response = _service.post_partition_find_as_stream(
db,
partition_key,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['productid', 'name', 'description']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_partition_find_as_stream_all_params_with_retries(self):
# Enable retries and run test_post_partition_find_as_stream_all_params.
_service.enable_retries()
self.test_post_partition_find_as_stream_all_params()
# Disable retries and run test_post_partition_find_as_stream_all_params.
_service.disable_retries()
self.test_post_partition_find_as_stream_all_params()
@responses.activate
def test_post_partition_find_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_partition/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
partition_key = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['productid', 'name', 'description']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"partition_key": partition_key,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_partition_find_as_stream(**req_copy)
def test_post_partition_find_as_stream_value_error_with_retries(self):
# Enable retries and run test_post_partition_find_as_stream_value_error.
_service.enable_retries()
self.test_post_partition_find_as_stream_value_error()
# Disable retries and run test_post_partition_find_as_stream_value_error.
_service.disable_retries()
self.test_post_partition_find_as_stream_value_error()
# endregion
##############################################################################
# End of Service: PartitionedDatabases
##############################################################################
##############################################################################
# Start of Service: Queries
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostExplain():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_explain_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_explain')
mock_response = '{"dbname": "dbname", "fields": ["fields"], "index": {"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}, "limit": 0, "opts": {"mapKey": "anyValue"}, "range": {"end_key": ["anyValue"], "start_key": ["anyValue"]}, "selector": {"mapKey": "anyValue"}, "skip": 0}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
response = _service.post_explain(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
def test_post_explain_all_params_with_retries(self):
_service.enable_retries()
self.test_post_explain_all_params()
_service.disable_retries()
self.test_post_explain_all_params()
@responses.activate
def test_post_explain_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_explain')
mock_response = '{"dbname": "dbname", "fields": ["fields"], "index": {"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}, "limit": 0, "opts": {"mapKey": "anyValue"}, "range": {"end_key": ["anyValue"], "start_key": ["anyValue"]}, "selector": {"mapKey": "anyValue"}, "skip": 0}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['testString']
limit = 0
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_explain(**req_copy)
def test_post_explain_value_error_with_retries(self):
_service.enable_retries()
self.test_post_explain_value_error()
_service.disable_retries()
self.test_post_explain_value_error()
class TestPostFind():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_find_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Invoke method
response = _service.post_find(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['_id', 'type', 'name', 'email']
assert req_body['limit'] == 3
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
def test_post_find_all_params_with_retries(self):
# Enable retries and run test_post_find_all_params.
_service.enable_retries()
self.test_post_find_all_params()
# Disable retries and run test_post_find_all_params.
_service.disable_retries()
self.test_post_find_all_params()
@responses.activate
def test_post_find_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"bookmark": "bookmark", "docs": [{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}], "execution_stats": {"execution_time_ms": 17, "results_returned": 0, "total_docs_examined": 0, "total_keys_examined": 0, "total_quorum_docs_examined": 0}, "warning": "warning"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_find(**req_copy)
def test_post_find_value_error_with_retries(self):
# Enable retries and run test_post_find_value_error.
_service.enable_retries()
self.test_post_find_value_error()
# Disable retries and run test_post_find_value_error.
_service.disable_retries()
self.test_post_find_value_error()
class TestPostFindAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_find_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
response = _service.post_find_as_stream(
db,
selector,
bookmark=bookmark,
conflicts=conflicts,
execution_stats=execution_stats,
fields=fields,
limit=limit,
skip=skip,
sort=sort,
stable=stable,
update=update,
use_index=use_index,
r=r,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['selector'] == {}
assert req_body['bookmark'] == 'testString'
assert req_body['conflicts'] == True
assert req_body['execution_stats'] == True
assert req_body['fields'] == ['_id', 'type', 'name', 'email']
assert req_body['limit'] == 3
assert req_body['skip'] == 0
assert req_body['sort'] == [{}]
assert req_body['stable'] == True
assert req_body['update'] == 'true'
assert req_body['use_index'] == ['testString']
assert req_body['r'] == 1
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_find_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_find_as_stream_all_params()
_service.disable_retries()
self.test_post_find_as_stream_all_params()
@responses.activate
def test_post_find_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_find')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
selector = {}
bookmark = 'testString'
conflicts = True
execution_stats = True
fields = ['_id', 'type', 'name', 'email']
limit = 3
skip = 0
sort = [{}]
stable = True
update = 'true'
use_index = ['testString']
r = 1
req_param_dict = {
"db": db,
"selector": selector,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_find_as_stream(**req_copy)
def test_post_find_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_find_as_stream_value_error()
_service.disable_retries()
self.test_post_find_as_stream_value_error()
class TestGetIndexesInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_indexes_information_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"total_rows": 0, "indexes": [{"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Invoke method
response = _service.get_indexes_information(
db,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_indexes_information_all_params_with_retries(self):
# Enable retries and run test_get_indexes_information_all_params.
_service.enable_retries()
self.test_get_indexes_information_all_params()
# Disable retries and run test_get_indexes_information_all_params.
_service.disable_retries()
self.test_get_indexes_information_all_params()
@responses.activate
def test_get_indexes_information_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"total_rows": 0, "indexes": [{"ddoc": "ddoc", "def": {"default_analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "default_field": {"analyzer": {"name": "classic", "stopwords": ["stopwords"]}, "enabled": true}, "fields": [{"name": "name", "type": "boolean"}], "index_array_lengths": true, "partial_filter_selector": {"mapKey": "anyValue"}}, "name": "name", "type": "json"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_indexes_information(**req_copy)
def test_get_indexes_information_value_error_with_retries(self):
# Enable retries and run test_get_indexes_information_value_error.
_service.enable_retries()
self.test_get_indexes_information_value_error()
# Disable retries and run test_get_indexes_information_value_error.
_service.disable_retries()
self.test_get_indexes_information_value_error()
class TestPostIndex():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_index_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"id": "id", "name": "name", "result": "created"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {}
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {}
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {}
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
db = 'testString'
index = index_definition_model
ddoc = 'testString'
def_ = index_definition_model
name = 'testString'
partitioned = True
type = 'json'
response = _service.post_index(
db,
index,
ddoc=ddoc,
def_=def_,
name=name,
partitioned=partitioned,
type=type,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['index'] == index_definition_model
assert req_body['ddoc'] == 'testString'
assert req_body['def'] == index_definition_model
assert req_body['name'] == 'testString'
assert req_body['partitioned'] == True
assert req_body['type'] == 'json'
def test_post_index_all_params_with_retries(self):
_service.enable_retries()
self.test_post_index_all_params()
_service.disable_retries()
self.test_post_index_all_params()
@responses.activate
def test_post_index_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_index')
mock_response = '{"id": "id", "name": "name", "result": "created"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
analyzer_model = {}
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {}
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {}
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {}
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
db = 'testString'
index = index_definition_model
ddoc = 'testString'
def_ = index_definition_model
name = 'testString'
partitioned = True
type = 'json'
req_param_dict = {
"db": db,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_index(**req_copy)
def test_post_index_value_error_with_retries(self):
_service.enable_retries()
self.test_post_index_value_error()
_service.disable_retries()
self.test_post_index_value_error()
class TestDeleteIndex():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_index_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index/_design/testString/json/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
type = 'json'
index = 'testString'
# Invoke method
response = _service.delete_index(
db,
ddoc,
type,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_delete_index_all_params_with_retries(self):
# Enable retries and run test_delete_index_all_params.
_service.enable_retries()
self.test_delete_index_all_params()
# Disable retries and run test_delete_index_all_params.
_service.disable_retries()
self.test_delete_index_all_params()
@responses.activate
def test_delete_index_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_index/_design/testString/json/testString')
mock_response = '{"ok": true}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
type = 'json'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"type": type,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_index(**req_copy)
def test_delete_index_value_error_with_retries(self):
# Enable retries and run test_delete_index_value_error.
_service.enable_retries()
self.test_delete_index_value_error()
# Disable retries and run test_delete_index_value_error.
_service.disable_retries()
self.test_delete_index_value_error()
# endregion
##############################################################################
# End of Service: Queries
##############################################################################
##############################################################################
# Start of Service: Searches
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestPostSearchAnalyze():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_analyze_all_params(self):
url = self.preprocess_url(_base_url + '/_search_analyze')
mock_response = '{"tokens": ["tokens"]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
analyzer = 'arabic'
text = 'testString'
response = _service.post_search_analyze(
analyzer,
text,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['analyzer'] == 'arabic'
assert req_body['text'] == 'testString'
def test_post_search_analyze_all_params_with_retries(self):
_service.enable_retries()
self.test_post_search_analyze_all_params()
_service.disable_retries()
self.test_post_search_analyze_all_params()
@responses.activate
def test_post_search_analyze_value_error(self):
url = self.preprocess_url(_base_url + '/_search_analyze')
mock_response = '{"tokens": ["tokens"]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
analyzer = 'arabic'
text = 'testString'
req_param_dict = {
"analyzer": analyzer,
"text": text,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search_analyze(**req_copy)
def test_post_search_analyze_value_error_with_retries(self):
_service.enable_retries()
self.test_post_search_analyze_value_error()
_service.disable_retries()
self.test_post_search_analyze_value_error()
class TestPostSearch():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Invoke method
response = _service.post_search(
db,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
counts=counts,
drilldown=drilldown,
group_field=group_field,
group_limit=group_limit,
group_sort=group_sort,
ranges=ranges,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 0
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
assert req_body['counts'] == ['testString']
assert req_body['drilldown'] == [['testString']]
assert req_body['group_field'] == 'testString'
assert req_body['group_limit'] == 1
assert req_body['group_sort'] == ['testString']
assert req_body['ranges'] == {}
def test_post_search_all_params_with_retries(self):
# Enable retries and run test_post_search_all_params.
_service.enable_retries()
self.test_post_search_all_params()
# Disable retries and run test_post_search_all_params.
_service.disable_retries()
self.test_post_search_all_params()
@responses.activate
def test_post_search_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}], "groups": [{"total_rows": 0, "bookmark": "bookmark", "by": "by", "counts": {"mapKey": {"mapKey": 0}}, "ranges": {"mapKey": {"mapKey": 0}}, "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "fields": {"mapKey": "anyValue"}, "highlights": {"mapKey": ["inner"]}, "id": "id"}]}]}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 0
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search(**req_copy)
def test_post_search_value_error_with_retries(self):
# Enable retries and run test_post_search_value_error.
_service.enable_retries()
self.test_post_search_value_error()
# Disable retries and run test_post_search_value_error.
_service.disable_retries()
self.test_post_search_value_error()
class TestPostSearchAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_search_as_stream_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
response = _service.post_search_as_stream(
db,
ddoc,
index,
query,
bookmark=bookmark,
highlight_fields=highlight_fields,
highlight_number=highlight_number,
highlight_post_tag=highlight_post_tag,
highlight_pre_tag=highlight_pre_tag,
highlight_size=highlight_size,
include_docs=include_docs,
include_fields=include_fields,
limit=limit,
sort=sort,
stale=stale,
counts=counts,
drilldown=drilldown,
group_field=group_field,
group_limit=group_limit,
group_sort=group_sort,
ranges=ranges,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['query'] == 'testString'
assert req_body['bookmark'] == 'testString'
assert req_body['highlight_fields'] == ['testString']
assert req_body['highlight_number'] == 1
assert req_body['highlight_post_tag'] == '</em>'
assert req_body['highlight_pre_tag'] == '<em>'
assert req_body['highlight_size'] == 1
assert req_body['include_docs'] == False
assert req_body['include_fields'] == ['testString']
assert req_body['limit'] == 3
assert req_body['sort'] == ['testString']
assert req_body['stale'] == 'ok'
assert req_body['counts'] == ['testString']
assert req_body['drilldown'] == [['testString']]
assert req_body['group_field'] == 'testString'
assert req_body['group_limit'] == 1
assert req_body['group_sort'] == ['testString']
assert req_body['ranges'] == {}
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_post_search_as_stream_all_params_with_retries(self):
_service.enable_retries()
self.test_post_search_as_stream_all_params()
_service.disable_retries()
self.test_post_search_as_stream_all_params()
@responses.activate
def test_post_search_as_stream_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
index = 'testString'
query = 'testString'
bookmark = 'testString'
highlight_fields = ['testString']
highlight_number = 1
highlight_post_tag = '</em>'
highlight_pre_tag = '<em>'
highlight_size = 1
include_docs = False
include_fields = ['testString']
limit = 3
sort = ['testString']
stale = 'ok'
counts = ['testString']
drilldown = [['testString']]
group_field = 'testString'
group_limit = 1
group_sort = ['testString']
ranges = {}
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
"query": query,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_search_as_stream(**req_copy)
def test_post_search_as_stream_value_error_with_retries(self):
_service.enable_retries()
self.test_post_search_as_stream_value_error()
_service.disable_retries()
self.test_post_search_as_stream_value_error()
class TestGetSearchInfo():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_search_info_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search_info/testString')
mock_response = '{"name": "name", "search_index": {"committed_seq": 13, "disk_size": 0, "doc_count": 0, "doc_del_count": 0, "pending_seq": 11}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_search_info(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_search_info_all_params_with_retries(self):
# Enable retries and run test_get_search_info_all_params.
_service.enable_retries()
self.test_get_search_info_all_params()
# Disable retries and run test_get_search_info_all_params.
_service.disable_retries()
self.test_get_search_info_all_params()
@responses.activate
def test_get_search_info_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_search_info/testString')
mock_response = '{"name": "name", "search_index": {"committed_seq": 13, "disk_size": 0, "doc_count": 0, "doc_del_count": 0, "pending_seq": 11}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_search_info(**req_copy)
def test_get_search_info_value_error_with_retries(self):
# Enable retries and run test_get_search_info_value_error.
_service.enable_retries()
self.test_get_search_info_value_error()
# Disable retries and run test_get_search_info_value_error.
_service.disable_retries()
self.test_get_search_info_value_error()
# endregion
##############################################################################
# End of Service: Searches
##############################################################################
##############################################################################
# Start of Service: Geospatial
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetGeo():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
index = 'testString'
bbox = 'testString'
bookmark = 'testString'
format = 'view'
g = 'testString'
include_docs = False
lat = -90
limit = 0
lon = -180
nearest = False
radius = 0
rangex = 0
rangey = 0
relation = 'intersects'
skip = 0
stale = 'ok'
response = _service.get_geo(
db,
ddoc,
index,
bbox=bbox,
bookmark=bookmark,
format=format,
g=g,
include_docs=include_docs,
lat=lat,
limit=limit,
lon=lon,
nearest=nearest,
radius=radius,
rangex=rangex,
rangey=rangey,
relation=relation,
skip=skip,
stale=stale,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'bbox={}'.format(bbox) in query_string
assert 'bookmark={}'.format(bookmark) in query_string
assert 'format={}'.format(format) in query_string
assert 'g={}'.format(g) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'lat={}'.format(lat) in query_string
assert 'limit={}'.format(limit) in query_string
assert 'lon={}'.format(lon) in query_string
assert 'nearest={}'.format('true' if nearest else 'false') in query_string
assert 'radius={}'.format(radius) in query_string
assert 'rangex={}'.format(rangex) in query_string
assert 'rangey={}'.format(rangey) in query_string
assert 'relation={}'.format(relation) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'stale={}'.format(stale) in query_string
def test_get_geo_all_params_with_retries(self):
_service.enable_retries()
self.test_get_geo_all_params()
_service.disable_retries()
self.test_get_geo_all_params()
@responses.activate
def test_get_geo_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
index = 'testString'
response = _service.get_geo(
db,
ddoc,
index,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_geo_required_params_with_retries(self):
_service.enable_retries()
self.test_get_geo_required_params()
_service.disable_retries()
self.test_get_geo_required_params()
@responses.activate
def test_get_geo_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"bookmark": "bookmark", "features": [{"_id": "id", "_rev": "rev", "bbox": [4], "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "properties": {"mapKey": "anyValue"}, "type": "Feature"}], "rows": [{"doc": {"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}]}, "geometry": {"type": "Point", "coordinates": ["anyValue"]}, "id": "id", "rev": "rev"}], "type": "FeatureCollection"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
db = 'testString'
ddoc = 'testString'
index = 'testString'
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo(**req_copy)
def test_get_geo_value_error_with_retries(self):
_service.enable_retries()
self.test_get_geo_value_error()
_service.disable_retries()
self.test_get_geo_value_error()
class TestGetGeoAsStream():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_as_stream_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
bbox = 'testString'
bookmark = 'testString'
format = 'view'
g = 'testString'
include_docs = False
lat = -90
limit = 0
lon = -180
nearest = False
radius = 0
rangex = 0
rangey = 0
relation = 'intersects'
skip = 0
stale = 'ok'
# Invoke method
response = _service.get_geo_as_stream(
db,
ddoc,
index,
bbox=bbox,
bookmark=bookmark,
format=format,
g=g,
include_docs=include_docs,
lat=lat,
limit=limit,
lon=lon,
nearest=nearest,
radius=radius,
rangex=rangex,
rangey=rangey,
relation=relation,
skip=skip,
stale=stale,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'bbox={}'.format(bbox) in query_string
assert 'bookmark={}'.format(bookmark) in query_string
assert 'format={}'.format(format) in query_string
assert 'g={}'.format(g) in query_string
assert 'include_docs={}'.format('true' if include_docs else 'false') in query_string
assert 'lat={}'.format(lat) in query_string
assert 'limit={}'.format(limit) in query_string
assert 'lon={}'.format(lon) in query_string
assert 'nearest={}'.format('true' if nearest else 'false') in query_string
assert 'radius={}'.format(radius) in query_string
assert 'rangex={}'.format(rangex) in query_string
assert 'rangey={}'.format(rangey) in query_string
assert 'relation={}'.format(relation) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'stale={}'.format(stale) in query_string
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_geo_as_stream_all_params_with_retries(self):
# Enable retries and run test_get_geo_as_stream_all_params.
_service.enable_retries()
self.test_get_geo_as_stream_all_params()
# Disable retries and run test_get_geo_as_stream_all_params.
_service.disable_retries()
self.test_get_geo_as_stream_all_params()
@responses.activate
def test_get_geo_as_stream_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_geo_as_stream(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
# Verify streamed JSON response
result = response.get_result()
assert isinstance(result, requests.models.Response)
response_buf = result.iter_content(chunk_size=1024)
assert str(next(response_buf), "utf-8") == mock_response
def test_get_geo_as_stream_required_params_with_retries(self):
# Enable retries and run test_get_geo_as_stream_required_params.
_service.enable_retries()
self.test_get_geo_as_stream_required_params()
# Disable retries and run test_get_geo_as_stream_required_params.
_service.disable_retries()
self.test_get_geo_as_stream_required_params()
@responses.activate
def test_get_geo_as_stream_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo/testString')
mock_response = '{"foo": "this is a mock response for JSON streaming"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo_as_stream(**req_copy)
def test_get_geo_as_stream_value_error_with_retries(self):
# Enable retries and run test_get_geo_as_stream_value_error.
_service.enable_retries()
self.test_get_geo_as_stream_value_error()
# Disable retries and run test_get_geo_as_stream_value_error.
_service.disable_retries()
self.test_get_geo_as_stream_value_error()
class TestPostGeoCleanup():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_geo_cleanup_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_geo_cleanup')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=202)
db = 'testString'
response = _service.post_geo_cleanup(
db,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 202
def test_post_geo_cleanup_all_params_with_retries(self):
_service.enable_retries()
self.test_post_geo_cleanup_all_params()
_service.disable_retries()
self.test_post_geo_cleanup_all_params()
@responses.activate
def test_post_geo_cleanup_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_geo_cleanup')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=202)
db = 'testString'
req_param_dict = {
"db": db,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_geo_cleanup(**req_copy)
def test_post_geo_cleanup_value_error_with_retries(self):
_service.enable_retries()
self.test_post_geo_cleanup_value_error()
_service.disable_retries()
self.test_post_geo_cleanup_value_error()
class TestGetGeoIndexInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_geo_index_information_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo_info/testString')
mock_response = '{"geo_index": {"data_size": 0, "disk_size": 0, "doc_count": 0}, "name": "name"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Invoke method
response = _service.get_geo_index_information(
db,
ddoc,
index,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_geo_index_information_all_params_with_retries(self):
# Enable retries and run test_get_geo_index_information_all_params.
_service.enable_retries()
self.test_get_geo_index_information_all_params()
# Disable retries and run test_get_geo_index_information_all_params.
_service.disable_retries()
self.test_get_geo_index_information_all_params()
@responses.activate
def test_get_geo_index_information_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/testString/_design/testString/_geo_info/testString')
mock_response = '{"geo_index": {"data_size": 0, "disk_size": 0, "doc_count": 0}, "name": "name"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
ddoc = 'testString'
index = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"ddoc": ddoc,
"index": index,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_geo_index_information(**req_copy)
def test_get_geo_index_information_value_error_with_retries(self):
# Enable retries and run test_get_geo_index_information_value_error.
_service.enable_retries()
self.test_get_geo_index_information_value_error()
# Disable retries and run test_get_geo_index_information_value_error.
_service.disable_retries()
self.test_get_geo_index_information_value_error()
# endregion
##############################################################################
# End of Service: Geospatial
##############################################################################
##############################################################################
# Start of Service: Replication
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestHeadReplicationDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_replication_document_all_params(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
doc_id = 'testString'
if_none_match = 'testString'
response = _service.head_replication_document(
doc_id,
if_none_match=if_none_match,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_replication_document_all_params_with_retries(self):
_service.enable_retries()
self.test_head_replication_document_all_params()
_service.disable_retries()
self.test_head_replication_document_all_params()
@responses.activate
def test_head_replication_document_required_params(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
doc_id = 'testString'
response = _service.head_replication_document(
doc_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_replication_document_required_params_with_retries(self):
_service.enable_retries()
self.test_head_replication_document_required_params()
_service.disable_retries()
self.test_head_replication_document_required_params()
@responses.activate
def test_head_replication_document_value_error(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
doc_id = 'testString'
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_replication_document(**req_copy)
def test_head_replication_document_value_error_with_retries(self):
_service.enable_retries()
self.test_head_replication_document_value_error()
_service.disable_retries()
self.test_head_replication_document_value_error()
class TestHeadSchedulerDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_scheduler_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.head_scheduler_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_scheduler_document_all_params_with_retries(self):
# Enable retries and run test_head_scheduler_document_all_params.
_service.enable_retries()
self.test_head_scheduler_document_all_params()
# Disable retries and run test_head_scheduler_document_all_params.
_service.disable_retries()
self.test_head_scheduler_document_all_params()
@responses.activate
def test_head_scheduler_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
responses.add(responses.HEAD,
url,
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_scheduler_document(**req_copy)
def test_head_scheduler_document_value_error_with_retries(self):
# Enable retries and run test_head_scheduler_document_value_error.
_service.enable_retries()
self.test_head_scheduler_document_value_error()
# Disable retries and run test_head_scheduler_document_value_error.
_service.disable_retries()
self.test_head_scheduler_document_value_error()
class TestHeadSchedulerJob():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_head_scheduler_job_all_params(self):
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
responses.add(responses.HEAD,
url,
status=200)
job_id = 'testString'
response = _service.head_scheduler_job(
job_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_head_scheduler_job_all_params_with_retries(self):
_service.enable_retries()
self.test_head_scheduler_job_all_params()
_service.disable_retries()
self.test_head_scheduler_job_all_params()
@responses.activate
def test_head_scheduler_job_value_error(self):
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
responses.add(responses.HEAD,
url,
status=200)
job_id = 'testString'
req_param_dict = {
"job_id": job_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.head_scheduler_job(**req_copy)
def test_head_scheduler_job_value_error_with_retries(self):
_service.enable_retries()
self.test_head_scheduler_job_value_error()
_service.disable_retries()
self.test_head_scheduler_job_value_error()
class TestDeleteReplicationDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_delete_replication_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
if_match = 'testString'
batch = 'ok'
rev = 'testString'
# Invoke method
response = _service.delete_replication_document(
doc_id,
if_match=if_match,
batch=batch,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'rev={}'.format(rev) in query_string
def test_delete_replication_document_all_params_with_retries(self):
# Enable retries and run test_delete_replication_document_all_params.
_service.enable_retries()
self.test_delete_replication_document_all_params()
# Disable retries and run test_delete_replication_document_all_params.
_service.disable_retries()
self.test_delete_replication_document_all_params()
@responses.activate
def test_delete_replication_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.delete_replication_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
def test_delete_replication_document_required_params_with_retries(self):
# Enable retries and run test_delete_replication_document_required_params.
_service.enable_retries()
self.test_delete_replication_document_required_params()
# Disable retries and run test_delete_replication_document_required_params.
_service.disable_retries()
self.test_delete_replication_document_required_params()
@responses.activate
def test_delete_replication_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.DELETE,
url,
body=mock_response,
content_type='application/json',
status=201)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.delete_replication_document(**req_copy)
def test_delete_replication_document_value_error_with_retries(self):
# Enable retries and run test_delete_replication_document_value_error.
_service.enable_retries()
self.test_delete_replication_document_value_error()
# Disable retries and run test_delete_replication_document_value_error.
_service.disable_retries()
self.test_delete_replication_document_value_error()
class TestGetReplicationDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_replication_document_all_params(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
doc_id = 'testString'
if_none_match = 'testString'
attachments = False
att_encoding_info = False
conflicts = False
deleted_conflicts = False
latest = False
local_seq = False
meta = False
rev = 'testString'
revs = False
revs_info = False
response = _service.get_replication_document(
doc_id,
if_none_match=if_none_match,
attachments=attachments,
att_encoding_info=att_encoding_info,
conflicts=conflicts,
deleted_conflicts=deleted_conflicts,
latest=latest,
local_seq=local_seq,
meta=meta,
rev=rev,
revs=revs,
revs_info=revs_info,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'attachments={}'.format('true' if attachments else 'false') in query_string
assert 'att_encoding_info={}'.format('true' if att_encoding_info else 'false') in query_string
assert 'conflicts={}'.format('true' if conflicts else 'false') in query_string
assert 'deleted_conflicts={}'.format('true' if deleted_conflicts else 'false') in query_string
assert 'latest={}'.format('true' if latest else 'false') in query_string
assert 'local_seq={}'.format('true' if local_seq else 'false') in query_string
assert 'meta={}'.format('true' if meta else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
assert 'revs={}'.format('true' if revs else 'false') in query_string
assert 'revs_info={}'.format('true' if revs_info else 'false') in query_string
def test_get_replication_document_all_params_with_retries(self):
_service.enable_retries()
self.test_get_replication_document_all_params()
_service.disable_retries()
self.test_get_replication_document_all_params()
@responses.activate
def test_get_replication_document_required_params(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
doc_id = 'testString'
response = _service.get_replication_document(
doc_id,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_replication_document_required_params_with_retries(self):
_service.enable_retries()
self.test_get_replication_document_required_params()
_service.disable_retries()
self.test_get_replication_document_required_params()
@responses.activate
def test_get_replication_document_value_error(self):
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"_attachments": {"mapKey": {"content_type": "content_type", "data": "VGhpcyBpcyBhbiBlbmNvZGVkIGJ5dGUgYXJyYXku", "digest": "digest", "encoded_length": 0, "encoding": "encoding", "follows": false, "length": 0, "revpos": 1, "stub": true}}, "_conflicts": ["conflicts"], "_deleted": false, "_deleted_conflicts": ["deleted_conflicts"], "_id": "id", "_local_seq": "local_seq", "_rev": "rev", "_revisions": {"ids": ["ids"], "start": 1}, "_revs_info": [{"rev": "rev", "status": "available"}], "cancel": true, "checkpoint_interval": 0, "connection_timeout": 0, "continuous": false, "create_target": false, "create_target_params": {"n": 1, "partitioned": false, "q": 1}, "doc_ids": ["doc_ids"], "filter": "filter", "http_connections": 1, "query_params": {"mapKey": "inner"}, "retries_per_request": 0, "selector": {"mapKey": "anyValue"}, "since_seq": "since_seq", "socket_options": "socket_options", "source": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "source_proxy": "source_proxy", "target": {"auth": {"basic": {"password": "password", "username": "username"}, "iam": {"api_key": "api_key"}}, "headers": {"mapKey": "inner"}, "url": "url"}, "target_proxy": "target_proxy", "use_checkpoints": true, "user_ctx": {"db": "db", "name": "name", "roles": ["_reader"]}, "worker_batch_size": 1, "worker_processes": 1}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
doc_id = 'testString'
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_replication_document(**req_copy)
def test_get_replication_document_value_error_with_retries(self):
_service.enable_retries()
self.test_get_replication_document_value_error()
_service.disable_retries()
self.test_get_replication_document_value_error()
class TestPutReplicationDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_replication_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
if_match = 'testString'
batch = 'ok'
new_edits = False
rev = 'testString'
# Invoke method
response = _service.put_replication_document(
doc_id,
replication_document,
if_match=if_match,
batch=batch,
new_edits=new_edits,
rev=rev,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# Validate query params
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
assert 'new_edits={}'.format('true' if new_edits else 'false') in query_string
assert 'rev={}'.format(rev) in query_string
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == replication_document
def test_put_replication_document_all_params_with_retries(self):
# Enable retries and run test_put_replication_document_all_params.
_service.enable_retries()
self.test_put_replication_document_all_params()
# Disable retries and run test_put_replication_document_all_params.
_service.disable_retries()
self.test_put_replication_document_all_params()
@responses.activate
def test_put_replication_document_required_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
# Invoke method
response = _service.put_replication_document(
doc_id,
replication_document,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 201
# decompress gzip compressed request body
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
# Validate body params
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body == replication_document
def test_put_replication_document_required_params_with_retries(self):
# Enable retries and run test_put_replication_document_required_params.
_service.enable_retries()
self.test_put_replication_document_required_params()
# Disable retries and run test_put_replication_document_required_params.
_service.disable_retries()
self.test_put_replication_document_required_params()
@responses.activate
def test_put_replication_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_replicator/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
# Construct a dict representation of a Attachment model
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
# Construct a dict representation of a Revisions model
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
# Construct a dict representation of a DocumentRevisionStatus model
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a dict representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model = {}
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
# Construct a dict representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model = {}
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model = {}
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a dict representation of a ReplicationDatabaseAuth model
replication_database_auth_model = {}
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a dict representation of a ReplicationDatabase model
replication_database_model = {}
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
# Construct a dict representation of a UserContext model
user_context_model = {}
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a dict representation of a ReplicationDocument model
replication_document_model = {}
replication_document_model['_attachments'] = {}
replication_document_model['_conflicts'] = ['testString']
replication_document_model['_deleted'] = True
replication_document_model['_deleted_conflicts'] = ['testString']
replication_document_model['_id'] = 'testString'
replication_document_model['_local_seq'] = 'testString'
replication_document_model['_rev'] = 'testString'
replication_document_model['_revisions'] = revisions_model
replication_document_model['_revs_info'] = [document_revision_status_model]
replication_document_model['cancel'] = True
replication_document_model['checkpoint_interval'] = 0
replication_document_model['connection_timeout'] = 0
replication_document_model['continuous'] = False
replication_document_model['create_target'] = False
replication_document_model['create_target_params'] = replication_create_target_parameters_model
replication_document_model['doc_ids'] = ['testString']
replication_document_model['filter'] = 'testString'
replication_document_model['http_connections'] = 1
replication_document_model['query_params'] = {}
replication_document_model['retries_per_request'] = 0
replication_document_model['selector'] = {}
replication_document_model['since_seq'] = 'testString'
replication_document_model['socket_options'] = 'testString'
replication_document_model['source'] = replication_database_model
replication_document_model['source_proxy'] = 'testString'
replication_document_model['target'] = replication_database_model
replication_document_model['target_proxy'] = 'testString'
replication_document_model['use_checkpoints'] = True
replication_document_model['user_ctx'] = user_context_model
replication_document_model['worker_batch_size'] = 1
replication_document_model['worker_processes'] = 1
replication_document_model['foo'] = 'testString'
# Set up parameter values
doc_id = 'testString'
replication_document = replication_document_model
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
"replication_document": replication_document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_replication_document(**req_copy)
def test_put_replication_document_value_error_with_retries(self):
# Enable retries and run test_put_replication_document_value_error.
_service.enable_retries()
self.test_put_replication_document_value_error()
# Disable retries and run test_put_replication_document_value_error.
_service.disable_retries()
self.test_put_replication_document_value_error()
class TestGetSchedulerDocs():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_docs_all_params(self):
url = self.preprocess_url(_base_url + '/_scheduler/docs')
mock_response = '{"total_rows": 0, "docs": [{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
limit = 0
skip = 0
states = ['initializing']
response = _service.get_scheduler_docs(
limit=limit,
skip=skip,
states=states,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'limit={}'.format(limit) in query_string
assert 'skip={}'.format(skip) in query_string
assert 'states={}'.format(','.join(states)) in query_string
def test_get_scheduler_docs_all_params_with_retries(self):
_service.enable_retries()
self.test_get_scheduler_docs_all_params()
_service.disable_retries()
self.test_get_scheduler_docs_all_params()
@responses.activate
def test_get_scheduler_docs_required_params(self):
url = self.preprocess_url(_base_url + '/_scheduler/docs')
mock_response = '{"total_rows": 0, "docs": [{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_scheduler_docs()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_docs_required_params_with_retries(self):
_service.enable_retries()
self.test_get_scheduler_docs_required_params()
_service.disable_retries()
self.test_get_scheduler_docs_required_params()
class TestGetSchedulerDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_document_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Invoke method
response = _service.get_scheduler_document(
doc_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_document_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_document_all_params.
_service.enable_retries()
self.test_get_scheduler_document_all_params()
# Disable retries and run test_get_scheduler_document_all_params.
_service.disable_retries()
self.test_get_scheduler_document_all_params()
@responses.activate
def test_get_scheduler_document_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/docs/_replicator/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "error_count": 0, "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "last_updated": "2019-01-01T12:00:00.000Z", "node": "node", "source": "source", "source_proxy": "source_proxy", "start_time": "2019-01-01T12:00:00.000Z", "state": "initializing", "target": "target", "target_proxy": "target_proxy"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_scheduler_document(**req_copy)
def test_get_scheduler_document_value_error_with_retries(self):
# Enable retries and run test_get_scheduler_document_value_error.
_service.enable_retries()
self.test_get_scheduler_document_value_error()
# Disable retries and run test_get_scheduler_document_value_error.
_service.disable_retries()
self.test_get_scheduler_document_value_error()
class TestGetSchedulerJobs():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_jobs_all_params(self):
url = self.preprocess_url(_base_url + '/_scheduler/jobs')
mock_response = '{"total_rows": 0, "jobs": [{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
limit = 0
skip = 0
response = _service.get_scheduler_jobs(
limit=limit,
skip=skip,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'limit={}'.format(limit) in query_string
assert 'skip={}'.format(skip) in query_string
def test_get_scheduler_jobs_all_params_with_retries(self):
_service.enable_retries()
self.test_get_scheduler_jobs_all_params()
_service.disable_retries()
self.test_get_scheduler_jobs_all_params()
@responses.activate
def test_get_scheduler_jobs_required_params(self):
url = self.preprocess_url(_base_url + '/_scheduler/jobs')
mock_response = '{"total_rows": 0, "jobs": [{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_scheduler_jobs()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_jobs_required_params_with_retries(self):
_service.enable_retries()
self.test_get_scheduler_jobs_required_params()
_service.disable_retries()
self.test_get_scheduler_jobs_required_params()
class TestGetSchedulerJob():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_scheduler_job_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
job_id = 'testString'
# Invoke method
response = _service.get_scheduler_job(
job_id,
headers={}
)
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_scheduler_job_all_params_with_retries(self):
# Enable retries and run test_get_scheduler_job_all_params.
_service.enable_retries()
self.test_get_scheduler_job_all_params()
# Disable retries and run test_get_scheduler_job_all_params.
_service.disable_retries()
self.test_get_scheduler_job_all_params()
@responses.activate
def test_get_scheduler_job_value_error(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_scheduler/jobs/testString')
mock_response = '{"database": "database", "doc_id": "doc_id", "history": [{"reason": "reason", "timestamp": "2019-01-01T12:00:00.000Z", "type": "type"}], "id": "id", "info": {"changes_pending": 0, "checkpointed_source_seq": "checkpointed_source_seq", "doc_write_failures": 0, "docs_read": 0, "docs_written": 0, "error": "error", "missing_revisions_found": 0, "revisions_checked": 0, "source_seq": "source_seq", "through_seq": "through_seq"}, "node": "node", "pid": "pid", "source": "source", "start_time": "2019-01-01T12:00:00.000Z", "target": "target", "user": "user"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
job_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"job_id": job_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_scheduler_job(**req_copy)
def test_get_scheduler_job_value_error_with_retries(self):
# Enable retries and run test_get_scheduler_job_value_error.
_service.enable_retries()
self.test_get_scheduler_job_value_error()
# Disable retries and run test_get_scheduler_job_value_error.
_service.disable_retries()
self.test_get_scheduler_job_value_error()
# endregion
##############################################################################
# End of Service: Replication
##############################################################################
##############################################################################
# Start of Service: Authentication
##############################################################################
# region
class TestNewInstance():
def test_new_instance(self):
os.environ['TEST_SERVICE_AUTH_TYPE'] = 'noAuth'
service = CloudantV1.new_instance(
service_name='TEST_SERVICE',
)
assert service is not None
assert isinstance(service, CloudantV1)
def test_new_instance_without_authenticator(self):
with pytest.raises(ValueError, match='authenticator must be provided'):
service = CloudantV1.new_instance(
)
class TestGetSessionInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_session_information_all_params(self):
url = self.preprocess_url(_base_url + '/_session')
mock_response = '{"ok": true, "info": {"authenticated": "authenticated", "authentication_db": "authentication_db", "authentication_handlers": ["authentication_handlers"]}, "userCtx": {"db": "db", "name": "name", "roles": ["_reader"]}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_session_information()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_session_information_all_params_with_retries(self):
_service.enable_retries()
self.test_get_session_information_all_params()
_service.disable_retries()
self.test_get_session_information_all_params()
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Set up parameter values
db = 'testString'
doc_id = 'testString'
# Pass in all but one required param and check for a ValueError
req_param_dict = {
"db": db,
"doc_id": doc_id,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.get_local_document(**req_copy)
def test_get_local_document_value_error_with_retries(self):
# Enable retries and run test_get_local_document_value_error.
_service.enable_retries()
self.test_get_local_document_value_error()
# Disable retries and run test_get_local_document_value_error.
_service.disable_retries()
self.test_get_local_document_value_error()
class TestPutLocalDocument():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_put_local_document_all_params(self):
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
db = 'testString'
doc_id = 'testString'
document = document_model
content_type = 'application/json'
batch = 'ok'
response = _service.put_local_document(
db,
doc_id,
document,
content_type=content_type,
batch=batch,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 201
query_string = responses.calls[0].request.url.split('?',1)[1]
query_string = urllib.parse.unquote_plus(query_string)
assert 'batch={}'.format(batch) in query_string
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
def test_put_local_document_all_params_with_retries(self):
_service.enable_retries()
self.test_put_local_document_all_params()
_service.disable_retries()
self.test_put_local_document_all_params()
@responses.activate
def test_put_local_document_required_params(self):
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
db = 'testString'
doc_id = 'testString'
document = document_model
response = _service.put_local_document(
db,
doc_id,
document,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 201
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
def test_put_local_document_required_params_with_retries(self):
_service.enable_retries()
self.test_put_local_document_required_params()
_service.disable_retries()
self.test_put_local_document_required_params()
@responses.activate
def test_put_local_document_value_error(self):
url = self.preprocess_url(_base_url + '/testString/_local/testString')
mock_response = '{"id": "id", "rev": "rev", "ok": true, "caused_by": "caused_by", "error": "error", "reason": "reason"}'
responses.add(responses.PUT,
url,
body=mock_response,
content_type='application/json',
status=201)
attachment_model = {}
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {}
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {}
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {}
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'exampleid'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['brand'] = 'Foo'
document_model['colours'] = '["red","green","black","blue"]'
document_model['description'] = 'Slim Colourful Design Electronic Cooking Appliance for ...'
document_model['image'] = 'assets/img/0gmsnghhew.jpg'
document_model['keywords'] = '["Foo","Scales","Weight","Digital","Kitchen"]'
document_model['name'] = 'Digital Kitchen Scales'
document_model['price'] = '14.99'
document_model['productid'] = '1000042'
document_model['taxonomy'] = '["Home","Kitchen","Small Appliances"]'
document_model['type'] = 'product'
db = 'testString'
doc_id = 'testString'
document = document_model
req_param_dict = {
"db": db,
"doc_id": doc_id,
"document": document,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.put_local_document(**req_copy)
def test_put_local_document_value_error_with_retries(self):
_service.enable_retries()
self.test_put_local_document_value_error()
_service.disable_retries()
self.test_put_local_document_value_error()
nses.calls) == 1
assert response.status_code == 200
def test_get_active_tasks_all_params_with_retries(self):
# Enable retries and run test_get_active_tasks_all_params.
_service.enable_retries()
self.test_get_active_tasks_all_params()
# Disable retries and run test_get_active_tasks_all_params.
_service.disable_retries()
self.test_get_active_tasks_all_params()
class TestGetUpInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_up_information_all_params(self):
url = self.preprocess_url(_base_url + '/_up')
mock_response = '{"seeds": {"anyKey": "anyValue"}, "status": "maintenance_mode"}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
response = _service.get_up_information()
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_up_information_all_params_with_retries(self):
_service.enable_retries()
self.test_get_up_information_all_params()
_service.disable_retries()
self.test_get_up_information_all_params()
class TestGetActivityTrackerEvents():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_activity_tracker_events_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"types": ["management"]}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_activity_tracker_events()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_activity_tracker_events_all_params_with_retries(self):
# Enable retries and run test_get_activity_tracker_events_all_params.
_service.enable_retries()
self.test_get_activity_tracker_events_all_params()
# Disable retries and run test_get_activity_tracker_events_all_params.
_service.disable_retries()
self.test_get_activity_tracker_events_all_params()
class TestPostActivityTrackerEvents():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url) # don't double-encode if already encoded
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_post_activity_tracker_events_all_params(self):
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
types = ['management']
response = _service.post_activity_tracker_events(
types,
headers={}
)
assert len(responses.calls) == 1
assert response.status_code == 200
responses.calls[0].request.body = gzip.decompress(responses.calls[0].request.body)
req_body = json.loads(str(responses.calls[0].request.body, 'utf-8'))
assert req_body['types'] == ['management']
def test_post_activity_tracker_events_all_params_with_retries(self):
_service.enable_retries()
self.test_post_activity_tracker_events_all_params()
_service.disable_retries()
self.test_post_activity_tracker_events_all_params()
@responses.activate
def test_post_activity_tracker_events_value_error(self):
url = self.preprocess_url(_base_url + '/_api/v2/user/activity_tracker/events')
mock_response = '{"ok": true}'
responses.add(responses.POST,
url,
body=mock_response,
content_type='application/json',
status=200)
types = ['management']
req_param_dict = {
"types": types,
}
for param in req_param_dict.keys():
req_copy = {key:val if key is not param else None for (key,val) in req_param_dict.items()}
with pytest.raises(ValueError):
_service.post_activity_tracker_events(**req_copy)
def test_post_activity_tracker_events_value_error_with_retries(self):
_service.enable_retries()
self.test_post_activity_tracker_events_value_error()
_service.disable_retries()
self.test_post_activity_tracker_events_value_error()
class TestGetCurrentThroughputInformation():
def preprocess_url(self, request_url: str):
request_url = urllib.parse.unquote(request_url)
request_url = urllib.parse.quote(request_url, safe=':/')
if re.fullmatch('.*/+', request_url) is None:
return request_url
else:
return re.compile(request_url.rstrip('/') + '/+')
@responses.activate
def test_get_current_throughput_information_all_params(self):
# Set up mock
url = self.preprocess_url(_base_url + '/_api/v2/user/current/throughput')
mock_response = '{"throughput": {"query": 0, "read": 0, "write": 0}}'
responses.add(responses.GET,
url,
body=mock_response,
content_type='application/json',
status=200)
# Invoke method
response = _service.get_current_throughput_information()
# Check for correct operation
assert len(responses.calls) == 1
assert response.status_code == 200
def test_get_current_throughput_information_all_params_with_retries(self):
# Enable retries and run test_get_current_throughput_information_all_params.
_service.enable_retries()
self.test_get_current_throughput_information_all_params()
# Disable retries and run test_get_current_throughput_information_all_params.
_service.disable_retries()
self.test_get_current_throughput_information_all_params()
# endregion
##############################################################################
# End of Service: Monitoring
##############################################################################
##############################################################################
# Start of Model Tests
##############################################################################
# region
class TestModel_ActiveTask():
def test_active_task_serialization(self):
# Construct a json representation of a ActiveTask model
active_task_model_json = {}
active_task_model_json['changes_done'] = 0
active_task_model_json['database'] = 'testString'
active_task_model_json['node'] = 'testString'
active_task_model_json['pid'] = 'testString'
active_task_model_json['progress'] = 0
active_task_model_json['started_on'] = 0
active_task_model_json['status'] = 'testString'
active_task_model_json['task'] = 'testString'
active_task_model_json['total_changes'] = 0
active_task_model_json['type'] = 'testString'
active_task_model_json['updated_on'] = 0
# Construct a model instance of ActiveTask by calling from_dict on the json representation
active_task_model = ActiveTask.from_dict(active_task_model_json)
assert active_task_model != False
# Construct a model instance of ActiveTask by calling from_dict on the json representation
active_task_model_dict = ActiveTask.from_dict(active_task_model_json).__dict__
active_task_model2 = ActiveTask(**active_task_model_dict)
# Verify the model instances are equivalent
assert active_task_model == active_task_model2
# Convert model instance back to dict and verify no loss of data
active_task_model_json2 = active_task_model.to_dict()
assert active_task_model_json2 == active_task_model_json
class TestModel_ActivityTrackerEvents():
def test_activity_tracker_events_serialization(self):
# Construct a json representation of a ActivityTrackerEvents model
activity_tracker_events_model_json = {}
activity_tracker_events_model_json['types'] = ['management']
# Construct a model instance of ActivityTrackerEvents by calling from_dict on the json representation
activity_tracker_events_model = ActivityTrackerEvents.from_dict(activity_tracker_events_model_json)
assert activity_tracker_events_model != False
# Construct a model instance of ActivityTrackerEvents by calling from_dict on the json representation
activity_tracker_events_model_dict = ActivityTrackerEvents.from_dict(activity_tracker_events_model_json).__dict__
activity_tracker_events_model2 = ActivityTrackerEvents(**activity_tracker_events_model_dict)
# Verify the model instances are equivalent
assert activity_tracker_events_model == activity_tracker_events_model2
# Convert model instance back to dict and verify no loss of data
activity_tracker_events_model_json2 = activity_tracker_events_model.to_dict()
assert activity_tracker_events_model_json2 == activity_tracker_events_model_json
class TestModel_AllDocsQueriesResult():
def test_all_docs_queries_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
docs_result_row_model = {} # DocsResultRow
docs_result_row_model['caused_by'] = 'testString'
docs_result_row_model['error'] = 'testString'
docs_result_row_model['reason'] = 'testString'
docs_result_row_model['doc'] = document_model
docs_result_row_model['id'] = 'testString'
docs_result_row_model['key'] = 'testString'
docs_result_row_model['value'] = docs_result_row_value_model
all_docs_result_model = {} # AllDocsResult
all_docs_result_model['total_rows'] = 0
all_docs_result_model['rows'] = [docs_result_row_model]
all_docs_result_model['update_seq'] = 'testString'
# Construct a json representation of a AllDocsQueriesResult model
all_docs_queries_result_model_json = {}
all_docs_queries_result_model_json['results'] = [all_docs_result_model]
# Construct a model instance of AllDocsQueriesResult by calling from_dict on the json representation
all_docs_queries_result_model = AllDocsQueriesResult.from_dict(all_docs_queries_result_model_json)
assert all_docs_queries_result_model != False
# Construct a model instance of AllDocsQueriesResult by calling from_dict on the json representation
all_docs_queries_result_model_dict = AllDocsQueriesResult.from_dict(all_docs_queries_result_model_json).__dict__
all_docs_queries_result_model2 = AllDocsQueriesResult(**all_docs_queries_result_model_dict)
# Verify the model instances are equivalent
assert all_docs_queries_result_model == all_docs_queries_result_model2
# Convert model instance back to dict and verify no loss of data
all_docs_queries_result_model_json2 = all_docs_queries_result_model.to_dict()
assert all_docs_queries_result_model_json2 == all_docs_queries_result_model_json
class TestModel_AllDocsQuery():
def test_all_docs_query_serialization(self):
# Construct a json representation of a AllDocsQuery model
all_docs_query_model_json = {}
all_docs_query_model_json['att_encoding_info'] = False
all_docs_query_model_json['attachments'] = False
all_docs_query_model_json['conflicts'] = False
all_docs_query_model_json['descending'] = False
all_docs_query_model_json['include_docs'] = False
all_docs_query_model_json['inclusive_end'] = True
all_docs_query_model_json['limit'] = 0
all_docs_query_model_json['skip'] = 0
all_docs_query_model_json['update_seq'] = False
all_docs_query_model_json['endkey'] = 'testString'
all_docs_query_model_json['key'] = 'testString'
all_docs_query_model_json['keys'] = ['testString']
all_docs_query_model_json['startkey'] = 'testString'
# Construct a model instance of AllDocsQuery by calling from_dict on the json representation
all_docs_query_model = AllDocsQuery.from_dict(all_docs_query_model_json)
assert all_docs_query_model != False
# Construct a model instance of AllDocsQuery by calling from_dict on the json representation
all_docs_query_model_dict = AllDocsQuery.from_dict(all_docs_query_model_json).__dict__
all_docs_query_model2 = AllDocsQuery(**all_docs_query_model_dict)
# Verify the model instances are equivalent
assert all_docs_query_model == all_docs_query_model2
# Convert model instance back to dict and verify no loss of data
all_docs_query_model_json2 = all_docs_query_model.to_dict()
assert all_docs_query_model_json2 == all_docs_query_model_json
class TestModel_AllDocsResult():
def test_all_docs_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
docs_result_row_model = {} # DocsResultRow
docs_result_row_model['caused_by'] = 'testString'
docs_result_row_model['error'] = 'testString'
docs_result_row_model['reason'] = 'testString'
docs_result_row_model['doc'] = document_model
docs_result_row_model['id'] = 'testString'
docs_result_row_model['key'] = 'testString'
docs_result_row_model['value'] = docs_result_row_value_model
# Construct a json representation of a AllDocsResult model
all_docs_result_model_json = {}
all_docs_result_model_json['total_rows'] = 0
all_docs_result_model_json['rows'] = [docs_result_row_model]
all_docs_result_model_json['update_seq'] = 'testString'
# Construct a model instance of AllDocsResult by calling from_dict on the json representation
all_docs_result_model = AllDocsResult.from_dict(all_docs_result_model_json)
assert all_docs_result_model != False
# Construct a model instance of AllDocsResult by calling from_dict on the json representation
all_docs_result_model_dict = AllDocsResult.from_dict(all_docs_result_model_json).__dict__
all_docs_result_model2 = AllDocsResult(**all_docs_result_model_dict)
# Verify the model instances are equivalent
assert all_docs_result_model == all_docs_result_model2
# Convert model instance back to dict and verify no loss of data
all_docs_result_model_json2 = all_docs_result_model.to_dict()
assert all_docs_result_model_json2 == all_docs_result_model_json
class TestModel_Analyzer():
def test_analyzer_serialization(self):
# Construct a json representation of a Analyzer model
analyzer_model_json = {}
analyzer_model_json['name'] = 'classic'
analyzer_model_json['stopwords'] = ['testString']
# Construct a model instance of Analyzer by calling from_dict on the json representation
analyzer_model = Analyzer.from_dict(analyzer_model_json)
assert analyzer_model != False
# Construct a model instance of Analyzer by calling from_dict on the json representation
analyzer_model_dict = Analyzer.from_dict(analyzer_model_json).__dict__
analyzer_model2 = Analyzer(**analyzer_model_dict)
# Verify the model instances are equivalent
assert analyzer_model == analyzer_model2
# Convert model instance back to dict and verify no loss of data
analyzer_model_json2 = analyzer_model.to_dict()
assert analyzer_model_json2 == analyzer_model_json
class TestModel_AnalyzerConfiguration():
def test_analyzer_configuration_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a json representation of a AnalyzerConfiguration model
analyzer_configuration_model_json = {}
analyzer_configuration_model_json['name'] = 'classic'
analyzer_configuration_model_json['stopwords'] = ['testString']
analyzer_configuration_model_json['fields'] = {}
# Construct a model instance of AnalyzerConfiguration by calling from_dict on the json representation
analyzer_configuration_model = AnalyzerConfiguration.from_dict(analyzer_configuration_model_json)
assert analyzer_configuration_model != False
# Construct a model instance of AnalyzerConfiguration by calling from_dict on the json representation
analyzer_configuration_model_dict = AnalyzerConfiguration.from_dict(analyzer_configuration_model_json).__dict__
analyzer_configuration_model2 = AnalyzerConfiguration(**analyzer_configuration_model_dict)
# Verify the model instances are equivalent
assert analyzer_configuration_model == analyzer_configuration_model2
# Convert model instance back to dict and verify no loss of data
analyzer_configuration_model_json2 = analyzer_configuration_model.to_dict()
assert analyzer_configuration_model_json2 == analyzer_configuration_model_json
class TestModel_ApiKeysResult():
def test_api_keys_result_serialization(self):
# Construct a json representation of a ApiKeysResult model
api_keys_result_model_json = {}
api_keys_result_model_json['ok'] = True
api_keys_result_model_json['key'] = 'testString'
api_keys_result_model_json['password'] = 'testString'
# Construct a model instance of ApiKeysResult by calling from_dict on the json representation
api_keys_result_model = ApiKeysResult.from_dict(api_keys_result_model_json)
assert api_keys_result_model != False
# Construct a model instance of ApiKeysResult by calling from_dict on the json representation
api_keys_result_model_dict = ApiKeysResult.from_dict(api_keys_result_model_json).__dict__
api_keys_result_model2 = ApiKeysResult(**api_keys_result_model_dict)
# Verify the model instances are equivalent
assert api_keys_result_model == api_keys_result_model2
# Convert model instance back to dict and verify no loss of data
api_keys_result_model_json2 = api_keys_result_model.to_dict()
assert api_keys_result_model_json2 == api_keys_result_model_json
class TestModel_Attachment():
def test_attachment_serialization(self):
# Construct a json representation of a Attachment model
attachment_model_json = {}
attachment_model_json['content_type'] = 'testString'
attachment_model_json['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model_json['digest'] = 'testString'
attachment_model_json['encoded_length'] = 0
attachment_model_json['encoding'] = 'testString'
attachment_model_json['follows'] = True
attachment_model_json['length'] = 0
attachment_model_json['revpos'] = 1
attachment_model_json['stub'] = True
# Construct a model instance of Attachment by calling from_dict on the json representation
attachment_model = Attachment.from_dict(attachment_model_json)
assert attachment_model != False
# Construct a model instance of Attachment by calling from_dict on the json representation
attachment_model_dict = Attachment.from_dict(attachment_model_json).__dict__
attachment_model2 = Attachment(**attachment_model_dict)
# Verify the model instances are equivalent
assert attachment_model == attachment_model2
# Convert model instance back to dict and verify no loss of data
attachment_model_json2 = attachment_model.to_dict()
assert attachment_model_json2 == attachment_model_json
class TestModel_BulkDocs():
def test_bulk_docs_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a BulkDocs model
bulk_docs_model_json = {}
bulk_docs_model_json['docs'] = [document_model]
bulk_docs_model_json['new_edits'] = True
# Construct a model instance of BulkDocs by calling from_dict on the json representation
bulk_docs_model = BulkDocs.from_dict(bulk_docs_model_json)
assert bulk_docs_model != False
# Construct a model instance of BulkDocs by calling from_dict on the json representation
bulk_docs_model_dict = BulkDocs.from_dict(bulk_docs_model_json).__dict__
bulk_docs_model2 = BulkDocs(**bulk_docs_model_dict)
# Verify the model instances are equivalent
assert bulk_docs_model == bulk_docs_model2
# Convert model instance back to dict and verify no loss of data
bulk_docs_model_json2 = bulk_docs_model.to_dict()
assert bulk_docs_model_json2 == bulk_docs_model_json
class TestModel_BulkGetQueryDocument():
def test_bulk_get_query_document_serialization(self):
# Construct a json representation of a BulkGetQueryDocument model
bulk_get_query_document_model_json = {}
bulk_get_query_document_model_json['atts_since'] = ['1-99b02e08da151943c2dcb40090160bb8']
bulk_get_query_document_model_json['id'] = 'testString'
bulk_get_query_document_model_json['rev'] = 'testString'
# Construct a model instance of BulkGetQueryDocument by calling from_dict on the json representation
bulk_get_query_document_model = BulkGetQueryDocument.from_dict(bulk_get_query_document_model_json)
assert bulk_get_query_document_model != False
# Construct a model instance of BulkGetQueryDocument by calling from_dict on the json representation
bulk_get_query_document_model_dict = BulkGetQueryDocument.from_dict(bulk_get_query_document_model_json).__dict__
bulk_get_query_document_model2 = BulkGetQueryDocument(**bulk_get_query_document_model_dict)
# Verify the model instances are equivalent
assert bulk_get_query_document_model == bulk_get_query_document_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_query_document_model_json2 = bulk_get_query_document_model.to_dict()
assert bulk_get_query_document_model_json2 == bulk_get_query_document_model_json
class TestModel_BulkGetResult():
def test_bulk_get_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
bulk_get_result_document_model = {} # BulkGetResultDocument
bulk_get_result_document_model['error'] = document_result_model
bulk_get_result_document_model['ok'] = document_model
bulk_get_result_item_model = {} # BulkGetResultItem
bulk_get_result_item_model['docs'] = [bulk_get_result_document_model]
bulk_get_result_item_model['id'] = 'testString'
# Construct a json representation of a BulkGetResult model
bulk_get_result_model_json = {}
bulk_get_result_model_json['results'] = [bulk_get_result_item_model]
# Construct a model instance of BulkGetResult by calling from_dict on the json representation
bulk_get_result_model = BulkGetResult.from_dict(bulk_get_result_model_json)
assert bulk_get_result_model != False
# Construct a model instance of BulkGetResult by calling from_dict on the json representation
bulk_get_result_model_dict = BulkGetResult.from_dict(bulk_get_result_model_json).__dict__
bulk_get_result_model2 = BulkGetResult(**bulk_get_result_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_model == bulk_get_result_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_model_json2 = bulk_get_result_model.to_dict()
assert bulk_get_result_model_json2 == bulk_get_result_model_json
class TestModel_BulkGetResultDocument():
def test_bulk_get_result_document_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a BulkGetResultDocument model
bulk_get_result_document_model_json = {}
bulk_get_result_document_model_json['error'] = document_result_model
bulk_get_result_document_model_json['ok'] = document_model
# Construct a model instance of BulkGetResultDocument by calling from_dict on the json representation
bulk_get_result_document_model = BulkGetResultDocument.from_dict(bulk_get_result_document_model_json)
assert bulk_get_result_document_model != False
# Construct a model instance of BulkGetResultDocument by calling from_dict on the json representation
bulk_get_result_document_model_dict = BulkGetResultDocument.from_dict(bulk_get_result_document_model_json).__dict__
bulk_get_result_document_model2 = BulkGetResultDocument(**bulk_get_result_document_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_document_model == bulk_get_result_document_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_document_model_json2 = bulk_get_result_document_model.to_dict()
assert bulk_get_result_document_model_json2 == bulk_get_result_document_model_json
class TestModel_BulkGetResultItem():
def test_bulk_get_result_item_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
document_result_model = {} # DocumentResult
document_result_model['id'] = 'testString'
document_result_model['rev'] = 'testString'
document_result_model['ok'] = True
document_result_model['caused_by'] = 'testString'
document_result_model['error'] = 'testString'
document_result_model['reason'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
bulk_get_result_document_model = {} # BulkGetResultDocument
bulk_get_result_document_model['error'] = document_result_model
bulk_get_result_document_model['ok'] = document_model
# Construct a json representation of a BulkGetResultItem model
bulk_get_result_item_model_json = {}
bulk_get_result_item_model_json['docs'] = [bulk_get_result_document_model]
bulk_get_result_item_model_json['id'] = 'testString'
# Construct a model instance of BulkGetResultItem by calling from_dict on the json representation
bulk_get_result_item_model = BulkGetResultItem.from_dict(bulk_get_result_item_model_json)
assert bulk_get_result_item_model != False
# Construct a model instance of BulkGetResultItem by calling from_dict on the json representation
bulk_get_result_item_model_dict = BulkGetResultItem.from_dict(bulk_get_result_item_model_json).__dict__
bulk_get_result_item_model2 = BulkGetResultItem(**bulk_get_result_item_model_dict)
# Verify the model instances are equivalent
assert bulk_get_result_item_model == bulk_get_result_item_model2
# Convert model instance back to dict and verify no loss of data
bulk_get_result_item_model_json2 = bulk_get_result_item_model.to_dict()
assert bulk_get_result_item_model_json2 == bulk_get_result_item_model_json
class TestModel_CapacityThroughputInformation():
def test_capacity_throughput_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
capacity_throughput_information_current_model = {} # CapacityThroughputInformationCurrent
capacity_throughput_information_current_model['throughput'] = throughput_information_model
capacity_throughput_information_target_model = {} # CapacityThroughputInformationTarget
capacity_throughput_information_target_model['throughput'] = throughput_information_model
# Construct a json representation of a CapacityThroughputInformation model
capacity_throughput_information_model_json = {}
capacity_throughput_information_model_json['current'] = capacity_throughput_information_current_model
capacity_throughput_information_model_json['target'] = capacity_throughput_information_target_model
# Construct a model instance of CapacityThroughputInformation by calling from_dict on the json representation
capacity_throughput_information_model = CapacityThroughputInformation.from_dict(capacity_throughput_information_model_json)
assert capacity_throughput_information_model != False
# Construct a model instance of CapacityThroughputInformation by calling from_dict on the json representation
capacity_throughput_information_model_dict = CapacityThroughputInformation.from_dict(capacity_throughput_information_model_json).__dict__
capacity_throughput_information_model2 = CapacityThroughputInformation(**capacity_throughput_information_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_model == capacity_throughput_information_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_model_json2 = capacity_throughput_information_model.to_dict()
assert capacity_throughput_information_model_json2 == capacity_throughput_information_model_json
class TestModel_CapacityThroughputInformationCurrent():
def test_capacity_throughput_information_current_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
# Construct a json representation of a CapacityThroughputInformationCurrent model
capacity_throughput_information_current_model_json = {}
capacity_throughput_information_current_model_json['throughput'] = throughput_information_model
# Construct a model instance of CapacityThroughputInformationCurrent by calling from_dict on the json representation
capacity_throughput_information_current_model = CapacityThroughputInformationCurrent.from_dict(capacity_throughput_information_current_model_json)
assert capacity_throughput_information_current_model != False
# Construct a model instance of CapacityThroughputInformationCurrent by calling from_dict on the json representation
capacity_throughput_information_current_model_dict = CapacityThroughputInformationCurrent.from_dict(capacity_throughput_information_current_model_json).__dict__
capacity_throughput_information_current_model2 = CapacityThroughputInformationCurrent(**capacity_throughput_information_current_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_current_model == capacity_throughput_information_current_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_current_model_json2 = capacity_throughput_information_current_model.to_dict()
assert capacity_throughput_information_current_model_json2 == capacity_throughput_information_current_model_json
class TestModel_CapacityThroughputInformationTarget():
def test_capacity_throughput_information_target_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
throughput_information_model = {} # ThroughputInformation
throughput_information_model['blocks'] = 0
throughput_information_model['query'] = 0
throughput_information_model['read'] = 0
throughput_information_model['write'] = 0
# Construct a json representation of a CapacityThroughputInformationTarget model
capacity_throughput_information_target_model_json = {}
capacity_throughput_information_target_model_json['throughput'] = throughput_information_model
# Construct a model instance of CapacityThroughputInformationTarget by calling from_dict on the json representation
capacity_throughput_information_target_model = CapacityThroughputInformationTarget.from_dict(capacity_throughput_information_target_model_json)
assert capacity_throughput_information_target_model != False
# Construct a model instance of CapacityThroughputInformationTarget by calling from_dict on the json representation
capacity_throughput_information_target_model_dict = CapacityThroughputInformationTarget.from_dict(capacity_throughput_information_target_model_json).__dict__
capacity_throughput_information_target_model2 = CapacityThroughputInformationTarget(**capacity_throughput_information_target_model_dict)
# Verify the model instances are equivalent
assert capacity_throughput_information_target_model == capacity_throughput_information_target_model2
# Convert model instance back to dict and verify no loss of data
capacity_throughput_information_target_model_json2 = capacity_throughput_information_target_model.to_dict()
assert capacity_throughput_information_target_model_json2 == capacity_throughput_information_target_model_json
class TestModel_Change():
def test_change_serialization(self):
# Construct a json representation of a Change model
change_model_json = {}
change_model_json['rev'] = 'testString'
# Construct a model instance of Change by calling from_dict on the json representation
change_model = Change.from_dict(change_model_json)
assert change_model != False
# Construct a model instance of Change by calling from_dict on the json representation
change_model_dict = Change.from_dict(change_model_json).__dict__
change_model2 = Change(**change_model_dict)
# Verify the model instances are equivalent
assert change_model == change_model2
# Convert model instance back to dict and verify no loss of data
change_model_json2 = change_model.to_dict()
assert change_model_json2 == change_model_json
class TestModel_ChangesResult():
def test_changes_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
change_model = {} # Change
change_model['rev'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
changes_result_item_model = {} # ChangesResultItem
changes_result_item_model['changes'] = [change_model]
changes_result_item_model['deleted'] = True
changes_result_item_model['doc'] = document_model
changes_result_item_model['id'] = 'testString'
changes_result_item_model['seq'] = 'testString'
# Construct a json representation of a ChangesResult model
changes_result_model_json = {}
changes_result_model_json['last_seq'] = 'testString'
changes_result_model_json['pending'] = 26
changes_result_model_json['results'] = [changes_result_item_model]
# Construct a model instance of ChangesResult by calling from_dict on the json representation
changes_result_model = ChangesResult.from_dict(changes_result_model_json)
assert changes_result_model != False
# Construct a model instance of ChangesResult by calling from_dict on the json representation
changes_result_model_dict = ChangesResult.from_dict(changes_result_model_json).__dict__
changes_result_model2 = ChangesResult(**changes_result_model_dict)
# Verify the model instances are equivalent
assert changes_result_model == changes_result_model2
# Convert model instance back to dict and verify no loss of data
changes_result_model_json2 = changes_result_model.to_dict()
assert changes_result_model_json2 == changes_result_model_json
class TestModel_ChangesResultItem():
def test_changes_result_item_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
change_model = {} # Change
change_model['rev'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a ChangesResultItem model
changes_result_item_model_json = {}
changes_result_item_model_json['changes'] = [change_model]
changes_result_item_model_json['deleted'] = True
changes_result_item_model_json['doc'] = document_model
changes_result_item_model_json['id'] = 'testString'
changes_result_item_model_json['seq'] = 'testString'
# Construct a model instance of ChangesResultItem by calling from_dict on the json representation
changes_result_item_model = ChangesResultItem.from_dict(changes_result_item_model_json)
assert changes_result_item_model != False
# Construct a model instance of ChangesResultItem by calling from_dict on the json representation
changes_result_item_model_dict = ChangesResultItem.from_dict(changes_result_item_model_json).__dict__
changes_result_item_model2 = ChangesResultItem(**changes_result_item_model_dict)
# Verify the model instances are equivalent
assert changes_result_item_model == changes_result_item_model2
# Convert model instance back to dict and verify no loss of data
changes_result_item_model_json2 = changes_result_item_model.to_dict()
assert changes_result_item_model_json2 == changes_result_item_model_json
class TestModel_ContentInformationSizes():
def test_content_information_sizes_serialization(self):
# Construct a json representation of a ContentInformationSizes model
content_information_sizes_model_json = {}
content_information_sizes_model_json['active'] = 26
content_information_sizes_model_json['external'] = 26
content_information_sizes_model_json['file'] = 26
# Construct a model instance of ContentInformationSizes by calling from_dict on the json representation
content_information_sizes_model = ContentInformationSizes.from_dict(content_information_sizes_model_json)
assert content_information_sizes_model != False
# Construct a model instance of ContentInformationSizes by calling from_dict on the json representation
content_information_sizes_model_dict = ContentInformationSizes.from_dict(content_information_sizes_model_json).__dict__
content_information_sizes_model2 = ContentInformationSizes(**content_information_sizes_model_dict)
# Verify the model instances are equivalent
assert content_information_sizes_model == content_information_sizes_model2
# Convert model instance back to dict and verify no loss of data
content_information_sizes_model_json2 = content_information_sizes_model.to_dict()
assert content_information_sizes_model_json2 == content_information_sizes_model_json
class TestModel_CorsInformation():
def test_cors_information_serialization(self):
# Construct a json representation of a CorsInformation model
cors_information_model_json = {}
cors_information_model_json['allow_credentials'] = True
cors_information_model_json['enable_cors'] = True
cors_information_model_json['origins'] = ['testString']
# Construct a model instance of CorsInformation by calling from_dict on the json representation
cors_information_model = CorsInformation.from_dict(cors_information_model_json)
assert cors_information_model != False
# Construct a model instance of CorsInformation by calling from_dict on the json representation
cors_information_model_dict = CorsInformation.from_dict(cors_information_model_json).__dict__
cors_information_model2 = CorsInformation(**cors_information_model_dict)
# Verify the model instances are equivalent
assert cors_information_model == cors_information_model2
# Convert model instance back to dict and verify no loss of data
cors_information_model_json2 = cors_information_model.to_dict()
assert cors_information_model_json2 == cors_information_model_json
class TestModel_CurrentThroughputInformation():
def test_current_throughput_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
current_throughput_information_throughput_model = {} # CurrentThroughputInformationThroughput
current_throughput_information_throughput_model['query'] = 0
current_throughput_information_throughput_model['read'] = 0
current_throughput_information_throughput_model['write'] = 0
# Construct a json representation of a CurrentThroughputInformation model
current_throughput_information_model_json = {}
current_throughput_information_model_json['throughput'] = current_throughput_information_throughput_model
# Construct a model instance of CurrentThroughputInformation by calling from_dict on the json representation
current_throughput_information_model = CurrentThroughputInformation.from_dict(current_throughput_information_model_json)
assert current_throughput_information_model != False
# Construct a model instance of CurrentThroughputInformation by calling from_dict on the json representation
current_throughput_information_model_dict = CurrentThroughputInformation.from_dict(current_throughput_information_model_json).__dict__
current_throughput_information_model2 = CurrentThroughputInformation(**current_throughput_information_model_dict)
# Verify the model instances are equivalent
assert current_throughput_information_model == current_throughput_information_model2
# Convert model instance back to dict and verify no loss of data
current_throughput_information_model_json2 = current_throughput_information_model.to_dict()
assert current_throughput_information_model_json2 == current_throughput_information_model_json
class TestModel_CurrentThroughputInformationThroughput():
def test_current_throughput_information_throughput_serialization(self):
# Construct a json representation of a CurrentThroughputInformationThroughput model
current_throughput_information_throughput_model_json = {}
current_throughput_information_throughput_model_json['query'] = 0
current_throughput_information_throughput_model_json['read'] = 0
current_throughput_information_throughput_model_json['write'] = 0
# Construct a model instance of CurrentThroughputInformationThroughput by calling from_dict on the json representation
current_throughput_information_throughput_model = CurrentThroughputInformationThroughput.from_dict(current_throughput_information_throughput_model_json)
assert current_throughput_information_throughput_model != False
# Construct a model instance of CurrentThroughputInformationThroughput by calling from_dict on the json representation
current_throughput_information_throughput_model_dict = CurrentThroughputInformationThroughput.from_dict(current_throughput_information_throughput_model_json).__dict__
current_throughput_information_throughput_model2 = CurrentThroughputInformationThroughput(**current_throughput_information_throughput_model_dict)
# Verify the model instances are equivalent
assert current_throughput_information_throughput_model == current_throughput_information_throughput_model2
# Convert model instance back to dict and verify no loss of data
current_throughput_information_throughput_model_json2 = current_throughput_information_throughput_model.to_dict()
assert current_throughput_information_throughput_model_json2 == current_throughput_information_throughput_model_json
class TestModel_DatabaseInformation():
def test_database_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
database_information_cluster_model = {} # DatabaseInformationCluster
database_information_cluster_model['n'] = 1
database_information_cluster_model['q'] = 1
database_information_cluster_model['r'] = 1
database_information_cluster_model['w'] = 1
database_information_props_model = {} # DatabaseInformationProps
database_information_props_model['partitioned'] = True
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
# Construct a json representation of a DatabaseInformation model
database_information_model_json = {}
database_information_model_json['cluster'] = database_information_cluster_model
database_information_model_json['committed_update_seq'] = 'testString'
database_information_model_json['compact_running'] = True
database_information_model_json['compacted_seq'] = 'testString'
database_information_model_json['db_name'] = 'testString'
database_information_model_json['disk_format_version'] = 26
database_information_model_json['doc_count'] = 0
database_information_model_json['doc_del_count'] = 0
database_information_model_json['engine'] = 'testString'
database_information_model_json['props'] = database_information_props_model
database_information_model_json['sizes'] = content_information_sizes_model
database_information_model_json['update_seq'] = 'testString'
database_information_model_json['uuid'] = 'testString'
# Construct a model instance of DatabaseInformation by calling from_dict on the json representation
database_information_model = DatabaseInformation.from_dict(database_information_model_json)
assert database_information_model != False
# Construct a model instance of DatabaseInformation by calling from_dict on the json representation
database_information_model_dict = DatabaseInformation.from_dict(database_information_model_json).__dict__
database_information_model2 = DatabaseInformation(**database_information_model_dict)
# Verify the model instances are equivalent
assert database_information_model == database_information_model2
# Convert model instance back to dict and verify no loss of data
database_information_model_json2 = database_information_model.to_dict()
assert database_information_model_json2 == database_information_model_json
class TestModel_DatabaseInformationCluster():
def test_database_information_cluster_serialization(self):
# Construct a json representation of a DatabaseInformationCluster model
database_information_cluster_model_json = {}
database_information_cluster_model_json['n'] = 1
database_information_cluster_model_json['q'] = 1
database_information_cluster_model_json['r'] = 1
database_information_cluster_model_json['w'] = 1
# Construct a model instance of DatabaseInformationCluster by calling from_dict on the json representation
database_information_cluster_model = DatabaseInformationCluster.from_dict(database_information_cluster_model_json)
assert database_information_cluster_model != False
# Construct a model instance of DatabaseInformationCluster by calling from_dict on the json representation
database_information_cluster_model_dict = DatabaseInformationCluster.from_dict(database_information_cluster_model_json).__dict__
database_information_cluster_model2 = DatabaseInformationCluster(**database_information_cluster_model_dict)
# Verify the model instances are equivalent
assert database_information_cluster_model == database_information_cluster_model2
# Convert model instance back to dict and verify no loss of data
database_information_cluster_model_json2 = database_information_cluster_model.to_dict()
assert database_information_cluster_model_json2 == database_information_cluster_model_json
class TestModel_DatabaseInformationProps():
def test_database_information_props_serialization(self):
# Construct a json representation of a DatabaseInformationProps model
database_information_props_model_json = {}
database_information_props_model_json['partitioned'] = True
# Construct a model instance of DatabaseInformationProps by calling from_dict on the json representation
database_information_props_model = DatabaseInformationProps.from_dict(database_information_props_model_json)
assert database_information_props_model != False
# Construct a model instance of DatabaseInformationProps by calling from_dict on the json representation
database_information_props_model_dict = DatabaseInformationProps.from_dict(database_information_props_model_json).__dict__
database_information_props_model2 = DatabaseInformationProps(**database_information_props_model_dict)
# Verify the model instances are equivalent
assert database_information_props_model == database_information_props_model2
# Convert model instance back to dict and verify no loss of data
database_information_props_model_json2 = database_information_props_model.to_dict()
assert database_information_props_model_json2 == database_information_props_model_json
class TestModel_DbEvent():
def test_db_event_serialization(self):
# Construct a json representation of a DbEvent model
db_event_model_json = {}
db_event_model_json['account'] = 'testString'
db_event_model_json['db_name'] = 'testString'
db_event_model_json['seq'] = 'testString'
db_event_model_json['type'] = 'created'
# Construct a model instance of DbEvent by calling from_dict on the json representation
db_event_model = DbEvent.from_dict(db_event_model_json)
assert db_event_model != False
# Construct a model instance of DbEvent by calling from_dict on the json representation
db_event_model_dict = DbEvent.from_dict(db_event_model_json).__dict__
db_event_model2 = DbEvent(**db_event_model_dict)
# Verify the model instances are equivalent
assert db_event_model == db_event_model2
# Convert model instance back to dict and verify no loss of data
db_event_model_json2 = db_event_model.to_dict()
assert db_event_model_json2 == db_event_model_json
class TestModel_DbUpdates():
def test_db_updates_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
db_event_model = {} # DbEvent
db_event_model['account'] = 'testString'
db_event_model['db_name'] = 'testString'
db_event_model['seq'] = 'testString'
db_event_model['type'] = 'created'
# Construct a json representation of a DbUpdates model
db_updates_model_json = {}
db_updates_model_json['last_seq'] = 'testString'
db_updates_model_json['results'] = [db_event_model]
# Construct a model instance of DbUpdates by calling from_dict on the json representation
db_updates_model = DbUpdates.from_dict(db_updates_model_json)
assert db_updates_model != False
# Construct a model instance of DbUpdates by calling from_dict on the json representation
db_updates_model_dict = DbUpdates.from_dict(db_updates_model_json).__dict__
db_updates_model2 = DbUpdates(**db_updates_model_dict)
# Verify the model instances are equivalent
assert db_updates_model == db_updates_model2
# Convert model instance back to dict and verify no loss of data
db_updates_model_json2 = db_updates_model.to_dict()
assert db_updates_model_json2 == db_updates_model_json
class TestModel_DbsInfoResult():
def test_dbs_info_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
database_information_cluster_model = {} # DatabaseInformationCluster
database_information_cluster_model['n'] = 1
database_information_cluster_model['q'] = 1
database_information_cluster_model['r'] = 1
database_information_cluster_model['w'] = 1
database_information_props_model = {} # DatabaseInformationProps
database_information_props_model['partitioned'] = True
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
database_information_model = {} # DatabaseInformation
database_information_model['cluster'] = database_information_cluster_model
database_information_model['committed_update_seq'] = 'testString'
database_information_model['compact_running'] = True
database_information_model['compacted_seq'] = 'testString'
database_information_model['db_name'] = 'testString'
database_information_model['disk_format_version'] = 26
database_information_model['doc_count'] = 0
database_information_model['doc_del_count'] = 0
database_information_model['engine'] = 'testString'
database_information_model['props'] = database_information_props_model
database_information_model['sizes'] = content_information_sizes_model
database_information_model['update_seq'] = 'testString'
database_information_model['uuid'] = 'testString'
# Construct a json representation of a DbsInfoResult model
dbs_info_result_model_json = {}
dbs_info_result_model_json['error'] = 'testString'
dbs_info_result_model_json['info'] = database_information_model
dbs_info_result_model_json['key'] = 'testString'
# Construct a model instance of DbsInfoResult by calling from_dict on the json representation
dbs_info_result_model = DbsInfoResult.from_dict(dbs_info_result_model_json)
assert dbs_info_result_model != False
# Construct a model instance of DbsInfoResult by calling from_dict on the json representation
dbs_info_result_model_dict = DbsInfoResult.from_dict(dbs_info_result_model_json).__dict__
dbs_info_result_model2 = DbsInfoResult(**dbs_info_result_model_dict)
# Verify the model instances are equivalent
assert dbs_info_result_model == dbs_info_result_model2
# Convert model instance back to dict and verify no loss of data
dbs_info_result_model_json2 = dbs_info_result_model.to_dict()
assert dbs_info_result_model_json2 == dbs_info_result_model_json
class TestModel_DesignDocument():
def test_design_document_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
analyzer_configuration_model = {} # AnalyzerConfiguration
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
search_index_definition_model = {} # SearchIndexDefinition
search_index_definition_model['analyzer'] = analyzer_configuration_model
search_index_definition_model['index'] = 'testString'
design_document_options_model = {} # DesignDocumentOptions
design_document_options_model['partitioned'] = True
design_document_views_map_reduce_model = {} # DesignDocumentViewsMapReduce
design_document_views_map_reduce_model['map'] = 'testString'
design_document_views_map_reduce_model['reduce'] = 'testString'
geo_index_definition_model = {} # GeoIndexDefinition
geo_index_definition_model['index'] = 'testString'
# Construct a json representation of a DesignDocument model
design_document_model_json = {}
design_document_model_json['_attachments'] = {}
design_document_model_json['_conflicts'] = ['testString']
design_document_model_json['_deleted'] = True
design_document_model_json['_deleted_conflicts'] = ['testString']
design_document_model_json['_id'] = 'testString'
design_document_model_json['_local_seq'] = 'testString'
design_document_model_json['_rev'] = 'testString'
design_document_model_json['_revisions'] = revisions_model
design_document_model_json['_revs_info'] = [document_revision_status_model]
design_document_model_json['autoupdate'] = True
design_document_model_json['filters'] = {}
design_document_model_json['indexes'] = {}
design_document_model_json['language'] = 'javascript'
design_document_model_json['options'] = design_document_options_model
design_document_model_json['validate_doc_update'] = 'testString'
design_document_model_json['views'] = {}
design_document_model_json['st_indexes'] = {}
design_document_model_json['foo'] = 'testString'
# Construct a model instance of DesignDocument by calling from_dict on the json representation
design_document_model = DesignDocument.from_dict(design_document_model_json)
assert design_document_model != False
# Construct a model instance of DesignDocument by calling from_dict on the json representation
design_document_model_dict = DesignDocument.from_dict(design_document_model_json).__dict__
design_document_model2 = DesignDocument(**design_document_model_dict)
# Verify the model instances are equivalent
assert design_document_model == design_document_model2
# Convert model instance back to dict and verify no loss of data
design_document_model_json2 = design_document_model.to_dict()
assert design_document_model_json2 == design_document_model_json
# Test get_properties and set_properties methods.
design_document_model.set_properties({})
actual_dict = design_document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
design_document_model.set_properties(expected_dict)
actual_dict = design_document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_DesignDocumentInformation():
def test_design_document_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
design_document_view_index_model = {} # DesignDocumentViewIndex
design_document_view_index_model['compact_running'] = True
design_document_view_index_model['language'] = 'testString'
design_document_view_index_model['signature'] = 'testString'
design_document_view_index_model['sizes'] = content_information_sizes_model
design_document_view_index_model['updater_running'] = True
design_document_view_index_model['waiting_clients'] = 0
design_document_view_index_model['waiting_commit'] = True
# Construct a json representation of a DesignDocumentInformation model
design_document_information_model_json = {}
design_document_information_model_json['name'] = 'testString'
design_document_information_model_json['view_index'] = design_document_view_index_model
# Construct a model instance of DesignDocumentInformation by calling from_dict on the json representation
design_document_information_model = DesignDocumentInformation.from_dict(design_document_information_model_json)
assert design_document_information_model != False
# Construct a model instance of DesignDocumentInformation by calling from_dict on the json representation
design_document_information_model_dict = DesignDocumentInformation.from_dict(design_document_information_model_json).__dict__
design_document_information_model2 = DesignDocumentInformation(**design_document_information_model_dict)
# Verify the model instances are equivalent
assert design_document_information_model == design_document_information_model2
# Convert model instance back to dict and verify no loss of data
design_document_information_model_json2 = design_document_information_model.to_dict()
assert design_document_information_model_json2 == design_document_information_model_json
class TestModel_DesignDocumentOptions():
def test_design_document_options_serialization(self):
# Construct a json representation of a DesignDocumentOptions model
design_document_options_model_json = {}
design_document_options_model_json['partitioned'] = True
# Construct a model instance of DesignDocumentOptions by calling from_dict on the json representation
design_document_options_model = DesignDocumentOptions.from_dict(design_document_options_model_json)
assert design_document_options_model != False
# Construct a model instance of DesignDocumentOptions by calling from_dict on the json representation
design_document_options_model_dict = DesignDocumentOptions.from_dict(design_document_options_model_json).__dict__
design_document_options_model2 = DesignDocumentOptions(**design_document_options_model_dict)
# Verify the model instances are equivalent
assert design_document_options_model == design_document_options_model2
# Convert model instance back to dict and verify no loss of data
design_document_options_model_json2 = design_document_options_model.to_dict()
assert design_document_options_model_json2 == design_document_options_model_json
class TestModel_DesignDocumentViewIndex():
def test_design_document_view_index_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
content_information_sizes_model = {} # ContentInformationSizes
content_information_sizes_model['active'] = 26
content_information_sizes_model['external'] = 26
content_information_sizes_model['file'] = 26
# Construct a json representation of a DesignDocumentViewIndex model
design_document_view_index_model_json = {}
design_document_view_index_model_json['compact_running'] = True
design_document_view_index_model_json['language'] = 'testString'
design_document_view_index_model_json['signature'] = 'testString'
design_document_view_index_model_json['sizes'] = content_information_sizes_model
design_document_view_index_model_json['updater_running'] = True
design_document_view_index_model_json['waiting_clients'] = 0
design_document_view_index_model_json['waiting_commit'] = True
# Construct a model instance of DesignDocumentViewIndex by calling from_dict on the json representation
design_document_view_index_model = DesignDocumentViewIndex.from_dict(design_document_view_index_model_json)
assert design_document_view_index_model != False
# Construct a model instance of DesignDocumentViewIndex by calling from_dict on the json representation
design_document_view_index_model_dict = DesignDocumentViewIndex.from_dict(design_document_view_index_model_json).__dict__
design_document_view_index_model2 = DesignDocumentViewIndex(**design_document_view_index_model_dict)
# Verify the model instances are equivalent
assert design_document_view_index_model == design_document_view_index_model2
# Convert model instance back to dict and verify no loss of data
design_document_view_index_model_json2 = design_document_view_index_model.to_dict()
assert design_document_view_index_model_json2 == design_document_view_index_model_json
class TestModel_DesignDocumentViewsMapReduce():
def test_design_document_views_map_reduce_serialization(self):
# Construct a json representation of a DesignDocumentViewsMapReduce model
design_document_views_map_reduce_model_json = {}
design_document_views_map_reduce_model_json['map'] = 'testString'
design_document_views_map_reduce_model_json['reduce'] = 'testString'
# Construct a model instance of DesignDocumentViewsMapReduce by calling from_dict on the json representation
design_document_views_map_reduce_model = DesignDocumentViewsMapReduce.from_dict(design_document_views_map_reduce_model_json)
assert design_document_views_map_reduce_model != False
# Construct a model instance of DesignDocumentViewsMapReduce by calling from_dict on the json representation
design_document_views_map_reduce_model_dict = DesignDocumentViewsMapReduce.from_dict(design_document_views_map_reduce_model_json).__dict__
design_document_views_map_reduce_model2 = DesignDocumentViewsMapReduce(**design_document_views_map_reduce_model_dict)
# Verify the model instances are equivalent
assert design_document_views_map_reduce_model == design_document_views_map_reduce_model2
# Convert model instance back to dict and verify no loss of data
design_document_views_map_reduce_model_json2 = design_document_views_map_reduce_model.to_dict()
assert design_document_views_map_reduce_model_json2 == design_document_views_map_reduce_model_json
class TestModel_DocsResultRow():
def test_docs_result_row_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
docs_result_row_value_model = {} # DocsResultRowValue
docs_result_row_value_model['rev'] = 'testString'
# Construct a json representation of a DocsResultRow model
docs_result_row_model_json = {}
docs_result_row_model_json['caused_by'] = 'testString'
docs_result_row_model_json['error'] = 'testString'
docs_result_row_model_json['reason'] = 'testString'
docs_result_row_model_json['doc'] = document_model
docs_result_row_model_json['id'] = 'testString'
docs_result_row_model_json['key'] = 'testString'
docs_result_row_model_json['value'] = docs_result_row_value_model
# Construct a model instance of DocsResultRow by calling from_dict on the json representation
docs_result_row_model = DocsResultRow.from_dict(docs_result_row_model_json)
assert docs_result_row_model != False
# Construct a model instance of DocsResultRow by calling from_dict on the json representation
docs_result_row_model_dict = DocsResultRow.from_dict(docs_result_row_model_json).__dict__
docs_result_row_model2 = DocsResultRow(**docs_result_row_model_dict)
# Verify the model instances are equivalent
assert docs_result_row_model == docs_result_row_model2
# Convert model instance back to dict and verify no loss of data
docs_result_row_model_json2 = docs_result_row_model.to_dict()
assert docs_result_row_model_json2 == docs_result_row_model_json
class TestModel_DocsResultRowValue():
def test_docs_result_row_value_serialization(self):
# Construct a json representation of a DocsResultRowValue model
docs_result_row_value_model_json = {}
docs_result_row_value_model_json['rev'] = 'testString'
# Construct a model instance of DocsResultRowValue by calling from_dict on the json representation
docs_result_row_value_model = DocsResultRowValue.from_dict(docs_result_row_value_model_json)
assert docs_result_row_value_model != False
# Construct a model instance of DocsResultRowValue by calling from_dict on the json representation
docs_result_row_value_model_dict = DocsResultRowValue.from_dict(docs_result_row_value_model_json).__dict__
docs_result_row_value_model2 = DocsResultRowValue(**docs_result_row_value_model_dict)
# Verify the model instances are equivalent
assert docs_result_row_value_model == docs_result_row_value_model2
# Convert model instance back to dict and verify no loss of data
docs_result_row_value_model_json2 = docs_result_row_value_model.to_dict()
assert docs_result_row_value_model_json2 == docs_result_row_value_model_json
class TestModel_Document():
def test_document_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
# Construct a json representation of a Document model
document_model_json = {}
document_model_json['_attachments'] = {}
document_model_json['_conflicts'] = ['testString']
document_model_json['_deleted'] = True
document_model_json['_deleted_conflicts'] = ['testString']
document_model_json['_id'] = 'testString'
document_model_json['_local_seq'] = 'testString'
document_model_json['_rev'] = 'testString'
document_model_json['_revisions'] = revisions_model
document_model_json['_revs_info'] = [document_revision_status_model]
document_model_json['foo'] = 'testString'
# Construct a model instance of Document by calling from_dict on the json representation
document_model = Document.from_dict(document_model_json)
assert document_model != False
# Construct a model instance of Document by calling from_dict on the json representation
document_model_dict = Document.from_dict(document_model_json).__dict__
document_model2 = Document(**document_model_dict)
# Verify the model instances are equivalent
assert document_model == document_model2
# Convert model instance back to dict and verify no loss of data
document_model_json2 = document_model.to_dict()
assert document_model_json2 == document_model_json
# Test get_properties and set_properties methods.
document_model.set_properties({})
actual_dict = document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
document_model.set_properties(expected_dict)
actual_dict = document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_DocumentResult():
def test_document_result_serialization(self):
# Construct a json representation of a DocumentResult model
document_result_model_json = {}
document_result_model_json['id'] = 'testString'
document_result_model_json['rev'] = 'testString'
document_result_model_json['ok'] = True
document_result_model_json['caused_by'] = 'testString'
document_result_model_json['error'] = 'testString'
document_result_model_json['reason'] = 'testString'
# Construct a model instance of DocumentResult by calling from_dict on the json representation
document_result_model = DocumentResult.from_dict(document_result_model_json)
assert document_result_model != False
# Construct a model instance of DocumentResult by calling from_dict on the json representation
document_result_model_dict = DocumentResult.from_dict(document_result_model_json).__dict__
document_result_model2 = DocumentResult(**document_result_model_dict)
# Verify the model instances are equivalent
assert document_result_model == document_result_model2
# Convert model instance back to dict and verify no loss of data
document_result_model_json2 = document_result_model.to_dict()
assert document_result_model_json2 == document_result_model_json
class TestModel_DocumentRevisionStatus():
def test_document_revision_status_serialization(self):
# Construct a json representation of a DocumentRevisionStatus model
document_revision_status_model_json = {}
document_revision_status_model_json['rev'] = 'testString'
document_revision_status_model_json['status'] = 'available'
# Construct a model instance of DocumentRevisionStatus by calling from_dict on the json representation
document_revision_status_model = DocumentRevisionStatus.from_dict(document_revision_status_model_json)
assert document_revision_status_model != False
# Construct a model instance of DocumentRevisionStatus by calling from_dict on the json representation
document_revision_status_model_dict = DocumentRevisionStatus.from_dict(document_revision_status_model_json).__dict__
document_revision_status_model2 = DocumentRevisionStatus(**document_revision_status_model_dict)
# Verify the model instances are equivalent
assert document_revision_status_model == document_revision_status_model2
# Convert model instance back to dict and verify no loss of data
document_revision_status_model_json2 = document_revision_status_model.to_dict()
assert document_revision_status_model_json2 == document_revision_status_model_json
class TestModel_DocumentShardInfo():
def test_document_shard_info_serialization(self):
# Construct a json representation of a DocumentShardInfo model
document_shard_info_model_json = {}
document_shard_info_model_json['nodes'] = ['testString']
document_shard_info_model_json['range'] = 'testString'
# Construct a model instance of DocumentShardInfo by calling from_dict on the json representation
document_shard_info_model = DocumentShardInfo.from_dict(document_shard_info_model_json)
assert document_shard_info_model != False
# Construct a model instance of DocumentShardInfo by calling from_dict on the json representation
document_shard_info_model_dict = DocumentShardInfo.from_dict(document_shard_info_model_json).__dict__
document_shard_info_model2 = DocumentShardInfo(**document_shard_info_model_dict)
# Verify the model instances are equivalent
assert document_shard_info_model == document_shard_info_model2
# Convert model instance back to dict and verify no loss of data
document_shard_info_model_json2 = document_shard_info_model.to_dict()
assert document_shard_info_model_json2 == document_shard_info_model_json
class TestModel_ExecutionStats():
def test_execution_stats_serialization(self):
# Construct a json representation of a ExecutionStats model
execution_stats_model_json = {}
execution_stats_model_json['execution_time_ms'] = 72.5
execution_stats_model_json['results_returned'] = 0
execution_stats_model_json['total_docs_examined'] = 0
execution_stats_model_json['total_keys_examined'] = 0
execution_stats_model_json['total_quorum_docs_examined'] = 0
# Construct a model instance of ExecutionStats by calling from_dict on the json representation
execution_stats_model = ExecutionStats.from_dict(execution_stats_model_json)
assert execution_stats_model != False
# Construct a model instance of ExecutionStats by calling from_dict on the json representation
execution_stats_model_dict = ExecutionStats.from_dict(execution_stats_model_json).__dict__
execution_stats_model2 = ExecutionStats(**execution_stats_model_dict)
# Verify the model instances are equivalent
assert execution_stats_model == execution_stats_model2
# Convert model instance back to dict and verify no loss of data
execution_stats_model_json2 = execution_stats_model.to_dict()
assert execution_stats_model_json2 == execution_stats_model_json
class TestModel_ExplainResult():
def test_explain_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
index_information_model = {} # IndexInformation
index_information_model['ddoc'] = 'testString'
index_information_model['def'] = index_definition_model
index_information_model['name'] = 'testString'
index_information_model['type'] = 'json'
explain_result_range_model = {} # ExplainResultRange
explain_result_range_model['end_key'] = ['testString']
explain_result_range_model['start_key'] = ['testString']
# Construct a json representation of a ExplainResult model
explain_result_model_json = {}
explain_result_model_json['dbname'] = 'testString'
explain_result_model_json['fields'] = ['testString']
explain_result_model_json['index'] = index_information_model
explain_result_model_json['limit'] = 0
explain_result_model_json['opts'] = {}
explain_result_model_json['range'] = explain_result_range_model
explain_result_model_json['selector'] = {}
explain_result_model_json['skip'] = 0
# Construct a model instance of ExplainResult by calling from_dict on the json representation
explain_result_model = ExplainResult.from_dict(explain_result_model_json)
assert explain_result_model != False
# Construct a model instance of ExplainResult by calling from_dict on the json representation
explain_result_model_dict = ExplainResult.from_dict(explain_result_model_json).__dict__
explain_result_model2 = ExplainResult(**explain_result_model_dict)
# Verify the model instances are equivalent
assert explain_result_model == explain_result_model2
# Convert model instance back to dict and verify no loss of data
explain_result_model_json2 = explain_result_model.to_dict()
assert explain_result_model_json2 == explain_result_model_json
class TestModel_ExplainResultRange():
def test_explain_result_range_serialization(self):
# Construct a json representation of a ExplainResultRange model
explain_result_range_model_json = {}
explain_result_range_model_json['end_key'] = ['testString']
explain_result_range_model_json['start_key'] = ['testString']
# Construct a model instance of ExplainResultRange by calling from_dict on the json representation
explain_result_range_model = ExplainResultRange.from_dict(explain_result_range_model_json)
assert explain_result_range_model != False
# Construct a model instance of ExplainResultRange by calling from_dict on the json representation
explain_result_range_model_dict = ExplainResultRange.from_dict(explain_result_range_model_json).__dict__
explain_result_range_model2 = ExplainResultRange(**explain_result_range_model_dict)
# Verify the model instances are equivalent
assert explain_result_range_model == explain_result_range_model2
# Convert model instance back to dict and verify no loss of data
explain_result_range_model_json2 = explain_result_range_model.to_dict()
assert explain_result_range_model_json2 == explain_result_range_model_json
class TestModel_FindResult():
def test_find_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
execution_stats_model = {} # ExecutionStats
execution_stats_model['execution_time_ms'] = 72.5
execution_stats_model['results_returned'] = 0
execution_stats_model['total_docs_examined'] = 0
execution_stats_model['total_keys_examined'] = 0
execution_stats_model['total_quorum_docs_examined'] = 0
# Construct a json representation of a FindResult model
find_result_model_json = {}
find_result_model_json['bookmark'] = 'testString'
find_result_model_json['docs'] = [document_model]
find_result_model_json['execution_stats'] = execution_stats_model
find_result_model_json['warning'] = 'testString'
# Construct a model instance of FindResult by calling from_dict on the json representation
find_result_model = FindResult.from_dict(find_result_model_json)
assert find_result_model != False
# Construct a model instance of FindResult by calling from_dict on the json representation
find_result_model_dict = FindResult.from_dict(find_result_model_json).__dict__
find_result_model2 = FindResult(**find_result_model_dict)
# Verify the model instances are equivalent
assert find_result_model == find_result_model2
# Convert model instance back to dict and verify no loss of data
find_result_model_json2 = find_result_model.to_dict()
assert find_result_model_json2 == find_result_model_json
class TestModel_GeoIndexDefinition():
def test_geo_index_definition_serialization(self):
# Construct a json representation of a GeoIndexDefinition model
geo_index_definition_model_json = {}
geo_index_definition_model_json['index'] = 'testString'
# Construct a model instance of GeoIndexDefinition by calling from_dict on the json representation
geo_index_definition_model = GeoIndexDefinition.from_dict(geo_index_definition_model_json)
assert geo_index_definition_model != False
# Construct a model instance of GeoIndexDefinition by calling from_dict on the json representation
geo_index_definition_model_dict = GeoIndexDefinition.from_dict(geo_index_definition_model_json).__dict__
geo_index_definition_model2 = GeoIndexDefinition(**geo_index_definition_model_dict)
# Verify the model instances are equivalent
assert geo_index_definition_model == geo_index_definition_model2
# Convert model instance back to dict and verify no loss of data
geo_index_definition_model_json2 = geo_index_definition_model.to_dict()
assert geo_index_definition_model_json2 == geo_index_definition_model_json
class TestModel_GeoIndexInformation():
def test_geo_index_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
geo_index_stats_model = {} # GeoIndexStats
geo_index_stats_model['data_size'] = 0
geo_index_stats_model['disk_size'] = 0
geo_index_stats_model['doc_count'] = 0
# Construct a json representation of a GeoIndexInformation model
geo_index_information_model_json = {}
geo_index_information_model_json['geo_index'] = geo_index_stats_model
geo_index_information_model_json['name'] = 'testString'
# Construct a model instance of GeoIndexInformation by calling from_dict on the json representation
geo_index_information_model = GeoIndexInformation.from_dict(geo_index_information_model_json)
assert geo_index_information_model != False
# Construct a model instance of GeoIndexInformation by calling from_dict on the json representation
geo_index_information_model_dict = GeoIndexInformation.from_dict(geo_index_information_model_json).__dict__
geo_index_information_model2 = GeoIndexInformation(**geo_index_information_model_dict)
# Verify the model instances are equivalent
assert geo_index_information_model == geo_index_information_model2
# Convert model instance back to dict and verify no loss of data
geo_index_information_model_json2 = geo_index_information_model.to_dict()
assert geo_index_information_model_json2 == geo_index_information_model_json
class TestModel_GeoIndexStats():
def test_geo_index_stats_serialization(self):
# Construct a json representation of a GeoIndexStats model
geo_index_stats_model_json = {}
geo_index_stats_model_json['data_size'] = 0
geo_index_stats_model_json['disk_size'] = 0
geo_index_stats_model_json['doc_count'] = 0
# Construct a model instance of GeoIndexStats by calling from_dict on the json representation
geo_index_stats_model = GeoIndexStats.from_dict(geo_index_stats_model_json)
assert geo_index_stats_model != False
# Construct a model instance of GeoIndexStats by calling from_dict on the json representation
geo_index_stats_model_dict = GeoIndexStats.from_dict(geo_index_stats_model_json).__dict__
geo_index_stats_model2 = GeoIndexStats(**geo_index_stats_model_dict)
# Verify the model instances are equivalent
assert geo_index_stats_model == geo_index_stats_model2
# Convert model instance back to dict and verify no loss of data
geo_index_stats_model_json2 = geo_index_stats_model.to_dict()
assert geo_index_stats_model_json2 == geo_index_stats_model_json
class TestModel_GeoJsonFeature():
def test_geo_json_feature_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_object_model = {} # GeoJsonGeometry
geo_json_geometry_object_model['type'] = 'Point'
geo_json_geometry_object_model['coordinates'] = ['testString']
# Construct a json representation of a GeoJsonFeature model
geo_json_feature_model_json = {}
geo_json_feature_model_json['_id'] = 'testString'
geo_json_feature_model_json['_rev'] = 'testString'
geo_json_feature_model_json['bbox'] = [72.5]
geo_json_feature_model_json['geometry'] = geo_json_geometry_object_model
geo_json_feature_model_json['properties'] = {}
geo_json_feature_model_json['type'] = 'Feature'
geo_json_feature_model_json['foo'] = 'testString'
# Construct a model instance of GeoJsonFeature by calling from_dict on the json representation
geo_json_feature_model = GeoJsonFeature.from_dict(geo_json_feature_model_json)
assert geo_json_feature_model != False
# Construct a model instance of GeoJsonFeature by calling from_dict on the json representation
geo_json_feature_model_dict = GeoJsonFeature.from_dict(geo_json_feature_model_json).__dict__
geo_json_feature_model2 = GeoJsonFeature(**geo_json_feature_model_dict)
# Verify the model instances are equivalent
assert geo_json_feature_model == geo_json_feature_model2
# Convert model instance back to dict and verify no loss of data
geo_json_feature_model_json2 = geo_json_feature_model.to_dict()
assert geo_json_feature_model_json2 == geo_json_feature_model_json
# Test get_properties and set_properties methods.
geo_json_feature_model.set_properties({})
actual_dict = geo_json_feature_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
geo_json_feature_model.set_properties(expected_dict)
actual_dict = geo_json_feature_model.get_properties()
assert actual_dict == expected_dict
class TestModel_GeoResult():
def test_geo_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_object_model = {} # GeoJsonGeometry
geo_json_geometry_object_model['type'] = 'Point'
geo_json_geometry_object_model['coordinates'] = ['testString']
geo_json_feature_model = {} # GeoJsonFeature
geo_json_feature_model['_id'] = 'testString'
geo_json_feature_model['_rev'] = 'testString'
geo_json_feature_model['bbox'] = [72.5]
geo_json_feature_model['geometry'] = geo_json_geometry_object_model
geo_json_feature_model['properties'] = {}
geo_json_feature_model['type'] = 'Feature'
geo_json_feature_model['foo'] = 'testString'
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
geo_result_row_model = {} # GeoResultRow
geo_result_row_model['doc'] = document_model
geo_result_row_model['geometry'] = geo_json_geometry_model
geo_result_row_model['id'] = 'testString'
geo_result_row_model['rev'] = 'testString'
# Construct a json representation of a GeoResult model
geo_result_model_json = {}
geo_result_model_json['bookmark'] = 'testString'
geo_result_model_json['features'] = [geo_json_feature_model]
geo_result_model_json['rows'] = [geo_result_row_model]
geo_result_model_json['type'] = 'FeatureCollection'
# Construct a model instance of GeoResult by calling from_dict on the json representation
geo_result_model = GeoResult.from_dict(geo_result_model_json)
assert geo_result_model != False
# Construct a model instance of GeoResult by calling from_dict on the json representation
geo_result_model_dict = GeoResult.from_dict(geo_result_model_json).__dict__
geo_result_model2 = GeoResult(**geo_result_model_dict)
# Verify the model instances are equivalent
assert geo_result_model == geo_result_model2
# Convert model instance back to dict and verify no loss of data
geo_result_model_json2 = geo_result_model.to_dict()
assert geo_result_model_json2 == geo_result_model_json
class TestModel_GeoResultRow():
def test_geo_result_row_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
# Construct a json representation of a GeoResultRow model
geo_result_row_model_json = {}
geo_result_row_model_json['doc'] = document_model
geo_result_row_model_json['geometry'] = geo_json_geometry_model
geo_result_row_model_json['id'] = 'testString'
geo_result_row_model_json['rev'] = 'testString'
# Construct a model instance of GeoResultRow by calling from_dict on the json representation
geo_result_row_model = GeoResultRow.from_dict(geo_result_row_model_json)
assert geo_result_row_model != False
# Construct a model instance of GeoResultRow by calling from_dict on the json representation
geo_result_row_model_dict = GeoResultRow.from_dict(geo_result_row_model_json).__dict__
geo_result_row_model2 = GeoResultRow(**geo_result_row_model_dict)
# Verify the model instances are equivalent
assert geo_result_row_model == geo_result_row_model2
# Convert model instance back to dict and verify no loss of data
geo_result_row_model_json2 = geo_result_row_model.to_dict()
assert geo_result_row_model_json2 == geo_result_row_model_json
class TestModel_IndexDefinition():
def test_index_definition_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
# Construct a json representation of a IndexDefinition model
index_definition_model_json = {}
index_definition_model_json['default_analyzer'] = analyzer_model
index_definition_model_json['default_field'] = index_text_operator_default_field_model
index_definition_model_json['fields'] = [index_field_model]
index_definition_model_json['index_array_lengths'] = True
index_definition_model_json['partial_filter_selector'] = {}
# Construct a model instance of IndexDefinition by calling from_dict on the json representation
index_definition_model = IndexDefinition.from_dict(index_definition_model_json)
assert index_definition_model != False
# Construct a model instance of IndexDefinition by calling from_dict on the json representation
index_definition_model_dict = IndexDefinition.from_dict(index_definition_model_json).__dict__
index_definition_model2 = IndexDefinition(**index_definition_model_dict)
# Verify the model instances are equivalent
assert index_definition_model == index_definition_model2
# Convert model instance back to dict and verify no loss of data
index_definition_model_json2 = index_definition_model.to_dict()
assert index_definition_model_json2 == index_definition_model_json
class TestModel_IndexField():
def test_index_field_serialization(self):
# Construct a json representation of a IndexField model
index_field_model_json = {}
index_field_model_json['name'] = 'testString'
index_field_model_json['type'] = 'boolean'
index_field_model_json['foo'] = 'asc'
# Construct a model instance of IndexField by calling from_dict on the json representation
index_field_model = IndexField.from_dict(index_field_model_json)
assert index_field_model != False
# Construct a model instance of IndexField by calling from_dict on the json representation
index_field_model_dict = IndexField.from_dict(index_field_model_json).__dict__
index_field_model2 = IndexField(**index_field_model_dict)
# Verify the model instances are equivalent
assert index_field_model == index_field_model2
# Convert model instance back to dict and verify no loss of data
index_field_model_json2 = index_field_model.to_dict()
assert index_field_model_json2 == index_field_model_json
# Test get_properties and set_properties methods.
index_field_model.set_properties({})
actual_dict = index_field_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'asc'}
index_field_model.set_properties(expected_dict)
actual_dict = index_field_model.get_properties()
assert actual_dict == expected_dict
class TestModel_IndexInformation():
def test_index_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
# Construct a json representation of a IndexInformation model
index_information_model_json = {}
index_information_model_json['ddoc'] = 'testString'
index_information_model_json['def'] = index_definition_model
index_information_model_json['name'] = 'testString'
index_information_model_json['type'] = 'json'
# Construct a model instance of IndexInformation by calling from_dict on the json representation
index_information_model = IndexInformation.from_dict(index_information_model_json)
assert index_information_model != False
# Construct a model instance of IndexInformation by calling from_dict on the json representation
index_information_model_dict = IndexInformation.from_dict(index_information_model_json).__dict__
index_information_model2 = IndexInformation(**index_information_model_dict)
# Verify the model instances are equivalent
assert index_information_model == index_information_model2
# Convert model instance back to dict and verify no loss of data
index_information_model_json2 = index_information_model.to_dict()
assert index_information_model_json2 == index_information_model_json
class TestModel_IndexResult():
def test_index_result_serialization(self):
# Construct a json representation of a IndexResult model
index_result_model_json = {}
index_result_model_json['id'] = 'testString'
index_result_model_json['name'] = 'testString'
index_result_model_json['result'] = 'created'
# Construct a model instance of IndexResult by calling from_dict on the json representation
index_result_model = IndexResult.from_dict(index_result_model_json)
assert index_result_model != False
# Construct a model instance of IndexResult by calling from_dict on the json representation
index_result_model_dict = IndexResult.from_dict(index_result_model_json).__dict__
index_result_model2 = IndexResult(**index_result_model_dict)
# Verify the model instances are equivalent
assert index_result_model == index_result_model2
# Convert model instance back to dict and verify no loss of data
index_result_model_json2 = index_result_model.to_dict()
assert index_result_model_json2 == index_result_model_json
class TestModel_IndexTextOperatorDefaultField():
def test_index_text_operator_default_field_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
# Construct a json representation of a IndexTextOperatorDefaultField model
index_text_operator_default_field_model_json = {}
index_text_operator_default_field_model_json['analyzer'] = analyzer_model
index_text_operator_default_field_model_json['enabled'] = True
# Construct a model instance of IndexTextOperatorDefaultField by calling from_dict on the json representation
index_text_operator_default_field_model = IndexTextOperatorDefaultField.from_dict(index_text_operator_default_field_model_json)
assert index_text_operator_default_field_model != False
# Construct a model instance of IndexTextOperatorDefaultField by calling from_dict on the json representation
index_text_operator_default_field_model_dict = IndexTextOperatorDefaultField.from_dict(index_text_operator_default_field_model_json).__dict__
index_text_operator_default_field_model2 = IndexTextOperatorDefaultField(**index_text_operator_default_field_model_dict)
# Verify the model instances are equivalent
assert index_text_operator_default_field_model == index_text_operator_default_field_model2
# Convert model instance back to dict and verify no loss of data
index_text_operator_default_field_model_json2 = index_text_operator_default_field_model.to_dict()
assert index_text_operator_default_field_model_json2 == index_text_operator_default_field_model_json
class TestModel_IndexesInformation():
def test_indexes_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
index_text_operator_default_field_model = {} # IndexTextOperatorDefaultField
index_text_operator_default_field_model['analyzer'] = analyzer_model
index_text_operator_default_field_model['enabled'] = True
index_field_model = {} # IndexField
index_field_model['name'] = 'testString'
index_field_model['type'] = 'boolean'
index_field_model['foo'] = 'asc'
index_definition_model = {} # IndexDefinition
index_definition_model['default_analyzer'] = analyzer_model
index_definition_model['default_field'] = index_text_operator_default_field_model
index_definition_model['fields'] = [index_field_model]
index_definition_model['index_array_lengths'] = True
index_definition_model['partial_filter_selector'] = {}
index_information_model = {} # IndexInformation
index_information_model['ddoc'] = 'testString'
index_information_model['def'] = index_definition_model
index_information_model['name'] = 'testString'
index_information_model['type'] = 'json'
# Construct a json representation of a IndexesInformation model
indexes_information_model_json = {}
indexes_information_model_json['total_rows'] = 0
indexes_information_model_json['indexes'] = [index_information_model]
# Construct a model instance of IndexesInformation by calling from_dict on the json representation
indexes_information_model = IndexesInformation.from_dict(indexes_information_model_json)
assert indexes_information_model != False
# Construct a model instance of IndexesInformation by calling from_dict on the json representation
indexes_information_model_dict = IndexesInformation.from_dict(indexes_information_model_json).__dict__
indexes_information_model2 = IndexesInformation(**indexes_information_model_dict)
# Verify the model instances are equivalent
assert indexes_information_model == indexes_information_model2
# Convert model instance back to dict and verify no loss of data
indexes_information_model_json2 = indexes_information_model.to_dict()
assert indexes_information_model_json2 == indexes_information_model_json
class TestModel_MembershipInformation():
def test_membership_information_serialization(self):
# Construct a json representation of a MembershipInformation model
membership_information_model_json = {}
membership_information_model_json['all_nodes'] = ['testString']
membership_information_model_json['cluster_nodes'] = ['testString']
# Construct a model instance of MembershipInformation by calling from_dict on the json representation
membership_information_model = MembershipInformation.from_dict(membership_information_model_json)
assert membership_information_model != False
# Construct a model instance of MembershipInformation by calling from_dict on the json representation
membership_information_model_dict = MembershipInformation.from_dict(membership_information_model_json).__dict__
membership_information_model2 = MembershipInformation(**membership_information_model_dict)
# Verify the model instances are equivalent
assert membership_information_model == membership_information_model2
# Convert model instance back to dict and verify no loss of data
membership_information_model_json2 = membership_information_model.to_dict()
assert membership_information_model_json2 == membership_information_model_json
class TestModel_Ok():
def test_ok_serialization(self):
# Construct a json representation of a Ok model
ok_model_json = {}
ok_model_json['ok'] = True
# Construct a model instance of Ok by calling from_dict on the json representation
ok_model = Ok.from_dict(ok_model_json)
assert ok_model != False
# Construct a model instance of Ok by calling from_dict on the json representation
ok_model_dict = Ok.from_dict(ok_model_json).__dict__
ok_model2 = Ok(**ok_model_dict)
# Verify the model instances are equivalent
assert ok_model == ok_model2
# Convert model instance back to dict and verify no loss of data
ok_model_json2 = ok_model.to_dict()
assert ok_model_json2 == ok_model_json
class TestModel_PartitionInformation():
def test_partition_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
partition_information_indexes_indexes_model = {} # PartitionInformationIndexesIndexes
partition_information_indexes_indexes_model['search'] = 0
partition_information_indexes_indexes_model['view'] = 0
partition_information_indexes_model = {} # PartitionInformationIndexes
partition_information_indexes_model['count'] = 0
partition_information_indexes_model['indexes'] = partition_information_indexes_indexes_model
partition_information_indexes_model['limit'] = 0
partition_information_sizes_model = {} # PartitionInformationSizes
partition_information_sizes_model['active'] = 0
partition_information_sizes_model['external'] = 0
# Construct a json representation of a PartitionInformation model
partition_information_model_json = {}
partition_information_model_json['db_name'] = 'testString'
partition_information_model_json['doc_count'] = 0
partition_information_model_json['doc_del_count'] = 0
partition_information_model_json['partition'] = 'testString'
partition_information_model_json['partitioned_indexes'] = partition_information_indexes_model
partition_information_model_json['sizes'] = partition_information_sizes_model
# Construct a model instance of PartitionInformation by calling from_dict on the json representation
partition_information_model = PartitionInformation.from_dict(partition_information_model_json)
assert partition_information_model != False
# Construct a model instance of PartitionInformation by calling from_dict on the json representation
partition_information_model_dict = PartitionInformation.from_dict(partition_information_model_json).__dict__
partition_information_model2 = PartitionInformation(**partition_information_model_dict)
# Verify the model instances are equivalent
assert partition_information_model == partition_information_model2
# Convert model instance back to dict and verify no loss of data
partition_information_model_json2 = partition_information_model.to_dict()
assert partition_information_model_json2 == partition_information_model_json
class TestModel_PartitionInformationIndexes():
def test_partition_information_indexes_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
partition_information_indexes_indexes_model = {} # PartitionInformationIndexesIndexes
partition_information_indexes_indexes_model['search'] = 0
partition_information_indexes_indexes_model['view'] = 0
# Construct a json representation of a PartitionInformationIndexes model
partition_information_indexes_model_json = {}
partition_information_indexes_model_json['count'] = 0
partition_information_indexes_model_json['indexes'] = partition_information_indexes_indexes_model
partition_information_indexes_model_json['limit'] = 0
# Construct a model instance of PartitionInformationIndexes by calling from_dict on the json representation
partition_information_indexes_model = PartitionInformationIndexes.from_dict(partition_information_indexes_model_json)
assert partition_information_indexes_model != False
# Construct a model instance of PartitionInformationIndexes by calling from_dict on the json representation
partition_information_indexes_model_dict = PartitionInformationIndexes.from_dict(partition_information_indexes_model_json).__dict__
partition_information_indexes_model2 = PartitionInformationIndexes(**partition_information_indexes_model_dict)
# Verify the model instances are equivalent
assert partition_information_indexes_model == partition_information_indexes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_indexes_model_json2 = partition_information_indexes_model.to_dict()
assert partition_information_indexes_model_json2 == partition_information_indexes_model_json
class TestModel_PartitionInformationIndexesIndexes():
def test_partition_information_indexes_indexes_serialization(self):
# Construct a json representation of a PartitionInformationIndexesIndexes model
partition_information_indexes_indexes_model_json = {}
partition_information_indexes_indexes_model_json['search'] = 0
partition_information_indexes_indexes_model_json['view'] = 0
# Construct a model instance of PartitionInformationIndexesIndexes by calling from_dict on the json representation
partition_information_indexes_indexes_model = PartitionInformationIndexesIndexes.from_dict(partition_information_indexes_indexes_model_json)
assert partition_information_indexes_indexes_model != False
# Construct a model instance of PartitionInformationIndexesIndexes by calling from_dict on the json representation
partition_information_indexes_indexes_model_dict = PartitionInformationIndexesIndexes.from_dict(partition_information_indexes_indexes_model_json).__dict__
partition_information_indexes_indexes_model2 = PartitionInformationIndexesIndexes(**partition_information_indexes_indexes_model_dict)
# Verify the model instances are equivalent
assert partition_information_indexes_indexes_model == partition_information_indexes_indexes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_indexes_indexes_model_json2 = partition_information_indexes_indexes_model.to_dict()
assert partition_information_indexes_indexes_model_json2 == partition_information_indexes_indexes_model_json
class TestModel_PartitionInformationSizes():
def test_partition_information_sizes_serialization(self):
# Construct a json representation of a PartitionInformationSizes model
partition_information_sizes_model_json = {}
partition_information_sizes_model_json['active'] = 0
partition_information_sizes_model_json['external'] = 0
# Construct a model instance of PartitionInformationSizes by calling from_dict on the json representation
partition_information_sizes_model = PartitionInformationSizes.from_dict(partition_information_sizes_model_json)
assert partition_information_sizes_model != False
# Construct a model instance of PartitionInformationSizes by calling from_dict on the json representation
partition_information_sizes_model_dict = PartitionInformationSizes.from_dict(partition_information_sizes_model_json).__dict__
partition_information_sizes_model2 = PartitionInformationSizes(**partition_information_sizes_model_dict)
# Verify the model instances are equivalent
assert partition_information_sizes_model == partition_information_sizes_model2
# Convert model instance back to dict and verify no loss of data
partition_information_sizes_model_json2 = partition_information_sizes_model.to_dict()
assert partition_information_sizes_model_json2 == partition_information_sizes_model_json
class TestModel_ReplicationCreateTargetParameters():
def test_replication_create_target_parameters_serialization(self):
# Construct a json representation of a ReplicationCreateTargetParameters model
replication_create_target_parameters_model_json = {}
replication_create_target_parameters_model_json['n'] = 1
replication_create_target_parameters_model_json['partitioned'] = False
replication_create_target_parameters_model_json['q'] = 1
# Construct a model instance of ReplicationCreateTargetParameters by calling from_dict on the json representation
replication_create_target_parameters_model = ReplicationCreateTargetParameters.from_dict(replication_create_target_parameters_model_json)
assert replication_create_target_parameters_model != False
# Construct a model instance of ReplicationCreateTargetParameters by calling from_dict on the json representation
replication_create_target_parameters_model_dict = ReplicationCreateTargetParameters.from_dict(replication_create_target_parameters_model_json).__dict__
replication_create_target_parameters_model2 = ReplicationCreateTargetParameters(**replication_create_target_parameters_model_dict)
# Verify the model instances are equivalent
assert replication_create_target_parameters_model == replication_create_target_parameters_model2
# Convert model instance back to dict and verify no loss of data
replication_create_target_parameters_model_json2 = replication_create_target_parameters_model.to_dict()
assert replication_create_target_parameters_model_json2 == replication_create_target_parameters_model_json
class TestModel_ReplicationDatabase():
def test_replication_database_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
replication_database_auth_model = {} # ReplicationDatabaseAuth
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
# Construct a json representation of a ReplicationDatabase model
replication_database_model_json = {}
replication_database_model_json['auth'] = replication_database_auth_model
replication_database_model_json['headers'] = {}
replication_database_model_json['url'] = 'testString'
# Construct a model instance of ReplicationDatabase by calling from_dict on the json representation
replication_database_model = ReplicationDatabase.from_dict(replication_database_model_json)
assert replication_database_model != False
# Construct a model instance of ReplicationDatabase by calling from_dict on the json representation
replication_database_model_dict = ReplicationDatabase.from_dict(replication_database_model_json).__dict__
replication_database_model2 = ReplicationDatabase(**replication_database_model_dict)
# Verify the model instances are equivalent
assert replication_database_model == replication_database_model2
# Convert model instance back to dict and verify no loss of data
replication_database_model_json2 = replication_database_model.to_dict()
assert replication_database_model_json2 == replication_database_model_json
class TestModel_ReplicationDatabaseAuth():
def test_replication_database_auth_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
# Construct a json representation of a ReplicationDatabaseAuth model
replication_database_auth_model_json = {}
replication_database_auth_model_json['basic'] = replication_database_auth_basic_model
replication_database_auth_model_json['iam'] = replication_database_auth_iam_model
# Construct a model instance of ReplicationDatabaseAuth by calling from_dict on the json representation
replication_database_auth_model = ReplicationDatabaseAuth.from_dict(replication_database_auth_model_json)
assert replication_database_auth_model != False
# Construct a model instance of ReplicationDatabaseAuth by calling from_dict on the json representation
replication_database_auth_model_dict = ReplicationDatabaseAuth.from_dict(replication_database_auth_model_json).__dict__
replication_database_auth_model2 = ReplicationDatabaseAuth(**replication_database_auth_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_model == replication_database_auth_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_model_json2 = replication_database_auth_model.to_dict()
assert replication_database_auth_model_json2 == replication_database_auth_model_json
class TestModel_ReplicationDatabaseAuthBasic():
def test_replication_database_auth_basic_serialization(self):
# Construct a json representation of a ReplicationDatabaseAuthBasic model
replication_database_auth_basic_model_json = {}
replication_database_auth_basic_model_json['password'] = 'testString'
replication_database_auth_basic_model_json['username'] = 'testString'
# Construct a model instance of ReplicationDatabaseAuthBasic by calling from_dict on the json representation
replication_database_auth_basic_model = ReplicationDatabaseAuthBasic.from_dict(replication_database_auth_basic_model_json)
assert replication_database_auth_basic_model != False
# Construct a model instance of ReplicationDatabaseAuthBasic by calling from_dict on the json representation
replication_database_auth_basic_model_dict = ReplicationDatabaseAuthBasic.from_dict(replication_database_auth_basic_model_json).__dict__
replication_database_auth_basic_model2 = ReplicationDatabaseAuthBasic(**replication_database_auth_basic_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_basic_model == replication_database_auth_basic_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_basic_model_json2 = replication_database_auth_basic_model.to_dict()
assert replication_database_auth_basic_model_json2 == replication_database_auth_basic_model_json
class TestModel_ReplicationDatabaseAuthIam():
def test_replication_database_auth_iam_serialization(self):
# Construct a json representation of a ReplicationDatabaseAuthIam model
replication_database_auth_iam_model_json = {}
replication_database_auth_iam_model_json['api_key'] = 'testString'
# Construct a model instance of ReplicationDatabaseAuthIam by calling from_dict on the json representation
replication_database_auth_iam_model = ReplicationDatabaseAuthIam.from_dict(replication_database_auth_iam_model_json)
assert replication_database_auth_iam_model != False
# Construct a model instance of ReplicationDatabaseAuthIam by calling from_dict on the json representation
replication_database_auth_iam_model_dict = ReplicationDatabaseAuthIam.from_dict(replication_database_auth_iam_model_json).__dict__
replication_database_auth_iam_model2 = ReplicationDatabaseAuthIam(**replication_database_auth_iam_model_dict)
# Verify the model instances are equivalent
assert replication_database_auth_iam_model == replication_database_auth_iam_model2
# Convert model instance back to dict and verify no loss of data
replication_database_auth_iam_model_json2 = replication_database_auth_iam_model.to_dict()
assert replication_database_auth_iam_model_json2 == replication_database_auth_iam_model_json
class TestModel_ReplicationDocument():
def test_replication_document_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
replication_create_target_parameters_model = {} # ReplicationCreateTargetParameters
replication_create_target_parameters_model['n'] = 1
replication_create_target_parameters_model['partitioned'] = False
replication_create_target_parameters_model['q'] = 1
replication_database_auth_basic_model = {} # ReplicationDatabaseAuthBasic
replication_database_auth_basic_model['password'] = 'testString'
replication_database_auth_basic_model['username'] = 'testString'
replication_database_auth_iam_model = {} # ReplicationDatabaseAuthIam
replication_database_auth_iam_model['api_key'] = 'testString'
replication_database_auth_model = {} # ReplicationDatabaseAuth
replication_database_auth_model['basic'] = replication_database_auth_basic_model
replication_database_auth_model['iam'] = replication_database_auth_iam_model
replication_database_model = {} # ReplicationDatabase
replication_database_model['auth'] = replication_database_auth_model
replication_database_model['headers'] = {}
replication_database_model['url'] = 'testString'
user_context_model = {} # UserContext
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a json representation of a ReplicationDocument model
replication_document_model_json = {}
replication_document_model_json['_attachments'] = {}
replication_document_model_json['_conflicts'] = ['testString']
replication_document_model_json['_deleted'] = True
replication_document_model_json['_deleted_conflicts'] = ['testString']
replication_document_model_json['_id'] = 'testString'
replication_document_model_json['_local_seq'] = 'testString'
replication_document_model_json['_rev'] = 'testString'
replication_document_model_json['_revisions'] = revisions_model
replication_document_model_json['_revs_info'] = [document_revision_status_model]
replication_document_model_json['cancel'] = True
replication_document_model_json['checkpoint_interval'] = 0
replication_document_model_json['connection_timeout'] = 0
replication_document_model_json['continuous'] = False
replication_document_model_json['create_target'] = False
replication_document_model_json['create_target_params'] = replication_create_target_parameters_model
replication_document_model_json['doc_ids'] = ['testString']
replication_document_model_json['filter'] = 'testString'
replication_document_model_json['http_connections'] = 1
replication_document_model_json['query_params'] = {}
replication_document_model_json['retries_per_request'] = 0
replication_document_model_json['selector'] = {}
replication_document_model_json['since_seq'] = 'testString'
replication_document_model_json['socket_options'] = 'testString'
replication_document_model_json['source'] = replication_database_model
replication_document_model_json['source_proxy'] = 'testString'
replication_document_model_json['target'] = replication_database_model
replication_document_model_json['target_proxy'] = 'testString'
replication_document_model_json['use_checkpoints'] = True
replication_document_model_json['user_ctx'] = user_context_model
replication_document_model_json['worker_batch_size'] = 1
replication_document_model_json['worker_processes'] = 1
replication_document_model_json['foo'] = 'testString'
# Construct a model instance of ReplicationDocument by calling from_dict on the json representation
replication_document_model = ReplicationDocument.from_dict(replication_document_model_json)
assert replication_document_model != False
# Construct a model instance of ReplicationDocument by calling from_dict on the json representation
replication_document_model_dict = ReplicationDocument.from_dict(replication_document_model_json).__dict__
replication_document_model2 = ReplicationDocument(**replication_document_model_dict)
# Verify the model instances are equivalent
assert replication_document_model == replication_document_model2
# Convert model instance back to dict and verify no loss of data
replication_document_model_json2 = replication_document_model.to_dict()
assert replication_document_model_json2 == replication_document_model_json
# Test get_properties and set_properties methods.
replication_document_model.set_properties({})
actual_dict = replication_document_model.get_properties()
assert actual_dict == {}
expected_dict = {'foo': 'testString'}
replication_document_model.set_properties(expected_dict)
actual_dict = replication_document_model.get_properties()
assert actual_dict == expected_dict
class TestModel_Revisions():
def test_revisions_serialization(self):
# Construct a json representation of a Revisions model
revisions_model_json = {}
revisions_model_json['ids'] = ['testString']
revisions_model_json['start'] = 1
# Construct a model instance of Revisions by calling from_dict on the json representation
revisions_model = Revisions.from_dict(revisions_model_json)
assert revisions_model != False
# Construct a model instance of Revisions by calling from_dict on the json representation
revisions_model_dict = Revisions.from_dict(revisions_model_json).__dict__
revisions_model2 = Revisions(**revisions_model_dict)
# Verify the model instances are equivalent
assert revisions_model == revisions_model2
# Convert model instance back to dict and verify no loss of data
revisions_model_json2 = revisions_model.to_dict()
assert revisions_model_json2 == revisions_model_json
class TestModel_RevsDiff():
def test_revs_diff_serialization(self):
# Construct a json representation of a RevsDiff model
revs_diff_model_json = {}
revs_diff_model_json['missing'] = ['testString']
revs_diff_model_json['possible_ancestors'] = ['testString']
# Construct a model instance of RevsDiff by calling from_dict on the json representation
revs_diff_model = RevsDiff.from_dict(revs_diff_model_json)
assert revs_diff_model != False
# Construct a model instance of RevsDiff by calling from_dict on the json representation
revs_diff_model_dict = RevsDiff.from_dict(revs_diff_model_json).__dict__
revs_diff_model2 = RevsDiff(**revs_diff_model_dict)
# Verify the model instances are equivalent
assert revs_diff_model == revs_diff_model2
# Convert model instance back to dict and verify no loss of data
revs_diff_model_json2 = revs_diff_model.to_dict()
assert revs_diff_model_json2 == revs_diff_model_json
class TestModel_SchedulerDocsResult():
def test_scheduler_docs_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
scheduler_document_model = {} # SchedulerDocument
scheduler_document_model['database'] = 'testString'
scheduler_document_model['doc_id'] = 'testString'
scheduler_document_model['error_count'] = 0
scheduler_document_model['id'] = 'testString'
scheduler_document_model['info'] = scheduler_info_model
scheduler_document_model['last_updated'] = "2019-01-01T12:00:00Z"
scheduler_document_model['node'] = 'testString'
scheduler_document_model['source'] = 'testString'
scheduler_document_model['source_proxy'] = 'testString'
scheduler_document_model['start_time'] = "2019-01-01T12:00:00Z"
scheduler_document_model['state'] = 'initializing'
scheduler_document_model['target'] = 'testString'
scheduler_document_model['target_proxy'] = 'testString'
# Construct a json representation of a SchedulerDocsResult model
scheduler_docs_result_model_json = {}
scheduler_docs_result_model_json['total_rows'] = 0
scheduler_docs_result_model_json['docs'] = [scheduler_document_model]
# Construct a model instance of SchedulerDocsResult by calling from_dict on the json representation
scheduler_docs_result_model = SchedulerDocsResult.from_dict(scheduler_docs_result_model_json)
assert scheduler_docs_result_model != False
# Construct a model instance of SchedulerDocsResult by calling from_dict on the json representation
scheduler_docs_result_model_dict = SchedulerDocsResult.from_dict(scheduler_docs_result_model_json).__dict__
scheduler_docs_result_model2 = SchedulerDocsResult(**scheduler_docs_result_model_dict)
# Verify the model instances are equivalent
assert scheduler_docs_result_model == scheduler_docs_result_model2
# Convert model instance back to dict and verify no loss of data
scheduler_docs_result_model_json2 = scheduler_docs_result_model.to_dict()
assert scheduler_docs_result_model_json2 == scheduler_docs_result_model_json
class TestModel_SchedulerDocument():
def test_scheduler_document_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
# Construct a json representation of a SchedulerDocument model
scheduler_document_model_json = {}
scheduler_document_model_json['database'] = 'testString'
scheduler_document_model_json['doc_id'] = 'testString'
scheduler_document_model_json['error_count'] = 0
scheduler_document_model_json['id'] = 'testString'
scheduler_document_model_json['info'] = scheduler_info_model
scheduler_document_model_json['last_updated'] = "2019-01-01T12:00:00Z"
scheduler_document_model_json['node'] = 'testString'
scheduler_document_model_json['source'] = 'testString'
scheduler_document_model_json['source_proxy'] = 'testString'
scheduler_document_model_json['start_time'] = "2019-01-01T12:00:00Z"
scheduler_document_model_json['state'] = 'initializing'
scheduler_document_model_json['target'] = 'testString'
scheduler_document_model_json['target_proxy'] = 'testString'
# Construct a model instance of SchedulerDocument by calling from_dict on the json representation
scheduler_document_model = SchedulerDocument.from_dict(scheduler_document_model_json)
assert scheduler_document_model != False
# Construct a model instance of SchedulerDocument by calling from_dict on the json representation
scheduler_document_model_dict = SchedulerDocument.from_dict(scheduler_document_model_json).__dict__
scheduler_document_model2 = SchedulerDocument(**scheduler_document_model_dict)
# Verify the model instances are equivalent
assert scheduler_document_model == scheduler_document_model2
# Convert model instance back to dict and verify no loss of data
scheduler_document_model_json2 = scheduler_document_model.to_dict()
assert scheduler_document_model_json2 == scheduler_document_model_json
class TestModel_SchedulerInfo():
def test_scheduler_info_serialization(self):
# Construct a json representation of a SchedulerInfo model
scheduler_info_model_json = {}
scheduler_info_model_json['changes_pending'] = 0
scheduler_info_model_json['checkpointed_source_seq'] = 'testString'
scheduler_info_model_json['doc_write_failures'] = 0
scheduler_info_model_json['docs_read'] = 0
scheduler_info_model_json['docs_written'] = 0
scheduler_info_model_json['error'] = 'testString'
scheduler_info_model_json['missing_revisions_found'] = 0
scheduler_info_model_json['revisions_checked'] = 0
scheduler_info_model_json['source_seq'] = 'testString'
scheduler_info_model_json['through_seq'] = 'testString'
# Construct a model instance of SchedulerInfo by calling from_dict on the json representation
scheduler_info_model = SchedulerInfo.from_dict(scheduler_info_model_json)
assert scheduler_info_model != False
# Construct a model instance of SchedulerInfo by calling from_dict on the json representation
scheduler_info_model_dict = SchedulerInfo.from_dict(scheduler_info_model_json).__dict__
scheduler_info_model2 = SchedulerInfo(**scheduler_info_model_dict)
# Verify the model instances are equivalent
assert scheduler_info_model == scheduler_info_model2
# Convert model instance back to dict and verify no loss of data
scheduler_info_model_json2 = scheduler_info_model.to_dict()
assert scheduler_info_model_json2 == scheduler_info_model_json
class TestModel_SchedulerJob():
def test_scheduler_job_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
scheduler_job_event_model = {} # SchedulerJobEvent
scheduler_job_event_model['reason'] = 'testString'
scheduler_job_event_model['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model['type'] = 'testString'
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
# Construct a json representation of a SchedulerJob model
scheduler_job_model_json = {}
scheduler_job_model_json['database'] = 'testString'
scheduler_job_model_json['doc_id'] = 'testString'
scheduler_job_model_json['history'] = [scheduler_job_event_model]
scheduler_job_model_json['id'] = 'testString'
scheduler_job_model_json['info'] = scheduler_info_model
scheduler_job_model_json['node'] = 'testString'
scheduler_job_model_json['pid'] = 'testString'
scheduler_job_model_json['source'] = 'testString'
scheduler_job_model_json['start_time'] = "2019-01-01T12:00:00Z"
scheduler_job_model_json['target'] = 'testString'
scheduler_job_model_json['user'] = 'testString'
# Construct a model instance of SchedulerJob by calling from_dict on the json representation
scheduler_job_model = SchedulerJob.from_dict(scheduler_job_model_json)
assert scheduler_job_model != False
# Construct a model instance of SchedulerJob by calling from_dict on the json representation
scheduler_job_model_dict = SchedulerJob.from_dict(scheduler_job_model_json).__dict__
scheduler_job_model2 = SchedulerJob(**scheduler_job_model_dict)
# Verify the model instances are equivalent
assert scheduler_job_model == scheduler_job_model2
# Convert model instance back to dict and verify no loss of data
scheduler_job_model_json2 = scheduler_job_model.to_dict()
assert scheduler_job_model_json2 == scheduler_job_model_json
class TestModel_SchedulerJobEvent():
def test_scheduler_job_event_serialization(self):
# Construct a json representation of a SchedulerJobEvent model
scheduler_job_event_model_json = {}
scheduler_job_event_model_json['reason'] = 'testString'
scheduler_job_event_model_json['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model_json['type'] = 'testString'
# Construct a model instance of SchedulerJobEvent by calling from_dict on the json representation
scheduler_job_event_model = SchedulerJobEvent.from_dict(scheduler_job_event_model_json)
assert scheduler_job_event_model != False
# Construct a model instance of SchedulerJobEvent by calling from_dict on the json representation
scheduler_job_event_model_dict = SchedulerJobEvent.from_dict(scheduler_job_event_model_json).__dict__
scheduler_job_event_model2 = SchedulerJobEvent(**scheduler_job_event_model_dict)
# Verify the model instances are equivalent
assert scheduler_job_event_model == scheduler_job_event_model2
# Convert model instance back to dict and verify no loss of data
scheduler_job_event_model_json2 = scheduler_job_event_model.to_dict()
assert scheduler_job_event_model_json2 == scheduler_job_event_model_json
class TestModel_SchedulerJobsResult():
def test_scheduler_jobs_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
scheduler_job_event_model = {} # SchedulerJobEvent
scheduler_job_event_model['reason'] = 'testString'
scheduler_job_event_model['timestamp'] = "2019-01-01T12:00:00Z"
scheduler_job_event_model['type'] = 'testString'
scheduler_info_model = {} # SchedulerInfo
scheduler_info_model['changes_pending'] = 0
scheduler_info_model['checkpointed_source_seq'] = 'testString'
scheduler_info_model['doc_write_failures'] = 0
scheduler_info_model['docs_read'] = 0
scheduler_info_model['docs_written'] = 0
scheduler_info_model['error'] = 'testString'
scheduler_info_model['missing_revisions_found'] = 0
scheduler_info_model['revisions_checked'] = 0
scheduler_info_model['source_seq'] = 'testString'
scheduler_info_model['through_seq'] = 'testString'
scheduler_job_model = {} # SchedulerJob
scheduler_job_model['database'] = 'testString'
scheduler_job_model['doc_id'] = 'testString'
scheduler_job_model['history'] = [scheduler_job_event_model]
scheduler_job_model['id'] = 'testString'
scheduler_job_model['info'] = scheduler_info_model
scheduler_job_model['node'] = 'testString'
scheduler_job_model['pid'] = 'testString'
scheduler_job_model['source'] = 'testString'
scheduler_job_model['start_time'] = "2019-01-01T12:00:00Z"
scheduler_job_model['target'] = 'testString'
scheduler_job_model['user'] = 'testString'
# Construct a json representation of a SchedulerJobsResult model
scheduler_jobs_result_model_json = {}
scheduler_jobs_result_model_json['total_rows'] = 0
scheduler_jobs_result_model_json['jobs'] = [scheduler_job_model]
# Construct a model instance of SchedulerJobsResult by calling from_dict on the json representation
scheduler_jobs_result_model = SchedulerJobsResult.from_dict(scheduler_jobs_result_model_json)
assert scheduler_jobs_result_model != False
# Construct a model instance of SchedulerJobsResult by calling from_dict on the json representation
scheduler_jobs_result_model_dict = SchedulerJobsResult.from_dict(scheduler_jobs_result_model_json).__dict__
scheduler_jobs_result_model2 = SchedulerJobsResult(**scheduler_jobs_result_model_dict)
# Verify the model instances are equivalent
assert scheduler_jobs_result_model == scheduler_jobs_result_model2
# Convert model instance back to dict and verify no loss of data
scheduler_jobs_result_model_json2 = scheduler_jobs_result_model.to_dict()
assert scheduler_jobs_result_model_json2 == scheduler_jobs_result_model_json
class TestModel_SearchAnalyzeResult():
def test_search_analyze_result_serialization(self):
# Construct a json representation of a SearchAnalyzeResult model
search_analyze_result_model_json = {}
search_analyze_result_model_json['tokens'] = ['testString']
# Construct a model instance of SearchAnalyzeResult by calling from_dict on the json representation
search_analyze_result_model = SearchAnalyzeResult.from_dict(search_analyze_result_model_json)
assert search_analyze_result_model != False
# Construct a model instance of SearchAnalyzeResult by calling from_dict on the json representation
search_analyze_result_model_dict = SearchAnalyzeResult.from_dict(search_analyze_result_model_json).__dict__
search_analyze_result_model2 = SearchAnalyzeResult(**search_analyze_result_model_dict)
# Verify the model instances are equivalent
assert search_analyze_result_model == search_analyze_result_model2
# Convert model instance back to dict and verify no loss of data
search_analyze_result_model_json2 = search_analyze_result_model.to_dict()
assert search_analyze_result_model_json2 == search_analyze_result_model_json
class TestModel_SearchIndexDefinition():
def test_search_index_definition_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
analyzer_model = {} # Analyzer
analyzer_model['name'] = 'classic'
analyzer_model['stopwords'] = ['testString']
analyzer_configuration_model = {} # AnalyzerConfiguration
analyzer_configuration_model['name'] = 'classic'
analyzer_configuration_model['stopwords'] = ['testString']
analyzer_configuration_model['fields'] = {}
# Construct a json representation of a SearchIndexDefinition model
search_index_definition_model_json = {}
search_index_definition_model_json['analyzer'] = analyzer_configuration_model
search_index_definition_model_json['index'] = 'testString'
# Construct a model instance of SearchIndexDefinition by calling from_dict on the json representation
search_index_definition_model = SearchIndexDefinition.from_dict(search_index_definition_model_json)
assert search_index_definition_model != False
# Construct a model instance of SearchIndexDefinition by calling from_dict on the json representation
search_index_definition_model_dict = SearchIndexDefinition.from_dict(search_index_definition_model_json).__dict__
search_index_definition_model2 = SearchIndexDefinition(**search_index_definition_model_dict)
# Verify the model instances are equivalent
assert search_index_definition_model == search_index_definition_model2
# Convert model instance back to dict and verify no loss of data
search_index_definition_model_json2 = search_index_definition_model.to_dict()
assert search_index_definition_model_json2 == search_index_definition_model_json
class TestModel_SearchIndexInfo():
def test_search_index_info_serialization(self):
# Construct a json representation of a SearchIndexInfo model
search_index_info_model_json = {}
search_index_info_model_json['committed_seq'] = 26
search_index_info_model_json['disk_size'] = 0
search_index_info_model_json['doc_count'] = 0
search_index_info_model_json['doc_del_count'] = 0
search_index_info_model_json['pending_seq'] = 26
# Construct a model instance of SearchIndexInfo by calling from_dict on the json representation
search_index_info_model = SearchIndexInfo.from_dict(search_index_info_model_json)
assert search_index_info_model != False
# Construct a model instance of SearchIndexInfo by calling from_dict on the json representation
search_index_info_model_dict = SearchIndexInfo.from_dict(search_index_info_model_json).__dict__
search_index_info_model2 = SearchIndexInfo(**search_index_info_model_dict)
# Verify the model instances are equivalent
assert search_index_info_model == search_index_info_model2
# Convert model instance back to dict and verify no loss of data
search_index_info_model_json2 = search_index_info_model.to_dict()
assert search_index_info_model_json2 == search_index_info_model_json
class TestModel_SearchInfoResult():
def test_search_info_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
search_index_info_model = {} # SearchIndexInfo
search_index_info_model['committed_seq'] = 26
search_index_info_model['disk_size'] = 0
search_index_info_model['doc_count'] = 0
search_index_info_model['doc_del_count'] = 0
search_index_info_model['pending_seq'] = 26
# Construct a json representation of a SearchInfoResult model
search_info_result_model_json = {}
search_info_result_model_json['name'] = 'testString'
search_info_result_model_json['search_index'] = search_index_info_model
# Construct a model instance of SearchInfoResult by calling from_dict on the json representation
search_info_result_model = SearchInfoResult.from_dict(search_info_result_model_json)
assert search_info_result_model != False
# Construct a model instance of SearchInfoResult by calling from_dict on the json representation
search_info_result_model_dict = SearchInfoResult.from_dict(search_info_result_model_json).__dict__
search_info_result_model2 = SearchInfoResult(**search_info_result_model_dict)
# Verify the model instances are equivalent
assert search_info_result_model == search_info_result_model2
# Convert model instance back to dict and verify no loss of data
search_info_result_model_json2 = search_info_result_model.to_dict()
assert search_info_result_model_json2 == search_info_result_model_json
class TestModel_SearchResult():
def test_search_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
search_result_row_model = {} # SearchResultRow
search_result_row_model['doc'] = document_model
search_result_row_model['fields'] = {}
search_result_row_model['highlights'] = {}
search_result_row_model['id'] = 'testString'
search_result_properties_model = {} # SearchResultProperties
search_result_properties_model['total_rows'] = 0
search_result_properties_model['bookmark'] = 'testString'
search_result_properties_model['by'] = 'testString'
search_result_properties_model['counts'] = {}
search_result_properties_model['ranges'] = {}
search_result_properties_model['rows'] = [search_result_row_model]
# Construct a json representation of a SearchResult model
search_result_model_json = {}
search_result_model_json['total_rows'] = 0
search_result_model_json['bookmark'] = 'testString'
search_result_model_json['by'] = 'testString'
search_result_model_json['counts'] = {}
search_result_model_json['ranges'] = {}
search_result_model_json['rows'] = [search_result_row_model]
search_result_model_json['groups'] = [search_result_properties_model]
# Construct a model instance of SearchResult by calling from_dict on the json representation
search_result_model = SearchResult.from_dict(search_result_model_json)
assert search_result_model != False
# Construct a model instance of SearchResult by calling from_dict on the json representation
search_result_model_dict = SearchResult.from_dict(search_result_model_json).__dict__
search_result_model2 = SearchResult(**search_result_model_dict)
# Verify the model instances are equivalent
assert search_result_model == search_result_model2
# Convert model instance back to dict and verify no loss of data
search_result_model_json2 = search_result_model.to_dict()
assert search_result_model_json2 == search_result_model_json
class TestModel_SearchResultProperties():
def test_search_result_properties_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
search_result_row_model = {} # SearchResultRow
search_result_row_model['doc'] = document_model
search_result_row_model['fields'] = {}
search_result_row_model['highlights'] = {}
search_result_row_model['id'] = 'testString'
# Construct a json representation of a SearchResultProperties model
search_result_properties_model_json = {}
search_result_properties_model_json['total_rows'] = 0
search_result_properties_model_json['bookmark'] = 'testString'
search_result_properties_model_json['by'] = 'testString'
search_result_properties_model_json['counts'] = {}
search_result_properties_model_json['ranges'] = {}
search_result_properties_model_json['rows'] = [search_result_row_model]
# Construct a model instance of SearchResultProperties by calling from_dict on the json representation
search_result_properties_model = SearchResultProperties.from_dict(search_result_properties_model_json)
assert search_result_properties_model != False
# Construct a model instance of SearchResultProperties by calling from_dict on the json representation
search_result_properties_model_dict = SearchResultProperties.from_dict(search_result_properties_model_json).__dict__
search_result_properties_model2 = SearchResultProperties(**search_result_properties_model_dict)
# Verify the model instances are equivalent
assert search_result_properties_model == search_result_properties_model2
# Convert model instance back to dict and verify no loss of data
search_result_properties_model_json2 = search_result_properties_model.to_dict()
assert search_result_properties_model_json2 == search_result_properties_model_json
class TestModel_SearchResultRow():
def test_search_result_row_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a SearchResultRow model
search_result_row_model_json = {}
search_result_row_model_json['doc'] = document_model
search_result_row_model_json['fields'] = {}
search_result_row_model_json['highlights'] = {}
search_result_row_model_json['id'] = 'testString'
# Construct a model instance of SearchResultRow by calling from_dict on the json representation
search_result_row_model = SearchResultRow.from_dict(search_result_row_model_json)
assert search_result_row_model != False
# Construct a model instance of SearchResultRow by calling from_dict on the json representation
search_result_row_model_dict = SearchResultRow.from_dict(search_result_row_model_json).__dict__
search_result_row_model2 = SearchResultRow(**search_result_row_model_dict)
# Verify the model instances are equivalent
assert search_result_row_model == search_result_row_model2
# Convert model instance back to dict and verify no loss of data
search_result_row_model_json2 = search_result_row_model.to_dict()
assert search_result_row_model_json2 == search_result_row_model_json
class TestModel_Security():
def test_security_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
security_object_model = {} # SecurityObject
security_object_model['names'] = ['testString']
security_object_model['roles'] = ['testString']
# Construct a json representation of a Security model
security_model_json = {}
security_model_json['admins'] = security_object_model
security_model_json['members'] = security_object_model
security_model_json['cloudant'] = {}
security_model_json['couchdb_auth_only'] = True
# Construct a model instance of Security by calling from_dict on the json representation
security_model = Security.from_dict(security_model_json)
assert security_model != False
# Construct a model instance of Security by calling from_dict on the json representation
security_model_dict = Security.from_dict(security_model_json).__dict__
security_model2 = Security(**security_model_dict)
# Verify the model instances are equivalent
assert security_model == security_model2
# Convert model instance back to dict and verify no loss of data
security_model_json2 = security_model.to_dict()
assert security_model_json2 == security_model_json
class TestModel_SecurityObject():
def test_security_object_serialization(self):
# Construct a json representation of a SecurityObject model
security_object_model_json = {}
security_object_model_json['names'] = ['testString']
security_object_model_json['roles'] = ['testString']
# Construct a model instance of SecurityObject by calling from_dict on the json representation
security_object_model = SecurityObject.from_dict(security_object_model_json)
assert security_object_model != False
# Construct a model instance of SecurityObject by calling from_dict on the json representation
security_object_model_dict = SecurityObject.from_dict(security_object_model_json).__dict__
security_object_model2 = SecurityObject(**security_object_model_dict)
# Verify the model instances are equivalent
assert security_object_model == security_object_model2
# Convert model instance back to dict and verify no loss of data
security_object_model_json2 = security_object_model.to_dict()
assert security_object_model_json2 == security_object_model_json
class TestModel_ServerInformation():
def test_server_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
server_vendor_model = {} # ServerVendor
server_vendor_model['name'] = 'testString'
server_vendor_model['variant'] = 'testString'
server_vendor_model['version'] = 'testString'
# Construct a json representation of a ServerInformation model
server_information_model_json = {}
server_information_model_json['couchdb'] = 'testString'
server_information_model_json['features'] = ['testString']
server_information_model_json['vendor'] = server_vendor_model
server_information_model_json['version'] = 'testString'
server_information_model_json['features_flags'] = ['testString']
# Construct a model instance of ServerInformation by calling from_dict on the json representation
server_information_model = ServerInformation.from_dict(server_information_model_json)
assert server_information_model != False
# Construct a model instance of ServerInformation by calling from_dict on the json representation
server_information_model_dict = ServerInformation.from_dict(server_information_model_json).__dict__
server_information_model2 = ServerInformation(**server_information_model_dict)
# Verify the model instances are equivalent
assert server_information_model == server_information_model2
# Convert model instance back to dict and verify no loss of data
server_information_model_json2 = server_information_model.to_dict()
assert server_information_model_json2 == server_information_model_json
class TestModel_ServerVendor():
def test_server_vendor_serialization(self):
# Construct a json representation of a ServerVendor model
server_vendor_model_json = {}
server_vendor_model_json['name'] = 'testString'
server_vendor_model_json['variant'] = 'testString'
server_vendor_model_json['version'] = 'testString'
# Construct a model instance of ServerVendor by calling from_dict on the json representation
server_vendor_model = ServerVendor.from_dict(server_vendor_model_json)
assert server_vendor_model != False
# Construct a model instance of ServerVendor by calling from_dict on the json representation
server_vendor_model_dict = ServerVendor.from_dict(server_vendor_model_json).__dict__
server_vendor_model2 = ServerVendor(**server_vendor_model_dict)
# Verify the model instances are equivalent
assert server_vendor_model == server_vendor_model2
# Convert model instance back to dict and verify no loss of data
server_vendor_model_json2 = server_vendor_model.to_dict()
assert server_vendor_model_json2 == server_vendor_model_json
class TestModel_SessionAuthentication():
def test_session_authentication_serialization(self):
# Construct a json representation of a SessionAuthentication model
session_authentication_model_json = {}
session_authentication_model_json['authenticated'] = 'testString'
session_authentication_model_json['authentication_db'] = 'testString'
session_authentication_model_json['authentication_handlers'] = ['testString']
# Construct a model instance of SessionAuthentication by calling from_dict on the json representation
session_authentication_model = SessionAuthentication.from_dict(session_authentication_model_json)
assert session_authentication_model != False
# Construct a model instance of SessionAuthentication by calling from_dict on the json representation
session_authentication_model_dict = SessionAuthentication.from_dict(session_authentication_model_json).__dict__
session_authentication_model2 = SessionAuthentication(**session_authentication_model_dict)
# Verify the model instances are equivalent
assert session_authentication_model == session_authentication_model2
# Convert model instance back to dict and verify no loss of data
session_authentication_model_json2 = session_authentication_model.to_dict()
assert session_authentication_model_json2 == session_authentication_model_json
class TestModel_SessionInformation():
def test_session_information_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
session_authentication_model = {} # SessionAuthentication
session_authentication_model['authenticated'] = 'testString'
session_authentication_model['authentication_db'] = 'testString'
session_authentication_model['authentication_handlers'] = ['testString']
user_context_model = {} # UserContext
user_context_model['db'] = 'testString'
user_context_model['name'] = 'testString'
user_context_model['roles'] = ['_reader']
# Construct a json representation of a SessionInformation model
session_information_model_json = {}
session_information_model_json['ok'] = True
session_information_model_json['info'] = session_authentication_model
session_information_model_json['userCtx'] = user_context_model
# Construct a model instance of SessionInformation by calling from_dict on the json representation
session_information_model = SessionInformation.from_dict(session_information_model_json)
assert session_information_model != False
# Construct a model instance of SessionInformation by calling from_dict on the json representation
session_information_model_dict = SessionInformation.from_dict(session_information_model_json).__dict__
session_information_model2 = SessionInformation(**session_information_model_dict)
# Verify the model instances are equivalent
assert session_information_model == session_information_model2
# Convert model instance back to dict and verify no loss of data
session_information_model_json2 = session_information_model.to_dict()
assert session_information_model_json2 == session_information_model_json
class TestModel_ShardsInformation():
def test_shards_information_serialization(self):
# Construct a json representation of a ShardsInformation model
shards_information_model_json = {}
shards_information_model_json['shards'] = {}
# Construct a model instance of ShardsInformation by calling from_dict on the json representation
shards_information_model = ShardsInformation.from_dict(shards_information_model_json)
assert shards_information_model != False
# Construct a model instance of ShardsInformation by calling from_dict on the json representation
shards_information_model_dict = ShardsInformation.from_dict(shards_information_model_json).__dict__
shards_information_model2 = ShardsInformation(**shards_information_model_dict)
# Verify the model instances are equivalent
assert shards_information_model == shards_information_model2
# Convert model instance back to dict and verify no loss of data
shards_information_model_json2 = shards_information_model.to_dict()
assert shards_information_model_json2 == shards_information_model_json
class TestModel_ThroughputInformation():
def test_throughput_information_serialization(self):
# Construct a json representation of a ThroughputInformation model
throughput_information_model_json = {}
throughput_information_model_json['blocks'] = 0
throughput_information_model_json['query'] = 0
throughput_information_model_json['read'] = 0
throughput_information_model_json['write'] = 0
# Construct a model instance of ThroughputInformation by calling from_dict on the json representation
throughput_information_model = ThroughputInformation.from_dict(throughput_information_model_json)
assert throughput_information_model != False
# Construct a model instance of ThroughputInformation by calling from_dict on the json representation
throughput_information_model_dict = ThroughputInformation.from_dict(throughput_information_model_json).__dict__
throughput_information_model2 = ThroughputInformation(**throughput_information_model_dict)
# Verify the model instances are equivalent
assert throughput_information_model == throughput_information_model2
# Convert model instance back to dict and verify no loss of data
throughput_information_model_json2 = throughput_information_model.to_dict()
assert throughput_information_model_json2 == throughput_information_model_json
class TestModel_UpInformation():
def test_up_information_serialization(self):
# Construct a json representation of a UpInformation model
up_information_model_json = {}
up_information_model_json['seeds'] = { 'foo': 'bar' }
up_information_model_json['status'] = 'maintenance_mode'
# Construct a model instance of UpInformation by calling from_dict on the json representation
up_information_model = UpInformation.from_dict(up_information_model_json)
assert up_information_model != False
# Construct a model instance of UpInformation by calling from_dict on the json representation
up_information_model_dict = UpInformation.from_dict(up_information_model_json).__dict__
up_information_model2 = UpInformation(**up_information_model_dict)
# Verify the model instances are equivalent
assert up_information_model == up_information_model2
# Convert model instance back to dict and verify no loss of data
up_information_model_json2 = up_information_model.to_dict()
assert up_information_model_json2 == up_information_model_json
class TestModel_UserContext():
def test_user_context_serialization(self):
# Construct a json representation of a UserContext model
user_context_model_json = {}
user_context_model_json['db'] = 'testString'
user_context_model_json['name'] = 'testString'
user_context_model_json['roles'] = ['_reader']
# Construct a model instance of UserContext by calling from_dict on the json representation
user_context_model = UserContext.from_dict(user_context_model_json)
assert user_context_model != False
# Construct a model instance of UserContext by calling from_dict on the json representation
user_context_model_dict = UserContext.from_dict(user_context_model_json).__dict__
user_context_model2 = UserContext(**user_context_model_dict)
# Verify the model instances are equivalent
assert user_context_model == user_context_model2
# Convert model instance back to dict and verify no loss of data
user_context_model_json2 = user_context_model.to_dict()
assert user_context_model_json2 == user_context_model_json
class TestModel_UuidsResult():
def test_uuids_result_serialization(self):
# Construct a json representation of a UuidsResult model
uuids_result_model_json = {}
uuids_result_model_json['uuids'] = ['testString']
# Construct a model instance of UuidsResult by calling from_dict on the json representation
uuids_result_model = UuidsResult.from_dict(uuids_result_model_json)
assert uuids_result_model != False
# Construct a model instance of UuidsResult by calling from_dict on the json representation
uuids_result_model_dict = UuidsResult.from_dict(uuids_result_model_json).__dict__
uuids_result_model2 = UuidsResult(**uuids_result_model_dict)
# Verify the model instances are equivalent
assert uuids_result_model == uuids_result_model2
# Convert model instance back to dict and verify no loss of data
uuids_result_model_json2 = uuids_result_model.to_dict()
assert uuids_result_model_json2 == uuids_result_model_json
class TestModel_ViewQueriesResult():
def test_view_queries_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
view_result_row_model = {} # ViewResultRow
view_result_row_model['caused_by'] = 'testString'
view_result_row_model['error'] = 'testString'
view_result_row_model['reason'] = 'testString'
view_result_row_model['doc'] = document_model
view_result_row_model['id'] = 'testString'
view_result_row_model['key'] = 'testString'
view_result_row_model['value'] = 'testString'
view_result_model = {} # ViewResult
view_result_model['total_rows'] = 0
view_result_model['update_seq'] = 'testString'
view_result_model['rows'] = [view_result_row_model]
# Construct a json representation of a ViewQueriesResult model
view_queries_result_model_json = {}
view_queries_result_model_json['results'] = [view_result_model]
# Construct a model instance of ViewQueriesResult by calling from_dict on the json representation
view_queries_result_model = ViewQueriesResult.from_dict(view_queries_result_model_json)
assert view_queries_result_model != False
# Construct a model instance of ViewQueriesResult by calling from_dict on the json representation
view_queries_result_model_dict = ViewQueriesResult.from_dict(view_queries_result_model_json).__dict__
view_queries_result_model2 = ViewQueriesResult(**view_queries_result_model_dict)
# Verify the model instances are equivalent
assert view_queries_result_model == view_queries_result_model2
# Convert model instance back to dict and verify no loss of data
view_queries_result_model_json2 = view_queries_result_model.to_dict()
assert view_queries_result_model_json2 == view_queries_result_model_json
class TestModel_ViewQuery():
def test_view_query_serialization(self):
# Construct a json representation of a ViewQuery model
view_query_model_json = {}
view_query_model_json['att_encoding_info'] = False
view_query_model_json['attachments'] = False
view_query_model_json['conflicts'] = False
view_query_model_json['descending'] = False
view_query_model_json['include_docs'] = False
view_query_model_json['inclusive_end'] = True
view_query_model_json['limit'] = 0
view_query_model_json['skip'] = 0
view_query_model_json['update_seq'] = False
view_query_model_json['endkey'] = 'testString'
view_query_model_json['endkey_docid'] = 'testString'
view_query_model_json['group'] = False
view_query_model_json['group_level'] = 1
view_query_model_json['key'] = 'testString'
view_query_model_json['keys'] = ['testString']
view_query_model_json['reduce'] = True
view_query_model_json['stable'] = False
view_query_model_json['startkey'] = 'testString'
view_query_model_json['startkey_docid'] = 'testString'
view_query_model_json['update'] = 'true'
# Construct a model instance of ViewQuery by calling from_dict on the json representation
view_query_model = ViewQuery.from_dict(view_query_model_json)
assert view_query_model != False
# Construct a model instance of ViewQuery by calling from_dict on the json representation
view_query_model_dict = ViewQuery.from_dict(view_query_model_json).__dict__
view_query_model2 = ViewQuery(**view_query_model_dict)
# Verify the model instances are equivalent
assert view_query_model == view_query_model2
# Convert model instance back to dict and verify no loss of data
view_query_model_json2 = view_query_model.to_dict()
assert view_query_model_json2 == view_query_model_json
class TestModel_ViewResult():
def test_view_result_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
view_result_row_model = {} # ViewResultRow
view_result_row_model['caused_by'] = 'testString'
view_result_row_model['error'] = 'testString'
view_result_row_model['reason'] = 'testString'
view_result_row_model['doc'] = document_model
view_result_row_model['id'] = 'testString'
view_result_row_model['key'] = 'testString'
view_result_row_model['value'] = 'testString'
# Construct a json representation of a ViewResult model
view_result_model_json = {}
view_result_model_json['total_rows'] = 0
view_result_model_json['update_seq'] = 'testString'
view_result_model_json['rows'] = [view_result_row_model]
# Construct a model instance of ViewResult by calling from_dict on the json representation
view_result_model = ViewResult.from_dict(view_result_model_json)
assert view_result_model != False
# Construct a model instance of ViewResult by calling from_dict on the json representation
view_result_model_dict = ViewResult.from_dict(view_result_model_json).__dict__
view_result_model2 = ViewResult(**view_result_model_dict)
# Verify the model instances are equivalent
assert view_result_model == view_result_model2
# Convert model instance back to dict and verify no loss of data
view_result_model_json2 = view_result_model.to_dict()
assert view_result_model_json2 == view_result_model_json
class TestModel_ViewResultRow():
def test_view_result_row_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
attachment_model = {} # Attachment
attachment_model['content_type'] = 'testString'
attachment_model['data'] = 'VGhpcyBpcyBhIG1vY2sgYnl0ZSBhcnJheSB2YWx1ZS4='
attachment_model['digest'] = 'testString'
attachment_model['encoded_length'] = 0
attachment_model['encoding'] = 'testString'
attachment_model['follows'] = True
attachment_model['length'] = 0
attachment_model['revpos'] = 1
attachment_model['stub'] = True
revisions_model = {} # Revisions
revisions_model['ids'] = ['testString']
revisions_model['start'] = 1
document_revision_status_model = {} # DocumentRevisionStatus
document_revision_status_model['rev'] = 'testString'
document_revision_status_model['status'] = 'available'
document_model = {} # Document
document_model['_attachments'] = {}
document_model['_conflicts'] = ['testString']
document_model['_deleted'] = True
document_model['_deleted_conflicts'] = ['testString']
document_model['_id'] = 'testString'
document_model['_local_seq'] = 'testString'
document_model['_rev'] = 'testString'
document_model['_revisions'] = revisions_model
document_model['_revs_info'] = [document_revision_status_model]
document_model['foo'] = 'testString'
# Construct a json representation of a ViewResultRow model
view_result_row_model_json = {}
view_result_row_model_json['caused_by'] = 'testString'
view_result_row_model_json['error'] = 'testString'
view_result_row_model_json['reason'] = 'testString'
view_result_row_model_json['doc'] = document_model
view_result_row_model_json['id'] = 'testString'
view_result_row_model_json['key'] = 'testString'
view_result_row_model_json['value'] = 'testString'
# Construct a model instance of ViewResultRow by calling from_dict on the json representation
view_result_row_model = ViewResultRow.from_dict(view_result_row_model_json)
assert view_result_row_model != False
# Construct a model instance of ViewResultRow by calling from_dict on the json representation
view_result_row_model_dict = ViewResultRow.from_dict(view_result_row_model_json).__dict__
view_result_row_model2 = ViewResultRow(**view_result_row_model_dict)
# Verify the model instances are equivalent
assert view_result_row_model == view_result_row_model2
# Convert model instance back to dict and verify no loss of data
view_result_row_model_json2 = view_result_row_model.to_dict()
assert view_result_row_model_json2 == view_result_row_model_json
class TestModel_GeoJsonGeometry():
def test_geo_json_geometry_serialization(self):
# Construct a json representation of a GeoJsonGeometry model
geo_json_geometry_model_json = {}
geo_json_geometry_model_json['type'] = 'Point'
geo_json_geometry_model_json['coordinates'] = ['testString']
# Construct a model instance of GeoJsonGeometry by calling from_dict on the json representation
geo_json_geometry_model = GeoJsonGeometry.from_dict(geo_json_geometry_model_json)
assert geo_json_geometry_model != False
# Construct a model instance of GeoJsonGeometry by calling from_dict on the json representation
geo_json_geometry_model_dict = GeoJsonGeometry.from_dict(geo_json_geometry_model_json).__dict__
geo_json_geometry_model2 = GeoJsonGeometry(**geo_json_geometry_model_dict)
# Verify the model instances are equivalent
assert geo_json_geometry_model == geo_json_geometry_model2
# Convert model instance back to dict and verify no loss of data
geo_json_geometry_model_json2 = geo_json_geometry_model.to_dict()
assert geo_json_geometry_model_json2 == geo_json_geometry_model_json
class TestModel_GeoJsonGeometryCollection():
def test_geo_json_geometry_collection_serialization(self):
# Construct dict forms of any model objects needed in order to build this model.
geo_json_geometry_model = {} # GeoJsonGeometry
geo_json_geometry_model['type'] = 'Point'
geo_json_geometry_model['coordinates'] = ['testString']
# Construct a json representation of a GeoJsonGeometryCollection model
geo_json_geometry_collection_model_json = {}
geo_json_geometry_collection_model_json['type'] = 'Point'
geo_json_geometry_collection_model_json['geometries'] = [geo_json_geometry_model]
# Construct a model instance of GeoJsonGeometryCollection by calling from_dict on the json representation
geo_json_geometry_collection_model = GeoJsonGeometryCollection.from_dict(geo_json_geometry_collection_model_json)
assert geo_json_geometry_collection_model != False
# Construct a model instance of GeoJsonGeometryCollection by calling from_dict on the json representation
geo_json_geometry_collection_model_dict = GeoJsonGeometryCollection.from_dict(geo_json_geometry_collection_model_json).__dict__
geo_json_geometry_collection_model2 = GeoJsonGeometryCollection(**geo_json_geometry_collection_model_dict)
# Verify the model instances are equivalent
assert geo_json_geometry_collection_model == geo_json_geometry_collection_model2
# Convert model instance back to dict and verify no loss of data
geo_json_geometry_collection_model_json2 = geo_json_geometry_collection_model.to_dict()
assert geo_json_geometry_collection_model_json2 == geo_json_geometry_collection_model_json
# endregion
##############################################################################
# End of Model Tests
##############################################################################
| true | true |
f7fe5ce54a5974d8e0a1765d3a0ffae24c2b3014 | 352 | py | Python | galaa/migrations/0002_rename_image_name_photos_name.py | lizgi/photo-gala | 67647314577afbf9174ab715be32ac86047f8fb0 | [
"MIT"
] | null | null | null | galaa/migrations/0002_rename_image_name_photos_name.py | lizgi/photo-gala | 67647314577afbf9174ab715be32ac86047f8fb0 | [
"MIT"
] | null | null | null | galaa/migrations/0002_rename_image_name_photos_name.py | lizgi/photo-gala | 67647314577afbf9174ab715be32ac86047f8fb0 | [
"MIT"
] | null | null | null | # Generated by Django 3.2.8 on 2021-11-26 22:19
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('galaa', '0001_initial'),
]
operations = [
migrations.RenameField(
model_name='photos',
old_name='image_name',
new_name='name',
),
]
| 18.526316 | 47 | 0.571023 |
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('galaa', '0001_initial'),
]
operations = [
migrations.RenameField(
model_name='photos',
old_name='image_name',
new_name='name',
),
]
| true | true |
f7fe5cfdd9ca84f74da4f55e7e6ee327870acbad | 3,091 | py | Python | airbyte-integrations/connectors/source-chargebee/source_chargebee/source.py | jinnig/airbyte | 1ccd21867b7908380b941ac4aa7737b59d18d4a9 | [
"MIT"
] | 2 | 2021-08-04T03:17:38.000Z | 2021-11-15T10:16:08.000Z | airbyte-integrations/connectors/source-chargebee/source_chargebee/source.py | jinnig/airbyte | 1ccd21867b7908380b941ac4aa7737b59d18d4a9 | [
"MIT"
] | null | null | null | airbyte-integrations/connectors/source-chargebee/source_chargebee/source.py | jinnig/airbyte | 1ccd21867b7908380b941ac4aa7737b59d18d4a9 | [
"MIT"
] | 1 | 2021-08-04T03:25:02.000Z | 2021-08-04T03:25:02.000Z | #
# MIT License
#
# Copyright (c) 2020 Airbyte
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
#
from typing import Any, List, Mapping, Tuple
import chargebee
from airbyte_cdk.models import SyncMode
from airbyte_cdk.sources import AbstractSource
from airbyte_cdk.sources.streams import Stream
from .streams import Addon, Customer, Invoice, Order, Plan, Subscription
class SourceChargebee(AbstractSource):
def check_connection(self, logger, config: Mapping[str, Any]) -> Tuple[bool, any]:
# Configure the Chargebee Python SDK
chargebee.configure(api_key=config["site_api_key"], site=config["site"])
try:
subscription_stream = Subscription(start_date=config["start_date"])
next(subscription_stream.read_records(sync_mode=SyncMode.full_refresh))
return True, None
except Exception as err:
# Should catch all exceptions which are already handled by Chargebee Python wrapper.
# https://github.com/chargebee/chargebee-python/blob/5346d833781de78a9eedbf9d12502f52c617c2d2/chargebee/http_request.py
return False, repr(err)
def streams(self, config) -> List[Stream]:
# Configure the Chargebee Python SDK
chargebee.configure(api_key=config["site_api_key"], site=config["site"])
kwargs = {"start_date": config["start_date"]}
product_catalog_version = config["product_catalog"]
# Below streams are suitable for both `Product Catalog 1.0` and `Product Catalog 2.0`.
common_streams = [
Customer(**kwargs),
Invoice(**kwargs),
Order(**kwargs),
Subscription(**kwargs),
]
if product_catalog_version == "1.0":
# Below streams are suitable only for `Product Catalog 1.0`.
product_catalog_v1_streams = [
Addon(**kwargs),
Plan(**kwargs),
]
return common_streams + product_catalog_v1_streams
# Below streams are suitable only for `Product Catalog 2.0`.
return common_streams
| 42.342466 | 131 | 0.703656 |
from typing import Any, List, Mapping, Tuple
import chargebee
from airbyte_cdk.models import SyncMode
from airbyte_cdk.sources import AbstractSource
from airbyte_cdk.sources.streams import Stream
from .streams import Addon, Customer, Invoice, Order, Plan, Subscription
class SourceChargebee(AbstractSource):
def check_connection(self, logger, config: Mapping[str, Any]) -> Tuple[bool, any]:
chargebee.configure(api_key=config["site_api_key"], site=config["site"])
try:
subscription_stream = Subscription(start_date=config["start_date"])
next(subscription_stream.read_records(sync_mode=SyncMode.full_refresh))
return True, None
except Exception as err:
return False, repr(err)
def streams(self, config) -> List[Stream]:
chargebee.configure(api_key=config["site_api_key"], site=config["site"])
kwargs = {"start_date": config["start_date"]}
product_catalog_version = config["product_catalog"]
common_streams = [
Customer(**kwargs),
Invoice(**kwargs),
Order(**kwargs),
Subscription(**kwargs),
]
if product_catalog_version == "1.0":
product_catalog_v1_streams = [
Addon(**kwargs),
Plan(**kwargs),
]
return common_streams + product_catalog_v1_streams
return common_streams
| true | true |
f7fe5d2291f6b08338083a0d398fa1269dbe65cf | 220 | py | Python | playground_env/.playground/connectors/passthrough/__init__.py | kandarpck/networksecurity2018 | dafe2ee8d39bd9596b1ce3fbc8b50ca645bcd626 | [
"MIT"
] | 3 | 2018-10-25T16:03:53.000Z | 2019-06-13T15:24:41.000Z | playground_env/.playground/connectors/passthrough/__init__.py | kandarpck/networksecurity2018 | dafe2ee8d39bd9596b1ce3fbc8b50ca645bcd626 | [
"MIT"
] | null | null | null | playground_env/.playground/connectors/passthrough/__init__.py | kandarpck/networksecurity2018 | dafe2ee8d39bd9596b1ce3fbc8b50ca645bcd626 | [
"MIT"
] | null | null | null | import playground
from .passthrough import pt_client, pt_server
passthrough_connector = playground.Connector(protocolStack=(
pt_client,
pt_server))
playground.setConnector('passthrough', passthrough_connector)
| 24.444444 | 61 | 0.818182 | import playground
from .passthrough import pt_client, pt_server
passthrough_connector = playground.Connector(protocolStack=(
pt_client,
pt_server))
playground.setConnector('passthrough', passthrough_connector)
| true | true |
f7fe5d3f1f2b914ef8863e51f4ff8041918b0ffa | 6,250 | py | Python | sunpy/map/sources/stereo.py | fluxtransport/sunpy | 351d3edca97e779179f367670292c95574c7a222 | [
"BSD-2-Clause"
] | null | null | null | sunpy/map/sources/stereo.py | fluxtransport/sunpy | 351d3edca97e779179f367670292c95574c7a222 | [
"BSD-2-Clause"
] | 1 | 2019-08-13T15:29:13.000Z | 2019-08-13T15:29:13.000Z | sunpy/map/sources/stereo.py | fluxtransport/sunpy | 351d3edca97e779179f367670292c95574c7a222 | [
"BSD-2-Clause"
] | 6 | 2017-03-15T07:17:05.000Z | 2020-09-30T18:36:49.000Z | """STEREO Map subclass definitions"""
__author__ = "Keith Hughitt"
__email__ = "keith.hughitt@nasa.gov"
import astropy.units as u
from astropy.visualization import PowerStretch
from astropy.visualization.mpl_normalize import ImageNormalize
from sunpy import log
from sunpy.map import GenericMap
from sunpy.map.sources.source_type import source_stretch
__all__ = ['EUVIMap', 'CORMap', 'HIMap']
class EUVIMap(GenericMap):
"""STEREO-SECCHI EUVI Image Map
EUVI is an extreme ultraviolet (EUV) imager. Part of the STEREO-SECCHI
suite it observes the Sun from 1 to 1.7 solar radii. It is capable of
observing at 304 (He II), 171 (Fe IX), 195 (Fe XII), and 284 (Fe XV)
Angstroms.
References
----------
* `STEREO Mission Page <https://stereo.gsfc.nasa.gov/>`_
* `STEREO SECCHI <http://secchi.nrl.navy.mil>`_
* `Instrument Page <http://secchi.lmsal.com/EUVI/>`_
"""
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'euvi{wl:d}'.format(wl=int(self.wavelength.value))
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.25)), clip=False)
self.meta['waveunit'] = self.meta.get('waveunit', 'Angstrom')
# Try to identify when the FITS meta data does not have the correct
# date FITS keyword
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
# fix CROTA to CROTAn
if "crota" in self.meta and "crota2" not in self.meta:
log.debug("EUVIMap: Changing the CROTA keyword to CROTA2")
self.meta["crota2"] = self.meta.pop("crota")
@property
def rsun_arcseconds(self):
"""
Radius of the sun in arcseconds.
References
----------
https://sohowww.nascom.nasa.gov/solarsoft/stereo/secchi/doc/FITS_keywords.pdf
"""
return self.meta.get('rsun', None)
@property
def rsun_obs(self):
"""
Radius of the sun in arcseconds as a quantity.
References
----------
https://sohowww.nascom.nasa.gov/solarsoft/stereo/secchi/doc/FITS_keywords.pdf
"""
rsun_arcseconds = self.meta.get('rsun', None)
if rsun_arcseconds is None:
rsun_arcseconds = super().rsun_obs
return u.Quantity(rsun_arcseconds, 'arcsec')
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
"""Determines if header corresponds to an EUVI image"""
return header.get('detector') == 'EUVI'
class CORMap(GenericMap):
"""STEREO-SECCHI CORonograph Image Map.
Part of the STEREO-SECCHI suite of remote sensing telescopes,
COR is a set of two coronographs (COR1, COR2) onboard STEREO.
They are both traditional Lyot coronagraphs.
The COR1 detectors observes from 1.3 to 4 solar radii while the
COR2 detectors observe a range from 2 to 15 solar radii.
References
----------
* `STEREO Mission Page <https://stereo.gsfc.nasa.gov/>`_
* `STEREO SECCHI <http://secchi.nrl.navy.mil>`_
* `COR1 Instrument Page <https://cor1.gsfc.nasa.gov>`_
* `COR2 Instrument Page <http://secchi.nrl.navy.mil/index.php?p=cor2>`_
* `COR1 User Guide <https://cor1.gsfc.nasa.gov/guide/>`_
"""
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'stereocor{det!s}'.format(det=self.detector[-1])
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.5)), clip=False)
# Try to identify when the FITS meta data does not have the correct
# date FITS keyword
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
@property
def measurement(self):
"""
Returns the type of data observed.
"""
# TODO: This needs to do more than white-light. Should give B, pB, etc.
return "white-light"
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
"""Determines if header corresponds to an COR image"""
return str(header.get('detector', '')).startswith('COR')
class HIMap(GenericMap):
"""STEREO-SECCHI Heliospheric Imager (HI) Map.
The HI is a wide-angle visible-light imaging system
for the detection of coronal mass ejection (CME) events
in interplanetary space and, in particular, of events
directed towards the Earth.
The Heliospheric imager consists of two instruments, the HI-1 and HI-2.
The HI1 observes from 15-80 solar radii while HI2 observes from 80-215
solar radii.
References
----------
* `STEREO Mission Page <https://stereo.gsfc.nasa.gov/>`_
* `STEREO SECCHI <https://secchi.nrl.navy.mil>`_
* `HI Instrument Page <http://www.stereo.rl.ac.uk>`_
"""
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'stereohi{det!s}'.format(det=self.detector[-1])
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.25)), clip=False)
# Try to identify when the FITS meta data does not have the correct
# date FITS keyword
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
@property
def measurement(self):
"""
Returns the type of data observed.
"""
# TODO: This needs to do more than white-light. Should give B, pB, etc.
return "white-light"
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
"""Determines if header corresponds to an COR image"""
return str(header.get('detector', '')).startswith('HI')
| 35.714286 | 87 | 0.64128 |
__author__ = "Keith Hughitt"
__email__ = "keith.hughitt@nasa.gov"
import astropy.units as u
from astropy.visualization import PowerStretch
from astropy.visualization.mpl_normalize import ImageNormalize
from sunpy import log
from sunpy.map import GenericMap
from sunpy.map.sources.source_type import source_stretch
__all__ = ['EUVIMap', 'CORMap', 'HIMap']
class EUVIMap(GenericMap):
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'euvi{wl:d}'.format(wl=int(self.wavelength.value))
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.25)), clip=False)
self.meta['waveunit'] = self.meta.get('waveunit', 'Angstrom')
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
if "crota" in self.meta and "crota2" not in self.meta:
log.debug("EUVIMap: Changing the CROTA keyword to CROTA2")
self.meta["crota2"] = self.meta.pop("crota")
@property
def rsun_arcseconds(self):
return self.meta.get('rsun', None)
@property
def rsun_obs(self):
rsun_arcseconds = self.meta.get('rsun', None)
if rsun_arcseconds is None:
rsun_arcseconds = super().rsun_obs
return u.Quantity(rsun_arcseconds, 'arcsec')
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
return header.get('detector') == 'EUVI'
class CORMap(GenericMap):
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'stereocor{det!s}'.format(det=self.detector[-1])
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.5)), clip=False)
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
@property
def measurement(self):
return "white-light"
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
return str(header.get('detector', '')).startswith('COR')
class HIMap(GenericMap):
def __init__(self, data, header, **kwargs):
GenericMap.__init__(self, data, header, **kwargs)
self._nickname = "{}-{}".format(self.detector, self.observatory[-1])
self.plot_settings['cmap'] = 'stereohi{det!s}'.format(det=self.detector[-1])
self.plot_settings['norm'] = ImageNormalize(
stretch=source_stretch(self.meta, PowerStretch(0.25)), clip=False)
if ('date_obs' in self.meta) and not('date-obs' in self.meta):
self.meta['date-obs'] = self.meta['date_obs']
@property
def measurement(self):
return "white-light"
@classmethod
def is_datasource_for(cls, data, header, **kwargs):
return str(header.get('detector', '')).startswith('HI')
| true | true |
f7fe5e550e01e609505d8cf74bc3c4e468c94e54 | 367 | py | Python | demo/app/controller/main.py | shiroyuki/Tori | 143b99075bf9e8d469d117f056516ab847234c8c | [
"MIT"
] | null | null | null | demo/app/controller/main.py | shiroyuki/Tori | 143b99075bf9e8d469d117f056516ab847234c8c | [
"MIT"
] | 6 | 2015-01-19T20:21:40.000Z | 2015-01-19T20:28:42.000Z | demo/app/controller/main.py | shiroyuki/Tori | 143b99075bf9e8d469d117f056516ab847234c8c | [
"MIT"
] | null | null | null | from tori import Controller
from tori.decorator.controller import renderer
from tori.exception import *
@renderer('demo.app.views')
class MainController(Controller):
def get(self):
try:
self.render('index.html', title="Testing Ground", uri=self.request.uri)
except Exception as e:
print(e)
| 30.583333 | 83 | 0.621253 | from tori import Controller
from tori.decorator.controller import renderer
from tori.exception import *
@renderer('demo.app.views')
class MainController(Controller):
def get(self):
try:
self.render('index.html', title="Testing Ground", uri=self.request.uri)
except Exception as e:
print(e)
| true | true |
f7fe5effe3c45f615f137cee01e9cd7dced4fd2b | 29,587 | py | Python | sqlparse/keywords.py | testtctc/sqlparse | d30bb97efee15e3c84cd436ad10991183fc4ffe7 | [
"BSD-3-Clause"
] | null | null | null | sqlparse/keywords.py | testtctc/sqlparse | d30bb97efee15e3c84cd436ad10991183fc4ffe7 | [
"BSD-3-Clause"
] | null | null | null | sqlparse/keywords.py | testtctc/sqlparse | d30bb97efee15e3c84cd436ad10991183fc4ffe7 | [
"BSD-3-Clause"
] | null | null | null | #
# Copyright (C) 2009-2020 the sqlparse authors and contributors
# <see AUTHORS file>
#
# This module is part of python-sqlparse and is released under
# the BSD License: https://opensource.org/licenses/BSD-3-Clause
import re
from sqlparse import tokens
def is_keyword(value):
#是否是关键字
val = value.upper()
return (KEYWORDS_COMMON.get(val)
or KEYWORDS_ORACLE.get(val)
or KEYWORDS_PLPGSQL.get(val)
or KEYWORDS_HQL.get(val)
or KEYWORDS.get(val, tokens.Name)), value
#sql语法
SQL_REGEX = {
'root': [
(r'(--|# )\+.*?(\r\n|\r|\n|$)', tokens.Comment.Single.Hint),
(r'/\*\+[\s\S]*?\*/', tokens.Comment.Multiline.Hint),
(r'(--|# ).*?(\r\n|\r|\n|$)', tokens.Comment.Single),
(r'/\*[\s\S]*?\*/', tokens.Comment.Multiline),
(r'(\r\n|\r|\n)', tokens.Newline),
(r'\s+?', tokens.Whitespace),
(r':=', tokens.Assignment),
(r'::', tokens.Punctuation),
(r'\*', tokens.Wildcard),
(r"`(``|[^`])*`", tokens.Name),
(r"´(´´|[^´])*´", tokens.Name),
(r'((?<!\S)\$(?:[_A-ZÀ-Ü]\w*)?\$)[\s\S]*?\1', tokens.Literal),
(r'\?', tokens.Name.Placeholder),
(r'%(\(\w+\))?s', tokens.Name.Placeholder),
(r'(?<!\w)[$:?]\w+', tokens.Name.Placeholder),
(r'\\\w+', tokens.Command),
(r'(NOT\s+)?(IN)\b', tokens.Operator.Comparison),
# FIXME(andi): VALUES shouldn't be listed here
# see https://github.com/andialbrecht/sqlparse/pull/64
# AS and IN are special, it may be followed by a parenthesis, but
# are never functions, see issue183 and issue507
(r'(CASE|IN|VALUES|USING|FROM|AS)\b', tokens.Keyword),
(r'(@|##|#)[A-ZÀ-Ü]\w+', tokens.Name),
# see issue #39
# Spaces around period `schema . name` are valid identifier
# TODO: Spaces before period not implemented
(r'[A-ZÀ-Ü]\w*(?=\s*\.)', tokens.Name), # 'Name' .
# FIXME(atronah): never match,
# because `re.match` doesn't work with look-behind regexp feature
(r'(?<=\.)[A-ZÀ-Ü]\w*', tokens.Name), # .'Name'
(r'[A-ZÀ-Ü]\w*(?=\()', tokens.Name), # side effect: change kw to func
(r'-?0x[\dA-F]+', tokens.Number.Hexadecimal),
(r'-?\d*(\.\d+)?E-?\d+', tokens.Number.Float),
(r'(?![_A-ZÀ-Ü])-?(\d+(\.\d*)|\.\d+)(?![_A-ZÀ-Ü])',
tokens.Number.Float),
(r'(?![_A-ZÀ-Ü])-?\d+(?![_A-ZÀ-Ü])', tokens.Number.Integer),
(r"'(''|\\\\|\\'|[^'])*'", tokens.String.Single),
# not a real string literal in ANSI SQL:
(r'"(""|\\\\|\\"|[^"])*"', tokens.String.Symbol),
(r'(""|".*?[^\\]")', tokens.String.Symbol),
# sqlite names can be escaped with [square brackets]. left bracket
# cannot be preceded by word character or a right bracket --
# otherwise it's probably an array index
(r'(?<![\w\])])(\[[^\]\[]+\])', tokens.Name),
(r'((LEFT\s+|RIGHT\s+|FULL\s+)?(INNER\s+|OUTER\s+|STRAIGHT\s+)?'
r'|(CROSS\s+|NATURAL\s+)?)?JOIN\b', tokens.Keyword),
(r'END(\s+IF|\s+LOOP|\s+WHILE)?\b', tokens.Keyword),
(r'NOT\s+NULL\b', tokens.Keyword),
(r'NULLS\s+(FIRST|LAST)\b', tokens.Keyword),
(r'UNION\s+ALL\b', tokens.Keyword),
(r'CREATE(\s+OR\s+REPLACE)?\b', tokens.Keyword.DDL),
(r'DOUBLE\s+PRECISION\b', tokens.Name.Builtin),
(r'GROUP\s+BY\b', tokens.Keyword),
(r'ORDER\s+BY\b', tokens.Keyword),
(r'HANDLER\s+FOR\b', tokens.Keyword),
(r'(LATERAL\s+VIEW\s+)'
r'(EXPLODE|INLINE|PARSE_URL_TUPLE|POSEXPLODE|STACK)\b',
tokens.Keyword),
(r"(AT|WITH')\s+TIME\s+ZONE\s+'[^']+'", tokens.Keyword.TZCast),
(r'(NOT\s+)?(LIKE|ILIKE|RLIKE)\b', tokens.Operator.Comparison),
(r'[0-9_A-ZÀ-Ü][_$#\w]*', is_keyword),
(r'[;:()\[\],\.]', tokens.Punctuation),
(r'[<>=~!]+', tokens.Operator.Comparison),
(r'[+/@#%^&|^-]+', tokens.Operator),
]}
#标签
FLAGS = re.IGNORECASE | re.UNICODE
SQL_REGEX = [(re.compile(rx, FLAGS).match, tt) for rx, tt in SQL_REGEX['root']]
# 通用关键字
KEYWORDS = {
'ABORT': tokens.Keyword,
'ABS': tokens.Keyword,
'ABSOLUTE': tokens.Keyword,
'ACCESS': tokens.Keyword,
'ADA': tokens.Keyword,
'ADD': tokens.Keyword,
'ADMIN': tokens.Keyword,
'AFTER': tokens.Keyword,
'AGGREGATE': tokens.Keyword,
'ALIAS': tokens.Keyword,
'ALL': tokens.Keyword,
'ALLOCATE': tokens.Keyword,
'ANALYSE': tokens.Keyword,
'ANALYZE': tokens.Keyword,
'ANY': tokens.Keyword,
'ARRAYLEN': tokens.Keyword,
'ARE': tokens.Keyword,
'ASC': tokens.Keyword.Order,
'ASENSITIVE': tokens.Keyword,
'ASSERTION': tokens.Keyword,
'ASSIGNMENT': tokens.Keyword,
'ASYMMETRIC': tokens.Keyword,
'AT': tokens.Keyword,
'ATOMIC': tokens.Keyword,
'AUDIT': tokens.Keyword,
'AUTHORIZATION': tokens.Keyword,
'AUTO_INCREMENT': tokens.Keyword,
'AVG': tokens.Keyword,
'BACKWARD': tokens.Keyword,
'BEFORE': tokens.Keyword,
'BEGIN': tokens.Keyword,
'BETWEEN': tokens.Keyword,
'BITVAR': tokens.Keyword,
'BIT_LENGTH': tokens.Keyword,
'BOTH': tokens.Keyword,
'BREADTH': tokens.Keyword,
# 'C': tokens.Keyword, # most likely this is an alias
'CACHE': tokens.Keyword,
'CALL': tokens.Keyword,
'CALLED': tokens.Keyword,
'CARDINALITY': tokens.Keyword,
'CASCADE': tokens.Keyword,
'CASCADED': tokens.Keyword,
'CAST': tokens.Keyword,
'CATALOG': tokens.Keyword,
'CATALOG_NAME': tokens.Keyword,
'CHAIN': tokens.Keyword,
'CHARACTERISTICS': tokens.Keyword,
'CHARACTER_LENGTH': tokens.Keyword,
'CHARACTER_SET_CATALOG': tokens.Keyword,
'CHARACTER_SET_NAME': tokens.Keyword,
'CHARACTER_SET_SCHEMA': tokens.Keyword,
'CHAR_LENGTH': tokens.Keyword,
'CHARSET': tokens.Keyword,
'CHECK': tokens.Keyword,
'CHECKED': tokens.Keyword,
'CHECKPOINT': tokens.Keyword,
'CLASS': tokens.Keyword,
'CLASS_ORIGIN': tokens.Keyword,
'CLOB': tokens.Keyword,
'CLOSE': tokens.Keyword,
'CLUSTER': tokens.Keyword,
'COALESCE': tokens.Keyword,
'COBOL': tokens.Keyword,
'COLLATE': tokens.Keyword,
'COLLATION': tokens.Keyword,
'COLLATION_CATALOG': tokens.Keyword,
'COLLATION_NAME': tokens.Keyword,
'COLLATION_SCHEMA': tokens.Keyword,
'COLLECT': tokens.Keyword,
'COLUMN': tokens.Keyword,
'COLUMN_NAME': tokens.Keyword,
'COMPRESS': tokens.Keyword,
'COMMAND_FUNCTION': tokens.Keyword,
'COMMAND_FUNCTION_CODE': tokens.Keyword,
'COMMENT': tokens.Keyword,
'COMMIT': tokens.Keyword.DML,
'COMMITTED': tokens.Keyword,
'COMPLETION': tokens.Keyword,
'CONCURRENTLY': tokens.Keyword,
'CONDITION_NUMBER': tokens.Keyword,
'CONNECT': tokens.Keyword,
'CONNECTION': tokens.Keyword,
'CONNECTION_NAME': tokens.Keyword,
'CONSTRAINT': tokens.Keyword,
'CONSTRAINTS': tokens.Keyword,
'CONSTRAINT_CATALOG': tokens.Keyword,
'CONSTRAINT_NAME': tokens.Keyword,
'CONSTRAINT_SCHEMA': tokens.Keyword,
'CONSTRUCTOR': tokens.Keyword,
'CONTAINS': tokens.Keyword,
'CONTINUE': tokens.Keyword,
'CONVERSION': tokens.Keyword,
'CONVERT': tokens.Keyword,
'COPY': tokens.Keyword,
'CORRESPONDING': tokens.Keyword,
'COUNT': tokens.Keyword,
'CREATEDB': tokens.Keyword,
'CREATEUSER': tokens.Keyword,
'CROSS': tokens.Keyword,
'CUBE': tokens.Keyword,
'CURRENT': tokens.Keyword,
'CURRENT_DATE': tokens.Keyword,
'CURRENT_PATH': tokens.Keyword,
'CURRENT_ROLE': tokens.Keyword,
'CURRENT_TIME': tokens.Keyword,
'CURRENT_TIMESTAMP': tokens.Keyword,
'CURRENT_USER': tokens.Keyword,
'CURSOR': tokens.Keyword,
'CURSOR_NAME': tokens.Keyword,
'CYCLE': tokens.Keyword,
'DATA': tokens.Keyword,
'DATABASE': tokens.Keyword,
'DATETIME_INTERVAL_CODE': tokens.Keyword,
'DATETIME_INTERVAL_PRECISION': tokens.Keyword,
'DAY': tokens.Keyword,
'DEALLOCATE': tokens.Keyword,
'DECLARE': tokens.Keyword,
'DEFAULT': tokens.Keyword,
'DEFAULTS': tokens.Keyword,
'DEFERRABLE': tokens.Keyword,
'DEFERRED': tokens.Keyword,
'DEFINED': tokens.Keyword,
'DEFINER': tokens.Keyword,
'DELIMITER': tokens.Keyword,
'DELIMITERS': tokens.Keyword,
'DEREF': tokens.Keyword,
'DESC': tokens.Keyword.Order,
'DESCRIBE': tokens.Keyword,
'DESCRIPTOR': tokens.Keyword,
'DESTROY': tokens.Keyword,
'DESTRUCTOR': tokens.Keyword,
'DETERMINISTIC': tokens.Keyword,
'DIAGNOSTICS': tokens.Keyword,
'DICTIONARY': tokens.Keyword,
'DISABLE': tokens.Keyword,
'DISCONNECT': tokens.Keyword,
'DISPATCH': tokens.Keyword,
'DO': tokens.Keyword,
'DOMAIN': tokens.Keyword,
'DYNAMIC': tokens.Keyword,
'DYNAMIC_FUNCTION': tokens.Keyword,
'DYNAMIC_FUNCTION_CODE': tokens.Keyword,
'EACH': tokens.Keyword,
'ENABLE': tokens.Keyword,
'ENCODING': tokens.Keyword,
'ENCRYPTED': tokens.Keyword,
'END-EXEC': tokens.Keyword,
'ENGINE': tokens.Keyword,
'EQUALS': tokens.Keyword,
'ESCAPE': tokens.Keyword,
'EVERY': tokens.Keyword,
'EXCEPT': tokens.Keyword,
'EXCEPTION': tokens.Keyword,
'EXCLUDING': tokens.Keyword,
'EXCLUSIVE': tokens.Keyword,
'EXEC': tokens.Keyword,
'EXECUTE': tokens.Keyword,
'EXISTING': tokens.Keyword,
'EXISTS': tokens.Keyword,
'EXPLAIN': tokens.Keyword,
'EXTERNAL': tokens.Keyword,
'EXTRACT': tokens.Keyword,
'FALSE': tokens.Keyword,
'FETCH': tokens.Keyword,
'FILE': tokens.Keyword,
'FINAL': tokens.Keyword,
'FIRST': tokens.Keyword,
'FORCE': tokens.Keyword,
'FOREACH': tokens.Keyword,
'FOREIGN': tokens.Keyword,
'FORTRAN': tokens.Keyword,
'FORWARD': tokens.Keyword,
'FOUND': tokens.Keyword,
'FREE': tokens.Keyword,
'FREEZE': tokens.Keyword,
'FULL': tokens.Keyword,
'FUNCTION': tokens.Keyword,
# 'G': tokens.Keyword,
'GENERAL': tokens.Keyword,
'GENERATED': tokens.Keyword,
'GET': tokens.Keyword,
'GLOBAL': tokens.Keyword,
'GO': tokens.Keyword,
'GOTO': tokens.Keyword,
'GRANT': tokens.Keyword,
'GRANTED': tokens.Keyword,
'GROUPING': tokens.Keyword,
'HAVING': tokens.Keyword,
'HIERARCHY': tokens.Keyword,
'HOLD': tokens.Keyword,
'HOUR': tokens.Keyword,
'HOST': tokens.Keyword,
'IDENTIFIED': tokens.Keyword,
'IDENTITY': tokens.Keyword,
'IGNORE': tokens.Keyword,
'ILIKE': tokens.Keyword,
'IMMEDIATE': tokens.Keyword,
'IMMUTABLE': tokens.Keyword,
'IMPLEMENTATION': tokens.Keyword,
'IMPLICIT': tokens.Keyword,
'INCLUDING': tokens.Keyword,
'INCREMENT': tokens.Keyword,
'INDEX': tokens.Keyword,
'INDITCATOR': tokens.Keyword,
'INFIX': tokens.Keyword,
'INHERITS': tokens.Keyword,
'INITIAL': tokens.Keyword,
'INITIALIZE': tokens.Keyword,
'INITIALLY': tokens.Keyword,
'INOUT': tokens.Keyword,
'INPUT': tokens.Keyword,
'INSENSITIVE': tokens.Keyword,
'INSTANTIABLE': tokens.Keyword,
'INSTEAD': tokens.Keyword,
'INTERSECT': tokens.Keyword,
'INTO': tokens.Keyword,
'INVOKER': tokens.Keyword,
'IS': tokens.Keyword,
'ISNULL': tokens.Keyword,
'ISOLATION': tokens.Keyword,
'ITERATE': tokens.Keyword,
# 'K': tokens.Keyword,
'KEY': tokens.Keyword,
'KEY_MEMBER': tokens.Keyword,
'KEY_TYPE': tokens.Keyword,
'LANCOMPILER': tokens.Keyword,
'LANGUAGE': tokens.Keyword,
'LARGE': tokens.Keyword,
'LAST': tokens.Keyword,
'LATERAL': tokens.Keyword,
'LEADING': tokens.Keyword,
'LENGTH': tokens.Keyword,
'LESS': tokens.Keyword,
'LEVEL': tokens.Keyword,
'LIMIT': tokens.Keyword,
'LISTEN': tokens.Keyword,
'LOAD': tokens.Keyword,
'LOCAL': tokens.Keyword,
'LOCALTIME': tokens.Keyword,
'LOCALTIMESTAMP': tokens.Keyword,
'LOCATION': tokens.Keyword,
'LOCATOR': tokens.Keyword,
'LOCK': tokens.Keyword,
'LOWER': tokens.Keyword,
# 'M': tokens.Keyword,
'MAP': tokens.Keyword,
'MATCH': tokens.Keyword,
'MAXEXTENTS': tokens.Keyword,
'MAXVALUE': tokens.Keyword,
'MESSAGE_LENGTH': tokens.Keyword,
'MESSAGE_OCTET_LENGTH': tokens.Keyword,
'MESSAGE_TEXT': tokens.Keyword,
'METHOD': tokens.Keyword,
'MINUTE': tokens.Keyword,
'MINUS': tokens.Keyword,
'MINVALUE': tokens.Keyword,
'MOD': tokens.Keyword,
'MODE': tokens.Keyword,
'MODIFIES': tokens.Keyword,
'MODIFY': tokens.Keyword,
'MONTH': tokens.Keyword,
'MORE': tokens.Keyword,
'MOVE': tokens.Keyword,
'MUMPS': tokens.Keyword,
'NAMES': tokens.Keyword,
'NATIONAL': tokens.Keyword,
'NATURAL': tokens.Keyword,
'NCHAR': tokens.Keyword,
'NCLOB': tokens.Keyword,
'NEW': tokens.Keyword,
'NEXT': tokens.Keyword,
'NO': tokens.Keyword,
'NOAUDIT': tokens.Keyword,
'NOCOMPRESS': tokens.Keyword,
'NOCREATEDB': tokens.Keyword,
'NOCREATEUSER': tokens.Keyword,
'NONE': tokens.Keyword,
'NOT': tokens.Keyword,
'NOTFOUND': tokens.Keyword,
'NOTHING': tokens.Keyword,
'NOTIFY': tokens.Keyword,
'NOTNULL': tokens.Keyword,
'NOWAIT': tokens.Keyword,
'NULL': tokens.Keyword,
'NULLABLE': tokens.Keyword,
'NULLIF': tokens.Keyword,
'OBJECT': tokens.Keyword,
'OCTET_LENGTH': tokens.Keyword,
'OF': tokens.Keyword,
'OFF': tokens.Keyword,
'OFFLINE': tokens.Keyword,
'OFFSET': tokens.Keyword,
'OIDS': tokens.Keyword,
'OLD': tokens.Keyword,
'ONLINE': tokens.Keyword,
'ONLY': tokens.Keyword,
'OPEN': tokens.Keyword,
'OPERATION': tokens.Keyword,
'OPERATOR': tokens.Keyword,
'OPTION': tokens.Keyword,
'OPTIONS': tokens.Keyword,
'ORDINALITY': tokens.Keyword,
'OUT': tokens.Keyword,
'OUTPUT': tokens.Keyword,
'OVERLAPS': tokens.Keyword,
'OVERLAY': tokens.Keyword,
'OVERRIDING': tokens.Keyword,
'OWNER': tokens.Keyword,
'QUARTER': tokens.Keyword,
'PAD': tokens.Keyword,
'PARAMETER': tokens.Keyword,
'PARAMETERS': tokens.Keyword,
'PARAMETER_MODE': tokens.Keyword,
'PARAMETER_NAME': tokens.Keyword,
'PARAMETER_ORDINAL_POSITION': tokens.Keyword,
'PARAMETER_SPECIFIC_CATALOG': tokens.Keyword,
'PARAMETER_SPECIFIC_NAME': tokens.Keyword,
'PARAMETER_SPECIFIC_SCHEMA': tokens.Keyword,
'PARTIAL': tokens.Keyword,
'PASCAL': tokens.Keyword,
'PCTFREE': tokens.Keyword,
'PENDANT': tokens.Keyword,
'PLACING': tokens.Keyword,
'PLI': tokens.Keyword,
'POSITION': tokens.Keyword,
'POSTFIX': tokens.Keyword,
'PRECISION': tokens.Keyword,
'PREFIX': tokens.Keyword,
'PREORDER': tokens.Keyword,
'PREPARE': tokens.Keyword,
'PRESERVE': tokens.Keyword,
'PRIMARY': tokens.Keyword,
'PRIOR': tokens.Keyword,
'PRIVILEGES': tokens.Keyword,
'PROCEDURAL': tokens.Keyword,
'PROCEDURE': tokens.Keyword,
'PUBLIC': tokens.Keyword,
'RAISE': tokens.Keyword,
'RAW': tokens.Keyword,
'READ': tokens.Keyword,
'READS': tokens.Keyword,
'RECHECK': tokens.Keyword,
'RECURSIVE': tokens.Keyword,
'REF': tokens.Keyword,
'REFERENCES': tokens.Keyword,
'REFERENCING': tokens.Keyword,
'REINDEX': tokens.Keyword,
'RELATIVE': tokens.Keyword,
'RENAME': tokens.Keyword,
'REPEATABLE': tokens.Keyword,
'RESET': tokens.Keyword,
'RESOURCE': tokens.Keyword,
'RESTART': tokens.Keyword,
'RESTRICT': tokens.Keyword,
'RESULT': tokens.Keyword,
'RETURN': tokens.Keyword,
'RETURNED_LENGTH': tokens.Keyword,
'RETURNED_OCTET_LENGTH': tokens.Keyword,
'RETURNED_SQLSTATE': tokens.Keyword,
'RETURNING': tokens.Keyword,
'RETURNS': tokens.Keyword,
'REVOKE': tokens.Keyword,
'RIGHT': tokens.Keyword,
'ROLE': tokens.Keyword,
'ROLLBACK': tokens.Keyword.DML,
'ROLLUP': tokens.Keyword,
'ROUTINE': tokens.Keyword,
'ROUTINE_CATALOG': tokens.Keyword,
'ROUTINE_NAME': tokens.Keyword,
'ROUTINE_SCHEMA': tokens.Keyword,
'ROW': tokens.Keyword,
'ROWS': tokens.Keyword,
'ROW_COUNT': tokens.Keyword,
'RULE': tokens.Keyword,
'SAVE_POINT': tokens.Keyword,
'SCALE': tokens.Keyword,
'SCHEMA': tokens.Keyword,
'SCHEMA_NAME': tokens.Keyword,
'SCOPE': tokens.Keyword,
'SCROLL': tokens.Keyword,
'SEARCH': tokens.Keyword,
'SECOND': tokens.Keyword,
'SECURITY': tokens.Keyword,
'SELF': tokens.Keyword,
'SENSITIVE': tokens.Keyword,
'SEQUENCE': tokens.Keyword,
'SERIALIZABLE': tokens.Keyword,
'SERVER_NAME': tokens.Keyword,
'SESSION': tokens.Keyword,
'SESSION_USER': tokens.Keyword,
'SETOF': tokens.Keyword,
'SETS': tokens.Keyword,
'SHARE': tokens.Keyword,
'SHOW': tokens.Keyword,
'SIMILAR': tokens.Keyword,
'SIMPLE': tokens.Keyword,
'SIZE': tokens.Keyword,
'SOME': tokens.Keyword,
'SOURCE': tokens.Keyword,
'SPACE': tokens.Keyword,
'SPECIFIC': tokens.Keyword,
'SPECIFICTYPE': tokens.Keyword,
'SPECIFIC_NAME': tokens.Keyword,
'SQL': tokens.Keyword,
'SQLBUF': tokens.Keyword,
'SQLCODE': tokens.Keyword,
'SQLERROR': tokens.Keyword,
'SQLEXCEPTION': tokens.Keyword,
'SQLSTATE': tokens.Keyword,
'SQLWARNING': tokens.Keyword,
'STABLE': tokens.Keyword,
'START': tokens.Keyword.DML,
# 'STATE': tokens.Keyword,
'STATEMENT': tokens.Keyword,
'STATIC': tokens.Keyword,
'STATISTICS': tokens.Keyword,
'STDIN': tokens.Keyword,
'STDOUT': tokens.Keyword,
'STORAGE': tokens.Keyword,
'STRICT': tokens.Keyword,
'STRUCTURE': tokens.Keyword,
'STYPE': tokens.Keyword,
'SUBCLASS_ORIGIN': tokens.Keyword,
'SUBLIST': tokens.Keyword,
'SUBSTRING': tokens.Keyword,
'SUCCESSFUL': tokens.Keyword,
'SUM': tokens.Keyword,
'SYMMETRIC': tokens.Keyword,
'SYNONYM': tokens.Keyword,
'SYSID': tokens.Keyword,
'SYSTEM': tokens.Keyword,
'SYSTEM_USER': tokens.Keyword,
'TABLE': tokens.Keyword,
'TABLE_NAME': tokens.Keyword,
'TEMP': tokens.Keyword,
'TEMPLATE': tokens.Keyword,
'TEMPORARY': tokens.Keyword,
'TERMINATE': tokens.Keyword,
'THAN': tokens.Keyword,
'TIMESTAMP': tokens.Keyword,
'TIMEZONE_HOUR': tokens.Keyword,
'TIMEZONE_MINUTE': tokens.Keyword,
'TO': tokens.Keyword,
'TOAST': tokens.Keyword,
'TRAILING': tokens.Keyword,
'TRANSATION': tokens.Keyword,
'TRANSACTIONS_COMMITTED': tokens.Keyword,
'TRANSACTIONS_ROLLED_BACK': tokens.Keyword,
'TRANSATION_ACTIVE': tokens.Keyword,
'TRANSFORM': tokens.Keyword,
'TRANSFORMS': tokens.Keyword,
'TRANSLATE': tokens.Keyword,
'TRANSLATION': tokens.Keyword,
'TREAT': tokens.Keyword,
'TRIGGER': tokens.Keyword,
'TRIGGER_CATALOG': tokens.Keyword,
'TRIGGER_NAME': tokens.Keyword,
'TRIGGER_SCHEMA': tokens.Keyword,
'TRIM': tokens.Keyword,
'TRUE': tokens.Keyword,
'TRUNCATE': tokens.Keyword,
'TRUSTED': tokens.Keyword,
'TYPE': tokens.Keyword,
'UID': tokens.Keyword,
'UNCOMMITTED': tokens.Keyword,
'UNDER': tokens.Keyword,
'UNENCRYPTED': tokens.Keyword,
'UNION': tokens.Keyword,
'UNIQUE': tokens.Keyword,
'UNKNOWN': tokens.Keyword,
'UNLISTEN': tokens.Keyword,
'UNNAMED': tokens.Keyword,
'UNNEST': tokens.Keyword,
'UNTIL': tokens.Keyword,
'UPPER': tokens.Keyword,
'USAGE': tokens.Keyword,
'USE': tokens.Keyword,
'USER': tokens.Keyword,
'USER_DEFINED_TYPE_CATALOG': tokens.Keyword,
'USER_DEFINED_TYPE_NAME': tokens.Keyword,
'USER_DEFINED_TYPE_SCHEMA': tokens.Keyword,
'USING': tokens.Keyword,
'VACUUM': tokens.Keyword,
'VALID': tokens.Keyword,
'VALIDATE': tokens.Keyword,
'VALIDATOR': tokens.Keyword,
'VALUES': tokens.Keyword,
'VARIABLE': tokens.Keyword,
'VERBOSE': tokens.Keyword,
'VERSION': tokens.Keyword,
'VIEW': tokens.Keyword,
'VOLATILE': tokens.Keyword,
'WEEK': tokens.Keyword,
'WHENEVER': tokens.Keyword,
'WITH': tokens.Keyword.CTE,
'WITHOUT': tokens.Keyword,
'WORK': tokens.Keyword,
'WRITE': tokens.Keyword,
'YEAR': tokens.Keyword,
'ZONE': tokens.Keyword,
# Name.Builtin
'ARRAY': tokens.Name.Builtin,
'BIGINT': tokens.Name.Builtin,
'BINARY': tokens.Name.Builtin,
'BIT': tokens.Name.Builtin,
'BLOB': tokens.Name.Builtin,
'BOOLEAN': tokens.Name.Builtin,
'CHAR': tokens.Name.Builtin,
'CHARACTER': tokens.Name.Builtin,
'DATE': tokens.Name.Builtin,
'DEC': tokens.Name.Builtin,
'DECIMAL': tokens.Name.Builtin,
'FILE_TYPE': tokens.Name.Builtin,
'FLOAT': tokens.Name.Builtin,
'INT': tokens.Name.Builtin,
'INT8': tokens.Name.Builtin,
'INTEGER': tokens.Name.Builtin,
'INTERVAL': tokens.Name.Builtin,
'LONG': tokens.Name.Builtin,
'NATURALN': tokens.Name.Builtin,
'NVARCHAR': tokens.Name.Builtin,
'NUMBER': tokens.Name.Builtin,
'NUMERIC': tokens.Name.Builtin,
'PLS_INTEGER': tokens.Name.Builtin,
'POSITIVE': tokens.Name.Builtin,
'POSITIVEN': tokens.Name.Builtin,
'REAL': tokens.Name.Builtin,
'ROWID': tokens.Name.Builtin,
'ROWLABEL': tokens.Name.Builtin,
'ROWNUM': tokens.Name.Builtin,
'SERIAL': tokens.Name.Builtin,
'SERIAL8': tokens.Name.Builtin,
'SIGNED': tokens.Name.Builtin,
'SIGNTYPE': tokens.Name.Builtin,
'SIMPLE_DOUBLE': tokens.Name.Builtin,
'SIMPLE_FLOAT': tokens.Name.Builtin,
'SIMPLE_INTEGER': tokens.Name.Builtin,
'SMALLINT': tokens.Name.Builtin,
'SYS_REFCURSOR': tokens.Name.Builtin,
'SYSDATE': tokens.Name,
'TEXT': tokens.Name.Builtin,
'TINYINT': tokens.Name.Builtin,
'UNSIGNED': tokens.Name.Builtin,
'UROWID': tokens.Name.Builtin,
'UTL_FILE': tokens.Name.Builtin,
'VARCHAR': tokens.Name.Builtin,
'VARCHAR2': tokens.Name.Builtin,
'VARYING': tokens.Name.Builtin,
}
KEYWORDS_COMMON = {
'SELECT': tokens.Keyword.DML,
'INSERT': tokens.Keyword.DML,
'DELETE': tokens.Keyword.DML,
'UPDATE': tokens.Keyword.DML,
'UPSERT': tokens.Keyword.DML,
'REPLACE': tokens.Keyword.DML,
'MERGE': tokens.Keyword.DML,
'DROP': tokens.Keyword.DDL,
'CREATE': tokens.Keyword.DDL,
'ALTER': tokens.Keyword.DDL,
'WHERE': tokens.Keyword,
'FROM': tokens.Keyword,
'INNER': tokens.Keyword,
'JOIN': tokens.Keyword,
'STRAIGHT_JOIN': tokens.Keyword,
'AND': tokens.Keyword,
'OR': tokens.Keyword,
'LIKE': tokens.Keyword,
'ON': tokens.Keyword,
'IN': tokens.Keyword,
'SET': tokens.Keyword,
'BY': tokens.Keyword,
'GROUP': tokens.Keyword,
'ORDER': tokens.Keyword,
'LEFT': tokens.Keyword,
'OUTER': tokens.Keyword,
'FULL': tokens.Keyword,
'IF': tokens.Keyword,
'END': tokens.Keyword,
'THEN': tokens.Keyword,
'LOOP': tokens.Keyword,
'AS': tokens.Keyword,
'ELSE': tokens.Keyword,
'FOR': tokens.Keyword,
'WHILE': tokens.Keyword,
'CASE': tokens.Keyword,
'WHEN': tokens.Keyword,
'MIN': tokens.Keyword,
'MAX': tokens.Keyword,
'DISTINCT': tokens.Keyword,
}
# oracle 关键字
KEYWORDS_ORACLE = {
'ARCHIVE': tokens.Keyword,
'ARCHIVELOG': tokens.Keyword,
'BACKUP': tokens.Keyword,
'BECOME': tokens.Keyword,
'BLOCK': tokens.Keyword,
'BODY': tokens.Keyword,
'CANCEL': tokens.Keyword,
'CHANGE': tokens.Keyword,
'COMPILE': tokens.Keyword,
'CONTENTS': tokens.Keyword,
'CONTROLFILE': tokens.Keyword,
'DATAFILE': tokens.Keyword,
'DBA': tokens.Keyword,
'DISMOUNT': tokens.Keyword,
'DOUBLE': tokens.Keyword,
'DUMP': tokens.Keyword,
'ELSIF': tokens.Keyword,
'EVENTS': tokens.Keyword,
'EXCEPTIONS': tokens.Keyword,
'EXPLAIN': tokens.Keyword,
'EXTENT': tokens.Keyword,
'EXTERNALLY': tokens.Keyword,
'FLUSH': tokens.Keyword,
'FREELIST': tokens.Keyword,
'FREELISTS': tokens.Keyword,
# groups seems too common as table name
# 'GROUPS': tokens.Keyword,
'INDICATOR': tokens.Keyword,
'INITRANS': tokens.Keyword,
'INSTANCE': tokens.Keyword,
'LAYER': tokens.Keyword,
'LINK': tokens.Keyword,
'LISTS': tokens.Keyword,
'LOGFILE': tokens.Keyword,
'MANAGE': tokens.Keyword,
'MANUAL': tokens.Keyword,
'MAXDATAFILES': tokens.Keyword,
'MAXINSTANCES': tokens.Keyword,
'MAXLOGFILES': tokens.Keyword,
'MAXLOGHISTORY': tokens.Keyword,
'MAXLOGMEMBERS': tokens.Keyword,
'MAXTRANS': tokens.Keyword,
'MINEXTENTS': tokens.Keyword,
'MODULE': tokens.Keyword,
'MOUNT': tokens.Keyword,
'NOARCHIVELOG': tokens.Keyword,
'NOCACHE': tokens.Keyword,
'NOCYCLE': tokens.Keyword,
'NOMAXVALUE': tokens.Keyword,
'NOMINVALUE': tokens.Keyword,
'NOORDER': tokens.Keyword,
'NORESETLOGS': tokens.Keyword,
'NORMAL': tokens.Keyword,
'NOSORT': tokens.Keyword,
'OPTIMAL': tokens.Keyword,
'OWN': tokens.Keyword,
'PACKAGE': tokens.Keyword,
'PARALLEL': tokens.Keyword,
'PCTINCREASE': tokens.Keyword,
'PCTUSED': tokens.Keyword,
'PLAN': tokens.Keyword,
'PRIVATE': tokens.Keyword,
'PROFILE': tokens.Keyword,
'QUOTA': tokens.Keyword,
'RECOVER': tokens.Keyword,
'RESETLOGS': tokens.Keyword,
'RESTRICTED': tokens.Keyword,
'REUSE': tokens.Keyword,
'ROLES': tokens.Keyword,
'SAVEPOINT': tokens.Keyword,
'SCN': tokens.Keyword,
'SECTION': tokens.Keyword,
'SEGMENT': tokens.Keyword,
'SHARED': tokens.Keyword,
'SNAPSHOT': tokens.Keyword,
'SORT': tokens.Keyword,
'STATEMENT_ID': tokens.Keyword,
'STOP': tokens.Keyword,
'SWITCH': tokens.Keyword,
'TABLES': tokens.Keyword,
'TABLESPACE': tokens.Keyword,
'THREAD': tokens.Keyword,
'TIME': tokens.Keyword,
'TRACING': tokens.Keyword,
'TRANSACTION': tokens.Keyword,
'TRIGGERS': tokens.Keyword,
'UNLIMITED': tokens.Keyword,
'UNLOCK': tokens.Keyword,
}
# PostgreSQL Syntax
KEYWORDS_PLPGSQL = {
'CONFLICT': tokens.Keyword,
'WINDOW': tokens.Keyword,
'PARTITION': tokens.Keyword,
'OVER': tokens.Keyword,
'PERFORM': tokens.Keyword,
'NOTICE': tokens.Keyword,
'PLPGSQL': tokens.Keyword,
'INHERIT': tokens.Keyword,
'INDEXES': tokens.Keyword,
'ON_ERROR_STOP': tokens.Keyword,
'BYTEA': tokens.Keyword,
'BIGSERIAL': tokens.Keyword,
'BIT VARYING': tokens.Keyword,
'BOX': tokens.Keyword,
'CHARACTER': tokens.Keyword,
'CHARACTER VARYING': tokens.Keyword,
'CIDR': tokens.Keyword,
'CIRCLE': tokens.Keyword,
'DOUBLE PRECISION': tokens.Keyword,
'INET': tokens.Keyword,
'JSON': tokens.Keyword,
'JSONB': tokens.Keyword,
'LINE': tokens.Keyword,
'LSEG': tokens.Keyword,
'MACADDR': tokens.Keyword,
'MONEY': tokens.Keyword,
'PATH': tokens.Keyword,
'PG_LSN': tokens.Keyword,
'POINT': tokens.Keyword,
'POLYGON': tokens.Keyword,
'SMALLSERIAL': tokens.Keyword,
'TSQUERY': tokens.Keyword,
'TSVECTOR': tokens.Keyword,
'TXID_SNAPSHOT': tokens.Keyword,
'UUID': tokens.Keyword,
'XML': tokens.Keyword,
'FOR': tokens.Keyword,
'IN': tokens.Keyword,
'LOOP': tokens.Keyword,
}
# Hive Syntax
# hive 语法
KEYWORDS_HQL = {
'EXPLODE': tokens.Keyword,
'DIRECTORY': tokens.Keyword,
'DISTRIBUTE': tokens.Keyword,
'INCLUDE': tokens.Keyword,
'LOCATE': tokens.Keyword,
'OVERWRITE': tokens.Keyword,
'POSEXPLODE': tokens.Keyword,
'ARRAY_CONTAINS': tokens.Keyword,
'CMP': tokens.Keyword,
'COLLECT_LIST': tokens.Keyword,
'CONCAT': tokens.Keyword,
'CONDITION': tokens.Keyword,
'DATE_ADD': tokens.Keyword,
'DATE_SUB': tokens.Keyword,
'DECODE': tokens.Keyword,
'DBMS_OUTPUT': tokens.Keyword,
'ELEMENTS': tokens.Keyword,
'EXCHANGE': tokens.Keyword,
'EXTENDED': tokens.Keyword,
'FLOOR': tokens.Keyword,
'FOLLOWING': tokens.Keyword,
'FROM_UNIXTIME': tokens.Keyword,
'FTP': tokens.Keyword,
'HOUR': tokens.Keyword,
'INLINE': tokens.Keyword,
'INSTR': tokens.Keyword,
'LEN': tokens.Keyword,
'MAXELEMENT': tokens.Keyword,
'MAXINDEX': tokens.Keyword,
'MAX_PART_DATE': tokens.Keyword,
'MAX_PART_INT': tokens.Keyword,
'MAX_PART_STRING': tokens.Keyword,
'MINELEMENT': tokens.Keyword,
'MININDEX': tokens.Keyword,
'MIN_PART_DATE': tokens.Keyword,
'MIN_PART_INT': tokens.Keyword,
'MIN_PART_STRING': tokens.Keyword,
'NOW': tokens.Keyword,
'NVL': tokens.Keyword,
'NVL2': tokens.Keyword,
'PARSE_URL_TUPLE': tokens.Keyword,
'PART_LOC': tokens.Keyword,
'PART_COUNT': tokens.Keyword,
'PART_COUNT_BY': tokens.Keyword,
'PRINT': tokens.Keyword,
'PUT_LINE': tokens.Keyword,
'RANGE': tokens.Keyword,
'REDUCE': tokens.Keyword,
'REGEXP_REPLACE': tokens.Keyword,
'RESIGNAL': tokens.Keyword,
'RTRIM': tokens.Keyword,
'SIGN': tokens.Keyword,
'SIGNAL': tokens.Keyword,
'SIN': tokens.Keyword,
'SPLIT': tokens.Keyword,
'SQRT': tokens.Keyword,
'STACK': tokens.Keyword,
'STR': tokens.Keyword,
'SUBSTR': tokens.Keyword,
'SUMMARY': tokens.Keyword,
'TBLPROPERTIES': tokens.Keyword,
'TIMESTAMP_ISO': tokens.Keyword,
'TO_CHAR': tokens.Keyword,
'TO_DATE': tokens.Keyword,
'TO_TIMESTAMP': tokens.Keyword,
'TRUNC': tokens.Keyword,
'UNBOUNDED': tokens.Keyword,
'UNIQUEJOIN': tokens.Keyword,
'UNIX_TIMESTAMP': tokens.Keyword,
'UTC_TIMESTAMP': tokens.Keyword,
'VIEWS': tokens.Keyword,
'EXIT': tokens.Keyword,
'BREAK': tokens.Keyword,
'LEAVE': tokens.Keyword,
}
| 30.72378 | 79 | 0.633961 |
import re
from sqlparse import tokens
def is_keyword(value):
val = value.upper()
return (KEYWORDS_COMMON.get(val)
or KEYWORDS_ORACLE.get(val)
or KEYWORDS_PLPGSQL.get(val)
or KEYWORDS_HQL.get(val)
or KEYWORDS.get(val, tokens.Name)), value
SQL_REGEX = {
'root': [
(r'(--|# )\+.*?(\r\n|\r|\n|$)', tokens.Comment.Single.Hint),
(r'/\*\+[\s\S]*?\*/', tokens.Comment.Multiline.Hint),
(r'(--|# ).*?(\r\n|\r|\n|$)', tokens.Comment.Single),
(r'/\*[\s\S]*?\*/', tokens.Comment.Multiline),
(r'(\r\n|\r|\n)', tokens.Newline),
(r'\s+?', tokens.Whitespace),
(r':=', tokens.Assignment),
(r'::', tokens.Punctuation),
(r'\*', tokens.Wildcard),
(r"`(``|[^`])*`", tokens.Name),
(r"´(´´|[^´])*´", tokens.Name),
(r'((?<!\S)\$(?:[_A-ZÀ-Ü]\w*)?\$)[\s\S]*?\1', tokens.Literal),
(r'\?', tokens.Name.Placeholder),
(r'%(\(\w+\))?s', tokens.Name.Placeholder),
(r'(?<!\w)[$:?]\w+', tokens.Name.Placeholder),
(r'\\\w+', tokens.Command),
(r'(NOT\s+)?(IN)\b', tokens.Operator.Comparison),
# see https://github.com/andialbrecht/sqlparse/pull/64
# AS and IN are special, it may be followed by a parenthesis, but
# are never functions, see issue183 and issue507
(r'(CASE|IN|VALUES|USING|FROM|AS)\b', tokens.Keyword),
(r'(@|hema . name` are valid identifier
# TODO: Spaces before period not implemented
(r'[A-ZÀ-Ü]\w*(?=\s*\.)', tokens.Name), # 'Name' .
# FIXME(atronah): never match,
# because `re.match` doesn't work with look-behind regexp feature
(r'(?<=\.)[A-ZÀ-Ü]\w*', tokens.Name),
(r'[A-ZÀ-Ü]\w*(?=\()', tokens.Name),
(r'-?0x[\dA-F]+', tokens.Number.Hexadecimal),
(r'-?\d*(\.\d+)?E-?\d+', tokens.Number.Float),
(r'(?![_A-ZÀ-Ü])-?(\d+(\.\d*)|\.\d+)(?![_A-ZÀ-Ü])',
tokens.Number.Float),
(r'(?![_A-ZÀ-Ü])-?\d+(?![_A-ZÀ-Ü])', tokens.Number.Integer),
(r"'(''|\\\\|\\'|[^'])*'", tokens.String.Single),
(r'"(""|\\\\|\\"|[^"])*"', tokens.String.Symbol),
(r'(""|".*?[^\\]")', tokens.String.Symbol),
(r'(?<![\w\])])(\[[^\]\[]+\])', tokens.Name),
(r'((LEFT\s+|RIGHT\s+|FULL\s+)?(INNER\s+|OUTER\s+|STRAIGHT\s+)?'
r'|(CROSS\s+|NATURAL\s+)?)?JOIN\b', tokens.Keyword),
(r'END(\s+IF|\s+LOOP|\s+WHILE)?\b', tokens.Keyword),
(r'NOT\s+NULL\b', tokens.Keyword),
(r'NULLS\s+(FIRST|LAST)\b', tokens.Keyword),
(r'UNION\s+ALL\b', tokens.Keyword),
(r'CREATE(\s+OR\s+REPLACE)?\b', tokens.Keyword.DDL),
(r'DOUBLE\s+PRECISION\b', tokens.Name.Builtin),
(r'GROUP\s+BY\b', tokens.Keyword),
(r'ORDER\s+BY\b', tokens.Keyword),
(r'HANDLER\s+FOR\b', tokens.Keyword),
(r'(LATERAL\s+VIEW\s+)'
r'(EXPLODE|INLINE|PARSE_URL_TUPLE|POSEXPLODE|STACK)\b',
tokens.Keyword),
(r"(AT|WITH')\s+TIME\s+ZONE\s+'[^']+'", tokens.Keyword.TZCast),
(r'(NOT\s+)?(LIKE|ILIKE|RLIKE)\b', tokens.Operator.Comparison),
(r'[0-9_A-ZÀ-Ü][_$
(r'[;:()\[\],\.]', tokens.Punctuation),
(r'[<>=~!]+', tokens.Operator.Comparison),
(r'[+/@
]}
#标签
FLAGS = re.IGNORECASE | re.UNICODE
SQL_REGEX = [(re.compile(rx, FLAGS).match, tt) for rx, tt in SQL_REGEX['root']]
# 通用关键字
KEYWORDS = {
'ABORT': tokens.Keyword,
'ABS': tokens.Keyword,
'ABSOLUTE': tokens.Keyword,
'ACCESS': tokens.Keyword,
'ADA': tokens.Keyword,
'ADD': tokens.Keyword,
'ADMIN': tokens.Keyword,
'AFTER': tokens.Keyword,
'AGGREGATE': tokens.Keyword,
'ALIAS': tokens.Keyword,
'ALL': tokens.Keyword,
'ALLOCATE': tokens.Keyword,
'ANALYSE': tokens.Keyword,
'ANALYZE': tokens.Keyword,
'ANY': tokens.Keyword,
'ARRAYLEN': tokens.Keyword,
'ARE': tokens.Keyword,
'ASC': tokens.Keyword.Order,
'ASENSITIVE': tokens.Keyword,
'ASSERTION': tokens.Keyword,
'ASSIGNMENT': tokens.Keyword,
'ASYMMETRIC': tokens.Keyword,
'AT': tokens.Keyword,
'ATOMIC': tokens.Keyword,
'AUDIT': tokens.Keyword,
'AUTHORIZATION': tokens.Keyword,
'AUTO_INCREMENT': tokens.Keyword,
'AVG': tokens.Keyword,
'BACKWARD': tokens.Keyword,
'BEFORE': tokens.Keyword,
'BEGIN': tokens.Keyword,
'BETWEEN': tokens.Keyword,
'BITVAR': tokens.Keyword,
'BIT_LENGTH': tokens.Keyword,
'BOTH': tokens.Keyword,
'BREADTH': tokens.Keyword,
# 'C': tokens.Keyword, # most likely this is an alias
'CACHE': tokens.Keyword,
'CALL': tokens.Keyword,
'CALLED': tokens.Keyword,
'CARDINALITY': tokens.Keyword,
'CASCADE': tokens.Keyword,
'CASCADED': tokens.Keyword,
'CAST': tokens.Keyword,
'CATALOG': tokens.Keyword,
'CATALOG_NAME': tokens.Keyword,
'CHAIN': tokens.Keyword,
'CHARACTERISTICS': tokens.Keyword,
'CHARACTER_LENGTH': tokens.Keyword,
'CHARACTER_SET_CATALOG': tokens.Keyword,
'CHARACTER_SET_NAME': tokens.Keyword,
'CHARACTER_SET_SCHEMA': tokens.Keyword,
'CHAR_LENGTH': tokens.Keyword,
'CHARSET': tokens.Keyword,
'CHECK': tokens.Keyword,
'CHECKED': tokens.Keyword,
'CHECKPOINT': tokens.Keyword,
'CLASS': tokens.Keyword,
'CLASS_ORIGIN': tokens.Keyword,
'CLOB': tokens.Keyword,
'CLOSE': tokens.Keyword,
'CLUSTER': tokens.Keyword,
'COALESCE': tokens.Keyword,
'COBOL': tokens.Keyword,
'COLLATE': tokens.Keyword,
'COLLATION': tokens.Keyword,
'COLLATION_CATALOG': tokens.Keyword,
'COLLATION_NAME': tokens.Keyword,
'COLLATION_SCHEMA': tokens.Keyword,
'COLLECT': tokens.Keyword,
'COLUMN': tokens.Keyword,
'COLUMN_NAME': tokens.Keyword,
'COMPRESS': tokens.Keyword,
'COMMAND_FUNCTION': tokens.Keyword,
'COMMAND_FUNCTION_CODE': tokens.Keyword,
'COMMENT': tokens.Keyword,
'COMMIT': tokens.Keyword.DML,
'COMMITTED': tokens.Keyword,
'COMPLETION': tokens.Keyword,
'CONCURRENTLY': tokens.Keyword,
'CONDITION_NUMBER': tokens.Keyword,
'CONNECT': tokens.Keyword,
'CONNECTION': tokens.Keyword,
'CONNECTION_NAME': tokens.Keyword,
'CONSTRAINT': tokens.Keyword,
'CONSTRAINTS': tokens.Keyword,
'CONSTRAINT_CATALOG': tokens.Keyword,
'CONSTRAINT_NAME': tokens.Keyword,
'CONSTRAINT_SCHEMA': tokens.Keyword,
'CONSTRUCTOR': tokens.Keyword,
'CONTAINS': tokens.Keyword,
'CONTINUE': tokens.Keyword,
'CONVERSION': tokens.Keyword,
'CONVERT': tokens.Keyword,
'COPY': tokens.Keyword,
'CORRESPONDING': tokens.Keyword,
'COUNT': tokens.Keyword,
'CREATEDB': tokens.Keyword,
'CREATEUSER': tokens.Keyword,
'CROSS': tokens.Keyword,
'CUBE': tokens.Keyword,
'CURRENT': tokens.Keyword,
'CURRENT_DATE': tokens.Keyword,
'CURRENT_PATH': tokens.Keyword,
'CURRENT_ROLE': tokens.Keyword,
'CURRENT_TIME': tokens.Keyword,
'CURRENT_TIMESTAMP': tokens.Keyword,
'CURRENT_USER': tokens.Keyword,
'CURSOR': tokens.Keyword,
'CURSOR_NAME': tokens.Keyword,
'CYCLE': tokens.Keyword,
'DATA': tokens.Keyword,
'DATABASE': tokens.Keyword,
'DATETIME_INTERVAL_CODE': tokens.Keyword,
'DATETIME_INTERVAL_PRECISION': tokens.Keyword,
'DAY': tokens.Keyword,
'DEALLOCATE': tokens.Keyword,
'DECLARE': tokens.Keyword,
'DEFAULT': tokens.Keyword,
'DEFAULTS': tokens.Keyword,
'DEFERRABLE': tokens.Keyword,
'DEFERRED': tokens.Keyword,
'DEFINED': tokens.Keyword,
'DEFINER': tokens.Keyword,
'DELIMITER': tokens.Keyword,
'DELIMITERS': tokens.Keyword,
'DEREF': tokens.Keyword,
'DESC': tokens.Keyword.Order,
'DESCRIBE': tokens.Keyword,
'DESCRIPTOR': tokens.Keyword,
'DESTROY': tokens.Keyword,
'DESTRUCTOR': tokens.Keyword,
'DETERMINISTIC': tokens.Keyword,
'DIAGNOSTICS': tokens.Keyword,
'DICTIONARY': tokens.Keyword,
'DISABLE': tokens.Keyword,
'DISCONNECT': tokens.Keyword,
'DISPATCH': tokens.Keyword,
'DO': tokens.Keyword,
'DOMAIN': tokens.Keyword,
'DYNAMIC': tokens.Keyword,
'DYNAMIC_FUNCTION': tokens.Keyword,
'DYNAMIC_FUNCTION_CODE': tokens.Keyword,
'EACH': tokens.Keyword,
'ENABLE': tokens.Keyword,
'ENCODING': tokens.Keyword,
'ENCRYPTED': tokens.Keyword,
'END-EXEC': tokens.Keyword,
'ENGINE': tokens.Keyword,
'EQUALS': tokens.Keyword,
'ESCAPE': tokens.Keyword,
'EVERY': tokens.Keyword,
'EXCEPT': tokens.Keyword,
'EXCEPTION': tokens.Keyword,
'EXCLUDING': tokens.Keyword,
'EXCLUSIVE': tokens.Keyword,
'EXEC': tokens.Keyword,
'EXECUTE': tokens.Keyword,
'EXISTING': tokens.Keyword,
'EXISTS': tokens.Keyword,
'EXPLAIN': tokens.Keyword,
'EXTERNAL': tokens.Keyword,
'EXTRACT': tokens.Keyword,
'FALSE': tokens.Keyword,
'FETCH': tokens.Keyword,
'FILE': tokens.Keyword,
'FINAL': tokens.Keyword,
'FIRST': tokens.Keyword,
'FORCE': tokens.Keyword,
'FOREACH': tokens.Keyword,
'FOREIGN': tokens.Keyword,
'FORTRAN': tokens.Keyword,
'FORWARD': tokens.Keyword,
'FOUND': tokens.Keyword,
'FREE': tokens.Keyword,
'FREEZE': tokens.Keyword,
'FULL': tokens.Keyword,
'FUNCTION': tokens.Keyword,
# 'G': tokens.Keyword,
'GENERAL': tokens.Keyword,
'GENERATED': tokens.Keyword,
'GET': tokens.Keyword,
'GLOBAL': tokens.Keyword,
'GO': tokens.Keyword,
'GOTO': tokens.Keyword,
'GRANT': tokens.Keyword,
'GRANTED': tokens.Keyword,
'GROUPING': tokens.Keyword,
'HAVING': tokens.Keyword,
'HIERARCHY': tokens.Keyword,
'HOLD': tokens.Keyword,
'HOUR': tokens.Keyword,
'HOST': tokens.Keyword,
'IDENTIFIED': tokens.Keyword,
'IDENTITY': tokens.Keyword,
'IGNORE': tokens.Keyword,
'ILIKE': tokens.Keyword,
'IMMEDIATE': tokens.Keyword,
'IMMUTABLE': tokens.Keyword,
'IMPLEMENTATION': tokens.Keyword,
'IMPLICIT': tokens.Keyword,
'INCLUDING': tokens.Keyword,
'INCREMENT': tokens.Keyword,
'INDEX': tokens.Keyword,
'INDITCATOR': tokens.Keyword,
'INFIX': tokens.Keyword,
'INHERITS': tokens.Keyword,
'INITIAL': tokens.Keyword,
'INITIALIZE': tokens.Keyword,
'INITIALLY': tokens.Keyword,
'INOUT': tokens.Keyword,
'INPUT': tokens.Keyword,
'INSENSITIVE': tokens.Keyword,
'INSTANTIABLE': tokens.Keyword,
'INSTEAD': tokens.Keyword,
'INTERSECT': tokens.Keyword,
'INTO': tokens.Keyword,
'INVOKER': tokens.Keyword,
'IS': tokens.Keyword,
'ISNULL': tokens.Keyword,
'ISOLATION': tokens.Keyword,
'ITERATE': tokens.Keyword,
# 'K': tokens.Keyword,
'KEY': tokens.Keyword,
'KEY_MEMBER': tokens.Keyword,
'KEY_TYPE': tokens.Keyword,
'LANCOMPILER': tokens.Keyword,
'LANGUAGE': tokens.Keyword,
'LARGE': tokens.Keyword,
'LAST': tokens.Keyword,
'LATERAL': tokens.Keyword,
'LEADING': tokens.Keyword,
'LENGTH': tokens.Keyword,
'LESS': tokens.Keyword,
'LEVEL': tokens.Keyword,
'LIMIT': tokens.Keyword,
'LISTEN': tokens.Keyword,
'LOAD': tokens.Keyword,
'LOCAL': tokens.Keyword,
'LOCALTIME': tokens.Keyword,
'LOCALTIMESTAMP': tokens.Keyword,
'LOCATION': tokens.Keyword,
'LOCATOR': tokens.Keyword,
'LOCK': tokens.Keyword,
'LOWER': tokens.Keyword,
# 'M': tokens.Keyword,
'MAP': tokens.Keyword,
'MATCH': tokens.Keyword,
'MAXEXTENTS': tokens.Keyword,
'MAXVALUE': tokens.Keyword,
'MESSAGE_LENGTH': tokens.Keyword,
'MESSAGE_OCTET_LENGTH': tokens.Keyword,
'MESSAGE_TEXT': tokens.Keyword,
'METHOD': tokens.Keyword,
'MINUTE': tokens.Keyword,
'MINUS': tokens.Keyword,
'MINVALUE': tokens.Keyword,
'MOD': tokens.Keyword,
'MODE': tokens.Keyword,
'MODIFIES': tokens.Keyword,
'MODIFY': tokens.Keyword,
'MONTH': tokens.Keyword,
'MORE': tokens.Keyword,
'MOVE': tokens.Keyword,
'MUMPS': tokens.Keyword,
'NAMES': tokens.Keyword,
'NATIONAL': tokens.Keyword,
'NATURAL': tokens.Keyword,
'NCHAR': tokens.Keyword,
'NCLOB': tokens.Keyword,
'NEW': tokens.Keyword,
'NEXT': tokens.Keyword,
'NO': tokens.Keyword,
'NOAUDIT': tokens.Keyword,
'NOCOMPRESS': tokens.Keyword,
'NOCREATEDB': tokens.Keyword,
'NOCREATEUSER': tokens.Keyword,
'NONE': tokens.Keyword,
'NOT': tokens.Keyword,
'NOTFOUND': tokens.Keyword,
'NOTHING': tokens.Keyword,
'NOTIFY': tokens.Keyword,
'NOTNULL': tokens.Keyword,
'NOWAIT': tokens.Keyword,
'NULL': tokens.Keyword,
'NULLABLE': tokens.Keyword,
'NULLIF': tokens.Keyword,
'OBJECT': tokens.Keyword,
'OCTET_LENGTH': tokens.Keyword,
'OF': tokens.Keyword,
'OFF': tokens.Keyword,
'OFFLINE': tokens.Keyword,
'OFFSET': tokens.Keyword,
'OIDS': tokens.Keyword,
'OLD': tokens.Keyword,
'ONLINE': tokens.Keyword,
'ONLY': tokens.Keyword,
'OPEN': tokens.Keyword,
'OPERATION': tokens.Keyword,
'OPERATOR': tokens.Keyword,
'OPTION': tokens.Keyword,
'OPTIONS': tokens.Keyword,
'ORDINALITY': tokens.Keyword,
'OUT': tokens.Keyword,
'OUTPUT': tokens.Keyword,
'OVERLAPS': tokens.Keyword,
'OVERLAY': tokens.Keyword,
'OVERRIDING': tokens.Keyword,
'OWNER': tokens.Keyword,
'QUARTER': tokens.Keyword,
'PAD': tokens.Keyword,
'PARAMETER': tokens.Keyword,
'PARAMETERS': tokens.Keyword,
'PARAMETER_MODE': tokens.Keyword,
'PARAMETER_NAME': tokens.Keyword,
'PARAMETER_ORDINAL_POSITION': tokens.Keyword,
'PARAMETER_SPECIFIC_CATALOG': tokens.Keyword,
'PARAMETER_SPECIFIC_NAME': tokens.Keyword,
'PARAMETER_SPECIFIC_SCHEMA': tokens.Keyword,
'PARTIAL': tokens.Keyword,
'PASCAL': tokens.Keyword,
'PCTFREE': tokens.Keyword,
'PENDANT': tokens.Keyword,
'PLACING': tokens.Keyword,
'PLI': tokens.Keyword,
'POSITION': tokens.Keyword,
'POSTFIX': tokens.Keyword,
'PRECISION': tokens.Keyword,
'PREFIX': tokens.Keyword,
'PREORDER': tokens.Keyword,
'PREPARE': tokens.Keyword,
'PRESERVE': tokens.Keyword,
'PRIMARY': tokens.Keyword,
'PRIOR': tokens.Keyword,
'PRIVILEGES': tokens.Keyword,
'PROCEDURAL': tokens.Keyword,
'PROCEDURE': tokens.Keyword,
'PUBLIC': tokens.Keyword,
'RAISE': tokens.Keyword,
'RAW': tokens.Keyword,
'READ': tokens.Keyword,
'READS': tokens.Keyword,
'RECHECK': tokens.Keyword,
'RECURSIVE': tokens.Keyword,
'REF': tokens.Keyword,
'REFERENCES': tokens.Keyword,
'REFERENCING': tokens.Keyword,
'REINDEX': tokens.Keyword,
'RELATIVE': tokens.Keyword,
'RENAME': tokens.Keyword,
'REPEATABLE': tokens.Keyword,
'RESET': tokens.Keyword,
'RESOURCE': tokens.Keyword,
'RESTART': tokens.Keyword,
'RESTRICT': tokens.Keyword,
'RESULT': tokens.Keyword,
'RETURN': tokens.Keyword,
'RETURNED_LENGTH': tokens.Keyword,
'RETURNED_OCTET_LENGTH': tokens.Keyword,
'RETURNED_SQLSTATE': tokens.Keyword,
'RETURNING': tokens.Keyword,
'RETURNS': tokens.Keyword,
'REVOKE': tokens.Keyword,
'RIGHT': tokens.Keyword,
'ROLE': tokens.Keyword,
'ROLLBACK': tokens.Keyword.DML,
'ROLLUP': tokens.Keyword,
'ROUTINE': tokens.Keyword,
'ROUTINE_CATALOG': tokens.Keyword,
'ROUTINE_NAME': tokens.Keyword,
'ROUTINE_SCHEMA': tokens.Keyword,
'ROW': tokens.Keyword,
'ROWS': tokens.Keyword,
'ROW_COUNT': tokens.Keyword,
'RULE': tokens.Keyword,
'SAVE_POINT': tokens.Keyword,
'SCALE': tokens.Keyword,
'SCHEMA': tokens.Keyword,
'SCHEMA_NAME': tokens.Keyword,
'SCOPE': tokens.Keyword,
'SCROLL': tokens.Keyword,
'SEARCH': tokens.Keyword,
'SECOND': tokens.Keyword,
'SECURITY': tokens.Keyword,
'SELF': tokens.Keyword,
'SENSITIVE': tokens.Keyword,
'SEQUENCE': tokens.Keyword,
'SERIALIZABLE': tokens.Keyword,
'SERVER_NAME': tokens.Keyword,
'SESSION': tokens.Keyword,
'SESSION_USER': tokens.Keyword,
'SETOF': tokens.Keyword,
'SETS': tokens.Keyword,
'SHARE': tokens.Keyword,
'SHOW': tokens.Keyword,
'SIMILAR': tokens.Keyword,
'SIMPLE': tokens.Keyword,
'SIZE': tokens.Keyword,
'SOME': tokens.Keyword,
'SOURCE': tokens.Keyword,
'SPACE': tokens.Keyword,
'SPECIFIC': tokens.Keyword,
'SPECIFICTYPE': tokens.Keyword,
'SPECIFIC_NAME': tokens.Keyword,
'SQL': tokens.Keyword,
'SQLBUF': tokens.Keyword,
'SQLCODE': tokens.Keyword,
'SQLERROR': tokens.Keyword,
'SQLEXCEPTION': tokens.Keyword,
'SQLSTATE': tokens.Keyword,
'SQLWARNING': tokens.Keyword,
'STABLE': tokens.Keyword,
'START': tokens.Keyword.DML,
# 'STATE': tokens.Keyword,
'STATEMENT': tokens.Keyword,
'STATIC': tokens.Keyword,
'STATISTICS': tokens.Keyword,
'STDIN': tokens.Keyword,
'STDOUT': tokens.Keyword,
'STORAGE': tokens.Keyword,
'STRICT': tokens.Keyword,
'STRUCTURE': tokens.Keyword,
'STYPE': tokens.Keyword,
'SUBCLASS_ORIGIN': tokens.Keyword,
'SUBLIST': tokens.Keyword,
'SUBSTRING': tokens.Keyword,
'SUCCESSFUL': tokens.Keyword,
'SUM': tokens.Keyword,
'SYMMETRIC': tokens.Keyword,
'SYNONYM': tokens.Keyword,
'SYSID': tokens.Keyword,
'SYSTEM': tokens.Keyword,
'SYSTEM_USER': tokens.Keyword,
'TABLE': tokens.Keyword,
'TABLE_NAME': tokens.Keyword,
'TEMP': tokens.Keyword,
'TEMPLATE': tokens.Keyword,
'TEMPORARY': tokens.Keyword,
'TERMINATE': tokens.Keyword,
'THAN': tokens.Keyword,
'TIMESTAMP': tokens.Keyword,
'TIMEZONE_HOUR': tokens.Keyword,
'TIMEZONE_MINUTE': tokens.Keyword,
'TO': tokens.Keyword,
'TOAST': tokens.Keyword,
'TRAILING': tokens.Keyword,
'TRANSATION': tokens.Keyword,
'TRANSACTIONS_COMMITTED': tokens.Keyword,
'TRANSACTIONS_ROLLED_BACK': tokens.Keyword,
'TRANSATION_ACTIVE': tokens.Keyword,
'TRANSFORM': tokens.Keyword,
'TRANSFORMS': tokens.Keyword,
'TRANSLATE': tokens.Keyword,
'TRANSLATION': tokens.Keyword,
'TREAT': tokens.Keyword,
'TRIGGER': tokens.Keyword,
'TRIGGER_CATALOG': tokens.Keyword,
'TRIGGER_NAME': tokens.Keyword,
'TRIGGER_SCHEMA': tokens.Keyword,
'TRIM': tokens.Keyword,
'TRUE': tokens.Keyword,
'TRUNCATE': tokens.Keyword,
'TRUSTED': tokens.Keyword,
'TYPE': tokens.Keyword,
'UID': tokens.Keyword,
'UNCOMMITTED': tokens.Keyword,
'UNDER': tokens.Keyword,
'UNENCRYPTED': tokens.Keyword,
'UNION': tokens.Keyword,
'UNIQUE': tokens.Keyword,
'UNKNOWN': tokens.Keyword,
'UNLISTEN': tokens.Keyword,
'UNNAMED': tokens.Keyword,
'UNNEST': tokens.Keyword,
'UNTIL': tokens.Keyword,
'UPPER': tokens.Keyword,
'USAGE': tokens.Keyword,
'USE': tokens.Keyword,
'USER': tokens.Keyword,
'USER_DEFINED_TYPE_CATALOG': tokens.Keyword,
'USER_DEFINED_TYPE_NAME': tokens.Keyword,
'USER_DEFINED_TYPE_SCHEMA': tokens.Keyword,
'USING': tokens.Keyword,
'VACUUM': tokens.Keyword,
'VALID': tokens.Keyword,
'VALIDATE': tokens.Keyword,
'VALIDATOR': tokens.Keyword,
'VALUES': tokens.Keyword,
'VARIABLE': tokens.Keyword,
'VERBOSE': tokens.Keyword,
'VERSION': tokens.Keyword,
'VIEW': tokens.Keyword,
'VOLATILE': tokens.Keyword,
'WEEK': tokens.Keyword,
'WHENEVER': tokens.Keyword,
'WITH': tokens.Keyword.CTE,
'WITHOUT': tokens.Keyword,
'WORK': tokens.Keyword,
'WRITE': tokens.Keyword,
'YEAR': tokens.Keyword,
'ZONE': tokens.Keyword,
# Name.Builtin
'ARRAY': tokens.Name.Builtin,
'BIGINT': tokens.Name.Builtin,
'BINARY': tokens.Name.Builtin,
'BIT': tokens.Name.Builtin,
'BLOB': tokens.Name.Builtin,
'BOOLEAN': tokens.Name.Builtin,
'CHAR': tokens.Name.Builtin,
'CHARACTER': tokens.Name.Builtin,
'DATE': tokens.Name.Builtin,
'DEC': tokens.Name.Builtin,
'DECIMAL': tokens.Name.Builtin,
'FILE_TYPE': tokens.Name.Builtin,
'FLOAT': tokens.Name.Builtin,
'INT': tokens.Name.Builtin,
'INT8': tokens.Name.Builtin,
'INTEGER': tokens.Name.Builtin,
'INTERVAL': tokens.Name.Builtin,
'LONG': tokens.Name.Builtin,
'NATURALN': tokens.Name.Builtin,
'NVARCHAR': tokens.Name.Builtin,
'NUMBER': tokens.Name.Builtin,
'NUMERIC': tokens.Name.Builtin,
'PLS_INTEGER': tokens.Name.Builtin,
'POSITIVE': tokens.Name.Builtin,
'POSITIVEN': tokens.Name.Builtin,
'REAL': tokens.Name.Builtin,
'ROWID': tokens.Name.Builtin,
'ROWLABEL': tokens.Name.Builtin,
'ROWNUM': tokens.Name.Builtin,
'SERIAL': tokens.Name.Builtin,
'SERIAL8': tokens.Name.Builtin,
'SIGNED': tokens.Name.Builtin,
'SIGNTYPE': tokens.Name.Builtin,
'SIMPLE_DOUBLE': tokens.Name.Builtin,
'SIMPLE_FLOAT': tokens.Name.Builtin,
'SIMPLE_INTEGER': tokens.Name.Builtin,
'SMALLINT': tokens.Name.Builtin,
'SYS_REFCURSOR': tokens.Name.Builtin,
'SYSDATE': tokens.Name,
'TEXT': tokens.Name.Builtin,
'TINYINT': tokens.Name.Builtin,
'UNSIGNED': tokens.Name.Builtin,
'UROWID': tokens.Name.Builtin,
'UTL_FILE': tokens.Name.Builtin,
'VARCHAR': tokens.Name.Builtin,
'VARCHAR2': tokens.Name.Builtin,
'VARYING': tokens.Name.Builtin,
}
KEYWORDS_COMMON = {
'SELECT': tokens.Keyword.DML,
'INSERT': tokens.Keyword.DML,
'DELETE': tokens.Keyword.DML,
'UPDATE': tokens.Keyword.DML,
'UPSERT': tokens.Keyword.DML,
'REPLACE': tokens.Keyword.DML,
'MERGE': tokens.Keyword.DML,
'DROP': tokens.Keyword.DDL,
'CREATE': tokens.Keyword.DDL,
'ALTER': tokens.Keyword.DDL,
'WHERE': tokens.Keyword,
'FROM': tokens.Keyword,
'INNER': tokens.Keyword,
'JOIN': tokens.Keyword,
'STRAIGHT_JOIN': tokens.Keyword,
'AND': tokens.Keyword,
'OR': tokens.Keyword,
'LIKE': tokens.Keyword,
'ON': tokens.Keyword,
'IN': tokens.Keyword,
'SET': tokens.Keyword,
'BY': tokens.Keyword,
'GROUP': tokens.Keyword,
'ORDER': tokens.Keyword,
'LEFT': tokens.Keyword,
'OUTER': tokens.Keyword,
'FULL': tokens.Keyword,
'IF': tokens.Keyword,
'END': tokens.Keyword,
'THEN': tokens.Keyword,
'LOOP': tokens.Keyword,
'AS': tokens.Keyword,
'ELSE': tokens.Keyword,
'FOR': tokens.Keyword,
'WHILE': tokens.Keyword,
'CASE': tokens.Keyword,
'WHEN': tokens.Keyword,
'MIN': tokens.Keyword,
'MAX': tokens.Keyword,
'DISTINCT': tokens.Keyword,
}
# oracle 关键字
KEYWORDS_ORACLE = {
'ARCHIVE': tokens.Keyword,
'ARCHIVELOG': tokens.Keyword,
'BACKUP': tokens.Keyword,
'BECOME': tokens.Keyword,
'BLOCK': tokens.Keyword,
'BODY': tokens.Keyword,
'CANCEL': tokens.Keyword,
'CHANGE': tokens.Keyword,
'COMPILE': tokens.Keyword,
'CONTENTS': tokens.Keyword,
'CONTROLFILE': tokens.Keyword,
'DATAFILE': tokens.Keyword,
'DBA': tokens.Keyword,
'DISMOUNT': tokens.Keyword,
'DOUBLE': tokens.Keyword,
'DUMP': tokens.Keyword,
'ELSIF': tokens.Keyword,
'EVENTS': tokens.Keyword,
'EXCEPTIONS': tokens.Keyword,
'EXPLAIN': tokens.Keyword,
'EXTENT': tokens.Keyword,
'EXTERNALLY': tokens.Keyword,
'FLUSH': tokens.Keyword,
'FREELIST': tokens.Keyword,
'FREELISTS': tokens.Keyword,
# groups seems too common as table name
# 'GROUPS': tokens.Keyword,
'INDICATOR': tokens.Keyword,
'INITRANS': tokens.Keyword,
'INSTANCE': tokens.Keyword,
'LAYER': tokens.Keyword,
'LINK': tokens.Keyword,
'LISTS': tokens.Keyword,
'LOGFILE': tokens.Keyword,
'MANAGE': tokens.Keyword,
'MANUAL': tokens.Keyword,
'MAXDATAFILES': tokens.Keyword,
'MAXINSTANCES': tokens.Keyword,
'MAXLOGFILES': tokens.Keyword,
'MAXLOGHISTORY': tokens.Keyword,
'MAXLOGMEMBERS': tokens.Keyword,
'MAXTRANS': tokens.Keyword,
'MINEXTENTS': tokens.Keyword,
'MODULE': tokens.Keyword,
'MOUNT': tokens.Keyword,
'NOARCHIVELOG': tokens.Keyword,
'NOCACHE': tokens.Keyword,
'NOCYCLE': tokens.Keyword,
'NOMAXVALUE': tokens.Keyword,
'NOMINVALUE': tokens.Keyword,
'NOORDER': tokens.Keyword,
'NORESETLOGS': tokens.Keyword,
'NORMAL': tokens.Keyword,
'NOSORT': tokens.Keyword,
'OPTIMAL': tokens.Keyword,
'OWN': tokens.Keyword,
'PACKAGE': tokens.Keyword,
'PARALLEL': tokens.Keyword,
'PCTINCREASE': tokens.Keyword,
'PCTUSED': tokens.Keyword,
'PLAN': tokens.Keyword,
'PRIVATE': tokens.Keyword,
'PROFILE': tokens.Keyword,
'QUOTA': tokens.Keyword,
'RECOVER': tokens.Keyword,
'RESETLOGS': tokens.Keyword,
'RESTRICTED': tokens.Keyword,
'REUSE': tokens.Keyword,
'ROLES': tokens.Keyword,
'SAVEPOINT': tokens.Keyword,
'SCN': tokens.Keyword,
'SECTION': tokens.Keyword,
'SEGMENT': tokens.Keyword,
'SHARED': tokens.Keyword,
'SNAPSHOT': tokens.Keyword,
'SORT': tokens.Keyword,
'STATEMENT_ID': tokens.Keyword,
'STOP': tokens.Keyword,
'SWITCH': tokens.Keyword,
'TABLES': tokens.Keyword,
'TABLESPACE': tokens.Keyword,
'THREAD': tokens.Keyword,
'TIME': tokens.Keyword,
'TRACING': tokens.Keyword,
'TRANSACTION': tokens.Keyword,
'TRIGGERS': tokens.Keyword,
'UNLIMITED': tokens.Keyword,
'UNLOCK': tokens.Keyword,
}
# PostgreSQL Syntax
KEYWORDS_PLPGSQL = {
'CONFLICT': tokens.Keyword,
'WINDOW': tokens.Keyword,
'PARTITION': tokens.Keyword,
'OVER': tokens.Keyword,
'PERFORM': tokens.Keyword,
'NOTICE': tokens.Keyword,
'PLPGSQL': tokens.Keyword,
'INHERIT': tokens.Keyword,
'INDEXES': tokens.Keyword,
'ON_ERROR_STOP': tokens.Keyword,
'BYTEA': tokens.Keyword,
'BIGSERIAL': tokens.Keyword,
'BIT VARYING': tokens.Keyword,
'BOX': tokens.Keyword,
'CHARACTER': tokens.Keyword,
'CHARACTER VARYING': tokens.Keyword,
'CIDR': tokens.Keyword,
'CIRCLE': tokens.Keyword,
'DOUBLE PRECISION': tokens.Keyword,
'INET': tokens.Keyword,
'JSON': tokens.Keyword,
'JSONB': tokens.Keyword,
'LINE': tokens.Keyword,
'LSEG': tokens.Keyword,
'MACADDR': tokens.Keyword,
'MONEY': tokens.Keyword,
'PATH': tokens.Keyword,
'PG_LSN': tokens.Keyword,
'POINT': tokens.Keyword,
'POLYGON': tokens.Keyword,
'SMALLSERIAL': tokens.Keyword,
'TSQUERY': tokens.Keyword,
'TSVECTOR': tokens.Keyword,
'TXID_SNAPSHOT': tokens.Keyword,
'UUID': tokens.Keyword,
'XML': tokens.Keyword,
'FOR': tokens.Keyword,
'IN': tokens.Keyword,
'LOOP': tokens.Keyword,
}
# Hive Syntax
# hive 语法
KEYWORDS_HQL = {
'EXPLODE': tokens.Keyword,
'DIRECTORY': tokens.Keyword,
'DISTRIBUTE': tokens.Keyword,
'INCLUDE': tokens.Keyword,
'LOCATE': tokens.Keyword,
'OVERWRITE': tokens.Keyword,
'POSEXPLODE': tokens.Keyword,
'ARRAY_CONTAINS': tokens.Keyword,
'CMP': tokens.Keyword,
'COLLECT_LIST': tokens.Keyword,
'CONCAT': tokens.Keyword,
'CONDITION': tokens.Keyword,
'DATE_ADD': tokens.Keyword,
'DATE_SUB': tokens.Keyword,
'DECODE': tokens.Keyword,
'DBMS_OUTPUT': tokens.Keyword,
'ELEMENTS': tokens.Keyword,
'EXCHANGE': tokens.Keyword,
'EXTENDED': tokens.Keyword,
'FLOOR': tokens.Keyword,
'FOLLOWING': tokens.Keyword,
'FROM_UNIXTIME': tokens.Keyword,
'FTP': tokens.Keyword,
'HOUR': tokens.Keyword,
'INLINE': tokens.Keyword,
'INSTR': tokens.Keyword,
'LEN': tokens.Keyword,
'MAXELEMENT': tokens.Keyword,
'MAXINDEX': tokens.Keyword,
'MAX_PART_DATE': tokens.Keyword,
'MAX_PART_INT': tokens.Keyword,
'MAX_PART_STRING': tokens.Keyword,
'MINELEMENT': tokens.Keyword,
'MININDEX': tokens.Keyword,
'MIN_PART_DATE': tokens.Keyword,
'MIN_PART_INT': tokens.Keyword,
'MIN_PART_STRING': tokens.Keyword,
'NOW': tokens.Keyword,
'NVL': tokens.Keyword,
'NVL2': tokens.Keyword,
'PARSE_URL_TUPLE': tokens.Keyword,
'PART_LOC': tokens.Keyword,
'PART_COUNT': tokens.Keyword,
'PART_COUNT_BY': tokens.Keyword,
'PRINT': tokens.Keyword,
'PUT_LINE': tokens.Keyword,
'RANGE': tokens.Keyword,
'REDUCE': tokens.Keyword,
'REGEXP_REPLACE': tokens.Keyword,
'RESIGNAL': tokens.Keyword,
'RTRIM': tokens.Keyword,
'SIGN': tokens.Keyword,
'SIGNAL': tokens.Keyword,
'SIN': tokens.Keyword,
'SPLIT': tokens.Keyword,
'SQRT': tokens.Keyword,
'STACK': tokens.Keyword,
'STR': tokens.Keyword,
'SUBSTR': tokens.Keyword,
'SUMMARY': tokens.Keyword,
'TBLPROPERTIES': tokens.Keyword,
'TIMESTAMP_ISO': tokens.Keyword,
'TO_CHAR': tokens.Keyword,
'TO_DATE': tokens.Keyword,
'TO_TIMESTAMP': tokens.Keyword,
'TRUNC': tokens.Keyword,
'UNBOUNDED': tokens.Keyword,
'UNIQUEJOIN': tokens.Keyword,
'UNIX_TIMESTAMP': tokens.Keyword,
'UTC_TIMESTAMP': tokens.Keyword,
'VIEWS': tokens.Keyword,
'EXIT': tokens.Keyword,
'BREAK': tokens.Keyword,
'LEAVE': tokens.Keyword,
}
| true | true |
f7fe5f5f307063ef2a363000c8b682531216c607 | 1,618 | py | Python | dataset/SamplingDataSetRnet.py | swpucwf/MTCNN_Pytorch | d9ffd1ca8ea28eb4f7cd1e5d24d2ec8402f0e0b0 | [
"Apache-2.0"
] | null | null | null | dataset/SamplingDataSetRnet.py | swpucwf/MTCNN_Pytorch | d9ffd1ca8ea28eb4f7cd1e5d24d2ec8402f0e0b0 | [
"Apache-2.0"
] | null | null | null | dataset/SamplingDataSetRnet.py | swpucwf/MTCNN_Pytorch | d9ffd1ca8ea28eb4f7cd1e5d24d2ec8402f0e0b0 | [
"Apache-2.0"
] | null | null | null | import torch
from torch.utils.data import Dataset
import os
from torchvision.transforms import transforms
from PIL import Image
class FaceDataset(Dataset):
def __init__(self,path_1=r"D:\DataSet",path_2="D:\DataSet\wider",size=24,tf=transforms.ToTensor()):
super(FaceDataset, self).__init__()
self.dataset = []
self.size = size
for path in [path_2,path_1]:
self.base_path_1 = path
self.path = os.path.join(self.base_path_1,str(self.size))
for txt in ["positive.txt","negative.txt","part.txt"]:
with open(os.path.join(self.path,txt),"r") as f:
data = f.readlines()
for line in data:
line = line.strip().split()
img_path = os.path.join(self.path,line[0])
benkdata = " ".join(line[1:])
self.dataset.append([img_path,benkdata])
self.tf = tf
def __len__(self):
return len(self.dataset) # 数据集长度
def __getitem__(self, index): # 获取数据
img_path,strs = self.dataset[index]
strs = strs.strip().split(" ") # 取一条数据，去掉前后字符串，再按空格分割
#标签：置信度+偏移量
cond = torch.Tensor([int(strs[0])]) # []莫丢，否则指定的是shape
offset = torch.Tensor([float(strs[1]),float(strs[2]),float(strs[3]),float(strs[4])])
#
# #样本：img_data
# print(img_path)
img = Image.open(img_path)
img = self.tf(img)
return img,cond,offset
# 测试
if __name__ == '__main__':
dataset = FaceDataset(size=12)
print(dataset[0][0].shape)
print(dataset[0][0]) | 32.36 | 103 | 0.573548 | import torch
from torch.utils.data import Dataset
import os
from torchvision.transforms import transforms
from PIL import Image
class FaceDataset(Dataset):
def __init__(self,path_1=r"D:\DataSet",path_2="D:\DataSet\wider",size=24,tf=transforms.ToTensor()):
super(FaceDataset, self).__init__()
self.dataset = []
self.size = size
for path in [path_2,path_1]:
self.base_path_1 = path
self.path = os.path.join(self.base_path_1,str(self.size))
for txt in ["positive.txt","negative.txt","part.txt"]:
with open(os.path.join(self.path,txt),"r") as f:
data = f.readlines()
for line in data:
line = line.strip().split()
img_path = os.path.join(self.path,line[0])
benkdata = " ".join(line[1:])
self.dataset.append([img_path,benkdata])
self.tf = tf
def __len__(self):
return len(self.dataset)
def __getitem__(self, index):
img_path,strs = self.dataset[index]
strs = strs.strip().split(" ")
cond = torch.Tensor([int(strs[0])])
offset = torch.Tensor([float(strs[1]),float(strs[2]),float(strs[3]),float(strs[4])])
img = Image.open(img_path)
img = self.tf(img)
return img,cond,offset
if __name__ == '__main__':
dataset = FaceDataset(size=12)
print(dataset[0][0].shape)
print(dataset[0][0]) | true | true |
f7fe5f7ea5da7a1c2f0d7e15ad992c72ffe12b0f | 177 | py | Python | scripts/add_path.py | XueLianjie/rpg_trajectory_evaluation | 7f49501d0fa09b5fa3790635ce68653ad8420d93 | [
"MIT"
] | 636 | 2018-10-03T10:37:54.000Z | 2022-03-29T12:36:11.000Z | scripts/add_path.py | XueLianjie/rpg_trajectory_evaluation | 7f49501d0fa09b5fa3790635ce68653ad8420d93 | [
"MIT"
] | 32 | 2018-10-12T07:43:39.000Z | 2022-03-18T09:46:56.000Z | scripts/add_path.py | XueLianjie/rpg_trajectory_evaluation | 7f49501d0fa09b5fa3790635ce68653ad8420d93 | [
"MIT"
] | 275 | 2018-10-06T12:48:46.000Z | 2022-03-14T07:52:48.000Z | #!/usr/bin/env python2
import os
import sys
sys.path.append(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
'../src/rpg_trajectory_evaluation'))
| 22.125 | 60 | 0.666667 |
import os
import sys
sys.path.append(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
'../src/rpg_trajectory_evaluation'))
| true | true |
f7fe5fa93f5b08ad07637ef68787f5ddcda596d8 | 4,428 | py | Python | examples/adwords/v201409/campaign_management/add_keywords_in_bulk.py | dietrichc/streamline-ppc-reports | 256f79246aba3c2cf8f792d87a066391a2f471e0 | [
"Apache-2.0"
] | null | null | null | examples/adwords/v201409/campaign_management/add_keywords_in_bulk.py | dietrichc/streamline-ppc-reports | 256f79246aba3c2cf8f792d87a066391a2f471e0 | [
"Apache-2.0"
] | null | null | null | examples/adwords/v201409/campaign_management/add_keywords_in_bulk.py | dietrichc/streamline-ppc-reports | 256f79246aba3c2cf8f792d87a066391a2f471e0 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python
#
# Copyright 2014 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""This code sample illustrates how to perform asynchronous requests.
The LoadFromStorage method is pulling credentials and properties from a
"googleads.yaml" file. By default, it looks for this file in your home
directory. For more information, see the "Caching authentication information"
section of our README.
Tags: MutateJobService.mutate
Tags: MutateJobService.get
Tags: MutateJobService.getResult
Api: AdWordsOnly
"""
__author__ = ('api.kwinter@gmail.com (Kevin Winter)'
'Joseph DiLallo')
import random
import re
import time
from googleads import adwords
from googleads import errors
RETRY_INTERVAL = 10
RETRIES_COUNT = 30
KEYWORD_NUMBER = 100
INDEX_REGEX = r'operations\[(\d+)\].operand'
AD_GROUP_ID = 'INSERT_AD_GROUP_ID_HERE'
def main(client, ad_group_id):
# Initialize appropriate service.
mutate_job_service = client.GetService('MutateJobService', version='v201409')
# Create list of all operations for the job.
operations = []
# Create AdGroupCriterionOperations to add keywords.
for i in range(KEYWORD_NUMBER):
keyword = 'mars%d' % i
if random.randint(1, 10) == 1:
keyword += '!!!'
operations.append({
'xsi_type': 'AdGroupCriterionOperation',
'operator': 'ADD',
'operand': {
'xsi_type': 'BiddableAdGroupCriterion',
'adGroupId': ad_group_id,
'criterion': {
'xsi_type': 'Keyword',
'matchType': 'BROAD',
'text': keyword
}
}
})
# You can specify up to 3 job IDs that must successfully complete before
# this job can be processed.
policy = {
'prerequisiteJobIds': []
}
# Call mutate to create a new job.
response = mutate_job_service.mutate(operations, policy)
if not response:
raise errors.GoogleAdsError('Failed to submit a job; aborting.')
job_id = response['id']
print 'Job with ID %s was successfully created.' % job_id
# Create selector to retrieve job status and wait for it to complete.
selector = {
'xsi_type': 'BulkMutateJobSelector',
'jobIds': [job_id]
}
time.sleep(RETRY_INTERVAL)
# Poll for job status until it's finished.
print 'Retrieving job status...'
for i in range(RETRIES_COUNT):
job_status_response = mutate_job_service.get(selector)
status = job_status_response[0]['status']
if status in ('COMPLETED', 'FAILED'):
break
print ('[%d] Current status is \'%s\', waiting %d seconds to retry...' %
(i, status, RETRY_INTERVAL))
time.sleep(RETRY_INTERVAL)
if status == 'FAILED':
raise errors.GoogleAdsError('Job failed with reason: \'%s\'' %
job_status_response[0]['failure_reason'])
if status in ('PROCESSING', 'PENDING'):
raise errors.GoogleAdsError('Job did not complete within %d seconds' %
(RETRY_INTERVAL * (RETRIES_COUNT - 1)))
# Status must be COMPLETED.
# Get the job result. Here we re-use the same selector.
result_response = mutate_job_service.getResult(selector)
# Output results.
index = 0
for result in result_response['SimpleMutateResult']['results']:
if 'PlaceHolder' in result:
print 'Operation [%d] - FAILED' % index
else:
print 'Operation [%d] - SUCCEEDED' % index
index += 1
# Output errors
for error in result_response['SimpleMutateResult']['errors']:
index = int(re.search(INDEX_REGEX, error['fieldPath']).group(1))
reason = error['reason']
keyword = operations[index]['operand']['criterion']['text']
print ('ERROR - keyword \'%s\' failed due to \'%s\'' %
(keyword, reason))
if __name__ == '__main__':
# Initialize client object.
adwords_client = adwords.AdWordsClient.LoadFromStorage()
main(adwords_client, AD_GROUP_ID)
| 31.183099 | 79 | 0.677733 |
"""This code sample illustrates how to perform asynchronous requests.
The LoadFromStorage method is pulling credentials and properties from a
"googleads.yaml" file. By default, it looks for this file in your home
directory. For more information, see the "Caching authentication information"
section of our README.
Tags: MutateJobService.mutate
Tags: MutateJobService.get
Tags: MutateJobService.getResult
Api: AdWordsOnly
"""
__author__ = ('api.kwinter@gmail.com (Kevin Winter)'
'Joseph DiLallo')
import random
import re
import time
from googleads import adwords
from googleads import errors
RETRY_INTERVAL = 10
RETRIES_COUNT = 30
KEYWORD_NUMBER = 100
INDEX_REGEX = r'operations\[(\d+)\].operand'
AD_GROUP_ID = 'INSERT_AD_GROUP_ID_HERE'
def main(client, ad_group_id):
mutate_job_service = client.GetService('MutateJobService', version='v201409')
operations = []
for i in range(KEYWORD_NUMBER):
keyword = 'mars%d' % i
if random.randint(1, 10) == 1:
keyword += '!!!'
operations.append({
'xsi_type': 'AdGroupCriterionOperation',
'operator': 'ADD',
'operand': {
'xsi_type': 'BiddableAdGroupCriterion',
'adGroupId': ad_group_id,
'criterion': {
'xsi_type': 'Keyword',
'matchType': 'BROAD',
'text': keyword
}
}
})
policy = {
'prerequisiteJobIds': []
}
response = mutate_job_service.mutate(operations, policy)
if not response:
raise errors.GoogleAdsError('Failed to submit a job; aborting.')
job_id = response['id']
print 'Job with ID %s was successfully created.' % job_id
selector = {
'xsi_type': 'BulkMutateJobSelector',
'jobIds': [job_id]
}
time.sleep(RETRY_INTERVAL)
print 'Retrieving job status...'
for i in range(RETRIES_COUNT):
job_status_response = mutate_job_service.get(selector)
status = job_status_response[0]['status']
if status in ('COMPLETED', 'FAILED'):
break
print ('[%d] Current status is \'%s\', waiting %d seconds to retry...' %
(i, status, RETRY_INTERVAL))
time.sleep(RETRY_INTERVAL)
if status == 'FAILED':
raise errors.GoogleAdsError('Job failed with reason: \'%s\'' %
job_status_response[0]['failure_reason'])
if status in ('PROCESSING', 'PENDING'):
raise errors.GoogleAdsError('Job did not complete within %d seconds' %
(RETRY_INTERVAL * (RETRIES_COUNT - 1)))
# Status must be COMPLETED.
# Get the job result. Here we re-use the same selector.
result_response = mutate_job_service.getResult(selector)
# Output results.
index = 0
for result in result_response['SimpleMutateResult']['results']:
if 'PlaceHolder' in result:
print 'Operation [%d] - FAILED' % index
else:
print 'Operation [%d] - SUCCEEDED' % index
index += 1
# Output errors
for error in result_response['SimpleMutateResult']['errors']:
index = int(re.search(INDEX_REGEX, error['fieldPath']).group(1))
reason = error['reason']
keyword = operations[index]['operand']['criterion']['text']
print ('ERROR - keyword \'%s\' failed due to \'%s\'' %
(keyword, reason))
if __name__ == '__main__':
# Initialize client object.
adwords_client = adwords.AdWordsClient.LoadFromStorage()
main(adwords_client, AD_GROUP_ID)
| false | true |
f7fe6045a0700d18c7c3dfbb20fa828b124aa0f5 | 7,677 | py | Python | salt/cli/batch.py | mattmb/salt | d02a718120cc202901437ef5ed8ec282c22178c3 | [
"Apache-2.0"
] | null | null | null | salt/cli/batch.py | mattmb/salt | d02a718120cc202901437ef5ed8ec282c22178c3 | [
"Apache-2.0"
] | null | null | null | salt/cli/batch.py | mattmb/salt | d02a718120cc202901437ef5ed8ec282c22178c3 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
'''
Execute batch runs
'''
# Import python libs
from __future__ import absolute_import, print_function
import math
import time
import copy
# Import salt libs
import salt.client
import salt.output
from salt.utils import print_cli
# Import 3rd-party libs
# pylint: disable=import-error,no-name-in-module,redefined-builtin
import salt.ext.six as six
from salt.ext.six.moves import range
# pylint: enable=import-error,no-name-in-module,redefined-builtin
class Batch(object):
'''
Manage the execution of batch runs
'''
def __init__(self, opts, eauth=None, quiet=False):
self.opts = opts
self.eauth = eauth if eauth else {}
self.quiet = quiet
self.local = salt.client.get_local_client(opts['conf_file'])
self.minions, self.ping_gen = self.__gather_minions()
def __gather_minions(self):
'''
Return a list of minions to use for the batch run
'''
args = [self.opts['tgt'],
'test.ping',
[],
self.opts['timeout'],
]
selected_target_option = self.opts.get('selected_target_option', None)
if selected_target_option is not None:
args.append(selected_target_option)
else:
args.append(self.opts.get('expr_form', 'glob'))
ping_gen = self.local.cmd_iter(*args, **self.eauth)
fret = set()
for ret in ping_gen:
m = next(six.iterkeys(ret))
if m is not None:
fret.add(m)
return (list(fret), ping_gen)
def get_bnum(self):
'''
Return the active number of minions to maintain
'''
partition = lambda x: float(x) / 100.0 * len(self.minions)
try:
if '%' in self.opts['batch']:
res = partition(float(self.opts['batch'].strip('%')))
if res < 1:
return int(math.ceil(res))
else:
return int(res)
else:
return int(self.opts['batch'])
except ValueError:
if not self.quiet:
print_cli('Invalid batch data sent: {0}\nData must be in the '
'form of %10, 10% or 3'.format(self.opts['batch']))
def run(self):
'''
Execute the batch run
'''
args = [[],
self.opts['fun'],
self.opts['arg'],
self.opts['timeout'],
'list',
]
bnum = self.get_bnum()
to_run = copy.deepcopy(self.minions)
active = []
ret = {}
iters = []
# the minion tracker keeps track of responses and iterators
# - it removes finished iterators from iters[]
# - if a previously detected minion does not respond, its
# added with an empty answer to ret{} once the timeout is reached
# - unresponsive minions are removed from active[] to make
# sure that the main while loop finishes even with unresp minions
minion_tracker = {}
# Iterate while we still have things to execute
while len(ret) < len(self.minions):
next_ = []
if len(to_run) <= bnum and not active:
# last bit of them, add them all to next iterator
while to_run:
next_.append(to_run.pop())
else:
for i in range(bnum - len(active)):
if to_run:
minion_id = to_run.pop()
if isinstance(minion_id, dict):
next_.append(minion_id.keys()[0])
else:
next_.append(minion_id)
active += next_
args[0] = next_
if next_:
if not self.quiet:
print_cli('\nExecuting run on {0}\n'.format(next_))
# create a new iterator for this batch of minions
new_iter = self.local.cmd_iter_no_block(
*args,
raw=self.opts.get('raw', False),
ret=self.opts.get('return', ''),
**self.eauth)
# add it to our iterators and to the minion_tracker
iters.append(new_iter)
minion_tracker[new_iter] = {}
# every iterator added is 'active' and has its set of minions
minion_tracker[new_iter]['minions'] = next_
minion_tracker[new_iter]['active'] = True
else:
time.sleep(0.02)
parts = {}
# see if we found more minions
for ping_ret in self.ping_gen:
if ping_ret is None:
break
m = next(ping_ret.iterkeys())
if m not in self.minions:
self.minions.append(m)
to_run.append(m)
for queue in iters:
try:
# Gather returns until we get to the bottom
ncnt = 0
while True:
part = next(queue)
if part is None:
time.sleep(0.01)
ncnt += 1
if ncnt > 5:
break
continue
if self.opts.get('raw'):
parts.update({part['id']: part})
else:
parts.update(part)
except StopIteration:
# if a iterator is done:
# - set it to inactive
# - add minions that have not responded to parts{}
# check if the tracker contains the iterator
if queue in minion_tracker:
minion_tracker[queue]['active'] = False
# add all minions that belong to this iterator and
# that have not responded to parts{} with an empty response
for minion in minion_tracker[queue]['minions']:
if minion not in parts:
parts[minion] = {}
parts[minion]['ret'] = {}
for minion, data in six.iteritems(parts):
active.remove(minion)
if self.opts.get('raw'):
yield data
else:
ret[minion] = data['ret']
yield {minion: data['ret']}
if not self.quiet:
ret[minion] = data['ret']
data[minion] = data.pop('ret')
if 'out' in data:
out = data.pop('out')
else:
out = None
salt.output.display_output(
data,
out,
self.opts)
# remove inactive iterators from the iters list
for queue in minion_tracker:
# only remove inactive queues
if not minion_tracker[queue]['active'] and queue in iters:
iters.remove(queue)
# also remove the iterator's minions from the active list
for minion in minion_tracker[queue]['minions']:
if minion in active:
active.remove(minion)
| 36.383886 | 83 | 0.470366 |
from __future__ import absolute_import, print_function
import math
import time
import copy
import salt.client
import salt.output
from salt.utils import print_cli
import salt.ext.six as six
from salt.ext.six.moves import range
class Batch(object):
def __init__(self, opts, eauth=None, quiet=False):
self.opts = opts
self.eauth = eauth if eauth else {}
self.quiet = quiet
self.local = salt.client.get_local_client(opts['conf_file'])
self.minions, self.ping_gen = self.__gather_minions()
def __gather_minions(self):
args = [self.opts['tgt'],
'test.ping',
[],
self.opts['timeout'],
]
selected_target_option = self.opts.get('selected_target_option', None)
if selected_target_option is not None:
args.append(selected_target_option)
else:
args.append(self.opts.get('expr_form', 'glob'))
ping_gen = self.local.cmd_iter(*args, **self.eauth)
fret = set()
for ret in ping_gen:
m = next(six.iterkeys(ret))
if m is not None:
fret.add(m)
return (list(fret), ping_gen)
def get_bnum(self):
partition = lambda x: float(x) / 100.0 * len(self.minions)
try:
if '%' in self.opts['batch']:
res = partition(float(self.opts['batch'].strip('%')))
if res < 1:
return int(math.ceil(res))
else:
return int(res)
else:
return int(self.opts['batch'])
except ValueError:
if not self.quiet:
print_cli('Invalid batch data sent: {0}\nData must be in the '
'form of %10, 10% or 3'.format(self.opts['batch']))
def run(self):
args = [[],
self.opts['fun'],
self.opts['arg'],
self.opts['timeout'],
'list',
]
bnum = self.get_bnum()
to_run = copy.deepcopy(self.minions)
active = []
ret = {}
iters = []
minion_tracker = {}
while len(ret) < len(self.minions):
next_ = []
if len(to_run) <= bnum and not active:
while to_run:
next_.append(to_run.pop())
else:
for i in range(bnum - len(active)):
if to_run:
minion_id = to_run.pop()
if isinstance(minion_id, dict):
next_.append(minion_id.keys()[0])
else:
next_.append(minion_id)
active += next_
args[0] = next_
if next_:
if not self.quiet:
print_cli('\nExecuting run on {0}\n'.format(next_))
new_iter = self.local.cmd_iter_no_block(
*args,
raw=self.opts.get('raw', False),
ret=self.opts.get('return', ''),
**self.eauth)
iters.append(new_iter)
minion_tracker[new_iter] = {}
minion_tracker[new_iter]['minions'] = next_
minion_tracker[new_iter]['active'] = True
else:
time.sleep(0.02)
parts = {}
for ping_ret in self.ping_gen:
if ping_ret is None:
break
m = next(ping_ret.iterkeys())
if m not in self.minions:
self.minions.append(m)
to_run.append(m)
for queue in iters:
try:
ncnt = 0
while True:
part = next(queue)
if part is None:
time.sleep(0.01)
ncnt += 1
if ncnt > 5:
break
continue
if self.opts.get('raw'):
parts.update({part['id']: part})
else:
parts.update(part)
except StopIteration:
if queue in minion_tracker:
minion_tracker[queue]['active'] = False
for minion in minion_tracker[queue]['minions']:
if minion not in parts:
parts[minion] = {}
parts[minion]['ret'] = {}
for minion, data in six.iteritems(parts):
active.remove(minion)
if self.opts.get('raw'):
yield data
else:
ret[minion] = data['ret']
yield {minion: data['ret']}
if not self.quiet:
ret[minion] = data['ret']
data[minion] = data.pop('ret')
if 'out' in data:
out = data.pop('out')
else:
out = None
salt.output.display_output(
data,
out,
self.opts)
for queue in minion_tracker:
if not minion_tracker[queue]['active'] and queue in iters:
iters.remove(queue)
for minion in minion_tracker[queue]['minions']:
if minion in active:
active.remove(minion)
| true | true |
f7fe62e9d80211104fecfb8d49bbab2d7c99e009 | 3,651 | py | Python | coderunner/myapp/tests.py | kelseylyn/CodeRunner | 4085515e46ca1b2dab42c9f91598acbd70b9227e | [
"MIT"
] | null | null | null | coderunner/myapp/tests.py | kelseylyn/CodeRunner | 4085515e46ca1b2dab42c9f91598acbd70b9227e | [
"MIT"
] | null | null | null | coderunner/myapp/tests.py | kelseylyn/CodeRunner | 4085515e46ca1b2dab42c9f91598acbd70b9227e | [
"MIT"
] | null | null | null | from django.test import TestCase
# myapp/tests.py
from channels.testing import ChannelsLiveServerTestCase
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.support.wait import WebDriverWait
class ChatTests(ChannelsLiveServerTestCase):
serve_static = True # emulate StaticLiveServerTestCase
@classmethod
def setUpClass(cls):
super().setUpClass()
try:
# NOTE: Requires "chromedriver" binary to be installed in $PATH
cls.driver = webdriver.Chrome()
except:
super().tearDownClass()
raise
@classmethod
def tearDownClass(cls):
cls.driver.quit()
super().tearDownClass()
def test_when_chat_message_posted_then_seen_by_everyone_in_same_room(self):
try:
self._enter_chat_room('room_1')
self._open_new_window()
self._enter_chat_room('room_1')
self._switch_to_window(0)
self._post_message('hello')
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 1 from window 1')
self._switch_to_window(1)
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 2 from window 1')
finally:
self._close_all_new_windows()
def test_when_chat_message_posted_then_not_seen_by_anyone_in_different_room(self):
try:
self._enter_chat_room('room_1')
self._open_new_window()
self._enter_chat_room('room_2')
self._switch_to_window(0)
self._post_message('hello')
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 1 from window 1')
self._switch_to_window(1)
self._post_message('world')
WebDriverWait(self.driver, 2).until(lambda _:
'world' in self._chat_log_value,
'Message was not received by window 2 from window 2')
self.assertTrue('hello' not in self._chat_log_value,
'Message was improperly received by window 2 from window 1')
finally:
self._close_all_new_windows()
# === Utility ===
def _enter_chat_room(self, room_name):
self.driver.get(self.live_server_url + '/chat/')
ActionChains(self.driver).send_keys(room_name + '\n').perform()
WebDriverWait(self.driver, 2).until(lambda _:
room_name in self.driver.current_url)
def _open_new_window(self):
self.driver.execute_script('window.open("about:blank", "_blank");')
self.driver.switch_to_window(self.driver.window_handles[-1])
def _close_all_new_windows(self):
while len(self.driver.window_handles) > 1:
self.driver.switch_to_window(self.driver.window_handles[-1])
self.driver.execute_script('window.close();')
if len(self.driver.window_handles) == 1:
self.driver.switch_to_window(self.driver.window_handles[0])
def _switch_to_window(self, window_index):
self.driver.switch_to_window(self.driver.window_handles[window_index])
def _post_message(self, message):
ActionChains(self.driver).send_keys(message + '\n').perform()
@property
def _chat_log_value(self):
return self.driver.find_element_by_css_selector('#chat-log').get_property('value')# Create your tests here.
| 38.03125 | 115 | 0.650781 | from django.test import TestCase
from channels.testing import ChannelsLiveServerTestCase
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.support.wait import WebDriverWait
class ChatTests(ChannelsLiveServerTestCase):
serve_static = True
@classmethod
def setUpClass(cls):
super().setUpClass()
try:
cls.driver = webdriver.Chrome()
except:
super().tearDownClass()
raise
@classmethod
def tearDownClass(cls):
cls.driver.quit()
super().tearDownClass()
def test_when_chat_message_posted_then_seen_by_everyone_in_same_room(self):
try:
self._enter_chat_room('room_1')
self._open_new_window()
self._enter_chat_room('room_1')
self._switch_to_window(0)
self._post_message('hello')
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 1 from window 1')
self._switch_to_window(1)
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 2 from window 1')
finally:
self._close_all_new_windows()
def test_when_chat_message_posted_then_not_seen_by_anyone_in_different_room(self):
try:
self._enter_chat_room('room_1')
self._open_new_window()
self._enter_chat_room('room_2')
self._switch_to_window(0)
self._post_message('hello')
WebDriverWait(self.driver, 2).until(lambda _:
'hello' in self._chat_log_value,
'Message was not received by window 1 from window 1')
self._switch_to_window(1)
self._post_message('world')
WebDriverWait(self.driver, 2).until(lambda _:
'world' in self._chat_log_value,
'Message was not received by window 2 from window 2')
self.assertTrue('hello' not in self._chat_log_value,
'Message was improperly received by window 2 from window 1')
finally:
self._close_all_new_windows()
def _enter_chat_room(self, room_name):
self.driver.get(self.live_server_url + '/chat/')
ActionChains(self.driver).send_keys(room_name + '\n').perform()
WebDriverWait(self.driver, 2).until(lambda _:
room_name in self.driver.current_url)
def _open_new_window(self):
self.driver.execute_script('window.open("about:blank", "_blank");')
self.driver.switch_to_window(self.driver.window_handles[-1])
def _close_all_new_windows(self):
while len(self.driver.window_handles) > 1:
self.driver.switch_to_window(self.driver.window_handles[-1])
self.driver.execute_script('window.close();')
if len(self.driver.window_handles) == 1:
self.driver.switch_to_window(self.driver.window_handles[0])
def _switch_to_window(self, window_index):
self.driver.switch_to_window(self.driver.window_handles[window_index])
def _post_message(self, message):
ActionChains(self.driver).send_keys(message + '\n').perform()
@property
def _chat_log_value(self):
return self.driver.find_element_by_css_selector('#chat-log').get_property('value')
| true | true |
f7fe64a6acb2e2a59e42278b437fcbb3e026050b | 746 | py | Python | LeetCodeSolutions/python/652_Find_Duplicate_Subtrees.py | ChuanleiGuo/AlgorithmsPlayground | 90b6287b742c8bfd3797540c408d679be2821a40 | [
"MIT"
] | 1 | 2017-03-27T13:38:37.000Z | 2017-03-27T13:38:37.000Z | LeetCodeSolutions/python/652_Find_Duplicate_Subtrees.py | ChuanleiGuo/AlgorithmsPlayground | 90b6287b742c8bfd3797540c408d679be2821a40 | [
"MIT"
] | null | null | null | LeetCodeSolutions/python/652_Find_Duplicate_Subtrees.py | ChuanleiGuo/AlgorithmsPlayground | 90b6287b742c8bfd3797540c408d679be2821a40 | [
"MIT"
] | null | null | null | class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def findDuplicateSubtrees(self, root):
"""
:type root: TreeNode
:rtype: List[TreeNode]
"""
res = []
self.subtree_serial(root, dict(), res)
return res
def subtree_serial(self, cur, hash_map, res):
if cur is None:
return '#'
serial = str(cur.val) + ',' + self.subtree_serial(cur.left, hash_map, res) + ',' + \
self.subtree_serial(cur.right, hash_map, res)
if hash_map.get(serial, 0) == 1:
res.append(cur)
hash_map[serial] = hash_map.get(serial, 0) + 1
return serial
| 27.62963 | 92 | 0.542895 | class TreeNode(object):
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def findDuplicateSubtrees(self, root):
res = []
self.subtree_serial(root, dict(), res)
return res
def subtree_serial(self, cur, hash_map, res):
if cur is None:
return '#'
serial = str(cur.val) + ',' + self.subtree_serial(cur.left, hash_map, res) + ',' + \
self.subtree_serial(cur.right, hash_map, res)
if hash_map.get(serial, 0) == 1:
res.append(cur)
hash_map[serial] = hash_map.get(serial, 0) + 1
return serial
| true | true |
f7fe655b6d6424d781be8957cb4989cf33dd3e62 | 934 | py | Python | lemur/plugins/bases/source.py | prdonahue/lemur | 267159af1950a77fa298275f234d7e458b91dda9 | [
"Apache-2.0"
] | null | null | null | lemur/plugins/bases/source.py | prdonahue/lemur | 267159af1950a77fa298275f234d7e458b91dda9 | [
"Apache-2.0"
] | 1 | 2022-03-29T22:05:53.000Z | 2022-03-29T22:05:53.000Z | lemur/plugins/bases/source.py | TinLe/lemur | dfb9e3a0c8f8f1f1bd908b1fcb8596af7c65f739 | [
"Apache-2.0"
] | null | null | null | """
.. module: lemur.plugins.bases.source
:platform: Unix
:copyright: (c) 2015 by Netflix Inc., see AUTHORS for more
:license: Apache, see LICENSE for more details.
.. moduleauthor:: Kevin Glisson <kglisson@netflix.com>
"""
from lemur.plugins.base import Plugin
class SourcePlugin(Plugin):
type = 'source'
default_options = [
{
'name': 'pollRate',
'type': 'int',
'required': False,
'helpMessage': 'Rate in seconds to poll source for new information.',
'default': '60',
}
]
def get_certificates(self, options, **kwargs):
raise NotImplementedError
def get_endpoints(self, options, **kwargs):
raise NotImplementedError
def clean(self, certificate, options, **kwargs):
raise NotImplementedError
@property
def options(self):
return self.default_options + self.additional_options
| 25.243243 | 81 | 0.624197 | from lemur.plugins.base import Plugin
class SourcePlugin(Plugin):
type = 'source'
default_options = [
{
'name': 'pollRate',
'type': 'int',
'required': False,
'helpMessage': 'Rate in seconds to poll source for new information.',
'default': '60',
}
]
def get_certificates(self, options, **kwargs):
raise NotImplementedError
def get_endpoints(self, options, **kwargs):
raise NotImplementedError
def clean(self, certificate, options, **kwargs):
raise NotImplementedError
@property
def options(self):
return self.default_options + self.additional_options
| true | true |
f7fe65a12de4eccfbbee75203b13bad6dff57dc2 | 27,558 | py | Python | tensorflow_probability/python/experimental/mcmc/gradient_based_trajectory_length_adaptation_test.py | jakee417/probability-1 | ae7117f37ac441bc7a888167ea23e5e620c5bcde | [
"Apache-2.0"
] | 3,670 | 2018-02-14T03:29:40.000Z | 2022-03-30T01:19:52.000Z | tensorflow_probability/python/experimental/mcmc/gradient_based_trajectory_length_adaptation_test.py | jakee417/probability-1 | ae7117f37ac441bc7a888167ea23e5e620c5bcde | [
"Apache-2.0"
] | 1,395 | 2018-02-24T02:28:49.000Z | 2022-03-31T16:12:06.000Z | tensorflow_probability/python/experimental/mcmc/gradient_based_trajectory_length_adaptation_test.py | jakee417/probability-1 | ae7117f37ac441bc7a888167ea23e5e620c5bcde | [
"Apache-2.0"
] | 1,135 | 2018-02-14T01:51:10.000Z | 2022-03-28T02:24:11.000Z | # Copyright 2020 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Tests for gradient_based_trajectory_length_adaptation."""
from absl.testing import parameterized
import numpy as np
import tensorflow.compat.v1 as tf1
import tensorflow.compat.v2 as tf
import tensorflow_probability as tfp
from tensorflow_probability.python.internal import distribute_lib
from tensorflow_probability.python.internal import distribute_test_lib
from tensorflow_probability.python.internal import samplers
from tensorflow_probability.python.internal import test_util
tfb = tfp.bijectors
tfd = tfp.distributions
JAX_MODE = False
def snaper_criterion_dummy_direction(previous_state, *args, **kwargs):
# Technically direction should be normalized, but omitting the normalization
# term only rescales the criterion so we're fine.
return tfp.experimental.mcmc.snaper_criterion(
previous_state,
*args,
direction=tf.nest.map_structure(tf.ones_like, previous_state),
**kwargs,
)
def snaper_criterion_2d_direction(previous_state, *args, **kwargs):
return tfp.experimental.mcmc.snaper_criterion(
previous_state,
*args,
direction=tf.constant([0., 1.], previous_state.dtype),
**kwargs,
)
@test_util.test_graph_and_eager_modes
class GradientBasedTrajectoryLengthAdaptationTestGeneric(
test_util.TestCase, parameterized.TestCase):
def testForbiddenTransformedKernel(self):
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2, step_size=0.1, num_leapfrog_steps=1)
kernel = tfp.mcmc.TransformedTransitionKernel(kernel, tfb.Identity())
with self.assertRaisesRegex(
ValueError,
'The inner kernel cannot contain a `TransformedTransitionKernel`'):
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100)
def testNestedStepSizeError(self):
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2,
step_size=[0.1],
num_leapfrog_steps=1)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100)
with self.assertRaisesRegex(ValueError, 'Step size must be a scalar'):
kernel.bootstrap_results([1.])
@parameterized.named_parameters(('StaticShape', True),
('DynamicShape', False))
def testNonScalarStepSizeError(self, use_static_shape):
step_size = tf1.placeholder_with_default(
[0.1, 0.2], shape=[2] if use_static_shape else None)
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2,
step_size=step_size,
num_leapfrog_steps=1)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100, validate_args=True)
with self.assertRaisesRegex(Exception, 'Step size must be a scalar'):
self.evaluate(kernel.bootstrap_results(tf.constant(1.)))
@parameterized.named_parameters(
('ChEESStaticShape', True, tfp.experimental.mcmc.chees_criterion),
('ChEESDynamicShape', False, tfp.experimental.mcmc.chees_criterion),
('SNAPERStaticShape', True, snaper_criterion_dummy_direction),
('SNAPERDynamicShape', False, snaper_criterion_dummy_direction),
)
def testTooFewChains(self, use_static_shape, criterion_fn):
state = tf1.placeholder_with_default(
[[0.1, 0.2]], shape=[1, 2] if use_static_shape else None)
accept_prob = tf1.placeholder_with_default(
[1.], shape=[1] if use_static_shape else None)
with self.assertRaisesRegex(Exception,
'chees_criterion requires at least 2 chains'):
self.evaluate(
tfp.experimental.mcmc.chees_criterion(
state, state, accept_prob, 1., validate_args=True))
@parameterized.named_parameters(
('ChEESStaticShape', True, tfp.experimental.mcmc.chees_criterion),
('ChEESDynamicShape', False, tfp.experimental.mcmc.chees_criterion),
('SNAPERStaticShape', True, snaper_criterion_dummy_direction),
('SNAPERDynamicShape', False, snaper_criterion_dummy_direction),
)
def testNoBatchDims(self, use_static_shape, criterion_fn):
state = tf1.placeholder_with_default(
[[0.1, 0.2]], shape=[1, 2] if use_static_shape else None)
accept_prob = tf1.placeholder_with_default(
1., shape=[] if use_static_shape else None)
with self.assertRaisesRegex(Exception, 'requires at least 2 chains'):
self.evaluate(
criterion_fn(state, state, accept_prob, 1., validate_args=True))
class _GradientBasedTrajectoryLengthAdaptationTest(test_util.TestCase):
def testDocstringExample(self):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.JointDistributionSequential([
tfd.Normal(0., tf.constant(20., dtype=self.dtype)),
tfd.HalfNormal(tf.constant(10., dtype=self.dtype)),
])
def target_log_prob_fn(*x):
return tf.cast(target.log_prob(x), self.dtype)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
kernel = tfp.mcmc.TransformedTransitionKernel(
kernel, [tfb.Identity(), tfb.Exp()])
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting for
# the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=[
tf.ones(num_chains, dtype=self.dtype),
tf.ones(num_chains, dtype=self.dtype)
],
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(0.52, mean_step_size, atol=0.2)
self.assertAllClose(46., mean_max_trajectory_length, atol=15)
self.assertAllClose(
target.mean(), [tf.reduce_mean(x, axis=[0, 1]) for x in chain],
atol=1.5)
self.assertAllClose(
target.variance(),
[tf.math.reduce_variance(x, axis=[0, 1]) for x in chain],
rtol=0.2)
def testStateMeanSNAPER(self):
state = np.array([[0.1, 0.2]], self.dtype)
accept_prob = np.ones([], self.dtype)
# This doesn't fail because state_mean is provided externally.
self.evaluate(tfp.experimental.mcmc.snaper_criterion(
state,
state,
accept_prob,
2.,
direction=tf.ones_like(state),
state_mean=state,
state_mean_weight=0.1,
))
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testScalarState(self, criterion_fn):
def target_log_prob_fn(x):
return -x**2 / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True)
state = tf.zeros([64], self.dtype)
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
# We expect it to move it a little bit.
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testTensorState(self, criterion_fn):
def target_log_prob_fn(x):
return -tf.reduce_mean(x**2, [-1, -2]) / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = (
tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True))
state = tf.zeros([64, 2, 3], self.dtype)
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
# We expect it to move it a little bit.
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testListState(self, criterion_fn):
def target_log_prob_fn(x, y):
return -x**2 / 2 - y**2 / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True)
state = [tf.zeros([64], self.dtype), tf.zeros([64], self.dtype)]
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
# We expect it to move it a little bit.
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_2d_direction),
)
def testAdaptation(self, criterion_fn):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.], self.dtype)), 1)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
criterion_fn=criterion_fn,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting for
# the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2], dtype=self.dtype),
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(1.5, mean_step_size, atol=0.2)
# Both SNAPER and ChEES-rate find roughly the same trajectory length for
# this target.
self.assertAllClose(15., mean_max_trajectory_length, rtol=0.3)
self.assertAllClose(
target.mean(), tf.reduce_mean(chain, axis=[0, 1]),
atol=1.)
self.assertAllClose(
target.variance(),
tf.math.reduce_variance(chain, axis=[0, 1]),
rtol=0.1)
def testPreconditionedHMC(self):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.], self.dtype)), 1)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.experimental.mcmc.PreconditionedHamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
momentum_distribution=tfd.Independent(
tfd.Normal(0., tf.constant([1., 1. / 10.], self.dtype)), 1),
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting for
# the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2], dtype=self.dtype),
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(1.2, mean_step_size, atol=0.2)
self.assertAllClose(1.5, mean_max_trajectory_length, rtol=0.25)
self.assertAllClose(
target.mean(), tf.reduce_mean(chain, axis=[0, 1]),
atol=0.3)
self.assertAllClose(
target.variance(),
tf.math.reduce_variance(chain, axis=[0, 1]),
rtol=0.1)
def testNumAdaptationSteps(self):
def target_log_prob_fn(x):
return -x**2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=1,
adaptation_rate=1.,
validate_args=True)
state = tf.zeros([64], self.dtype)
seed = test_util.test_seed(sampler_type='stateless')
step_0_kernel_results = kernel.bootstrap_results(state)
state, step_1_kernel_results = kernel.one_step(
state, step_0_kernel_results, seed=seed)
_, step_2_kernel_results = kernel.one_step(
state, step_1_kernel_results, seed=seed)
(step_0_kernel_results, step_1_kernel_results,
step_2_kernel_results) = self.evaluate([
step_0_kernel_results,
step_1_kernel_results,
step_2_kernel_results,
])
# The intention of num_adaptation_steps is that we should adapt for 1 step
# and then hold the hyperparameters constant.
self.assertGreater(
np.abs(step_0_kernel_results.max_trajectory_length -
step_1_kernel_results.max_trajectory_length), 0.005)
self.assertAllClose(step_1_kernel_results.max_trajectory_length,
step_2_kernel_results.max_trajectory_length)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testCriterionStateEquivalence(self, criterion_fn):
# Criteria should not care about the exact arrangement of state parts.
previous_state = np.random.randn(4, 6).astype(self.dtype)
new_state = np.random.randn(4, 6).astype(self.dtype)
accept_prob = np.random.uniform(size=(4,)).astype(self.dtype)
matrix_previous_state = previous_state.reshape([4, 3, 2])
matrix_new_state = new_state.reshape([4, 3, 2])
list_previous_state = [previous_state[:, :2], previous_state[:, 2:]]
list_new_state = [new_state[:, :2], new_state[:, 2:]]
criterion = criterion_fn(
previous_state, new_state, accept_prob, 1.)
matrix_criterion = criterion_fn(
matrix_previous_state, matrix_new_state, accept_prob, 1.)
list_criterion = criterion_fn(
list_previous_state, list_new_state, accept_prob, 1.)
self.assertAllEqual([4], criterion.shape)
self.assertAllClose(criterion, matrix_criterion)
self.assertAllClose(criterion, list_criterion)
class GradientBasedTrajectoryLengthAdaptationTestFloat32(
_GradientBasedTrajectoryLengthAdaptationTest):
dtype = np.float32
class GradientBasedTrajectoryLengthAdaptationTestFloat64(
_GradientBasedTrajectoryLengthAdaptationTest):
dtype = np.float64
@test_util.test_all_tf_execution_regimes
class DistributedGBTLATest(distribute_test_lib.DistributedTest):
def test_gbtla_kernel_tracks_axis_names(self):
inner_kernel = tfp.mcmc.HamiltonianMonteCarlo(tfd.Normal(0, 1).log_prob,
step_size=1.9,
num_leapfrog_steps=2)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1)
self.assertIsNone(kernel.experimental_shard_axis_names)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1, experimental_shard_axis_names=['a'])
self.assertListEqual(kernel.experimental_shard_axis_names, ['a'])
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1).experimental_with_shard_axes(['a'])
self.assertListEqual(kernel.experimental_shard_axis_names, ['a'])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def test_gbtla_kernel_computes_same_criterion_info_with_sharded_state(
self,
criterion_fn,
):
if not JAX_MODE:
self.skipTest('Test in TF runs into `merge_call` error: see b/178944108')
def target_log_prob(a, b):
return (
tfd.Normal(0., 1.).log_prob(a)
+ distribute_lib.psum(tfd.Normal(
distribute_lib.pbroadcast(a, 'foo'), 1.).log_prob(b), 'foo'))
kernel = tfp.mcmc.HamiltonianMonteCarlo(target_log_prob,
step_size=1e-2,
num_leapfrog_steps=2)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, 10, criterion_fn=criterion_fn)
sharded_kernel = kernel.experimental_with_shard_axes([None, ['foo']])
def run(seed):
init_seed, sample_seed = samplers.split_seed(seed)
state_seeds = samplers.split_seed(init_seed)
state = [
samplers.normal(seed=state_seeds[0], shape=[5]),
samplers.normal(seed=state_seeds[1], shape=[5])
]
kr = sharded_kernel.bootstrap_results(state)
_, kr = sharded_kernel.one_step(state, kr, seed=sample_seed)
return (
kr.criterion,
kr.averaged_sq_grad,
kr.averaged_max_trajectory_length
)
criterion, avg_sq_grad, avg_max_tl = self.evaluate(
self.per_replica_to_tensor(self.strategy_run(
run, args=(samplers.zeros_seed(),), in_axes=None, axis_name='foo'),
0))
for i in range(distribute_test_lib.NUM_DEVICES):
self.assertAllClose(criterion[0], criterion[i])
self.assertAllClose(avg_sq_grad[0], avg_sq_grad[i])
self.assertAllClose(avg_max_tl[0], avg_max_tl[i])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def test_gbtla_kernel_can_shard_chains_across_devices(self, criterion_fn):
def target_log_prob(a, b):
return (
tfd.Normal(0., 1.).log_prob(a)
+ tfd.Sample(tfd.Normal(a, 1.), 4).log_prob(b))
kernel = tfp.mcmc.HamiltonianMonteCarlo(target_log_prob,
step_size=1e-2,
num_leapfrog_steps=2)
sharded_kernel = (
tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
10,
experimental_reduce_chain_axis_names=self.axis_name,
criterion_fn=criterion_fn))
def run(seed):
init_seed, sample_seed = samplers.split_seed(seed)
state_seeds = samplers.split_seed(init_seed)
state = [
samplers.normal(seed=state_seeds[0], shape=[]),
samplers.normal(seed=state_seeds[1], shape=[4])
]
kr = sharded_kernel.bootstrap_results(state)
_, kr = sharded_kernel.one_step(state, kr, seed=sample_seed)
return (
kr.averaged_sq_grad,
kr.averaged_max_trajectory_length
)
seeds = self.shard_values(tf.stack(tfp.random.split_seed(
samplers.zeros_seed(), distribute_test_lib.NUM_DEVICES)), 0)
avg_sq_grad, avg_max_tl = self.evaluate(
self.per_replica_to_tensor(self.strategy_run(
run, args=(seeds,), axis_name=self.axis_name), 0))
for i in range(distribute_test_lib.NUM_DEVICES):
self.assertAllClose(avg_sq_grad[0], avg_sq_grad[i])
self.assertAllClose(avg_max_tl[0], avg_max_tl[i])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_2d_direction),
)
def test_adaptation(self, criterion_fn):
# Compare this to testAdaptation. There we don't use SPMD, but should
# get the same hyperparameters.
if not JAX_MODE:
self.skipTest('TF does not have pmax implemented.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.])), 1)
def run(seed):
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16 // distribute_test_lib.NUM_DEVICES
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
criterion_fn=criterion_fn,
experimental_reduce_chain_axis_names=self.axis_name,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps,
experimental_reduce_chain_axis_names=self.axis_name)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting
# for the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2]),
kernel=kernel,
trace_fn=trace_fn,
seed=seed))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
mean = tf.reduce_mean(chain, axis=[0, 1])
var = tf.reduce_variance(chain, axis=[0, 1])
return mean, var, p_accept, mean_step_size, mean_max_trajectory_length
seeds = self.shard_values(tf.stack(tfp.random.split_seed(
samplers.zeros_seed(), distribute_test_lib.NUM_DEVICES)), 0)
(mean, var, p_accept, mean_step_size, mean_max_trajectory_length) = (
self.evaluate(
self.per_replica_to_tensor(
self.strategy_run(run, args=(seeds,), axis_name=self.axis_name),
0,
)))
self.assertAllClose(0.75, p_accept.mean(), atol=0.1)
# Both ChEES-rate and SNAPER learn roughly the same trajectory length.
self.assertAllClose(1.5, mean_step_size[0], atol=0.2)
self.assertAllClose(15., mean_max_trajectory_length[0], rtol=0.3)
self.assertAllClose(
target.mean(), mean.mean(0),
atol=1.)
self.assertAllClose(
target.variance(),
var.mean(0) + mean.var(0),
rtol=0.1)
del _GradientBasedTrajectoryLengthAdaptationTest
if __name__ == '__main__':
test_util.main()
| 37.59618 | 80 | 0.684774 |
from absl.testing import parameterized
import numpy as np
import tensorflow.compat.v1 as tf1
import tensorflow.compat.v2 as tf
import tensorflow_probability as tfp
from tensorflow_probability.python.internal import distribute_lib
from tensorflow_probability.python.internal import distribute_test_lib
from tensorflow_probability.python.internal import samplers
from tensorflow_probability.python.internal import test_util
tfb = tfp.bijectors
tfd = tfp.distributions
JAX_MODE = False
def snaper_criterion_dummy_direction(previous_state, *args, **kwargs):
return tfp.experimental.mcmc.snaper_criterion(
previous_state,
*args,
direction=tf.nest.map_structure(tf.ones_like, previous_state),
**kwargs,
)
def snaper_criterion_2d_direction(previous_state, *args, **kwargs):
return tfp.experimental.mcmc.snaper_criterion(
previous_state,
*args,
direction=tf.constant([0., 1.], previous_state.dtype),
**kwargs,
)
@test_util.test_graph_and_eager_modes
class GradientBasedTrajectoryLengthAdaptationTestGeneric(
test_util.TestCase, parameterized.TestCase):
def testForbiddenTransformedKernel(self):
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2, step_size=0.1, num_leapfrog_steps=1)
kernel = tfp.mcmc.TransformedTransitionKernel(kernel, tfb.Identity())
with self.assertRaisesRegex(
ValueError,
'The inner kernel cannot contain a `TransformedTransitionKernel`'):
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100)
def testNestedStepSizeError(self):
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2,
step_size=[0.1],
num_leapfrog_steps=1)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100)
with self.assertRaisesRegex(ValueError, 'Step size must be a scalar'):
kernel.bootstrap_results([1.])
@parameterized.named_parameters(('StaticShape', True),
('DynamicShape', False))
def testNonScalarStepSizeError(self, use_static_shape):
step_size = tf1.placeholder_with_default(
[0.1, 0.2], shape=[2] if use_static_shape else None)
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=lambda x: -x**2,
step_size=step_size,
num_leapfrog_steps=1)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, num_adaptation_steps=100, validate_args=True)
with self.assertRaisesRegex(Exception, 'Step size must be a scalar'):
self.evaluate(kernel.bootstrap_results(tf.constant(1.)))
@parameterized.named_parameters(
('ChEESStaticShape', True, tfp.experimental.mcmc.chees_criterion),
('ChEESDynamicShape', False, tfp.experimental.mcmc.chees_criterion),
('SNAPERStaticShape', True, snaper_criterion_dummy_direction),
('SNAPERDynamicShape', False, snaper_criterion_dummy_direction),
)
def testTooFewChains(self, use_static_shape, criterion_fn):
state = tf1.placeholder_with_default(
[[0.1, 0.2]], shape=[1, 2] if use_static_shape else None)
accept_prob = tf1.placeholder_with_default(
[1.], shape=[1] if use_static_shape else None)
with self.assertRaisesRegex(Exception,
'chees_criterion requires at least 2 chains'):
self.evaluate(
tfp.experimental.mcmc.chees_criterion(
state, state, accept_prob, 1., validate_args=True))
@parameterized.named_parameters(
('ChEESStaticShape', True, tfp.experimental.mcmc.chees_criterion),
('ChEESDynamicShape', False, tfp.experimental.mcmc.chees_criterion),
('SNAPERStaticShape', True, snaper_criterion_dummy_direction),
('SNAPERDynamicShape', False, snaper_criterion_dummy_direction),
)
def testNoBatchDims(self, use_static_shape, criterion_fn):
state = tf1.placeholder_with_default(
[[0.1, 0.2]], shape=[1, 2] if use_static_shape else None)
accept_prob = tf1.placeholder_with_default(
1., shape=[] if use_static_shape else None)
with self.assertRaisesRegex(Exception, 'requires at least 2 chains'):
self.evaluate(
criterion_fn(state, state, accept_prob, 1., validate_args=True))
class _GradientBasedTrajectoryLengthAdaptationTest(test_util.TestCase):
def testDocstringExample(self):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.JointDistributionSequential([
tfd.Normal(0., tf.constant(20., dtype=self.dtype)),
tfd.HalfNormal(tf.constant(10., dtype=self.dtype)),
])
def target_log_prob_fn(*x):
return tf.cast(target.log_prob(x), self.dtype)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
kernel = tfp.mcmc.TransformedTransitionKernel(
kernel, [tfb.Identity(), tfb.Exp()])
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting for
# the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=[
tf.ones(num_chains, dtype=self.dtype),
tf.ones(num_chains, dtype=self.dtype)
],
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(0.52, mean_step_size, atol=0.2)
self.assertAllClose(46., mean_max_trajectory_length, atol=15)
self.assertAllClose(
target.mean(), [tf.reduce_mean(x, axis=[0, 1]) for x in chain],
atol=1.5)
self.assertAllClose(
target.variance(),
[tf.math.reduce_variance(x, axis=[0, 1]) for x in chain],
rtol=0.2)
def testStateMeanSNAPER(self):
state = np.array([[0.1, 0.2]], self.dtype)
accept_prob = np.ones([], self.dtype)
# This doesn't fail because state_mean is provided externally.
self.evaluate(tfp.experimental.mcmc.snaper_criterion(
state,
state,
accept_prob,
2.,
direction=tf.ones_like(state),
state_mean=state,
state_mean_weight=0.1,
))
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testScalarState(self, criterion_fn):
def target_log_prob_fn(x):
return -x**2 / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True)
state = tf.zeros([64], self.dtype)
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testTensorState(self, criterion_fn):
def target_log_prob_fn(x):
return -tf.reduce_mean(x**2, [-1, -2]) / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = (
tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True))
state = tf.zeros([64, 2, 3], self.dtype)
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testListState(self, criterion_fn):
def target_log_prob_fn(x, y):
return -x**2 / 2 - y**2 / 2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=5,
adaptation_rate=1.,
criterion_fn=criterion_fn,
validate_args=True)
state = [tf.zeros([64], self.dtype), tf.zeros([64], self.dtype)]
init_kernel_results = kernel.bootstrap_results(state)
init_kernel_results, (_, final_kernel_results) = self.evaluate([
init_kernel_results,
kernel.one_step(
state,
init_kernel_results,
seed=test_util.test_seed(sampler_type='stateless'))
])
self.assertGreater(
np.abs(init_kernel_results.max_trajectory_length -
final_kernel_results.max_trajectory_length), 0.0005)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_2d_direction),
)
def testAdaptation(self, criterion_fn):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.], self.dtype)), 1)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
criterion_fn=criterion_fn,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2], dtype=self.dtype),
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(1.5, mean_step_size, atol=0.2)
self.assertAllClose(15., mean_max_trajectory_length, rtol=0.3)
self.assertAllClose(
target.mean(), tf.reduce_mean(chain, axis=[0, 1]),
atol=1.)
self.assertAllClose(
target.variance(),
tf.math.reduce_variance(chain, axis=[0, 1]),
rtol=0.1)
def testPreconditionedHMC(self):
if tf.executing_eagerly() and not JAX_MODE:
self.skipTest('Too slow for TF Eager.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.], self.dtype)), 1)
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16
step_size = 0.1
kernel = tfp.experimental.mcmc.PreconditionedHamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
momentum_distribution=tfd.Independent(
tfd.Normal(0., tf.constant([1., 1. / 10.], self.dtype)), 1),
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2], dtype=self.dtype),
kernel=kernel,
trace_fn=trace_fn,
seed=test_util.test_seed(sampler_type='stateless')))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
self.assertAllClose(0.75, p_accept, atol=0.1)
self.assertAllClose(1.2, mean_step_size, atol=0.2)
self.assertAllClose(1.5, mean_max_trajectory_length, rtol=0.25)
self.assertAllClose(
target.mean(), tf.reduce_mean(chain, axis=[0, 1]),
atol=0.3)
self.assertAllClose(
target.variance(),
tf.math.reduce_variance(chain, axis=[0, 1]),
rtol=0.1)
def testNumAdaptationSteps(self):
def target_log_prob_fn(x):
return -x**2
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target_log_prob_fn,
step_size=0.1,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=1,
adaptation_rate=1.,
validate_args=True)
state = tf.zeros([64], self.dtype)
seed = test_util.test_seed(sampler_type='stateless')
step_0_kernel_results = kernel.bootstrap_results(state)
state, step_1_kernel_results = kernel.one_step(
state, step_0_kernel_results, seed=seed)
_, step_2_kernel_results = kernel.one_step(
state, step_1_kernel_results, seed=seed)
(step_0_kernel_results, step_1_kernel_results,
step_2_kernel_results) = self.evaluate([
step_0_kernel_results,
step_1_kernel_results,
step_2_kernel_results,
])
self.assertGreater(
np.abs(step_0_kernel_results.max_trajectory_length -
step_1_kernel_results.max_trajectory_length), 0.005)
self.assertAllClose(step_1_kernel_results.max_trajectory_length,
step_2_kernel_results.max_trajectory_length)
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def testCriterionStateEquivalence(self, criterion_fn):
previous_state = np.random.randn(4, 6).astype(self.dtype)
new_state = np.random.randn(4, 6).astype(self.dtype)
accept_prob = np.random.uniform(size=(4,)).astype(self.dtype)
matrix_previous_state = previous_state.reshape([4, 3, 2])
matrix_new_state = new_state.reshape([4, 3, 2])
list_previous_state = [previous_state[:, :2], previous_state[:, 2:]]
list_new_state = [new_state[:, :2], new_state[:, 2:]]
criterion = criterion_fn(
previous_state, new_state, accept_prob, 1.)
matrix_criterion = criterion_fn(
matrix_previous_state, matrix_new_state, accept_prob, 1.)
list_criterion = criterion_fn(
list_previous_state, list_new_state, accept_prob, 1.)
self.assertAllEqual([4], criterion.shape)
self.assertAllClose(criterion, matrix_criterion)
self.assertAllClose(criterion, list_criterion)
class GradientBasedTrajectoryLengthAdaptationTestFloat32(
_GradientBasedTrajectoryLengthAdaptationTest):
dtype = np.float32
class GradientBasedTrajectoryLengthAdaptationTestFloat64(
_GradientBasedTrajectoryLengthAdaptationTest):
dtype = np.float64
@test_util.test_all_tf_execution_regimes
class DistributedGBTLATest(distribute_test_lib.DistributedTest):
def test_gbtla_kernel_tracks_axis_names(self):
inner_kernel = tfp.mcmc.HamiltonianMonteCarlo(tfd.Normal(0, 1).log_prob,
step_size=1.9,
num_leapfrog_steps=2)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1)
self.assertIsNone(kernel.experimental_shard_axis_names)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1, experimental_shard_axis_names=['a'])
self.assertListEqual(kernel.experimental_shard_axis_names, ['a'])
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
inner_kernel, 1).experimental_with_shard_axes(['a'])
self.assertListEqual(kernel.experimental_shard_axis_names, ['a'])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def test_gbtla_kernel_computes_same_criterion_info_with_sharded_state(
self,
criterion_fn,
):
if not JAX_MODE:
self.skipTest('Test in TF runs into `merge_call` error: see b/178944108')
def target_log_prob(a, b):
return (
tfd.Normal(0., 1.).log_prob(a)
+ distribute_lib.psum(tfd.Normal(
distribute_lib.pbroadcast(a, 'foo'), 1.).log_prob(b), 'foo'))
kernel = tfp.mcmc.HamiltonianMonteCarlo(target_log_prob,
step_size=1e-2,
num_leapfrog_steps=2)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel, 10, criterion_fn=criterion_fn)
sharded_kernel = kernel.experimental_with_shard_axes([None, ['foo']])
def run(seed):
init_seed, sample_seed = samplers.split_seed(seed)
state_seeds = samplers.split_seed(init_seed)
state = [
samplers.normal(seed=state_seeds[0], shape=[5]),
samplers.normal(seed=state_seeds[1], shape=[5])
]
kr = sharded_kernel.bootstrap_results(state)
_, kr = sharded_kernel.one_step(state, kr, seed=sample_seed)
return (
kr.criterion,
kr.averaged_sq_grad,
kr.averaged_max_trajectory_length
)
criterion, avg_sq_grad, avg_max_tl = self.evaluate(
self.per_replica_to_tensor(self.strategy_run(
run, args=(samplers.zeros_seed(),), in_axes=None, axis_name='foo'),
0))
for i in range(distribute_test_lib.NUM_DEVICES):
self.assertAllClose(criterion[0], criterion[i])
self.assertAllClose(avg_sq_grad[0], avg_sq_grad[i])
self.assertAllClose(avg_max_tl[0], avg_max_tl[i])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_criterion),
('ChEESR', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_dummy_direction),
)
def test_gbtla_kernel_can_shard_chains_across_devices(self, criterion_fn):
def target_log_prob(a, b):
return (
tfd.Normal(0., 1.).log_prob(a)
+ tfd.Sample(tfd.Normal(a, 1.), 4).log_prob(b))
kernel = tfp.mcmc.HamiltonianMonteCarlo(target_log_prob,
step_size=1e-2,
num_leapfrog_steps=2)
sharded_kernel = (
tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
10,
experimental_reduce_chain_axis_names=self.axis_name,
criterion_fn=criterion_fn))
def run(seed):
init_seed, sample_seed = samplers.split_seed(seed)
state_seeds = samplers.split_seed(init_seed)
state = [
samplers.normal(seed=state_seeds[0], shape=[]),
samplers.normal(seed=state_seeds[1], shape=[4])
]
kr = sharded_kernel.bootstrap_results(state)
_, kr = sharded_kernel.one_step(state, kr, seed=sample_seed)
return (
kr.averaged_sq_grad,
kr.averaged_max_trajectory_length
)
seeds = self.shard_values(tf.stack(tfp.random.split_seed(
samplers.zeros_seed(), distribute_test_lib.NUM_DEVICES)), 0)
avg_sq_grad, avg_max_tl = self.evaluate(
self.per_replica_to_tensor(self.strategy_run(
run, args=(seeds,), axis_name=self.axis_name), 0))
for i in range(distribute_test_lib.NUM_DEVICES):
self.assertAllClose(avg_sq_grad[0], avg_sq_grad[i])
self.assertAllClose(avg_max_tl[0], avg_max_tl[i])
@parameterized.named_parameters(
('ChEES', tfp.experimental.mcmc.chees_rate_criterion),
('SNAPER', snaper_criterion_2d_direction),
)
def test_adaptation(self, criterion_fn):
# get the same hyperparameters.
if not JAX_MODE:
self.skipTest('TF does not have pmax implemented.')
target = tfd.Independent(
tfd.Normal(0., tf.constant([1., 10.])), 1)
def run(seed):
num_burnin_steps = 1000
num_adaptation_steps = int(num_burnin_steps * 0.8)
num_results = 500
num_chains = 16 // distribute_test_lib.NUM_DEVICES
step_size = 0.1
kernel = tfp.mcmc.HamiltonianMonteCarlo(
target_log_prob_fn=target.log_prob,
step_size=step_size,
num_leapfrog_steps=1,
)
kernel = tfp.experimental.mcmc.GradientBasedTrajectoryLengthAdaptation(
kernel,
num_adaptation_steps=num_adaptation_steps,
criterion_fn=criterion_fn,
experimental_reduce_chain_axis_names=self.axis_name,
validate_args=True)
kernel = tfp.mcmc.DualAveragingStepSizeAdaptation(
kernel, num_adaptation_steps=num_adaptation_steps,
experimental_reduce_chain_axis_names=self.axis_name)
def trace_fn(_, pkr):
return (
pkr.inner_results.inner_results.accepted_results
.step_size,
pkr.inner_results.max_trajectory_length,
pkr.inner_results.inner_results.log_accept_ratio,
)
# The chain will be stepped for num_results + num_burnin_steps, adapting
# for the first num_adaptation_steps.
chain, [step_size, max_trajectory_length, log_accept_ratio] = (
tfp.mcmc.sample_chain(
num_results=num_results,
num_burnin_steps=num_burnin_steps,
current_state=tf.zeros([num_chains, 2]),
kernel=kernel,
trace_fn=trace_fn,
seed=seed))
p_accept = tf.math.exp(
tfp.math.reduce_logmeanexp(tf.minimum(log_accept_ratio, 0.)))
mean_step_size = tf.reduce_mean(step_size)
mean_max_trajectory_length = tf.reduce_mean(max_trajectory_length)
mean = tf.reduce_mean(chain, axis=[0, 1])
var = tf.reduce_variance(chain, axis=[0, 1])
return mean, var, p_accept, mean_step_size, mean_max_trajectory_length
seeds = self.shard_values(tf.stack(tfp.random.split_seed(
samplers.zeros_seed(), distribute_test_lib.NUM_DEVICES)), 0)
(mean, var, p_accept, mean_step_size, mean_max_trajectory_length) = (
self.evaluate(
self.per_replica_to_tensor(
self.strategy_run(run, args=(seeds,), axis_name=self.axis_name),
0,
)))
self.assertAllClose(0.75, p_accept.mean(), atol=0.1)
# Both ChEES-rate and SNAPER learn roughly the same trajectory length.
self.assertAllClose(1.5, mean_step_size[0], atol=0.2)
self.assertAllClose(15., mean_max_trajectory_length[0], rtol=0.3)
self.assertAllClose(
target.mean(), mean.mean(0),
atol=1.)
self.assertAllClose(
target.variance(),
var.mean(0) + mean.var(0),
rtol=0.1)
del _GradientBasedTrajectoryLengthAdaptationTest
if __name__ == '__main__':
test_util.main()
| true | true |
f7fe65b23c0297d29f75693515a88dffa7e50e93 | 2,718 | py | Python | counters/views.py | aisahana/eclinic_api | feb67008f55f6af978adf2e55600ed17e7e514d3 | [
"MIT"
] | 5 | 2019-10-29T22:45:24.000Z | 2021-08-15T07:04:50.000Z | counters/views.py | AldiAE/eclinic_api | feb67008f55f6af978adf2e55600ed17e7e514d3 | [
"MIT"
] | 5 | 2020-06-06T00:16:24.000Z | 2022-02-10T10:43:15.000Z | counters/views.py | AldiAE/eclinic_api | feb67008f55f6af978adf2e55600ed17e7e514d3 | [
"MIT"
] | 8 | 2019-10-29T04:17:14.000Z | 2022-03-02T13:32:25.000Z | from rest_framework import viewsets, status
from rest_framework.authentication import TokenAuthentication
from rest_framework.decorators import action
from rest_framework.permissions import IsAuthenticated, AllowAny
from rest_framework.response import Response
from counters.models import Counter, Queue
from counters.serializers import CounterSerializer, QueueSerializer, GenerateQueueSerializer
from utils.views import generate_queue
class CounterViewSet(viewsets.ModelViewSet):
serializer_class = CounterSerializer
queryset = Counter.objects.all()
authentication_classes = (TokenAuthentication,)
permission_classes = (IsAuthenticated,)
ordering_fields = ['created',]
search_fields = [
'counter_number',
'name',
]
filterset_fields = [
'is_draft',
]
@action(detail=True, methods=['post'])
def publish(self, request, pk=None):
counter = self.get_object()
counter.is_draft = False
counter.save()
return Response(self.get_serializer(counter, many=False).data)
@action(detail=True, methods=['post'])
def draft(self, request, pk=None):
counter = self.get_object()
counter.is_draft = True
counter.save()
return Response(self.get_serializer(counter, many=False).data)
@action(detail=False, methods=['get'], permission_classes=[AllowAny])
def public(self, request):
queryset = self.get_queryset().filter(is_draft=False)
return Response(self.get_serializer(queryset, many=True).data)
class QueueViewSet(viewsets.ModelViewSet):
serializer_class = QueueSerializer
queryset = Queue.objects.all()
authentication_classes = (TokenAuthentication,)
permission_classes = (IsAuthenticated,)
ordering_fields = ['created',]
search_fields = [
'counter__counter_number',
'counter__counter_name',
'number',
]
filterset_fields = [
'is_draft',
'is_complete',
]
@action(detail=False, methods=['post'], permission_classes=[AllowAny])
def generate(self, request):
serializer = GenerateQueueSerializer(data=request.data)
if serializer.is_valid():
queue = serializer.save()
queue = generate_queue(queue.counter, queue)
return Response(self.get_serializer(queue, many=False).data)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
@action(detail=True, methods=['post'], permission_classes=[AllowAny])
def next_number(self, request, pk=None):
queue = self.get_object()
queue.is_complete = True
queue.save()
return Response(self.get_serializer(queue, many=False).data) | 33.975 | 92 | 0.696836 | from rest_framework import viewsets, status
from rest_framework.authentication import TokenAuthentication
from rest_framework.decorators import action
from rest_framework.permissions import IsAuthenticated, AllowAny
from rest_framework.response import Response
from counters.models import Counter, Queue
from counters.serializers import CounterSerializer, QueueSerializer, GenerateQueueSerializer
from utils.views import generate_queue
class CounterViewSet(viewsets.ModelViewSet):
serializer_class = CounterSerializer
queryset = Counter.objects.all()
authentication_classes = (TokenAuthentication,)
permission_classes = (IsAuthenticated,)
ordering_fields = ['created',]
search_fields = [
'counter_number',
'name',
]
filterset_fields = [
'is_draft',
]
@action(detail=True, methods=['post'])
def publish(self, request, pk=None):
counter = self.get_object()
counter.is_draft = False
counter.save()
return Response(self.get_serializer(counter, many=False).data)
@action(detail=True, methods=['post'])
def draft(self, request, pk=None):
counter = self.get_object()
counter.is_draft = True
counter.save()
return Response(self.get_serializer(counter, many=False).data)
@action(detail=False, methods=['get'], permission_classes=[AllowAny])
def public(self, request):
queryset = self.get_queryset().filter(is_draft=False)
return Response(self.get_serializer(queryset, many=True).data)
class QueueViewSet(viewsets.ModelViewSet):
serializer_class = QueueSerializer
queryset = Queue.objects.all()
authentication_classes = (TokenAuthentication,)
permission_classes = (IsAuthenticated,)
ordering_fields = ['created',]
search_fields = [
'counter__counter_number',
'counter__counter_name',
'number',
]
filterset_fields = [
'is_draft',
'is_complete',
]
@action(detail=False, methods=['post'], permission_classes=[AllowAny])
def generate(self, request):
serializer = GenerateQueueSerializer(data=request.data)
if serializer.is_valid():
queue = serializer.save()
queue = generate_queue(queue.counter, queue)
return Response(self.get_serializer(queue, many=False).data)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)
@action(detail=True, methods=['post'], permission_classes=[AllowAny])
def next_number(self, request, pk=None):
queue = self.get_object()
queue.is_complete = True
queue.save()
return Response(self.get_serializer(queue, many=False).data) | true | true |
f7fe662a0c6c60ba566830b70edc654b6129c849 | 2,538 | py | Python | Dynamic-channels/test.py | void-zxh/CS337-SRDGI | e86413affd5867d42f9bbe66030d13b29bd2e067 | [
"MIT"
] | null | null | null | Dynamic-channels/test.py | void-zxh/CS337-SRDGI | e86413affd5867d42f9bbe66030d13b29bd2e067 | [
"MIT"
] | null | null | null | Dynamic-channels/test.py | void-zxh/CS337-SRDGI | e86413affd5867d42f9bbe66030d13b29bd2e067 | [
"MIT"
] | 1 | 2022-01-04T12:32:40.000Z | 2022-01-04T12:32:40.000Z | import argparse
import os
import time
import torch
from torch.autograd import Variable
from dynamic_channels import sample_tiny_sub_channel
from model import G
from util import is_image, load_image, save_image
parser = argparse.ArgumentParser(description='DeepRendering-implementation')
parser.add_argument('--dataset', required=True, help='unity')
parser.add_argument('--model', type=str, required=True, help='model file')
parser.add_argument('--accuracy', type=int, default=1, help='model file')
parser.add_argument('--n_channel_input', type=int, default=3, help='input channel')
parser.add_argument('--n_channel_output', type=int, default=3, help='output channel')
parser.add_argument('--n_generator_filters', type=int, default=64, help="number of generator filters")
opt = parser.parse_args()
netG_model = torch.load(opt.model)
netG = G(opt.n_channel_input * 4, opt.n_channel_output, opt.n_generator_filters)
netG.load_state_dict(netG_model['state_dict_G'])
root_dir = 'dataset/{}/test/'.format(opt.dataset)
image_dir = 'dataset/{}/test/albedo'.format(opt.dataset)
image_filenames = [x for x in os.listdir(image_dir) if is_image(x)]
time_list=[]
for image_name in image_filenames:
albedo_image = load_image(root_dir + 'albedo/' + image_name)
direct_image = load_image(root_dir + 'direct/' + image_name)
normal_image = load_image(root_dir + 'normal/' + image_name)
depth_image = load_image(root_dir + 'depth/' + image_name)
gt_image = load_image(root_dir + 'gt/' + image_name)
albedo = Variable(albedo_image).view(1, -1, 256, 256).cuda()
direct = Variable(direct_image).view(1, -1, 256, 256).cuda()
normal = Variable(normal_image).view(1, -1, 256, 256).cuda()
depth = Variable(depth_image).view(1, -1, 256, 256).cuda()
sample_tiny_sub_channel(netG, size=opt.accuracy, n_filters=opt.n_generator_filters)
netG = netG.cuda()
start_p=time.time()
out = netG(torch.cat((albedo, direct, normal, depth), 1))
end_p=time.time()
out = out.cpu()
out_img = out.data[0]
time_list.append(end_p-start_p)
if not os.path.exists("result"):
os.mkdir("result")
if not os.path.exists(os.path.join("result", "accuracy_{}".format(opt.accuracy))):
os.mkdir(os.path.join("result", "accuracy_{}".format(opt.accuracy)))
save_image(out_img, "result/accuracy_{}/{}".format(opt.accuracy, image_name))
save_image(gt_image, "result/accuracy_{}/GT{}".format(opt.accuracy, image_name))
print(time_list) | 45.321429 | 103 | 0.70922 | import argparse
import os
import time
import torch
from torch.autograd import Variable
from dynamic_channels import sample_tiny_sub_channel
from model import G
from util import is_image, load_image, save_image
parser = argparse.ArgumentParser(description='DeepRendering-implementation')
parser.add_argument('--dataset', required=True, help='unity')
parser.add_argument('--model', type=str, required=True, help='model file')
parser.add_argument('--accuracy', type=int, default=1, help='model file')
parser.add_argument('--n_channel_input', type=int, default=3, help='input channel')
parser.add_argument('--n_channel_output', type=int, default=3, help='output channel')
parser.add_argument('--n_generator_filters', type=int, default=64, help="number of generator filters")
opt = parser.parse_args()
netG_model = torch.load(opt.model)
netG = G(opt.n_channel_input * 4, opt.n_channel_output, opt.n_generator_filters)
netG.load_state_dict(netG_model['state_dict_G'])
root_dir = 'dataset/{}/test/'.format(opt.dataset)
image_dir = 'dataset/{}/test/albedo'.format(opt.dataset)
image_filenames = [x for x in os.listdir(image_dir) if is_image(x)]
time_list=[]
for image_name in image_filenames:
albedo_image = load_image(root_dir + 'albedo/' + image_name)
direct_image = load_image(root_dir + 'direct/' + image_name)
normal_image = load_image(root_dir + 'normal/' + image_name)
depth_image = load_image(root_dir + 'depth/' + image_name)
gt_image = load_image(root_dir + 'gt/' + image_name)
albedo = Variable(albedo_image).view(1, -1, 256, 256).cuda()
direct = Variable(direct_image).view(1, -1, 256, 256).cuda()
normal = Variable(normal_image).view(1, -1, 256, 256).cuda()
depth = Variable(depth_image).view(1, -1, 256, 256).cuda()
sample_tiny_sub_channel(netG, size=opt.accuracy, n_filters=opt.n_generator_filters)
netG = netG.cuda()
start_p=time.time()
out = netG(torch.cat((albedo, direct, normal, depth), 1))
end_p=time.time()
out = out.cpu()
out_img = out.data[0]
time_list.append(end_p-start_p)
if not os.path.exists("result"):
os.mkdir("result")
if not os.path.exists(os.path.join("result", "accuracy_{}".format(opt.accuracy))):
os.mkdir(os.path.join("result", "accuracy_{}".format(opt.accuracy)))
save_image(out_img, "result/accuracy_{}/{}".format(opt.accuracy, image_name))
save_image(gt_image, "result/accuracy_{}/GT{}".format(opt.accuracy, image_name))
print(time_list) | true | true |
f7fe67c0cfeb378edf623c5d01b3a275d4d5bf9d | 336 | py | Python | docs/add_glossary.py | NotMyFault/templating-engine-plugin | a3506f938a189909a5c8b921f18845b87a8ac5c7 | [
"Apache-2.0"
] | 133 | 2019-03-07T21:08:02.000Z | 2022-03-29T14:05:53.000Z | docs/add_glossary.py | NotMyFault/templating-engine-plugin | a3506f938a189909a5c8b921f18845b87a8ac5c7 | [
"Apache-2.0"
] | 156 | 2019-07-30T13:46:57.000Z | 2022-03-28T16:27:19.000Z | docs/add_glossary.py | NotMyFault/templating-engine-plugin | a3506f938a189909a5c8b921f18845b87a8ac5c7 | [
"Apache-2.0"
] | 61 | 2019-03-07T20:00:18.000Z | 2022-03-21T01:28:06.000Z | import mkdocs_gen_files
import os
import glob
# iterate over pages and append glossary
for file in glob.glob("/docs/docs/**/*.md", recursive = True):
if file.endswith('.md'):
text = open(file).read()
with mkdocs_gen_files.open(file.replace('/docs/docs/', ''), "w") as f:
print(text + '\n--8<-- "./glossary.md"', file=f) | 33.6 | 74 | 0.64881 | import mkdocs_gen_files
import os
import glob
for file in glob.glob("/docs/docs/**/*.md", recursive = True):
if file.endswith('.md'):
text = open(file).read()
with mkdocs_gen_files.open(file.replace('/docs/docs/', ''), "w") as f:
print(text + '\n--8<-- "./glossary.md"', file=f) | true | true |
f7fe68d6d7de6e694493f5f30e97587cbc29d818 | 394 | py | Python | instagram_api/response/post_live_viewer_list.py | Yuego/instagram_api | b53f72db36c505a2eb24ebac1ba8267a0cc295bb | [
"MIT"
] | 13 | 2019-08-07T21:24:34.000Z | 2020-12-12T12:23:50.000Z | instagram_api/response/post_live_viewer_list.py | Yuego/instagram_api | b53f72db36c505a2eb24ebac1ba8267a0cc295bb | [
"MIT"
] | null | null | null | instagram_api/response/post_live_viewer_list.py | Yuego/instagram_api | b53f72db36c505a2eb24ebac1ba8267a0cc295bb | [
"MIT"
] | null | null | null | from .mapper import ApiResponse, ApiResponseInterface
from .mapper.types import Timestamp, AnyType
from .model import User
__all__ = ['PostLiveViewerListResponse']
class PostLiveViewerListResponseInterface(ApiResponseInterface):
users: [User]
next_max_id: str
total_viewer_count: int
class PostLiveViewerListResponse(ApiResponse, PostLiveViewerListResponseInterface):
pass
| 24.625 | 83 | 0.814721 | from .mapper import ApiResponse, ApiResponseInterface
from .mapper.types import Timestamp, AnyType
from .model import User
__all__ = ['PostLiveViewerListResponse']
class PostLiveViewerListResponseInterface(ApiResponseInterface):
users: [User]
next_max_id: str
total_viewer_count: int
class PostLiveViewerListResponse(ApiResponse, PostLiveViewerListResponseInterface):
pass
| true | true |
f7fe68f88a88b9128f190f27c71f8783dc3120dc | 607 | py | Python | integration_tests/test_leica_disto_r12.py | jkjt/ezdxf | 2acc5611b81476ea16b98063b9f55446a9182b81 | [
"MIT"
] | 515 | 2017-01-25T05:46:52.000Z | 2022-03-29T09:52:27.000Z | integration_tests/test_leica_disto_r12.py | jkjt/ezdxf | 2acc5611b81476ea16b98063b9f55446a9182b81 | [
"MIT"
] | 417 | 2017-01-25T10:01:17.000Z | 2022-03-29T09:22:04.000Z | integration_tests/test_leica_disto_r12.py | jkjt/ezdxf | 2acc5611b81476ea16b98063b9f55446a9182b81 | [
"MIT"
] | 149 | 2017-02-01T15:52:02.000Z | 2022-03-17T10:33:38.000Z | # Copyright (c) 2020, Manfred Moitzi
# License: MIT License
import os
import pytest
import ezdxf
BASEDIR = os.path.dirname(__file__)
DATADIR = "data"
@pytest.fixture(params=["Leica_Disto_S910.dxf"])
def filename(request):
filename = os.path.join(BASEDIR, DATADIR, request.param)
if not os.path.exists(filename):
pytest.skip(f"File {filename} not found.")
return filename
def test_leica_disto_r12(filename):
doc = ezdxf.readfile(filename)
msp = doc.modelspace()
points = list(msp.query("POINT"))
assert len(points) == 11
assert len(points[0].dxf.location) == 3
| 24.28 | 60 | 0.69687 |
import os
import pytest
import ezdxf
BASEDIR = os.path.dirname(__file__)
DATADIR = "data"
@pytest.fixture(params=["Leica_Disto_S910.dxf"])
def filename(request):
filename = os.path.join(BASEDIR, DATADIR, request.param)
if not os.path.exists(filename):
pytest.skip(f"File {filename} not found.")
return filename
def test_leica_disto_r12(filename):
doc = ezdxf.readfile(filename)
msp = doc.modelspace()
points = list(msp.query("POINT"))
assert len(points) == 11
assert len(points[0].dxf.location) == 3
| true | true |
f7fe6aaab78490f28adb8207d40caa3e9121ddc2 | 663 | py | Python | modules/jquery/chuck_module.py | msabramo/django-chuck | bbef6171c9b3738460dc05cb77e65ba88fcc5ad8 | [
"BSD-2-Clause"
] | 1 | 2020-05-29T04:27:50.000Z | 2020-05-29T04:27:50.000Z | modules/jquery/chuck_module.py | msabramo/django-chuck | bbef6171c9b3738460dc05cb77e65ba88fcc5ad8 | [
"BSD-2-Clause"
] | null | null | null | modules/jquery/chuck_module.py | msabramo/django-chuck | bbef6171c9b3738460dc05cb77e65ba88fcc5ad8 | [
"BSD-2-Clause"
] | null | null | null | import subprocess
import os
description = """
Installs the jQuery javascript library into the static folders.
Please note, that this module requires Git in order to work properly.
For more information, visit:
http://jquery.org/
"""
def post_build():
jquery_dir = os.path.join(project_dir, 'static/scripts/libs/jquery')
if not os.path.exists(jquery_dir):
os.makedirs(jquery_dir)
subprocess.call(
'cd '+site_dir+'; mkdir .src; cd .src; \
git clone git://github.com/jquery/jquery.git; \
cd jquery; \
make; \
mv -v dist/* '+jquery_dir+'; \
cd '+site_dir+'; rm -rf .src;',
shell=True) | 27.625 | 72 | 0.636501 | import subprocess
import os
description = """
Installs the jQuery javascript library into the static folders.
Please note, that this module requires Git in order to work properly.
For more information, visit:
http://jquery.org/
"""
def post_build():
jquery_dir = os.path.join(project_dir, 'static/scripts/libs/jquery')
if not os.path.exists(jquery_dir):
os.makedirs(jquery_dir)
subprocess.call(
'cd '+site_dir+'; mkdir .src; cd .src; \
git clone git://github.com/jquery/jquery.git; \
cd jquery; \
make; \
mv -v dist/* '+jquery_dir+'; \
cd '+site_dir+'; rm -rf .src;',
shell=True) | true | true |
f7fe6cf13e7d36f7c5800d10790a765e3630fd45 | 3,994 | py | Python | src/cowrie/ssh_proxy/protocols/exec_term.py | iconnor/cowrie | 33c3f7c7d0ec797fd098043d4b1c201e8e1f4a11 | [
"BSD-3-Clause"
] | 1 | 2021-10-15T05:00:15.000Z | 2021-10-15T05:00:15.000Z | src/cowrie/ssh_proxy/protocols/exec_term.py | iconnor/cowrie | 33c3f7c7d0ec797fd098043d4b1c201e8e1f4a11 | [
"BSD-3-Clause"
] | 3 | 2021-09-13T02:37:23.000Z | 2022-03-03T21:48:46.000Z | src/cowrie/ssh_proxy/protocols/exec_term.py | iconnor/cowrie | 33c3f7c7d0ec797fd098043d4b1c201e8e1f4a11 | [
"BSD-3-Clause"
] | null | null | null | # Copyright (c) 2016 Thomas Nicholson <tnnich@googlemail.com>
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# 3. The names of the author(s) may not be used to endorse or promote
# products derived from this software without specific prior written
# permission.
#
# THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
# IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
# OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
# IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
# BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
# AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY
# OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
# SUCH DAMAGE.
import os
import time
from twisted.python import log
from cowrie.core import ttylog
from cowrie.core.config import CowrieConfig
from cowrie.ssh_proxy.protocols import base_protocol
class ExecTerm(base_protocol.BaseProtocol):
def __init__(self, uuid, channelName, ssh, channelId, command):
super().__init__(uuid, channelName, ssh)
try:
log.msg(
eventid="cowrie.command.input",
input=command.decode("utf8"),
format="CMD: %(input)s",
)
except UnicodeDecodeError:
log.err("Unusual execcmd: {}".format(repr(command)))
self.transportId = ssh.server.transportId
self.channelId = channelId
self.startTime: float = time.time()
self.ttylogPath: str = CowrieConfig.get("honeypot", "ttylog_path")
self.ttylogEnabled: bool = CowrieConfig.getboolean(
"honeypot", "ttylog", fallback=True
)
self.ttylogSize: bool = 0
if self.ttylogEnabled:
self.ttylogFile = "{}/{}-{}-{}e.log".format(
self.ttylogPath,
time.strftime("%Y%m%d-%H%M%S"),
self.transportId,
self.channelId,
)
ttylog.ttylog_open(self.ttylogFile, self.startTime)
def parse_packet(self, parent, payload):
if self.ttylogEnabled:
ttylog.ttylog_write(
self.ttylogFile, len(payload), ttylog.TYPE_OUTPUT, time.time(), payload
)
self.ttylogSize += len(payload)
def channel_closed(self):
if self.ttylogEnabled:
ttylog.ttylog_close(self.ttylogFile, time.time())
shasum = ttylog.ttylog_inputhash(self.ttylogFile)
shasumfile = os.path.join(self.ttylogPath, shasum)
if os.path.exists(shasumfile):
duplicate = True
os.remove(self.ttylogFile)
else:
duplicate = False
os.rename(self.ttylogFile, shasumfile)
umask = os.umask(0)
os.umask(umask)
os.chmod(shasumfile, 0o666 & ~umask)
log.msg(
eventid="cowrie.log.closed",
format="Closing TTY Log: %(ttylog)s after %(duration)d seconds",
ttylog=shasumfile,
size=self.ttylogSize,
shasum=shasum,
duplicate=duplicate,
duration=time.time() - self.startTime,
)
| 38.776699 | 87 | 0.641963 |
import os
import time
from twisted.python import log
from cowrie.core import ttylog
from cowrie.core.config import CowrieConfig
from cowrie.ssh_proxy.protocols import base_protocol
class ExecTerm(base_protocol.BaseProtocol):
def __init__(self, uuid, channelName, ssh, channelId, command):
super().__init__(uuid, channelName, ssh)
try:
log.msg(
eventid="cowrie.command.input",
input=command.decode("utf8"),
format="CMD: %(input)s",
)
except UnicodeDecodeError:
log.err("Unusual execcmd: {}".format(repr(command)))
self.transportId = ssh.server.transportId
self.channelId = channelId
self.startTime: float = time.time()
self.ttylogPath: str = CowrieConfig.get("honeypot", "ttylog_path")
self.ttylogEnabled: bool = CowrieConfig.getboolean(
"honeypot", "ttylog", fallback=True
)
self.ttylogSize: bool = 0
if self.ttylogEnabled:
self.ttylogFile = "{}/{}-{}-{}e.log".format(
self.ttylogPath,
time.strftime("%Y%m%d-%H%M%S"),
self.transportId,
self.channelId,
)
ttylog.ttylog_open(self.ttylogFile, self.startTime)
def parse_packet(self, parent, payload):
if self.ttylogEnabled:
ttylog.ttylog_write(
self.ttylogFile, len(payload), ttylog.TYPE_OUTPUT, time.time(), payload
)
self.ttylogSize += len(payload)
def channel_closed(self):
if self.ttylogEnabled:
ttylog.ttylog_close(self.ttylogFile, time.time())
shasum = ttylog.ttylog_inputhash(self.ttylogFile)
shasumfile = os.path.join(self.ttylogPath, shasum)
if os.path.exists(shasumfile):
duplicate = True
os.remove(self.ttylogFile)
else:
duplicate = False
os.rename(self.ttylogFile, shasumfile)
umask = os.umask(0)
os.umask(umask)
os.chmod(shasumfile, 0o666 & ~umask)
log.msg(
eventid="cowrie.log.closed",
format="Closing TTY Log: %(ttylog)s after %(duration)d seconds",
ttylog=shasumfile,
size=self.ttylogSize,
shasum=shasum,
duplicate=duplicate,
duration=time.time() - self.startTime,
)
| true | true |
f7fe6df0e3dabb730e3d388fe3b34f930ffd281f | 954 | py | Python | test/t_normalrdmbased.py | ZitongLu1996/PyCTRSA | 7b243930321c089e235c9fc1e771b6432d530819 | [
"MIT"
] | 17 | 2020-07-26T17:05:12.000Z | 2022-03-09T04:59:09.000Z | test/t_normalrdmbased.py | ZitongLu1996/PyCTRSA | 7b243930321c089e235c9fc1e771b6432d530819 | [
"MIT"
] | null | null | null | test/t_normalrdmbased.py | ZitongLu1996/PyCTRSA | 7b243930321c089e235c9fc1e771b6432d530819 | [
"MIT"
] | 3 | 2020-08-02T14:48:02.000Z | 2020-11-26T12:31:46.000Z | # -*- coding: utf-8
"""
@File : t_normalrdmbased.py
@Author : Zitong Lu
@Contact : zitonglu1996@gmail.com
@License : MIT License
"""
import numpy as np
import unittest
from pyctrsa.ctsimilarity.normalrdmbased import ctsimilarities_cal
class test_normalrdmbased(unittest.TestCase):
def test_ctsimilarities_cal(self):
RDMs = np.random.rand(20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 20)
self.assertEqual(len(CTSimilarities.shape), 3)
RDMs = np.random.rand(5, 20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 5)
self.assertEqual(len(CTSimilarities.shape), 4)
RDMs = np.random.rand(5, 4, 20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 5)
self.assertEqual(len(CTSimilarities.shape), 5) | 30.774194 | 66 | 0.675052 |
import numpy as np
import unittest
from pyctrsa.ctsimilarity.normalrdmbased import ctsimilarities_cal
class test_normalrdmbased(unittest.TestCase):
def test_ctsimilarities_cal(self):
RDMs = np.random.rand(20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 20)
self.assertEqual(len(CTSimilarities.shape), 3)
RDMs = np.random.rand(5, 20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 5)
self.assertEqual(len(CTSimilarities.shape), 4)
RDMs = np.random.rand(5, 4, 20, 6, 6)
CTSimilarities = ctsimilarities_cal(RDMs)
self.assertEqual(CTSimilarities.shape[0], 5)
self.assertEqual(len(CTSimilarities.shape), 5) | true | true |
f7fe6e12069e9f9aeeb94f79139bee9b65302204 | 3,491 | py | Python | test/test_bytesstorage.py | Pat-Laub/pyABC | f23f0ff8d430a8ce0a0c8253b45e19add9121992 | [
"BSD-3-Clause"
] | null | null | null | test/test_bytesstorage.py | Pat-Laub/pyABC | f23f0ff8d430a8ce0a0c8253b45e19add9121992 | [
"BSD-3-Clause"
] | null | null | null | test/test_bytesstorage.py | Pat-Laub/pyABC | f23f0ff8d430a8ce0a0c8253b45e19add9121992 | [
"BSD-3-Clause"
] | null | null | null | import pytest
from pyabc.storage.bytes_storage import to_bytes, from_bytes
import pandas as pd
import numpy as np
import scipy as sp
from rpy2.robjects import r
import rpy2.robjects as robjects
from rpy2.robjects import pandas2ri
@pytest.fixture(params=["empty", "int", "float", "non_numeric_str",
"numeric_str", "int-float-numeric_str",
"int-float-non_numeric_str-str_ind",
"int-float-numeric_str-str_ind",
"py-int",
"py-float",
"py-str",
"r-df-cars",
"r-df-faithful" # TODO re-add iris, see #45
])
def object_(request):
par = request.param
if par == "empty":
return pd.DataFrame()
if par == "int":
return pd.DataFrame({"a": sp.random.randint(-20, 20, 100),
"b": sp.random.randint(-20, 20, 100)})
if par == "float":
return pd.DataFrame({"a": sp.randn(100),
"b": sp.randn(100)})
if par == "non_numeric_str":
return pd.DataFrame({"a": ["foo", "bar"],
"b": ["bar", "foo"]})
if par == "numeric_str":
return pd.DataFrame({"a": list(map(str, sp.randn(100))),
"b": list(map(str,
sp.random.randint(-20, 20, 100)))})
if par == "int-float-numeric_str":
return pd.DataFrame({"a": sp.random.randint(-20, 20, 100),
"b": sp.randn(100),
"c": list(map(str,
sp.random.randint(-20, 20, 100)))})
if par == "int-float-non_numeric_str-str_ind":
return pd.DataFrame({"a": [1, 2],
"b": [1.1, 2.2],
"c": ["foo", "bar"]},
index=["first", "second"])
if par == "int-float-numeric_str-str_ind":
return pd.DataFrame({"a": [1, 2],
"b": [1.1, 2.2],
"c": ["1", "2"]},
index=["first", "second"])
if par == "py-int":
return 42
if par == "py-float":
return 42.42
if par == "py-str":
return "foo bar"
if par == "np-int":
return sp.random.randint(-20, 20, 100)
if par == "np-float":
return sp.random.randn(100)
if par == "r-df-cars":
return r["mtcars"]
if par == "r-df-iris":
return r["iris"]
if par == "r-df-faithful":
return r["faithful"]
raise Exception("Invalid Test DataFrame Type")
def test_storage(object_):
serial = to_bytes(object_)
assert isinstance(serial, bytes)
rebuilt = from_bytes(serial)
if not isinstance(object_, robjects.DataFrame):
assert isinstance(object_, type(rebuilt))
if isinstance(object_, int):
assert object_ == rebuilt
elif isinstance(object_, float):
assert object_ == rebuilt
elif isinstance(object_, str):
assert object_ == rebuilt
elif isinstance(object_, np.ndarray):
assert (object_ == rebuilt).all()
elif isinstance(object_, pd.DataFrame):
assert (object_ == rebuilt).all().all()
elif isinstance(object_, robjects.DataFrame):
assert (pandas2ri.ri2py(object_) == rebuilt).all().all()
else:
raise Exception("Could not compare")
| 36.747368 | 78 | 0.496419 | import pytest
from pyabc.storage.bytes_storage import to_bytes, from_bytes
import pandas as pd
import numpy as np
import scipy as sp
from rpy2.robjects import r
import rpy2.robjects as robjects
from rpy2.robjects import pandas2ri
@pytest.fixture(params=["empty", "int", "float", "non_numeric_str",
"numeric_str", "int-float-numeric_str",
"int-float-non_numeric_str-str_ind",
"int-float-numeric_str-str_ind",
"py-int",
"py-float",
"py-str",
"r-df-cars",
"r-df-faithful" ])
def object_(request):
par = request.param
if par == "empty":
return pd.DataFrame()
if par == "int":
return pd.DataFrame({"a": sp.random.randint(-20, 20, 100),
"b": sp.random.randint(-20, 20, 100)})
if par == "float":
return pd.DataFrame({"a": sp.randn(100),
"b": sp.randn(100)})
if par == "non_numeric_str":
return pd.DataFrame({"a": ["foo", "bar"],
"b": ["bar", "foo"]})
if par == "numeric_str":
return pd.DataFrame({"a": list(map(str, sp.randn(100))),
"b": list(map(str,
sp.random.randint(-20, 20, 100)))})
if par == "int-float-numeric_str":
return pd.DataFrame({"a": sp.random.randint(-20, 20, 100),
"b": sp.randn(100),
"c": list(map(str,
sp.random.randint(-20, 20, 100)))})
if par == "int-float-non_numeric_str-str_ind":
return pd.DataFrame({"a": [1, 2],
"b": [1.1, 2.2],
"c": ["foo", "bar"]},
index=["first", "second"])
if par == "int-float-numeric_str-str_ind":
return pd.DataFrame({"a": [1, 2],
"b": [1.1, 2.2],
"c": ["1", "2"]},
index=["first", "second"])
if par == "py-int":
return 42
if par == "py-float":
return 42.42
if par == "py-str":
return "foo bar"
if par == "np-int":
return sp.random.randint(-20, 20, 100)
if par == "np-float":
return sp.random.randn(100)
if par == "r-df-cars":
return r["mtcars"]
if par == "r-df-iris":
return r["iris"]
if par == "r-df-faithful":
return r["faithful"]
raise Exception("Invalid Test DataFrame Type")
def test_storage(object_):
serial = to_bytes(object_)
assert isinstance(serial, bytes)
rebuilt = from_bytes(serial)
if not isinstance(object_, robjects.DataFrame):
assert isinstance(object_, type(rebuilt))
if isinstance(object_, int):
assert object_ == rebuilt
elif isinstance(object_, float):
assert object_ == rebuilt
elif isinstance(object_, str):
assert object_ == rebuilt
elif isinstance(object_, np.ndarray):
assert (object_ == rebuilt).all()
elif isinstance(object_, pd.DataFrame):
assert (object_ == rebuilt).all().all()
elif isinstance(object_, robjects.DataFrame):
assert (pandas2ri.ri2py(object_) == rebuilt).all().all()
else:
raise Exception("Could not compare")
| true | true |
f7fe6ff68f166ec3b32d20a529d63d348ef8636d | 2,564 | py | Python | pypy/module/_rawffi/__init__.py | benoitc/pypy | a3e1b12d1d01dc29056b7badc051ffc034297658 | [
"MIT"
] | 1 | 2020-01-21T11:10:51.000Z | 2020-01-21T11:10:51.000Z | pypy/module/_rawffi/__init__.py | benoitc/pypy | a3e1b12d1d01dc29056b7badc051ffc034297658 | [
"MIT"
] | null | null | null | pypy/module/_rawffi/__init__.py | benoitc/pypy | a3e1b12d1d01dc29056b7badc051ffc034297658 | [
"MIT"
] | null | null | null |
""" Low-level interface to clibffi
"""
from pypy.interpreter.mixedmodule import MixedModule
from pypy.module._rawffi.interp_rawffi import W_CDLL
from pypy.rpython.lltypesystem import lltype, rffi
from pypy.module._rawffi.tracker import Tracker
import sys
class Module(MixedModule):
interpleveldefs = {
'CDLL' : 'interp_rawffi.W_CDLL',
'FuncPtr' : 'interp_rawffi.W_FuncPtr',
'Structure' : 'structure.W_Structure',
'StructureInstance' : 'structure.W_StructureInstance',
'StructureInstanceAutoFree' : 'structure.W_StructureInstanceAutoFree',
'Array' : 'array.W_Array',
'ArrayInstance' : 'array.W_ArrayInstance',
'ArrayInstanceAutoFree' : 'array.W_ArrayInstanceAutoFree',
'sizeof' : 'interp_rawffi.sizeof',
'alignment' : 'interp_rawffi.alignment',
'charp2string' : 'interp_rawffi.charp2string',
'wcharp2unicode' : 'interp_rawffi.wcharp2unicode',
'charp2rawstring' : 'interp_rawffi.charp2rawstring',
'wcharp2rawunicode' : 'interp_rawffi.wcharp2rawunicode',
'CallbackPtr' : 'callback.W_CallbackPtr',
'_num_of_allocated_objects' : 'tracker.num_of_allocated_objects',
'get_libc' : 'interp_rawffi.get_libc',
'get_errno' : 'interp_rawffi.get_errno',
'set_errno' : 'interp_rawffi.set_errno',
'SegfaultException' : 'space.new_exception_class("_rawffi.SegfaultException")',
}
if sys.platform == 'win32':
interpleveldefs['get_last_error'] = 'interp_rawffi.get_last_error'
interpleveldefs['set_last_error'] = 'interp_rawffi.set_last_error'
appleveldefs = {
}
def buildloaders(cls):
from pypy.module._rawffi import interp_rawffi
if hasattr(interp_rawffi, 'FormatError'):
Module.interpleveldefs['FormatError'] = 'interp_rawffi.FormatError'
if hasattr(interp_rawffi, 'check_HRESULT'):
Module.interpleveldefs['check_HRESULT'] = 'interp_rawffi.check_HRESULT'
from pypy.rlib import clibffi
for name in ['FUNCFLAG_STDCALL', 'FUNCFLAG_CDECL', 'FUNCFLAG_PYTHONAPI',
'FUNCFLAG_USE_ERRNO', 'FUNCFLAG_USE_LASTERROR',
]:
if hasattr(clibffi, name):
Module.interpleveldefs[name] = "space.wrap(%r)" % getattr(clibffi, name)
super(Module, cls).buildloaders()
buildloaders = classmethod(buildloaders)
| 42.733333 | 88 | 0.640796 |
from pypy.interpreter.mixedmodule import MixedModule
from pypy.module._rawffi.interp_rawffi import W_CDLL
from pypy.rpython.lltypesystem import lltype, rffi
from pypy.module._rawffi.tracker import Tracker
import sys
class Module(MixedModule):
interpleveldefs = {
'CDLL' : 'interp_rawffi.W_CDLL',
'FuncPtr' : 'interp_rawffi.W_FuncPtr',
'Structure' : 'structure.W_Structure',
'StructureInstance' : 'structure.W_StructureInstance',
'StructureInstanceAutoFree' : 'structure.W_StructureInstanceAutoFree',
'Array' : 'array.W_Array',
'ArrayInstance' : 'array.W_ArrayInstance',
'ArrayInstanceAutoFree' : 'array.W_ArrayInstanceAutoFree',
'sizeof' : 'interp_rawffi.sizeof',
'alignment' : 'interp_rawffi.alignment',
'charp2string' : 'interp_rawffi.charp2string',
'wcharp2unicode' : 'interp_rawffi.wcharp2unicode',
'charp2rawstring' : 'interp_rawffi.charp2rawstring',
'wcharp2rawunicode' : 'interp_rawffi.wcharp2rawunicode',
'CallbackPtr' : 'callback.W_CallbackPtr',
'_num_of_allocated_objects' : 'tracker.num_of_allocated_objects',
'get_libc' : 'interp_rawffi.get_libc',
'get_errno' : 'interp_rawffi.get_errno',
'set_errno' : 'interp_rawffi.set_errno',
'SegfaultException' : 'space.new_exception_class("_rawffi.SegfaultException")',
}
if sys.platform == 'win32':
interpleveldefs['get_last_error'] = 'interp_rawffi.get_last_error'
interpleveldefs['set_last_error'] = 'interp_rawffi.set_last_error'
appleveldefs = {
}
def buildloaders(cls):
from pypy.module._rawffi import interp_rawffi
if hasattr(interp_rawffi, 'FormatError'):
Module.interpleveldefs['FormatError'] = 'interp_rawffi.FormatError'
if hasattr(interp_rawffi, 'check_HRESULT'):
Module.interpleveldefs['check_HRESULT'] = 'interp_rawffi.check_HRESULT'
from pypy.rlib import clibffi
for name in ['FUNCFLAG_STDCALL', 'FUNCFLAG_CDECL', 'FUNCFLAG_PYTHONAPI',
'FUNCFLAG_USE_ERRNO', 'FUNCFLAG_USE_LASTERROR',
]:
if hasattr(clibffi, name):
Module.interpleveldefs[name] = "space.wrap(%r)" % getattr(clibffi, name)
super(Module, cls).buildloaders()
buildloaders = classmethod(buildloaders)
| true | true |
f7fe703f6f2db29de7ef8d07447547769508e6c1 | 8,759 | py | Python | official/vision/beta/projects/simclr/heads/simclr_head.py | 1ucky40nc3/models | 1933222e454f0d2ab8582e48fcc46f26c36ace87 | [
"Apache-2.0"
] | 1 | 2021-05-22T12:50:50.000Z | 2021-05-22T12:50:50.000Z | official/vision/beta/projects/simclr/heads/simclr_head.py | DemonDamon/mask-detection-based-on-tf2odapi | 192ae544169c1230c21141c033800aa1bd94e9b6 | [
"MIT"
] | null | null | null | official/vision/beta/projects/simclr/heads/simclr_head.py | DemonDamon/mask-detection-based-on-tf2odapi | 192ae544169c1230c21141c033800aa1bd94e9b6 | [
"MIT"
] | null | null | null | # Copyright 2021 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Dense prediction heads."""
from typing import Text, Optional
import tensorflow as tf
from official.vision.beta.projects.simclr.modeling.layers import nn_blocks
regularizers = tf.keras.regularizers
layers = tf.keras.layers
@tf.keras.utils.register_keras_serializable(package='simclr')
class ProjectionHead(tf.keras.layers.Layer):
"""Projection head."""
def __init__(
self,
num_proj_layers: int = 3,
proj_output_dim: Optional[int] = None,
ft_proj_idx: int = 0,
kernel_initializer: Text = 'VarianceScaling',
kernel_regularizer: Optional[regularizers.Regularizer] = None,
bias_regularizer: Optional[regularizers.Regularizer] = None,
use_sync_bn: bool = False,
norm_momentum: float = 0.99,
norm_epsilon: float = 0.001,
**kwargs):
"""The projection head used during pretraining of SimCLR.
Args:
num_proj_layers: `int` number of Dense layers used.
proj_output_dim: `int` output dimension of projection head, i.e., output
dimension of the final layer.
ft_proj_idx: `int` index of layer to use during fine-tuning. 0 means no
projection head during fine tuning, -1 means the final layer.
kernel_initializer: kernel_initializer for convolutional layers.
kernel_regularizer: tf.keras.regularizers.Regularizer object for Conv2D.
Default to None.
bias_regularizer: tf.keras.regularizers.Regularizer object for Conv2d.
Default to None.
use_sync_bn: if True, use synchronized batch normalization.
norm_momentum: `float` normalization omentum for the moving average.
norm_epsilon: `float` small float added to variance to avoid dividing by
zero.
**kwargs: keyword arguments to be passed.
"""
super(ProjectionHead, self).__init__(**kwargs)
assert proj_output_dim is not None or num_proj_layers == 0
assert ft_proj_idx <= num_proj_layers, (num_proj_layers, ft_proj_idx)
self._proj_output_dim = proj_output_dim
self._num_proj_layers = num_proj_layers
self._ft_proj_idx = ft_proj_idx
self._kernel_initializer = kernel_initializer
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._use_sync_bn = use_sync_bn
self._norm_momentum = norm_momentum
self._norm_epsilon = norm_epsilon
self._layers = []
def get_config(self):
config = {
'proj_output_dim': self._proj_output_dim,
'num_proj_layers': self._num_proj_layers,
'ft_proj_idx': self._ft_proj_idx,
'kernel_initializer': self._kernel_initializer,
'kernel_regularizer': self._kernel_regularizer,
'bias_regularizer': self._bias_regularizer,
'use_normalization': self._use_normalization,
'norm_momentum': self._norm_momentum,
'norm_epsilon': self._norm_epsilon
}
base_config = super(ProjectionHead, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
def build(self, input_shape):
self._layers = []
if self._num_proj_layers > 0:
intermediate_dim = int(input_shape[-1])
for j in range(self._num_proj_layers):
if j != self._num_proj_layers - 1:
# for the middle layers, use bias and relu for the output.
layer = nn_blocks.DenseBN(
output_dim=intermediate_dim,
use_bias=True,
use_normalization=True,
activation='relu',
kernel_initializer=self._kernel_initializer,
kernel_regularizer=self._kernel_regularizer,
bias_regularizer=self._bias_regularizer,
use_sync_bn=self._use_sync_bn,
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
name='nl_%d' % j)
else:
# for the final layer, neither bias nor relu is used.
layer = nn_blocks.DenseBN(
output_dim=self._proj_output_dim,
use_bias=False,
use_normalization=True,
activation=None,
kernel_regularizer=self._kernel_regularizer,
kernel_initializer=self._kernel_initializer,
use_sync_bn=self._use_sync_bn,
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
name='nl_%d' % j)
self._layers.append(layer)
super(ProjectionHead, self).build(input_shape)
def call(self, inputs, training=None):
hiddens_list = [tf.identity(inputs, 'proj_head_input')]
if self._num_proj_layers == 0:
proj_head_output = inputs
proj_finetune_output = inputs
else:
for j in range(self._num_proj_layers):
hiddens = self._layers[j](hiddens_list[-1], training)
hiddens_list.append(hiddens)
proj_head_output = tf.identity(
hiddens_list[-1], 'proj_head_output')
proj_finetune_output = tf.identity(
hiddens_list[self._ft_proj_idx], 'proj_finetune_output')
# The first element is the output of the projection head.
# The second element is the input of the finetune head.
return proj_head_output, proj_finetune_output
@tf.keras.utils.register_keras_serializable(package='simclr')
class ClassificationHead(tf.keras.layers.Layer):
"""Classification Head."""
def __init__(
self,
num_classes: int,
kernel_initializer: Text = 'random_uniform',
kernel_regularizer: Optional[regularizers.Regularizer] = None,
bias_regularizer: Optional[regularizers.Regularizer] = None,
name: Text = 'head_supervised',
**kwargs):
"""The classification head used during pretraining or fine tuning.
Args:
num_classes: `int` size of the output dimension or number of classes
for classification task.
kernel_initializer: kernel_initializer for convolutional layers.
kernel_regularizer: tf.keras.regularizers.Regularizer object for Conv2D.
Default to None.
bias_regularizer: tf.keras.regularizers.Regularizer object for Conv2d.
Default to None.
name: `str`, name of the layer.
**kwargs: keyword arguments to be passed.
"""
super(ClassificationHead, self).__init__(name=name, **kwargs)
self._num_classes = num_classes
self._kernel_initializer = kernel_initializer
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._name = name
def get_config(self):
config = {
'num_classes': self._num_classes,
'kernel_initializer': self._kernel_initializer,
'kernel_regularizer': self._kernel_regularizer,
'bias_regularizer': self._bias_regularizer,
}
base_config = super(ClassificationHead, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
def build(self, input_shape):
self._dense0 = layers.Dense(
units=self._num_classes,
kernel_initializer=self._kernel_initializer,
kernel_regularizer=self._kernel_regularizer,
bias_regularizer=self._bias_regularizer,
activation=None)
super(ClassificationHead, self).build(input_shape)
def call(self, inputs, training=None):
inputs = self._dense0(inputs)
return inputs
| 40.550926 | 81 | 0.67816 |
from typing import Text, Optional
import tensorflow as tf
from official.vision.beta.projects.simclr.modeling.layers import nn_blocks
regularizers = tf.keras.regularizers
layers = tf.keras.layers
@tf.keras.utils.register_keras_serializable(package='simclr')
class ProjectionHead(tf.keras.layers.Layer):
def __init__(
self,
num_proj_layers: int = 3,
proj_output_dim: Optional[int] = None,
ft_proj_idx: int = 0,
kernel_initializer: Text = 'VarianceScaling',
kernel_regularizer: Optional[regularizers.Regularizer] = None,
bias_regularizer: Optional[regularizers.Regularizer] = None,
use_sync_bn: bool = False,
norm_momentum: float = 0.99,
norm_epsilon: float = 0.001,
**kwargs):
super(ProjectionHead, self).__init__(**kwargs)
assert proj_output_dim is not None or num_proj_layers == 0
assert ft_proj_idx <= num_proj_layers, (num_proj_layers, ft_proj_idx)
self._proj_output_dim = proj_output_dim
self._num_proj_layers = num_proj_layers
self._ft_proj_idx = ft_proj_idx
self._kernel_initializer = kernel_initializer
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._use_sync_bn = use_sync_bn
self._norm_momentum = norm_momentum
self._norm_epsilon = norm_epsilon
self._layers = []
def get_config(self):
config = {
'proj_output_dim': self._proj_output_dim,
'num_proj_layers': self._num_proj_layers,
'ft_proj_idx': self._ft_proj_idx,
'kernel_initializer': self._kernel_initializer,
'kernel_regularizer': self._kernel_regularizer,
'bias_regularizer': self._bias_regularizer,
'use_normalization': self._use_normalization,
'norm_momentum': self._norm_momentum,
'norm_epsilon': self._norm_epsilon
}
base_config = super(ProjectionHead, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
def build(self, input_shape):
self._layers = []
if self._num_proj_layers > 0:
intermediate_dim = int(input_shape[-1])
for j in range(self._num_proj_layers):
if j != self._num_proj_layers - 1:
layer = nn_blocks.DenseBN(
output_dim=intermediate_dim,
use_bias=True,
use_normalization=True,
activation='relu',
kernel_initializer=self._kernel_initializer,
kernel_regularizer=self._kernel_regularizer,
bias_regularizer=self._bias_regularizer,
use_sync_bn=self._use_sync_bn,
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
name='nl_%d' % j)
else:
layer = nn_blocks.DenseBN(
output_dim=self._proj_output_dim,
use_bias=False,
use_normalization=True,
activation=None,
kernel_regularizer=self._kernel_regularizer,
kernel_initializer=self._kernel_initializer,
use_sync_bn=self._use_sync_bn,
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
name='nl_%d' % j)
self._layers.append(layer)
super(ProjectionHead, self).build(input_shape)
def call(self, inputs, training=None):
hiddens_list = [tf.identity(inputs, 'proj_head_input')]
if self._num_proj_layers == 0:
proj_head_output = inputs
proj_finetune_output = inputs
else:
for j in range(self._num_proj_layers):
hiddens = self._layers[j](hiddens_list[-1], training)
hiddens_list.append(hiddens)
proj_head_output = tf.identity(
hiddens_list[-1], 'proj_head_output')
proj_finetune_output = tf.identity(
hiddens_list[self._ft_proj_idx], 'proj_finetune_output')
return proj_head_output, proj_finetune_output
@tf.keras.utils.register_keras_serializable(package='simclr')
class ClassificationHead(tf.keras.layers.Layer):
def __init__(
self,
num_classes: int,
kernel_initializer: Text = 'random_uniform',
kernel_regularizer: Optional[regularizers.Regularizer] = None,
bias_regularizer: Optional[regularizers.Regularizer] = None,
name: Text = 'head_supervised',
**kwargs):
super(ClassificationHead, self).__init__(name=name, **kwargs)
self._num_classes = num_classes
self._kernel_initializer = kernel_initializer
self._kernel_regularizer = kernel_regularizer
self._bias_regularizer = bias_regularizer
self._name = name
def get_config(self):
config = {
'num_classes': self._num_classes,
'kernel_initializer': self._kernel_initializer,
'kernel_regularizer': self._kernel_regularizer,
'bias_regularizer': self._bias_regularizer,
}
base_config = super(ClassificationHead, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
def build(self, input_shape):
self._dense0 = layers.Dense(
units=self._num_classes,
kernel_initializer=self._kernel_initializer,
kernel_regularizer=self._kernel_regularizer,
bias_regularizer=self._bias_regularizer,
activation=None)
super(ClassificationHead, self).build(input_shape)
def call(self, inputs, training=None):
inputs = self._dense0(inputs)
return inputs
| true | true |
f7fe706cc3d2b9e764a5ada9585376ae6d90e939 | 692 | py | Python | post/admin.py | Neknu/news-site | 39606e099f742312bc203262bb9cc17b6c8a998d | [
"Apache-2.0"
] | null | null | null | post/admin.py | Neknu/news-site | 39606e099f742312bc203262bb9cc17b6c8a998d | [
"Apache-2.0"
] | 5 | 2021-03-19T10:51:15.000Z | 2021-06-10T20:12:59.000Z | post/admin.py | danylott/news-site | 39606e099f742312bc203262bb9cc17b6c8a998d | [
"Apache-2.0"
] | null | null | null | from django.contrib import admin
from .models import Post
@admin.register(Post)
class PostAdmin(admin.ModelAdmin):
# prepopulated_fields = {'slug': ('title',)}
list_display = ['title', 'author', 'status', 'created']
fieldsets = [
('User content', {'fields': ['title', 'content', 'author']}),
('Admin info', {'fields': ['status', 'slug', 'created']}),
]
readonly_fields = ['created', 'slug']
search_fields = ['title', 'content']
list_filter = ['status', 'created', 'author']
ordering = ('created',)
admin.site.site_header = "News Site Admin"
admin.site.site_title = "Portal to post your news here"
admin.site.index_title = "News Site Admin"
| 31.454545 | 69 | 0.634393 | from django.contrib import admin
from .models import Post
@admin.register(Post)
class PostAdmin(admin.ModelAdmin):
list_display = ['title', 'author', 'status', 'created']
fieldsets = [
('User content', {'fields': ['title', 'content', 'author']}),
('Admin info', {'fields': ['status', 'slug', 'created']}),
]
readonly_fields = ['created', 'slug']
search_fields = ['title', 'content']
list_filter = ['status', 'created', 'author']
ordering = ('created',)
admin.site.site_header = "News Site Admin"
admin.site.site_title = "Portal to post your news here"
admin.site.index_title = "News Site Admin"
| true | true |
f7fe70976e3c341cbe527d9e7563942cd20a1582 | 83 | py | Python | ChangeCoordinate/__init__.py | GaryLea/ChangeCoordinate | 5a2a94270b9b3eff59163b5bf32e1d2c4c5cd7a6 | [
"MIT"
] | 10 | 2019-07-17T06:41:49.000Z | 2021-11-24T01:17:07.000Z | ChangeCoordinate/__init__.py | GaryLea/ChangeCoordinate | 5a2a94270b9b3eff59163b5bf32e1d2c4c5cd7a6 | [
"MIT"
] | null | null | null | ChangeCoordinate/__init__.py | GaryLea/ChangeCoordinate | 5a2a94270b9b3eff59163b5bf32e1d2c4c5cd7a6 | [
"MIT"
] | 7 | 2019-09-21T11:56:31.000Z | 2021-12-10T06:47:38.000Z | # -*- coding: utf-8 -*-
from ChangeCoordinate.change_coordinate import ChangeCoord | 27.666667 | 58 | 0.771084 |
from ChangeCoordinate.change_coordinate import ChangeCoord | true | true |
f7fe739bf4e1a8a8f56b8db57b3c8fdf1d39edf3 | 14,911 | py | Python | flexget/tests/conftest.py | astrotee/Flexget | 34121f79eaef2ce27dd2d37b6d1c2e8dfbf98c51 | [
"MIT"
] | 1,322 | 2015-01-01T22:00:25.000Z | 2022-03-30T05:37:46.000Z | flexget/tests/conftest.py | astrotee/Flexget | 34121f79eaef2ce27dd2d37b6d1c2e8dfbf98c51 | [
"MIT"
] | 2,384 | 2015-01-01T04:23:15.000Z | 2022-03-31T01:06:43.000Z | flexget/tests/conftest.py | soloam/Flexget | f39812981d9ab2665358d8285c7ea7758759ab8d | [
"MIT"
] | 617 | 2015-01-02T15:15:07.000Z | 2022-03-15T12:29:31.000Z | import itertools
import logging
import os
import re
import shutil
import sys
from contextlib import contextmanager
from http import client
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional
from unittest import mock
import flask
import jsonschema
import pytest
import requests
import yaml
from _pytest.logging import caplog as _caplog
from loguru import logger
from vcr import VCR
from vcr.stubs import VCRHTTPConnection, VCRHTTPSConnection
import flexget.log
from flexget import plugin
from flexget.api import api_app
from flexget.event import event
from flexget.manager import Manager, Session
from flexget.plugin import load_plugins
from flexget.task import Task, TaskAbort
from flexget.webserver import User
logger = logger.bind(name='tests')
VCR_CASSETTE_DIR = os.path.join(os.path.dirname(__file__), 'cassettes')
VCR_RECORD_MODE = os.environ.get('VCR_RECORD_MODE', 'once')
vcr = VCR(
cassette_library_dir=VCR_CASSETTE_DIR,
record_mode=VCR_RECORD_MODE,
custom_patches=(
(client, 'HTTPSConnection', VCRHTTPSConnection),
(client, 'HTTPConnection', VCRHTTPConnection),
),
)
# --- These are the public fixtures tests can ask for ---
@pytest.fixture(scope='class')
def config(request):
"""
If used inside a test class, uses the `config` class attribute of the class.
This is used by `manager` fixture, and can be parametrized.
"""
return request.cls.config
@pytest.fixture()
def manager(
request, config, caplog, monkeypatch, filecopy
): # enforce filecopy is run before manager
"""
Create a :class:`MockManager` for this test based on `config` argument.
"""
if 'tmpdir' in request.fixturenames:
config = config.replace('__tmp__', request.getfixturevalue('tmpdir').strpath)
try:
mockmanager = MockManager(config, request.cls.__name__)
except Exception:
# Since we haven't entered the test function yet, pytest won't print the logs on failure. Print them manually.
print(caplog.text)
raise
yield mockmanager
mockmanager.shutdown()
@pytest.fixture()
def execute_task(manager: Manager) -> Callable[..., Task]:
"""
A function that can be used to execute and return a named task in `config` argument.
"""
def execute(task_name: str, abort: bool = False, options: bool = None) -> Task:
"""
Use to execute one test task from config.
:param abort: If `True` expect (and require) this task to abort.
"""
logger.info('********** Running task: {} ********** ', task_name)
config = manager.config['tasks'][task_name]
task = Task(manager, task_name, config=config, options=options)
try:
if abort:
with pytest.raises(TaskAbort):
task.execute()
else:
task.execute()
finally:
try:
task.session.close()
except Exception:
pass
return task
return execute
@pytest.fixture()
def use_vcr(request, monkeypatch):
"""
This fixture is applied automatically to any test using the `online` mark. It will record and playback network
sessions using VCR.
The record mode of VCR can be set using the VCR_RECORD_MODE environment variable when running tests.
"""
if VCR_RECORD_MODE == 'off':
yield None
else:
module = request.module.__name__.split('tests.')[-1]
class_name = request.cls.__name__
cassette_name = '.'.join([module, class_name, request.function.__name__])
cassette_path = os.path.join(VCR_CASSETTE_DIR, cassette_name)
online = True
if vcr.record_mode == 'none':
online = False
elif vcr.record_mode == 'once':
online = not os.path.exists(cassette_path)
# If we are not going online, disable domain limiting during test
if not online:
logger.debug('Disabling domain limiters during VCR playback.')
monkeypatch.setattr('flexget.utils.requests.limit_domains', mock.Mock())
with vcr.use_cassette(path=cassette_path) as cassette:
yield cassette
@pytest.fixture()
def api_client(manager) -> 'APIClient':
with Session() as session:
user = session.query(User).first()
if not user:
user = User(name='flexget', password='flexget')
session.add(user)
session.commit()
return APIClient(user.token)
@pytest.fixture()
def schema_match(manager) -> Callable[[dict, Any], List[dict]]:
"""
This fixture enables verifying JSON Schema. Return a list of validation error dicts. List is empty if no errors
occurred.
"""
def match(schema: dict, response: Any) -> List[dict]:
validator = jsonschema.Draft4Validator(schema)
errors = list(validator.iter_errors(response))
return [dict(value=list(e.path), message=e.message) for e in errors]
return match
@pytest.fixture()
def link_headers(manager) -> Callable[[flask.Response], Dict[str, dict]]:
"""
Parses link headers and return them in dict form
"""
def headers(response: flask.Response) -> Dict[str, dict]:
links = {}
for link in requests.utils.parse_header_links(response.headers.get('link')):
url = link['url']
page = int(re.search(r'(?<!per_)page=(\d)', url).group(1))
links[link['rel']] = dict(url=url, page=page)
return links
return headers
@pytest.fixture(autouse=True)
def caplog(pytestconfig, _caplog):
"""
Override caplog so that we can send loguru messages to logging for compatibility.
"""
# set logging level according to pytest verbosity
level = logger.level('DEBUG')
if pytestconfig.getoption('verbose') == 1:
level = logger.level('TRACE')
elif pytestconfig.getoption('quiet', None) == 1:
level = logger.level('INFO')
class PropagateHandler(logging.Handler):
def emit(self, record):
logging.getLogger(record.name).handle(record)
handler_id = logger.add(PropagateHandler(), level=level.no, format="{message}", catch=False)
_caplog.set_level(level.no)
yield _caplog
logger.remove(handler_id)
# --- End Public Fixtures ---
def pytest_configure(config):
# register the filecopy marker
config.addinivalue_line(
'markers',
'filecopy(src, dst): mark test to copy a file from `src` to `dst` before running.',
)
config.addinivalue_line(
'markers', 'online: mark a test that goes online. VCR will automatically be used.'
)
def pytest_runtest_setup(item):
# Add the filcopy fixture to any test marked with filecopy
if item.get_closest_marker('filecopy'):
item.fixturenames.append('filecopy')
# Add the online marker to tests that will go online
if item.get_closest_marker('online'):
item.fixturenames.append('use_vcr')
else:
item.fixturenames.append('no_requests')
@pytest.fixture()
def filecopy(request):
out_files = []
for marker in request.node.iter_markers('filecopy'):
copy_list = marker.args[0] if len(marker.args) == 1 else [marker.args]
for sources, dst in copy_list:
if isinstance(sources, str):
sources = [sources]
if 'tmpdir' in request.fixturenames:
dst = dst.replace('__tmp__', request.getfixturevalue('tmpdir').strpath)
dst = Path(dst)
for f in itertools.chain(*(Path().glob(src) for src in sources)):
dest_path = dst
if dest_path.is_dir():
dest_path = dest_path / f.name
logger.debug('copying {} to {}', f, dest_path)
if not os.path.isdir(os.path.dirname(dest_path)):
os.makedirs(os.path.dirname(dest_path))
if os.path.isdir(f):
shutil.copytree(f, dest_path)
else:
shutil.copy(f, dest_path)
out_files.append(dest_path)
yield
if out_files:
for f in out_files:
try:
if os.path.isdir(f):
shutil.rmtree(f)
else:
f.unlink()
except OSError as e:
print("couldn't remove %s: %s" % (f, e))
@pytest.fixture()
def no_requests(monkeypatch):
online_funcs = ['requests.sessions.Session.request', 'http.client.HTTPConnection.request']
# Don't monkey patch HTTPSConnection if ssl not installed as it won't exist in backports
try:
import ssl # noqa
from ssl import SSLContext # noqa
online_funcs.append('http.client.HTTPSConnection.request')
except ImportError:
pass
online_funcs.extend(
['http.client.HTTPConnection.request', 'http.client.HTTPSConnection.request']
)
for func in online_funcs:
monkeypatch.setattr(
func, mock.Mock(side_effect=Exception('Online tests should use @pytest.mark.online'))
)
@pytest.fixture(scope='session', autouse=True)
def setup_once(pytestconfig, request):
# os.chdir(os.path.join(pytestconfig.rootdir.strpath, 'flexget', 'tests'))
flexget.log.initialize(True)
m = MockManager(
'tasks: {}', 'init'
) # This makes sure our template environment is set up before any tests are run
m.shutdown()
logging.getLogger().setLevel(logging.DEBUG)
load_plugins()
@pytest.fixture(autouse=True)
def chdir(pytestconfig, request):
"""
By marking test with chdir flag we will change current working directory
to that module location. Task configuration can then assume this being
location for relative paths
"""
if 'chdir' in request.fixturenames:
os.chdir(os.path.dirname(request.module.__file__))
@pytest.fixture(autouse=True)
def clear_caches():
"""Make sure cached_input, and other caches are cleared between tests."""
from flexget.utils.tools import TimedDict
TimedDict.clear_all()
class CrashReport(Exception):
def __init__(self, message: str, crash_log: str):
self.message = message
self.crash_log = crash_log
class MockManager(Manager):
unit_test = True
def __init__(self, config_text: str, config_name: str, db_uri: Optional[str] = None):
self.config_text = config_text
self._db_uri = db_uri or 'sqlite:///:memory:'
super().__init__(['execute'])
self.config_name = config_name
self.database_uri = self._db_uri
logger.debug('database_uri: {}', self.database_uri)
self.initialize()
def _init_config(self, *args, **kwargs):
"""
Override configuration loading
"""
self.config_base = os.path.dirname(os.path.abspath(sys.path[0]))
def load_config(self, *args, **kwargs):
"""
Just load our config from the text passed in on init
"""
config = yaml.safe_load(self.config_text) or {}
self.update_config(config)
@property
def conn(self):
return self.engine.connect()
# no lock files with unit testing
@contextmanager
def acquire_lock(self, **kwargs):
self._has_lock = True
yield
def release_lock(self):
pass
def crash_report(self):
# We don't want to silently swallow crash reports during unit tests
logger.opt(exception=True).error('Crash Report Traceback:')
raise CrashReport(
'Crash report created during unit test, check log for traceback.',
flexget.log.debug_buffer,
)
def shutdown(self, finish_queue=True):
super().shutdown(finish_queue=finish_queue)
self._shutdown()
# Perhaps this bit should go somewhere else... The way reruns work can be complicated, and was causing issues in
# some cases. This plugin should run on all tests in the suite, to make sure certain phases aren't getting
# called twice. https://github.com/Flexget/Flexget/issues/3254
class DoublePhaseChecker:
@staticmethod
def on_phase(task, phase):
if getattr(task, f'did_{phase}', None):
raise Exception(f'{phase} phase should not run twice')
setattr(task, f'did_{phase}', True)
def on_task_start(self, task, config):
self.on_phase(task, 'start')
def on_task_prepare(self, task, config):
self.on_phase(task, 'prepare')
def on_task_exit(self, task, config):
self.on_phase(task, 'exit')
@event('plugin.register')
def register_plugin():
plugin.register(DoublePhaseChecker, 'test_dobule_phase', api_ver=2, debug=True, builtin=True)
class APIClient:
def __init__(self, api_key: str) -> None:
self.api_key = api_key
self.client = api_app.test_client()
def _append_header(self, key, value, kwargs):
if 'headers' not in kwargs:
kwargs['headers'] = {}
kwargs['headers'][key] = value
def json_post(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.post(*args, **kwargs)
def json_put(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.put(*args, **kwargs)
def json_patch(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.patch(*args, **kwargs)
def get(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.get(*args, **kwargs)
def delete(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.delete(*args, **kwargs)
def json_delete(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.delete(*args, **kwargs)
def head(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.head(*args, **kwargs)
| 32.988938 | 118 | 0.64382 | import itertools
import logging
import os
import re
import shutil
import sys
from contextlib import contextmanager
from http import client
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional
from unittest import mock
import flask
import jsonschema
import pytest
import requests
import yaml
from _pytest.logging import caplog as _caplog
from loguru import logger
from vcr import VCR
from vcr.stubs import VCRHTTPConnection, VCRHTTPSConnection
import flexget.log
from flexget import plugin
from flexget.api import api_app
from flexget.event import event
from flexget.manager import Manager, Session
from flexget.plugin import load_plugins
from flexget.task import Task, TaskAbort
from flexget.webserver import User
logger = logger.bind(name='tests')
VCR_CASSETTE_DIR = os.path.join(os.path.dirname(__file__), 'cassettes')
VCR_RECORD_MODE = os.environ.get('VCR_RECORD_MODE', 'once')
vcr = VCR(
cassette_library_dir=VCR_CASSETTE_DIR,
record_mode=VCR_RECORD_MODE,
custom_patches=(
(client, 'HTTPSConnection', VCRHTTPSConnection),
(client, 'HTTPConnection', VCRHTTPConnection),
),
)
@pytest.fixture(scope='class')
def config(request):
return request.cls.config
@pytest.fixture()
def manager(
request, config, caplog, monkeypatch, filecopy
):
if 'tmpdir' in request.fixturenames:
config = config.replace('__tmp__', request.getfixturevalue('tmpdir').strpath)
try:
mockmanager = MockManager(config, request.cls.__name__)
except Exception:
print(caplog.text)
raise
yield mockmanager
mockmanager.shutdown()
@pytest.fixture()
def execute_task(manager: Manager) -> Callable[..., Task]:
def execute(task_name: str, abort: bool = False, options: bool = None) -> Task:
logger.info('********** Running task: {} ********** ', task_name)
config = manager.config['tasks'][task_name]
task = Task(manager, task_name, config=config, options=options)
try:
if abort:
with pytest.raises(TaskAbort):
task.execute()
else:
task.execute()
finally:
try:
task.session.close()
except Exception:
pass
return task
return execute
@pytest.fixture()
def use_vcr(request, monkeypatch):
if VCR_RECORD_MODE == 'off':
yield None
else:
module = request.module.__name__.split('tests.')[-1]
class_name = request.cls.__name__
cassette_name = '.'.join([module, class_name, request.function.__name__])
cassette_path = os.path.join(VCR_CASSETTE_DIR, cassette_name)
online = True
if vcr.record_mode == 'none':
online = False
elif vcr.record_mode == 'once':
online = not os.path.exists(cassette_path)
if not online:
logger.debug('Disabling domain limiters during VCR playback.')
monkeypatch.setattr('flexget.utils.requests.limit_domains', mock.Mock())
with vcr.use_cassette(path=cassette_path) as cassette:
yield cassette
@pytest.fixture()
def api_client(manager) -> 'APIClient':
with Session() as session:
user = session.query(User).first()
if not user:
user = User(name='flexget', password='flexget')
session.add(user)
session.commit()
return APIClient(user.token)
@pytest.fixture()
def schema_match(manager) -> Callable[[dict, Any], List[dict]]:
def match(schema: dict, response: Any) -> List[dict]:
validator = jsonschema.Draft4Validator(schema)
errors = list(validator.iter_errors(response))
return [dict(value=list(e.path), message=e.message) for e in errors]
return match
@pytest.fixture()
def link_headers(manager) -> Callable[[flask.Response], Dict[str, dict]]:
def headers(response: flask.Response) -> Dict[str, dict]:
links = {}
for link in requests.utils.parse_header_links(response.headers.get('link')):
url = link['url']
page = int(re.search(r'(?<!per_)page=(\d)', url).group(1))
links[link['rel']] = dict(url=url, page=page)
return links
return headers
@pytest.fixture(autouse=True)
def caplog(pytestconfig, _caplog):
level = logger.level('DEBUG')
if pytestconfig.getoption('verbose') == 1:
level = logger.level('TRACE')
elif pytestconfig.getoption('quiet', None) == 1:
level = logger.level('INFO')
class PropagateHandler(logging.Handler):
def emit(self, record):
logging.getLogger(record.name).handle(record)
handler_id = logger.add(PropagateHandler(), level=level.no, format="{message}", catch=False)
_caplog.set_level(level.no)
yield _caplog
logger.remove(handler_id)
def pytest_configure(config):
config.addinivalue_line(
'markers',
'filecopy(src, dst): mark test to copy a file from `src` to `dst` before running.',
)
config.addinivalue_line(
'markers', 'online: mark a test that goes online. VCR will automatically be used.'
)
def pytest_runtest_setup(item):
if item.get_closest_marker('filecopy'):
item.fixturenames.append('filecopy')
if item.get_closest_marker('online'):
item.fixturenames.append('use_vcr')
else:
item.fixturenames.append('no_requests')
@pytest.fixture()
def filecopy(request):
out_files = []
for marker in request.node.iter_markers('filecopy'):
copy_list = marker.args[0] if len(marker.args) == 1 else [marker.args]
for sources, dst in copy_list:
if isinstance(sources, str):
sources = [sources]
if 'tmpdir' in request.fixturenames:
dst = dst.replace('__tmp__', request.getfixturevalue('tmpdir').strpath)
dst = Path(dst)
for f in itertools.chain(*(Path().glob(src) for src in sources)):
dest_path = dst
if dest_path.is_dir():
dest_path = dest_path / f.name
logger.debug('copying {} to {}', f, dest_path)
if not os.path.isdir(os.path.dirname(dest_path)):
os.makedirs(os.path.dirname(dest_path))
if os.path.isdir(f):
shutil.copytree(f, dest_path)
else:
shutil.copy(f, dest_path)
out_files.append(dest_path)
yield
if out_files:
for f in out_files:
try:
if os.path.isdir(f):
shutil.rmtree(f)
else:
f.unlink()
except OSError as e:
print("couldn't remove %s: %s" % (f, e))
@pytest.fixture()
def no_requests(monkeypatch):
online_funcs = ['requests.sessions.Session.request', 'http.client.HTTPConnection.request']
# Don't monkey patch HTTPSConnection if ssl not installed as it won't exist in backports
try:
import ssl # noqa
from ssl import SSLContext # noqa
online_funcs.append('http.client.HTTPSConnection.request')
except ImportError:
pass
online_funcs.extend(
['http.client.HTTPConnection.request', 'http.client.HTTPSConnection.request']
)
for func in online_funcs:
monkeypatch.setattr(
func, mock.Mock(side_effect=Exception('Online tests should use @pytest.mark.online'))
)
@pytest.fixture(scope='session', autouse=True)
def setup_once(pytestconfig, request):
# os.chdir(os.path.join(pytestconfig.rootdir.strpath, 'flexget', 'tests'))
flexget.log.initialize(True)
m = MockManager(
'tasks: {}', 'init'
) # This makes sure our template environment is set up before any tests are run
m.shutdown()
logging.getLogger().setLevel(logging.DEBUG)
load_plugins()
@pytest.fixture(autouse=True)
def chdir(pytestconfig, request):
if 'chdir' in request.fixturenames:
os.chdir(os.path.dirname(request.module.__file__))
@pytest.fixture(autouse=True)
def clear_caches():
from flexget.utils.tools import TimedDict
TimedDict.clear_all()
class CrashReport(Exception):
def __init__(self, message: str, crash_log: str):
self.message = message
self.crash_log = crash_log
class MockManager(Manager):
unit_test = True
def __init__(self, config_text: str, config_name: str, db_uri: Optional[str] = None):
self.config_text = config_text
self._db_uri = db_uri or 'sqlite:///:memory:'
super().__init__(['execute'])
self.config_name = config_name
self.database_uri = self._db_uri
logger.debug('database_uri: {}', self.database_uri)
self.initialize()
def _init_config(self, *args, **kwargs):
self.config_base = os.path.dirname(os.path.abspath(sys.path[0]))
def load_config(self, *args, **kwargs):
config = yaml.safe_load(self.config_text) or {}
self.update_config(config)
@property
def conn(self):
return self.engine.connect()
# no lock files with unit testing
@contextmanager
def acquire_lock(self, **kwargs):
self._has_lock = True
yield
def release_lock(self):
pass
def crash_report(self):
# We don't want to silently swallow crash reports during unit tests
logger.opt(exception=True).error('Crash Report Traceback:')
raise CrashReport(
'Crash report created during unit test, check log for traceback.',
flexget.log.debug_buffer,
)
def shutdown(self, finish_queue=True):
super().shutdown(finish_queue=finish_queue)
self._shutdown()
# called twice. https://github.com/Flexget/Flexget/issues/3254
class DoublePhaseChecker:
@staticmethod
def on_phase(task, phase):
if getattr(task, f'did_{phase}', None):
raise Exception(f'{phase} phase should not run twice')
setattr(task, f'did_{phase}', True)
def on_task_start(self, task, config):
self.on_phase(task, 'start')
def on_task_prepare(self, task, config):
self.on_phase(task, 'prepare')
def on_task_exit(self, task, config):
self.on_phase(task, 'exit')
@event('plugin.register')
def register_plugin():
plugin.register(DoublePhaseChecker, 'test_dobule_phase', api_ver=2, debug=True, builtin=True)
class APIClient:
def __init__(self, api_key: str) -> None:
self.api_key = api_key
self.client = api_app.test_client()
def _append_header(self, key, value, kwargs):
if 'headers' not in kwargs:
kwargs['headers'] = {}
kwargs['headers'][key] = value
def json_post(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.post(*args, **kwargs)
def json_put(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.put(*args, **kwargs)
def json_patch(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.patch(*args, **kwargs)
def get(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.get(*args, **kwargs)
def delete(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.delete(*args, **kwargs)
def json_delete(self, *args, **kwargs) -> flask.Response:
self._append_header('Content-Type', 'application/json', kwargs)
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.delete(*args, **kwargs)
def head(self, *args, **kwargs) -> flask.Response:
if kwargs.get('auth', True):
self._append_header('Authorization', 'Token %s' % self.api_key, kwargs)
return self.client.head(*args, **kwargs)
| true | true |
f7fe7452ae0237857a9b68aa5dbd9cc51bd907e4 | 3,984 | py | Python | Image/download.py | c11/earthengine-py-notebooks | 144b57e4d952da095ba73c3cc8ce2f36291162ff | [
"MIT"
] | 1 | 2020-05-31T14:19:59.000Z | 2020-05-31T14:19:59.000Z | Image/download.py | c11/earthengine-py-notebooks | 144b57e4d952da095ba73c3cc8ce2f36291162ff | [
"MIT"
] | null | null | null | Image/download.py | c11/earthengine-py-notebooks | 144b57e4d952da095ba73c3cc8ce2f36291162ff | [
"MIT"
] | null | null | null | # %%
"""
<table class="ee-notebook-buttons" align="left">
<td><a target="_blank" href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/Image/download.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
<td><a target="_blank" href="https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Image/download.ipynb"><img width=26px src="https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png" />Notebook Viewer</a></td>
<td><a target="_blank" href="https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Image/download.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" /> Run in Google Colab</a></td>
</table>
"""
# %%
"""
## Install Earth Engine API and geemap
Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geemap](https://github.com/giswqs/geemap). The **geemap** Python package is built upon the [ipyleaflet](https://github.com/jupyter-widgets/ipyleaflet) and [folium](https://github.com/python-visualization/folium) packages and implements several methods for interacting with Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, and `Map.centerObject()`.
The following script checks if the geemap package has been installed. If not, it will install geemap, which automatically installs its [dependencies](https://github.com/giswqs/geemap#dependencies), including earthengine-api, folium, and ipyleaflet.
**Important note**: A key difference between folium and ipyleaflet is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only ([source](https://blog.jupyter.org/interactive-gis-in-jupyter-with-ipyleaflet-52f9657fa7a)). Note that [Google Colab](https://colab.research.google.com/) currently does not support ipyleaflet ([source](https://github.com/googlecolab/colabtools/issues/60#issuecomment-596225619)). Therefore, if you are using geemap with Google Colab, you should use [`import geemap.eefolium`](https://github.com/giswqs/geemap/blob/master/geemap/eefolium.py). If you are using geemap with [binder](https://mybinder.org/) or a local Jupyter notebook server, you can use [`import geemap`](https://github.com/giswqs/geemap/blob/master/geemap/geemap.py), which provides more functionalities for capturing user input (e.g., mouse-clicking and moving).
"""
# %%
# Installs geemap package
import subprocess
try:
import geemap
except ImportError:
print('geemap package not installed. Installing ...')
subprocess.check_call(["python", '-m', 'pip', 'install', 'geemap'])
# Checks whether this notebook is running on Google Colab
try:
import google.colab
import geemap.eefolium as emap
except:
import geemap as emap
# Authenticates and initializes Earth Engine
import ee
try:
ee.Initialize()
except Exception as e:
ee.Authenticate()
ee.Initialize()
# %%
"""
## Create an interactive map
The default basemap is `Google Satellite`. [Additional basemaps](https://github.com/giswqs/geemap/blob/master/geemap/geemap.py#L13) can be added using the `Map.add_basemap()` function.
"""
# %%
Map = emap.Map(center=[40,-100], zoom=4)
Map.add_basemap('ROADMAP') # Add Google Map
Map
# %%
"""
## Add Earth Engine Python script
"""
# %%
# Add Earth Engine dataset
# Get a download URL for an image.
image1 = ee.Image('srtm90_v4')
path = image1.getDownloadUrl({
'scale': 30,
'crs': 'EPSG:4326',
'region': '[[-120, 35], [-119, 35], [-119, 34], [-120, 34]]'
})
print(path)
vis_params = {'min': 0, 'max': 3000}
Map.addLayer(image1, vis_params)
# %%
"""
## Display Earth Engine data layers
"""
# %%
Map.addLayerControl() # This line is not needed for ipyleaflet-based Map.
Map | 48 | 1,021 | 0.735944 |
import subprocess
try:
import geemap
except ImportError:
print('geemap package not installed. Installing ...')
subprocess.check_call(["python", '-m', 'pip', 'install', 'geemap'])
try:
import google.colab
import geemap.eefolium as emap
except:
import geemap as emap
import ee
try:
ee.Initialize()
except Exception as e:
ee.Authenticate()
ee.Initialize()
Map = emap.Map(center=[40,-100], zoom=4)
Map.add_basemap('ROADMAP')
Map
image1 = ee.Image('srtm90_v4')
path = image1.getDownloadUrl({
'scale': 30,
'crs': 'EPSG:4326',
'region': '[[-120, 35], [-119, 35], [-119, 34], [-120, 34]]'
})
print(path)
vis_params = {'min': 0, 'max': 3000}
Map.addLayer(image1, vis_params)
Map.addLayerControl()
Map | true | true |
f7fe74a15292c234d13cbd919f84484b57430357 | 580 | py | Python | molecule/common/tests/test_pacemaker.py | incubateur-pe/pacemaker | 4b4bd65be4f87ba147a4a5a0739c0689e6ec5671 | [
"BSD-3-Clause"
] | null | null | null | molecule/common/tests/test_pacemaker.py | incubateur-pe/pacemaker | 4b4bd65be4f87ba147a4a5a0739c0689e6ec5671 | [
"BSD-3-Clause"
] | null | null | null | molecule/common/tests/test_pacemaker.py | incubateur-pe/pacemaker | 4b4bd65be4f87ba147a4a5a0739c0689e6ec5671 | [
"BSD-3-Clause"
] | null | null | null | """Role testing files using testinfra."""
import pytest
@pytest.mark.parametrize("name", [
"pcsd",
"corosync",
"pacemaker"
])
def test_cluster_services(host, name):
service = host.service(name)
# assert service.is_valid
assert service.is_enabled
assert service.is_running
def test_cluster_status(host):
cmd = host.run("pcs status")
assert "2 nodes configured" in cmd.stdout
assert "Online: [ vm-1 vm-2 ]" in cmd.stdout
def test_resource_listening(host):
socket = host.socket('tcp://0.0.0.0:8080')
assert socket.is_listening
| 20 | 48 | 0.684483 | import pytest
@pytest.mark.parametrize("name", [
"pcsd",
"corosync",
"pacemaker"
])
def test_cluster_services(host, name):
service = host.service(name)
assert service.is_enabled
assert service.is_running
def test_cluster_status(host):
cmd = host.run("pcs status")
assert "2 nodes configured" in cmd.stdout
assert "Online: [ vm-1 vm-2 ]" in cmd.stdout
def test_resource_listening(host):
socket = host.socket('tcp://0.0.0.0:8080')
assert socket.is_listening
| true | true |
f7fe75f8e1e49e4cb85cb1a2e452d03481eb2601 | 6,044 | py | Python | BouncingBall014.py | BrianDunneKK/BouncingBall | bd491e4615b86c16179c7aac6c5e348ff85122b8 | [
"MIT"
] | null | null | null | BouncingBall014.py | BrianDunneKK/BouncingBall | bd491e4615b86c16179c7aac6c5e348ff85122b8 | [
"MIT"
] | null | null | null | BouncingBall014.py | BrianDunneKK/BouncingBall | bd491e4615b86c16179c7aac6c5e348ff85122b8 | [
"MIT"
] | null | null | null | import cdkk
import pygame
import random
# --------------------------------------------------
class Sprite_Ball(cdkk.Sprite):
files = ["ball_red.png", "ball_yellow.png", "ball_green.png", "ball_brown.png",
"ball_blue.png", "ball_pink.png", "ball_black.png"]
def __init__(self, value, limits):
super().__init__()
self.load_image_from_file(self.files[value - 1])
self.rect.left = random.randint(limits.width * 0.2, limits.width * 0.8)
self.rect.top = 10
speed = value * 3 + 5
angle = random.randint(45, 135)
self.rect.set_speed_angle(speed, angle)
self.rect.bounce_cor = self.rect.perfect_bounce
bounce_event = cdkk.EventManager.gc_event(
"Boundary", ball_id=self.uuid)
self.rect.add_limit(cdkk.Physics_Limit(
limits, cdkk.LIMIT_KEEP_INSIDE, cdkk.AT_LIMIT_BOUNCE, bounce_event))
self.rect.go()
def update(self):
super().update()
self.rect.move_physics()
# --------------------------------------------------
class Manager_Ball(cdkk.SpriteManager):
def __init__(self, limits, total, at_a_time):
super().__init__("Ball Manager")
self._limits = limits
self._at_a_time = at_a_time
self._total = total
self.balls_left = total
self.add_balls()
def add_balls(self):
current_balls = len(self.sprites())
new_balls = self._at_a_time - current_balls
if new_balls > self.balls_left:
new_balls = self.balls_left
for i in range(new_balls):
value = random.randint(1, len(Sprite_Ball.files))
ball = Sprite_Ball(value, self._limits)
self.add(ball)
self.balls_left -= 1
def event(self, e):
dealt_with = super().event(e)
if not dealt_with and e.type == cdkk.EVENT_GAME_CONTROL:
if e.action == "Boundary":
if e.at_limit_y & cdkk.AT_LIMIT_BOTTOM:
self.kill_uuid(e.info["ball_id"])
self.add_balls()
return dealt_with
def check_bat_hits(self, bat):
for ball in self.sprites():
ball.rect.dynamic_limit(cdkk.Physics_Limit(
bat.rect, cdkk.LIMIT_KEEP_OUTSIDE, cdkk.AT_LIMIT_Y_BOUNCE_Y))
# --------------------------------------------------
class Sprite_Bat(cdkk.Sprite):
def __init__(self, limits):
super().__init__("Bat")
self.load_image_from_file("bat.png")
self.rect.centerx = limits.width / 2
self.rect.top = limits.height * 0.9
self.rect.add_limit(cdkk.Physics_Limit(
limits, cdkk.LIMIT_KEEP_INSIDE, cdkk.AT_LIMIT_X_HOLD_POS_X))
# --------------------------------------------------
class Manager_Bat(cdkk.SpriteManager):
def __init__(self, limits, name="Bat Manager"):
super().__init__(name)
self._bat = Sprite_Bat(limits)
self.add(self._bat)
def event(self, e):
dealt_with = False
if e.type == cdkk.EVENT_GAME_CONTROL:
if e.action == "MouseMotion":
x, y = e.info["pos"]
self._bat.rect.move_to(x, None)
dealt_with = True
return dealt_with
# --------------------------------------------------
class Manager_Scoreboard(cdkk.SpriteManager):
def __init__(self, limits, game_time):
super().__init__("Scoreboard Manager")
self._game_time = game_time
text_style = {"fillcolour": None, "outlinecolour": None,
"align_horiz": "L", "width": 200, "height": 35}
tb_score = cdkk.Sprite_TextBox("Score", style=text_style)
tb_score.set_text_format("Score: {0}", 0)
tb_score.rect.midleft = (limits.width * 0.1, limits.height * 0.05)
self.add(tb_score)
self.score = 0
self._timer = cdkk.Timer(self._game_time, cdkk.EVENT_GAME_TIMER_1)
tb_time_left = cdkk.Sprite_TextBox("Time Left", style=text_style)
tb_time_left.set_text_format("Time Left: {0:0.1f}", 0)
tb_time_left.rect.center = (limits.width * 0.45, limits.height * 0.05)
self.add(tb_time_left)
tb_balls_left = cdkk.Sprite_TextBox("Balls Left", style=text_style)
tb_balls_left.set_text_format("Balls Left: {0}", 0)
tb_balls_left.rect.midright = (
limits.width * 0.85, limits.height * 0.05)
self.add(tb_balls_left)
self.balls_left = 0
@property
def score(self):
return self._score
@score.setter
def score(self, new_score):
self._score = new_score
self.sprite("Score").set_text(self.score)
@property
def balls_left(self):
return self._balls_left
@balls_left.setter
def balls_left(self, new_balls_left):
self._balls_left = new_balls_left
self.sprite("Balls Left").set_text(self.balls_left)
def update(self):
super().update()
self.sprite("Time Left").set_text(self._timer.time_left)
# --------------------------------------------------
class MyGame(cdkk.PyGameApp):
def init(self):
super().init()
self._ball_mgr = Manager_Ball(self.boundary, 10, 3)
self.add_sprite_mgr(self._ball_mgr)
self._bat_mgr = Manager_Bat(self.boundary)
self.add_sprite_mgr(self._bat_mgr)
self._scoreboard_mgr = Manager_Scoreboard(self.boundary, 15)
self.add_sprite_mgr(self._scoreboard_mgr)
key_map = {
pygame.K_q: "Quit",
pygame.K_s: "StartGame"
}
self.event_mgr.event_map(key_event_map=key_map)
def update(self):
super().update()
bat = self.sprite("Bat Manager", "Bat")
self._ball_mgr.check_bat_hits(bat)
self._scoreboard_mgr.balls_left = self._ball_mgr.balls_left
app_config = {
"width": 1200,
"height": 920,
"background_fill": "burlywood",
"caption": "Bouncing Ball",
"image_path": "BouncingBall\\Images\\",
"auto_start": False,
}
MyGame(app_config).execute()
| 32.320856 | 83 | 0.587359 | import cdkk
import pygame
import random
class Sprite_Ball(cdkk.Sprite):
files = ["ball_red.png", "ball_yellow.png", "ball_green.png", "ball_brown.png",
"ball_blue.png", "ball_pink.png", "ball_black.png"]
def __init__(self, value, limits):
super().__init__()
self.load_image_from_file(self.files[value - 1])
self.rect.left = random.randint(limits.width * 0.2, limits.width * 0.8)
self.rect.top = 10
speed = value * 3 + 5
angle = random.randint(45, 135)
self.rect.set_speed_angle(speed, angle)
self.rect.bounce_cor = self.rect.perfect_bounce
bounce_event = cdkk.EventManager.gc_event(
"Boundary", ball_id=self.uuid)
self.rect.add_limit(cdkk.Physics_Limit(
limits, cdkk.LIMIT_KEEP_INSIDE, cdkk.AT_LIMIT_BOUNCE, bounce_event))
self.rect.go()
def update(self):
super().update()
self.rect.move_physics()
class Manager_Ball(cdkk.SpriteManager):
def __init__(self, limits, total, at_a_time):
super().__init__("Ball Manager")
self._limits = limits
self._at_a_time = at_a_time
self._total = total
self.balls_left = total
self.add_balls()
def add_balls(self):
current_balls = len(self.sprites())
new_balls = self._at_a_time - current_balls
if new_balls > self.balls_left:
new_balls = self.balls_left
for i in range(new_balls):
value = random.randint(1, len(Sprite_Ball.files))
ball = Sprite_Ball(value, self._limits)
self.add(ball)
self.balls_left -= 1
def event(self, e):
dealt_with = super().event(e)
if not dealt_with and e.type == cdkk.EVENT_GAME_CONTROL:
if e.action == "Boundary":
if e.at_limit_y & cdkk.AT_LIMIT_BOTTOM:
self.kill_uuid(e.info["ball_id"])
self.add_balls()
return dealt_with
def check_bat_hits(self, bat):
for ball in self.sprites():
ball.rect.dynamic_limit(cdkk.Physics_Limit(
bat.rect, cdkk.LIMIT_KEEP_OUTSIDE, cdkk.AT_LIMIT_Y_BOUNCE_Y))
class Sprite_Bat(cdkk.Sprite):
def __init__(self, limits):
super().__init__("Bat")
self.load_image_from_file("bat.png")
self.rect.centerx = limits.width / 2
self.rect.top = limits.height * 0.9
self.rect.add_limit(cdkk.Physics_Limit(
limits, cdkk.LIMIT_KEEP_INSIDE, cdkk.AT_LIMIT_X_HOLD_POS_X))
class Manager_Bat(cdkk.SpriteManager):
def __init__(self, limits, name="Bat Manager"):
super().__init__(name)
self._bat = Sprite_Bat(limits)
self.add(self._bat)
def event(self, e):
dealt_with = False
if e.type == cdkk.EVENT_GAME_CONTROL:
if e.action == "MouseMotion":
x, y = e.info["pos"]
self._bat.rect.move_to(x, None)
dealt_with = True
return dealt_with
class Manager_Scoreboard(cdkk.SpriteManager):
def __init__(self, limits, game_time):
super().__init__("Scoreboard Manager")
self._game_time = game_time
text_style = {"fillcolour": None, "outlinecolour": None,
"align_horiz": "L", "width": 200, "height": 35}
tb_score = cdkk.Sprite_TextBox("Score", style=text_style)
tb_score.set_text_format("Score: {0}", 0)
tb_score.rect.midleft = (limits.width * 0.1, limits.height * 0.05)
self.add(tb_score)
self.score = 0
self._timer = cdkk.Timer(self._game_time, cdkk.EVENT_GAME_TIMER_1)
tb_time_left = cdkk.Sprite_TextBox("Time Left", style=text_style)
tb_time_left.set_text_format("Time Left: {0:0.1f}", 0)
tb_time_left.rect.center = (limits.width * 0.45, limits.height * 0.05)
self.add(tb_time_left)
tb_balls_left = cdkk.Sprite_TextBox("Balls Left", style=text_style)
tb_balls_left.set_text_format("Balls Left: {0}", 0)
tb_balls_left.rect.midright = (
limits.width * 0.85, limits.height * 0.05)
self.add(tb_balls_left)
self.balls_left = 0
@property
def score(self):
return self._score
@score.setter
def score(self, new_score):
self._score = new_score
self.sprite("Score").set_text(self.score)
@property
def balls_left(self):
return self._balls_left
@balls_left.setter
def balls_left(self, new_balls_left):
self._balls_left = new_balls_left
self.sprite("Balls Left").set_text(self.balls_left)
def update(self):
super().update()
self.sprite("Time Left").set_text(self._timer.time_left)
class MyGame(cdkk.PyGameApp):
def init(self):
super().init()
self._ball_mgr = Manager_Ball(self.boundary, 10, 3)
self.add_sprite_mgr(self._ball_mgr)
self._bat_mgr = Manager_Bat(self.boundary)
self.add_sprite_mgr(self._bat_mgr)
self._scoreboard_mgr = Manager_Scoreboard(self.boundary, 15)
self.add_sprite_mgr(self._scoreboard_mgr)
key_map = {
pygame.K_q: "Quit",
pygame.K_s: "StartGame"
}
self.event_mgr.event_map(key_event_map=key_map)
def update(self):
super().update()
bat = self.sprite("Bat Manager", "Bat")
self._ball_mgr.check_bat_hits(bat)
self._scoreboard_mgr.balls_left = self._ball_mgr.balls_left
app_config = {
"width": 1200,
"height": 920,
"background_fill": "burlywood",
"caption": "Bouncing Ball",
"image_path": "BouncingBall\\Images\\",
"auto_start": False,
}
MyGame(app_config).execute()
| true | true |
f7fe760bdb51e989ee04ce549c78f9ce71ef5afe | 2,976 | py | Python | examples/config/settings.py | oliver-zhou/django-templated-mail | bcadd81e414aa53ba27dd42030bb85896688dc09 | [
"MIT"
] | 89 | 2017-09-19T10:04:51.000Z | 2022-02-10T08:29:40.000Z | examples/config/settings.py | oliver-zhou/django-templated-mail | bcadd81e414aa53ba27dd42030bb85896688dc09 | [
"MIT"
] | 21 | 2018-01-02T12:21:18.000Z | 2022-02-23T11:50:08.000Z | examples/config/settings.py | oliver-zhou/django-templated-mail | bcadd81e414aa53ba27dd42030bb85896688dc09 | [
"MIT"
] | 18 | 2018-01-17T11:01:31.000Z | 2021-12-17T03:39:36.000Z | import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '()!xq2ufm%j@n^!v^p08&w87vvg)rk^=aoj8u1(4xho5iuh-)l'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'templated_mail',
'simple',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'config.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': ['templates'],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'config.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
EMAIL_BACKEND = 'django.core.mail.backends.console.EmailBackend'
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.'
'UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
| 25.220339 | 79 | 0.672379 | import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
SECRET_KEY = '()!xq2ufm%j@n^!v^p08&w87vvg)rk^=aoj8u1(4xho5iuh-)l'
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'templated_mail',
'simple',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'config.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': ['templates'],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'config.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
EMAIL_BACKEND = 'django.core.mail.backends.console.EmailBackend'
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.'
'UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.'
'NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
| true | true |
f7fe76988824699de105fb6240a54558dbfcb8b2 | 3,931 | py | Python | tests/modules/test_macho.py | CLEAR-seclab/viper | 58189220119a85c7a660f160cc664822de2c8412 | [
"BSD-3-Clause"
] | 2 | 2015-12-17T20:25:09.000Z | 2017-10-08T19:14:57.000Z | tests/modules/test_macho.py | detrojones/viper | 045e0952552fe29bb5e9780568486b36fd12e9ab | [
"BSD-3-Clause"
] | 1 | 2015-01-05T18:07:13.000Z | 2015-01-07T21:43:57.000Z | tests/modules/test_macho.py | detrojones/viper | 045e0952552fe29bb5e9780568486b36fd12e9ab | [
"BSD-3-Clause"
] | 3 | 2017-10-18T00:56:53.000Z | 2020-05-24T09:38:54.000Z | # -*- coding: utf-8 -*-
# This file is part of Viper - https://github.com/viper-framework/viper
# See the file 'LICENSE' for copying permission.
import os
import re
import pytest
from tests.conftest import FIXTURE_DIR
from viper.modules.macho import Macho, HAVE_MACHO
from viper.common.abstracts import Module
from viper.common.abstracts import ArgumentErrorCallback
from viper.core.session import __sessions__
class TestMacho:
def teardown_method(self):
__sessions__.close()
def test_init(self):
instance = Macho()
assert isinstance(instance, Macho)
assert isinstance(instance, Module)
def test_have_macho(self):
assert HAVE_MACHO is True
def test_args_exception(self):
instance = Macho()
with pytest.raises(ArgumentErrorCallback) as excinfo:
instance.parser.parse_args(["-h"])
excinfo.match(r".*Get Macho OSX Headers.*")
@pytest.mark.usefixtures("cleandir")
def test_no_session(self, capsys):
instance = Macho()
instance.command_line = ["-a"]
instance.run()
out, err = capsys.readouterr()
assert re.search(r".*No open session.*", out)
@pytest.mark.parametrize("filename", ["whoami.exe"])
def test_no_macho_file(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-hd"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Not a Mach-O file.*", lines[1])
@pytest.mark.parametrize("filename", ["MachO-OSX-x86-ls"])
def test_no_argument(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Session opened on.*", lines[0])
@pytest.mark.parametrize("filename,magic,cputype", [
("MachO-OSX-x86-ls", "0xfeedface - 32 bits", "0x7 - i386"),
("MachO-OSX-x64-ls", "0xfeedfacf - 64 bits", "0x1000007 - x86_64")
])
def test_headers(self, capsys, filename, magic, cputype):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-hd"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Headers", lines[1])
assert re.search(r".*{}.*".format(magic), out)
assert re.search(r".*{}.*".format(cputype), out)
@pytest.mark.parametrize("filename,amount_segments", [
("MachO-OSX-x86-ls", 4)
])
def test_segments(self, capsys, filename, amount_segments):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-sg"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Segments \({}\)".format(amount_segments), lines[1])
@pytest.mark.parametrize("filename,amount_commands", [
("MachO-OSX-x86-ls", 12),
])
def test_load_commands(self, capsys, filename, amount_commands):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-lc"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Load Commands \({}\)".format(amount_commands), lines[1])
@pytest.mark.parametrize("filename", ["MachO-OSX-x86-ls"])
def test_all(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-a"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Headers", lines[1])
| 31.198413 | 85 | 0.622488 |
import os
import re
import pytest
from tests.conftest import FIXTURE_DIR
from viper.modules.macho import Macho, HAVE_MACHO
from viper.common.abstracts import Module
from viper.common.abstracts import ArgumentErrorCallback
from viper.core.session import __sessions__
class TestMacho:
def teardown_method(self):
__sessions__.close()
def test_init(self):
instance = Macho()
assert isinstance(instance, Macho)
assert isinstance(instance, Module)
def test_have_macho(self):
assert HAVE_MACHO is True
def test_args_exception(self):
instance = Macho()
with pytest.raises(ArgumentErrorCallback) as excinfo:
instance.parser.parse_args(["-h"])
excinfo.match(r".*Get Macho OSX Headers.*")
@pytest.mark.usefixtures("cleandir")
def test_no_session(self, capsys):
instance = Macho()
instance.command_line = ["-a"]
instance.run()
out, err = capsys.readouterr()
assert re.search(r".*No open session.*", out)
@pytest.mark.parametrize("filename", ["whoami.exe"])
def test_no_macho_file(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-hd"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Not a Mach-O file.*", lines[1])
@pytest.mark.parametrize("filename", ["MachO-OSX-x86-ls"])
def test_no_argument(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Session opened on.*", lines[0])
@pytest.mark.parametrize("filename,magic,cputype", [
("MachO-OSX-x86-ls", "0xfeedface - 32 bits", "0x7 - i386"),
("MachO-OSX-x64-ls", "0xfeedfacf - 64 bits", "0x1000007 - x86_64")
])
def test_headers(self, capsys, filename, magic, cputype):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-hd"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Headers", lines[1])
assert re.search(r".*{}.*".format(magic), out)
assert re.search(r".*{}.*".format(cputype), out)
@pytest.mark.parametrize("filename,amount_segments", [
("MachO-OSX-x86-ls", 4)
])
def test_segments(self, capsys, filename, amount_segments):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-sg"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Segments \({}\)".format(amount_segments), lines[1])
@pytest.mark.parametrize("filename,amount_commands", [
("MachO-OSX-x86-ls", 12),
])
def test_load_commands(self, capsys, filename, amount_commands):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-lc"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Load Commands \({}\)".format(amount_commands), lines[1])
@pytest.mark.parametrize("filename", ["MachO-OSX-x86-ls"])
def test_all(self, capsys, filename):
__sessions__.new(os.path.join(FIXTURE_DIR, filename))
instance = Macho()
instance.command_line = ["-a"]
instance.run()
out, err = capsys.readouterr()
lines = out.split("\n")
assert re.search(r".*Headers", lines[1])
| true | true |
f7fe76ab269b44c25fcc74c3b8d338ad3b600d39 | 4,439 | py | Python | stateoftheuniverse/widgets/constellations.py | Pratere/stateoftheuniverse | 2ad341cb9f0a45b8a624ba23a2dc3224e03de455 | [
"MIT"
] | null | null | null | stateoftheuniverse/widgets/constellations.py | Pratere/stateoftheuniverse | 2ad341cb9f0a45b8a624ba23a2dc3224e03de455 | [
"MIT"
] | null | null | null | stateoftheuniverse/widgets/constellations.py | Pratere/stateoftheuniverse | 2ad341cb9f0a45b8a624ba23a2dc3224e03de455 | [
"MIT"
] | null | null | null | """
Get a list of constellations that will be visible from a location on the
earth as a given time.
"""
# -------------------------
# Imports
# ------------------------
from astropy.utils.exceptions import AstropyDeprecationWarning
import warnings
from datetime import datetime as dt
from astropy import units as u
from astropy.coordinates import SkyCoord, AltAz, get_constellation, EarthLocation
from astropy.time import Time
import numpy as np
from typing import Optional
from stateoftheuniverse.widgets.prototypes import WidgetPrototype
from stateoftheuniverse.widgets.utils import stringdecorator
warnings.filterwarnings('ignore', category=AstropyDeprecationWarning)
# -------------------------
# Function Definitions
# ------------------------
class ConstellationsWidget(WidgetPrototype):
"""
A widget that collects and holds list of constellations which will
be in the sky at the users location at midnight
Args:
longitude: the longitude of the user
latitude: the latitude of the user
datetime: a datetime.datetime object in UTC
"""
def __init__(self,
longitude: Optional[float] = None,
latitude: Optional[float] = None,
datetime: Optional[dt] = None):
super().__init__(longitude=longitude,
latitude=latitude,
datetime=datetime)
self.height = 1500
self.location = EarthLocation.from_geodetic(lon=self.longitude * u.degree,
lat=self.latitude * u.degree,
height=self.height * u.meter)
if self.datetime is None:
self.datetime = dt.now()
self.datetime = str(self.datetime)[:10] + ' 23:00:00'
self.time = Time(self.datetime)
else:
self.time = Time(str(self.datetime)[:10]+' 23:00:00')
self.alt, self.az = np.meshgrid(np.arange(5, 85, 5), np.arange(5, 355, 5))
self.alt = self.alt.ravel()
self.az = self.az.ravel()
self.dome = SkyCoord(az=self.az * u.degree,
alt=self.alt * u.degree,
frame=AltAz(obstime=self.time, location=self.location))
self.constellations = None
self.name = "TONIGHT'S CONSTELLATIONS"
self.dict_name = "consts"
def get_data(self):
"""
Update and store list of tonight's constellations, based on the users
location. Uses a matrix of points on the sky to retrieve constellations
that they are located in.
"""
self.constellations = list(set(get_constellation(self.dome)))
self.constellations.sort()
return self.constellations
@stringdecorator
def get_string(self):
"""
Return formatted output string of visible constellations.
"""
if self.constellations is None:
self.get_data()
string = '\n\t'.join(self.constellations)
return string
def check_const(self, const_check):
"""
Return bool or list of bools for if a given constellation will be in visible on data.
"""
if self.constellations is None:
self.get_data()
if type(const_check) == str:
if const_check.lower() in [constellation.lower() for constellation in self.constellations]:
return f"{const_check} will be visible tonight."
else:
return f"{const_check} will not be visible tonight."
elif type(const_check) == list:
avail_consts = []
for const in const_check:
if const.lower() in [constellation.lower() for constellation in self.constellations]:
avail_consts.append(f"{const} will be visible tonight.")
else:
avail_consts.append(f"{const} will not be visible tonight.")
return avail_consts
else:
print("Function takes string or list of stings")
return False
if __name__ == "__main__":
const = ConstellationsWidget(longitude=52.2053, latitude=0.1218)
print(const.get_string())
for constellation in const.constellations:
if not const.check_const(str(constellation)):
print("Failed to find " + constellation)
print(const.check_const(const.constellations))
| 35.230159 | 103 | 0.601487 |
from astropy.utils.exceptions import AstropyDeprecationWarning
import warnings
from datetime import datetime as dt
from astropy import units as u
from astropy.coordinates import SkyCoord, AltAz, get_constellation, EarthLocation
from astropy.time import Time
import numpy as np
from typing import Optional
from stateoftheuniverse.widgets.prototypes import WidgetPrototype
from stateoftheuniverse.widgets.utils import stringdecorator
warnings.filterwarnings('ignore', category=AstropyDeprecationWarning)
class ConstellationsWidget(WidgetPrototype):
def __init__(self,
longitude: Optional[float] = None,
latitude: Optional[float] = None,
datetime: Optional[dt] = None):
super().__init__(longitude=longitude,
latitude=latitude,
datetime=datetime)
self.height = 1500
self.location = EarthLocation.from_geodetic(lon=self.longitude * u.degree,
lat=self.latitude * u.degree,
height=self.height * u.meter)
if self.datetime is None:
self.datetime = dt.now()
self.datetime = str(self.datetime)[:10] + ' 23:00:00'
self.time = Time(self.datetime)
else:
self.time = Time(str(self.datetime)[:10]+' 23:00:00')
self.alt, self.az = np.meshgrid(np.arange(5, 85, 5), np.arange(5, 355, 5))
self.alt = self.alt.ravel()
self.az = self.az.ravel()
self.dome = SkyCoord(az=self.az * u.degree,
alt=self.alt * u.degree,
frame=AltAz(obstime=self.time, location=self.location))
self.constellations = None
self.name = "TONIGHT'S CONSTELLATIONS"
self.dict_name = "consts"
def get_data(self):
self.constellations = list(set(get_constellation(self.dome)))
self.constellations.sort()
return self.constellations
@stringdecorator
def get_string(self):
if self.constellations is None:
self.get_data()
string = '\n\t'.join(self.constellations)
return string
def check_const(self, const_check):
if self.constellations is None:
self.get_data()
if type(const_check) == str:
if const_check.lower() in [constellation.lower() for constellation in self.constellations]:
return f"{const_check} will be visible tonight."
else:
return f"{const_check} will not be visible tonight."
elif type(const_check) == list:
avail_consts = []
for const in const_check:
if const.lower() in [constellation.lower() for constellation in self.constellations]:
avail_consts.append(f"{const} will be visible tonight.")
else:
avail_consts.append(f"{const} will not be visible tonight.")
return avail_consts
else:
print("Function takes string or list of stings")
return False
if __name__ == "__main__":
const = ConstellationsWidget(longitude=52.2053, latitude=0.1218)
print(const.get_string())
for constellation in const.constellations:
if not const.check_const(str(constellation)):
print("Failed to find " + constellation)
print(const.check_const(const.constellations))
| true | true |
f7fe7748462965c14b63197643cfb9d0ea77e413 | 32 | py | Python | examples/python/mypackage/module.py | ech0-de/popper | 58b994660c954ab267407820e30d76a739a4d2df | [
"MIT"
] | 179 | 2016-11-19T22:38:07.000Z | 2020-05-24T10:42:30.000Z | examples/python/mypackage/module.py | ech0-de/popper | 58b994660c954ab267407820e30d76a739a4d2df | [
"MIT"
] | 739 | 2016-10-05T21:31:13.000Z | 2020-05-22T20:42:55.000Z | examples/python/mypackage/module.py | ech0-de/popper | 58b994660c954ab267407820e30d76a739a4d2df | [
"MIT"
] | 51 | 2016-10-14T05:42:10.000Z | 2020-05-15T19:05:33.000Z | def myfunc(x):
return x + 1
| 10.666667 | 16 | 0.5625 | def myfunc(x):
return x + 1
| true | true |
f7fe78db2738e5fc116176b624b1d6a2f4e865bb | 580 | py | Python | script/python3/util/__init__.py | setminami/IrControl | bcdd44b7f6aeca75226cdcfc611dc63032c38949 | [
"MIT"
] | null | null | null | script/python3/util/__init__.py | setminami/IrControl | bcdd44b7f6aeca75226cdcfc611dc63032c38949 | [
"MIT"
] | 2 | 2018-09-21T11:53:28.000Z | 2018-12-30T03:37:23.000Z | script/python3/util/__init__.py | setminami/IrControl | bcdd44b7f6aeca75226cdcfc611dc63032c38949 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# this made for python3
import logging, os
def is_debug(sysname='Darwin'):
""" for device debug """
return os.uname().sysname == sysname
def module_logger(modname):
logger = logging.getLogger(modname)
handler = logging.StreamHandler()
formatter = logging.Formatter('[%(asctime)s | %(name)s | %(levelname)s] %(message)s',
datefmt='%y%m%dT%H%M%S')
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.setLevel(logging.DEBUG if is_debug() else logging.INFO)
return logger
| 32.222222 | 89 | 0.639655 |
import logging, os
def is_debug(sysname='Darwin'):
return os.uname().sysname == sysname
def module_logger(modname):
logger = logging.getLogger(modname)
handler = logging.StreamHandler()
formatter = logging.Formatter('[%(asctime)s | %(name)s | %(levelname)s] %(message)s',
datefmt='%y%m%dT%H%M%S')
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.setLevel(logging.DEBUG if is_debug() else logging.INFO)
return logger
| true | true |
f7fe7906d343fc6cf019096931c1533d5633140d | 690 | py | Python | test/timing.py | plotnick/prettyprinter | edde630011ad5eada6476366a2b2da422f4a9d74 | [
"MIT"
] | null | null | null | test/timing.py | plotnick/prettyprinter | edde630011ad5eada6476366a2b2da422f4a9d74 | [
"MIT"
] | null | null | null | test/timing.py | plotnick/prettyprinter | edde630011ad5eada6476366a2b2da422f4a9d74 | [
"MIT"
] | null | null | null | from __future__ import with_statement
import timeit
setup = """
import pprint
import prettyprinter as pp
from format import format, parse_control_string
null = open("/dev/null", "w")
tupler = "(~{~A,~^ ~@{~A~^, ~}~})"
l = tuple(xrange(1000))
d = dict(zip(range(100), range(100, 200)))
"""[1:]
stmts = (("parse", """tuple(parse_control_string(tupler))"""),
("format", """format(null, "~~foo: ~D pon~:@P~%", 3)"""),
("iteration", """format(null, tupler, l)"""),
("prettyprinter", """pp.pprint(l, stream=null)"""),
("pprint", """pprint.pprint(l, null)"""))
for name, stmt in stmts:
print ">> %s" % name
timeit.main(["-s", setup, stmt])
print
| 28.75 | 66 | 0.573913 | from __future__ import with_statement
import timeit
setup = """
import pprint
import prettyprinter as pp
from format import format, parse_control_string
null = open("/dev/null", "w")
tupler = "(~{~A,~^ ~@{~A~^, ~}~})"
l = tuple(xrange(1000))
d = dict(zip(range(100), range(100, 200)))
"""[1:]
stmts = (("parse", """tuple(parse_control_string(tupler))"""),
("format", """format(null, "~~foo: ~D pon~:@P~%", 3)"""),
("iteration", """format(null, tupler, l)"""),
("prettyprinter", """pp.pprint(l, stream=null)"""),
("pprint", """pprint.pprint(l, null)"""))
for name, stmt in stmts:
print ">> %s" % name
timeit.main(["-s", setup, stmt])
print
| false | true |
f7fe7998d90376bfcb58386941deaf7b073ff2a4 | 3,812 | py | Python | archive/transfer_learning_runresults2.py | marjanin/tendon_stiffness | b1dc379b09bbf9c044410a6bc51afbee0cba2e05 | [
"MIT"
] | 1 | 2020-07-20T02:04:46.000Z | 2020-07-20T02:04:46.000Z | archive/transfer_learning_runresults2.py | marjanin/tendon_stiffness | b1dc379b09bbf9c044410a6bc51afbee0cba2e05 | [
"MIT"
] | null | null | null | archive/transfer_learning_runresults2.py | marjanin/tendon_stiffness | b1dc379b09bbf9c044410a6bc51afbee0cba2e05 | [
"MIT"
] | 1 | 2020-05-11T11:41:39.000Z | 2020-05-11T11:41:39.000Z |
# next is to add accel and see the difference
# add stiffness too
import numpy as np
from scipy import signal, stats
from matplotlib import pyplot as plt
from all_functions import *
import pickle
from warnings import simplefilter
simplefilter(action='ignore', category=FutureWarning)
experiment_ID = "transfer_learning_6"
errors_all_A_A = np.load("./results/{}/errors_all_A_A.npy".format(experiment_ID))
errors_all_A_B = np.load("./results/{}/errors_all_A_B.npy".format(experiment_ID))
errors_all_B_B = np.load("./results/{}/errors_all_B_B.npy".format(experiment_ID))
## printing the results
print("errors_mean: ",errors_all_A_A.mean(2))
print("errors_std: ",errors_all_A_A.std(2))
print("errors_mean: ",errors_all_A_B.mean(2))
print("errors_std: ",errors_all_A_B.std(2))
print("errors_mean: ",errors_all_B_B.mean(2))
print("errors_std: ",errors_all_B_B.std(2))
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[0],errors_all_A_B.mean(0)[0])
print("p-value (babbling/average/A_A vs A_B): ", p_val_avg)
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[1],errors_all_A_B.mean(0)[1])
print("p-value (refined/average/A_A vs A_B): ", p_val_avg)
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[1],errors_all_B_B.mean(0)[1])
print("p-value (refined/average/A_A vs B_B): ", p_val_avg)
# [f_ow, p_val_q0] = stats.f_oneway(errors_all_A_A[0,:],errors_all_A_B[0,:])
# print("p-value (q0): ", p_val_q0)
# [f_ow, p_val_q1] = stats.f_oneway(errors_all_A_A[1,:],errors_all_A_B[1,:])
# print("p-value (q1): ", p_val_q1)
y_lim=[0, 0.9]
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12, 5))
p0 = axes[0][0].boxplot(
[errors_all_A_A.mean(0)[0], errors_all_A_B.mean(0)[0], errors_all_B_B.mean(0)[0]],
notch=True,
patch_artist=True)
axes[0][0].set_title(r'$(q_0+q_1)/2$',fontsize=12)
axes[0][0].set_ylim(y_lim)
#axes[0].set_xlabel('stiffness')
axes[0][0].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
axes[0][0].set_ylabel('RMSE')
p1 = axes[0][1].boxplot(
[errors_all_A_A[0,0,:], errors_all_A_B[0,0,:], errors_all_B_B[0,0,:]],
notch=True,
patch_artist=True)
axes[0][1].set_title('$q_0$', fontsize=12)
axes[0][1].set_ylim(y_lim)
axes[0][1].set_yticklabels([])
#axes[1].set_xlabel('stiffness')
axes[0][1].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
p2 = axes[0][2].boxplot(
[errors_all_A_A[1,0,:], errors_all_A_B[1,0,:], errors_all_B_B[1,0,:]],
notch=True,
patch_artist=True)
axes[0][2].set_title('$q_1$', fontsize=12)
axes[0][2].set_ylim(y_lim)
axes[0][2].set_yticklabels([])
#axes[2].set_xlabel('stiffness')
axes[0][2].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
p3 = axes[1][0].boxplot(
[errors_all_A_A.mean(0)[-1], errors_all_A_B.mean(0)[-1], errors_all_B_B.mean(0)[-1]],
notch=True,
patch_artist=True)
#axes[1][0].set_title(r'$(q_0+q_1)/2$',fontsize=12)
axes[1][0].set_ylim(y_lim)
#axes[0].set_xlabel('stiffness')
axes[1][0].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
axes[1][0].set_ylabel('RMSE')
p4 = axes[1][1].boxplot(
[errors_all_A_A[0,-1,:], errors_all_A_B[0,-1,:], errors_all_B_B[0,-1,:]],
notch=True,
patch_artist=True)
#axes[1][1].set_title('$q_0$', fontsize=12)
axes[1][1].set_ylim(y_lim)
axes[1][1].set_yticklabels([])
#axes[1].set_xlabel('stiffness')
axes[1][1].set_xticklabels(["A_A","A_B", "B_B"], rotation=45, fontsize=8)
p5 = axes[1][2].boxplot(
[errors_all_A_A[1,-1,:], errors_all_A_B[1,-1,:], errors_all_B_B[1,-1,:]],
notch=True,
patch_artist=True)
#axes[1][2].set_title('$q_1$', fontsize=12)
axes[1][2].set_ylim(y_lim)
axes[1][2].set_yticklabels([])
#axes[2].set_xlabel('stiffness')
axes[1][2].set_xticklabels(["A_A","A_B","B_B"], rotation=45, fontsize=8)
for i_row in range(2):
for j_col in range(3):
axes[i_row][j_col].grid(True)
plt.show()
#import pdb; pdb.set_trace()
| 38.505051 | 87 | 0.705142 |
import numpy as np
from scipy import signal, stats
from matplotlib import pyplot as plt
from all_functions import *
import pickle
from warnings import simplefilter
simplefilter(action='ignore', category=FutureWarning)
experiment_ID = "transfer_learning_6"
errors_all_A_A = np.load("./results/{}/errors_all_A_A.npy".format(experiment_ID))
errors_all_A_B = np.load("./results/{}/errors_all_A_B.npy".format(experiment_ID))
errors_all_B_B = np.load("./results/{}/errors_all_B_B.npy".format(experiment_ID))
,errors_all_A_A.mean(2))
print("errors_std: ",errors_all_A_A.std(2))
print("errors_mean: ",errors_all_A_B.mean(2))
print("errors_std: ",errors_all_A_B.std(2))
print("errors_mean: ",errors_all_B_B.mean(2))
print("errors_std: ",errors_all_B_B.std(2))
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[0],errors_all_A_B.mean(0)[0])
print("p-value (babbling/average/A_A vs A_B): ", p_val_avg)
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[1],errors_all_A_B.mean(0)[1])
print("p-value (refined/average/A_A vs A_B): ", p_val_avg)
[f_ow, p_val_avg] = stats.f_oneway(errors_all_A_A.mean(0)[1],errors_all_B_B.mean(0)[1])
print("p-value (refined/average/A_A vs B_B): ", p_val_avg)
y_lim=[0, 0.9]
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(12, 5))
p0 = axes[0][0].boxplot(
[errors_all_A_A.mean(0)[0], errors_all_A_B.mean(0)[0], errors_all_B_B.mean(0)[0]],
notch=True,
patch_artist=True)
axes[0][0].set_title(r'$(q_0+q_1)/2$',fontsize=12)
axes[0][0].set_ylim(y_lim)
axes[0][0].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
axes[0][0].set_ylabel('RMSE')
p1 = axes[0][1].boxplot(
[errors_all_A_A[0,0,:], errors_all_A_B[0,0,:], errors_all_B_B[0,0,:]],
notch=True,
patch_artist=True)
axes[0][1].set_title('$q_0$', fontsize=12)
axes[0][1].set_ylim(y_lim)
axes[0][1].set_yticklabels([])
axes[0][1].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
p2 = axes[0][2].boxplot(
[errors_all_A_A[1,0,:], errors_all_A_B[1,0,:], errors_all_B_B[1,0,:]],
notch=True,
patch_artist=True)
axes[0][2].set_title('$q_1$', fontsize=12)
axes[0][2].set_ylim(y_lim)
axes[0][2].set_yticklabels([])
axes[0][2].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
p3 = axes[1][0].boxplot(
[errors_all_A_A.mean(0)[-1], errors_all_A_B.mean(0)[-1], errors_all_B_B.mean(0)[-1]],
notch=True,
patch_artist=True)
axes[1][0].set_ylim(y_lim)
axes[1][0].set_xticklabels(["A_A", "A_B", "B_B"], rotation=45, fontsize=8)
axes[1][0].set_ylabel('RMSE')
p4 = axes[1][1].boxplot(
[errors_all_A_A[0,-1,:], errors_all_A_B[0,-1,:], errors_all_B_B[0,-1,:]],
notch=True,
patch_artist=True)
axes[1][1].set_ylim(y_lim)
axes[1][1].set_yticklabels([])
axes[1][1].set_xticklabels(["A_A","A_B", "B_B"], rotation=45, fontsize=8)
p5 = axes[1][2].boxplot(
[errors_all_A_A[1,-1,:], errors_all_A_B[1,-1,:], errors_all_B_B[1,-1,:]],
notch=True,
patch_artist=True)
axes[1][2].set_ylim(y_lim)
axes[1][2].set_yticklabels([])
axes[1][2].set_xticklabels(["A_A","A_B","B_B"], rotation=45, fontsize=8)
for i_row in range(2):
for j_col in range(3):
axes[i_row][j_col].grid(True)
plt.show()
| true | true |
f7fe79e0ea2f62e8e12d449296f3fa9492d3b1cc | 11,653 | py | Python | tf_agents/policies/actor_policy_test.py | ayansengupta17/agents | c5a2f1f57d4fd0070eb75204aa0b1663de3e2c0a | [
"Apache-2.0"
] | 2 | 2021-02-02T06:56:58.000Z | 2021-04-21T08:39:45.000Z | tf_agents/policies/actor_policy_test.py | MarioBonse/agents | c727141f67051b86d2564c4bd5fbc080623bfe19 | [
"Apache-2.0"
] | null | null | null | tf_agents/policies/actor_policy_test.py | MarioBonse/agents | c727141f67051b86d2564c4bd5fbc080623bfe19 | [
"Apache-2.0"
] | 6 | 2020-10-09T06:33:23.000Z | 2022-02-03T16:16:36.000Z | # coding=utf-8
# Copyright 2018 The TF-Agents Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for tf_agents.policies.actor_policy."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import parameterized
import numpy as np
import tensorflow as tf # pylint: disable=g-explicit-tensorflow-version-import
import tensorflow_probability as tfp
from tf_agents.networks import actor_distribution_network
from tf_agents.networks import network
from tf_agents.policies import actor_policy
from tf_agents.specs import tensor_spec
from tf_agents.trajectories import time_step as ts
from tf_agents.utils import test_utils
class DummyActionNet(network.Network):
def __init__(self, input_tensor_spec, output_tensor_spec):
super(DummyActionNet, self).__init__(
input_tensor_spec=input_tensor_spec,
state_spec=(),
name='DummyActionNet')
single_action_spec = tf.nest.flatten(output_tensor_spec)[0]
self._output_tensor_spec = output_tensor_spec
self._sub_layers = [
tf.keras.layers.Dense(
single_action_spec.shape.num_elements(),
activation=tf.nn.tanh,
kernel_initializer=tf.compat.v1.initializers.constant([2, 1]),
bias_initializer=tf.compat.v1.initializers.constant([5]),
),
]
def call(self, observations, step_type, network_state):
del step_type
states = tf.cast(tf.nest.flatten(observations)[0], tf.float32)
for layer in self._sub_layers:
states = layer(states)
single_action_spec = tf.nest.flatten(self._output_tensor_spec)[0]
means = tf.reshape(states, [-1] + single_action_spec.shape.as_list())
spec_means = (single_action_spec.maximum + single_action_spec.minimum) / 2.0
spec_ranges = (
single_action_spec.maximum - single_action_spec.minimum) / 2.0
action_means = spec_means + spec_ranges * means
return (tf.nest.pack_sequence_as(self._output_tensor_spec, [action_means]),
network_state)
class DummyActionDistributionNet(DummyActionNet):
def call(self, observations, step_type, network_state):
action_means, network_state = super(DummyActionDistributionNet, self).call(
observations, step_type, network_state)
def _action_distribution(action_mean):
action_std = tf.ones_like(action_mean)
return tfp.distributions.Normal(action_mean, action_std)
return tf.nest.map_structure(_action_distribution,
action_means), network_state
def test_cases():
return parameterized.named_parameters({
'testcase_name': 'SimpleNet',
'network_ctor': DummyActionNet,
}, {
'testcase_name': 'DistributionNet',
'network_ctor': DummyActionDistributionNet,
})
class ActorPolicyTest(parameterized.TestCase, test_utils.TestCase):
def setUp(self):
super(ActorPolicyTest, self).setUp()
self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
self._time_step_spec = ts.time_step_spec(self._obs_spec)
self._action_spec = tensor_spec.BoundedTensorSpec([1], tf.float32, 2, 3)
@property
def _time_step(self):
return ts.restart(tf.constant([1, 2], dtype=tf.float32))
@property
def _time_step_batch(self):
return ts.TimeStep(
tf.constant(
ts.StepType.FIRST, dtype=tf.int32, shape=[2], name='step_type'),
tf.constant(0.0, dtype=tf.float32, shape=[2], name='reward'),
tf.constant(1.0, dtype=tf.float32, shape=[2], name='discount'),
tf.constant([[1, 2], [3, 4]], dtype=tf.float32, name='observation'))
@test_cases()
def testBuild(self, network_ctor):
actor_network = network_ctor(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertEqual(policy.time_step_spec, self._time_step_spec)
self.assertEqual(policy.action_spec, self._action_spec)
self.assertLen(policy.variables(), 2)
@test_cases()
def testActionBatch(self, network_ctor):
actor_network = network_ctor(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertEqual(action_step.action.shape.as_list(), [2, 1])
self.assertEqual(action_step.action.dtype, tf.float32)
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testUpdate(self):
tf.compat.v1.set_random_seed(1)
actor_network = DummyActionNet(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertLen(policy.variables(), 2)
new_policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertLen(policy.variables(), 2)
new_action_step = new_policy.action(self._time_step_batch)
self.assertLen(new_policy.variables(), 2)
self.assertEqual(action_step.action.shape, new_action_step.action.shape)
self.assertEqual(action_step.action.dtype, new_action_step.action.dtype)
self.evaluate(tf.compat.v1.global_variables_initializer())
self.evaluate(new_policy.update(policy))
actions_, new_actions_ = self.evaluate(
[action_step.action, new_action_step.action])
self.assertAllEqual(actions_, new_actions_)
def testDeterministicDistribution(self):
actor_network = DummyActionNet(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
distribution_step = policy.distribution(self._time_step_batch)
self.assertIsInstance(distribution_step.action,
tfp.distributions.Deterministic)
distribution_mean = distribution_step.action.mean()
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
distribution_mean_ = self.evaluate(distribution_mean)
self.assertNear(actions_[0], distribution_mean_[0], 1e-6)
def testGaussianDistribution(self):
actor_network = DummyActionDistributionNet(self._obs_spec,
self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
distribution_step = policy.distribution(self._time_step_batch)
self.assertIsInstance(distribution_step.action, tfp.distributions.Normal)
class ActorPolicyDiscreteActionsTest(test_utils.TestCase):
def setUp(self):
super(ActorPolicyDiscreteActionsTest, self).setUp()
self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
self._time_step_spec = ts.time_step_spec(self._obs_spec)
self._action_spec = tensor_spec.BoundedTensorSpec([1], tf.int32, 0, 7)
@property
def _time_step(self):
return ts.restart(tf.constant([1, 2], dtype=tf.float32))
@property
def _time_step_batch(self):
return ts.TimeStep(
tf.constant(
ts.StepType.FIRST, dtype=tf.int32, shape=[2], name='step_type'),
tf.constant(0.0, dtype=tf.float32, shape=[2], name='reward'),
tf.constant(1.0, dtype=tf.float32, shape=[2], name='discount'),
tf.constant([[1, 2], [3, 4]], dtype=tf.float32, name='observation'))
def testBuild(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertEqual(policy.time_step_spec, self._time_step_spec)
self.assertEqual(policy.action_spec, self._action_spec)
def testActionBatch(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertEqual(action_step.action.shape.as_list(), [2, 1])
self.assertEqual(action_step.action.dtype, self._action_spec.dtype)
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testActionDistribution(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
# Force creation of variables before global_variables_initializer.
policy.variables()
self.evaluate(tf.compat.v1.global_variables_initializer())
distribution = policy.distribution(self._time_step_batch)
actions_ = self.evaluate(distribution.action.sample())
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testMasking(self):
batch_size = 1000
num_state_dims = 5
num_actions = 8
observations = tf.random.uniform([batch_size, num_state_dims])
time_step = ts.restart(observations, batch_size=batch_size)
input_tensor_spec = tensor_spec.TensorSpec([num_state_dims], tf.float32)
time_step_spec = ts.time_step_spec(input_tensor_spec)
action_spec = tensor_spec.BoundedTensorSpec(
[1], tf.int32, 0, num_actions - 1)
# We create a fixed mask here for testing purposes. Normally the mask would
# be part of the observation.
mask = [0, 1, 0, 1, 0, 0, 1, 0]
np_mask = np.array(mask)
tf_mask = tf.constant([mask for _ in range(batch_size)])
actor_network = actor_distribution_network.ActorDistributionNetwork(
input_tensor_spec, action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
time_step_spec, action_spec, actor_network=actor_network,
observation_and_action_constraint_splitter=(
lambda observation: (observation, tf_mask)))
# Force creation of variables before global_variables_initializer.
policy.variables()
self.evaluate(tf.compat.v1.global_variables_initializer())
# Sample from the policy 1000 times, and ensure that actions considered
# invalid according to the mask are never chosen.
action_step = policy.action(time_step)
action = self.evaluate(action_step.action)
self.assertEqual(action.shape, (batch_size, 1))
self.assertAllEqual(np_mask[action], np.ones([batch_size, 1]))
if __name__ == '__main__':
tf.test.main()
| 41.322695 | 80 | 0.73878 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import parameterized
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
from tf_agents.networks import actor_distribution_network
from tf_agents.networks import network
from tf_agents.policies import actor_policy
from tf_agents.specs import tensor_spec
from tf_agents.trajectories import time_step as ts
from tf_agents.utils import test_utils
class DummyActionNet(network.Network):
def __init__(self, input_tensor_spec, output_tensor_spec):
super(DummyActionNet, self).__init__(
input_tensor_spec=input_tensor_spec,
state_spec=(),
name='DummyActionNet')
single_action_spec = tf.nest.flatten(output_tensor_spec)[0]
self._output_tensor_spec = output_tensor_spec
self._sub_layers = [
tf.keras.layers.Dense(
single_action_spec.shape.num_elements(),
activation=tf.nn.tanh,
kernel_initializer=tf.compat.v1.initializers.constant([2, 1]),
bias_initializer=tf.compat.v1.initializers.constant([5]),
),
]
def call(self, observations, step_type, network_state):
del step_type
states = tf.cast(tf.nest.flatten(observations)[0], tf.float32)
for layer in self._sub_layers:
states = layer(states)
single_action_spec = tf.nest.flatten(self._output_tensor_spec)[0]
means = tf.reshape(states, [-1] + single_action_spec.shape.as_list())
spec_means = (single_action_spec.maximum + single_action_spec.minimum) / 2.0
spec_ranges = (
single_action_spec.maximum - single_action_spec.minimum) / 2.0
action_means = spec_means + spec_ranges * means
return (tf.nest.pack_sequence_as(self._output_tensor_spec, [action_means]),
network_state)
class DummyActionDistributionNet(DummyActionNet):
def call(self, observations, step_type, network_state):
action_means, network_state = super(DummyActionDistributionNet, self).call(
observations, step_type, network_state)
def _action_distribution(action_mean):
action_std = tf.ones_like(action_mean)
return tfp.distributions.Normal(action_mean, action_std)
return tf.nest.map_structure(_action_distribution,
action_means), network_state
def test_cases():
return parameterized.named_parameters({
'testcase_name': 'SimpleNet',
'network_ctor': DummyActionNet,
}, {
'testcase_name': 'DistributionNet',
'network_ctor': DummyActionDistributionNet,
})
class ActorPolicyTest(parameterized.TestCase, test_utils.TestCase):
def setUp(self):
super(ActorPolicyTest, self).setUp()
self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
self._time_step_spec = ts.time_step_spec(self._obs_spec)
self._action_spec = tensor_spec.BoundedTensorSpec([1], tf.float32, 2, 3)
@property
def _time_step(self):
return ts.restart(tf.constant([1, 2], dtype=tf.float32))
@property
def _time_step_batch(self):
return ts.TimeStep(
tf.constant(
ts.StepType.FIRST, dtype=tf.int32, shape=[2], name='step_type'),
tf.constant(0.0, dtype=tf.float32, shape=[2], name='reward'),
tf.constant(1.0, dtype=tf.float32, shape=[2], name='discount'),
tf.constant([[1, 2], [3, 4]], dtype=tf.float32, name='observation'))
@test_cases()
def testBuild(self, network_ctor):
actor_network = network_ctor(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertEqual(policy.time_step_spec, self._time_step_spec)
self.assertEqual(policy.action_spec, self._action_spec)
self.assertLen(policy.variables(), 2)
@test_cases()
def testActionBatch(self, network_ctor):
actor_network = network_ctor(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertEqual(action_step.action.shape.as_list(), [2, 1])
self.assertEqual(action_step.action.dtype, tf.float32)
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testUpdate(self):
tf.compat.v1.set_random_seed(1)
actor_network = DummyActionNet(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertLen(policy.variables(), 2)
new_policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertLen(policy.variables(), 2)
new_action_step = new_policy.action(self._time_step_batch)
self.assertLen(new_policy.variables(), 2)
self.assertEqual(action_step.action.shape, new_action_step.action.shape)
self.assertEqual(action_step.action.dtype, new_action_step.action.dtype)
self.evaluate(tf.compat.v1.global_variables_initializer())
self.evaluate(new_policy.update(policy))
actions_, new_actions_ = self.evaluate(
[action_step.action, new_action_step.action])
self.assertAllEqual(actions_, new_actions_)
def testDeterministicDistribution(self):
actor_network = DummyActionNet(self._obs_spec, self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
distribution_step = policy.distribution(self._time_step_batch)
self.assertIsInstance(distribution_step.action,
tfp.distributions.Deterministic)
distribution_mean = distribution_step.action.mean()
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
distribution_mean_ = self.evaluate(distribution_mean)
self.assertNear(actions_[0], distribution_mean_[0], 1e-6)
def testGaussianDistribution(self):
actor_network = DummyActionDistributionNet(self._obs_spec,
self._action_spec)
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
distribution_step = policy.distribution(self._time_step_batch)
self.assertIsInstance(distribution_step.action, tfp.distributions.Normal)
class ActorPolicyDiscreteActionsTest(test_utils.TestCase):
def setUp(self):
super(ActorPolicyDiscreteActionsTest, self).setUp()
self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
self._time_step_spec = ts.time_step_spec(self._obs_spec)
self._action_spec = tensor_spec.BoundedTensorSpec([1], tf.int32, 0, 7)
@property
def _time_step(self):
return ts.restart(tf.constant([1, 2], dtype=tf.float32))
@property
def _time_step_batch(self):
return ts.TimeStep(
tf.constant(
ts.StepType.FIRST, dtype=tf.int32, shape=[2], name='step_type'),
tf.constant(0.0, dtype=tf.float32, shape=[2], name='reward'),
tf.constant(1.0, dtype=tf.float32, shape=[2], name='discount'),
tf.constant([[1, 2], [3, 4]], dtype=tf.float32, name='observation'))
def testBuild(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
self.assertEqual(policy.time_step_spec, self._time_step_spec)
self.assertEqual(policy.action_spec, self._action_spec)
def testActionBatch(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
action_step = policy.action(self._time_step_batch)
self.assertEqual(action_step.action.shape.as_list(), [2, 1])
self.assertEqual(action_step.action.dtype, self._action_spec.dtype)
self.evaluate(tf.compat.v1.global_variables_initializer())
actions_ = self.evaluate(action_step.action)
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testActionDistribution(self):
actor_network = actor_distribution_network.ActorDistributionNetwork(
self._obs_spec, self._action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
self._time_step_spec, self._action_spec, actor_network=actor_network)
policy.variables()
self.evaluate(tf.compat.v1.global_variables_initializer())
distribution = policy.distribution(self._time_step_batch)
actions_ = self.evaluate(distribution.action.sample())
self.assertTrue(np.all(actions_ >= self._action_spec.minimum))
self.assertTrue(np.all(actions_ <= self._action_spec.maximum))
def testMasking(self):
batch_size = 1000
num_state_dims = 5
num_actions = 8
observations = tf.random.uniform([batch_size, num_state_dims])
time_step = ts.restart(observations, batch_size=batch_size)
input_tensor_spec = tensor_spec.TensorSpec([num_state_dims], tf.float32)
time_step_spec = ts.time_step_spec(input_tensor_spec)
action_spec = tensor_spec.BoundedTensorSpec(
[1], tf.int32, 0, num_actions - 1)
mask = [0, 1, 0, 1, 0, 0, 1, 0]
np_mask = np.array(mask)
tf_mask = tf.constant([mask for _ in range(batch_size)])
actor_network = actor_distribution_network.ActorDistributionNetwork(
input_tensor_spec, action_spec, fc_layer_params=(2, 1))
policy = actor_policy.ActorPolicy(
time_step_spec, action_spec, actor_network=actor_network,
observation_and_action_constraint_splitter=(
lambda observation: (observation, tf_mask)))
policy.variables()
self.evaluate(tf.compat.v1.global_variables_initializer())
action_step = policy.action(time_step)
action = self.evaluate(action_step.action)
self.assertEqual(action.shape, (batch_size, 1))
self.assertAllEqual(np_mask[action], np.ones([batch_size, 1]))
if __name__ == '__main__':
tf.test.main()
| true | true |
f7fe7b39823cb214a93650991b086952e666f36c | 308 | py | Python | feedz/users/apps.py | Dimercel/feedz | d1f0ab1558b6df63452d1ac12847e3e816c83c31 | [
"MIT"
] | null | null | null | feedz/users/apps.py | Dimercel/feedz | d1f0ab1558b6df63452d1ac12847e3e816c83c31 | [
"MIT"
] | null | null | null | feedz/users/apps.py | Dimercel/feedz | d1f0ab1558b6df63452d1ac12847e3e816c83c31 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class UsersConfig(AppConfig):
name = "feedz.users"
verbose_name = _("Users")
def ready(self):
try:
import feedz.users.signals # noqa F401
except ImportError:
pass
| 22 | 54 | 0.649351 | from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class UsersConfig(AppConfig):
name = "feedz.users"
verbose_name = _("Users")
def ready(self):
try:
import feedz.users.signals
except ImportError:
pass
| true | true |
f7fe7b7cddac60490fd507db0067a3b0e0cf4da2 | 2,858 | py | Python | janitor/functions/collapse_levels.py | thatlittleboy/pyjanitor | f7977e00d3d9bf49aebeaa62db2965a668c50c90 | [
"MIT"
] | null | null | null | janitor/functions/collapse_levels.py | thatlittleboy/pyjanitor | f7977e00d3d9bf49aebeaa62db2965a668c50c90 | [
"MIT"
] | null | null | null | janitor/functions/collapse_levels.py | thatlittleboy/pyjanitor | f7977e00d3d9bf49aebeaa62db2965a668c50c90 | [
"MIT"
] | null | null | null | """Implementation of the `collapse_levels` function."""
import pandas as pd
import pandas_flavor as pf
from janitor.utils import check
@pf.register_dataframe_method
def collapse_levels(df: pd.DataFrame, sep: str = "_") -> pd.DataFrame:
"""Flatten multi-level column dataframe to a single level.
This method mutates the original DataFrame.
Given a DataFrame containing multi-level columns, flatten to single-level
by string-joining the column labels in each level.
After a `groupby` / `aggregate` operation where `.agg()` is passed a
list of multiple aggregation functions, a multi-level DataFrame is
returned with the name of the function applied in the second level.
It is sometimes convenient for later indexing to flatten out this
multi-level configuration back into a single level. This function does
this through a simple string-joining of all the names across different
levels in a single column.
Example:
>>> import pandas as pd
>>> import janitor
>>> df = pd.DataFrame({
... "class": ["bird", "bird", "bird", "mammal", "mammal"],
... "max_speed": [389, 389, 24, 80, 21],
... "type": ["falcon", "falcon", "parrot", "Lion", "Monkey"],
... })
>>> df
class max_speed type
0 bird 389 falcon
1 bird 389 falcon
2 bird 24 parrot
3 mammal 80 Lion
4 mammal 21 Monkey
>>> grouped_df = df.groupby("class").agg(["mean", "median"])
>>> grouped_df # doctest: +NORMALIZE_WHITESPACE
max_speed
mean median
class
bird 267.333333 389.0
mammal 50.500000 50.5
>>> grouped_df.collapse_levels(sep="_") # doctest: +NORMALIZE_WHITESPACE
max_speed_mean max_speed_median
class
bird 267.333333 389.0
mammal 50.500000 50.5
Before applying `.collapse_levels`, the `.agg` operation returns a
multi-level column DataFrame whose columns are `(level 1, level 2)`:
[("max_speed", "mean"), ("max_speed", "median")]
`.collapse_levels` then flattens the column MultiIndex into a single
level index with names:
["max_speed_mean", "max_speed_median"]
:param df: A pandas DataFrame.
:param sep: String separator used to join the column level names.
:returns: A pandas DataFrame with single-level column index.
""" # noqa: E501
check("sep", sep, [str])
# if already single-level, just return the DataFrame
if not isinstance(df.columns, pd.MultiIndex):
return df
df.columns = [
sep.join(str(el) for el in tup if str(el) != "")
for tup in df # noqa: PD011
]
return df
| 35.283951 | 81 | 0.607068 | import pandas as pd
import pandas_flavor as pf
from janitor.utils import check
@pf.register_dataframe_method
def collapse_levels(df: pd.DataFrame, sep: str = "_") -> pd.DataFrame:
check("sep", sep, [str])
if not isinstance(df.columns, pd.MultiIndex):
return df
df.columns = [
sep.join(str(el) for el in tup if str(el) != "")
for tup in df
]
return df
| true | true |
f7fe7be8107302b407a6207200066210a6ed92fc | 847 | py | Python | Chapter09/extract_stats.py | marcjour303/PytML | cd1391976167a7a671e98a1f588898c01585cee9 | [
"MIT"
] | 36 | 2019-04-05T00:58:57.000Z | 2022-03-12T09:25:04.000Z | Chapter09/extract_stats.py | ClauPorto/Python-Machine-Learning-Cookbook-Second-Edition | 99d8b799dbfe1d9a82f0bcc3648aaeb147b7298f | [
"MIT"
] | null | null | null | Chapter09/extract_stats.py | ClauPorto/Python-Machine-Learning-Cookbook-Second-Edition | 99d8b799dbfe1d9a82f0bcc3648aaeb147b7298f | [
"MIT"
] | 37 | 2019-04-16T00:50:20.000Z | 2022-02-28T18:14:41.000Z | import pandas as pd
import matplotlib.pyplot as plt
from convert_to_timeseries import convert_data_to_timeseries
# Input file containing data
input_file = 'data_timeseries.txt'
# Load data
data1 = convert_data_to_timeseries(input_file, 2)
data2 = convert_data_to_timeseries(input_file, 3)
dataframe = pd.DataFrame({'first': data1, 'second': data2})
# Print max and min
print('Maximum:\n', dataframe.max())
print('Minimum:\n', dataframe.min())
# Print mean
print('Mean:\n', dataframe.mean())
print('Mean row-wise:\n', dataframe.mean(1)[:10])
# Plot rolling mean
DFMean = dataframe.rolling(window=24).mean()
plt.plot(DFMean)
# Print correlation coefficients
print('Correlation coefficients:\n', dataframe.corr())
# Plot rolling correlation
plt.figure()
DFCorr= dataframe.rolling(window=60).corr(pairwise=False)
plt.plot(DFCorr)
plt.show()
| 23.527778 | 60 | 0.75915 | import pandas as pd
import matplotlib.pyplot as plt
from convert_to_timeseries import convert_data_to_timeseries
input_file = 'data_timeseries.txt'
data1 = convert_data_to_timeseries(input_file, 2)
data2 = convert_data_to_timeseries(input_file, 3)
dataframe = pd.DataFrame({'first': data1, 'second': data2})
print('Maximum:\n', dataframe.max())
print('Minimum:\n', dataframe.min())
print('Mean:\n', dataframe.mean())
print('Mean row-wise:\n', dataframe.mean(1)[:10])
DFMean = dataframe.rolling(window=24).mean()
plt.plot(DFMean)
print('Correlation coefficients:\n', dataframe.corr())
plt.figure()
DFCorr= dataframe.rolling(window=60).corr(pairwise=False)
plt.plot(DFCorr)
plt.show()
| true | true |
f7fe7c3e9a50e5313f3c1ed8e488b4a3eb47b65e | 332 | py | Python | school/migrations/0018_auto_20200610_0808.py | ankit986/school-management | cdffab5280199856397cdef36d18e84def841f93 | [
"MIT"
] | null | null | null | school/migrations/0018_auto_20200610_0808.py | ankit986/school-management | cdffab5280199856397cdef36d18e84def841f93 | [
"MIT"
] | 6 | 2021-03-19T04:29:01.000Z | 2021-09-22T19:09:31.000Z | school/migrations/0018_auto_20200610_0808.py | ankit986/school-management | cdffab5280199856397cdef36d18e84def841f93 | [
"MIT"
] | null | null | null | # Generated by Django 3.0.5 on 2020-06-10 08:08
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('school', '0017_auto_20200610_0807'),
]
operations = [
migrations.RenameModel(
old_name='Subjects',
new_name='Subject',
),
]
| 18.444444 | 47 | 0.596386 |
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('school', '0017_auto_20200610_0807'),
]
operations = [
migrations.RenameModel(
old_name='Subjects',
new_name='Subject',
),
]
| true | true |
f7fe7fb8c35219db1d8d21029b362a1bc08ef011 | 781 | py | Python | venv/bin/rst2html4.py | anthodemorais/spaces | e2f4b70bf2438a39ce1e1bd954f8dc98bea5280d | [
"MIT"
] | null | null | null | venv/bin/rst2html4.py | anthodemorais/spaces | e2f4b70bf2438a39ce1e1bd954f8dc98bea5280d | [
"MIT"
] | null | null | null | venv/bin/rst2html4.py | anthodemorais/spaces | e2f4b70bf2438a39ce1e1bd954f8dc98bea5280d | [
"MIT"
] | null | null | null | #!/Users/anthonydemorais/Documents/travail/supinternet/python/spaces/venv/bin/python3
# $Id: rst2html4.py 7994 2016-12-10 17:41:45Z milde $
# Author: David Goodger <goodger@python.org>
# Copyright: This module has been placed in the public domain.
"""
A minimal front end to the Docutils Publisher, producing (X)HTML.
The output conforms to XHTML 1.0 transitional
and almost to HTML 4.01 transitional (except for closing empty tags).
"""
try:
import locale
locale.setlocale(locale.LC_ALL, '')
except:
pass
from docutils.core import publish_cmdline, default_description
description = ('Generates (X)HTML documents from standalone reStructuredText '
'sources. ' + default_description)
publish_cmdline(writer_name='html4', description=description)
| 28.925926 | 85 | 0.754161 |
try:
import locale
locale.setlocale(locale.LC_ALL, '')
except:
pass
from docutils.core import publish_cmdline, default_description
description = ('Generates (X)HTML documents from standalone reStructuredText '
'sources. ' + default_description)
publish_cmdline(writer_name='html4', description=description)
| true | true |
f7fe7fe0ec0ed226b6d14b0fd44f387f10cebd93 | 10,897 | py | Python | custom_components/awox/config_flow.py | valentingc/home-assistant-awox | 3015f524404962b66bad961b446a37263b717882 | [
"MIT"
] | null | null | null | custom_components/awox/config_flow.py | valentingc/home-assistant-awox | 3015f524404962b66bad961b446a37263b717882 | [
"MIT"
] | null | null | null | custom_components/awox/config_flow.py | valentingc/home-assistant-awox | 3015f524404962b66bad961b446a37263b717882 | [
"MIT"
] | null | null | null | """Config flow for AwoX MESH lights"""
from typing import Mapping, Optional
import logging
import pygatt
import voluptuous as vol
from homeassistant import config_entries
from homeassistant.const import (
CONF_USERNAME,
CONF_PASSWORD
)
from .scanner import DeviceScanner
from .const import DOMAIN, CONF_MESH_NAME, CONF_MESH_PASSWORD, CONF_MESH_KEY
from .awox_connect import AwoxConnect
from bluepy.btle import BTLEManagementError
_LOGGER = logging.getLogger(__name__)
def create_awox_connect_object(username, password) -> AwoxConnect:
return AwoxConnect(username, password)
class AwoxMeshFlowHandler(config_entries.ConfigFlow, domain=DOMAIN):
"""Handle a Awox config flow."""
VERSION = 1
CONNECTION_CLASS = config_entries.CONN_CLASS_LOCAL_POLL
config: Optional[Mapping] = {}
def __init__(self):
"""Initialize the UPnP/IGD config flow."""
self._discoveries: Optional[Mapping] = None
self._mesh_info: Optional[Mapping] = None
async def async_step_user(self, user_input: Optional[Mapping] = None):
return await self.async_step_awox_connect()
# todo: fix manual connect
_LOGGER.debug("async_step_user: user_input: %s", user_input)
if self._mesh_info is None:
return await self.async_step_mesh_info()
if user_input is not None and user_input.get('mac'):
# Ensure wanted device is available
test_ok = await DeviceScanner.connect_device(
user_input.get('mac'),
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD),
self._mesh_info.get(CONF_MESH_KEY)
)
if not test_ok:
return self.async_abort(reason="device_not_found")
await self.async_set_unique_id(
self._mesh_info.get(CONF_MESH_NAME), raise_on_progress=False
)
return await self._async_create_entry_from_discovery(
user_input.get('mac'),
user_input.get('name'),
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD),
self._mesh_info.get(CONF_MESH_KEY)
)
# Scan for devices
scan_successful = False
try:
discoveries = await DeviceScanner.find_devices(
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD)
)
scan_successful = True
except (RuntimeError, pygatt.exceptions.BLEError) as e:
_LOGGER.exception("Failed while scanning for devices [%s]", str(e))
if not scan_successful:
return self.async_show_form(
step_id="manual",
data_schema=vol.Schema({
vol.Required('mac'): str,
vol.Required("name", description={"suggested_value": "AwoX light"}): str,
}),
)
# Store discoveries which have not been configured, add name for each discovery.
current_devices = {entry.unique_id for entry in self._async_current_entries()}
self._discoveries = [
{
**discovery,
'name': discovery['name'],
}
for discovery in discoveries
if discovery['mac'] not in current_devices
]
# Ensure anything to add.
if not self._discoveries:
return self.async_abort(reason="no_devices_found")
data_schema = vol.Schema(
{
vol.Required("mac"): vol.In(
{
discovery['mac']: discovery['name']
for discovery in self._discoveries
}
),
vol.Required("name", description={"suggested_value": "AwoX light"}): str,
}
)
return self.async_show_form(
step_id="select_device",
data_schema=data_schema,
)
async def async_step_awox_connect(self, user_input: Optional[Mapping] = None):
errors = {}
username: str = ''
password: str = ''
awox_connect = None
if user_input is not None:
username = user_input.get(CONF_USERNAME)
password = user_input.get(CONF_PASSWORD)
if username and password:
try:
awox_connect = await self.hass.async_add_executor_job(create_awox_connect_object, username, password)
except Exception as e:
_LOGGER.error('Can not login to AwoX Smart Connect [%s]', e)
errors[CONF_PASSWORD] = 'cannot_connect'
if user_input is None or awox_connect is None or errors:
return self.async_show_form(
step_id="awox_connect",
data_schema=vol.Schema({
vol.Required(CONF_USERNAME, default=username): str,
vol.Required(CONF_PASSWORD, default=password): str,
}),
errors=errors,
)
devices = []
for device in await self.hass.async_add_executor_job(awox_connect.devices):
_LOGGER.debug('Processing device - %s', device)
if 'type' not in device:
_LOGGER.warning('Skipped device, missing type - %s', device)
continue
if 'address' not in device:
_LOGGER.warning('Skipped device, missing address - %s', device)
continue
if 'macAddress' not in device:
_LOGGER.warning('Skipped device, missing macAddress - %s', device)
continue
if 'displayName' not in device:
_LOGGER.warning('Skipped device, missing displayName - %s', device)
continue
if 'modelName' not in device:
device['modelName'] = 'unknown'
if 'vendor' not in device:
device['vendor'] = 'unknown'
if 'version' not in device:
device['version'] = 'unknown'
if 'hardwareVersion' not in device:
device['hardwareVersion'] = None
devices.append({
'mesh_id': int(device['address']),
'name': device['displayName'],
'mac': device['macAddress'],
'model': device['modelName'],
'manufacturer': device['vendor'],
'firmware': device['version'],
'hardware': device['hardwareVersion'],
'type': device['type']
})
if len(devices) == 0:
return self.async_abort(reason="no_devices_found")
credentials = await self.hass.async_add_executor_job(awox_connect.credentials)
data = {
CONF_MESH_NAME: credentials['client_id'],
CONF_MESH_PASSWORD: credentials['access_token'],
CONF_MESH_KEY: credentials['refresh_token'],
# 'awox_connect': {
# CONF_USERNAME: user_input[CONF_USERNAME],
# CONF_PASSWORD: user_input[CONF_PASSWORD]
# },
'devices': devices
}
return self.async_create_entry(title='AwoX Smart Connect', data=data)
async def async_step_mesh_info(self, user_input: Optional[Mapping] = None):
_LOGGER.debug("async_step_mesh_info: user_input: %s", user_input)
errors = {}
name: str = ''
password: str = ''
key: str = ''
if user_input is not None:
name = user_input.get(CONF_MESH_NAME)
password = user_input.get(CONF_MESH_PASSWORD)
key = user_input.get(CONF_MESH_KEY)
if len(user_input.get(CONF_MESH_NAME)) > 16:
errors[CONF_MESH_NAME] = 'max_length_16'
if len(user_input.get(CONF_MESH_PASSWORD)) > 16:
errors[CONF_MESH_PASSWORD] = 'max_length_16'
if len(user_input.get(CONF_MESH_KEY)) > 16:
errors[CONF_MESH_KEY] = 'max_length_16'
if user_input is None or errors:
return self.async_show_form(
step_id="mesh_info",
data_schema=vol.Schema({
vol.Required(CONF_MESH_NAME, default=name): str,
vol.Required(CONF_MESH_PASSWORD, default=password): str,
vol.Required(CONF_MESH_KEY, default=key): str
}),
errors=errors,
)
self._mesh_info = user_input
return await self.async_step_user()
async def async_step_manual(self, user_input: Optional[Mapping] = None):
"""Forward result of manual input form to step user"""
return await self.async_step_user(user_input)
async def async_step_select_device(self, user_input: Optional[Mapping] = None):
"""Forward result of device select form to step user"""
return await self.async_step_user(user_input)
# @staticmethod
# @callback
# def async_get_options_flow(config_entry):
# """Define the config flow to handle options."""
# return UpnpOptionsFlowHandler(config_entry)
async def _async_create_entry_from_discovery(
self,
mac: str,
name: str,
mesh_name: str,
mesh_pass: str,
mesh_key: str
):
"""Create an entry from discovery."""
_LOGGER.debug(
"_async_create_entry_from_discovery: device: %s [%s]",
name,
mac
)
data = {
CONF_MESH_NAME: mesh_name,
CONF_MESH_PASSWORD: mesh_pass,
CONF_MESH_KEY: mesh_key,
'devices': [
{
'mac': mac,
'name': name,
}
]
}
return self.async_create_entry(title=name, data=data)
#
# async def _async_get_name_for_discovery(self, discovery: Mapping):
# """Get the name of the device from a discovery."""
# _LOGGER.debug("_async_get_name_for_discovery: discovery: %s", discovery)
# device = await Device.async_create_device(
# self.hass, discovery[DISCOVERY_LOCATION]
# )
# return device.name
#
#
# async def _async_get_name_for_discovery(self, discovery: Mapping):
# """Get the name of the device from a discovery."""
# _LOGGER.debug("_async_get_name_for_discovery: discovery: %s", discovery)
# device = await Device.async_create_device(
# self.hass, discovery['name']
# )
# return device.name
#
# async def _async_has_devices(hass) -> bool:
# """Return if there are devices that can be discovered."""
# devices = await DeviceScanner.find_devices()
# return len(devices) > 0
| 35.611111 | 117 | 0.578691 |
from typing import Mapping, Optional
import logging
import pygatt
import voluptuous as vol
from homeassistant import config_entries
from homeassistant.const import (
CONF_USERNAME,
CONF_PASSWORD
)
from .scanner import DeviceScanner
from .const import DOMAIN, CONF_MESH_NAME, CONF_MESH_PASSWORD, CONF_MESH_KEY
from .awox_connect import AwoxConnect
from bluepy.btle import BTLEManagementError
_LOGGER = logging.getLogger(__name__)
def create_awox_connect_object(username, password) -> AwoxConnect:
return AwoxConnect(username, password)
class AwoxMeshFlowHandler(config_entries.ConfigFlow, domain=DOMAIN):
VERSION = 1
CONNECTION_CLASS = config_entries.CONN_CLASS_LOCAL_POLL
config: Optional[Mapping] = {}
def __init__(self):
self._discoveries: Optional[Mapping] = None
self._mesh_info: Optional[Mapping] = None
async def async_step_user(self, user_input: Optional[Mapping] = None):
return await self.async_step_awox_connect()
_LOGGER.debug("async_step_user: user_input: %s", user_input)
if self._mesh_info is None:
return await self.async_step_mesh_info()
if user_input is not None and user_input.get('mac'):
test_ok = await DeviceScanner.connect_device(
user_input.get('mac'),
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD),
self._mesh_info.get(CONF_MESH_KEY)
)
if not test_ok:
return self.async_abort(reason="device_not_found")
await self.async_set_unique_id(
self._mesh_info.get(CONF_MESH_NAME), raise_on_progress=False
)
return await self._async_create_entry_from_discovery(
user_input.get('mac'),
user_input.get('name'),
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD),
self._mesh_info.get(CONF_MESH_KEY)
)
scan_successful = False
try:
discoveries = await DeviceScanner.find_devices(
self._mesh_info.get(CONF_MESH_NAME),
self._mesh_info.get(CONF_MESH_PASSWORD)
)
scan_successful = True
except (RuntimeError, pygatt.exceptions.BLEError) as e:
_LOGGER.exception("Failed while scanning for devices [%s]", str(e))
if not scan_successful:
return self.async_show_form(
step_id="manual",
data_schema=vol.Schema({
vol.Required('mac'): str,
vol.Required("name", description={"suggested_value": "AwoX light"}): str,
}),
)
current_devices = {entry.unique_id for entry in self._async_current_entries()}
self._discoveries = [
{
**discovery,
'name': discovery['name'],
}
for discovery in discoveries
if discovery['mac'] not in current_devices
]
if not self._discoveries:
return self.async_abort(reason="no_devices_found")
data_schema = vol.Schema(
{
vol.Required("mac"): vol.In(
{
discovery['mac']: discovery['name']
for discovery in self._discoveries
}
),
vol.Required("name", description={"suggested_value": "AwoX light"}): str,
}
)
return self.async_show_form(
step_id="select_device",
data_schema=data_schema,
)
async def async_step_awox_connect(self, user_input: Optional[Mapping] = None):
errors = {}
username: str = ''
password: str = ''
awox_connect = None
if user_input is not None:
username = user_input.get(CONF_USERNAME)
password = user_input.get(CONF_PASSWORD)
if username and password:
try:
awox_connect = await self.hass.async_add_executor_job(create_awox_connect_object, username, password)
except Exception as e:
_LOGGER.error('Can not login to AwoX Smart Connect [%s]', e)
errors[CONF_PASSWORD] = 'cannot_connect'
if user_input is None or awox_connect is None or errors:
return self.async_show_form(
step_id="awox_connect",
data_schema=vol.Schema({
vol.Required(CONF_USERNAME, default=username): str,
vol.Required(CONF_PASSWORD, default=password): str,
}),
errors=errors,
)
devices = []
for device in await self.hass.async_add_executor_job(awox_connect.devices):
_LOGGER.debug('Processing device - %s', device)
if 'type' not in device:
_LOGGER.warning('Skipped device, missing type - %s', device)
continue
if 'address' not in device:
_LOGGER.warning('Skipped device, missing address - %s', device)
continue
if 'macAddress' not in device:
_LOGGER.warning('Skipped device, missing macAddress - %s', device)
continue
if 'displayName' not in device:
_LOGGER.warning('Skipped device, missing displayName - %s', device)
continue
if 'modelName' not in device:
device['modelName'] = 'unknown'
if 'vendor' not in device:
device['vendor'] = 'unknown'
if 'version' not in device:
device['version'] = 'unknown'
if 'hardwareVersion' not in device:
device['hardwareVersion'] = None
devices.append({
'mesh_id': int(device['address']),
'name': device['displayName'],
'mac': device['macAddress'],
'model': device['modelName'],
'manufacturer': device['vendor'],
'firmware': device['version'],
'hardware': device['hardwareVersion'],
'type': device['type']
})
if len(devices) == 0:
return self.async_abort(reason="no_devices_found")
credentials = await self.hass.async_add_executor_job(awox_connect.credentials)
data = {
CONF_MESH_NAME: credentials['client_id'],
CONF_MESH_PASSWORD: credentials['access_token'],
CONF_MESH_KEY: credentials['refresh_token'],
'devices': devices
}
return self.async_create_entry(title='AwoX Smart Connect', data=data)
async def async_step_mesh_info(self, user_input: Optional[Mapping] = None):
_LOGGER.debug("async_step_mesh_info: user_input: %s", user_input)
errors = {}
name: str = ''
password: str = ''
key: str = ''
if user_input is not None:
name = user_input.get(CONF_MESH_NAME)
password = user_input.get(CONF_MESH_PASSWORD)
key = user_input.get(CONF_MESH_KEY)
if len(user_input.get(CONF_MESH_NAME)) > 16:
errors[CONF_MESH_NAME] = 'max_length_16'
if len(user_input.get(CONF_MESH_PASSWORD)) > 16:
errors[CONF_MESH_PASSWORD] = 'max_length_16'
if len(user_input.get(CONF_MESH_KEY)) > 16:
errors[CONF_MESH_KEY] = 'max_length_16'
if user_input is None or errors:
return self.async_show_form(
step_id="mesh_info",
data_schema=vol.Schema({
vol.Required(CONF_MESH_NAME, default=name): str,
vol.Required(CONF_MESH_PASSWORD, default=password): str,
vol.Required(CONF_MESH_KEY, default=key): str
}),
errors=errors,
)
self._mesh_info = user_input
return await self.async_step_user()
async def async_step_manual(self, user_input: Optional[Mapping] = None):
return await self.async_step_user(user_input)
async def async_step_select_device(self, user_input: Optional[Mapping] = None):
return await self.async_step_user(user_input)
async def _async_create_entry_from_discovery(
self,
mac: str,
name: str,
mesh_name: str,
mesh_pass: str,
mesh_key: str
):
_LOGGER.debug(
"_async_create_entry_from_discovery: device: %s [%s]",
name,
mac
)
data = {
CONF_MESH_NAME: mesh_name,
CONF_MESH_PASSWORD: mesh_pass,
CONF_MESH_KEY: mesh_key,
'devices': [
{
'mac': mac,
'name': name,
}
]
}
return self.async_create_entry(title=name, data=data)
| true | true |
f7fe80cc025cab2659f427cb5a3aa43e110f43d1 | 992 | py | Python | samples/v1beta1/test_create_entry_group.py | LaudateCorpus1/python-datacatalog | 7d8c3bc9bf540d3e5c0b0bd80a619792162c4fe2 | [
"Apache-2.0"
] | 41 | 2020-05-12T08:00:04.000Z | 2022-03-28T22:54:06.000Z | samples/v1beta1/test_create_entry_group.py | LaudateCorpus1/python-datacatalog | 7d8c3bc9bf540d3e5c0b0bd80a619792162c4fe2 | [
"Apache-2.0"
] | 114 | 2020-02-07T02:48:37.000Z | 2022-03-23T00:46:01.000Z | samples/v1beta1/test_create_entry_group.py | LaudateCorpus1/python-datacatalog | 7d8c3bc9bf540d3e5c0b0bd80a619792162c4fe2 | [
"Apache-2.0"
] | 21 | 2020-01-31T21:14:59.000Z | 2022-02-15T07:26:39.000Z | # Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import create_entry_group
def test_create_entry_group(capsys, client, project_id, random_entry_group_id):
create_entry_group.create_entry_group(project_id, random_entry_group_id)
out, err = capsys.readouterr()
assert (
"Created entry group"
" projects/{}/locations/{}/entryGroups/{}".format(
project_id, "us-central1", random_entry_group_id
)
in out
)
| 33.066667 | 79 | 0.729839 |
import create_entry_group
def test_create_entry_group(capsys, client, project_id, random_entry_group_id):
create_entry_group.create_entry_group(project_id, random_entry_group_id)
out, err = capsys.readouterr()
assert (
"Created entry group"
" projects/{}/locations/{}/entryGroups/{}".format(
project_id, "us-central1", random_entry_group_id
)
in out
)
| true | true |
f7fe80e8482fbcf1ea81dec053a2c1afcba45fd1 | 497 | py | Python | samples/python/preview.py | tmq902005/RealSenseID | b6882748cc7f47e041089c09a40eab6b0043fc9f | [
"Apache-2.0"
] | 63 | 2020-12-27T16:56:36.000Z | 2022-03-25T06:20:36.000Z | samples/python/preview.py | tmq902005/RealSenseID | b6882748cc7f47e041089c09a40eab6b0043fc9f | [
"Apache-2.0"
] | 122 | 2021-01-14T11:14:28.000Z | 2022-03-08T06:15:29.000Z | samples/python/preview.py | Surfndez/RealSenseID | f29171b8a5aba828d40e0ab120550730e5fbc080 | [
"Apache-2.0"
] | 39 | 2020-12-30T09:58:24.000Z | 2022-03-18T01:58:40.000Z | """
License: Apache 2.0. See LICENSE file in root directory.
Copyright(c) 2020-2021 Intel Corporation. All Rights Reserved.
"""
import time
import os
import rsid_py
def on_image(frame):
print(f'got_frame #{frame.number} {frame.width}x{frame.height}')
if frame.number > 10:
os._exit(0)
if __name__ == '__main__':
preview_cfg = rsid_py.PreviewConfig()
preview_cfg.camera_number = 0
p = rsid_py.Preview(preview_cfg)
p.start(on_image)
while True: time.sleep(10) | 23.666667 | 68 | 0.698189 | import time
import os
import rsid_py
def on_image(frame):
print(f'got_frame #{frame.number} {frame.width}x{frame.height}')
if frame.number > 10:
os._exit(0)
if __name__ == '__main__':
preview_cfg = rsid_py.PreviewConfig()
preview_cfg.camera_number = 0
p = rsid_py.Preview(preview_cfg)
p.start(on_image)
while True: time.sleep(10) | true | true |
f7fe80f2f6670205bcd2605e627c18a2e743f195 | 3,753 | py | Python | test/jobTest.py | harvardinformatics/jobTree | b4bdaeb2462b90ab8251713d4d2d8130c842cbe0 | [
"MIT"
] | 10 | 2015-02-05T16:02:06.000Z | 2020-07-17T06:12:42.000Z | test/jobTest.py | harvardinformatics/jobTree | b4bdaeb2462b90ab8251713d4d2d8130c842cbe0 | [
"MIT"
] | 16 | 2015-01-06T05:56:58.000Z | 2015-10-07T01:03:37.000Z | test/jobTest.py | benedictpaten/jobTree | 072be69f6214e06bd8588b5e73a60b758c191663 | [
"MIT"
] | 14 | 2015-01-05T23:34:12.000Z | 2019-03-07T17:45:17.000Z | #!/usr/bin/env python
"""Test Job class
"""
import unittest
import os
import time
import sys
import random
from sonLib.bioio import parseSuiteTestOptions
from sonLib.bioio import logger, system
from jobTree.src.job import Job
class TestCase(unittest.TestCase):
def testJobReadWriteAndDelete(self):
jobDir = os.path.join(os.getcwd(), "testJobDir")
os.mkdir(jobDir) #If directory already exists then the test will fail
command = "by your command"
memory = 2^32
cpu = 1
tryCount = 100
for i in xrange(10):
startTime = time.time()
for j in xrange(100):
j = Job(command, memory, cpu, tryCount, jobDir)
self.assertEquals(j.remainingRetryCount, tryCount)
self.assertEquals(j.jobDir, jobDir)
self.assertEquals(j.children, [])
self.assertEquals(j.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(j.messages, [])
j.write()
j = Job.read(j.getJobFileName())
self.assertEquals(j.remainingRetryCount, tryCount)
self.assertEquals(j.jobDir, jobDir)
self.assertEquals(j.children, [])
self.assertEquals(j.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(j.messages, [])
self.assertTrue(os.path.exists(j.getJobFileName()))
j.delete()
self.assertTrue(not os.path.exists(j.getJobFileName()))
print "It took %f seconds to load/unload jobs" % (time.time() - startTime) #We've just used it for benchmarking, so far
#Would be good to extend this trivial test
system("rm -rf %s" % jobDir)
def testJobUpdate(self):
jobDir = os.path.join(os.getcwd(), "testJobDir")
os.mkdir(jobDir) #If directory already exists then the test will fail
command = "by your command"
memory = 2^32
cpu = 1
tryCount = 100
for i in xrange(40):
startTime = time.time()
j = Job(command, memory, cpu, tryCount, jobDir)
childNumber = random.choice(range(20))
for k in xrange(childNumber):
j.children.append((command, memory, cpu))
self.assertEquals(len(j.children), childNumber)
j.update(tryCount=tryCount, depth=0)
j = Job.read(j.getJobFileName())
self.assertEquals(len(j.children) + len(j.followOnCommands), childNumber + 1)
for childJobFile, memory, cpu in j.children:
cJ = Job.read(childJobFile)
self.assertEquals(cJ.remainingRetryCount, tryCount)
#self.assertEquals(cJ.jobDir, os.path.split(cJ)[0])
self.assertEquals(cJ.children, [])
self.assertEquals(cJ.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(cJ.messages, [])
self.assertTrue(os.path.exists(cJ.getJobFileName()))
cJ.delete()
self.assertTrue(not os.path.exists(cJ.getJobFileName()))
self.assertEquals(os.listdir(jobDir), [ "job" ])
j.delete()
print "It took %f seconds to update jobs" % (time.time() - startTime) #We've just used it for benchmarking, so far
system("rm -rf %s" % jobDir)
def main():
parseSuiteTestOptions()
sys.argv = sys.argv[:1]
unittest.main()
if __name__ == '__main__':
#import cProfile
#cProfile.run('main()', "fooprof")
#import pstats
#p = pstats.Stats('fooprof')
#p.strip_dirs().sort_stats(-1).print_stats()
#print p
main()
| 39.09375 | 132 | 0.57927 |
"""Test Job class
"""
import unittest
import os
import time
import sys
import random
from sonLib.bioio import parseSuiteTestOptions
from sonLib.bioio import logger, system
from jobTree.src.job import Job
class TestCase(unittest.TestCase):
def testJobReadWriteAndDelete(self):
jobDir = os.path.join(os.getcwd(), "testJobDir")
os.mkdir(jobDir)
command = "by your command"
memory = 2^32
cpu = 1
tryCount = 100
for i in xrange(10):
startTime = time.time()
for j in xrange(100):
j = Job(command, memory, cpu, tryCount, jobDir)
self.assertEquals(j.remainingRetryCount, tryCount)
self.assertEquals(j.jobDir, jobDir)
self.assertEquals(j.children, [])
self.assertEquals(j.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(j.messages, [])
j.write()
j = Job.read(j.getJobFileName())
self.assertEquals(j.remainingRetryCount, tryCount)
self.assertEquals(j.jobDir, jobDir)
self.assertEquals(j.children, [])
self.assertEquals(j.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(j.messages, [])
self.assertTrue(os.path.exists(j.getJobFileName()))
j.delete()
self.assertTrue(not os.path.exists(j.getJobFileName()))
print "It took %f seconds to load/unload jobs" % (time.time() - startTime)
#Would be good to extend this trivial test
system("rm -rf %s" % jobDir)
def testJobUpdate(self):
jobDir = os.path.join(os.getcwd(), "testJobDir")
os.mkdir(jobDir) #If directory already exists then the test will fail
command = "by your command"
memory = 2^32
cpu = 1
tryCount = 100
for i in xrange(40):
startTime = time.time()
j = Job(command, memory, cpu, tryCount, jobDir)
childNumber = random.choice(range(20))
for k in xrange(childNumber):
j.children.append((command, memory, cpu))
self.assertEquals(len(j.children), childNumber)
j.update(tryCount=tryCount, depth=0)
j = Job.read(j.getJobFileName())
self.assertEquals(len(j.children) + len(j.followOnCommands), childNumber + 1)
for childJobFile, memory, cpu in j.children:
cJ = Job.read(childJobFile)
self.assertEquals(cJ.remainingRetryCount, tryCount)
#self.assertEquals(cJ.jobDir, os.path.split(cJ)[0])
self.assertEquals(cJ.children, [])
self.assertEquals(cJ.followOnCommands, [ (command, memory, cpu, 0)])
self.assertEquals(cJ.messages, [])
self.assertTrue(os.path.exists(cJ.getJobFileName()))
cJ.delete()
self.assertTrue(not os.path.exists(cJ.getJobFileName()))
self.assertEquals(os.listdir(jobDir), [ "job" ])
j.delete()
print "It took %f seconds to update jobs" % (time.time() - startTime) #We've just used it for benchmarking, so far
system("rm -rf %s" % jobDir)
def main():
parseSuiteTestOptions()
sys.argv = sys.argv[:1]
unittest.main()
if __name__ == '__main__':
main()
| false | true |
f7fe81eb8b18aea5e9f85788db3c3c72624547db | 1,278 | py | Python | hs_core/tests/api/rest/test_resource_meta.py | hydroshare/hydroshare | bf9888bbe61507aff070b1dfcec2fdec1921468d | [
"BSD-3-Clause"
] | 178 | 2015-01-08T23:03:36.000Z | 2022-03-03T13:56:45.000Z | hs_core/tests/api/rest/test_resource_meta.py | hydroshare/hydroshare | bf9888bbe61507aff070b1dfcec2fdec1921468d | [
"BSD-3-Clause"
] | 4,125 | 2015-01-01T14:26:15.000Z | 2022-03-31T16:38:55.000Z | hs_core/tests/api/rest/test_resource_meta.py | hydroshare/hydroshare | bf9888bbe61507aff070b1dfcec2fdec1921468d | [
"BSD-3-Clause"
] | 53 | 2015-03-15T17:56:51.000Z | 2022-03-17T00:32:16.000Z | import os
import json
import tempfile
import shutil
from lxml import etree
from rest_framework import status
from hs_core.hydroshare import resource
from .base import HSRESTTestCase
class TestResourceMetadata(HSRESTTestCase):
def setUp(self):
super(TestResourceMetadata, self).setUp()
self.rtype = 'GenericResource'
self.title = 'My Test resource'
res = resource.create_resource(self.rtype,
self.user,
self.title)
self.pid = res.short_id
self.resources_to_delete.append(self.pid)
def test_get_sysmeta(self):
# Get the resource system metadata
sysmeta_url = "/hsapi/resource/{res_id}/sysmeta/".format(res_id=self.pid)
response = self.client.get(sysmeta_url)
self.assertEqual(response.status_code, status.HTTP_200_OK)
content = json.loads(response.content.decode())
self.assertEqual(content['resource_type'], self.rtype)
self.assertEqual(content['resource_title'], self.title)
res_tail = '/' + os.path.join('resource', self.pid) + '/'
self.assertTrue(content['resource_url'].startswith('http://'))
self.assertTrue(content['resource_url'].endswith(res_tail))
| 33.631579 | 81 | 0.656495 | import os
import json
import tempfile
import shutil
from lxml import etree
from rest_framework import status
from hs_core.hydroshare import resource
from .base import HSRESTTestCase
class TestResourceMetadata(HSRESTTestCase):
def setUp(self):
super(TestResourceMetadata, self).setUp()
self.rtype = 'GenericResource'
self.title = 'My Test resource'
res = resource.create_resource(self.rtype,
self.user,
self.title)
self.pid = res.short_id
self.resources_to_delete.append(self.pid)
def test_get_sysmeta(self):
sysmeta_url = "/hsapi/resource/{res_id}/sysmeta/".format(res_id=self.pid)
response = self.client.get(sysmeta_url)
self.assertEqual(response.status_code, status.HTTP_200_OK)
content = json.loads(response.content.decode())
self.assertEqual(content['resource_type'], self.rtype)
self.assertEqual(content['resource_title'], self.title)
res_tail = '/' + os.path.join('resource', self.pid) + '/'
self.assertTrue(content['resource_url'].startswith('http://'))
self.assertTrue(content['resource_url'].endswith(res_tail))
| true | true |
f7fe822d158e70215afe6a1961af6b057bea9abb | 875 | py | Python | setup.py | jialuechen/raptor | bac516a45dfee9d21ac14221a2d9d5bef810cbd0 | [
"MIT"
] | null | null | null | setup.py | jialuechen/raptor | bac516a45dfee9d21ac14221a2d9d5bef810cbd0 | [
"MIT"
] | null | null | null | setup.py | jialuechen/raptor | bac516a45dfee9d21ac14221a2d9d5bef810cbd0 | [
"MIT"
] | null | null | null | from distutils.core import setup
setup(
name="raptor",
packages=["raptor"],
version="0.1.0",
description="Technical Analysis Library",
long_description="It is a Technical Analysis library to financial time series datasets.",
author="Julius Chen",
author_email="quantchen@protonmail.com",
url="https://github.com/jialuechen/raptor",
maintainer="Julius Chen",
maintainer_email="quantchen@protonmail.com",
install_requires=[
"dask",
],
download_url="https://github.com/jialuechen/raptor/raptor/0.1.0",
keywords=["technical analysis", "python3", "dask"],
license="The MIT License (MIT)",
classifiers=[
"Intended Audience :: Quantitative Finance Industry",
"Programming Language :: Python :: 3.9",
"License :: OSI Approved :: MIT License",
],
project_urls={
},
) | 31.25 | 93 | 0.649143 | from distutils.core import setup
setup(
name="raptor",
packages=["raptor"],
version="0.1.0",
description="Technical Analysis Library",
long_description="It is a Technical Analysis library to financial time series datasets.",
author="Julius Chen",
author_email="quantchen@protonmail.com",
url="https://github.com/jialuechen/raptor",
maintainer="Julius Chen",
maintainer_email="quantchen@protonmail.com",
install_requires=[
"dask",
],
download_url="https://github.com/jialuechen/raptor/raptor/0.1.0",
keywords=["technical analysis", "python3", "dask"],
license="The MIT License (MIT)",
classifiers=[
"Intended Audience :: Quantitative Finance Industry",
"Programming Language :: Python :: 3.9",
"License :: OSI Approved :: MIT License",
],
project_urls={
},
) | true | true |
f7fe82420c012cc1f5bb4fa6be66f74146bdf04f | 13,963 | py | Python | lib/interface.py | Messer4/electrum-cash | 531547ec2b0f26569caddbf6f1037095c200d4e6 | [
"MIT"
] | 1 | 2018-01-15T04:34:53.000Z | 2018-01-15T04:34:53.000Z | lib/interface.py | Messer4/electrum-cash | 531547ec2b0f26569caddbf6f1037095c200d4e6 | [
"MIT"
] | null | null | null | lib/interface.py | Messer4/electrum-cash | 531547ec2b0f26569caddbf6f1037095c200d4e6 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
#
# Electrum - lightweight Bitcoin client
# Copyright (C) 2011 thomasv@gitorious
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation files
# (the "Software"), to deal in the Software without restriction,
# including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sublicense, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so,
# subject to the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
# BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import os
import re
import socket
import ssl
import sys
import threading
import time
import traceback
import requests
from .util import print_error
ca_path = requests.certs.where()
from . import util
from . import x509
from . import pem
def Connection(server, queue, config_path):
"""Makes asynchronous connections to a remote electrum server.
Returns the running thread that is making the connection.
Once the thread has connected, it finishes, placing a tuple on the
queue of the form (server, socket), where socket is None if
connection failed.
"""
host, port, protocol = server.rsplit(':', 2)
if not protocol in 'st':
raise Exception('Unknown protocol: %s' % protocol)
c = TcpConnection(server, queue, config_path)
c.start()
return c
class TcpConnection(threading.Thread, util.PrintError):
def __init__(self, server, queue, config_path):
threading.Thread.__init__(self)
self.config_path = config_path
self.queue = queue
self.server = server
self.host, self.port, self.protocol = self.server.rsplit(':', 2)
self.host = str(self.host)
self.port = int(self.port)
self.use_ssl = (self.protocol == 's')
self.daemon = True
def diagnostic_name(self):
return self.host
def check_host_name(self, peercert, name):
"""Simple certificate/host name checker. Returns True if the
certificate matches, False otherwise. Does not support
wildcards."""
# Check that the peer has supplied a certificate.
# None/{} is not acceptable.
if not peercert:
return False
if 'subjectAltName' in peercert:
for typ, val in peercert["subjectAltName"]:
if typ == "DNS" and val == name:
return True
else:
# Only check the subject DN if there is no subject alternative
# name.
cn = None
for attr, val in peercert["subject"]:
# Use most-specific (last) commonName attribute.
if attr == "commonName":
cn = val
if cn is not None:
return cn == name
return False
def get_simple_socket(self):
try:
l = socket.getaddrinfo(self.host, self.port, socket.AF_UNSPEC, socket.SOCK_STREAM)
except socket.gaierror:
self.print_error("cannot resolve hostname")
return
e = None
for res in l:
try:
s = socket.socket(res[0], socket.SOCK_STREAM)
s.settimeout(10)
s.connect(res[4])
s.settimeout(2)
s.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)
return s
except BaseException as _e:
e = _e
continue
else:
self.print_error("failed to connect", str(e))
@staticmethod
def get_ssl_context(cert_reqs, ca_certs):
context = ssl.create_default_context(purpose=ssl.Purpose.SERVER_AUTH, cafile=ca_certs)
context.check_hostname = False
context.verify_mode = cert_reqs
context.options |= ssl.OP_NO_SSLv2
context.options |= ssl.OP_NO_SSLv3
context.options |= ssl.OP_NO_TLSv1
return context
def get_socket(self):
if self.use_ssl:
cert_path = os.path.join(self.config_path, 'certs', self.host)
if not os.path.exists(cert_path):
is_new = True
s = self.get_simple_socket()
if s is None:
return
# try with CA first
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_REQUIRED, ca_certs=ca_path)
s = context.wrap_socket(s, do_handshake_on_connect=True)
except ssl.SSLError as e:
self.print_error(e)
s = None
except:
return
if s and self.check_host_name(s.getpeercert(), self.host):
self.print_error("SSL certificate signed by CA")
return s
# get server certificate.
# Do not use ssl.get_server_certificate because it does not work with proxy
s = self.get_simple_socket()
if s is None:
return
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_NONE, ca_certs=None)
s = context.wrap_socket(s)
except ssl.SSLError as e:
self.print_error("SSL error retrieving SSL certificate:", e)
return
except:
return
dercert = s.getpeercert(True)
s.close()
cert = ssl.DER_cert_to_PEM_cert(dercert)
# workaround android bug
cert = re.sub("([^\n])-----END CERTIFICATE-----","\\1\n-----END CERTIFICATE-----",cert)
temporary_path = cert_path + '.temp'
with open(temporary_path,"w") as f:
f.write(cert)
else:
is_new = False
s = self.get_simple_socket()
if s is None:
return
if self.use_ssl:
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_REQUIRED,
ca_certs=(temporary_path if is_new else cert_path))
s = context.wrap_socket(s, do_handshake_on_connect=True)
except socket.timeout:
self.print_error('timeout')
return
except ssl.SSLError as e:
self.print_error("SSL error:", e)
if e.errno != 1:
return
if is_new:
rej = cert_path + '.rej'
if os.path.exists(rej):
os.unlink(rej)
os.rename(temporary_path, rej)
else:
with open(cert_path) as f:
cert = f.read()
try:
b = pem.dePem(cert, 'CERTIFICATE')
x = x509.X509(b)
except:
traceback.print_exc(file=sys.stderr)
self.print_error("wrong certificate")
return
try:
x.check_date()
except:
self.print_error("certificate has expired:", cert_path)
os.unlink(cert_path)
return
self.print_error("wrong certificate")
if e.errno == 104:
return
return
except BaseException as e:
self.print_error(e)
traceback.print_exc(file=sys.stderr)
return
if is_new:
self.print_error("saving certificate")
os.rename(temporary_path, cert_path)
return s
def run(self):
socket = self.get_socket()
if socket:
self.print_error("connected")
self.queue.put((self.server, socket))
class Interface(util.PrintError):
"""The Interface class handles a socket connected to a single remote
electrum server. It's exposed API is:
- Member functions close(), fileno(), get_responses(), has_timed_out(),
ping_required(), queue_request(), send_requests()
- Member variable server.
"""
def __init__(self, server, socket):
self.server = server
self.host, _, _ = server.rsplit(':', 2)
self.socket = socket
self.pipe = util.SocketPipe(socket)
self.pipe.set_timeout(0.0) # Don't wait for data
# Dump network messages. Set at runtime from the console.
self.debug = False
self.unsent_requests = []
self.unanswered_requests = {}
# Set last ping to zero to ensure immediate ping
self.last_request = time.time()
self.last_ping = 0
self.closed_remotely = False
def diagnostic_name(self):
return self.host
def fileno(self):
# Needed for select
return self.socket.fileno()
def close(self):
if not self.closed_remotely:
try:
self.socket.shutdown(socket.SHUT_RDWR)
except socket.error:
pass
self.socket.close()
def queue_request(self, *args): # method, params, _id
'''Queue a request, later to be send with send_requests when the
socket is available for writing.
'''
self.request_time = time.time()
self.unsent_requests.append(args)
def num_requests(self):
'''Keep unanswered requests below 100'''
n = 100 - len(self.unanswered_requests)
return min(n, len(self.unsent_requests))
def send_requests(self):
'''Sends queued requests. Returns False on failure.'''
make_dict = lambda m, p, i: {'method': m, 'params': p, 'id': i}
n = self.num_requests()
wire_requests = self.unsent_requests[0:n]
try:
self.pipe.send_all([make_dict(*r) for r in wire_requests])
except socket.error as e:
self.print_error("socket error:", e)
return False
self.unsent_requests = self.unsent_requests[n:]
for request in wire_requests:
if self.debug:
self.print_error("-->", request)
self.unanswered_requests[request[2]] = request
return True
def ping_required(self):
'''Maintains time since last ping. Returns True if a ping should
be sent.
'''
now = time.time()
if now - self.last_ping > 60:
self.last_ping = now
return True
return False
def has_timed_out(self):
'''Returns True if the interface has timed out.'''
if (self.unanswered_requests and time.time() - self.request_time > 10
and self.pipe.idle_time() > 10):
self.print_error("timeout", len(self.unanswered_requests))
return True
return False
def get_responses(self):
'''Call if there is data available on the socket. Returns a list of
(request, response) pairs. Notifications are singleton
unsolicited responses presumably as a result of prior
subscriptions, so request is None and there is no 'id' member.
Otherwise it is a response, which has an 'id' member and a
corresponding request. If the connection was closed remotely
or the remote server is misbehaving, a (None, None) will appear.
'''
responses = []
while True:
try:
response = self.pipe.get()
except util.timeout:
break
if not type(response) is dict:
responses.append((None, None))
if response is None:
self.closed_remotely = True
self.print_error("connection closed remotely")
break
if self.debug:
self.print_error("<--", response)
wire_id = response.get('id', None)
if wire_id is None: # Notification
responses.append((None, response))
else:
request = self.unanswered_requests.pop(wire_id, None)
if request:
responses.append((request, response))
else:
self.print_error("unknown wire ID", wire_id)
responses.append((None, None)) # Signal
break
return responses
def check_cert(host, cert):
try:
b = pem.dePem(cert, 'CERTIFICATE')
x = x509.X509(b)
except:
traceback.print_exc(file=sys.stdout)
return
try:
x.check_date()
expired = False
except:
expired = True
m = "host: %s\n"%host
m += "has_expired: %s\n"% expired
util.print_msg(m)
# Used by tests
def _match_hostname(name, val):
if val == name:
return True
return val.startswith('*.') and name.endswith(val[1:])
def test_certificates():
from .simple_config import SimpleConfig
config = SimpleConfig()
mydir = os.path.join(config.path, "certs")
certs = os.listdir(mydir)
for c in certs:
p = os.path.join(mydir,c)
with open(p) as f:
cert = f.read()
check_cert(c, cert)
if __name__ == "__main__":
test_certificates()
| 34.476543 | 103 | 0.563919 |
import os
import re
import socket
import ssl
import sys
import threading
import time
import traceback
import requests
from .util import print_error
ca_path = requests.certs.where()
from . import util
from . import x509
from . import pem
def Connection(server, queue, config_path):
host, port, protocol = server.rsplit(':', 2)
if not protocol in 'st':
raise Exception('Unknown protocol: %s' % protocol)
c = TcpConnection(server, queue, config_path)
c.start()
return c
class TcpConnection(threading.Thread, util.PrintError):
def __init__(self, server, queue, config_path):
threading.Thread.__init__(self)
self.config_path = config_path
self.queue = queue
self.server = server
self.host, self.port, self.protocol = self.server.rsplit(':', 2)
self.host = str(self.host)
self.port = int(self.port)
self.use_ssl = (self.protocol == 's')
self.daemon = True
def diagnostic_name(self):
return self.host
def check_host_name(self, peercert, name):
if not peercert:
return False
if 'subjectAltName' in peercert:
for typ, val in peercert["subjectAltName"]:
if typ == "DNS" and val == name:
return True
else:
cn = None
for attr, val in peercert["subject"]:
if attr == "commonName":
cn = val
if cn is not None:
return cn == name
return False
def get_simple_socket(self):
try:
l = socket.getaddrinfo(self.host, self.port, socket.AF_UNSPEC, socket.SOCK_STREAM)
except socket.gaierror:
self.print_error("cannot resolve hostname")
return
e = None
for res in l:
try:
s = socket.socket(res[0], socket.SOCK_STREAM)
s.settimeout(10)
s.connect(res[4])
s.settimeout(2)
s.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1)
return s
except BaseException as _e:
e = _e
continue
else:
self.print_error("failed to connect", str(e))
@staticmethod
def get_ssl_context(cert_reqs, ca_certs):
context = ssl.create_default_context(purpose=ssl.Purpose.SERVER_AUTH, cafile=ca_certs)
context.check_hostname = False
context.verify_mode = cert_reqs
context.options |= ssl.OP_NO_SSLv2
context.options |= ssl.OP_NO_SSLv3
context.options |= ssl.OP_NO_TLSv1
return context
def get_socket(self):
if self.use_ssl:
cert_path = os.path.join(self.config_path, 'certs', self.host)
if not os.path.exists(cert_path):
is_new = True
s = self.get_simple_socket()
if s is None:
return
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_REQUIRED, ca_certs=ca_path)
s = context.wrap_socket(s, do_handshake_on_connect=True)
except ssl.SSLError as e:
self.print_error(e)
s = None
except:
return
if s and self.check_host_name(s.getpeercert(), self.host):
self.print_error("SSL certificate signed by CA")
return s
s = self.get_simple_socket()
if s is None:
return
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_NONE, ca_certs=None)
s = context.wrap_socket(s)
except ssl.SSLError as e:
self.print_error("SSL error retrieving SSL certificate:", e)
return
except:
return
dercert = s.getpeercert(True)
s.close()
cert = ssl.DER_cert_to_PEM_cert(dercert)
cert = re.sub("([^\n])-----END CERTIFICATE-----","\\1\n-----END CERTIFICATE-----",cert)
temporary_path = cert_path + '.temp'
with open(temporary_path,"w") as f:
f.write(cert)
else:
is_new = False
s = self.get_simple_socket()
if s is None:
return
if self.use_ssl:
try:
context = self.get_ssl_context(cert_reqs=ssl.CERT_REQUIRED,
ca_certs=(temporary_path if is_new else cert_path))
s = context.wrap_socket(s, do_handshake_on_connect=True)
except socket.timeout:
self.print_error('timeout')
return
except ssl.SSLError as e:
self.print_error("SSL error:", e)
if e.errno != 1:
return
if is_new:
rej = cert_path + '.rej'
if os.path.exists(rej):
os.unlink(rej)
os.rename(temporary_path, rej)
else:
with open(cert_path) as f:
cert = f.read()
try:
b = pem.dePem(cert, 'CERTIFICATE')
x = x509.X509(b)
except:
traceback.print_exc(file=sys.stderr)
self.print_error("wrong certificate")
return
try:
x.check_date()
except:
self.print_error("certificate has expired:", cert_path)
os.unlink(cert_path)
return
self.print_error("wrong certificate")
if e.errno == 104:
return
return
except BaseException as e:
self.print_error(e)
traceback.print_exc(file=sys.stderr)
return
if is_new:
self.print_error("saving certificate")
os.rename(temporary_path, cert_path)
return s
def run(self):
socket = self.get_socket()
if socket:
self.print_error("connected")
self.queue.put((self.server, socket))
class Interface(util.PrintError):
def __init__(self, server, socket):
self.server = server
self.host, _, _ = server.rsplit(':', 2)
self.socket = socket
self.pipe = util.SocketPipe(socket)
self.pipe.set_timeout(0.0)
# Dump network messages. Set at runtime from the console.
self.debug = False
self.unsent_requests = []
self.unanswered_requests = {}
# Set last ping to zero to ensure immediate ping
self.last_request = time.time()
self.last_ping = 0
self.closed_remotely = False
def diagnostic_name(self):
return self.host
def fileno(self):
# Needed for select
return self.socket.fileno()
def close(self):
if not self.closed_remotely:
try:
self.socket.shutdown(socket.SHUT_RDWR)
except socket.error:
pass
self.socket.close()
def queue_request(self, *args): # method, params, _id
self.request_time = time.time()
self.unsent_requests.append(args)
def num_requests(self):
n = 100 - len(self.unanswered_requests)
return min(n, len(self.unsent_requests))
def send_requests(self):
make_dict = lambda m, p, i: {'method': m, 'params': p, 'id': i}
n = self.num_requests()
wire_requests = self.unsent_requests[0:n]
try:
self.pipe.send_all([make_dict(*r) for r in wire_requests])
except socket.error as e:
self.print_error("socket error:", e)
return False
self.unsent_requests = self.unsent_requests[n:]
for request in wire_requests:
if self.debug:
self.print_error("-->", request)
self.unanswered_requests[request[2]] = request
return True
def ping_required(self):
now = time.time()
if now - self.last_ping > 60:
self.last_ping = now
return True
return False
def has_timed_out(self):
if (self.unanswered_requests and time.time() - self.request_time > 10
and self.pipe.idle_time() > 10):
self.print_error("timeout", len(self.unanswered_requests))
return True
return False
def get_responses(self):
responses = []
while True:
try:
response = self.pipe.get()
except util.timeout:
break
if not type(response) is dict:
responses.append((None, None))
if response is None:
self.closed_remotely = True
self.print_error("connection closed remotely")
break
if self.debug:
self.print_error("<--", response)
wire_id = response.get('id', None)
if wire_id is None: # Notification
responses.append((None, response))
else:
request = self.unanswered_requests.pop(wire_id, None)
if request:
responses.append((request, response))
else:
self.print_error("unknown wire ID", wire_id)
responses.append((None, None)) # Signal
break
return responses
def check_cert(host, cert):
try:
b = pem.dePem(cert, 'CERTIFICATE')
x = x509.X509(b)
except:
traceback.print_exc(file=sys.stdout)
return
try:
x.check_date()
expired = False
except:
expired = True
m = "host: %s\n"%host
m += "has_expired: %s\n"% expired
util.print_msg(m)
# Used by tests
def _match_hostname(name, val):
if val == name:
return True
return val.startswith('*.') and name.endswith(val[1:])
def test_certificates():
from .simple_config import SimpleConfig
config = SimpleConfig()
mydir = os.path.join(config.path, "certs")
certs = os.listdir(mydir)
for c in certs:
p = os.path.join(mydir,c)
with open(p) as f:
cert = f.read()
check_cert(c, cert)
if __name__ == "__main__":
test_certificates()
| true | true |
f7fe83299a66644de31003a17d8b9e1d748891ee | 1,334 | py | Python | spanner/tests/system/utils/scrub_instances.py | jo2y/google-cloud-python | 1b76727be16bc4335276f793340bb72d32be7166 | [
"Apache-2.0"
] | 1 | 2018-06-29T17:53:28.000Z | 2018-06-29T17:53:28.000Z | spanner/tests/system/utils/scrub_instances.py | jo2y/google-cloud-python | 1b76727be16bc4335276f793340bb72d32be7166 | [
"Apache-2.0"
] | 4 | 2018-11-13T22:15:36.000Z | 2018-12-07T18:31:38.000Z | spanner/tests/system/utils/scrub_instances.py | jo2y/google-cloud-python | 1b76727be16bc4335276f793340bb72d32be7166 | [
"Apache-2.0"
] | 1 | 2021-06-30T11:44:03.000Z | 2021-06-30T11:44:03.000Z | # Copyright 2017 Google LLC All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from google.cloud.spanner import Client
from .streaming_utils import INSTANCE_NAME as STREAMING_INSTANCE
STANDARD_INSTANCE = 'google-cloud-python-systest'
def scrub_instances(client):
for instance in client.list_instances():
if instance.name == STREAMING_INSTANCE:
print('Not deleting streaming instance: {}'.format(
STREAMING_INSTANCE))
continue
elif instance.name == STANDARD_INSTANCE:
print('Not deleting standard instance: {}'.format(
STANDARD_INSTANCE))
else:
print("deleting instance: {}".format(instance.name))
instance.delete()
if __name__ == '__main__':
client = Client()
scrub_instances(client)
| 35.105263 | 74 | 0.703148 |
from google.cloud.spanner import Client
from .streaming_utils import INSTANCE_NAME as STREAMING_INSTANCE
STANDARD_INSTANCE = 'google-cloud-python-systest'
def scrub_instances(client):
for instance in client.list_instances():
if instance.name == STREAMING_INSTANCE:
print('Not deleting streaming instance: {}'.format(
STREAMING_INSTANCE))
continue
elif instance.name == STANDARD_INSTANCE:
print('Not deleting standard instance: {}'.format(
STANDARD_INSTANCE))
else:
print("deleting instance: {}".format(instance.name))
instance.delete()
if __name__ == '__main__':
client = Client()
scrub_instances(client)
| true | true |
f7fe8377430d72eab44fd5820adc26aa07a46ba2 | 6,769 | py | Python | models/sequential_model.py | aasseman/mi-prometheus | c655c88cc6aec4d0724c19ea95209f1c2dd6770d | [
"Apache-2.0"
] | null | null | null | models/sequential_model.py | aasseman/mi-prometheus | c655c88cc6aec4d0724c19ea95209f1c2dd6770d | [
"Apache-2.0"
] | null | null | null | models/sequential_model.py | aasseman/mi-prometheus | c655c88cc6aec4d0724c19ea95209f1c2dd6770d | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright (C) IBM Corporation 2018
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""sequential_model.py: contains base model for all sequential models"""
__author__ = "Tomasz Kornuta"
import numpy as np
import logging
import torch
from models.model import Model
from problems.problem import DataTuple
class SequentialModel(Model):
"""
Class representing base class for all sequential models.
Provides basic plotting functionality.
"""
def __init__(self, params):
"""
Initializes application state and sets plot if visualization flag is
turned on.
:param params: Parameters read from configuration file.
"""
super(SequentialModel, self).__init__(params)
def plot(self, data_tuple, predictions, sample_number=0):
"""
Creates a default interactive visualization, with a slider enabling to
move forth and back along the time axis (iteration in a given episode).
The default visualizatoin contains input, output and target sequences.
For more model/problem dependent visualization please overwrite this
method in the derived model class.
:param data_tuple: Data tuple containing
- input [BATCH_SIZE x SEQUENCE_LENGTH x INPUT_DATA_SIZE] and
- target sequences [BATCH_SIZE x SEQUENCE_LENGTH x OUTPUT_DATA_SIZE]
:param predictions: Prediction sequence [BATCH_SIZE x SEQUENCE_LENGTH x OUTPUT_DATA_SIZE]
:param sample_number: Number of sample in batch (DEFAULT: 0)
"""
# Check if we are supposed to visualize at all.
if not self.app_state.visualize:
return False
# Initialize timePlot window - if required.
if self.plotWindow is None:
from utils.time_plot import TimePlot
self.plotWindow = TimePlot()
from matplotlib.figure import Figure
import matplotlib.ticker as ticker
# Change fonts globally - for all figures/subsplots at once.
#from matplotlib import rc
#rc('font', **{'family': 'Times New Roman'})
import matplotlib.pylab as pylab
params = {
# 'legend.fontsize': '28',
'axes.titlesize': 'large',
'axes.labelsize': 'large',
'xtick.labelsize': 'medium',
'ytick.labelsize': 'medium'}
pylab.rcParams.update(params)
# Create a single "figure layout" for all displayed frames.
fig = Figure()
axes = fig.subplots(3, 1, sharex=True, sharey=False, gridspec_kw={
'width_ratios': [predictions.shape[0]]})
# Set ticks.
axes[0].xaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[0].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[1].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[2].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
# Set labels.
axes[0].set_title('Inputs')
axes[0].set_ylabel('Control/Data bits')
axes[1].set_title('Targets')
axes[1].set_ylabel('Data bits')
axes[2].set_title('Predictions')
axes[2].set_ylabel('Data bits')
axes[2].set_xlabel('Item number')
fig.set_tight_layout(True)
# Detach a sample from batch and copy it to CPU.
inputs_seq = data_tuple.inputs[sample_number].cpu().detach().numpy()
targets_seq = data_tuple.targets[sample_number].cpu().detach().numpy()
predictions_seq = predictions[sample_number].cpu().detach().numpy()
# Create empty matrices.
x = np.transpose(np.zeros(inputs_seq.shape))
y = np.transpose(np.zeros(predictions_seq.shape))
z = np.transpose(np.zeros(targets_seq.shape))
# Log sequence length - so the user can understand what is going on.
logger = logging.getLogger('ModelBase')
logger.info(
"Generating dynamic visualization of {} figures, please wait...".format(
inputs_seq.shape[0]))
# Create frames - a list of lists, where each row is a list of artists
# used to draw a given frame.
frames = []
for i, (input_word, prediction_word, target_word) in enumerate(
zip(inputs_seq, predictions_seq, targets_seq)):
# Display information every 10% of figures.
if (inputs_seq.shape[0] > 10) and (i %
(inputs_seq.shape[0] // 10) == 0):
logger.info(
"Generating figure {}/{}".format(i, inputs_seq.shape[0]))
# Add words to adequate positions.
x[:, i] = input_word
y[:, i] = target_word
z[:, i] = prediction_word
# Create "Artists" drawing data on "ImageAxes".
artists = [None] * len(fig.axes)
# Tell artists what to do;)
artists[0] = axes[0].imshow(
x, interpolation='nearest', aspect='auto')
artists[1] = axes[1].imshow(
y, interpolation='nearest', aspect='auto')
artists[2] = axes[2].imshow(
z, interpolation='nearest', aspect='auto')
# Add "frame".
frames.append(artists)
# Plot figure and list of frames.
self.plotWindow.update(fig, frames)
# Return True if user closed the window.
return self.plotWindow.is_closed
if __name__ == '__main__':
# Set logging level.
logging.basicConfig(level=logging.DEBUG)
# Set visualization.
AppState().visualize = True
# Test sequential model.
test = SequentialModel()
while True:
# Generate new sequence.
x = np.random.binomial(1, 0.5, (1, 8, 15))
y = np.random.binomial(1, 0.5, (1, 8, 15))
z = np.random.binomial(1, 0.5, (1, 8, 15))
# Transform to PyTorch.
x = torch.from_numpy(x).type(torch.FloatTensor)
y = torch.from_numpy(y).type(torch.FloatTensor)
z = torch.from_numpy(z).type(torch.FloatTensor)
dt = DataTuple(x, y)
# Plot it and check whether window was closed or not.
if test.plot(dt, z):
break
| 36.589189 | 97 | 0.622987 |
__author__ = "Tomasz Kornuta"
import numpy as np
import logging
import torch
from models.model import Model
from problems.problem import DataTuple
class SequentialModel(Model):
def __init__(self, params):
super(SequentialModel, self).__init__(params)
def plot(self, data_tuple, predictions, sample_number=0):
if not self.app_state.visualize:
return False
if self.plotWindow is None:
from utils.time_plot import TimePlot
self.plotWindow = TimePlot()
from matplotlib.figure import Figure
import matplotlib.ticker as ticker
import matplotlib.pylab as pylab
params = {
'axes.titlesize': 'large',
'axes.labelsize': 'large',
'xtick.labelsize': 'medium',
'ytick.labelsize': 'medium'}
pylab.rcParams.update(params)
fig = Figure()
axes = fig.subplots(3, 1, sharex=True, sharey=False, gridspec_kw={
'width_ratios': [predictions.shape[0]]})
axes[0].xaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[0].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[1].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[2].yaxis.set_major_locator(ticker.MaxNLocator(integer=True))
axes[0].set_title('Inputs')
axes[0].set_ylabel('Control/Data bits')
axes[1].set_title('Targets')
axes[1].set_ylabel('Data bits')
axes[2].set_title('Predictions')
axes[2].set_ylabel('Data bits')
axes[2].set_xlabel('Item number')
fig.set_tight_layout(True)
inputs_seq = data_tuple.inputs[sample_number].cpu().detach().numpy()
targets_seq = data_tuple.targets[sample_number].cpu().detach().numpy()
predictions_seq = predictions[sample_number].cpu().detach().numpy()
x = np.transpose(np.zeros(inputs_seq.shape))
y = np.transpose(np.zeros(predictions_seq.shape))
z = np.transpose(np.zeros(targets_seq.shape))
logger = logging.getLogger('ModelBase')
logger.info(
"Generating dynamic visualization of {} figures, please wait...".format(
inputs_seq.shape[0]))
frames = []
for i, (input_word, prediction_word, target_word) in enumerate(
zip(inputs_seq, predictions_seq, targets_seq)):
if (inputs_seq.shape[0] > 10) and (i %
(inputs_seq.shape[0] // 10) == 0):
logger.info(
"Generating figure {}/{}".format(i, inputs_seq.shape[0]))
x[:, i] = input_word
y[:, i] = target_word
z[:, i] = prediction_word
artists = [None] * len(fig.axes)
artists[0] = axes[0].imshow(
x, interpolation='nearest', aspect='auto')
artists[1] = axes[1].imshow(
y, interpolation='nearest', aspect='auto')
artists[2] = axes[2].imshow(
z, interpolation='nearest', aspect='auto')
frames.append(artists)
self.plotWindow.update(fig, frames)
return self.plotWindow.is_closed
if __name__ == '__main__':
logging.basicConfig(level=logging.DEBUG)
AppState().visualize = True
test = SequentialModel()
while True:
x = np.random.binomial(1, 0.5, (1, 8, 15))
y = np.random.binomial(1, 0.5, (1, 8, 15))
z = np.random.binomial(1, 0.5, (1, 8, 15))
x = torch.from_numpy(x).type(torch.FloatTensor)
y = torch.from_numpy(y).type(torch.FloatTensor)
z = torch.from_numpy(z).type(torch.FloatTensor)
dt = DataTuple(x, y)
if test.plot(dt, z):
break
| true | true |
f7fe8399b91c10eca23e3b1a1abbacc1912f9d54 | 1,591 | py | Python | county_boundaries/python/main.py | CrunchyData/crunchy-foss4g-demodata | 1d8f92a07faf9bc1c6468e00c8e9148ae2ba8dfc | [
"Apache-2.0"
] | 9 | 2019-08-03T01:08:53.000Z | 2021-12-30T21:01:28.000Z | county_boundaries/python/main.py | CrunchyData/crunchy-foss4g-demodata | 1d8f92a07faf9bc1c6468e00c8e9148ae2ba8dfc | [
"Apache-2.0"
] | 11 | 2019-04-04T13:56:29.000Z | 2020-07-15T18:29:13.000Z | county_boundaries/python/main.py | CrunchyData/crunchy-foss4g-demodata | 1d8f92a07faf9bc1c6468e00c8e9148ae2ba8dfc | [
"Apache-2.0"
] | 2 | 2020-10-23T00:31:06.000Z | 2020-12-26T10:38:31.000Z | import fiona
from shapely.geometry import shape
from shapely.geometry import Point
from shapely.geometry import Polygon
from shapely.geometry import MultiPolygon
from shapely.wkb import dumps
import pprint
with fiona.open("../shapefile/tl_2018_us_county.shp", "r") as features:
pprint.pprint(next(features))
pprint.pprint(features.crs)
with open("../output/county_boundaries_copy.txt", "w") as output:
for item in features:
#pprint.pprint(item['id'])
output.write('"'+ item['properties']['STATEFP'] + '","')
output.write(item['properties']['COUNTYFP'] + '","')
output.write(item['properties']['COUNTYNS'] + '","')
output.write(item['properties']['GEOID'] + '","')
output.write(item['properties']['NAME'] + '","')
output.write(item['properties']['NAMELSAD'] + '","')
output.write(item['properties']['FUNCSTAT'] + '",')
output.write(str(item['properties']['ALAND']) + ',')
output.write(str(item['properties']['AWATER']) + ',')
lat = float(item['properties']['INTPTLAT'])
lon = float(item['properties']['INTPTLON'])
the_point = Point(lon, lat)
output.write(dumps(the_point, hex=True) + ',')
geom = None
try:
geom = MultiPolygon(item['geometry'])
except:
tempgeom = shape(item['geometry'])
geom = MultiPolygon([tempgeom])
output.write(dumps(geom, hex=True))
output.write('\n')
print("Done")
| 36.159091 | 71 | 0.568196 | import fiona
from shapely.geometry import shape
from shapely.geometry import Point
from shapely.geometry import Polygon
from shapely.geometry import MultiPolygon
from shapely.wkb import dumps
import pprint
with fiona.open("../shapefile/tl_2018_us_county.shp", "r") as features:
pprint.pprint(next(features))
pprint.pprint(features.crs)
with open("../output/county_boundaries_copy.txt", "w") as output:
for item in features:
output.write('"'+ item['properties']['STATEFP'] + '","')
output.write(item['properties']['COUNTYFP'] + '","')
output.write(item['properties']['COUNTYNS'] + '","')
output.write(item['properties']['GEOID'] + '","')
output.write(item['properties']['NAME'] + '","')
output.write(item['properties']['NAMELSAD'] + '","')
output.write(item['properties']['FUNCSTAT'] + '",')
output.write(str(item['properties']['ALAND']) + ',')
output.write(str(item['properties']['AWATER']) + ',')
lat = float(item['properties']['INTPTLAT'])
lon = float(item['properties']['INTPTLON'])
the_point = Point(lon, lat)
output.write(dumps(the_point, hex=True) + ',')
geom = None
try:
geom = MultiPolygon(item['geometry'])
except:
tempgeom = shape(item['geometry'])
geom = MultiPolygon([tempgeom])
output.write(dumps(geom, hex=True))
output.write('\n')
print("Done")
| true | true |
f7fe83d525177aa784e9d88b687bc0ef6c672ca1 | 26,304 | py | Python | src/consensus.py | isovic/samscripts | 4b8c122220ee7bc5909903e3ecabb8ed6a72965d | [
"MIT"
] | 4 | 2015-09-30T13:17:47.000Z | 2019-03-13T14:25:15.000Z | src/consensus.py | isovic/samscripts | 4b8c122220ee7bc5909903e3ecabb8ed6a72965d | [
"MIT"
] | 5 | 2015-11-09T09:21:44.000Z | 2016-08-18T09:18:44.000Z | src/consensus.py | isovic/samscripts | 4b8c122220ee7bc5909903e3ecabb8ed6a72965d | [
"MIT"
] | 6 | 2015-05-11T09:04:52.000Z | 2020-06-08T21:47:51.000Z | #! /usr/bin/env python
# Copyright Ivan Sovic, 2015. www.sovic.org
#
# Creates a pileup from a given SAM/BAM file, and calls consensus bases (or variants).
import os;
import sys;
import operator;
import subprocess;
def increase_in_dict(dict_counter, value):
try:
dict_counter[value] += 1;
except:
dict_counter[value] = 1;
def process_mpileup_line(line, line_number, ret_variant_list, ret_vcf_list, ret_snp_count, ret_insertion_count, ret_deletion_count, ret_num_undercovered_bases, ret_num_called_bases, ret_num_correct_bases, ret_coverage_sum, coverage_threshold, verbose=False):
# Split the line, and perform a sanity check.
split_line = line.strip().split('\t');
if (len(split_line) < 5 or len(split_line) > 6):
sys.stderr.write(line + '\n');
return 0;
ref_name = split_line[0];
position = split_line[1];
ref_base = split_line[2];
coverage = split_line[3];
original_bases = split_line[4];
if (len(split_line) == 6):
qualities = split_line[5];
bases = '';
# Replace the '.' and ',' signs with the actual reference base.
i = 0;
while (i < len(original_bases)):
if (original_bases[i] == '.' or original_bases[i] == ','):
bases += ref_base;
else:
bases += original_bases[i];
i += 1;
base_counts = {};
insertion_count = 0;
current_base_deletion_count = 0;
deletion_count = 0;
insertion_event_counts = {};
deletion_event_counts = {};
end_counts = 0;
# print 'position: %s' % position;
# print 'bases: "%s"' % bases;
# print 'line_number: %d' % line_number;
# print line;
# print '';
# sys.stdout.flush();
i = 0;
while (i < len(bases)):
base = bases[i];
if (base == r'^'):
# This is the starting position of a read. It encodes two
# symbols: '^' marking the read start and a char marking the
# mapping quality of the read.
#increase_in_dict(base_counts, bases[i + 1].upper());
i += 1; # Increase only by 1, because we have i += 1 down there.
elif (base == r'$'):
# This marks the end of a read.
end_counts += 1;
elif (base == r'*'):
# This is a deletion, just count it.
current_base_deletion_count += 1;
elif (base == r'-'):
# This marks the occurance of deletions. It is a composite object
# consisting of: the special character '-', the number of the deleted bases
# and the actual bases that are deleted (these bases follow the current position).
# In our approach, we ignore this case, because we count deletions one by one
# through the '*' character.
# Get the number of bases that need to be skipped in the string.
j = (i + 1);
while (bases[j] in '0123456789'):
j += 1;
num_bases = int(bases[(i + 1):j]);
skip_bases = (j - i) + num_bases - 1;
deletion_count += 1;
deletion = bases[j : (j + num_bases)].upper();
increase_in_dict(deletion_event_counts, deletion);
# Skip the length of the numeric entry plus the actual number of bases
# that need to be skipped.
i += skip_bases;
elif (base == r'+'):
# This marks the occurance of an insertion. It is a composite object
# consisting of: the special character '+', the number of the inserted bases
# and the actual bases that are inserted (these bases follow the current position).
# Similar to the deletion marking, but here we actually care about the bases,
# and we need to make an allele aware count.
# Get the number of bases that are inserted;
j = (i + 1);
while (bases[j] in '0123456789'):
j += 1;
num_bases = int(bases[(i + 1):j]);
skip_bases = (j - i) + num_bases - 1;
insertion_count += 1;
insertion = bases[j : (j + num_bases)].upper();
increase_in_dict(insertion_event_counts, insertion);
i += skip_bases;
else:
increase_in_dict(base_counts, bases[i].upper());
i += 1;
# TODO: An additional problematic case, discovered this on 03.11.2014., when analyzing BWA-MEM's mpileup.
# There are pileup bases that do not have any actual bases, but only the '*' symbols. How should this be handled properly?
# Example line from the mpileup file:
# gi|48994873|gb|U00096.2|_Escherichia_coli_str._K-12_substr._MG1655,_complete_genome 1938202 T 20 ******************** 8,2*#-;)$B>2$1&D-
# I chose to handle them as undercovered bases.
non_indel_coverage_current_base = int(coverage) - current_base_deletion_count;
if (verbose == True):
sys.stdout.write('%s\nbase_counts: %s\n' % (line.strip(), str(base_counts)));
# EDIT: Previously I compared the total coverage of the current base with the coverage threshold.
# However, the total coverage also accounts for the deletions denoted with the '*' sign, which I think
# isn't relevant, as deletions are counted prior to occuring, and at that point is already decided if there is going
# to be a deletion event. If we wound up at this base (i.e. this base didn't get skipped because of a deletion
# consensus), then the deletions on this base are ignored.
#if (int(coverage) < coverage_threshold or int(coverage) == current_base_deletion_count):
# if (non_indel_coverage_current_base < coverage_threshold):
if (int(coverage) < coverage_threshold):
ret_num_undercovered_bases[0] += 1;
# ret_coverage_sum[0] += 0;
ret_coverage_sum[0] += int(coverage); # TODO: Should I count total coverage of this base, or the non_indel_coverage_current_base?
sorted_base_counts = [['A', 0], ['C', 0], ['T', 0], ['G', 0]];
sorted_base_counts = sorted(base_counts.items(), key=operator.itemgetter(1));
try:
most_common_base_count = sorted_base_counts[-1][1];
except Exception, e:
most_common_base_count = 0;
pass;
#variant_line = 'undercovered1\tpos = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
#ret_variant_list.append(variant_line);
variant_line = 'undercovered1\tpos = %s\tref = %s\tcoverage = %d\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s' % (position, ref_name, int(coverage), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts));
ret_variant_list.append(variant_line);
### VCF output ###
qual = 1000;
info = 'DP=%s;TYPE=snp' % (coverage);
ref_field = ref_base;
alt_field = 'N';
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
else:
ret_num_called_bases[0] += 1;
ret_coverage_sum[0] += int(coverage); # TODO: Should I count total coverage of this base, or the non_indel_coverage_current_base?
most_common_base_count = 0;
### Handling base consensus.
sorted_base_counts = sorted(base_counts.items(), key=operator.itemgetter(1));
try:
most_common_base_count = sorted_base_counts[-1][1];
except Exception, e:
pass;
# sys.stderr.write(str(e) + '\n');
# sys.stderr.write('sorted_base_counts:\n');
# sys.stderr.write(str(sorted_base_counts) + '\n');
# sys.stderr.write('base_counts:\n');
# sys.stderr.write(str(base_counts) + '\n');
# sys.stderr.write('original_bases:\n');
# sys.stderr.write(str(original_bases) + '\n');
# sys.stderr.write('line:\n');
# sys.stderr.write(line.strip() + '\n');
# most_common_base_count = 0;
# Allow for the case where there are multiple equally good choices.
# In this case, we prefer the choice which is equal to the reference.
is_good = False;
for base_count in sorted_base_counts:
if (base_count[1] == most_common_base_count):
if (base_count[0] == ref_base):
is_good = True;
break;
if (is_good == False):
if (len(sorted_base_counts) > 0):
ret_snp_count[0] += 1;
# ret_variant_list.append(line_number);
variant_line = 'SNP\tpos = %s\tref = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0])), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
### VCF output ###
alt_base = ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0]));
qual = 1000;
info = 'DP=%s;TYPE=snp' % (coverage);
ref_field = ref_base;
alt_field = alt_base;
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
else:
sys.stderr.write('\nWarning: a SNP was detected, but there were no bases in the sorted_base_counts!')
variant_line = 'SNP\tpos = %s\tref = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0])), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
sys.stderr.write('\n');
else:
ret_num_correct_bases[0] += 1;
if (verbose == True):
sys.stdout.write('Reference base: %s\n' % (ref_base));
sys.stdout.write('Consensus base: %s\n\n' % (base_count[0]));
#if (int(position) == 100000 or int(position) == 1000000 or int(position) == 2000000 or int(position) == 3000000 or int(position) == 4000000):
#print '\nTEST\tpos = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s\n' % (position, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
### Handling indel consensus.
### Put a different coverage threshold. Here we are interested even in the reads
### which had a '*' at the current position (because we don't know where it ends).
non_indel_coverage_next_base = int(coverage) - end_counts - deletion_count - insertion_count;
if ((non_indel_coverage_next_base + deletion_count + insertion_count) > coverage_threshold):
# Sanity check, just to see if there actually were any insertions (to avoid index out of bounds error).
# If there are insertions, get the most common one.
if (len(insertion_event_counts.keys()) > 0):
sorted_insertion_counts = sorted(insertion_event_counts.items(), key=operator.itemgetter(1));
most_common_insertion_count = sorted_insertion_counts[-1][1];
most_common_insertion_length = len(sorted_insertion_counts[-1][0]);
insertion_unique = True if (sum([int(insertion_count[1] == most_common_insertion_count) for insertion_count in sorted_insertion_counts]) == 1) else False;
else:
most_common_insertion_count = 0;
most_common_insertion_length = 0;
insertion_unique = False;
# Sanity check, just to see if there actually were any deletions (to avoid index out of bounds error).
# If there are deletions, get the most common one.
if (len(deletion_event_counts.keys()) > 0):
sorted_deletion_counts = sorted(deletion_event_counts.items(), key=operator.itemgetter(1));
most_common_deletion_count = sorted_deletion_counts[-1][1];
most_common_deletion_length = len(sorted_deletion_counts[-1][0]);
deletion_unique = True if (sum([int(deletion_count[1] == most_common_deletion_count) for deletion_count in sorted_deletion_counts]) == 1) else False;
else:
most_common_deletion_count = 0;
most_common_deletion_length = 0;
deletion_unique = False;
if (most_common_insertion_count > most_common_deletion_count and most_common_insertion_count > non_indel_coverage_next_base):
# In this case, insertions are a clear winner.
if (insertion_unique == True):
#ret_insertion_count[0] += most_common_insertion_length;
ret_insertion_count[0] += 1;
ret_num_called_bases[0] += most_common_insertion_length;
#variant_line = 'insertion\t%d\t%s\t%s\t%s\t%s' % (most_common_insertion_count, str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
#ret_variant_list.append(variant_line);
try:
temp_sorted_bc = sorted_base_counts[-1][0];
except:
temp_sorted_bc = 0;
indel_length = most_common_insertion_length;
variant_line = 'ins\tpos = %s\tref = %s\tnon_indel_cov_next = %d\tnon_indel_cov_curr = %d\tmost_common_insertion_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, non_indel_coverage_next_base, non_indel_coverage_current_base, most_common_insertion_count, ref_base, temp_sorted_bc, str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
### Insertions in the VCF format specifies the position where a insertion occurs. The ref position should contain the base which is the same as ref, but the alt field contains the ref base + the insertion event.
### VCF output ###
alt_base = ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0]));
qual = 1000;
info = 'DP=%s;TYPE=ins' % (coverage);
ref_field = ref_base;
alt_field = '%s%s' % (ref_base, sorted_insertion_counts[-1][0]);
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
elif (most_common_deletion_count > most_common_insertion_count and most_common_deletion_count > non_indel_coverage_next_base):
# In this case, deletions are a clear winner.
if (deletion_unique == True):
#ret_deletion_count[0] += most_common_deletion_length;
ret_deletion_count[0] += 1;
#variant_line = 'deletion\t%d\t%s\t%s\t%s\t%s' % (most_common_deletion_count, str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
#ret_variant_list.append(variant_line);
#return most_common_deletion_length;
variant_line = 'del\tpos = %s\tref = %s\tnon_indel_cov_next = %d\tnon_indel_cov_curr = %d\tmost_common_deletion_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, non_indel_coverage_next_base, non_indel_coverage_current_base, most_common_deletion_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
### Deletions in the VCF format specifies the position where a deletion occurs, with the first base being non-deletion, and the following bases being a deletion event.
### VCF output ###
alt_base = ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0]));
qual = 1000;
info = 'DP=%s;TYPE=del' % (coverage);
ref_field = '%s%s' % (ref_base, sorted_deletion_counts[-1][0]);
alt_field = ref_base;
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
return most_common_deletion_length;
else:
# In this case, either the base count consensus wins, or the
# insertion/deletion count is ambiguous.
pass;
return 0;
def process_mpileup(alignments_path, reference_path, mpileup_path, coverage_threshold, output_prefix, thread_id=0, bed_position=''):
fp = None;
try:
fp = open(mpileup_path, 'r');
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for reading!\n' % mpileup_path);
return None;
ret_variant_list = [];
ret_vcf_list = [];
ret_snp_count = [0];
ret_insertion_count = [0];
ret_deletion_count = [0];
ret_num_undercovered_bases = [0];
ret_num_called_bases = [0];
ret_num_correct_bases = [0];
ret_coverage_sum = [0];
# lines = fp.readlines();
fp_variant = None;
fp_vcf = None;
if (output_prefix != ''):
if (not os.path.exists(os.path.dirname(output_prefix))):
os.makedirs(os.path.dirname(output_prefix));
variant_file = ('%s-cov_%d.variant.csv' % (output_prefix, coverage_threshold));
fp_variant = open(variant_file, 'w');
vcf_file = ('%s-cov_%d.variant.vcf' % (output_prefix, coverage_threshold));
fp_vcf = open(vcf_file, 'w');
fp_vcf.write('##fileformat=VCFv4.0\n');
fp_vcf.write('##fileDate=20150409\n');
fp_vcf.write('##source=%s\n' % (' '.join(sys.argv)));
fp_vcf.write('##reference=%s\n' % reference_path);
fp_vcf.write('##INFO=<ID=DP,Number=1,Type=Integer,Description="Raw Depth">\n');
fp_vcf.write('##INFO=<ID=TYPE,Number=A,Type=String,Description="Type of each allele (snp, ins, del, mnp, complex)">\n');
fp_vcf.write('##INFO=<ID=AF,Number=1,Type=Float,Description="Allele Frequency">\n');
fp_vcf.write('##INFO=<ID=SB,Number=1,Type=Integer,Description="Phred-scaled strand bias at this position">\n');
fp_vcf.write('##INFO=<ID=DP4,Number=4,Type=Integer,Description="Counts for ref-forward bases, ref-reverse, alt-forward and alt-reverse bases">\n');
fp_vcf.write('##INFO=<ID=INDEL,Number=0,Type=Flag,Description="Indicates that the variant is an INDEL.">\n');
fp_vcf.write('##INFO=<ID=CONSVAR,Number=0,Type=Flag,Description="Indicates that the variant is a consensus variant (as opposed to a low frequency variant).">\n');
fp_vcf.write('##INFO=<ID=HRUN,Number=1,Type=Integer,Description="Homopolymer length to the right of report indel position">\n');
fp_vcf.write('#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\n');
fp_vcf.flush();
use_bed = False;
bed_chromosome = "";
bed_pos_start = 0;
# bed_pos_end = len(lines);
bed_pos_end = -1;
if (bed_position != ""):
bed_split = bed_position.split(':');
if (len(bed_split) != 2):
use_bed = False;
else:
bed_chromosome = bed_split[0];
bed_pos_split = bed_split[1].split('-');
if (len(bed_pos_split) != 2):
use_bed = False;
else:
bed_pos_start = int(bed_pos_split[0]);
bed_pos_end = int(bed_pos_split[1]);
use_bed = True;
sys.stderr.write('Using location specified through commandline:\n');
sys.stderr.write('\tChromosome: "%s"\n' % bed_chromosome);
sys.stderr.write('\tStart: %d\n' % bed_pos_start);
sys.stderr.write('\tEnd: %d\n\n' % bed_pos_end);
# i = 0;
i = 0 if (use_bed == False) else max((bed_pos_start - 10), 0);
j = 0;
# while (i < bed_pos_end): # len(lines)):
num_bases_to_skip = 0;
for line in fp:
# line = lines[i];
if (num_bases_to_skip > 0):
num_bases_to_skip -= 1;
continue;
if (use_bed == True):
line_split = line.strip().split('\t');
if (len(line_split) > 2 and line_split[0] == bed_chromosome):
current_pos = int(line_split[1]);
if (current_pos < bed_pos_start or current_pos >= bed_pos_end):
i += 1;
j += 1;
continue;
else:
# print line_split[0];
# print bed_chromosome;
i += 1;
j += 1;
continue;
if (thread_id == 0):
if ((j % 1000) == 0):
sys.stderr.write('\r[%d] snps = %d, insertions = %d, deletions = %d, undercovered = %d, coverage = %.2f' % (i, ret_snp_count[0], ret_insertion_count[0], ret_deletion_count[0], ret_num_undercovered_bases[0], (float(ret_coverage_sum[0])/float((i + 1)))));
sys.stderr.flush();
variant_list_length = len(ret_variant_list);
vcf_list_length = len(ret_vcf_list);
num_bases_to_skip = process_mpileup_line(line, i, ret_variant_list, ret_vcf_list, ret_snp_count, ret_insertion_count, ret_deletion_count, ret_num_undercovered_bases, ret_num_called_bases, ret_num_correct_bases, ret_coverage_sum, coverage_threshold, verbose=use_bed);
if (len(ret_variant_list) > variant_list_length and fp_variant != None):
fp_variant.write('\n'.join(ret_variant_list[variant_list_length:]) + '\n');
fp_variant.flush();
if (len(ret_vcf_list) > vcf_list_length and fp_vcf != None):
fp_vcf.write('\n'.join(ret_vcf_list[vcf_list_length:]) + '\n');
fp_vcf.flush();
i += num_bases_to_skip;
i += 1;
j += 1;
#if (i > 10000):
#break;
fp.close();
sys.stderr.write('\n')
if (fp_variant != None):
fp_variant.close();
if (fp_vcf != None):
fp_vcf.close();
summary_lines = '';
summary_lines += 'alignments_file: %s\n' % alignments_path;
summary_lines += 'mpileup_file: %s\n' % mpileup_path;
summary_lines += 'coverage_threshold: %d\n' % coverage_threshold;
summary_lines += 'snp_count: %d\n' % ret_snp_count[0];
summary_lines += 'insertion_count: %d\n' % ret_insertion_count[0];
summary_lines += 'deletion_count: %d\n' % ret_deletion_count[0];
summary_lines += 'num_undercovered_bases: %d\n' % ret_num_undercovered_bases[0];
summary_lines += 'num_called_bases: %d\n' % ret_num_called_bases[0];
summary_lines += 'num_correct_bases: %d\n' % ret_num_correct_bases[0];
summary_lines += 'average_coverage: %.2f\n' % ((float(ret_coverage_sum[0])/float((i + 1))));
sys.stderr.write(summary_lines + '\n');
sys.stderr.write('\n');
if (output_prefix != ''):
#summary_file = output_prefix + '.conssum';
summary_file = ('%s-cov_%d.variant.sum' % (output_prefix, coverage_threshold));
try:
fp_sum = open(summary_file, 'w');
fp_sum.write(summary_lines);
fp_sum.close();
return summary_file;
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for writing!\n' % (summary_file));
return None;
return None;
def main(alignments_path, reference_path, coverage_threshold, output_prefix, thread_id=0, bed_position=""):
# Sanity checking the existence of the file, and the correctness of its extension.
# Also, if input file is a SAM file, then convert it to a sorted BAM.
alignments_path_bam = alignments_path;
if (os.path.exists(alignments_path) == False):
sys.stderr.write('ERROR: File "%s" does not exist!\n' % alignments_path);
return;
if (alignments_path.endswith('sam')):
# Determine the path where the new BAM file will be generated.
dir_name = os.path.dirname(alignments_path);
if (dir_name == ''):
dir_name = '.';
alignments_path_bam = dir_name + '/' + os.path.splitext(os.path.basename(alignments_path))[0] + '.bam'
alignments_path_bam_exists = os.path.exists(alignments_path_bam);
# Check if a BAM file with the given name already exists.
if (alignments_path_bam_exists == False or (alignments_path_bam_exists == True and os.path.getmtime(alignments_path) > os.path.getmtime(alignments_path_bam))):
# Convert the SAM file to a sorted BAM file.
command = 'samtools view -bS %s | samtools sort - %s' % (alignments_path, os.path.splitext(alignments_path_bam)[0]);
sys.stderr.write(command + '\n')
subprocess.call(command, shell='True');
# Create the BAM index file.
command = 'samtools index %s %s.bai' % (alignments_path_bam, alignments_path_bam);
subprocess.call(command, shell='True');
elif (alignments_path.endswith('bam') == False):
sys.stderr.write('ERROR: File extension needs to be either .sam or .bam! Input file path: "%s".\n' % alignments_path);
return;
# Convert the sorted BAM file to a mpileup file if it doesn't exist yet.
mpileup_path = ('%s.mpileup' % alignments_path_bam);
mpileup_exists = os.path.exists(mpileup_path);
if (mpileup_exists == False or (mpileup_exists == True and os.path.getmtime(alignments_path) > os.path.getmtime(mpileup_path))):
command = 'samtools mpileup -B -d 1000000 -Q 0 -A -f %s %s > %s.mpileup' % (reference_path, alignments_path_bam, alignments_path_bam);
subprocess.call(command, shell='True');
sys.stderr.write('Processing file "%s"...\n' % alignments_path);
sys.stderr.write('Reference file "%s"...\n' % reference_path);
sys.stderr.write('Coverage threshold: %d\n' % coverage_threshold);
summary_file = process_mpileup(alignments_path, reference_path, ('%s.mpileup' % alignments_path_bam), coverage_threshold, output_prefix, thread_id, bed_position);
def CollectSummaries(sam_files, prefix_for_intermediate_results, collective_output_file):
fp_collect = None;
try:
fp_collect = open(collective_output_file, 'w');
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for writing!\n' % collective_output_file);
return;
for sam_file in sam_files:
summary_file = prefix_for_intermediate_results + '.sum';
try:
fp_sum = open(summary_file, 'r');
lines = fp_sum.readlines();
fp_sum.close();
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for reading!\n' % summary_file);
continue;
fp_collect.write(''.join(lines) + '\n');
fp_collect.close();
if __name__ == "__main__":
# if (len(sys.argv) < 5):
# sys.stderr.write('Usage:\n');
# sys.stderr.write('\t%s <reference_file_path> coverage_threshold <collective_output_file> <{sb}am_file_1> [<{sb}am_file_2> <{sb}am_file_3> ...]\n' % sys.argv[0]);
# sys.stderr.write('\t(If <collective_output_file> is equal to "-", no files will be written to disk.)\n');
# exit(1);
if (len(sys.argv) < 5):
sys.stderr.write('Usage:\n');
sys.stderr.write('\t%s <reference_file_path> coverage_threshold <output_prefix> <{sb}am_file_> [position]\n' % sys.argv[0]);
sys.stderr.write('\t(If <collective_output_file> is equal to "-", no files will be written to disk.)\n');
sys.stderr.write('\tPosition parameter is a string specifying "chromosome:start-end"\n\n');
exit(1);
reference_file = sys.argv[1];
coverage_threshold = int(sys.argv[2]);
output_prefix = sys.argv[3];
sam_file = sys.argv[4];
bed_position = '';
if (len(sys.argv) > 5):
bed_position = sys.argv[5];
# sys.stderr.write('bed_position: "%s"\n\n' % bed_position);
processes = [];
if (output_prefix == '-'):
output_prefix = os.path.splitext(sam_file)[0];
main(sam_file, reference_file, coverage_threshold, output_prefix, 0, bed_position);
# if (output_prefix != '-'):
# CollectSummaries([sam_file], output_prefix, output_prefix + '.variant.sum');
| 46.555752 | 493 | 0.701718 |
import os;
import sys;
import operator;
import subprocess;
def increase_in_dict(dict_counter, value):
try:
dict_counter[value] += 1;
except:
dict_counter[value] = 1;
def process_mpileup_line(line, line_number, ret_variant_list, ret_vcf_list, ret_snp_count, ret_insertion_count, ret_deletion_count, ret_num_undercovered_bases, ret_num_called_bases, ret_num_correct_bases, ret_coverage_sum, coverage_threshold, verbose=False):
split_line = line.strip().split('\t');
if (len(split_line) < 5 or len(split_line) > 6):
sys.stderr.write(line + '\n');
return 0;
ref_name = split_line[0];
position = split_line[1];
ref_base = split_line[2];
coverage = split_line[3];
original_bases = split_line[4];
if (len(split_line) == 6):
qualities = split_line[5];
bases = '';
i = 0;
while (i < len(original_bases)):
if (original_bases[i] == '.' or original_bases[i] == ','):
bases += ref_base;
else:
bases += original_bases[i];
i += 1;
base_counts = {};
insertion_count = 0;
current_base_deletion_count = 0;
deletion_count = 0;
insertion_event_counts = {};
deletion_event_counts = {};
end_counts = 0;
i = 0;
while (i < len(bases)):
base = bases[i];
if (base == r'^'):
i += 1;
elif (base == r'$'):
end_counts += 1;
elif (base == r'*'):
current_base_deletion_count += 1;
elif (base == r'-'):
j = (i + 1);
while (bases[j] in '0123456789'):
j += 1;
num_bases = int(bases[(i + 1):j]);
skip_bases = (j - i) + num_bases - 1;
deletion_count += 1;
deletion = bases[j : (j + num_bases)].upper();
increase_in_dict(deletion_event_counts, deletion);
i += skip_bases;
elif (base == r'+'):
j = (i + 1);
while (bases[j] in '0123456789'):
j += 1;
num_bases = int(bases[(i + 1):j]);
skip_bases = (j - i) + num_bases - 1;
insertion_count += 1;
insertion = bases[j : (j + num_bases)].upper();
increase_in_dict(insertion_event_counts, insertion);
i += skip_bases;
else:
increase_in_dict(base_counts, bases[i].upper());
i += 1;
# There are pileup bases that do not have any actual bases, but only the '*' symbols. How should this be handled properly?
# Example line from the mpileup file:
# gi|48994873|gb|U00096.2|_Escherichia_coli_str._K-12_substr._MG1655,_complete_genome 1938202 T 20 ******************** 8,2*#-;)$B>2$1&D-
# I chose to handle them as undercovered bases.
non_indel_coverage_current_base = int(coverage) - current_base_deletion_count;
if (verbose == True):
sys.stdout.write('%s\nbase_counts: %s\n' % (line.strip(), str(base_counts)));
# EDIT: Previously I compared the total coverage of the current base with the coverage threshold.
# However, the total coverage also accounts for the deletions denoted with the '*' sign, which I think
# isn't relevant, as deletions are counted prior to occuring, and at that point is already decided if there is going
# consensus), then the deletions on this base are ignored.
#if (int(coverage) < coverage_threshold or int(coverage) == current_base_deletion_count):
# if (non_indel_coverage_current_base < coverage_threshold):
if (int(coverage) < coverage_threshold):
ret_num_undercovered_bases[0] += 1;
# ret_coverage_sum[0] += 0;
ret_coverage_sum[0] += int(coverage); # TODO: Should I count total coverage of this base, or the non_indel_coverage_current_base?
sorted_base_counts = [['A', 0], ['C', 0], ['T', 0], ['G', 0]];
sorted_base_counts = sorted(base_counts.items(), key=operator.itemgetter(1));
try:
most_common_base_count = sorted_base_counts[-1][1];
except Exception, e:
most_common_base_count = 0;
pass;
#variant_line = 'undercovered1\tpos = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
#ret_variant_list.append(variant_line);
variant_line = 'undercovered1\tpos = %s\tref = %s\tcoverage = %d\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s' % (position, ref_name, int(coverage), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts));
ret_variant_list.append(variant_line);
### VCF output ###
qual = 1000;
info = 'DP=%s;TYPE=snp' % (coverage);
ref_field = ref_base;
alt_field = 'N';
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
else:
ret_num_called_bases[0] += 1;
ret_coverage_sum[0] += int(coverage); # TODO: Should I count total coverage of this base, or the non_indel_coverage_current_base?
most_common_base_count = 0;
### Handling base consensus.
sorted_base_counts = sorted(base_counts.items(), key=operator.itemgetter(1));
try:
most_common_base_count = sorted_base_counts[-1][1];
except Exception, e:
pass;
# sys.stderr.write(str(e) + '\n');
# sys.stderr.write('sorted_base_counts:\n');
# sys.stderr.write(str(sorted_base_counts) + '\n');
# sys.stderr.write('base_counts:\n');
# sys.stderr.write(str(base_counts) + '\n');
# sys.stderr.write('original_bases:\n');
# sys.stderr.write(str(original_bases) + '\n');
# sys.stderr.write('line:\n');
# sys.stderr.write(line.strip() + '\n');
# most_common_base_count = 0;
# Allow for the case where there are multiple equally good choices.
# In this case, we prefer the choice which is equal to the reference.
is_good = False;
for base_count in sorted_base_counts:
if (base_count[1] == most_common_base_count):
if (base_count[0] == ref_base):
is_good = True;
break;
if (is_good == False):
if (len(sorted_base_counts) > 0):
ret_snp_count[0] += 1;
# ret_variant_list.append(line_number);
variant_line = 'SNP\tpos = %s\tref = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0])), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
### VCF output ###
alt_base = ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0]));
qual = 1000;
info = 'DP=%s;TYPE=snp' % (coverage);
ref_field = ref_base;
alt_field = alt_base;
vcf_line = '%s\t%s\t.\t%s\t%s\t%d\tPASS\t%s' % (ref_name, position, ref_field, alt_field, qual, info);
ret_vcf_list.append(vcf_line);
##################
else:
sys.stderr.write('\nWarning: a SNP was detected, but there were no bases in the sorted_base_counts!')
variant_line = 'SNP\tpos = %s\tref = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, ('{}') if (len(sorted_base_counts) == 0) else (str(sorted_base_counts[-1][0])), str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
sys.stderr.write('\n');
else:
ret_num_correct_bases[0] += 1;
if (verbose == True):
sys.stdout.write('Reference base: %s\n' % (ref_base));
sys.stdout.write('Consensus base: %s\n\n' % (base_count[0]));
#if (int(position) == 100000 or int(position) == 1000000 or int(position) == 2000000 or int(position) == 3000000 or int(position) == 4000000):
#print '\nTEST\tpos = %s\tcoverage = %d\tnon_indel_cov_curr = %d\tmost_common_base_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s\n' % (position, int(coverage), non_indel_coverage_current_base, most_common_base_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
### Handling indel consensus.
### Put a different coverage threshold. Here we are interested even in the reads
### which had a '*' at the current position (because we don't know where it ends).
non_indel_coverage_next_base = int(coverage) - end_counts - deletion_count - insertion_count;
if ((non_indel_coverage_next_base + deletion_count + insertion_count) > coverage_threshold):
if (len(insertion_event_counts.keys()) > 0):
sorted_insertion_counts = sorted(insertion_event_counts.items(), key=operator.itemgetter(1));
most_common_insertion_count = sorted_insertion_counts[-1][1];
most_common_insertion_length = len(sorted_insertion_counts[-1][0]);
insertion_unique = True if (sum([int(insertion_count[1] == most_common_insertion_count) for insertion_count in sorted_insertion_counts]) == 1) else False;
else:
most_common_insertion_count = 0;
most_common_insertion_length = 0;
insertion_unique = False;
if (len(deletion_event_counts.keys()) > 0):
sorted_deletion_counts = sorted(deletion_event_counts.items(), key=operator.itemgetter(1));
most_common_deletion_count = sorted_deletion_counts[-1][1];
most_common_deletion_length = len(sorted_deletion_counts[-1][0]);
deletion_unique = True if (sum([int(deletion_count[1] == most_common_deletion_count) for deletion_count in sorted_deletion_counts]) == 1) else False;
else:
most_common_deletion_count = 0;
most_common_deletion_length = 0;
deletion_unique = False;
if (most_common_insertion_count > most_common_deletion_count and most_common_insertion_count > non_indel_coverage_next_base):
if (insertion_unique == True):
ret_insertion_count[0] += 1;
ret_num_called_bases[0] += most_common_insertion_length;
try:
temp_sorted_bc = sorted_base_counts[-1][0];
except:
temp_sorted_bc = 0;
indel_length = most_common_insertion_length;
variant_line = 'ins\tpos = %s\tref = %s\tnon_indel_cov_next = %d\tnon_indel_cov_curr = %d\tmost_common_insertion_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, non_indel_coverage_next_base, non_indel_coverage_current_base, most_common_insertion_count, ref_base, temp_sorted_bc, str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
variant_line = 'del\tpos = %s\tref = %s\tnon_indel_cov_next = %d\tnon_indel_cov_curr = %d\tmost_common_deletion_count = %d\tref_base = %s\tcons_base = %s\tbase_counts = %s\tinsertion_counts = %s\tdeletion_counts = %s\t%s' % (position, ref_name, non_indel_coverage_next_base, non_indel_coverage_current_base, most_common_deletion_count, ref_base, sorted_base_counts[-1][0], str(sorted_base_counts), str(insertion_event_counts), str(deletion_event_counts), line.strip());
ret_variant_list.append(variant_line);
cf_list.append(vcf_line);
e_threshold, output_prefix, thread_id=0, bed_position=''):
fp = None;
try:
fp = open(mpileup_path, 'r');
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for reading!\n' % mpileup_path);
return None;
ret_variant_list = [];
ret_vcf_list = [];
ret_snp_count = [0];
ret_insertion_count = [0];
ret_deletion_count = [0];
ret_num_undercovered_bases = [0];
ret_num_called_bases = [0];
ret_num_correct_bases = [0];
ret_coverage_sum = [0];
fp_variant = None;
fp_vcf = None;
if (output_prefix != ''):
if (not os.path.exists(os.path.dirname(output_prefix))):
os.makedirs(os.path.dirname(output_prefix));
variant_file = ('%s-cov_%d.variant.csv' % (output_prefix, coverage_threshold));
fp_variant = open(variant_file, 'w');
vcf_file = ('%s-cov_%d.variant.vcf' % (output_prefix, coverage_threshold));
fp_vcf = open(vcf_file, 'w');
fp_vcf.write('##fileformat=VCFv4.0\n');
fp_vcf.write('##fileDate=20150409\n');
fp_vcf.write('##source=%s\n' % (' '.join(sys.argv)));
fp_vcf.write('##reference=%s\n' % reference_path);
fp_vcf.write('##INFO=<ID=DP,Number=1,Type=Integer,Description="Raw Depth">\n');
fp_vcf.write('##INFO=<ID=TYPE,Number=A,Type=String,Description="Type of each allele (snp, ins, del, mnp, complex)">\n');
fp_vcf.write('##INFO=<ID=AF,Number=1,Type=Float,Description="Allele Frequency">\n');
fp_vcf.write('##INFO=<ID=SB,Number=1,Type=Integer,Description="Phred-scaled strand bias at this position">\n');
fp_vcf.write('##INFO=<ID=DP4,Number=4,Type=Integer,Description="Counts for ref-forward bases, ref-reverse, alt-forward and alt-reverse bases">\n');
fp_vcf.write('##INFO=<ID=INDEL,Number=0,Type=Flag,Description="Indicates that the variant is an INDEL.">\n');
fp_vcf.write('##INFO=<ID=CONSVAR,Number=0,Type=Flag,Description="Indicates that the variant is a consensus variant (as opposed to a low frequency variant).">\n');
fp_vcf.write('##INFO=<ID=HRUN,Number=1,Type=Integer,Description="Homopolymer length to the right of report indel position">\n');
fp_vcf.write('#CHROM\tPOS\tID\tREF\tALT\tQUAL\tFILTER\tINFO\n');
fp_vcf.flush();
use_bed = False;
bed_chromosome = "";
bed_pos_start = 0;
bed_pos_end = -1;
if (bed_position != ""):
bed_split = bed_position.split(':');
if (len(bed_split) != 2):
use_bed = False;
else:
bed_chromosome = bed_split[0];
bed_pos_split = bed_split[1].split('-');
if (len(bed_pos_split) != 2):
use_bed = False;
else:
bed_pos_start = int(bed_pos_split[0]);
bed_pos_end = int(bed_pos_split[1]);
use_bed = True;
sys.stderr.write('Using location specified through commandline:\n');
sys.stderr.write('\tChromosome: "%s"\n' % bed_chromosome);
sys.stderr.write('\tStart: %d\n' % bed_pos_start);
sys.stderr.write('\tEnd: %d\n\n' % bed_pos_end);
i = 0 if (use_bed == False) else max((bed_pos_start - 10), 0);
j = 0;
_skip = 0;
for line in fp:
if (num_bases_to_skip > 0):
num_bases_to_skip -= 1;
continue;
if (use_bed == True):
line_split = line.strip().split('\t');
if (len(line_split) > 2 and line_split[0] == bed_chromosome):
current_pos = int(line_split[1]);
if (current_pos < bed_pos_start or current_pos >= bed_pos_end):
i += 1;
j += 1;
continue;
else:
i += 1;
j += 1;
continue;
if (thread_id == 0):
if ((j % 1000) == 0):
sys.stderr.write('\r[%d] snps = %d, insertions = %d, deletions = %d, undercovered = %d, coverage = %.2f' % (i, ret_snp_count[0], ret_insertion_count[0], ret_deletion_count[0], ret_num_undercovered_bases[0], (float(ret_coverage_sum[0])/float((i + 1)))));
sys.stderr.flush();
variant_list_length = len(ret_variant_list);
vcf_list_length = len(ret_vcf_list);
num_bases_to_skip = process_mpileup_line(line, i, ret_variant_list, ret_vcf_list, ret_snp_count, ret_insertion_count, ret_deletion_count, ret_num_undercovered_bases, ret_num_called_bases, ret_num_correct_bases, ret_coverage_sum, coverage_threshold, verbose=use_bed);
if (len(ret_variant_list) > variant_list_length and fp_variant != None):
fp_variant.write('\n'.join(ret_variant_list[variant_list_length:]) + '\n');
fp_variant.flush();
if (len(ret_vcf_list) > vcf_list_length and fp_vcf != None):
fp_vcf.write('\n'.join(ret_vcf_list[vcf_list_length:]) + '\n');
fp_vcf.flush();
i += num_bases_to_skip;
i += 1;
j += 1;
fp.close();
sys.stderr.write('\n')
if (fp_variant != None):
fp_variant.close();
if (fp_vcf != None):
fp_vcf.close();
summary_lines = '';
summary_lines += 'alignments_file: %s\n' % alignments_path;
summary_lines += 'mpileup_file: %s\n' % mpileup_path;
summary_lines += 'coverage_threshold: %d\n' % coverage_threshold;
summary_lines += 'snp_count: %d\n' % ret_snp_count[0];
summary_lines += 'insertion_count: %d\n' % ret_insertion_count[0];
summary_lines += 'deletion_count: %d\n' % ret_deletion_count[0];
summary_lines += 'num_undercovered_bases: %d\n' % ret_num_undercovered_bases[0];
summary_lines += 'num_called_bases: %d\n' % ret_num_called_bases[0];
summary_lines += 'num_correct_bases: %d\n' % ret_num_correct_bases[0];
summary_lines += 'average_coverage: %.2f\n' % ((float(ret_coverage_sum[0])/float((i + 1))));
sys.stderr.write(summary_lines + '\n');
sys.stderr.write('\n');
if (output_prefix != ''):
summary_file = ('%s-cov_%d.variant.sum' % (output_prefix, coverage_threshold));
try:
fp_sum = open(summary_file, 'w');
fp_sum.write(summary_lines);
fp_sum.close();
return summary_file;
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for writing!\n' % (summary_file));
return None;
return None;
def main(alignments_path, reference_path, coverage_threshold, output_prefix, thread_id=0, bed_position=""):
alignments_path_bam = alignments_path;
if (os.path.exists(alignments_path) == False):
sys.stderr.write('ERROR: File "%s" does not exist!\n' % alignments_path);
return;
if (alignments_path.endswith('sam')):
dir_name = os.path.dirname(alignments_path);
if (dir_name == ''):
dir_name = '.';
alignments_path_bam = dir_name + '/' + os.path.splitext(os.path.basename(alignments_path))[0] + '.bam'
alignments_path_bam_exists = os.path.exists(alignments_path_bam);
if (alignments_path_bam_exists == False or (alignments_path_bam_exists == True and os.path.getmtime(alignments_path) > os.path.getmtime(alignments_path_bam))):
command = 'samtools view -bS %s | samtools sort - %s' % (alignments_path, os.path.splitext(alignments_path_bam)[0]);
sys.stderr.write(command + '\n')
subprocess.call(command, shell='True');
command = 'samtools index %s %s.bai' % (alignments_path_bam, alignments_path_bam);
subprocess.call(command, shell='True');
elif (alignments_path.endswith('bam') == False):
sys.stderr.write('ERROR: File extension needs to be either .sam or .bam! Input file path: "%s".\n' % alignments_path);
return;
mpileup_path = ('%s.mpileup' % alignments_path_bam);
mpileup_exists = os.path.exists(mpileup_path);
if (mpileup_exists == False or (mpileup_exists == True and os.path.getmtime(alignments_path) > os.path.getmtime(mpileup_path))):
command = 'samtools mpileup -B -d 1000000 -Q 0 -A -f %s %s > %s.mpileup' % (reference_path, alignments_path_bam, alignments_path_bam);
subprocess.call(command, shell='True');
sys.stderr.write('Processing file "%s"...\n' % alignments_path);
sys.stderr.write('Reference file "%s"...\n' % reference_path);
sys.stderr.write('Coverage threshold: %d\n' % coverage_threshold);
summary_file = process_mpileup(alignments_path, reference_path, ('%s.mpileup' % alignments_path_bam), coverage_threshold, output_prefix, thread_id, bed_position);
def CollectSummaries(sam_files, prefix_for_intermediate_results, collective_output_file):
fp_collect = None;
try:
fp_collect = open(collective_output_file, 'w');
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for writing!\n' % collective_output_file);
return;
for sam_file in sam_files:
summary_file = prefix_for_intermediate_results + '.sum';
try:
fp_sum = open(summary_file, 'r');
lines = fp_sum.readlines();
fp_sum.close();
except IOError:
sys.stderr.write('ERROR: Could not open file "%s" for reading!\n' % summary_file);
continue;
fp_collect.write(''.join(lines) + '\n');
fp_collect.close();
if __name__ == "__main__":
# if (len(sys.argv) < 5):
# sys.stderr.write('Usage:\n');
# sys.stderr.write('\t%s <reference_file_path> coverage_threshold <collective_output_file> <{sb}am_file_1> [<{sb}am_file_2> <{sb}am_file_3> ...]\n' % sys.argv[0]);
# sys.stderr.write('\t(If <collective_output_file> is equal to "-", no files will be written to disk.)\n');
# exit(1);
if (len(sys.argv) < 5):
sys.stderr.write('Usage:\n');
sys.stderr.write('\t%s <reference_file_path> coverage_threshold <output_prefix> <{sb}am_file_> [position]\n' % sys.argv[0]);
sys.stderr.write('\t(If <collective_output_file> is equal to "-", no files will be written to disk.)\n');
sys.stderr.write('\tPosition parameter is a string specifying "chromosome:start-end"\n\n');
exit(1);
reference_file = sys.argv[1];
coverage_threshold = int(sys.argv[2]);
output_prefix = sys.argv[3];
sam_file = sys.argv[4];
bed_position = '';
if (len(sys.argv) > 5):
bed_position = sys.argv[5];
# sys.stderr.write('bed_position: "%s"\n\n' % bed_position);
processes = [];
if (output_prefix == '-'):
output_prefix = os.path.splitext(sam_file)[0];
main(sam_file, reference_file, coverage_threshold, output_prefix, 0, bed_position);
# if (output_prefix != '-'):
# CollectSummaries([sam_file], output_prefix, output_prefix + '.variant.sum');
| false | true |
f7fe83ebf8fc4ea77d58cdf5ea08a00b8eb21944 | 39 | py | Python | sentiment_analysis/data_provider.py | mengfanShi/SpiderMan | 679b3b5b64e8e6883eca0a22ddeec23a7a9d61bb | [
"MIT"
] | 1 | 2018-01-02T17:07:28.000Z | 2018-01-02T17:07:28.000Z | sentiment_analysis/data_provider.py | mengfanShi/SpiderMan | 679b3b5b64e8e6883eca0a22ddeec23a7a9d61bb | [
"MIT"
] | null | null | null | sentiment_analysis/data_provider.py | mengfanShi/SpiderMan | 679b3b5b64e8e6883eca0a22ddeec23a7a9d61bb | [
"MIT"
] | 2 | 2018-01-02T15:38:36.000Z | 2021-04-06T05:50:41.000Z | # -*- coding: utf-8 -*-
import jieba
| 7.8 | 23 | 0.538462 |
import jieba
| true | true |
f7fe84288dcebceea381116a51baee3b3a17183d | 2,127 | py | Python | src_multilevel/utils/data_processor.py | vineetjohn/ecom-sigir-task-2018 | 1be3d5670912e43cf21090faf3b4f51ac3bbba9f | [
"MIT"
] | 1 | 2018-08-07T12:38:47.000Z | 2018-08-07T12:38:47.000Z | src_multilevel/utils/data_processor.py | vineetjohn/ecom-sigir-task-2018 | 1be3d5670912e43cf21090faf3b4f51ac3bbba9f | [
"MIT"
] | null | null | null | src_multilevel/utils/data_processor.py | vineetjohn/ecom-sigir-task-2018 | 1be3d5670912e43cf21090faf3b4f51ac3bbba9f | [
"MIT"
] | null | null | null | import logging
import re
import spacy
from spacy.lang.en import English
from src.config import global_config
from src.utils import stopword_aggregator
logger = logging.getLogger(global_config.logger_name)
def is_valid_token(token):
return len(token) >= 3 and token not in stopword_aggregator.custom_stopwords
def clean_product(string, tokenizer):
string = re.sub(r"[^A-Za-z]", " ", string)
string = re.sub(r"\s{2,}", " ", string)
string = string.strip().lower()
tokens = tokenizer(string)
tokens = [str(x) for x in tokens if is_valid_token(str(x))]
return " ".join(tokens)
def get_training_data(input_file_path):
products, labels = list(), list()
spacy_nlp = spacy.load("en")
tokenizer = English().Defaults.create_tokenizer(spacy_nlp)
max_category_depth = 1
with open(input_file_path) as input_file:
i = 0
for line in input_file:
if not ((i + 1) % 10000):
logger.info("{} lines processed".format(i + 1))
i += 1
[product, category_string] = line.strip().split('\t')
categories = category_string.strip().split('>')
max_category_depth = len(categories) if len(categories) > max_category_depth else max_category_depth
cleaned_product = clean_product(product, tokenizer)
if cleaned_product:
logger.debug("original: {}, cleaned: {}".format(product, cleaned_product))
products.append(cleaned_product)
labels.append(categories)
else:
logger.error("skipped product {}".format(product))
logger.info("max_category_depth: {}".format(max_category_depth))
return products, labels
def get_test_data(input_file_path):
products = list()
spacy_nlp = spacy.load("en")
tokenizer = English().Defaults.create_tokenizer(spacy_nlp)
with open(input_file_path) as input_file:
for line in input_file:
product = line.strip()
cleaned_product = clean_product(product, tokenizer)
products.append(cleaned_product)
return products
| 31.746269 | 112 | 0.652562 | import logging
import re
import spacy
from spacy.lang.en import English
from src.config import global_config
from src.utils import stopword_aggregator
logger = logging.getLogger(global_config.logger_name)
def is_valid_token(token):
return len(token) >= 3 and token not in stopword_aggregator.custom_stopwords
def clean_product(string, tokenizer):
string = re.sub(r"[^A-Za-z]", " ", string)
string = re.sub(r"\s{2,}", " ", string)
string = string.strip().lower()
tokens = tokenizer(string)
tokens = [str(x) for x in tokens if is_valid_token(str(x))]
return " ".join(tokens)
def get_training_data(input_file_path):
products, labels = list(), list()
spacy_nlp = spacy.load("en")
tokenizer = English().Defaults.create_tokenizer(spacy_nlp)
max_category_depth = 1
with open(input_file_path) as input_file:
i = 0
for line in input_file:
if not ((i + 1) % 10000):
logger.info("{} lines processed".format(i + 1))
i += 1
[product, category_string] = line.strip().split('\t')
categories = category_string.strip().split('>')
max_category_depth = len(categories) if len(categories) > max_category_depth else max_category_depth
cleaned_product = clean_product(product, tokenizer)
if cleaned_product:
logger.debug("original: {}, cleaned: {}".format(product, cleaned_product))
products.append(cleaned_product)
labels.append(categories)
else:
logger.error("skipped product {}".format(product))
logger.info("max_category_depth: {}".format(max_category_depth))
return products, labels
def get_test_data(input_file_path):
products = list()
spacy_nlp = spacy.load("en")
tokenizer = English().Defaults.create_tokenizer(spacy_nlp)
with open(input_file_path) as input_file:
for line in input_file:
product = line.strip()
cleaned_product = clean_product(product, tokenizer)
products.append(cleaned_product)
return products
| true | true |
f7fe8436091bd5d409cc6f6db5d50d49536600c2 | 17,601 | py | Python | python_modules/dagster/dagster/core/definitions/resource_definition.py | rpatil524/dagster | 6f918d94cbd543ab752ab484a65e3a40fd441716 | [
"Apache-2.0"
] | 4,606 | 2018-06-21T17:45:20.000Z | 2022-03-31T23:39:42.000Z | python_modules/dagster/dagster/core/definitions/resource_definition.py | rpatil524/dagster | 6f918d94cbd543ab752ab484a65e3a40fd441716 | [
"Apache-2.0"
] | 6,221 | 2018-06-12T04:36:01.000Z | 2022-03-31T21:43:05.000Z | python_modules/dagster/dagster/core/definitions/resource_definition.py | rpatil524/dagster | 6f918d94cbd543ab752ab484a65e3a40fd441716 | [
"Apache-2.0"
] | 619 | 2018-08-22T22:43:09.000Z | 2022-03-31T22:48:06.000Z | from collections import namedtuple
from functools import update_wrapper
from typing import (
TYPE_CHECKING,
AbstractSet,
Any,
Callable,
Dict,
List,
Optional,
Union,
cast,
overload,
)
from dagster import check
from dagster.core.definitions.config import is_callable_valid_config_arg
from dagster.core.definitions.configurable import AnonymousConfigurableDefinition
from dagster.core.errors import (
DagsterInvalidDefinitionError,
DagsterInvalidInvocationError,
DagsterUnknownResourceError,
)
from dagster.seven import funcsigs
from dagster.utils.backcompat import experimental_arg_warning
from ..decorator_utils import (
get_function_params,
is_required_param,
positional_arg_name_list,
validate_expected_params,
)
from .definition_config_schema import (
IDefinitionConfigSchema,
convert_user_facing_definition_config_schema,
)
from .resource_invocation import resource_invocation_result
if TYPE_CHECKING:
from dagster.core.execution.resources_init import InitResourceContext
def is_context_provided(params: List[funcsigs.Parameter]) -> bool:
return len(params) >= 1
class ResourceDefinition(AnonymousConfigurableDefinition):
"""Core class for defining resources.
Resources are scoped ways to make external resources (like database connections) available to
during job execution and to clean up after execution resolves.
If resource_fn yields once rather than returning (in the manner of functions decorable with
:py:func:`@contextlib.contextmanager <python:contextlib.contextmanager>`) then the body of the
function after the yield will be run after execution resolves, allowing users to write their
own teardown/cleanup logic.
Depending on your executor, resources may be instantiated and cleaned up more than once in a
job execution.
Args:
resource_fn (Callable[[InitResourceContext], Any]): User-provided function to instantiate
the resource, which will be made available to executions keyed on the
``context.resources`` object.
config_schema (Optional[ConfigSchema): The schema for the config. If set, Dagster will check
that config provided for the resource matches this schema and fail if it does not. If
not set, Dagster will accept any config provided for the resource.
description (Optional[str]): A human-readable description of the resource.
required_resource_keys: (Optional[Set[str]]) Keys for the resources required by this
resource. A DagsterInvariantViolationError will be raised during initialization if
dependencies are cyclic.
version (Optional[str]): (Experimental) The version of the resource's definition fn. Two
wrapped resource functions should only have the same version if they produce the same
resource definition when provided with the same inputs.
"""
def __init__(
self,
resource_fn: Callable[["InitResourceContext"], Any],
config_schema: Optional[Union[Any, IDefinitionConfigSchema]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version: Optional[str] = None,
):
self._resource_fn = check.callable_param(resource_fn, "resource_fn")
self._config_schema = convert_user_facing_definition_config_schema(config_schema)
self._description = check.opt_str_param(description, "description")
self._required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys"
)
self._version = check.opt_str_param(version, "version")
if version:
experimental_arg_warning("version", "ResourceDefinition.__init__")
@property
def resource_fn(self) -> Callable[..., Any]:
return self._resource_fn
@property
def config_schema(self) -> IDefinitionConfigSchema:
return self._config_schema
@property
def description(self) -> Optional[str]:
return self._description
@property
def version(self) -> Optional[str]:
return self._version
@property
def required_resource_keys(self) -> AbstractSet[str]:
return self._required_resource_keys
@staticmethod
def none_resource(description: Optional[str] = None) -> "ResourceDefinition":
"""A helper function that returns a none resource.
Args:
description ([Optional[str]]): The description of the resource. Defaults to None.
Returns:
[ResourceDefinition]: A resource that does nothing.
"""
return ResourceDefinition.hardcoded_resource(value=None, description=description)
@staticmethod
def hardcoded_resource(value: Any, description: Optional[str] = None) -> "ResourceDefinition":
"""A helper function that creates a ``ResourceDefinition`` with a hardcoded object.
Args:
value (Any): The value that will be accessible via context.resources.resource_name.
description ([Optional[str]]): The description of the resource. Defaults to None.
Returns:
[ResourceDefinition]: A hardcoded resource.
"""
return ResourceDefinition(resource_fn=lambda _init_context: value, description=description)
@staticmethod
def mock_resource(description: Optional[str] = None) -> "ResourceDefinition":
"""A helper function that creates a ``ResourceDefinition`` which wraps a ``mock.MagicMock``.
Args:
description ([Optional[str]]): The description of the resource. Defaults to None.
Returns:
[ResourceDefinition]: A resource that creates the magic methods automatically and helps
you mock existing resources.
"""
from unittest import mock
return ResourceDefinition(
resource_fn=lambda _init_context: mock.MagicMock(), description=description
)
@staticmethod
def string_resource(description: Optional[str] = None) -> "ResourceDefinition":
return ResourceDefinition(
resource_fn=lambda init_context: init_context.resource_config,
config_schema=str,
description=description,
)
def copy_for_configured(
self, description: Optional[str], config_schema: IDefinitionConfigSchema, _
) -> "ResourceDefinition":
return ResourceDefinition(
config_schema=config_schema,
description=description or self.description,
resource_fn=self.resource_fn,
required_resource_keys=self.required_resource_keys,
version=self.version,
)
def __call__(self, *args, **kwargs):
from dagster.core.execution.resources_init import InitResourceContext
context_provided = is_context_provided(get_function_params(self.resource_fn))
if context_provided:
if len(args) + len(kwargs) == 0:
raise DagsterInvalidInvocationError(
"Resource initialization function has context argument, but no context was provided "
"when invoking."
)
if len(args) + len(kwargs) > 1:
raise DagsterInvalidInvocationError(
"Initialization of resource received multiple arguments. Only a first "
"positional context parameter should be provided when invoking."
)
context_param_name = get_function_params(self.resource_fn)[0].name
if args:
check.opt_inst_param(args[0], context_param_name, InitResourceContext)
return resource_invocation_result(self, args[0])
else:
if context_param_name not in kwargs:
raise DagsterInvalidInvocationError(
f"Resource initialization expected argument '{context_param_name}'."
)
check.opt_inst_param(
kwargs[context_param_name], context_param_name, InitResourceContext
)
return resource_invocation_result(self, kwargs[context_param_name])
else:
return resource_invocation_result(self, None)
class _ResourceDecoratorCallable:
def __init__(
self,
config_schema: Optional[Dict[str, Any]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version: Optional[str] = None,
):
self.config_schema = config_schema # checked by underlying definition
self.description = check.opt_str_param(description, "description")
self.version = check.opt_str_param(version, "version")
self.required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys"
)
def __call__(self, resource_fn: Callable[["InitResourceContext"], Any]):
check.callable_param(resource_fn, "resource_fn")
any_name = ["*"] if is_context_provided(get_function_params(resource_fn)) else []
params = get_function_params(resource_fn)
missing_positional = validate_expected_params(params, any_name)
if missing_positional:
raise DagsterInvalidDefinitionError(
f"@resource decorated function '{resource_fn.__name__}' expects a single "
"positional argument."
)
extras = params[len(any_name) :]
required_extras = list(filter(is_required_param, extras))
if required_extras:
raise DagsterInvalidDefinitionError(
f"@resource decorated function '{resource_fn.__name__}' expects only a single positional required argument. "
f"Got required extra params {', '.join(positional_arg_name_list(required_extras))}"
)
resource_def = ResourceDefinition(
resource_fn=resource_fn,
config_schema=self.config_schema,
description=self.description,
version=self.version,
required_resource_keys=self.required_resource_keys,
)
update_wrapper(resource_def, wrapped=resource_fn)
return resource_def
@overload
def resource(config_schema=Callable[["InitResourceContext"], Any]) -> ResourceDefinition:
...
@overload
def resource(
config_schema: Optional[Dict[str, Any]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version=None,
) -> Callable[[Callable[["InitResourceContext"], Any]], "ResourceDefinition"]:
...
def resource(
config_schema: Optional[
Union[Callable[["InitResourceContext"], Any], IDefinitionConfigSchema, Dict[str, Any]]
] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version=None,
) -> Union[
Callable[[Callable[["InitResourceContext"], Any]], "ResourceDefinition"], "ResourceDefinition"
]:
"""Define a resource.
The decorated function should accept an :py:class:`InitResourceContext` and return an instance of
the resource. This function will become the ``resource_fn`` of an underlying
:py:class:`ResourceDefinition`.
If the decorated function yields once rather than returning (in the manner of functions
decorable with :py:func:`@contextlib.contextmanager <python:contextlib.contextmanager>`) then
the body of the function after the yield will be run after execution resolves, allowing users
to write their own teardown/cleanup logic.
Args:
config_schema (Optional[ConfigSchema]): The schema for the config. Configuration data available in
`init_context.resource_config`. If not set, Dagster will accept any config provided.
description(Optional[str]): A human-readable description of the resource.
version (Optional[str]): (Experimental) The version of a resource function. Two wrapped
resource functions should only have the same version if they produce the same resource
definition when provided with the same inputs.
required_resource_keys (Optional[Set[str]]): Keys for the resources required by this resource.
"""
# This case is for when decorator is used bare, without arguments.
# E.g. @resource versus @resource()
if callable(config_schema) and not is_callable_valid_config_arg(config_schema):
return _ResourceDecoratorCallable()(config_schema)
def _wrap(resource_fn: Callable[["InitResourceContext"], Any]) -> "ResourceDefinition":
return _ResourceDecoratorCallable(
config_schema=cast(Optional[Dict[str, Any]], config_schema),
description=description,
required_resource_keys=required_resource_keys,
version=version,
)(resource_fn)
return _wrap
class Resources:
"""This class functions as a "tag" that we can use to type the namedtuple returned by
ScopedResourcesBuilder.build(). The way that we create the namedtuple returned by build() is
incompatible with type annotations on its own due to its dynamic attributes, so this tag class
provides a workaround."""
class IContainsGenerator:
"""This class adds an additional tag to indicate that the resources object has at least one
resource that has been yielded from a generator, and thus may require teardown."""
class ScopedResourcesBuilder(
namedtuple("ScopedResourcesBuilder", "resource_instance_dict contains_generator")
):
"""There are concepts in the codebase (e.g. ops, system storage) that receive
only the resources that they have specified in required_resource_keys.
ScopedResourcesBuilder is responsible for dynamically building a class with
only those required resources and returning an instance of that class."""
def __new__(
cls,
resource_instance_dict: Optional[Dict[str, Any]] = None,
contains_generator: Optional[bool] = False,
):
return super(ScopedResourcesBuilder, cls).__new__(
cls,
resource_instance_dict=check.opt_dict_param(
resource_instance_dict, "resource_instance_dict", key_type=str
),
contains_generator=contains_generator,
)
def build(self, required_resource_keys: Optional[AbstractSet[str]]) -> Resources:
"""We dynamically create a type that has the resource keys as properties, to enable dotting into
the resources from a context.
For example, given:
resources = {'foo': <some resource>, 'bar': <some other resource>}
then this will create the type Resource(namedtuple('foo bar'))
and then binds the specified resources into an instance of this object, which can be consumed
as, e.g., context.resources.foo.
"""
required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys", of_type=str
)
# it is possible that the surrounding context does NOT have the required resource keys
# because we are building a context for steps that we are not going to execute (e.g. in the
# resume/retry case, in order to generate copy intermediates events)
resource_instance_dict = {
key: self.resource_instance_dict[key]
for key in required_resource_keys
if key in self.resource_instance_dict
}
# If any of the resources are generators, add the IContainsGenerator subclass to flag that
# this is the case.
if self.contains_generator:
class _ScopedResourcesContainsGenerator(
namedtuple("_ScopedResourcesContainsGenerator", list(resource_instance_dict.keys())), # type: ignore[misc]
Resources,
IContainsGenerator,
):
def __getattr__(self, attr):
raise DagsterUnknownResourceError(attr)
return _ScopedResourcesContainsGenerator(**resource_instance_dict) # type: ignore[call-arg]
else:
class _ScopedResources(
namedtuple("_ScopedResources", list(resource_instance_dict.keys())), # type: ignore[misc]
Resources,
):
def __getattr__(self, attr):
raise DagsterUnknownResourceError(attr)
return _ScopedResources(**resource_instance_dict) # type: ignore[call-arg]
def make_values_resource(**kwargs: Any) -> ResourceDefinition:
"""A helper function that creates a ``ResourceDefinition`` to take in user-defined values.
This is useful for sharing values between ops.
Args:
**kwargs: Arbitrary keyword arguments that will be passed to the config schema of the
returned resource definition. If not set, Dagster will accept any config provided for
the resource.
For example:
.. code-block:: python
@op(required_resource_keys={"globals"})
def my_op(context):
print(context.resources.globals["my_str_var"])
@job(resource_defs={"globals": make_values_resource(my_str_var=str, my_int_var=int)})
def my_job():
my_op()
Returns:
ResourceDefinition: A resource that passes in user-defined values.
"""
return ResourceDefinition(
resource_fn=lambda init_context: init_context.resource_config,
config_schema=kwargs or Any,
)
| 40.002273 | 125 | 0.684279 | from collections import namedtuple
from functools import update_wrapper
from typing import (
TYPE_CHECKING,
AbstractSet,
Any,
Callable,
Dict,
List,
Optional,
Union,
cast,
overload,
)
from dagster import check
from dagster.core.definitions.config import is_callable_valid_config_arg
from dagster.core.definitions.configurable import AnonymousConfigurableDefinition
from dagster.core.errors import (
DagsterInvalidDefinitionError,
DagsterInvalidInvocationError,
DagsterUnknownResourceError,
)
from dagster.seven import funcsigs
from dagster.utils.backcompat import experimental_arg_warning
from ..decorator_utils import (
get_function_params,
is_required_param,
positional_arg_name_list,
validate_expected_params,
)
from .definition_config_schema import (
IDefinitionConfigSchema,
convert_user_facing_definition_config_schema,
)
from .resource_invocation import resource_invocation_result
if TYPE_CHECKING:
from dagster.core.execution.resources_init import InitResourceContext
def is_context_provided(params: List[funcsigs.Parameter]) -> bool:
return len(params) >= 1
class ResourceDefinition(AnonymousConfigurableDefinition):
def __init__(
self,
resource_fn: Callable[["InitResourceContext"], Any],
config_schema: Optional[Union[Any, IDefinitionConfigSchema]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version: Optional[str] = None,
):
self._resource_fn = check.callable_param(resource_fn, "resource_fn")
self._config_schema = convert_user_facing_definition_config_schema(config_schema)
self._description = check.opt_str_param(description, "description")
self._required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys"
)
self._version = check.opt_str_param(version, "version")
if version:
experimental_arg_warning("version", "ResourceDefinition.__init__")
@property
def resource_fn(self) -> Callable[..., Any]:
return self._resource_fn
@property
def config_schema(self) -> IDefinitionConfigSchema:
return self._config_schema
@property
def description(self) -> Optional[str]:
return self._description
@property
def version(self) -> Optional[str]:
return self._version
@property
def required_resource_keys(self) -> AbstractSet[str]:
return self._required_resource_keys
@staticmethod
def none_resource(description: Optional[str] = None) -> "ResourceDefinition":
return ResourceDefinition.hardcoded_resource(value=None, description=description)
@staticmethod
def hardcoded_resource(value: Any, description: Optional[str] = None) -> "ResourceDefinition":
return ResourceDefinition(resource_fn=lambda _init_context: value, description=description)
@staticmethod
def mock_resource(description: Optional[str] = None) -> "ResourceDefinition":
from unittest import mock
return ResourceDefinition(
resource_fn=lambda _init_context: mock.MagicMock(), description=description
)
@staticmethod
def string_resource(description: Optional[str] = None) -> "ResourceDefinition":
return ResourceDefinition(
resource_fn=lambda init_context: init_context.resource_config,
config_schema=str,
description=description,
)
def copy_for_configured(
self, description: Optional[str], config_schema: IDefinitionConfigSchema, _
) -> "ResourceDefinition":
return ResourceDefinition(
config_schema=config_schema,
description=description or self.description,
resource_fn=self.resource_fn,
required_resource_keys=self.required_resource_keys,
version=self.version,
)
def __call__(self, *args, **kwargs):
from dagster.core.execution.resources_init import InitResourceContext
context_provided = is_context_provided(get_function_params(self.resource_fn))
if context_provided:
if len(args) + len(kwargs) == 0:
raise DagsterInvalidInvocationError(
"Resource initialization function has context argument, but no context was provided "
"when invoking."
)
if len(args) + len(kwargs) > 1:
raise DagsterInvalidInvocationError(
"Initialization of resource received multiple arguments. Only a first "
"positional context parameter should be provided when invoking."
)
context_param_name = get_function_params(self.resource_fn)[0].name
if args:
check.opt_inst_param(args[0], context_param_name, InitResourceContext)
return resource_invocation_result(self, args[0])
else:
if context_param_name not in kwargs:
raise DagsterInvalidInvocationError(
f"Resource initialization expected argument '{context_param_name}'."
)
check.opt_inst_param(
kwargs[context_param_name], context_param_name, InitResourceContext
)
return resource_invocation_result(self, kwargs[context_param_name])
else:
return resource_invocation_result(self, None)
class _ResourceDecoratorCallable:
def __init__(
self,
config_schema: Optional[Dict[str, Any]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version: Optional[str] = None,
):
self.config_schema = config_schema
self.description = check.opt_str_param(description, "description")
self.version = check.opt_str_param(version, "version")
self.required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys"
)
def __call__(self, resource_fn: Callable[["InitResourceContext"], Any]):
check.callable_param(resource_fn, "resource_fn")
any_name = ["*"] if is_context_provided(get_function_params(resource_fn)) else []
params = get_function_params(resource_fn)
missing_positional = validate_expected_params(params, any_name)
if missing_positional:
raise DagsterInvalidDefinitionError(
f"@resource decorated function '{resource_fn.__name__}' expects a single "
"positional argument."
)
extras = params[len(any_name) :]
required_extras = list(filter(is_required_param, extras))
if required_extras:
raise DagsterInvalidDefinitionError(
f"@resource decorated function '{resource_fn.__name__}' expects only a single positional required argument. "
f"Got required extra params {', '.join(positional_arg_name_list(required_extras))}"
)
resource_def = ResourceDefinition(
resource_fn=resource_fn,
config_schema=self.config_schema,
description=self.description,
version=self.version,
required_resource_keys=self.required_resource_keys,
)
update_wrapper(resource_def, wrapped=resource_fn)
return resource_def
@overload
def resource(config_schema=Callable[["InitResourceContext"], Any]) -> ResourceDefinition:
...
@overload
def resource(
config_schema: Optional[Dict[str, Any]] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version=None,
) -> Callable[[Callable[["InitResourceContext"], Any]], "ResourceDefinition"]:
...
def resource(
config_schema: Optional[
Union[Callable[["InitResourceContext"], Any], IDefinitionConfigSchema, Dict[str, Any]]
] = None,
description: Optional[str] = None,
required_resource_keys: Optional[AbstractSet[str]] = None,
version=None,
) -> Union[
Callable[[Callable[["InitResourceContext"], Any]], "ResourceDefinition"], "ResourceDefinition"
]:
if callable(config_schema) and not is_callable_valid_config_arg(config_schema):
return _ResourceDecoratorCallable()(config_schema)
def _wrap(resource_fn: Callable[["InitResourceContext"], Any]) -> "ResourceDefinition":
return _ResourceDecoratorCallable(
config_schema=cast(Optional[Dict[str, Any]], config_schema),
description=description,
required_resource_keys=required_resource_keys,
version=version,
)(resource_fn)
return _wrap
class Resources:
class IContainsGenerator:
class ScopedResourcesBuilder(
namedtuple("ScopedResourcesBuilder", "resource_instance_dict contains_generator")
):
def __new__(
cls,
resource_instance_dict: Optional[Dict[str, Any]] = None,
contains_generator: Optional[bool] = False,
):
return super(ScopedResourcesBuilder, cls).__new__(
cls,
resource_instance_dict=check.opt_dict_param(
resource_instance_dict, "resource_instance_dict", key_type=str
),
contains_generator=contains_generator,
)
def build(self, required_resource_keys: Optional[AbstractSet[str]]) -> Resources:
required_resource_keys = check.opt_set_param(
required_resource_keys, "required_resource_keys", of_type=str
)
resource_instance_dict = {
key: self.resource_instance_dict[key]
for key in required_resource_keys
if key in self.resource_instance_dict
}
if self.contains_generator:
class _ScopedResourcesContainsGenerator(
namedtuple("_ScopedResourcesContainsGenerator", list(resource_instance_dict.keys())),
Resources,
IContainsGenerator,
):
def __getattr__(self, attr):
raise DagsterUnknownResourceError(attr)
return _ScopedResourcesContainsGenerator(**resource_instance_dict)
else:
class _ScopedResources(
namedtuple("_ScopedResources", list(resource_instance_dict.keys())),
Resources,
):
def __getattr__(self, attr):
raise DagsterUnknownResourceError(attr)
return _ScopedResources(**resource_instance_dict)
def make_values_resource(**kwargs: Any) -> ResourceDefinition:
return ResourceDefinition(
resource_fn=lambda init_context: init_context.resource_config,
config_schema=kwargs or Any,
)
| true | true |
f7fe84ce03cdd504b8f1583950e160169cbd9d90 | 3,878 | py | Python | python/bot.py | dev-null-undefined/felix | addad2375bc46683c75674ba83acc04495526830 | [
"MIT"
] | 135 | 2018-09-08T18:56:27.000Z | 2022-03-24T10:27:34.000Z | python/bot.py | dev-null-undefined/felix | addad2375bc46683c75674ba83acc04495526830 | [
"MIT"
] | 73 | 2018-09-29T07:40:10.000Z | 2022-03-06T11:57:19.000Z | python/bot.py | dev-null-undefined/felix | addad2375bc46683c75674ba83acc04495526830 | [
"MIT"
] | 105 | 2018-09-08T20:52:32.000Z | 2022-03-03T16:16:23.000Z | """Felix Discord Bot
This file starts the bot and loads all extensions/cogs and configs/permissions
The Bot automatically tries to load all extensions found in the "cogs/" folder
plus the hangman.hangman extension.
An extension can be reloaded without restarting the bot.
The extension "management" provides the commands to load/unload other extensions
This bot requires discord.py
pip install -U discord.py
"""
import json
import traceback
import sys
from datetime import datetime
from os import path, listdir
from discord.ext.commands import Bot, when_mentioned_or
from discord import DMChannel, Message, Activity, Intents, AllowedMentions
from aiohttp import ClientSession, ClientTimeout
class Felix(Bot):
def __init__(self, *args, **options):
super().__init__(*args, **options)
self.session = None
self.flood_mode = False
with open('../config.json') as conffile:
self.config = json.load(conffile)
self.last_errors = []
async def start(self, *args, **kwargs):
self.session = ClientSession(timeout=ClientTimeout(total=30))
await super().start(self.config["bot_key"], *args, **kwargs)
async def close(self):
await self.session.close()
await super().close()
def user_is_admin(self, user):
try:
user_roles = [role.id for role in user.roles]
except AttributeError:
return False
permitted_roles = self.config['admin_roles']
return any(role in permitted_roles for role in user_roles)
def user_is_superuser(self, user):
superusers = self.config['superusers']
return user.id in superusers
client = Felix(
command_prefix=when_mentioned_or('felix ', 'Felix '),
description='Hi I am Felix!',
max_messages=15000,
intents=Intents.all(),
allowed_mentions=AllowedMentions(everyone=False, users=True, roles=True)
)
STARTUP_EXTENSIONS = []
for file in listdir(path.join(path.dirname(__file__), 'cogs/')):
filename, ext = path.splitext(file)
if '.py' in ext:
STARTUP_EXTENSIONS.append(f'cogs.{filename}')
for extension in reversed(STARTUP_EXTENSIONS):
try:
client.load_extension(f'{extension}')
except Exception as e:
client.last_errors.append((e, datetime.utcnow(), None, None))
exc = f'{type(e).__name__}: {e}'
print(f'Failed to load extension {extension}\n{exc}')
@client.event
async def on_ready():
main_id = client.config['main_guild']
client.main_guild = client.get_guild(main_id) or client.guilds[0]
print('\nActive in these guilds/servers:')
[print(g.name) for g in client.guilds]
print('\nMain guild:', client.main_guild.name)
print('\nFelix-Python started successfully')
return True
@client.event
async def on_error(event_method, *args, **kwargs):
"""|coro|
The default error handler provided by the client.
By default this prints to :data:`sys.stderr` however it could be
overridden to have a different implementation.
Check :func:`~discord.on_error` for more details.
"""
print('Default Handler: Ignoring exception in {}'.format(event_method), file=sys.stderr)
traceback.print_exc()
# --------------- custom code below -------------------------------
# Saving the error if it resulted from a message edit
if len(args) > 1:
a1, a2, *_ = args
if isinstance(a1, Message) and isinstance(a2, Message):
client.last_errors.append((sys.exc_info()[1], datetime.utcnow(), a2, a2.content))
await client.change_presence(
activity=Activity(name='ERROR encountered', url=None, type=3)
)
@client.event
async def on_message(msg):
# Ignore DMs
if isinstance(msg.channel, DMChannel):
return
await client.process_commands(msg)
client.run()
print('Felix-Python has exited')
| 32.049587 | 93 | 0.676637 | import json
import traceback
import sys
from datetime import datetime
from os import path, listdir
from discord.ext.commands import Bot, when_mentioned_or
from discord import DMChannel, Message, Activity, Intents, AllowedMentions
from aiohttp import ClientSession, ClientTimeout
class Felix(Bot):
def __init__(self, *args, **options):
super().__init__(*args, **options)
self.session = None
self.flood_mode = False
with open('../config.json') as conffile:
self.config = json.load(conffile)
self.last_errors = []
async def start(self, *args, **kwargs):
self.session = ClientSession(timeout=ClientTimeout(total=30))
await super().start(self.config["bot_key"], *args, **kwargs)
async def close(self):
await self.session.close()
await super().close()
def user_is_admin(self, user):
try:
user_roles = [role.id for role in user.roles]
except AttributeError:
return False
permitted_roles = self.config['admin_roles']
return any(role in permitted_roles for role in user_roles)
def user_is_superuser(self, user):
superusers = self.config['superusers']
return user.id in superusers
client = Felix(
command_prefix=when_mentioned_or('felix ', 'Felix '),
description='Hi I am Felix!',
max_messages=15000,
intents=Intents.all(),
allowed_mentions=AllowedMentions(everyone=False, users=True, roles=True)
)
STARTUP_EXTENSIONS = []
for file in listdir(path.join(path.dirname(__file__), 'cogs/')):
filename, ext = path.splitext(file)
if '.py' in ext:
STARTUP_EXTENSIONS.append(f'cogs.{filename}')
for extension in reversed(STARTUP_EXTENSIONS):
try:
client.load_extension(f'{extension}')
except Exception as e:
client.last_errors.append((e, datetime.utcnow(), None, None))
exc = f'{type(e).__name__}: {e}'
print(f'Failed to load extension {extension}\n{exc}')
@client.event
async def on_ready():
main_id = client.config['main_guild']
client.main_guild = client.get_guild(main_id) or client.guilds[0]
print('\nActive in these guilds/servers:')
[print(g.name) for g in client.guilds]
print('\nMain guild:', client.main_guild.name)
print('\nFelix-Python started successfully')
return True
@client.event
async def on_error(event_method, *args, **kwargs):
print('Default Handler: Ignoring exception in {}'.format(event_method), file=sys.stderr)
traceback.print_exc()
if len(args) > 1:
a1, a2, *_ = args
if isinstance(a1, Message) and isinstance(a2, Message):
client.last_errors.append((sys.exc_info()[1], datetime.utcnow(), a2, a2.content))
await client.change_presence(
activity=Activity(name='ERROR encountered', url=None, type=3)
)
@client.event
async def on_message(msg):
if isinstance(msg.channel, DMChannel):
return
await client.process_commands(msg)
client.run()
print('Felix-Python has exited')
| true | true |
f7fe84f5af308e1f6c379272bf01425d466b1ac6 | 518 | py | Python | myBinaries/src/kvs/workloadGen.py | alex1230608/gem5 | d5225681568102a6441ce2c32d82f5b1b45ea4e2 | [
"BSD-3-Clause"
] | null | null | null | myBinaries/src/kvs/workloadGen.py | alex1230608/gem5 | d5225681568102a6441ce2c32d82f5b1b45ea4e2 | [
"BSD-3-Clause"
] | null | null | null | myBinaries/src/kvs/workloadGen.py | alex1230608/gem5 | d5225681568102a6441ce2c32d82f5b1b45ea4e2 | [
"BSD-3-Clause"
] | null | null | null | num_nic = 2
time_period = 100
separate = 10000
test_range = 2
test_repeat = 300
interval = 1
sharded = 1
readWrite = 1
print("%d"%num_nic)
for nic in range(0, num_nic):
print "%d"%(test_repeat*(test_range/interval)),
print ""
for nic in range(0, num_nic):
if sharded == 1:
start = nic*separate
else:
start = 0
end = start + test_range
print ""
time = 0
for i in range(0, test_repeat):
for key in range(start, end, interval):
time = time + time_period
print("%d\t%d\t%d"%(time, key, readWrite))
| 17.266667 | 48 | 0.662162 | num_nic = 2
time_period = 100
separate = 10000
test_range = 2
test_repeat = 300
interval = 1
sharded = 1
readWrite = 1
print("%d"%num_nic)
for nic in range(0, num_nic):
print "%d"%(test_repeat*(test_range/interval)),
print ""
for nic in range(0, num_nic):
if sharded == 1:
start = nic*separate
else:
start = 0
end = start + test_range
print ""
time = 0
for i in range(0, test_repeat):
for key in range(start, end, interval):
time = time + time_period
print("%d\t%d\t%d"%(time, key, readWrite))
| false | true |
f7fe8605c92c4ee75d7e0097fdb100a8c6fd6e57 | 6,501 | py | Python | bocce/utils.py | brianjpetersen/bocce | 20a4845400e8759173c5391ce52f18dafbf4c678 | [
"MIT"
] | null | null | null | bocce/utils.py | brianjpetersen/bocce | 20a4845400e8759173c5391ce52f18dafbf4c678 | [
"MIT"
] | null | null | null | bocce/utils.py | brianjpetersen/bocce | 20a4845400e8759173c5391ce52f18dafbf4c678 | [
"MIT"
] | null | null | null | # standard libraries
import os
import functools
import collections
import collections.abc
import datetime
import json
import multiprocessing
import threading
import traceback
import time
# third party libraries
pass
# first party libraries
pass
__where__ = os.path.dirname(os.path.abspath(__file__))
class repeat(threading.Thread):
def __init__(self, function, period, how='thread', on_error=None,
args=None, kwargs=None):
super(repeat, self).__init__(daemon=True)
if args is None:
args = ()
if kwargs is None:
kwargs = {}
if on_error is None:
def on_error(exception):
traceback.print_exc()
print()
def wrapped():
try:
function(*args, **kwargs)
except Exception as exception:
on_error(exception)
self.function = wrapped
self.period = period
if how == 'thread':
self.How = threading.Thread
elif how == 'process':
self.How = multiprocessing.Process
self.terminated = False
self.start()
def run(self):
while self.terminated == False:
try:
start = time.time()
runner = self.How(target=self.function)
runner.start()
runner.join()
duration = time.time() - start
if duration < self.period:
time.sleep(self.period - duration)
except:
continue
def terminate(self):
self.terminated = True
def cached_getter(allow_get=True, allow_set=True, allow_delete=True):
class Wrapper:
__slots__ = ('getter', 'name', 'cached_name', )
def __init__(self, getter):
self.getter = getter
self.name = getter.__name__
self.cached_name = '_cached_{}'.format(self.name)
def __get__(self, instance, owner=None):
if self.allow_get == False:
raise AttributeError
try:
return getattr(instance, self.cached_name)
except:
value = self.getter(instance)
setattr(instance, self.cached_name, value)
return value
def __set__(self, instance, value):
if self.allow_set == False:
raise AttributeError
setattr(instance, self.cached_name, value)
def __delete__(self, instance):
if self.allow_delete == False:
raise AttributeError
delattr(instance, self.cached_name)
Wrapper.allow_get = allow_get
Wrapper.allow_set = allow_set
Wrapper.allow_delete = allow_delete
return Wrapper
"""
def cached_setter(allow_get=True, set_once=False, allow_delete=True):
class Wrapper:
__slots__ = ('name', 'setter', 'was_set', 'value', )
def __init__(self, setter):
self.setter = setter
self.name = setter.__name__
self.was_set = False
def __get__(self, obj, type=None):
if self.allow_get == False:
raise AttributeError
return self.value
def __set__(self, obj, value):
if self.was_set and self.set_once:
raise AttributeError
self.value = self.setter(obj, value)
def __delete__(self, obj):
if self.allow_delete == False:
raise AttributeError
delattr(obj, self.name)
Wrapper.allow_get = allow_get
Wrapper.allow_delete = allow_delete
Wrapper.set_once = set_once
return Wrapper
"""
def once(f):
@functools.wraps(f)
def decorator(*args, **kwargs):
try:
return f._result
except AttributeError:
result = f._result = f(*args, **kwargs)
return result
return decorator
class LRUCache(collections.abc.MutableMapping):
def __init__(self, size=None):
if not isinstance(size, (int, float)):
raise TypeError()
else:
if size < 0:
raise ValueError()
self._size = size
self._cache = collections.OrderedDict()
def __getitem__(self, key):
return self.touch(key)
def flush(self):
self._cache = collections.OrderedDict()
@property
def overflowing(self):
return len(self) > self.size
def touch(self, key):
value = self._cache.pop(key)
self._cache[key] = value
return value
def __setitem__(self, key, value):
self._cache[key] = value
if self.size is not None:
self.squeeze()
@property
def size(self):
return self._size
@size.setter
def size(self, size):
self._size = size
self.squeeze()
def squeeze(self):
while self.overflowing:
self._cache.popitem(last=False)
def __delitem__(self, key):
del self._cache[key]
def __iter__(self):
return iter(self._cache)
def __len__(self):
return len(self._cache)
class When:
@staticmethod
def timestamp(when=None, format='%Y-%m-%dT%H:%M:%SZ'):
if when is None:
when = datetime.datetime.utcnow()
return when.strftime(format)
@staticmethod
def iso_timestamp(when=None):
return When.timestamp(when, format='%Y-%m-%dT%H:%M:%SZ')
@staticmethod
def unix_timestamp(when=None):
if when is None:
when = datetime.datetime.utcnow()
return when.timestamp()
@staticmethod
def http_timestamp(when=None):
return When.timestamp(when, format='%a, %d-%b-%Y %T GMT')
"""
@staticmethod
def from_timestamp(timestamp, format='YYYY-MM-DD'):
pass
"""
class JsonEncoder(json.JSONEncoder):
def __init__(self, indent=None, serializers=None):
super(JsonEncoder, self).__init__(indent=indent)
if serializers is None:
serializers = {}
self.serializers = serializers
def default(self, obj):
try:
serializer = self.serializers[obj.__class__]
return serializer(obj)
except:
return super(JsonEncoder, self).default(obj)
| 26.21371 | 69 | 0.557607 |
import os
import functools
import collections
import collections.abc
import datetime
import json
import multiprocessing
import threading
import traceback
import time
pass
pass
__where__ = os.path.dirname(os.path.abspath(__file__))
class repeat(threading.Thread):
def __init__(self, function, period, how='thread', on_error=None,
args=None, kwargs=None):
super(repeat, self).__init__(daemon=True)
if args is None:
args = ()
if kwargs is None:
kwargs = {}
if on_error is None:
def on_error(exception):
traceback.print_exc()
print()
def wrapped():
try:
function(*args, **kwargs)
except Exception as exception:
on_error(exception)
self.function = wrapped
self.period = period
if how == 'thread':
self.How = threading.Thread
elif how == 'process':
self.How = multiprocessing.Process
self.terminated = False
self.start()
def run(self):
while self.terminated == False:
try:
start = time.time()
runner = self.How(target=self.function)
runner.start()
runner.join()
duration = time.time() - start
if duration < self.period:
time.sleep(self.period - duration)
except:
continue
def terminate(self):
self.terminated = True
def cached_getter(allow_get=True, allow_set=True, allow_delete=True):
class Wrapper:
__slots__ = ('getter', 'name', 'cached_name', )
def __init__(self, getter):
self.getter = getter
self.name = getter.__name__
self.cached_name = '_cached_{}'.format(self.name)
def __get__(self, instance, owner=None):
if self.allow_get == False:
raise AttributeError
try:
return getattr(instance, self.cached_name)
except:
value = self.getter(instance)
setattr(instance, self.cached_name, value)
return value
def __set__(self, instance, value):
if self.allow_set == False:
raise AttributeError
setattr(instance, self.cached_name, value)
def __delete__(self, instance):
if self.allow_delete == False:
raise AttributeError
delattr(instance, self.cached_name)
Wrapper.allow_get = allow_get
Wrapper.allow_set = allow_set
Wrapper.allow_delete = allow_delete
return Wrapper
def once(f):
@functools.wraps(f)
def decorator(*args, **kwargs):
try:
return f._result
except AttributeError:
result = f._result = f(*args, **kwargs)
return result
return decorator
class LRUCache(collections.abc.MutableMapping):
def __init__(self, size=None):
if not isinstance(size, (int, float)):
raise TypeError()
else:
if size < 0:
raise ValueError()
self._size = size
self._cache = collections.OrderedDict()
def __getitem__(self, key):
return self.touch(key)
def flush(self):
self._cache = collections.OrderedDict()
@property
def overflowing(self):
return len(self) > self.size
def touch(self, key):
value = self._cache.pop(key)
self._cache[key] = value
return value
def __setitem__(self, key, value):
self._cache[key] = value
if self.size is not None:
self.squeeze()
@property
def size(self):
return self._size
@size.setter
def size(self, size):
self._size = size
self.squeeze()
def squeeze(self):
while self.overflowing:
self._cache.popitem(last=False)
def __delitem__(self, key):
del self._cache[key]
def __iter__(self):
return iter(self._cache)
def __len__(self):
return len(self._cache)
class When:
@staticmethod
def timestamp(when=None, format='%Y-%m-%dT%H:%M:%SZ'):
if when is None:
when = datetime.datetime.utcnow()
return when.strftime(format)
@staticmethod
def iso_timestamp(when=None):
return When.timestamp(when, format='%Y-%m-%dT%H:%M:%SZ')
@staticmethod
def unix_timestamp(when=None):
if when is None:
when = datetime.datetime.utcnow()
return when.timestamp()
@staticmethod
def http_timestamp(when=None):
return When.timestamp(when, format='%a, %d-%b-%Y %T GMT')
class JsonEncoder(json.JSONEncoder):
def __init__(self, indent=None, serializers=None):
super(JsonEncoder, self).__init__(indent=indent)
if serializers is None:
serializers = {}
self.serializers = serializers
def default(self, obj):
try:
serializer = self.serializers[obj.__class__]
return serializer(obj)
except:
return super(JsonEncoder, self).default(obj)
| true | true |
f7fe88093ad7d02c94f780d3849b03a3795789a9 | 14,209 | py | Python | JFit/physics/nu_oscillation/Prob_e2e.py | J-Fit/JFit | 85c67aaca0295a75714db2011e35222dabf50c38 | [
"MIT"
] | 1 | 2021-03-02T12:51:42.000Z | 2021-03-02T12:51:42.000Z | JFit/physics/nu_oscillation/Prob_e2e.py | J-Fit/JFit | 85c67aaca0295a75714db2011e35222dabf50c38 | [
"MIT"
] | null | null | null | JFit/physics/nu_oscillation/Prob_e2e.py | J-Fit/JFit | 85c67aaca0295a75714db2011e35222dabf50c38 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
''' pure nue -> nue
author: Jinnan Zhang
zhangjinnan@ihep.ac.cn
date: 2021.03.08
'''
import numpy as np
def get_parser():
import argparse
parser = argparse.ArgumentParser(description="Check or show the oscillation pattern.")
parser.add_argument(
"--cME",
action="store_true",
help="Check the matter effect model, the JUNO Yellow book model, the Yufeng model, and the Hiroshi model."
)
parser.set_defaults(cME=False)
parser.add_argument("--pNMO",
action="store_true",
help="Show pattern of neutrino mass ordering.")
parser.set_defaults(pNMO=False)
parser.add_argument(
"--NMO-op",
type=str,
help="The NMO show option.")
return parser
class Prob_e2e:
def __init__(self, NMO=1, ME=True, NameSpace='PDG2020'):
self.NameSpace = NameSpace
if NMO == 1:
self.NMO = 'normal' # mass ordering, 1 for normal, others for invert
else:
self.NMO = 'invert'
self.ME = ME # in Matter or not
import os
import yaml
curPath = os.path.dirname(os.path.realpath(__file__))
OsciPar_yamlPath = curPath + "/data/OscillationParameters.yaml"
f_osci_par = open(OsciPar_yamlPath)
self.OsciPar = yaml.load(f_osci_par.read(), Loader=yaml.Loader)
self.Sin_sqTheta12 = self.OsciPar[self.NameSpace][self.NMO]['sinsq12']
self.DeltaM21_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq21']
self.DeltaM31_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq31']
self.DeltaM32_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq32']
self.Sin_sqTheta13 = self.OsciPar[self.NameSpace][self.NMO]['sinsq13']
self.matter_density = self.OsciPar['MatterDensity']
self.cal_matter_potential()
def out(self):
print(self.A_MatPoten_0)
def cal_matter_potential(self):
M_unified_atomic_kg = 1.6605390666e-27
N_e = self.matter_density / M_unified_atomic_kg / 2.0
hbar_C = 197.3269804 # MeV.fm
G_F = 1.1663787e-5
#- sign for antineutrinos
self.A_MatPoten_0 = -2 * np.sqrt(
2) * G_F * N_e * hbar_C * hbar_C * hbar_C * 1e-39
def get_prob_e2e_Amir(self, Enu, baseline, ME=True):
'''
Enu: MeV, baseline: cm
Based on: arXiv:1910.12900, from Amir N. Khan, Hiroshi Nunokawa,...
'''
Sin_sqTheta12 = self.Sin_sqTheta12
DeltaM21_sq = self.DeltaM21_sq
DeltaM31_sq = self.DeltaM31_sq
DeltaM32_sq = self.DeltaM32_sq
Sin_sqTheta13 = self.Sin_sqTheta13
E = Enu
BaseLine = baseline * 1e-2 # cm to m
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
# reverse the relation
A_MatPoten = E * self.A_MatPoten_0
# eq. 6
DeltaMsq_ee = DeltaM31_sq * (1 - Sin_sqTheta12) + DeltaM32_sq * Sin_sqTheta12
Cos_2Theta_12 = 1 - 2 * Sin_sqTheta12
Cos_2Theta_13 = 1 - 2 * Sin_sqTheta13
# eq. 8
DeltaMsq_ee_M = DeltaMsq_ee*np.sqrt((Cos_2Theta_13-A_MatPoten/DeltaMsq_ee)**2+Sinsq2Theta13)
# eq. 7
Cos_2Theta_13_M=(DeltaMsq_ee*Cos_2Theta_13-A_MatPoten)/DeltaMsq_ee_M
# eq. 11
A_MatPoten_prime=0.5*(A_MatPoten+DeltaMsq_ee-DeltaMsq_ee_M)
# eq.12
Cos_sq_theta13M_minus_theta13=(DeltaMsq_ee_M+DeltaMsq_ee-A_MatPoten*Cos_2Theta_13)*0.5/DeltaMsq_ee_M
# eq. 10
DeltaM21_sq_M= DeltaM21_sq*np.sqrt((Cos_2Theta_12-A_MatPoten_prime/DeltaM21_sq)**2+Cos_sq_theta13M_minus_theta13*Sinsq2Theta12)
# eq. 9
Cos_2Theta_12_M=(DeltaM21_sq*Cos_2Theta_12-A_MatPoten_prime)/DeltaM21_sq_M
Sin_sqTheta13_M=(1-Cos_2Theta_13_M)/2
Sinsq2Theta13_M = 1-Cos_2Theta_13_M*Cos_2Theta_13_M
Sin_sqTheta12_M = (1-Cos_2Theta_12_M)/2
Sinsq2Theta12_M=1-Cos_2Theta_12_M*Cos_2Theta_12_M
DeltaM31_sq_M = DeltaMsq_ee_M+Sin_sqTheta12_M*DeltaM21_sq_M
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
return prob
def get_prob_e2e_Yufeng(self, Enu, baseline, ME=True):
'''
Enu: MeV, baseline: cm
Based on: https://juno.ihep.ac.cn/cgi-bin/Dev_DocDB/ShowDocument?docid=6859
'''
Sin_sqTheta12 = self.Sin_sqTheta12
DeltaM21_sq = self.DeltaM21_sq
DeltaM31_sq = self.DeltaM31_sq
DeltaM32_sq = self.DeltaM32_sq
Sin_sqTheta13 = self.Sin_sqTheta13
E = Enu
BaseLine = baseline * 1e-2 # cm to m
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
# reverse the relation, for neutrino
A_MatPoten = E * self.A_MatPoten_0
Delta_c = DeltaM31_sq * (1 - Sin_sqTheta12) + DeltaM32_sq * Sin_sqTheta12 # eq. 8
alpha_c = DeltaM21_sq / Delta_c # eq .8
A_star = A_MatPoten * (1 - Sin_sqTheta13) / DeltaM21_sq # eq .9
A_c = A_MatPoten / Delta_c # eq. 9
Cos_2Theta_12 = 1 - 2 * Sin_sqTheta12
Cos_2Theta_13 = 1 - 2 * Sin_sqTheta13
# C_hat_12 = np.sqrt(1 - 2.0 * A_star * Cos_2Theta_12 +A_star * A_star)
# C_hat_13 = np.sqrt(1 - 2.0 * A_c * Cos_2Theta_13 +A_c * A_c)
C_hat_12_prime = np.sqrt(1 - 2.0 * A_star * Cos_2Theta_12 +A_star * A_star)
C_hat_13_prime = np.sqrt(1 - 2.0 * A_c * Cos_2Theta_13 + A_c * A_c)
Cos_sq_Theta12_tilde = 0.5*(1-(A_star-Cos_2Theta_12)/C_hat_12_prime)
Cos_sq_Theta13_tilde = 0.5*(1-(A_c-Cos_2Theta_13)/C_hat_13_prime)
Sin_sqTheta13_M=1-Cos_sq_Theta13_tilde
Sinsq2Theta13_M = 4*Sin_sqTheta13_M*Cos_sq_Theta13_tilde
Sin_sqTheta12_M = 1-Cos_sq_Theta12_tilde
Sinsq2Theta12_M=4*Sin_sqTheta12_M*Cos_sq_Theta12_tilde
DeltaM21_sq_M = Delta_c*(0.5*(1+A_c-C_hat_13_prime)+alpha_c*(C_hat_12_prime-A_star))
DeltaM31_sq_M = Delta_c*(0.5*(1+A_c+C_hat_13_prime)+alpha_c*0.5*(C_hat_12_prime-A_star-Cos_2Theta_12))
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
# print()
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
# print("Yufeng: ",self.DeltaM31_sq)
return prob
def get_prob_e2e_YB(self, Enu, baseline, ME=True):
'''
Enu: MeV, baseline: cm
'''
E = Enu
BaseLine = baseline * 1e-2 # cm to m
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
A_MatPoten = E * self.A_MatPoten_0
eta_12 = (1 - 2 * self.Sin_sqTheta12 -
A_MatPoten / self.DeltaM21_sq) * (
1 - 2 * self.Sin_sqTheta12 -
A_MatPoten / self.DeltaM21_sq) + Sinsq2Theta12
eta_13 = (1 - 2 * self.Sin_sqTheta13 -
A_MatPoten / self.DeltaM31_sq) * (
1 - 2 * self.Sin_sqTheta13 -
A_MatPoten / self.DeltaM31_sq) + Sinsq2Theta13
Sinsq2Theta12_M = Sinsq2Theta12 / eta_12
Sinsq2Theta13_M = Sinsq2Theta13 / eta_13
Sin_sqTheta12_M = (1 - np.sqrt(1 - Sinsq2Theta12_M)) / 2.
Sin_sqTheta13_M = (1 - np.sqrt(1 - Sinsq2Theta13_M)) / 2.
DeltaM21_sq_M = self.DeltaM21_sq * np.sqrt(eta_12)
DeltaM31_sq_M = self.DeltaM31_sq * np.sqrt(eta_13)
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
# print("YB: ",self.DeltaM31_sq)
return prob
def Check_YB_Hermitian(E_low=0.8, E_up=15., N=1000, BaseLine=52.5e5,ME=1):
def GetAsy(a, b):
# return 2 * (a - b) / (a + b)
return (a - b) / ( b)
Es = np.linspace(E_low, E_up, N)
# JUNO Yellow formula
P_e2e_YB = Prob_e2e(NMO=1)
y_YB = P_e2e_YB.get_prob_e2e_YB(Es, baseline=BaseLine,ME=ME)
y_Yufeng=P_e2e_YB.get_prob_e2e_Yufeng(Es, baseline=BaseLine,ME=ME)
y_Amir=P_e2e_YB.get_prob_e2e_Amir(Es, baseline=BaseLine,ME=ME)
# Hermitian approach
import sys
sys.path.append('../..')
from physics.nu_oscillation import oscprob3nu, hamiltonians3nu
from physics.nu_oscillation.globaldefs import CONV_CM_TO_INV_EV, VCC_EARTH_CRUST, S23_NO_BF, DCP_NO_BF
S12_NO_BF = np.sqrt(P_e2e_YB.Sin_sqTheta12)
S13_NO_BF = np.sqrt(P_e2e_YB.Sin_sqTheta13)
D21_NO_BF = P_e2e_YB.DeltaM21_sq
D31_NO_BF = P_e2e_YB.DeltaM31_sq
h_vacuum_energy_indep = hamiltonians3nu.hamiltonian_3nu_vacuum_energy_independent(
S12_NO_BF, S23_NO_BF, S13_NO_BF, -DCP_NO_BF, D21_NO_BF,
D31_NO_BF) # sign - DCP_NO_BF for antineutrinos
y_Het = np.zeros(N)
for i, energy in enumerate(Es):
# sign - for antineutrinos
if ME:
h_matter = hamiltonians3nu.hamiltonian_3nu_matter(h_vacuum_energy_indep, energy * 1e6,-VCC_EARTH_CRUST)
else:
h_matter = np.multiply(1/(energy*1e6),h_vacuum_energy_indep)
Pee, Pem, Pet, Pme, Pmm, Pmt, Pte, Ptm, Ptt = oscprob3nu.probabilities_3nu(
h_matter, BaseLine * CONV_CM_TO_INV_EV)
y_Het[i] = Pee
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
plt.style.use('../../detector/DYB_like/lib/Paper.mplstyle')
with PdfPages('results/ME_models.pdf') as pdf:
fig, ax = plt.subplots()
ax.set_ylabel(r'$\frac{2\cdot(A-B)}{(A+B)}$')
ax.set_xlabel('Neutrino Energy [MeV]')
# ax.plot(Es, y_Het, label='Hamiltonian approach')
# ax.plot(Es, y_YB, label='Yellow Book Approach')
# ax.plot(Es, y_Yufeng, label='Yufeng Approach')
# ax.plot(Es, y_Amir, label='Amir Approach')
# ax.plot(Es, GetAsy(y_YB, y_Het), label='YB/Hamiltonian')
# ax.plot(Es, GetAsy(y_Amir,y_Yufeng), label='Amir/Yufeng')
ax.plot(Es, GetAsy(y_Amir,y_Yufeng), label='Amir/Yufeng')
ax.text(y=0.,x=6,s="Amir: arXiv:1910.12900\n Yufeng: JUNO-doc-6859")
ax.legend()
pdf.savefig()
# ax.cla()
# fig.savefig('./results/Yufeng_Amir.png')
ax.plot(Es, GetAsy(y_YB, y_Het), label='YB/Hamiltonian')
ax.plot(Es, GetAsy(y_YB, y_Yufeng), label='YB/Yufeng')
ax.plot(Es, GetAsy(y_Yufeng,y_Het), label='Yufeng/Hamiltonian')
# ax.plot(Es, GetAsy(y_Amir,y_Het), label='Amir/Hamiltonian')
ax.set_ylabel(r'$\frac{2\cdot(A-B)}{(A+B)}$')
ax.set_xlabel('Neutrino Energy [MeV]')
ax.legend()
pdf.savefig()
# fig.savefig('./results/four_model.png')
# plt.show()
def show_NMO_pattern(pattern='nue2nue'):
print(pattern)
if __name__ == "__main__":
parser = get_parser()
args = parser.parse_args()
if args.cME:
Check_YB_Hermitian()
if args.pNMO:
show_NMO_pattern(args.NMO_op)
| 44.823344 | 139 | 0.597157 |
import numpy as np
def get_parser():
import argparse
parser = argparse.ArgumentParser(description="Check or show the oscillation pattern.")
parser.add_argument(
"--cME",
action="store_true",
help="Check the matter effect model, the JUNO Yellow book model, the Yufeng model, and the Hiroshi model."
)
parser.set_defaults(cME=False)
parser.add_argument("--pNMO",
action="store_true",
help="Show pattern of neutrino mass ordering.")
parser.set_defaults(pNMO=False)
parser.add_argument(
"--NMO-op",
type=str,
help="The NMO show option.")
return parser
class Prob_e2e:
def __init__(self, NMO=1, ME=True, NameSpace='PDG2020'):
self.NameSpace = NameSpace
if NMO == 1:
self.NMO = 'normal'
else:
self.NMO = 'invert'
self.ME = ME
import os
import yaml
curPath = os.path.dirname(os.path.realpath(__file__))
OsciPar_yamlPath = curPath + "/data/OscillationParameters.yaml"
f_osci_par = open(OsciPar_yamlPath)
self.OsciPar = yaml.load(f_osci_par.read(), Loader=yaml.Loader)
self.Sin_sqTheta12 = self.OsciPar[self.NameSpace][self.NMO]['sinsq12']
self.DeltaM21_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq21']
self.DeltaM31_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq31']
self.DeltaM32_sq = self.OsciPar[self.NameSpace][self.NMO]['dmsq32']
self.Sin_sqTheta13 = self.OsciPar[self.NameSpace][self.NMO]['sinsq13']
self.matter_density = self.OsciPar['MatterDensity']
self.cal_matter_potential()
def out(self):
print(self.A_MatPoten_0)
def cal_matter_potential(self):
M_unified_atomic_kg = 1.6605390666e-27
N_e = self.matter_density / M_unified_atomic_kg / 2.0
hbar_C = 197.3269804
G_F = 1.1663787e-5
self.A_MatPoten_0 = -2 * np.sqrt(
2) * G_F * N_e * hbar_C * hbar_C * hbar_C * 1e-39
def get_prob_e2e_Amir(self, Enu, baseline, ME=True):
Sin_sqTheta12 = self.Sin_sqTheta12
DeltaM21_sq = self.DeltaM21_sq
DeltaM31_sq = self.DeltaM31_sq
DeltaM32_sq = self.DeltaM32_sq
Sin_sqTheta13 = self.Sin_sqTheta13
E = Enu
BaseLine = baseline * 1e-2
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
A_MatPoten = E * self.A_MatPoten_0
DeltaMsq_ee = DeltaM31_sq * (1 - Sin_sqTheta12) + DeltaM32_sq * Sin_sqTheta12
Cos_2Theta_12 = 1 - 2 * Sin_sqTheta12
Cos_2Theta_13 = 1 - 2 * Sin_sqTheta13
DeltaMsq_ee_M = DeltaMsq_ee*np.sqrt((Cos_2Theta_13-A_MatPoten/DeltaMsq_ee)**2+Sinsq2Theta13)
Cos_2Theta_13_M=(DeltaMsq_ee*Cos_2Theta_13-A_MatPoten)/DeltaMsq_ee_M
A_MatPoten_prime=0.5*(A_MatPoten+DeltaMsq_ee-DeltaMsq_ee_M)
Cos_sq_theta13M_minus_theta13=(DeltaMsq_ee_M+DeltaMsq_ee-A_MatPoten*Cos_2Theta_13)*0.5/DeltaMsq_ee_M
DeltaM21_sq_M= DeltaM21_sq*np.sqrt((Cos_2Theta_12-A_MatPoten_prime/DeltaM21_sq)**2+Cos_sq_theta13M_minus_theta13*Sinsq2Theta12)
Cos_2Theta_12_M=(DeltaM21_sq*Cos_2Theta_12-A_MatPoten_prime)/DeltaM21_sq_M
Sin_sqTheta13_M=(1-Cos_2Theta_13_M)/2
Sinsq2Theta13_M = 1-Cos_2Theta_13_M*Cos_2Theta_13_M
Sin_sqTheta12_M = (1-Cos_2Theta_12_M)/2
Sinsq2Theta12_M=1-Cos_2Theta_12_M*Cos_2Theta_12_M
DeltaM31_sq_M = DeltaMsq_ee_M+Sin_sqTheta12_M*DeltaM21_sq_M
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
return prob
def get_prob_e2e_Yufeng(self, Enu, baseline, ME=True):
Sin_sqTheta12 = self.Sin_sqTheta12
DeltaM21_sq = self.DeltaM21_sq
DeltaM31_sq = self.DeltaM31_sq
DeltaM32_sq = self.DeltaM32_sq
Sin_sqTheta13 = self.Sin_sqTheta13
E = Enu
BaseLine = baseline * 1e-2
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
A_MatPoten = E * self.A_MatPoten_0
Delta_c = DeltaM31_sq * (1 - Sin_sqTheta12) + DeltaM32_sq * Sin_sqTheta12
alpha_c = DeltaM21_sq / Delta_c
A_star = A_MatPoten * (1 - Sin_sqTheta13) / DeltaM21_sq
A_c = A_MatPoten / Delta_c
Cos_2Theta_12 = 1 - 2 * Sin_sqTheta12
Cos_2Theta_13 = 1 - 2 * Sin_sqTheta13
C_hat_12_prime = np.sqrt(1 - 2.0 * A_star * Cos_2Theta_12 +A_star * A_star)
C_hat_13_prime = np.sqrt(1 - 2.0 * A_c * Cos_2Theta_13 + A_c * A_c)
Cos_sq_Theta12_tilde = 0.5*(1-(A_star-Cos_2Theta_12)/C_hat_12_prime)
Cos_sq_Theta13_tilde = 0.5*(1-(A_c-Cos_2Theta_13)/C_hat_13_prime)
Sin_sqTheta13_M=1-Cos_sq_Theta13_tilde
Sinsq2Theta13_M = 4*Sin_sqTheta13_M*Cos_sq_Theta13_tilde
Sin_sqTheta12_M = 1-Cos_sq_Theta12_tilde
Sinsq2Theta12_M=4*Sin_sqTheta12_M*Cos_sq_Theta12_tilde
DeltaM21_sq_M = Delta_c*(0.5*(1+A_c-C_hat_13_prime)+alpha_c*(C_hat_12_prime-A_star))
DeltaM31_sq_M = Delta_c*(0.5*(1+A_c+C_hat_13_prime)+alpha_c*0.5*(C_hat_12_prime-A_star-Cos_2Theta_12))
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
return prob
def get_prob_e2e_YB(self, Enu, baseline, ME=True):
E = Enu
BaseLine = baseline * 1e-2
prob = 0
Sinsq2Theta12 = (4 * self.Sin_sqTheta12 * (1 - self.Sin_sqTheta12))
Sinsq2Theta13 = (4 * self.Sin_sqTheta13 * (1 - self.Sin_sqTheta13))
if ME:
A_MatPoten = E * self.A_MatPoten_0
eta_12 = (1 - 2 * self.Sin_sqTheta12 -
A_MatPoten / self.DeltaM21_sq) * (
1 - 2 * self.Sin_sqTheta12 -
A_MatPoten / self.DeltaM21_sq) + Sinsq2Theta12
eta_13 = (1 - 2 * self.Sin_sqTheta13 -
A_MatPoten / self.DeltaM31_sq) * (
1 - 2 * self.Sin_sqTheta13 -
A_MatPoten / self.DeltaM31_sq) + Sinsq2Theta13
Sinsq2Theta12_M = Sinsq2Theta12 / eta_12
Sinsq2Theta13_M = Sinsq2Theta13 / eta_13
Sin_sqTheta12_M = (1 - np.sqrt(1 - Sinsq2Theta12_M)) / 2.
Sin_sqTheta13_M = (1 - np.sqrt(1 - Sinsq2Theta13_M)) / 2.
DeltaM21_sq_M = self.DeltaM21_sq * np.sqrt(eta_12)
DeltaM31_sq_M = self.DeltaM31_sq * np.sqrt(eta_13)
DeltaM32_sq_M = DeltaM31_sq_M - DeltaM21_sq_M
Delta21 = 1.266932679815373 * DeltaM21_sq_M * BaseLine / E
Delta31 = 1.266932679815373 * DeltaM31_sq_M * BaseLine / E
Delta32 = 1.266932679815373 * DeltaM32_sq_M * BaseLine / E
prob = 1. - Sinsq2Theta13_M * (
(1 - Sin_sqTheta12_M) * np.sin(Delta31)**2. +
Sin_sqTheta12_M * np.sin(Delta32)**2.) - (
(1 - Sin_sqTheta13_M)**
2.) * Sinsq2Theta12_M * np.sin(Delta21)**2.
else:
Delta21 = 1.266932679815373 * self.DeltaM21_sq * BaseLine / E
Delta31 = 1.266932679815373 * self.DeltaM31_sq * BaseLine / E
Delta32 = 1.266932679815373 * self.DeltaM32_sq * BaseLine / E
prob = 1. - Sinsq2Theta13 * (
(1 - self.Sin_sqTheta12) * np.sin(Delta31)**2. +
self.Sin_sqTheta12 * np.sin(Delta32)**2.) - (
(1 - self.Sin_sqTheta13)**
2.) * Sinsq2Theta12 * np.sin(Delta21)**2.
return prob
def Check_YB_Hermitian(E_low=0.8, E_up=15., N=1000, BaseLine=52.5e5,ME=1):
def GetAsy(a, b):
return (a - b) / ( b)
Es = np.linspace(E_low, E_up, N)
P_e2e_YB = Prob_e2e(NMO=1)
y_YB = P_e2e_YB.get_prob_e2e_YB(Es, baseline=BaseLine,ME=ME)
y_Yufeng=P_e2e_YB.get_prob_e2e_Yufeng(Es, baseline=BaseLine,ME=ME)
y_Amir=P_e2e_YB.get_prob_e2e_Amir(Es, baseline=BaseLine,ME=ME)
import sys
sys.path.append('../..')
from physics.nu_oscillation import oscprob3nu, hamiltonians3nu
from physics.nu_oscillation.globaldefs import CONV_CM_TO_INV_EV, VCC_EARTH_CRUST, S23_NO_BF, DCP_NO_BF
S12_NO_BF = np.sqrt(P_e2e_YB.Sin_sqTheta12)
S13_NO_BF = np.sqrt(P_e2e_YB.Sin_sqTheta13)
D21_NO_BF = P_e2e_YB.DeltaM21_sq
D31_NO_BF = P_e2e_YB.DeltaM31_sq
h_vacuum_energy_indep = hamiltonians3nu.hamiltonian_3nu_vacuum_energy_independent(
S12_NO_BF, S23_NO_BF, S13_NO_BF, -DCP_NO_BF, D21_NO_BF,
D31_NO_BF)
y_Het = np.zeros(N)
for i, energy in enumerate(Es):
if ME:
h_matter = hamiltonians3nu.hamiltonian_3nu_matter(h_vacuum_energy_indep, energy * 1e6,-VCC_EARTH_CRUST)
else:
h_matter = np.multiply(1/(energy*1e6),h_vacuum_energy_indep)
Pee, Pem, Pet, Pme, Pmm, Pmt, Pte, Ptm, Ptt = oscprob3nu.probabilities_3nu(
h_matter, BaseLine * CONV_CM_TO_INV_EV)
y_Het[i] = Pee
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
plt.style.use('../../detector/DYB_like/lib/Paper.mplstyle')
with PdfPages('results/ME_models.pdf') as pdf:
fig, ax = plt.subplots()
ax.set_ylabel(r'$\frac{2\cdot(A-B)}{(A+B)}$')
ax.set_xlabel('Neutrino Energy [MeV]')
ax.plot(Es, GetAsy(y_Amir,y_Yufeng), label='Amir/Yufeng')
ax.text(y=0.,x=6,s="Amir: arXiv:1910.12900\n Yufeng: JUNO-doc-6859")
ax.legend()
pdf.savefig()
ax.plot(Es, GetAsy(y_YB, y_Het), label='YB/Hamiltonian')
ax.plot(Es, GetAsy(y_YB, y_Yufeng), label='YB/Yufeng')
ax.plot(Es, GetAsy(y_Yufeng,y_Het), label='Yufeng/Hamiltonian')
ax.set_ylabel(r'$\frac{2\cdot(A-B)}{(A+B)}$')
ax.set_xlabel('Neutrino Energy [MeV]')
ax.legend()
pdf.savefig()
def show_NMO_pattern(pattern='nue2nue'):
print(pattern)
if __name__ == "__main__":
parser = get_parser()
args = parser.parse_args()
if args.cME:
Check_YB_Hermitian()
if args.pNMO:
show_NMO_pattern(args.NMO_op)
| true | true |
f7fe881573c50b01cca6dca48fde1cc4ad374b83 | 2,316 | py | Python | examples/ami/sd0/local/dataio.py | phecda-xu/PaddleSpeech | 6bf0d3bf57229091a74912633e837dabc6215c86 | [
"Apache-2.0"
] | 1 | 2022-02-26T01:48:00.000Z | 2022-02-26T01:48:00.000Z | examples/ami/sd0/local/dataio.py | ziwenag/PaddleSpeech | 89e69ee10ee02b875af663146bc46fcf095e812a | [
"Apache-2.0"
] | null | null | null | examples/ami/sd0/local/dataio.py | ziwenag/PaddleSpeech | 89e69ee10ee02b875af663146bc46fcf095e812a | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Data reading and writing.
Authors
* qingenz123@126.com (Qingen ZHAO) 2022
"""
import os
import pickle
def save_pkl(obj, file):
"""Save an object in pkl format.
Arguments
---------
obj : object
Object to save in pkl format
file : str
Path to the output file
sampling_rate : int
Sampling rate of the audio file, TODO: this is not used?
Example
-------
>>> tmpfile = os.path.join(getfixture('tmpdir'), "example.pkl")
>>> save_pkl([1, 2, 3, 4, 5], tmpfile)
>>> load_pkl(tmpfile)
[1, 2, 3, 4, 5]
"""
with open(file, "wb") as f:
pickle.dump(obj, f)
def load_pickle(pickle_path):
"""Utility function for loading .pkl pickle files.
Arguments
---------
pickle_path : str
Path to pickle file.
Returns
-------
out : object
Python object loaded from pickle.
"""
with open(pickle_path, "rb") as f:
out = pickle.load(f)
return out
def load_pkl(file):
"""Loads a pkl file.
For an example, see `save_pkl`.
Arguments
---------
file : str
Path to the input pkl file.
Returns
-------
The loaded object.
"""
# Deals with the situation where two processes are trying
# to access the same label dictionary by creating a lock
count = 100
while count > 0:
if os.path.isfile(file + ".lock"):
time.sleep(1)
count -= 1
else:
break
try:
open(file + ".lock", "w").close()
with open(file, "rb") as f:
return pickle.load(f)
finally:
if os.path.isfile(file + ".lock"):
os.remove(file + ".lock")
| 23.632653 | 74 | 0.6019 |
import os
import pickle
def save_pkl(obj, file):
with open(file, "wb") as f:
pickle.dump(obj, f)
def load_pickle(pickle_path):
with open(pickle_path, "rb") as f:
out = pickle.load(f)
return out
def load_pkl(file):
count = 100
while count > 0:
if os.path.isfile(file + ".lock"):
time.sleep(1)
count -= 1
else:
break
try:
open(file + ".lock", "w").close()
with open(file, "rb") as f:
return pickle.load(f)
finally:
if os.path.isfile(file + ".lock"):
os.remove(file + ".lock")
| true | true |
f7fe89ff2c106eb98d907bf2dbfdab13c48c8747 | 2,223 | py | Python | squeezer/onnx/export.py | esceptico/squeezer | 98bc4c7923c6aa3b12ac81444d79392826fc34c6 | [
"MIT"
] | 29 | 2021-11-16T18:50:54.000Z | 2022-03-13T08:18:29.000Z | squeezer/onnx/export.py | esceptico/squeezer | 98bc4c7923c6aa3b12ac81444d79392826fc34c6 | [
"MIT"
] | null | null | null | squeezer/onnx/export.py | esceptico/squeezer | 98bc4c7923c6aa3b12ac81444d79392826fc34c6 | [
"MIT"
] | null | null | null | from logging import getLogger
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.onnx import export
logger = getLogger(__name__)
def export_to_onnx(
model: nn.Module,
dummy_input: [Union[Tuple], torch.Tensor],
file,
opset_version: int = 12,
input_names: Optional[List[str]] = None,
output_names: Optional[List[str]] = None,
dynamic_axes: Dict[str, Dict[int, str]] = None
) -> None:
"""Exports PyTorch model to ONNX format.
Args:
model: PyTorch module.
dummy_input: Dummy input.
file: Path to save converted model or file-like object.
opset_version: Version of ONNX operator set. Defaults to 12.
input_names: Names of model inputs. Defaults to None.
output_names: Names of model outputs. Defaults to None.
dynamic_axes: Axes (input or/and outputs) with dynamic shapes.
Defaults to None.
Examples:
>>> from transformers import AutoModel, AutoTokenizer
>>> tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
>>> model = AutoModel.from_pretrained('bert-base-uncased')
>>> encoded = tokenizer('aboba', return_tensors='np')
>>>
>>> export_to_onnx(
>>> model,
>>> dummy_input=tuple(encoded.values()),
>>> path_to_save='model.onnx',
>>> input_names=list(encoded.keys()),
>>> output_names=['last_hidden_state', 'pooler_output'],
>>> dynamic_axes={
>>> 'input_ids' : {0 : 'batch_size', 1: 'seq'},
>>> 'token_type_ids' : {0 : 'batch_size', 1: 'seq'},
>>> 'attention_mask' : {0 : 'batch_size', 1: 'seq'},
>>> 'last_hidden_state' : {0 : 'batch_size', 1: 'seq'},
>>> 'pooler_output' : {0 : 'batch_size', 1: 'seq'}
>>> }
>>> )
"""
model.eval()
export(
model,
dummy_input,
file,
opset_version=opset_version,
do_constant_folding=True,
input_names=input_names,
output_names=output_names,
dynamic_axes=dynamic_axes
)
logger.warning(f'Model was exported to ONNX.')
| 34.2 | 74 | 0.589744 | from logging import getLogger
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.onnx import export
logger = getLogger(__name__)
def export_to_onnx(
model: nn.Module,
dummy_input: [Union[Tuple], torch.Tensor],
file,
opset_version: int = 12,
input_names: Optional[List[str]] = None,
output_names: Optional[List[str]] = None,
dynamic_axes: Dict[str, Dict[int, str]] = None
) -> None:
model.eval()
export(
model,
dummy_input,
file,
opset_version=opset_version,
do_constant_folding=True,
input_names=input_names,
output_names=output_names,
dynamic_axes=dynamic_axes
)
logger.warning(f'Model was exported to ONNX.')
| true | true |
f7fe8aea28a782debcb6c52ead11ec2710fb20c0 | 23,189 | py | Python | nuitka/tools/specialize/__main__.py | lurid-bogey/Nuitka | 7eca8d66874e08f6d8472ad4e63255a08ad0c3c5 | [
"Apache-2.0"
] | null | null | null | nuitka/tools/specialize/__main__.py | lurid-bogey/Nuitka | 7eca8d66874e08f6d8472ad4e63255a08ad0c3c5 | [
"Apache-2.0"
] | null | null | null | nuitka/tools/specialize/__main__.py | lurid-bogey/Nuitka | 7eca8d66874e08f6d8472ad4e63255a08ad0c3c5 | [
"Apache-2.0"
] | null | null | null | # Copyright 2019, Kay Hayen, mailto:kay.hayen@gmail.com
#
# Part of "Nuitka", an optimizing Python compiler that is compatible and
# integrates with CPython, but also works on its own.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
""" This tool is generating code variants for helper codes from Jinja templates.
"""
from __future__ import print_function
import os
from abc import abstractmethod
import jinja2
import nuitka.codegen.OperationCodes
from nuitka.__past__ import getMetaClassBase
from nuitka.tools.quality.autoformat.Autoformat import autoformat
class TypeDescBase(getMetaClassBase("Type")):
# To be overloaded
type_name = None
type_desc = None
type_decl = None
python_requirement = None
def __init__(self):
assert self.type_name
assert self.type_desc
assert self.type_decl
def __repr__(self):
return "<%s %s %s>" % (self.__class__.__name__, self.type_name, self.type_desc)
@classmethod
def getHelperCodeName(cls):
return cls.type_name.upper()
@classmethod
def getTypeName2(cls):
return cls.type_name
@classmethod
def getTypeName3(cls):
return cls.type_name
@classmethod
def getVariableDecl(cls, variable_name):
if cls.type_decl.endswith("*"):
return cls.type_decl + variable_name
else:
return cls.type_decl + " " + variable_name
@classmethod
def getCheckValueCode(cls, operand):
return "CHECK_OBJECT(%s);" % operand
@classmethod
def getTypeValueExpression(cls, operand):
return "Py_TYPE(%s)" % operand
@abstractmethod
def getNewStyleNumberTypeCheckExpression(self, operand):
pass
@staticmethod
def needsIndexConversion():
return True
def canTypeCoerceObjects(self, left):
if left is self and left is not object_desc:
return "0"
# TODO: Provide hook for float to say it can do int.
return (
"1"
if self.getSlotValueCheckExpression("type2", "nb_coerce") != "false"
else "0"
)
@classmethod
def getIntCheckExpression(cls, operand):
if cls.type_name == "int":
return "1"
elif cls.type_name == "object":
return "PyInt_CheckExact(%s)" % operand
else:
return "0"
def getIndexCheckExpression(self, operand):
if self.hasSlot("nb_index"):
return "1"
elif self.type_name == "object":
return "PyIndex_Check(%s)" % operand
else:
return "0"
def getTypeIdenticalCheckExpression(self, other, operand1, operand2):
if self is object_desc or other is object_desc:
return "%s == %s" % (operand1, operand2)
elif self is other:
return "1"
else:
return "0"
@staticmethod
def getRealSubTypeCheckCode(right, operand2, operand1):
if right is object_desc:
return "PyType_IsSubtype(%s, %s)" % (operand2, operand1)
else:
return 0
def getSlotComparisonEqualExpression(self, right, operand1, operand2):
if right is object_desc or self is object_desc:
return "%s == %s" % (operand1, operand2)
else:
return "0"
@abstractmethod
def hasSlot(self, slot):
pass
def _getSlotValueExpression(self, operand, slot):
if slot.startswith("nb_"):
return "(%s) ? %s : NULL" % (
operand
+ "->tp_as_number != NULL && "
+ self.getNewStyleNumberTypeCheckExpression(operand),
operand + "->tp_as_number->" + slot,
)
elif slot.startswith("sq_"):
return "%s ? %s : NULL" % (
operand + "->tp_as_sequence" + " != NULL",
operand + "->tp_as_sequence->" + slot,
)
else:
assert False, slot
def getSlotValueExpression(self, operand, slot):
if not self.hasSlot(slot):
return "NULL"
return self._getSlotValueExpression(operand, slot)
def getSlotValueCheckExpression(self, operand, slot):
# Virtual method, pylint: disable=unused-argument
return "true" if self.hasSlot(slot) else "false"
def getRaiseUnsupportedTypeError(self, operation, other, operand1, operand2):
args = []
if self is object_desc:
args.append("%s->tp_name" % operand1)
if other is object_desc:
args.append("%s->tp_name" % operand2)
if args:
args = ", " + ", ".join(args)
else:
args = ""
if (
self.getTypeName2() != self.getTypeName3()
or other.getTypeName2() != other.getTypeName3()
):
return """\
#if PYTHON_VERSION < 300
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
#else
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
#endif
return NULL;""" % (
operation,
"%s" if self is object_desc else self.getTypeName2(),
"%s" if other is object_desc else other.getTypeName2(),
args,
operation,
"%s" if self is object_desc else self.getTypeName3(),
"%s" if other is object_desc else other.getTypeName3(),
args,
)
else:
return """\
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
return NULL;""" % (
operation,
"%s" if self is object_desc else self.getTypeName2(),
"%s" if other is object_desc else other.getTypeName2(),
args,
)
def getSameTypeSpecializationCode(
self, other, nb_slot, sq_slot, operand1, operand2
):
cand = self if self is not object_desc else other
if cand is object_desc:
return ""
# Special case for sequence concats/repeats.
if sq_slot is not None and not cand.hasSlot(nb_slot) and cand.hasSlot(sq_slot):
slot = sq_slot
else:
slot = nb_slot
if slot == "sq_repeat":
if cand in (list_desc, tuple_desc, unicode_desc, str_desc, bytes_desc):
return ""
return "return SLOT_%s_%s_%s(%s, %s);" % (
slot,
cand.getHelperCodeName(),
cand.getHelperCodeName(),
operand1,
operand2,
)
def getSimilarTypeSpecializationCode(self, other, nb_slot, operand1, operand2):
return "return SLOT_%s_%s_%s(%s, %s);" % (
nb_slot,
self.getHelperCodeName(),
other.getHelperCodeName(),
operand1,
operand2,
)
def getTypeSpecializationCode(self, other, nb_slot, sq_slot, operand1, operand2):
if self is object_desc or other is object_desc:
return ""
if self is other:
return self.getSameTypeSpecializationCode(
other, nb_slot, sq_slot, operand1, operand2
)
if other in related_types.get(self, ()):
return self.getSimilarTypeSpecializationCode(
other, nb_slot, operand1, operand2
)
return ""
@abstractmethod
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
pass
class ConcreteTypeBase(TypeDescBase):
type_decl = "PyObject *"
def _getSlotValueExpression(self, operand, slot):
if slot.startswith("nb_"):
return self.getTypeValueExpression(operand)[1:] + ".tp_as_number->" + slot
elif slot.startswith("sq_"):
return self.getTypeValueExpression(operand)[1:] + ".tp_as_sequence->" + slot
else:
assert False, slot
def getCheckValueCode(self, operand):
return """\
CHECK_OBJECT(%(operand)s);
assert(%(type_name)s_CheckExact(%(operand)s));
#if PYTHON_VERSION < 300
assert(%(is_newstyle)sNEW_STYLE_NUMBER(%(operand)s));
#endif""" % {
"operand": operand,
"type_name": self.getTypeValueExpression(operand)[1:].split("_")[0],
"is_newstyle": ""
if self.getNewStyleNumberTypeCheckExpression(operand) == "1"
else "!",
}
@abstractmethod
def getTypeValueExpression(self, operand):
pass
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
if not self.hasSlot(slot):
return ""
# TODO: Use second type eventually when we specialize those too.
return "return SLOT_%s_%s_%s(%s, %s);" % (
slot,
self.getHelperCodeName(),
other.getHelperCodeName(),
operand1,
operand2,
)
class IntDesc(ConcreteTypeBase):
type_name = "int"
type_desc = "Python2 'int'"
python_requirement = "PYTHON_VERSION < 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyInt_Type"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False
@staticmethod
def needsIndexConversion():
return False
@staticmethod
def getAsLongValueExpression(operand):
return "PyInt_AS_LONG(%s)" % operand
@staticmethod
def getAsObjectValueExpression(operand):
return operand
@staticmethod
def releaseAsObjectValueStatement(operand):
# Virtual method, pylint: disable=unused-argument
return ""
int_desc = IntDesc()
class StrDesc(ConcreteTypeBase):
type_name = "str"
type_desc = "Python2 'str'"
python_requirement = "PYTHON_VERSION < 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyString_Type"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
str_desc = StrDesc()
class UnicodeDesc(ConcreteTypeBase):
type_name = "UNICODE"
type_desc = "Python2 'unicode', Python3 'str'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyUnicode_Type"
@classmethod
def getCheckValueCode(cls, operand):
return """\
CHECK_OBJECT(%(operand)s);
assert(PyUnicode_CheckExact(%(operand)s));
assert(NEW_STYLE_NUMBER(%(operand)s));""" % {
"operand": operand
}
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
unicode_desc = UnicodeDesc()
class FloatDesc(ConcreteTypeBase):
type_name = "float"
type_desc = "Python 'float'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyFloat_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
float_desc = FloatDesc()
class TupleDesc(ConcreteTypeBase):
type_name = "tuple"
type_desc = "Python 'tuple'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyTuple_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return False
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
tuple_desc = TupleDesc()
class ListDesc(ConcreteTypeBase):
type_name = "list"
type_desc = "Python 'list'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyList_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return False
elif slot.startswith("sq_"):
return True
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
list_desc = ListDesc()
class BytesDesc(ConcreteTypeBase):
type_name = "bytes"
type_desc = "Python3 'bytes'"
python_requirement = "PYTHON_VERSION >= 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyBytes_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot and slot != "sq_slice"
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
bytes_desc = BytesDesc()
class LongDesc(ConcreteTypeBase):
type_name = "long"
type_desc = "Python2 'long', Python3 'int'"
@classmethod
def getTypeName3(cls):
return "int"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyLong_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
@staticmethod
def needsIndexConversion():
return False
long_desc = LongDesc()
class ObjectDesc(TypeDescBase):
type_name = "object"
type_desc = "any Python object"
type_decl = "PyObject *"
def hasSlot(self, slot):
# Don't want to get asked, we cannot know.
assert False
def getIndexCheckExpression(self, operand):
return "PyIndex_Check(%s)" % operand
def getNewStyleNumberTypeCheckExpression(self, operand):
return "NEW_STYLE_NUMBER_TYPE(%s)" % operand
def getSlotValueExpression(self, operand, slot):
# Always check.
return self._getSlotValueExpression(operand, slot)
def getSlotValueCheckExpression(self, operand, slot):
return "(%s) != NULL" % self._getSlotValueExpression(operand, slot)
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
return ""
object_desc = ObjectDesc()
class CLongDesc(TypeDescBase):
type_name = "clong"
type_desc = "C platform long value"
type_decl = "long"
@classmethod
def getCheckValueCode(cls, operand):
return ""
@classmethod
def getTypeValueExpression(cls, operand):
return "NULL"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
def hasSlot(self, slot):
return False
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
return ""
@staticmethod
def getAsLongValueExpression(operand):
return operand
@staticmethod
def getAsObjectValueExpression(operand):
return "PyLong_FromLong(%s)" % operand
@staticmethod
def releaseAsObjectValueStatement(operand):
return "Py_DECREF(%s);" % operand
clong_desc = CLongDesc()
related_types = {clong_desc: (int_desc,), int_desc: (clong_desc,)}
class AlternativeTypeBase(object):
# TODO: Base class for alternative types
pass
class AlternativeIntOrClong(AlternativeTypeBase):
# TODO: Base class for alternative type int or clong.
pass
env = jinja2.Environment(
loader=jinja2.PackageLoader("nuitka.tools.specialize", "templates"),
trim_blocks=True,
lstrip_blocks=True,
)
env.undefined = jinja2.StrictUndefined
types = (
int_desc,
str_desc,
unicode_desc,
float_desc,
tuple_desc,
list_desc,
bytes_desc,
long_desc,
clong_desc,
object_desc,
)
def findTypeFromCodeName(code_name):
for candidate in types:
if candidate.getHelperCodeName() == code_name:
return candidate
assert False, code_name
add_codes = set()
def makeNbSlotCode(operand, op_code, left, right, emit):
key = operand, op_code, left, right
if key in add_codes:
return
if left in (int_desc, clong_desc):
template = env.get_template("HelperOperationBinaryInt.c.j2")
elif left == long_desc:
template = env.get_template("HelperOperationBinaryLong.c.j2")
elif left == float_desc:
template = env.get_template("HelperOperationBinaryFloat.c.j2")
else:
return
code = template.render(
operand=operand,
left=left,
right=right,
nb_slot=_getNbSlotFromOperand(operand, op_code),
)
emit(code)
add_codes.add(key)
mul_repeats = set()
def makeMulRepeatCode(left, right, emit):
key = right, left
if key in mul_repeats:
return
template = env.get_template("HelperOperationMulRepeatSlot.c.j2")
code = template.render(left=left, right=right)
emit(code)
mul_repeats.add(key)
def _getNbSlotFromOperand(operand, op_code):
if operand == "+":
return "nb_add"
elif operand == "*":
return "nb_multiply"
elif operand == "-":
return "nb_subtract"
elif operand == "//":
return "nb_floor_divide"
elif operand == "/":
if op_code == "TRUEDIV":
return "nb_true_divide"
else:
return "nb_divide"
else:
assert False, operand
def makeHelperOperations(template, helpers_set, operand, op_code, emit_h, emit_c, emit):
# Complexity comes natural, pylint: disable=too-many-branches
emit(
'/* C helpers for type specialized "%s" (%s) operations */' % (operand, op_code)
)
emit()
for helper_name in helpers_set:
left = findTypeFromCodeName(helper_name.split("_")[3])
right = findTypeFromCodeName(helper_name.split("_")[4])
if left.python_requirement:
emit("#if %s" % left.python_requirement)
elif right.python_requirement:
emit("#if %s" % right.python_requirement)
nb_slot = _getNbSlotFromOperand(operand, op_code)
code = left.getSameTypeSpecializationCode(
right, nb_slot, None, "operand1", "operand2"
)
if code:
cand = left if left is not object_desc else right
makeNbSlotCode(operand, op_code, cand, cand, emit_c)
if left is not right and right in related_types.get(left, ()):
code = left.getSimilarTypeSpecializationCode(
right, nb_slot, "operand1", "operand2"
)
if code:
makeNbSlotCode(operand, op_code, left, right, emit_c)
if operand == "*":
repeat = left.getSqConcatSlotSpecializationCode(
right, "sq_repeat", "operand2", "operand1"
)
if repeat:
makeMulRepeatCode(left, right, emit_c)
repeat = right.getSqConcatSlotSpecializationCode(
left, "sq_repeat", "operand2", "operand1"
)
if repeat:
makeMulRepeatCode(right, left, emit_c)
emit(
'/* Code referring to "%s" corresponds to %s and "%s" to %s. */'
% (
left.getHelperCodeName(),
left.type_desc,
right.getHelperCodeName(),
right.type_desc,
)
)
if operand == "+":
sq_slot = "sq_concat"
elif operand == "*":
sq_slot = "sq_repeat"
else:
sq_slot = None
code = template.render(
left=left,
right=right,
op_code=op_code,
operand=operand,
nb_slot=_getNbSlotFromOperand(operand, op_code),
sq_slot1=sq_slot,
)
emit_c(code)
emit_h("extern " + code.splitlines()[0].replace(" {", ";"))
if left.python_requirement or right.python_requirement:
emit("#endif")
emit()
def makeHelpersBinaryOperation(operand, op_code):
specialized_op_helpers_set = getattr(
nuitka.codegen.OperationCodes, "specialized_%s_helpers_set" % op_code.lower()
)
template = env.get_template("HelperOperationBinary.c.j2")
filename_c = "nuitka/build/static_src/HelpersOperationBinary%s.c" % op_code.title()
filename_h = (
"nuitka/build/include/nuitka/helper/operations_binary_%s.h" % op_code.lower()
)
with open(filename_c, "w") as output_c:
with open(filename_h, "w") as output_h:
def emit_h(*args):
writeline(output_h, *args)
def emit_c(*args):
writeline(output_c, *args)
def emit(*args):
emit_h(*args)
emit_c(*args)
def emitGenerationWarning(emit):
emit(
"/* WARNING, this code is GENERATED. Modify the template %s instead! */"
% template.name
)
emitGenerationWarning(emit_h)
emitGenerationWarning(emit_c)
filename_utils = filename_c[:-2] + "Utils.c"
if os.path.exists(filename_utils):
emit_c('#include "%s"' % os.path.basename(filename_utils))
makeHelperOperations(
template,
specialized_op_helpers_set,
operand,
op_code,
emit_h,
emit_c,
emit,
)
autoformat(filename_c, None, True)
autoformat(filename_h, None, True)
def writeline(output, *args):
if not args:
output.write("\n")
elif len(args) == 1:
output.write(args[0] + "\n")
else:
assert False, args
def main():
makeHelpersBinaryOperation("+", "ADD")
makeHelpersBinaryOperation("-", "SUB")
makeHelpersBinaryOperation("*", "MUL")
makeHelpersBinaryOperation("//", "FLOORDIV")
makeHelpersBinaryOperation("/", "TRUEDIV")
makeHelpersBinaryOperation("/", "OLDDIV")
if __name__ == "__main__":
main()
| 26.59289 | 92 | 0.60201 |
from __future__ import print_function
import os
from abc import abstractmethod
import jinja2
import nuitka.codegen.OperationCodes
from nuitka.__past__ import getMetaClassBase
from nuitka.tools.quality.autoformat.Autoformat import autoformat
class TypeDescBase(getMetaClassBase("Type")):
type_name = None
type_desc = None
type_decl = None
python_requirement = None
def __init__(self):
assert self.type_name
assert self.type_desc
assert self.type_decl
def __repr__(self):
return "<%s %s %s>" % (self.__class__.__name__, self.type_name, self.type_desc)
@classmethod
def getHelperCodeName(cls):
return cls.type_name.upper()
@classmethod
def getTypeName2(cls):
return cls.type_name
@classmethod
def getTypeName3(cls):
return cls.type_name
@classmethod
def getVariableDecl(cls, variable_name):
if cls.type_decl.endswith("*"):
return cls.type_decl + variable_name
else:
return cls.type_decl + " " + variable_name
@classmethod
def getCheckValueCode(cls, operand):
return "CHECK_OBJECT(%s);" % operand
@classmethod
def getTypeValueExpression(cls, operand):
return "Py_TYPE(%s)" % operand
@abstractmethod
def getNewStyleNumberTypeCheckExpression(self, operand):
pass
@staticmethod
def needsIndexConversion():
return True
def canTypeCoerceObjects(self, left):
if left is self and left is not object_desc:
return "0"
return (
"1"
if self.getSlotValueCheckExpression("type2", "nb_coerce") != "false"
else "0"
)
@classmethod
def getIntCheckExpression(cls, operand):
if cls.type_name == "int":
return "1"
elif cls.type_name == "object":
return "PyInt_CheckExact(%s)" % operand
else:
return "0"
def getIndexCheckExpression(self, operand):
if self.hasSlot("nb_index"):
return "1"
elif self.type_name == "object":
return "PyIndex_Check(%s)" % operand
else:
return "0"
def getTypeIdenticalCheckExpression(self, other, operand1, operand2):
if self is object_desc or other is object_desc:
return "%s == %s" % (operand1, operand2)
elif self is other:
return "1"
else:
return "0"
@staticmethod
def getRealSubTypeCheckCode(right, operand2, operand1):
if right is object_desc:
return "PyType_IsSubtype(%s, %s)" % (operand2, operand1)
else:
return 0
def getSlotComparisonEqualExpression(self, right, operand1, operand2):
if right is object_desc or self is object_desc:
return "%s == %s" % (operand1, operand2)
else:
return "0"
@abstractmethod
def hasSlot(self, slot):
pass
def _getSlotValueExpression(self, operand, slot):
if slot.startswith("nb_"):
return "(%s) ? %s : NULL" % (
operand
+ "->tp_as_number != NULL && "
+ self.getNewStyleNumberTypeCheckExpression(operand),
operand + "->tp_as_number->" + slot,
)
elif slot.startswith("sq_"):
return "%s ? %s : NULL" % (
operand + "->tp_as_sequence" + " != NULL",
operand + "->tp_as_sequence->" + slot,
)
else:
assert False, slot
def getSlotValueExpression(self, operand, slot):
if not self.hasSlot(slot):
return "NULL"
return self._getSlotValueExpression(operand, slot)
def getSlotValueCheckExpression(self, operand, slot):
return "true" if self.hasSlot(slot) else "false"
def getRaiseUnsupportedTypeError(self, operation, other, operand1, operand2):
args = []
if self is object_desc:
args.append("%s->tp_name" % operand1)
if other is object_desc:
args.append("%s->tp_name" % operand2)
if args:
args = ", " + ", ".join(args)
else:
args = ""
if (
self.getTypeName2() != self.getTypeName3()
or other.getTypeName2() != other.getTypeName3()
):
return """\
#if PYTHON_VERSION < 300
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
#else
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
#endif
return NULL;""" % (
operation,
"%s" if self is object_desc else self.getTypeName2(),
"%s" if other is object_desc else other.getTypeName2(),
args,
operation,
"%s" if self is object_desc else self.getTypeName3(),
"%s" if other is object_desc else other.getTypeName3(),
args,
)
else:
return """\
PyErr_Format(PyExc_TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%s);
return NULL;""" % (
operation,
"%s" if self is object_desc else self.getTypeName2(),
"%s" if other is object_desc else other.getTypeName2(),
args,
)
def getSameTypeSpecializationCode(
self, other, nb_slot, sq_slot, operand1, operand2
):
cand = self if self is not object_desc else other
if cand is object_desc:
return ""
if sq_slot is not None and not cand.hasSlot(nb_slot) and cand.hasSlot(sq_slot):
slot = sq_slot
else:
slot = nb_slot
if slot == "sq_repeat":
if cand in (list_desc, tuple_desc, unicode_desc, str_desc, bytes_desc):
return ""
return "return SLOT_%s_%s_%s(%s, %s);" % (
slot,
cand.getHelperCodeName(),
cand.getHelperCodeName(),
operand1,
operand2,
)
def getSimilarTypeSpecializationCode(self, other, nb_slot, operand1, operand2):
return "return SLOT_%s_%s_%s(%s, %s);" % (
nb_slot,
self.getHelperCodeName(),
other.getHelperCodeName(),
operand1,
operand2,
)
def getTypeSpecializationCode(self, other, nb_slot, sq_slot, operand1, operand2):
if self is object_desc or other is object_desc:
return ""
if self is other:
return self.getSameTypeSpecializationCode(
other, nb_slot, sq_slot, operand1, operand2
)
if other in related_types.get(self, ()):
return self.getSimilarTypeSpecializationCode(
other, nb_slot, operand1, operand2
)
return ""
@abstractmethod
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
pass
class ConcreteTypeBase(TypeDescBase):
type_decl = "PyObject *"
def _getSlotValueExpression(self, operand, slot):
if slot.startswith("nb_"):
return self.getTypeValueExpression(operand)[1:] + ".tp_as_number->" + slot
elif slot.startswith("sq_"):
return self.getTypeValueExpression(operand)[1:] + ".tp_as_sequence->" + slot
else:
assert False, slot
def getCheckValueCode(self, operand):
return """\
CHECK_OBJECT(%(operand)s);
assert(%(type_name)s_CheckExact(%(operand)s));
#if PYTHON_VERSION < 300
assert(%(is_newstyle)sNEW_STYLE_NUMBER(%(operand)s));
#endif""" % {
"operand": operand,
"type_name": self.getTypeValueExpression(operand)[1:].split("_")[0],
"is_newstyle": ""
if self.getNewStyleNumberTypeCheckExpression(operand) == "1"
else "!",
}
@abstractmethod
def getTypeValueExpression(self, operand):
pass
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
if not self.hasSlot(slot):
return ""
return "return SLOT_%s_%s_%s(%s, %s);" % (
slot,
self.getHelperCodeName(),
other.getHelperCodeName(),
operand1,
operand2,
)
class IntDesc(ConcreteTypeBase):
type_name = "int"
type_desc = "Python2 'int'"
python_requirement = "PYTHON_VERSION < 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyInt_Type"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False
@staticmethod
def needsIndexConversion():
return False
@staticmethod
def getAsLongValueExpression(operand):
return "PyInt_AS_LONG(%s)" % operand
@staticmethod
def getAsObjectValueExpression(operand):
return operand
@staticmethod
def releaseAsObjectValueStatement(operand):
return ""
int_desc = IntDesc()
class StrDesc(ConcreteTypeBase):
type_name = "str"
type_desc = "Python2 'str'"
python_requirement = "PYTHON_VERSION < 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyString_Type"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
str_desc = StrDesc()
class UnicodeDesc(ConcreteTypeBase):
type_name = "UNICODE"
type_desc = "Python2 'unicode', Python3 'str'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyUnicode_Type"
@classmethod
def getCheckValueCode(cls, operand):
return """\
CHECK_OBJECT(%(operand)s);
assert(PyUnicode_CheckExact(%(operand)s));
assert(NEW_STYLE_NUMBER(%(operand)s));""" % {
"operand": operand
}
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
unicode_desc = UnicodeDesc()
class FloatDesc(ConcreteTypeBase):
type_name = "float"
type_desc = "Python 'float'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyFloat_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
float_desc = FloatDesc()
class TupleDesc(ConcreteTypeBase):
type_name = "tuple"
type_desc = "Python 'tuple'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyTuple_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return False
elif slot.startswith("sq_"):
return "ass" not in slot
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
tuple_desc = TupleDesc()
class ListDesc(ConcreteTypeBase):
type_name = "list"
type_desc = "Python 'list'"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyList_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return False
elif slot.startswith("sq_"):
return True
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
list_desc = ListDesc()
class BytesDesc(ConcreteTypeBase):
type_name = "bytes"
type_desc = "Python3 'bytes'"
python_requirement = "PYTHON_VERSION >= 300"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyBytes_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return "slot" == "nb_remainder"
elif slot.startswith("sq_"):
return "ass" not in slot and slot != "sq_slice"
else:
assert False, slot
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
bytes_desc = BytesDesc()
class LongDesc(ConcreteTypeBase):
type_name = "long"
type_desc = "Python2 'long', Python3 'int'"
@classmethod
def getTypeName3(cls):
return "int"
@classmethod
def getTypeValueExpression(cls, operand):
return "&PyLong_Type"
def hasSlot(self, slot):
if slot.startswith("nb_"):
return True
elif slot.startswith("sq_"):
return False
else:
assert False
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "1"
@staticmethod
def needsIndexConversion():
return False
long_desc = LongDesc()
class ObjectDesc(TypeDescBase):
type_name = "object"
type_desc = "any Python object"
type_decl = "PyObject *"
def hasSlot(self, slot):
assert False
def getIndexCheckExpression(self, operand):
return "PyIndex_Check(%s)" % operand
def getNewStyleNumberTypeCheckExpression(self, operand):
return "NEW_STYLE_NUMBER_TYPE(%s)" % operand
def getSlotValueExpression(self, operand, slot):
# Always check.
return self._getSlotValueExpression(operand, slot)
def getSlotValueCheckExpression(self, operand, slot):
return "(%s) != NULL" % self._getSlotValueExpression(operand, slot)
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
return ""
object_desc = ObjectDesc()
class CLongDesc(TypeDescBase):
type_name = "clong"
type_desc = "C platform long value"
type_decl = "long"
@classmethod
def getCheckValueCode(cls, operand):
return ""
@classmethod
def getTypeValueExpression(cls, operand):
return "NULL"
@classmethod
def getNewStyleNumberTypeCheckExpression(cls, operand):
return "0"
def hasSlot(self, slot):
return False
def getSqConcatSlotSpecializationCode(self, other, slot, operand1, operand2):
return ""
@staticmethod
def getAsLongValueExpression(operand):
return operand
@staticmethod
def getAsObjectValueExpression(operand):
return "PyLong_FromLong(%s)" % operand
@staticmethod
def releaseAsObjectValueStatement(operand):
return "Py_DECREF(%s);" % operand
clong_desc = CLongDesc()
related_types = {clong_desc: (int_desc,), int_desc: (clong_desc,)}
class AlternativeTypeBase(object):
# TODO: Base class for alternative types
pass
class AlternativeIntOrClong(AlternativeTypeBase):
# TODO: Base class for alternative type int or clong.
pass
env = jinja2.Environment(
loader=jinja2.PackageLoader("nuitka.tools.specialize", "templates"),
trim_blocks=True,
lstrip_blocks=True,
)
env.undefined = jinja2.StrictUndefined
types = (
int_desc,
str_desc,
unicode_desc,
float_desc,
tuple_desc,
list_desc,
bytes_desc,
long_desc,
clong_desc,
object_desc,
)
def findTypeFromCodeName(code_name):
for candidate in types:
if candidate.getHelperCodeName() == code_name:
return candidate
assert False, code_name
add_codes = set()
def makeNbSlotCode(operand, op_code, left, right, emit):
key = operand, op_code, left, right
if key in add_codes:
return
if left in (int_desc, clong_desc):
template = env.get_template("HelperOperationBinaryInt.c.j2")
elif left == long_desc:
template = env.get_template("HelperOperationBinaryLong.c.j2")
elif left == float_desc:
template = env.get_template("HelperOperationBinaryFloat.c.j2")
else:
return
code = template.render(
operand=operand,
left=left,
right=right,
nb_slot=_getNbSlotFromOperand(operand, op_code),
)
emit(code)
add_codes.add(key)
mul_repeats = set()
def makeMulRepeatCode(left, right, emit):
key = right, left
if key in mul_repeats:
return
template = env.get_template("HelperOperationMulRepeatSlot.c.j2")
code = template.render(left=left, right=right)
emit(code)
mul_repeats.add(key)
def _getNbSlotFromOperand(operand, op_code):
if operand == "+":
return "nb_add"
elif operand == "*":
return "nb_multiply"
elif operand == "-":
return "nb_subtract"
elif operand == "//":
return "nb_floor_divide"
elif operand == "/":
if op_code == "TRUEDIV":
return "nb_true_divide"
else:
return "nb_divide"
else:
assert False, operand
def makeHelperOperations(template, helpers_set, operand, op_code, emit_h, emit_c, emit):
# Complexity comes natural, pylint: disable=too-many-branches
emit(
'/* C helpers for type specialized "%s" (%s) operations */' % (operand, op_code)
)
emit()
for helper_name in helpers_set:
left = findTypeFromCodeName(helper_name.split("_")[3])
right = findTypeFromCodeName(helper_name.split("_")[4])
if left.python_requirement:
emit("#if %s" % left.python_requirement)
elif right.python_requirement:
emit("#if %s" % right.python_requirement)
nb_slot = _getNbSlotFromOperand(operand, op_code)
code = left.getSameTypeSpecializationCode(
right, nb_slot, None, "operand1", "operand2"
)
if code:
cand = left if left is not object_desc else right
makeNbSlotCode(operand, op_code, cand, cand, emit_c)
if left is not right and right in related_types.get(left, ()):
code = left.getSimilarTypeSpecializationCode(
right, nb_slot, "operand1", "operand2"
)
if code:
makeNbSlotCode(operand, op_code, left, right, emit_c)
if operand == "*":
repeat = left.getSqConcatSlotSpecializationCode(
right, "sq_repeat", "operand2", "operand1"
)
if repeat:
makeMulRepeatCode(left, right, emit_c)
repeat = right.getSqConcatSlotSpecializationCode(
left, "sq_repeat", "operand2", "operand1"
)
if repeat:
makeMulRepeatCode(right, left, emit_c)
emit(
'/* Code referring to "%s" corresponds to %s and "%s" to %s. */'
% (
left.getHelperCodeName(),
left.type_desc,
right.getHelperCodeName(),
right.type_desc,
)
)
if operand == "+":
sq_slot = "sq_concat"
elif operand == "*":
sq_slot = "sq_repeat"
else:
sq_slot = None
code = template.render(
left=left,
right=right,
op_code=op_code,
operand=operand,
nb_slot=_getNbSlotFromOperand(operand, op_code),
sq_slot1=sq_slot,
)
emit_c(code)
emit_h("extern " + code.splitlines()[0].replace(" {", ";"))
if left.python_requirement or right.python_requirement:
emit("#endif")
emit()
def makeHelpersBinaryOperation(operand, op_code):
specialized_op_helpers_set = getattr(
nuitka.codegen.OperationCodes, "specialized_%s_helpers_set" % op_code.lower()
)
template = env.get_template("HelperOperationBinary.c.j2")
filename_c = "nuitka/build/static_src/HelpersOperationBinary%s.c" % op_code.title()
filename_h = (
"nuitka/build/include/nuitka/helper/operations_binary_%s.h" % op_code.lower()
)
with open(filename_c, "w") as output_c:
with open(filename_h, "w") as output_h:
def emit_h(*args):
writeline(output_h, *args)
def emit_c(*args):
writeline(output_c, *args)
def emit(*args):
emit_h(*args)
emit_c(*args)
def emitGenerationWarning(emit):
emit(
"/* WARNING, this code is GENERATED. Modify the template %s instead! */"
% template.name
)
emitGenerationWarning(emit_h)
emitGenerationWarning(emit_c)
filename_utils = filename_c[:-2] + "Utils.c"
if os.path.exists(filename_utils):
emit_c('
makeHelperOperations(
template,
specialized_op_helpers_set,
operand,
op_code,
emit_h,
emit_c,
emit,
)
autoformat(filename_c, None, True)
autoformat(filename_h, None, True)
def writeline(output, *args):
if not args:
output.write("\n")
elif len(args) == 1:
output.write(args[0] + "\n")
else:
assert False, args
def main():
makeHelpersBinaryOperation("+", "ADD")
makeHelpersBinaryOperation("-", "SUB")
makeHelpersBinaryOperation("*", "MUL")
makeHelpersBinaryOperation("//", "FLOORDIV")
makeHelpersBinaryOperation("/", "TRUEDIV")
makeHelpersBinaryOperation("/", "OLDDIV")
if __name__ == "__main__":
main()
| true | true |
f7fe8b1e75fed505e11af640bc149b84a1c652b2 | 47,069 | py | Python | mytardis_ngs_ingestor/illumina/models.py | mytardis/mytardis_ngs_ingestor | 5232c688574c8e6cd9a50951c37cd878a09feba3 | [
"BSD-3-Clause"
] | 1 | 2020-11-19T19:10:20.000Z | 2020-11-19T19:10:20.000Z | mytardis_ngs_ingestor/illumina/models.py | mytardis/mytardis_ngs_ingestor | 5232c688574c8e6cd9a50951c37cd878a09feba3 | [
"BSD-3-Clause"
] | 3 | 2017-10-02T03:48:03.000Z | 2020-03-12T23:52:47.000Z | mytardis_ngs_ingestor/illumina/models.py | mytardis/mytardis_ngs_ingestor | 5232c688574c8e6cd9a50951c37cd878a09feba3 | [
"BSD-3-Clause"
] | null | null | null | # Data model generated from ../fixtures/sequencing_facility_schema.json
from mytardis_ngs_ingestor.mytardis_models import MyTardisParameterSet
class IlluminaSequencingRunBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type run_number: float
:type flowcell_id: unicode
:type instrument_id: unicode
:type instrument_model: unicode
:type read_cycles: unicode
:type chemistry: unicode
:type operator_name: unicode
:type rta_version: unicode
:type ingestor_useragent: unicode
:type demultiplexing_program: unicode
:type demultiplexing_commandline_options: unicode
"""
def __init__(self):
super(IlluminaSequencingRunBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Run number
self.run_number = None # type: float
# Flowcell ID
self.flowcell_id = None # type: unicode
# Instrument ID
self.instrument_id = None # type: unicode
# Instrument model
self.instrument_model = None # type: unicode
# Number of cycles in each read [index reads in (brackets)]
self.read_cycles = None # type: unicode
# Terminator chemistry
self.chemistry = None # type: unicode
# Instrument operator
self.operator_name = None # type: unicode
# Illumina RTA version
self.rta_version = None # type: unicode
# Ingestor User Agent
self.ingestor_useragent = None # type: unicode
# Demultiplexing program version
self.demultiplexing_program = None # type: unicode
# Demultiplexing program commandline options
self.demultiplexing_commandline_options = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# run_number fixture
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# flowcell_id fixture
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# instrument_id fixture
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# instrument_model fixture
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# read_cycles fixture
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of'
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# chemistry fixture
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator '
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# operator_name fixture
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# rta_version fixture
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
# ingestor_useragent fixture
self._ingestor_useragent__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields': {u'name': u'ingestor_useragent',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Ingestor User Agent', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}} # type: dict
self._demultiplexing_program__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_program',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing program version', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}
} # type: dict
self._demultiplexing_commandline_options__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_commandline_options',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing commandline options', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}
} # type: dict
self._subtype__schema = "illumina-sequencing-run" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Illumina Sequencing Run" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 1 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina" # type: unicode
self._immutable__schema = True # type: bool
class DemultiplexedSamplesBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type project_id: unicode
:type run_experiment: unicode
:type run_number: float
:type flowcell_id: unicode
:type instrument_id: unicode
:type instrument_model: unicode
:type read_cycles: unicode
:type chemistry: unicode
:type operator_name: unicode
:type rta_version: unicode
:type ingestor_useragent: unicode
:type demultiplexing_program: unicode
:type demultiplexing_commandline_options: unicode
"""
def __init__(self):
super(DemultiplexedSamplesBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Project ID
self.project_id = None # type: unicode
# Run Experiment link
self.run_experiment = None # type: unicode
# Run number
self.run_number = None # type: float
# Flowcell ID
self.flowcell_id = None # type: unicode
# Instrument ID
self.instrument_id = None # type: unicode
# Instrument model
self.instrument_model = None # type: unicode
# Number of cycles in each read [index reads in (brackets)]
self.read_cycles = None # type: unicode
# Terminator chemistry
self.chemistry = None # type: unicode
# Instrument operator
self.operator_name = None # type: unicode
# Illumina RTA version
self.rta_version = None # type: unicode
# Ingestor User Agent
self.ingestor_useragent = None # type: unicode
# Demultiplexing program version
self.demultiplexing_program = None # type: unicode
# Demultiplexing program commandline options
self.demultiplexing_commandline_options = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# project_id fixture
self._project_id__attr_schema = {
u'pk': None,
u'model': u'tardis_portal.parametername',
u'fields': {
u'name': u'project_id',
u'data_type': 2,
u'is_searchable': True,
u'choices': u'',
u'comparison_type': 1,
u'full_name': u'Project ID',
u'units': u'',
u'order': 9999,
u'immutable': True,
u'schema': [
u'http://www.tardis.edu.au/schemas/ngs/project'
]
}
} # type: dict
# run_experiment fixture
self._run_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run Experiment link', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# run_number fixture
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# flowcell_id fixture
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# instrument_id fixture
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# instrument_model fixture
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# read_cycles fixture
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of '
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# chemistry fixture
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator'
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# operator_name fixture
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# rta_version fixture
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
# ingestor_useragent fixture
self._ingestor_useragent__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields': {u'name': u'ingestor_useragent',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Ingestor User Agent', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}} # type: dict
self._demultiplexing_program__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_program',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing program version', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}
} # type: dict
self._demultiplexing_commandline_options__attr_schema = {
u'pk': None, u'model': u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_commandline_options',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing commandline options',
u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}
} # type: dict
self._subtype__schema = "demultiplexed-samples" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Sequencing Project (Demultiplexed Sample Set)" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 1 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project" # type: unicode
self._immutable__schema = True # type: bool
class NucleotideRawReadsDatasetBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type project_experiment: unicode
:type run_experiment: unicode
:type fastqc_dataset: unicode
:type run_number: float
:type flowcell_id: unicode
:type instrument_id: unicode
:type instrument_model: unicode
:type read_cycles: unicode
:type chemistry: unicode
:type operator_name: unicode
:type rta_version: unicode
"""
def __init__(self):
super(NucleotideRawReadsDatasetBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Project Experiment link
self.project_experiment = None # type: unicode
# Run Experiment link
self.run_experiment = None # type: unicode
# Associated FastQC reports
self.fastqc_dataset = None # type: unicode
# Run number
self.run_number = None # type: float
# Flowcell ID
self.flowcell_id = None # type: unicode
# Instrument ID
self.instrument_id = None # type: unicode
# Instrument model
self.instrument_model = None # type: unicode
# Number of cycles in each read [index reads in (brackets)]
self.read_cycles = None # type: unicode
# Terminator chemistry
self.chemistry = None # type: unicode
# Instrument operator
self.operator_name = None # type: unicode
# Illumina RTA version
self.rta_version = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# project_experiment fixture
self._project_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'project_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Project Experiment link', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# run_experiment fixture
self._run_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run Experiment link', u'units': u'', u'order': 9999,
u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# fastqc_dataset fixture
self._fastqc_dataset__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_dataset', u'data_type': 4, u'immutable': False,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Associated FastQC reports', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# run_number fixture
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# flowcell_id fixture
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# instrument_id fixture
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# instrument_model fixture
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# read_cycles fixture
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of'
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# chemistry fixture
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator'
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# operator_name fixture
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
# rta_version fixture
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}} # type: dict
self._subtype__schema = "nucleotide-raw-reads-dataset" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Nucleotide Sequencing Project Raw Reads" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 2 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/raw_reads" # type: unicode
self._immutable__schema = True # type: bool
class FastqcReportsBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type project: unicode
:type raw_reads_dataset: unicode
:type fastqc_version: unicode
"""
def __init__(self):
super(FastqcReportsBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Project name
self.project = None # type: unicode
# Raw reads project link
self.raw_reads_dataset = None # type: unicode
# FastQC software version
self.fastqc_version = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}} # type: dict
# project fixture
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}} # type: dict
# raw_reads_dataset fixture
self._raw_reads_dataset__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'raw_reads_dataset', u'data_type': 4, u'immutable': False,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Raw reads project link', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}} # type: dict
# fastqc_version fixture
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}} # type: dict
self._subtype__schema = "fastqc-reports" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "FastQC Reports" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 2 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/fastqc" # type: unicode
self._immutable__schema = True # type: bool
class HiddenFastqcProjectSummaryBase(MyTardisParameterSet):
"""
:type hidden_fastqc_summary_json: dict
:type fastqc_version: unicode
"""
def __init__(self):
super(HiddenFastqcProjectSummaryBase, self).__init__()
# (Hidden) FastQC summary for all samples (JSON)
self.hidden_fastqc_summary_json = None # type: dict
# FastQC software version
self.fastqc_version = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# hidden_fastqc_summary_json fixture
self._hidden_fastqc_summary_json__attr_schema = {u'pk': None,
u'model': u'tardis_portal.parametername', u'fields': {u'name':
u'hidden_fastqc_summary_json', u'data_type': 8, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'(Hidden) FastQC summary for all samples (JSON)',
u'units': u'fastqc-summary-table', u'order': 9999, u'schema': [u'http:'
u'//www.tardis.edu.au/schemas/ngs/project/hidden_fastqc_summary']}} # type: dict
# fastqc_version fixture
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project/__hid'
u'den__fastqc_summary']}} # type: dict
self._subtype__schema = "hidden-fastqc-project-summary" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "FastQC Project Summary" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 2 # type: int
self._hidden__schema = True # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/hidden_fastqc_summary" # type: unicode
self._immutable__schema = True # type: bool
class FastqRawReadsBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type sample_id: unicode
:type reference_genome: unicode
:type index_sequence: unicode
:type is_control: unicode
:type recipe: unicode
:type operator_name: unicode
:type description: unicode
:type project: unicode
:type number_of_reads: float
:type number_of_poor_quality_reads: float
:type read_length: float
"""
def __init__(self):
super(FastqRawReadsBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Sample ID
self.sample_id = None # type: unicode
# Sample name
self.sample_name = None # type: unicode
# Lane
self.lane = None # type: int
# Read number
self.read = None # type: int
# Reference genome
self.reference_genome = None # type: unicode
# Index sequence (barcode) for this sample
self.index_sequence = None # type: unicode
# Is control ?
self.is_control = None # type: unicode
# Recipe
self.recipe = None # type: unicode
# Instrument Operator
self.operator_name = None # type: unicode
# Description
self.description = None # type: unicode
# Project name
self.project = None # type: unicode
# Number of reads
self.number_of_reads = None # type: float
# Number of reads flagged as poor quality (FastQC)
self.number_of_poor_quality_reads = None # type: float
# Read length
self.read_length = None # type: float
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# sample_id fixture
self._sample_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_id',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# sample_name fixture
self._sample_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# lane fixture
self._lane__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'lane', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Lane', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
# read fixture
self._read__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'read', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Read number', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
# reference_genome fixture
self._reference_genome__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'reference_genome', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Reference genome', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# index_sequence fixture
self._index_sequence__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'index_sequence', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Index sequence (barcode) for this sample', u'units':
u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# is_control fixture
self._is_control__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'is_control',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Is control ?',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# recipe fixture
self._recipe__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'recipe',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Recipe',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# operator_name fixture
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'Operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# description fixture
self._description__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'description',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Description',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# project fixture
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# number_of_reads fixture
self._number_of_reads__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'number_of_reads', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Number of reads', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# number_of_poor_quality_reads fixture
self._number_of_poor_quality_reads__attr_schema = {u'pk': None,
u'model': u'tardis_portal.parametername', u'fields': {u'name':
u'number_of_poor_quality_reads', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Number of reads flagged as poor quality (FastQC)',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
# read_length fixture
self._read_length__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_length',
u'data_type': 1, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Read length',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}} # type: dict
self._subtype__schema = "fastq-raw-reads" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Nucleotide Sequence Raw Reads (FASTQ)" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 3 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/file/fastq" # type: unicode
self._immutable__schema = True # type: bool
class FastqcOutputBase(MyTardisParameterSet):
"""
:type run_id: unicode
:type sample_id: unicode
:type project: unicode
:type fastqc_version: unicode
"""
def __init__(self):
super(FastqcOutputBase, self).__init__()
# Run Unique ID
self.run_id = None # type: unicode
# Sample ID
self.sample_id = None # type: unicode
# Project name
self.project = None # type: unicode
# FastQC software version
self.fastqc_version = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# run_id fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}} # type: dict
# sample_id fixture
self._sample_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_id',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}} # type: dict
# project fixture
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}} # type: dict
# fastqc_version fixture
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}} # type: dict
self._subtype__schema = "fastqc-output" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "FastQC report" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 3 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/file/fastqc" # type: unicode
self._immutable__schema = True # type: bool
class IlluminaRunConfigBase(MyTardisParameterSet):
"""
:type run_id: unicode
"""
def __init__(self):
super(IlluminaRunConfigBase, self).__init__()
# the run ID
self.run_id = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# fastqc_version fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/config']}} # type: dict
self._subtype__schema = "illumina-run-config" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Illumia run config and log files" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 2 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina/config" # type: unicode
self._immutable__schema = True # type: bool
class IlluminaRunInstrumentFilesBase(MyTardisParameterSet):
"""
:type run_id: unicode
"""
def __init__(self):
super(IlluminaRunInstrumentFilesBase, self).__init__()
# the run ID
self.run_id = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# fastqc_version fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/files']}} # type: dict
self._subtype__schema = "illumina-run-instrument-files" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Illumia run instrument files" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 2 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina/files" # type: unicode
self._immutable__schema = True # type: bool
class IlluminaRunInstrumentFileBase(MyTardisParameterSet):
"""
:type run_id: unicode
"""
def __init__(self):
super(IlluminaRunInstrumentFileBase, self).__init__()
# the run ID
self.run_id = None # type: unicode
# Dictionaries to allow reconstitution of the schema for each parameter
# fastqc_version fixture
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/files']}} # type: dict
self._subtype__schema = "illumina-run-instrument-file" # type: unicode
self._model__schema = "tardis_portal.schema" # type: unicode
self._name__schema = "Illumina instrument run file" # type: unicode
self._pk__schema = None # type: NoneType
self._type__schema = 3 # type: int
self._hidden__schema = False # type: bool
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/file" # type: unicode
self._immutable__schema = True # type: bool
| 44.615166 | 119 | 0.608362 |
from mytardis_ngs_ingestor.mytardis_models import MyTardisParameterSet
class IlluminaSequencingRunBase(MyTardisParameterSet):
def __init__(self):
super(IlluminaSequencingRunBase, self).__init__()
self.run_id = None
self.run_number = None
self.flowcell_id = None
self.instrument_id = None
self.instrument_model = None
self.read_cycles = None
self.chemistry = None
self.operator_name = None
self.rta_version = None
self.ingestor_useragent = None
self.demultiplexing_program = None
self.demultiplexing_commandline_options = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of'
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator '
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._ingestor_useragent__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields': {u'name': u'ingestor_useragent',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Ingestor User Agent', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}}
self._demultiplexing_program__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_program',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing program version', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}
}
self._demultiplexing_commandline_options__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_commandline_options',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing commandline options', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina']}
}
self._subtype__schema = "illumina-sequencing-run"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Illumina Sequencing Run"
self._pk__schema = None
self._type__schema = 1
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina"
self._immutable__schema = True
class DemultiplexedSamplesBase(MyTardisParameterSet):
def __init__(self):
super(DemultiplexedSamplesBase, self).__init__()
self.run_id = None
self.project_id = None
self.run_experiment = None
self.run_number = None
self.flowcell_id = None
self.instrument_id = None
self.instrument_model = None
self.read_cycles = None
self.chemistry = None
self.operator_name = None
self.rta_version = None
self.ingestor_useragent = None
self.demultiplexing_program = None
self.demultiplexing_commandline_options = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._project_id__attr_schema = {
u'pk': None,
u'model': u'tardis_portal.parametername',
u'fields': {
u'name': u'project_id',
u'data_type': 2,
u'is_searchable': True,
u'choices': u'',
u'comparison_type': 1,
u'full_name': u'Project ID',
u'units': u'',
u'order': 9999,
u'immutable': True,
u'schema': [
u'http://www.tardis.edu.au/schemas/ngs/project'
]
}
}
self._run_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run Experiment link', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of '
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator'
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._ingestor_useragent__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields': {u'name': u'ingestor_useragent',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Ingestor User Agent', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}}
self._demultiplexing_program__attr_schema = {
u'pk': None, u'model':
u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_program',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing program version', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}
}
self._demultiplexing_commandline_options__attr_schema = {
u'pk': None, u'model': u'tardis_portal.parametername',
u'fields':
{u'name': u'demultiplexing_commandline_options',
u'data_type': 2, u'immutable': True,
u'is_searchable': False,
u'choices': u'', u'comparison_type': 1,
u'full_name': u'Demultiplexing commandline options',
u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project']}
}
self._subtype__schema = "demultiplexed-samples"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Sequencing Project (Demultiplexed Sample Set)"
self._pk__schema = None
self._type__schema = 1
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project"
self._immutable__schema = True
class NucleotideRawReadsDatasetBase(MyTardisParameterSet):
def __init__(self):
super(NucleotideRawReadsDatasetBase, self).__init__()
self.run_id = None
self.project_experiment = None
self.run_experiment = None
self.fastqc_dataset = None
self.run_number = None
self.flowcell_id = None
self.instrument_id = None
self.instrument_model = None
self.read_cycles = None
self.chemistry = None
self.operator_name = None
self.rta_version = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._project_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'project_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Project Experiment link', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._run_experiment__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_experiment', u'data_type': 4, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run Experiment link', u'units': u'', u'order': 9999,
u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._fastqc_dataset__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_dataset', u'data_type': 4, u'immutable': False,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Associated FastQC reports', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._run_number__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_number',
u'data_type': 1, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run number',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._flowcell_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'flowcell_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Flowcell ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._instrument_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'instrument_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._instrument_model__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'instrument_model', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Instrument model', u'units': u'', u'order': 9999,
u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._read_cycles__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_cycles',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Number of'
u'cycles in each read [index reads in (brackets)]', u'units': u'',
u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._chemistry__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'chemistry',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Terminator'
u'chemistry', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._rta_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'rta_version',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Illumina RTA '
u'version', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/raw_reads']}}
self._subtype__schema = "nucleotide-raw-reads-dataset"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Nucleotide Sequencing Project Raw Reads"
self._pk__schema = None
self._type__schema = 2
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/raw_reads"
self._immutable__schema = True
class FastqcReportsBase(MyTardisParameterSet):
def __init__(self):
super(FastqcReportsBase, self).__init__()
self.run_id = None
self.project = None
self.raw_reads_dataset = None
self.fastqc_version = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}}
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}}
self._raw_reads_dataset__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'raw_reads_dataset', u'data_type': 4, u'immutable': False,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Raw reads project link', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}}
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/project/fastqc']}}
self._subtype__schema = "fastqc-reports"
self._model__schema = "tardis_portal.schema"
self._name__schema = "FastQC Reports"
self._pk__schema = None
self._type__schema = 2
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/fastqc"
self._immutable__schema = True
class HiddenFastqcProjectSummaryBase(MyTardisParameterSet):
def __init__(self):
super(HiddenFastqcProjectSummaryBase, self).__init__()
self.hidden_fastqc_summary_json = None
self.fastqc_version = None
self._hidden_fastqc_summary_json__attr_schema = {u'pk': None,
u'model': u'tardis_portal.parametername', u'fields': {u'name':
u'hidden_fastqc_summary_json', u'data_type': 8, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'(Hidden) FastQC summary for all samples (JSON)',
u'units': u'fastqc-summary-table', u'order': 9999, u'schema': [u'http:'
u'//www.tardis.edu.au/schemas/ngs/project/hidden_fastqc_summary']}}
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema': [u'http://www.tardis.edu.au/schemas/ngs/project/__hid'
u'den__fastqc_summary']}}
self._subtype__schema = "hidden-fastqc-project-summary"
self._model__schema = "tardis_portal.schema"
self._name__schema = "FastQC Project Summary"
self._pk__schema = None
self._type__schema = 2
self._hidden__schema = True
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/project/hidden_fastqc_summary"
self._immutable__schema = True
class FastqRawReadsBase(MyTardisParameterSet):
def __init__(self):
super(FastqRawReadsBase, self).__init__()
self.run_id = None
self.sample_id = None
self.sample_name = None
self.lane = None
self.read = None
self.reference_genome = None
self.index_sequence = None
self.is_control = None
self.recipe = None
self.operator_name = None
self.description = None
self.project = None
self.number_of_reads = None
self.number_of_poor_quality_reads = None
self.read_length = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._sample_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_id',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._sample_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._lane__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'lane', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Lane', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._read__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'read', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Read number', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._reference_genome__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'reference_genome', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Reference genome', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._index_sequence__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'index_sequence', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Index sequence (barcode) for this sample', u'units':
u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._is_control__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'is_control',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Is control ?',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._recipe__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'recipe',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Recipe',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._operator_name__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'operator_name',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Instrument '
u'Operator', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._description__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'description',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Description',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._number_of_reads__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'number_of_reads', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Number of reads', u'units': u'', u'order': 9999,
u'schema': [u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._number_of_poor_quality_reads__attr_schema = {u'pk': None,
u'model': u'tardis_portal.parametername', u'fields': {u'name':
u'number_of_poor_quality_reads', u'data_type': 1, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Number of reads flagged as poor quality (FastQC)',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._read_length__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'read_length',
u'data_type': 1, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Read length',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastq']}}
self._subtype__schema = "fastq-raw-reads"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Nucleotide Sequence Raw Reads (FASTQ)"
self._pk__schema = None
self._type__schema = 3
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/file/fastq"
self._immutable__schema = True
class FastqcOutputBase(MyTardisParameterSet):
def __init__(self):
super(FastqcOutputBase, self).__init__()
self.run_id = None
self.sample_id = None
self.project = None
self.fastqc_version = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'run_id',
u'data_type': 2, u'immutable': True, u'is_searchable': True,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Run Unique '
u'ID', u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}}
self._sample_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'sample_id',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Sample ID',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}}
self._project__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name': u'project',
u'data_type': 2, u'immutable': True, u'is_searchable': False,
u'choices': u'', u'comparison_type': 1, u'full_name': u'Project name',
u'units': u'', u'order': 9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}}
self._fastqc_version__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'fastqc_version', u'data_type': 2, u'immutable': True,
u'is_searchable': False, u'choices': u'', u'comparison_type': 1,
u'full_name': u'FastQC software version', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/file/fastqc']}}
self._subtype__schema = "fastqc-output"
self._model__schema = "tardis_portal.schema"
self._name__schema = "FastQC report"
self._pk__schema = None
self._type__schema = 3
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/file/fastqc"
self._immutable__schema = True
class IlluminaRunConfigBase(MyTardisParameterSet):
def __init__(self):
super(IlluminaRunConfigBase, self).__init__()
self.run_id = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/config']}}
self._subtype__schema = "illumina-run-config"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Illumia run config and log files"
self._pk__schema = None
self._type__schema = 2
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina/config"
self._immutable__schema = True
class IlluminaRunInstrumentFilesBase(MyTardisParameterSet):
def __init__(self):
super(IlluminaRunInstrumentFilesBase, self).__init__()
self.run_id = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/files']}}
self._subtype__schema = "illumina-run-instrument-files"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Illumia run instrument files"
self._pk__schema = None
self._type__schema = 2
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/illumina/files"
self._immutable__schema = True
class IlluminaRunInstrumentFileBase(MyTardisParameterSet):
def __init__(self):
super(IlluminaRunInstrumentFileBase, self).__init__()
self.run_id = None
self._run_id__attr_schema = {u'pk': None, u'model':
u'tardis_portal.parametername', u'fields': {u'name':
u'run_id', u'data_type': 2, u'immutable': True,
u'is_searchable': True, u'choices': u'', u'comparison_type': 1,
u'full_name': u'Run ID', u'units': u'', u'order':
9999, u'schema':
[u'http://www.tardis.edu.au/schemas/ngs/run/illumina/files']}}
self._subtype__schema = "illumina-run-instrument-file"
self._model__schema = "tardis_portal.schema"
self._name__schema = "Illumina instrument run file"
self._pk__schema = None
self._type__schema = 3
self._hidden__schema = False
self._namespace__schema = "http://www.tardis.edu.au/schemas/ngs/run/file"
self._immutable__schema = True
| true | true |
f7fe8c079b89289ce6b4343d8a4e2c41a431580a | 68,217 | py | Python | Python/Version 5.1 (English Real-Time search)/maze51.py | clayfish/maze | 03bad22426d90225eca71d20f16e2da590a22aa2 | [
"MIT"
] | null | null | null | Python/Version 5.1 (English Real-Time search)/maze51.py | clayfish/maze | 03bad22426d90225eca71d20f16e2da590a22aa2 | [
"MIT"
] | null | null | null | Python/Version 5.1 (English Real-Time search)/maze51.py | clayfish/maze | 03bad22426d90225eca71d20f16e2da590a22aa2 | [
"MIT"
] | null | null | null | from tkinter import *
from tkinter import font
from tkinter import messagebox
from functools import partial
from operator import attrgetter
import webbrowser
import numpy
import random
import math
import os
"""
@author Nikos Kanargias
E-mail: nkana@tee.gr
@version 5.1
The software solves and visualizes the robot motion planning problem,
by implementing variants of DFS, BFS and A* algorithms, as described
by E. Keravnou in her book: "Artificial Intelligence and Expert Systems",
Hellenic Open University, Patra 2000 (in Greek)
as well as the Greedy search algorithm, as a special case of A*.
The software also implements Dijkstra's algorithm,
as just described in the relevant article in Wikipedia.
http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
The superiority of A* and Dijkstra's algorithms against the other three becomes obvious.
The user can change the number of the grid cells, indicating
the desired number of rows and columns.
The user can add as many obstacles he/she wants, as he/she
would "paint" free curves with a drawing program.
Individual obstacles can be removed by clicking them.
The position of the robot and/or the target can be changed by dragging with the mouse.
Jump from search in "Step-by-Step" way to "Animation" way and vice versa is done
by pressing the corresponding button, even when the search is in progress.
The speed of a search can be changed, even if the search is in progress.
It is sufficient to place the slider "Speed" in the new desired position
and then press the "Animation" button.
The application considers that the robot itself has some volume.
Therefore it can’t move diagonally to a free cell passing between two obstacles
adjacent to one apex.
When 'Step-by-Step' or 'Animation' search is underway it is not possible to change the position of obstacles,
robot and target, as well as the search algorithm.
When 'Real-Time' search is underway the position of obstacles, robot and target can be changed.
Drawing of arrows to predecessors, when requested, is performed only at the end of the search.
"""
class Maze51:
class CreateToolTip(object):
"""
Helper class that creates a tooltip for a given widget
"""
# from https://stackoverflow.com/questions/3221956/what-is-the-simplest-way-to-make-tooltips-in-tkinter
def __init__(self, widget, text='widget info'):
self.waittime = 500 # milliseconds
self.wraplength = 180 # pixels
self.widget = widget
self.text = text
self.widget.bind("<Enter>", self.enter)
self.widget.bind("<Leave>", self.leave)
self.widget.bind("<ButtonPress>", self.leave)
self._id = None
self.tw = None
def enter(self, event=None):
self.schedule()
def leave(self, event=None):
self.unschedule()
self.hidetip()
def schedule(self):
self.unschedule()
self._id = self.widget.after(self.waittime, self.showtip)
def unschedule(self):
_id = self._id
self._id = None
if _id:
self.widget.after_cancel(_id)
def showtip(self, event=None):
x, y, cx, cy = self.widget.bbox("insert")
x += self.widget.winfo_rootx() + 25
y += self.widget.winfo_rooty() + 20
# creates a toplevel window
self.tw = Toplevel(self.widget)
# Leaves only the label and removes the app window
self.tw.wm_overrideredirect(True)
self.tw.wm_geometry("+%d+%d" % (x, y))
label = Label(self.tw, text=self.text, justify='left', background="#ffffff",
relief='solid', borderwidth=1, wraplength=self.wraplength)
label.pack(ipadx=1)
def hidetip(self):
tw = self.tw
self.tw = None
if tw:
tw.destroy()
class MyMaze(object):
"""
Helper class that creates a random, perfect (without cycles) maze
"""
# The code of the class is an adaptation, with the original commentary, of the answer given
# by user DoubleMx2 on August 25, 2013 to a question posted by user nazar_art at stackoverflow.com:
# http://stackoverflow.com/questions/18396364/maze-generation-arrayindexoutofboundsexception
def __init__(self, x_dimension, y_dimension):
self.dimensionX = x_dimension # dimension of maze
self.dimensionY = y_dimension
self.gridDimensionX = x_dimension * 2 + 1 # dimension of output grid
self.gridDimensionY = y_dimension * 2 + 1
# output grid
self.mazeGrid = [[' ' for y in range(self.gridDimensionY)] for x in range(self.gridDimensionX)]
# 2d array of Cells
self.cells = [[self.Cell(x, y, False) for y in range(self.dimensionY)] for x in range(self.dimensionX)]
self.generate_maze()
self.update_grid()
class Cell(object):
"""
inner class to represent a cell
"""
def __init__(self, x, y, is_wall=True):
self.neighbors = [] # cells this cell is connected to
self.open = True # if true, has yet to be used in generation
self.x = x # coordinates
self.y = y
self.wall = is_wall # impassable cell
def add_neighbor(self, other):
"""
add a neighbor to this cell, and this cell as a neighbor to the other
"""
if other not in self.neighbors: # avoid duplicates
self.neighbors.append(other)
if self not in other.neighbors: # avoid duplicates
other.neighbors.append(self)
def is_cell_below_neighbor(self):
"""
used in update_grid()
"""
return self.__class__(self.x, self.y + 1) in self.neighbors
def is_cell_right_neighbor(self):
"""
used in update_grid()
"""
return self.__class__(self.x + 1, self.y) in self.neighbors
def __eq__(self, other):
"""
useful Cell equivalence
"""
if isinstance(other, self.__class__):
return self.x == other.x and self.y == other.y
else:
return False
def generate_maze(self):
"""
generate the maze from upper left (In computing the y increases down often)
"""
start_at = self.get_cell(0, 0)
start_at.open = False # indicate cell closed for generation
cells = [start_at]
while cells:
# this is to reduce but not completely eliminate the number
# of long twisting halls with short easy to detect branches
# which results in easy mazes
if random.randint(0, 9) == 0:
cell = cells.pop(random.randint(0, cells.__len__()) - 1)
else:
cell = cells.pop(cells.__len__() - 1)
# for collection
neighbors = []
# cells that could potentially be neighbors
potential_neighbors = [self.get_cell(cell.x + 1, cell.y), self.get_cell(cell.x, cell.y + 1),
self.get_cell(cell.x - 1, cell.y), self.get_cell(cell.x, cell.y - 1)]
for other in potential_neighbors:
# skip if outside, is a wall or is not opened
if other is None or other.wall or not other.open:
continue
neighbors.append(other)
if not neighbors:
continue
# get random cell
selected = neighbors[random.randint(0, neighbors.__len__()) - 1]
# add as neighbor
selected.open = False # indicate cell closed for generation
cell.add_neighbor(selected)
cells.append(cell)
cells.append(selected)
def get_cell(self, x, y):
"""
used to get a Cell at x, y; returns None out of bounds
"""
if x < 0 or y < 0:
return None
try:
return self.cells[x][y]
except IndexError: # catch out of bounds
return None
def update_grid(self):
"""
draw the maze
"""
back_char = ' '
wall_char = 'X'
cell_char = ' '
# fill background
for x in range(self.gridDimensionX):
for y in range(self.gridDimensionY):
self.mazeGrid[x][y] = back_char
# build walls
for x in range(self.gridDimensionX):
for y in range(self.gridDimensionY):
if x % 2 == 0 or y % 2 == 0:
self.mazeGrid[x][y] = wall_char
# make meaningful representation
for x in range(self.dimensionX):
for y in range(self.dimensionY):
current = self.get_cell(x, y)
grid_x = x * 2 + 1
grid_y = y * 2 + 1
self.mazeGrid[grid_x][grid_y] = cell_char
if current.is_cell_below_neighbor():
self.mazeGrid[grid_x][grid_y + 1] = cell_char
if current.is_cell_right_neighbor():
self.mazeGrid[grid_x + 1][grid_y] = cell_char
class Cell(object):
"""
Helper class that represents the cell of the grid
"""
def __init__(self, row, col):
self.row = row # the row number of the cell(row 0 is the top)
self.col = col # the column number of the cell (column 0 is the left)
self.g = 0 # the value of the function g of A* and Greedy algorithms
self.h = 0 # the value of the function h of A* and Greedy algorithms
self.f = 0 # the value of the function f of A* and Greedy algorithms
# the distance of the cell from the initial position of the robot
# Ie the label that updates the Dijkstra's algorithm
self.dist = 0
# Each state corresponds to a cell
# and each state has a predecessor which
# stored in this variable
self.prev = self.__class__
def __eq__(self, other):
"""
useful Cell equivalence
"""
if isinstance(other, self.__class__):
return self.row == other.row and self.col == other.col
else:
return False
#######################################
# #
# Constants of Maze42 class #
# #
#######################################
INFINITY = sys.maxsize # The representation of the infinite
EMPTY = 0 # empty cell
OBST = 1 # cell with obstacle
ROBOT = 2 # the position of the robot
TARGET = 3 # the position of the target
FRONTIER = 4 # cells that form the frontier (OPEN SET)
CLOSED = 5 # cells that form the CLOSED SET
ROUTE = 6 # cells that form the robot-to-target path
MSG_DRAW_AND_SELECT = "\"Paint\" obstacles, then click 'Real-Time' or 'Step-by-Step' or 'Animation'"
MSG_SELECT_STEP_BY_STEP_ETC = "Click 'Step-by-Step' or 'Animation' or 'Clear'"
MSG_NO_SOLUTION = "There is no path to the target !!!"
def __init__(self, maze):
"""
Constructor
"""
self.center(maze)
self.rows = 41 # the number of rows of the grid
self.columns = 41 # the number of columns of the grid
self.square_size = int(500/self.rows) # the cell size in pixels
self.arrow_size = int(self.square_size/2) # the size of the tips of the arrow pointing the predecessor cell
self.openSet = [] # the OPEN SET
self.closedSet = [] # the CLOSED SET
self.graph = [] # the set of vertices of the graph to be explored by Dijkstra's algorithm
self.robotStart = self.Cell(self.rows - 2, 1) # the initial position of the robot
self.targetPos = self.Cell(1, self.columns - 2) # the position of the target
self.grid = [[]] # the grid
self.realTime = False # Solution is displayed instantly
self.found = False # flag that the goal was found
self.searching = False # flag that the search is in progress
self.endOfSearch = False # flag that the search came to an end
self.animation = False # flag that the animation is running
self.delay = 500 # time delay of animation (in msec)
self.expanded = 0 # the number of nodes that have been expanded
self.selected_algo = "DFS" # DFS is initially selected
self.array = numpy.array([0] * (83 * 83))
self.cur_row = self.cur_col = self.cur_val = 0
app_highlight_font = font.Font(app, family='Helvetica', size=10, weight='bold')
##########################################
# #
# the widgets of the user interface #
# #
##########################################
self.message = Label(app, text=self.MSG_DRAW_AND_SELECT, width=55, anchor='center',
font=('Helvetica', 12), fg="BLUE")
self.message.place(x=5, y=510)
rows_lbl = Label(app, text="# of rows (5-83):", width=16, anchor='e', font=("Helvetica", 9))
rows_lbl.place(x=530, y=5)
validate_rows_cmd = (app.register(self.validate_rows), '%P')
invalid_rows_cmd = (app.register(self.invalid_rows))
self.rows_var = StringVar()
self.rows_var.set(41)
self.rowsSpinner = Spinbox(app, width=3, from_=5, to=83, textvariable=self.rows_var, validate='focus',
validatecommand=validate_rows_cmd, invalidcommand=invalid_rows_cmd)
self.rowsSpinner.place(x=652, y=5)
cols_lbl = Label(app, text="# of columns (5-83):", width=16, anchor='e', font=("Helvetica", 9))
cols_lbl.place(x=530, y=35)
validate_cols_cmd = (app.register(self.validate_cols), '%P')
invalid_cols_cmd = (app.register(self.invalid_cols))
self.cols_var = StringVar()
self.cols_var.set(41)
self.colsSpinner = Spinbox(app, width=3, from_=5, to=83, textvariable=self.cols_var, validate='focus',
validatecommand=validate_cols_cmd, invalidcommand=invalid_cols_cmd)
self.colsSpinner.place(x=652, y=35)
self.buttons = list()
buttons_tool_tips = ("Clears and redraws the grid according to the given rows and columns",
"Creates a random maze",
"First click: clears search, Second click: clears obstacles",
"Position of obstacles, robot and target can be changed when search is underway",
"The search is performed step-by-step for every click",
"The search is performed automatically")
for i, action in enumerate(("New grid", "Maze", "Clear", "Real-Time", "Step-by-Step", "Animation")):
btn = Button(app, text=action, width=20, font=app_highlight_font, bg="light grey",
command=partial(self.select_action, action))
btn.place(x=515, y=65+30*i)
self.CreateToolTip(btn, buttons_tool_tips[i])
self.buttons.append(btn)
time_delay = Label(app, text="Delay (msec)", width=27, anchor='center', font=("Helvetica", 8))
time_delay.place(x=515, y=243)
slider_value = IntVar()
slider_value.set(500)
self.slider = Scale(app, orient=HORIZONTAL, length=165, width=10, from_=0, to=1000,
showvalue=1, variable=slider_value,)
self.slider.place(x=515, y=260)
self.CreateToolTip(self.slider, "Regulates the delay for each step (0 to 1000 msec)")
self.frame = LabelFrame(app, text="Algorithms", width=170, height=100)
self.frame.place(x=515, y=300)
self.radio_buttons = list()
radio_buttons_tool_tips = ("Depth First Search algorithm",
"Breadth First Search algorithm",
"A* algorithm",
"Greedy search algorithm",
"Dijkstra's algorithm")
for i, algorithm in enumerate(("DFS", "BFS", "A*", "Greedy", "Dijkstra")):
btn = Radiobutton(self.frame, text=algorithm, font=app_highlight_font, value=i + 1,
command=partial(self.select_algo, algorithm))
btn.place(x=10 if i % 2 == 0 else 90, y=int(i/2)*25)
self.CreateToolTip(btn, radio_buttons_tool_tips[i])
btn.deselect()
self.radio_buttons.append(btn)
self.radio_buttons[0].select()
self.diagonal = IntVar()
self.diagonalBtn = Checkbutton(app, text="Diagonal movements", font=app_highlight_font,
variable=self.diagonal)
self.diagonalBtn.place(x=515, y=405)
self.CreateToolTip(self.diagonalBtn, "Diagonal movements are also allowed")
self.drawArrows = IntVar()
self.drawArrowsBtn = Checkbutton(app, text="Arrows to predecessors", font=app_highlight_font,
variable=self.drawArrows)
self.drawArrowsBtn.place(x=515, y=430)
self.CreateToolTip(self.drawArrowsBtn, "Draw arrows to predecessors")
memo_colors = ("RED", "GREEN", "BLUE", "CYAN")
for i, memo in enumerate(("Robot", "Target", "Frontier", "Closed set")):
label = Label(app, text=memo, width=8, anchor='center', fg=memo_colors[i], font=("Helvetica", 11))
label.place(x=515 if i % 2 == 0 else 605, y=460+int(i/2)*20)
self.about_button = Button(app, text='About Maze', width=20, font=app_highlight_font, bg="light grey",
command=self.about_click)
self.about_button.place(x=515, y=505)
self.canvas = Canvas(app, bd=0, highlightthickness=0)
self.canvas.bind("<Button-1>", self.left_click)
self.canvas.bind("<B1-Motion>", self.drag)
self.initialize_grid(False)
def validate_rows(self, entry):
"""
Validates entry in rowsSpinner
:param entry: the value entered by the user
:return: True, if entry is valid
"""
try:
value = int(entry)
valid = value in range(5, 84)
except ValueError:
valid = False
if not valid:
app.bell()
# The following line is due to user PRMoureu of stackoverflow. See:
# https://stackoverflow.com/questions/46861236/widget-validation-in-tkinter/46863849?noredirect=1#comment80675412_46863849
self.rowsSpinner.after_idle(lambda: self.rowsSpinner.config(validate='focusout'))
return valid
def invalid_rows(self):
"""
Sets default value to rowsSpinner in case of invalid entry
"""
self.rows_var.set(41)
def validate_cols(self, entry):
"""
Validates entry in colsSpinner
:param entry: the value entered by the user
:return: True, if entry is valid
"""
try:
value = int(entry)
valid = value in range(5, 84)
except ValueError:
valid = False
if not valid:
app.bell()
self.colsSpinner.after_idle(lambda: self.colsSpinner.config(validate='focusout'))
return valid
def invalid_cols(self):
"""
Sets default value to colsSpinner in case of invalid entry
"""
self.cols_var.set(41)
def select_action(self, action):
if action == "New grid":
self.reset_click()
elif action == "Maze":
self.maze_click()
elif action == "Clear":
self.clear_click()
elif action == "Real-Time":
self.real_time_click()
elif action == "Step-by-Step":
self.step_by_step_click()
elif action == "Animation":
self.animation_click()
def select_algo(self, algorithm):
self.selected_algo = algorithm
def left_click(self, event):
"""
Handles clicks of left mouse button as we add or remove obstacles
"""
row = int(event.y/self.square_size)
col = int(event.x/self.square_size)
if row in range(self.rows) and col in range(self.columns):
if True if self.realTime else (not self.found and not self.searching):
if self.realTime:
self.fill_grid()
self.cur_row = row
self.cur_col = col
self.cur_val = self.grid[row][col]
if self.cur_val == self.EMPTY:
self.grid[row][col] = self.OBST
self.paint_cell(row, col, "BLACK")
if self.cur_val == self.OBST:
self.grid[row][col] = self.EMPTY
self.paint_cell(row, col, "WHITE")
if self.realTime and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
if self.realTime:
self.real_Time_action()
def drag(self, event):
"""
Handles mouse movements as we "paint" obstacles or move the robot and/or target.
"""
row = int(event.y/self.square_size)
col = int(event.x/self.square_size)
if row in range(self.rows) and col in range(self.columns):
if True if self.realTime else (not self.found and not self.searching):
if self.realTime:
self.fill_grid()
if self.Cell(row, col) != self.Cell(self.cur_row, self.cur_col) and\
self.cur_val in [self.ROBOT, self.TARGET]:
new_val = self.grid[row][col]
if new_val == self.EMPTY:
self.grid[row][col] = self.cur_val
if self.cur_val == self.ROBOT:
self.grid[self.robotStart.row][self.robotStart.col] = self.EMPTY
self.paint_cell(self.robotStart.row, self.robotStart.col, "WHITE")
self.robotStart.row = row
self.robotStart.col = col
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.paint_cell(self.robotStart.row, self.robotStart.col, "RED")
else:
self.grid[self.targetPos.row][self.targetPos.col] = self.EMPTY
self.paint_cell(self.targetPos.row, self.targetPos.col, "WHITE")
self.targetPos.row = row
self.targetPos.col = col
self.grid[self.targetPos.row][self.targetPos.col] = self.TARGET
self.paint_cell(self.targetPos.row, self.targetPos.col, "GREEN")
self.cur_row = row
self.cur_col = col
self.cur_val = self.grid[row][col]
elif self.grid[row][col] != self.ROBOT and self.grid[row][col] != self.TARGET:
self.grid[row][col] = self.OBST
self.paint_cell(row, col, "BLACK")
if self.realTime and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
if self.realTime:
self.real_Time_action()
def initialize_grid(self, make_maze):
"""
Creates a new clean grid or a new maze
:param make_maze: flag that indicates the creation of a random maze
"""
self.rows = int(self.rowsSpinner.get())
self.columns = int(self.colsSpinner.get())
if make_maze and self.rows % 2 == 0:
self.rows -= 1
if make_maze and self.columns % 2 == 0:
self.columns -= 1
self.square_size = int(500/(self.rows if self.rows > self.columns else self.columns))
self.arrow_size = int(self.square_size/2)
self.grid = self.array[:self.rows*self.columns]
self.grid = self.grid.reshape(self.rows, self.columns)
self.canvas.configure(width=self.columns*self.square_size+1, height=self.rows*self.square_size+1)
self.canvas.place(x=10, y=10)
self.canvas.create_rectangle(0, 0, self.columns*self.square_size+1,
self.rows*self.square_size+1, width=0, fill="DARK GREY")
for r in list(range(self.rows)):
for c in list(range(self.columns)):
self.grid[r][c] = self.EMPTY
self.robotStart = self.Cell(self.rows-2, 1)
self.targetPos = self.Cell(1, self.columns-2)
self.fill_grid()
if make_maze:
maze = self.MyMaze(int(self.rows/2), int(self.columns/2))
for x in range(maze.gridDimensionX):
for y in range(maze.gridDimensionY):
if maze.mazeGrid[x][y] == 'X': # maze.wall_char:
self.grid[x][y] = self.OBST
self.repaint()
def fill_grid(self):
"""
Gives initial values for the cells in the grid.
"""
# With the first click on button 'Clear' clears the data
# of any search was performed (Frontier, Closed Set, Route)
# and leaves intact the obstacles and the robot and target positions
# in order to be able to run another algorithm
# with the same data.
# With the second click removes any obstacles also.
if self.searching or self.endOfSearch:
for r in list(range(self.rows)):
for c in list(range(self.columns)):
if self.grid[r][c] in [self.FRONTIER, self.CLOSED, self.ROUTE]:
self.grid[r][c] = self.EMPTY
if self.grid[r][c] == self.ROBOT:
self.robotStart = self.Cell(r, c)
self.searching = False
else:
for r in list(range(self.rows)):
for c in list(range(self.columns)):
self.grid[r][c] = self.EMPTY
self.robotStart = self.Cell(self.rows-2, 1)
self.targetPos = self.Cell(1, self.columns-2)
if self.selected_algo in ["A*", "Greedy"]:
self.robotStart.g = 0
self.robotStart.h = 0
self.robotStart.f = 0
self.expanded = 0
self.found = False
self.searching = False
self.endOfSearch = False
self.openSet.clear()
self.closedSet.clear()
self.openSet = [self.robotStart]
self.closedSet = []
self.grid[self.targetPos.row][self.targetPos.col] = self.TARGET
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.message.configure(text=self.MSG_DRAW_AND_SELECT)
self.repaint()
def repaint(self):
"""
Repaints the grid
"""
color = ""
for r in list(range(self.rows)):
for c in list(range(self.columns)):
if self.grid[r][c] == self.EMPTY:
color = "WHITE"
elif self.grid[r][c] == self.ROBOT:
color = "RED"
elif self.grid[r][c] == self.TARGET:
color = "GREEN"
elif self.grid[r][c] == self.OBST:
color = "BLACK"
elif self.grid[r][c] == self.FRONTIER:
color = "BLUE"
elif self.grid[r][c] == self.CLOSED:
color = "CYAN"
elif self.grid[r][c] == self.ROUTE:
color = "YELLOW"
self.paint_cell(r, c, color)
def paint_cell(self, row, col, color):
"""
Paints a particular cell
:param row: # the row of the cell
:param col: # the column of the cell
:param color: # the color of the cell
"""
self.canvas.create_rectangle(1 + col * self.square_size, 1 + row * self.square_size,
1 + (col + 1) * self.square_size - 1, 1 + (row + 1) * self.square_size - 1,
width=0, fill=color)
def reset_click(self):
"""
Action performed when user clicks "New grid" button
"""
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.initialize_grid(False)
def maze_click(self):
"""
Action performed when user clicks "Maze" button
"""
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.initialize_grid(True)
def clear_click(self):
"""
Action performed when user clicks "Clear" button
"""
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.fill_grid()
def real_time_click(self):
"""
Action performed when user clicks "Real-Time" button
"""
if self.realTime:
return
self.realTime = True
self.searching = True
# The Dijkstra's initialization should be done just before the
# start of search, because obstacles must be in place.
if self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.buttons[3].configure(fg="RED") # Real-Time button
self.slider.configure(state="disabled")
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.real_Time_action()
def real_Time_action(self):
"""
Action performed during real-time search
"""
while not self.endOfSearch:
self.check_termination()
def step_by_step_click(self):
"""
Action performed when user clicks "Step-by-Step" button
"""
if self.found or self.endOfSearch:
return
if not self.searching and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.animation = False
self.searching = True
self.message.configure(text=self.MSG_SELECT_STEP_BY_STEP_ETC)
self.buttons[3].configure(state="disabled") # Real-Time button
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.check_termination()
def animation_click(self):
"""
Action performed when user clicks "Animation" button
"""
self.animation = True
if not self.searching and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.searching = True
self.message.configure(text=self.MSG_SELECT_STEP_BY_STEP_ETC)
self.buttons[3].configure(state="disabled") # Real-Time button
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.delay = self.slider.get()
self.animation_action()
def animation_action(self):
"""
The action periodically performed during searching in animation mode
"""
if self.animation:
self.check_termination()
if self.endOfSearch:
return
self.canvas.after(self.delay, self.animation_action)
def about_click(self):
"""
Action performed when user clicks "About Maze" button
"""
about_box = Toplevel(master=app)
about_box.title("")
about_box.geometry("340x160")
about_box.resizable(False, False)
self.center(about_box)
about_box.transient(app) # only one window in the task bar
about_box.grab_set() # modal
title = Label(about_box, text="Maze", width=20, anchor='center', fg='SANDY BROWN', font=("Helvetica", 20))
title.place(x=0, y=0)
version = Label(about_box, text="Version: 5.1", width=35, anchor='center', font=("Helvetica", 11, 'bold'))
version.place(x=0, y=35)
programmer = Label(about_box, text="Designer: Nikos Kanargias", width=35, anchor='center',
font=("Helvetica", 12))
programmer.place(x=0, y=60)
email = Label(about_box, text="E-mail: nkana@tee.gr", width=40, anchor='center', font=("Helvetica", 10))
email.place(x=0, y=80)
source_code = Label(about_box, text="Code and documentation", fg="blue", cursor="hand2", width=35,
anchor='center',
font=("Helvetica", 12))
f = font.Font(source_code, source_code.cget("font"))
f.configure(underline=True)
source_code.configure(font=f)
source_code.place(x=0, y=100)
source_code.bind("<Button-1>", self.source_code_callback)
self.CreateToolTip(source_code, "Click this link to retrieve code and documentation from DropBox")
video = Label(about_box, text="Watch demo video on YouTube", fg="blue", cursor="hand2", width=35,
anchor='center')
video.configure(font=f)
video.place(x=0, y=125)
video.bind("<Button-1>", self.video_callback)
self.CreateToolTip(video, "Click this link to watch a demo video on YouTube")
def check_termination(self):
"""
Checks if search is completed
"""
# Here we decide whether we can continue the search or not.
# In the case of DFS, BFS, A* and Greedy algorithms
# here we have the second step:
# 2. If OPEN SET = [], then terminate. There is no solution.
if (self.selected_algo == "Dijkstra" and not self.graph) or\
self.selected_algo != "Dijkstra" and not self.openSet:
self.endOfSearch = True
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.message.configure(text=self.MSG_NO_SOLUTION)
self.buttons[4].configure(state="disabled") # Step-by-Step button
self.buttons[5].configure(state="disabled") # Animation button
self.slider.configure(state="disabled")
self.repaint()
if self.drawArrows.get():
self.draw_arrows()
else:
self.expand_node()
if self.found:
self.endOfSearch = True
self.plot_route()
self.buttons[4].configure(state="disabled") # Step-by-Step button
self.buttons[5].configure(state="disabled") # Animation button
self.slider.configure(state="disabled")
def expand_node(self):
"""
Expands a node and creates his successors
"""
# Dijkstra's algorithm to handle separately
if self.selected_algo == "Dijkstra":
# 11: while Q is not empty:
if not self.graph:
return
# 12: u := vertex in Q (graph) with smallest distance in dist[] ;
# 13: remove u from Q (graph);
u = self.graph.pop(0)
# Add vertex u in closed set
self.closedSet.append(u)
# If target has been found ...
if u == self.targetPos:
self.found = True
return
# Counts nodes that have expanded.
self.expanded += 1
# Update the color of the cell
self.grid[u.row][u.col] = self.CLOSED
# paint the cell
self.paint_cell(u.row, u.col, "CYAN")
# 14: if dist[u] = infinity:
if u.dist == self.INFINITY:
# ... then there is no solution.
# 15: break;
return
# 16: end if
# Create the neighbors of u
neighbors = self.create_successors(u, False)
# 18: for each neighbor v of u:
for v in neighbors:
# 20: alt := dist[u] + dist_between(u, v) ;
alt = u.dist + self.dist_between(u, v)
# 21: if alt < dist[v]:
if alt < v.dist:
# 22: dist[v] := alt ;
v.dist = alt
# 23: previous[v] := u ;
v.prev = u
# Update the color of the cell
self.grid[v.row][v.col] = self.FRONTIER
# paint the cell
self.paint_cell(v.row, v.col, "BLUE")
# 24: decrease-key v in Q;
# (sort list of nodes with respect to dist)
self.graph.sort(key=attrgetter("dist"))
# The handling of the other four algorithms
else:
if self.selected_algo in ["DFS", "BFS"]:
# Here is the 3rd step of the algorithms DFS and BFS
# 3. Remove the first state, Si, from OPEN SET ...
current = self.openSet.pop(0)
else:
# Here is the 3rd step of the algorithms A* and Greedy
# 3. Remove the first state, Si, from OPEN SET,
# for which f(Si) ≤ f(Sj) for all other
# open states Sj ...
# (sort first OPEN SET list with respect to 'f')
self.openSet.sort(key=attrgetter("f"))
current = self.openSet.pop(0)
# ... and add it to CLOSED SET.
self.closedSet.insert(0, current)
# Update the color of the cell
self.grid[current.row][current.col] = self.CLOSED
# paint the cell
self.paint_cell(current.row, current.col, "CYAN")
# If the selected node is the target ...
if current == self.targetPos:
# ... then terminate etc
last = self.targetPos
last.prev = current.prev
self.closedSet.append(last)
self.found = True
return
# Count nodes that have been expanded.
self.expanded += 1
# Here is the 4rd step of the algorithms
# 4. Create the successors of Si, based on actions
# that can be implemented on Si.
# Each successor has a pointer to the Si, as its predecessor.
# In the case of DFS and BFS algorithms, successors should not
# belong neither to the OPEN SET nor the CLOSED SET.
successors = self.create_successors(current, False)
# Here is the 5th step of the algorithms
# 5. For each successor of Si, ...
for cell in successors:
# ... if we are running DFS ...
if self.selected_algo == "DFS":
# ... add the successor at the beginning of the list OPEN SET
self.openSet.insert(0, cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if we are runnig BFS ...
elif self.selected_algo == "BFS":
# ... add the successor at the end of the list OPEN SET
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if we are running A* or Greedy algorithms (step 5 of A* algorithm) ...
elif self.selected_algo in ["A*", "Greedy"]:
# ... calculate the value f(Sj) ...
dxg = current.col - cell.col
dyg = current.row - cell.row
dxh = self.targetPos.col - cell.col
dyh = self.targetPos.row - cell.row
if self.diagonal.get():
# with diagonal movements, calculate the Euclidean distance
if self.selected_algo == "Greedy":
# especially for the Greedy ...
cell.g = 0
else:
cell.g = current.g + math.sqrt(dxg*dxg + dyg*dyg)
cell.h = math.sqrt(dxh*dxh + dyh*dyh)
else:
# without diagonal movements, calculate the Manhattan distance
if self.selected_algo == "Greedy":
# especially for the Greedy ...
cell.g = 0
else:
cell.g = current.g + abs(dxg) + abs(dyg)
cell.h = abs(dxh) + abs(dyh)
cell.f = cell.g+cell.h
# ... If Sj is neither in the OPEN SET nor in the CLOSED SET states ...
if cell not in self.openSet and cell not in self.closedSet:
# ... then add Sj in the OPEN SET ...
# ... evaluated as f(Sj)
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# Else ...
else:
# ... if already belongs to the OPEN SET, then ...
if cell in self.openSet:
open_index = self.openSet.index(cell)
# ... compare the new value assessment with the old one.
# If old <= new ...
if self.openSet[open_index].f <= cell.f:
# ... then eject the new node with state Sj.
# (ie do nothing for this node).
pass
# Else, ...
else:
# ... remove the element (Sj, old) from the list
# to which it belongs ...
self.openSet.pop(open_index)
# ... and add the item (Sj, new) to the OPEN SET.
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if already belongs to the CLOSED SET, then ...
elif cell in self.closedSet:
closed_index = self.closedSet.index(cell)
# ... compare the new value assessment with the old one.
# If old <= new ...
if self.closedSet[closed_index].f <= cell.f:
# ... then eject the new node with state Sj.
# (ie do nothing for this node).
pass
# Else, ...
else:
# ... remove the element (Sj, old) from the list
# to which it belongs ...
self.closedSet.pop(closed_index)
# ... and add the item (Sj, new) to the OPEN SET.
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
def create_successors(self, current, make_connected):
"""
Creates the successors of a state/cell
:param current: the cell for which we ask successors
:param make_connected: flag that indicates that we are interested only on the coordinates
of cells and not on the label 'dist' (concerns only Dijkstra's)
:return: the successors of the cell as a list
"""
r = current.row
c = current.col
# We create an empty list for the successors of the current cell.
temp = []
# With diagonal movements priority is:
# 1: Up 2: Up-right 3: Right 4: Down-right
# 5: Down 6: Down-left 7: Left 8: Up-left
# Without diagonal movements the priority is:
# 1: Up 2: Right 3: Down 4: Left
# If not at the topmost limit of the grid
# and the up-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r > 0 and self.grid[r-1][c] != self.OBST and\
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c) in self.openSet and not self.Cell(r-1, c) in self.closedSet)):
cell = self.Cell(r-1, c)
# In the case of Dijkstra's algorithm we can not append to
# the list of successors the "naked" cell we have just created.
# The cell must be accompanied by the label 'dist',
# so we need to track it down through the list 'graph'
# and then copy it back to the list of successors.
# The flag makeConnected is necessary to be able
# the present method create_succesors() to collaborate
# with the method find_connected_component(), which creates
# the connected component when Dijkstra's initializes.
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-side cell so it points the current one ...
cell.prev = current
# ... and add the up-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the topmost nor at the rightmost border of the grid
# and the up-right-side cell is not an obstacle
# and one of the upper side or right side cells are not obstacles
# (because it is not reasonable to allow the robot to pass through a "slot")
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor CLOSED SET ...
if r > 0 and c < self.columns-1 and self.grid[r-1][c+1] != self.OBST and \
(self.grid[r-1][c] != self.OBST or self.grid[r][c+1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c+1) in self.openSet and not self.Cell(r-1, c+1) in self.closedSet)):
cell = self.Cell(r-1, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-right-side cell so it points the current one ...
cell.prev = current
# ... and add the up-right-side cell to the successors of the current one.
temp.append(cell)
# If not at the rightmost limit of the grid
# and the right-side cell is not an obstacle ...
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if c < self.columns-1 and self.grid[r][c+1] != self.OBST and\
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r, c+1) in self.openSet and not self.Cell(r, c+1) in self.closedSet)):
cell = self.Cell(r, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the right-side cell so it points the current one ...
cell.prev = current
# ... and add the right-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the lowermost nor at the rightmost border of the grid
# and the down-right-side cell is not an obstacle
# and one of the down-side or right-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and c < self.columns-1 and self.grid[r+1][c+1] != self.OBST and \
(self.grid[r+1][c] != self.OBST or self.grid[r][c+1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c+1) in self.openSet and not self.Cell(r+1, c+1) in self.closedSet)):
cell = self.Cell(r+1, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the downr-right-side cell so it points the current one ...
cell.prev = current
# ... and add the down-right-side cell to the successors of the current one.
temp.append(cell)
# If not at the lowermost limit of the grid
# and the down-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and self.grid[r+1][c] != self.OBST and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c) in self.openSet and not self.Cell(r+1, c) in self.closedSet)):
cell = self.Cell(r+1, c)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the down-side cell so it points the current one ...
cell.prev = current
# ... and add the down-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the lowermost nor at the leftmost border of the grid
# and the down-left-side cell is not an obstacle
# and one of the down-side or left-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and c > 0 and self.grid[r+1][c-1] != self.OBST and \
(self.grid[r+1][c] != self.OBST or self.grid[r][c-1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c-1) in self.openSet and not self.Cell(r+1, c-1) in self.closedSet)):
cell = self.Cell(r+1, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the down-left-side cell so it points the current one ...
cell.prev = current
# ... and add the down-left-side cell to the successors of the current one.
temp.append(cell)
# If not at the leftmost limit of the grid
# and the left-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if c > 0 and self.grid[r][c-1] != self.OBST and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r, c-1) in self.openSet and not self.Cell(r, c-1) in self.closedSet)):
cell = self.Cell(r, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the left-side cell so it points the current one ...
cell.prev = current
# ... and add the left-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the topmost nor at the leftmost border of the grid
# and the up-left-side cell is not an obstacle
# and one of the up-side or left-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r > 0 and c > 0 and self.grid[r-1][c-1] != self.OBST and \
(self.grid[r-1][c] != self.OBST or self.grid[r][c-1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c-1) in self.openSet and not self.Cell(r-1, c-1) in self.closedSet)):
cell = self.Cell(r-1, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-left-side cell so it points the current one ...
cell.prev = current
# ... and add the up-left-side cell to the successors of the current one.
temp.append(cell)
# When DFS algorithm is in use, cells are added one by one at the beginning of the
# OPEN SET list. Because of this, we must reverse the order of successors formed,
# so the successor corresponding to the highest priority, to be placed the first in the list.
# For the Greedy, A* and Dijkstra's no issue, because the list is sorted
# according to 'f' or 'dist' before extracting the first element of.
if self.selected_algo == "DFS":
return reversed(temp)
else:
return temp
def dist_between(self, u, v):
"""
Returns the distance between two cells
:param u: the first cell
:param v: the other cell
:return: the distance between the cells u and v
"""
dx = u.col - v.col
dy = u.row - v.row
if self.diagonal.get():
# with diagonal movements calculate the Euclidean distance
return math.sqrt(dx*dx + dy*dy)
else:
# without diagonal movements calculate the Manhattan distance
return abs(dx) + abs(dy)
def plot_route(self):
"""
Calculates the path from the target to the initial position of the robot,
counts the corresponding steps and measures the distance traveled.
"""
self.repaint()
self.searching = False
steps = 0
distance = 0.0
index = self.closedSet.index(self.targetPos)
cur = self.closedSet[index]
self.grid[cur.row][cur.col] = self.TARGET
self.paint_cell(cur.row, cur.col, "GREEN")
while cur != self.robotStart:
steps += 1
if self.diagonal.get():
dx = cur.col - cur.prev.col
dy = cur.row - cur.prev.row
distance += math.sqrt(dx*dx + dy*dy)
else:
distance += 1
cur = cur.prev
self.grid[cur.row][cur.col] = self.ROUTE
self.paint_cell(cur.row, cur.col, "YELLOW")
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.paint_cell(self.robotStart.row, self.robotStart.col, "RED")
if self.drawArrows.get():
self.draw_arrows()
msg = "Nodes expanded: {0}, Steps: {1}, Distance: {2:.3f}".format(self.expanded, steps, distance)
self.message.configure(text=msg)
def find_connected_component(self, v):
"""
Appends to the list containing the nodes of the graph only
the cells belonging to the same connected component with node v.
:param v: the starting node
"""
# This is a Breadth First Search of the graph starting from node v.
stack = [v]
self.graph.append(v)
while stack:
v = stack.pop()
successors = self.create_successors(v, True)
for c in successors:
if c not in self.graph:
stack.append(c)
self.graph.append(c)
def initialize_dijkstra(self):
"""
Initialization of Dijkstra's algorithm
"""
# When one thinks of Wikipedia pseudocode, observe that the
# algorithm is still looking for his target while there are still
# nodes in the queue Q.
# Only when we run out of queue and the target has not been found,
# can answer that there is no solution.
# As is known, the algorithm models the problem as a connected graph
# It is obvious that no solution exists only when the graph is not
# connected and the target is in a different connected component
# of this initial position of the robot
# To be thus possible negative response from the algorithm,
# should search be made ONLY in the coherent component to which the
# initial position of the robot belongs.
# First create the connected component
# to which the initial position of the robot belongs.
self.graph.clear()
self.find_connected_component(self.robotStart)
# Here is the initialization of Dijkstra's algorithm
# 2: for each vertex v in Graph;
for v in self.graph:
# 3: dist[v] := infinity ;
v.dist = self.INFINITY
# 5: previous[v] := undefined ;
v.prev = None
# 8: dist[source] := 0;
self.graph[self.graph.index(self.robotStart)].dist = 0
# 9: Q := the set of all nodes in Graph;
# Instead of the variable Q we will use the list
# 'graph' itself, which has already been initialised.
# Sorts the list of nodes with respect to 'dist'.
self.graph.sort(key=attrgetter("dist"))
# Initializes the list of closed nodes
self.closedSet.clear()
def draw_arrows(self):
"""
Draws the arrows to predecessors
"""
# We draw black arrows from each open or closed state to its predecessor.
for r in range(self.rows):
for c in range(self.columns):
tail = head = cell = self.Cell(r, c)
# If the current cell is an open state, or is a closed state
# but not the initial position of the robot
if self.grid[r][c] in [self.FRONTIER, self.CLOSED] and not cell == self.robotStart:
# The tail of the arrow is the current cell, while
# the arrowhead is the predecessor cell.
if self.grid[r][c] == self.FRONTIER:
if self.selected_algo == "Dijkstra":
tail = self.graph[self.graph.index(cell)]
head = tail.prev
else:
tail = self.openSet[self.openSet.index(cell)]
head = tail.prev
elif self.grid[r][c] == self.CLOSED:
tail = self.closedSet[self.closedSet.index(cell)]
head = tail.prev
self.draw_arrow(tail, head, self.arrow_size, "BLACK", 2 if self.square_size >= 25 else 1)
if self.found:
# We draw red arrows along the path from robotStart to targetPos.
# index = self.closedSet.index(self.targetPos)
cur = self.closedSet[self.closedSet.index(self.targetPos)]
while cur != self.robotStart:
head = cur
cur = cur.prev
tail = cur
self.draw_arrow(tail, head, self.arrow_size, "RED", 2 if self.square_size >= 25 else 1)
def draw_arrow(self, tail, head, a, color, width):
"""
Draws an arrow from center of tail cell to center of head cell
:param tail: the tail of the arrow
:param head: the head of the arrow
:param a: size of arrow tips
:param color: color of the arrow
:param width: thickness of the lines
"""
# The coordinates of the center of the tail cell
x1 = 1 + tail.col * self.square_size + self.square_size / 2
y1 = 1 + tail.row * self.square_size + self.square_size / 2
# The coordinates of the center of the head cell
x2 = 1 + head.col * self.square_size + self.square_size / 2
y2 = 1 + head.row * self.square_size + self.square_size / 2
sin20 = math.sin(20*math.pi/180)
cos20 = math.cos(20*math.pi/180)
sin25 = math.sin(25*math.pi/180)
cos25 = math.cos(25*math.pi/180)
u3 = v3 = u4 = v4 = 0
if x1 == x2 and y1 > y2: # up
u3 = x2 - a*sin20
v3 = y2 + a*cos20
u4 = x2 + a*sin20
v4 = v3
elif x1 < x2 and y1 > y2: # up-right
u3 = x2 - a*cos25
v3 = y2 + a*sin25
u4 = x2 - a*sin25
v4 = y2 + a*cos25
elif x1 < x2 and y1 == y2: # right
u3 = x2 - a*cos20
v3 = y2 - a*sin20
u4 = u3
v4 = y2 + a*sin20
elif x1 < x2 and y1 < y2: # righr-down
u3 = x2 - a*cos25
v3 = y2 - a*sin25
u4 = x2 - a*sin25
v4 = y2 - a*cos25
elif x1 == x2 and y1 < y2: # down
u3 = x2 - a*sin20
v3 = y2 - a*cos20
u4 = x2 + a*sin20
v4 = v3
elif x1 > x2 and y1 < y2: # left-down
u3 = x2 + a*sin25
v3 = y2 - a*cos25
u4 = x2 + a*cos25
v4 = y2 - a*sin25
elif x1 > x2 and y1 == y2: # left
u3 = x2 + a*cos20
v3 = y2 - a*sin20
u4 = u3
v4 = y2 + a*sin20
elif x1 > x2 and y1 > y2: # left-up
u3 = x2 + a*sin25
v3 = y2 + a*cos25
u4 = x2 + a*cos25
v4 = y2 + a*sin25
self.canvas.create_line(x1, y1, x2, y2, fill=color, width=width)
self.canvas.create_line(x2, y2, u3, v3, fill=color, width=width)
self.canvas.create_line(x2, y2, u4, v4, fill=color, width=width)
@staticmethod
def center(window):
"""
Places a window at the center of the screen
"""
window.update_idletasks()
w = window.winfo_screenwidth()
h = window.winfo_screenheight()
size = tuple(int(_) for _ in window.geometry().split('+')[0].split('x'))
x = w / 2 - size[0] / 2
y = h / 2 - size[1] / 2
window.geometry("%dx%d+%d+%d" % (size + (x, y)))
@staticmethod
def source_code_callback(self):
webbrowser.open_new(r"https://goo.gl/tRaLfe")
@staticmethod
def video_callback(self):
webbrowser.open_new(r"https://youtu.be/7GLqy61X2oU")
def on_closing():
if messagebox.askokcancel("Quit", "Do you want to quit?"):
os._exit(0)
if __name__ == '__main__':
app = Tk()
app.protocol("WM_DELETE_WINDOW", on_closing)
app.title("Maze 5.1")
app.geometry("693x545")
app.resizable(False, False)
Maze51(app)
app.mainloop()
| 45.447702 | 134 | 0.538165 | from tkinter import *
from tkinter import font
from tkinter import messagebox
from functools import partial
from operator import attrgetter
import webbrowser
import numpy
import random
import math
import os
class Maze51:
class CreateToolTip(object):
def __init__(self, widget, text='widget info'):
self.waittime = 500
self.wraplength = 180
self.widget = widget
self.text = text
self.widget.bind("<Enter>", self.enter)
self.widget.bind("<Leave>", self.leave)
self.widget.bind("<ButtonPress>", self.leave)
self._id = None
self.tw = None
def enter(self, event=None):
self.schedule()
def leave(self, event=None):
self.unschedule()
self.hidetip()
def schedule(self):
self.unschedule()
self._id = self.widget.after(self.waittime, self.showtip)
def unschedule(self):
_id = self._id
self._id = None
if _id:
self.widget.after_cancel(_id)
def showtip(self, event=None):
x, y, cx, cy = self.widget.bbox("insert")
x += self.widget.winfo_rootx() + 25
y += self.widget.winfo_rooty() + 20
self.tw = Toplevel(self.widget)
self.tw.wm_overrideredirect(True)
self.tw.wm_geometry("+%d+%d" % (x, y))
label = Label(self.tw, text=self.text, justify='left', background="#ffffff",
relief='solid', borderwidth=1, wraplength=self.wraplength)
label.pack(ipadx=1)
def hidetip(self):
tw = self.tw
self.tw = None
if tw:
tw.destroy()
class MyMaze(object):
def __init__(self, x_dimension, y_dimension):
self.dimensionX = x_dimension
self.dimensionY = y_dimension
self.gridDimensionX = x_dimension * 2 + 1
self.gridDimensionY = y_dimension * 2 + 1
self.mazeGrid = [[' ' for y in range(self.gridDimensionY)] for x in range(self.gridDimensionX)]
self.cells = [[self.Cell(x, y, False) for y in range(self.dimensionY)] for x in range(self.dimensionX)]
self.generate_maze()
self.update_grid()
class Cell(object):
def __init__(self, x, y, is_wall=True):
self.neighbors = []
self.open = True
self.x = x
self.y = y
self.wall = is_wall
def add_neighbor(self, other):
if other not in self.neighbors:
self.neighbors.append(other)
if self not in other.neighbors:
other.neighbors.append(self)
def is_cell_below_neighbor(self):
return self.__class__(self.x, self.y + 1) in self.neighbors
def is_cell_right_neighbor(self):
return self.__class__(self.x + 1, self.y) in self.neighbors
def __eq__(self, other):
if isinstance(other, self.__class__):
return self.x == other.x and self.y == other.y
else:
return False
def generate_maze(self):
start_at = self.get_cell(0, 0)
start_at.open = False
cells = [start_at]
while cells:
if random.randint(0, 9) == 0:
cell = cells.pop(random.randint(0, cells.__len__()) - 1)
else:
cell = cells.pop(cells.__len__() - 1)
neighbors = []
potential_neighbors = [self.get_cell(cell.x + 1, cell.y), self.get_cell(cell.x, cell.y + 1),
self.get_cell(cell.x - 1, cell.y), self.get_cell(cell.x, cell.y - 1)]
for other in potential_neighbors:
if other is None or other.wall or not other.open:
continue
neighbors.append(other)
if not neighbors:
continue
selected = neighbors[random.randint(0, neighbors.__len__()) - 1]
selected.open = False
cell.add_neighbor(selected)
cells.append(cell)
cells.append(selected)
def get_cell(self, x, y):
if x < 0 or y < 0:
return None
try:
return self.cells[x][y]
except IndexError:
return None
def update_grid(self):
back_char = ' '
wall_char = 'X'
cell_char = ' '
for x in range(self.gridDimensionX):
for y in range(self.gridDimensionY):
self.mazeGrid[x][y] = back_char
for x in range(self.gridDimensionX):
for y in range(self.gridDimensionY):
if x % 2 == 0 or y % 2 == 0:
self.mazeGrid[x][y] = wall_char
for x in range(self.dimensionX):
for y in range(self.dimensionY):
current = self.get_cell(x, y)
grid_x = x * 2 + 1
grid_y = y * 2 + 1
self.mazeGrid[grid_x][grid_y] = cell_char
if current.is_cell_below_neighbor():
self.mazeGrid[grid_x][grid_y + 1] = cell_char
if current.is_cell_right_neighbor():
self.mazeGrid[grid_x + 1][grid_y] = cell_char
class Cell(object):
def __init__(self, row, col):
self.row = row
self.col = col
self.g = 0
self.h = 0
self.f = 0
self.dist = 0
# Each state corresponds to a cell
# and each state has a predecessor which
# stored in this variable
self.prev = self.__class__
def __eq__(self, other):
if isinstance(other, self.__class__):
return self.row == other.row and self.col == other.col
else:
return False
#######################################
# #
# Constants of Maze42 class #
# #
#######################################
INFINITY = sys.maxsize # The representation of the infinite
EMPTY = 0 # empty cell
OBST = 1 # cell with obstacle
ROBOT = 2 # the position of the robot
TARGET = 3 # the position of the target
FRONTIER = 4 # cells that form the frontier (OPEN SET)
CLOSED = 5 # cells that form the CLOSED SET
ROUTE = 6 # cells that form the robot-to-target path
MSG_DRAW_AND_SELECT = "\"Paint\" obstacles, then click 'Real-Time' or 'Step-by-Step' or 'Animation'"
MSG_SELECT_STEP_BY_STEP_ETC = "Click 'Step-by-Step' or 'Animation' or 'Clear'"
MSG_NO_SOLUTION = "There is no path to the target !!!"
def __init__(self, maze):
self.center(maze)
self.rows = 41 # the number of rows of the grid
self.columns = 41 # the number of columns of the grid
self.square_size = int(500/self.rows) # the cell size in pixels
self.arrow_size = int(self.square_size/2) # the size of the tips of the arrow pointing the predecessor cell
self.openSet = [] # the OPEN SET
self.closedSet = [] # the CLOSED SET
self.graph = [] # the set of vertices of the graph to be explored by Dijkstra's algorithm
self.robotStart = self.Cell(self.rows - 2, 1)
self.targetPos = self.Cell(1, self.columns - 2)
self.grid = [[]]
self.realTime = False
self.found = False
self.searching = False
self.endOfSearch = False
self.animation = False
self.delay = 500
self.expanded = 0
self.selected_algo = "DFS"
self.array = numpy.array([0] * (83 * 83))
self.cur_row = self.cur_col = self.cur_val = 0
app_highlight_font = font.Font(app, family='Helvetica', size=10, weight='bold')
"Position of obstacles, robot and target can be changed when search is underway",
"The search is performed step-by-step for every click",
"The search is performed automatically")
for i, action in enumerate(("New grid", "Maze", "Clear", "Real-Time", "Step-by-Step", "Animation")):
btn = Button(app, text=action, width=20, font=app_highlight_font, bg="light grey",
command=partial(self.select_action, action))
btn.place(x=515, y=65+30*i)
self.CreateToolTip(btn, buttons_tool_tips[i])
self.buttons.append(btn)
time_delay = Label(app, text="Delay (msec)", width=27, anchor='center', font=("Helvetica", 8))
time_delay.place(x=515, y=243)
slider_value = IntVar()
slider_value.set(500)
self.slider = Scale(app, orient=HORIZONTAL, length=165, width=10, from_=0, to=1000,
showvalue=1, variable=slider_value,)
self.slider.place(x=515, y=260)
self.CreateToolTip(self.slider, "Regulates the delay for each step (0 to 1000 msec)")
self.frame = LabelFrame(app, text="Algorithms", width=170, height=100)
self.frame.place(x=515, y=300)
self.radio_buttons = list()
radio_buttons_tool_tips = ("Depth First Search algorithm",
"Breadth First Search algorithm",
"A* algorithm",
"Greedy search algorithm",
"Dijkstra's algorithm")
for i, algorithm in enumerate(("DFS", "BFS", "A*", "Greedy", "Dijkstra")):
btn = Radiobutton(self.frame, text=algorithm, font=app_highlight_font, value=i + 1,
command=partial(self.select_algo, algorithm))
btn.place(x=10 if i % 2 == 0 else 90, y=int(i/2)*25)
self.CreateToolTip(btn, radio_buttons_tool_tips[i])
btn.deselect()
self.radio_buttons.append(btn)
self.radio_buttons[0].select()
self.diagonal = IntVar()
self.diagonalBtn = Checkbutton(app, text="Diagonal movements", font=app_highlight_font,
variable=self.diagonal)
self.diagonalBtn.place(x=515, y=405)
self.CreateToolTip(self.diagonalBtn, "Diagonal movements are also allowed")
self.drawArrows = IntVar()
self.drawArrowsBtn = Checkbutton(app, text="Arrows to predecessors", font=app_highlight_font,
variable=self.drawArrows)
self.drawArrowsBtn.place(x=515, y=430)
self.CreateToolTip(self.drawArrowsBtn, "Draw arrows to predecessors")
memo_colors = ("RED", "GREEN", "BLUE", "CYAN")
for i, memo in enumerate(("Robot", "Target", "Frontier", "Closed set")):
label = Label(app, text=memo, width=8, anchor='center', fg=memo_colors[i], font=("Helvetica", 11))
label.place(x=515 if i % 2 == 0 else 605, y=460+int(i/2)*20)
self.about_button = Button(app, text='About Maze', width=20, font=app_highlight_font, bg="light grey",
command=self.about_click)
self.about_button.place(x=515, y=505)
self.canvas = Canvas(app, bd=0, highlightthickness=0)
self.canvas.bind("<Button-1>", self.left_click)
self.canvas.bind("<B1-Motion>", self.drag)
self.initialize_grid(False)
def validate_rows(self, entry):
try:
value = int(entry)
valid = value in range(5, 84)
except ValueError:
valid = False
if not valid:
app.bell()
# The following line is due to user PRMoureu of stackoverflow. See:
# https://stackoverflow.com/questions/46861236/widget-validation-in-tkinter/46863849?noredirect=1#comment80675412_46863849
self.rowsSpinner.after_idle(lambda: self.rowsSpinner.config(validate='focusout'))
return valid
def invalid_rows(self):
self.rows_var.set(41)
def validate_cols(self, entry):
try:
value = int(entry)
valid = value in range(5, 84)
except ValueError:
valid = False
if not valid:
app.bell()
self.colsSpinner.after_idle(lambda: self.colsSpinner.config(validate='focusout'))
return valid
def invalid_cols(self):
self.cols_var.set(41)
def select_action(self, action):
if action == "New grid":
self.reset_click()
elif action == "Maze":
self.maze_click()
elif action == "Clear":
self.clear_click()
elif action == "Real-Time":
self.real_time_click()
elif action == "Step-by-Step":
self.step_by_step_click()
elif action == "Animation":
self.animation_click()
def select_algo(self, algorithm):
self.selected_algo = algorithm
def left_click(self, event):
row = int(event.y/self.square_size)
col = int(event.x/self.square_size)
if row in range(self.rows) and col in range(self.columns):
if True if self.realTime else (not self.found and not self.searching):
if self.realTime:
self.fill_grid()
self.cur_row = row
self.cur_col = col
self.cur_val = self.grid[row][col]
if self.cur_val == self.EMPTY:
self.grid[row][col] = self.OBST
self.paint_cell(row, col, "BLACK")
if self.cur_val == self.OBST:
self.grid[row][col] = self.EMPTY
self.paint_cell(row, col, "WHITE")
if self.realTime and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
if self.realTime:
self.real_Time_action()
def drag(self, event):
row = int(event.y/self.square_size)
col = int(event.x/self.square_size)
if row in range(self.rows) and col in range(self.columns):
if True if self.realTime else (not self.found and not self.searching):
if self.realTime:
self.fill_grid()
if self.Cell(row, col) != self.Cell(self.cur_row, self.cur_col) and\
self.cur_val in [self.ROBOT, self.TARGET]:
new_val = self.grid[row][col]
if new_val == self.EMPTY:
self.grid[row][col] = self.cur_val
if self.cur_val == self.ROBOT:
self.grid[self.robotStart.row][self.robotStart.col] = self.EMPTY
self.paint_cell(self.robotStart.row, self.robotStart.col, "WHITE")
self.robotStart.row = row
self.robotStart.col = col
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.paint_cell(self.robotStart.row, self.robotStart.col, "RED")
else:
self.grid[self.targetPos.row][self.targetPos.col] = self.EMPTY
self.paint_cell(self.targetPos.row, self.targetPos.col, "WHITE")
self.targetPos.row = row
self.targetPos.col = col
self.grid[self.targetPos.row][self.targetPos.col] = self.TARGET
self.paint_cell(self.targetPos.row, self.targetPos.col, "GREEN")
self.cur_row = row
self.cur_col = col
self.cur_val = self.grid[row][col]
elif self.grid[row][col] != self.ROBOT and self.grid[row][col] != self.TARGET:
self.grid[row][col] = self.OBST
self.paint_cell(row, col, "BLACK")
if self.realTime and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
if self.realTime:
self.real_Time_action()
def initialize_grid(self, make_maze):
self.rows = int(self.rowsSpinner.get())
self.columns = int(self.colsSpinner.get())
if make_maze and self.rows % 2 == 0:
self.rows -= 1
if make_maze and self.columns % 2 == 0:
self.columns -= 1
self.square_size = int(500/(self.rows if self.rows > self.columns else self.columns))
self.arrow_size = int(self.square_size/2)
self.grid = self.array[:self.rows*self.columns]
self.grid = self.grid.reshape(self.rows, self.columns)
self.canvas.configure(width=self.columns*self.square_size+1, height=self.rows*self.square_size+1)
self.canvas.place(x=10, y=10)
self.canvas.create_rectangle(0, 0, self.columns*self.square_size+1,
self.rows*self.square_size+1, width=0, fill="DARK GREY")
for r in list(range(self.rows)):
for c in list(range(self.columns)):
self.grid[r][c] = self.EMPTY
self.robotStart = self.Cell(self.rows-2, 1)
self.targetPos = self.Cell(1, self.columns-2)
self.fill_grid()
if make_maze:
maze = self.MyMaze(int(self.rows/2), int(self.columns/2))
for x in range(maze.gridDimensionX):
for y in range(maze.gridDimensionY):
if maze.mazeGrid[x][y] == 'X': # maze.wall_char:
self.grid[x][y] = self.OBST
self.repaint()
def fill_grid(self):
# With the first click on button 'Clear' clears the data
# of any search was performed (Frontier, Closed Set, Route)
# and leaves intact the obstacles and the robot and target positions
# in order to be able to run another algorithm
# with the same data.
# With the second click removes any obstacles also.
if self.searching or self.endOfSearch:
for r in list(range(self.rows)):
for c in list(range(self.columns)):
if self.grid[r][c] in [self.FRONTIER, self.CLOSED, self.ROUTE]:
self.grid[r][c] = self.EMPTY
if self.grid[r][c] == self.ROBOT:
self.robotStart = self.Cell(r, c)
self.searching = False
else:
for r in list(range(self.rows)):
for c in list(range(self.columns)):
self.grid[r][c] = self.EMPTY
self.robotStart = self.Cell(self.rows-2, 1)
self.targetPos = self.Cell(1, self.columns-2)
if self.selected_algo in ["A*", "Greedy"]:
self.robotStart.g = 0
self.robotStart.h = 0
self.robotStart.f = 0
self.expanded = 0
self.found = False
self.searching = False
self.endOfSearch = False
self.openSet.clear()
self.closedSet.clear()
self.openSet = [self.robotStart]
self.closedSet = []
self.grid[self.targetPos.row][self.targetPos.col] = self.TARGET
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.message.configure(text=self.MSG_DRAW_AND_SELECT)
self.repaint()
def repaint(self):
color = ""
for r in list(range(self.rows)):
for c in list(range(self.columns)):
if self.grid[r][c] == self.EMPTY:
color = "WHITE"
elif self.grid[r][c] == self.ROBOT:
color = "RED"
elif self.grid[r][c] == self.TARGET:
color = "GREEN"
elif self.grid[r][c] == self.OBST:
color = "BLACK"
elif self.grid[r][c] == self.FRONTIER:
color = "BLUE"
elif self.grid[r][c] == self.CLOSED:
color = "CYAN"
elif self.grid[r][c] == self.ROUTE:
color = "YELLOW"
self.paint_cell(r, c, color)
def paint_cell(self, row, col, color):
self.canvas.create_rectangle(1 + col * self.square_size, 1 + row * self.square_size,
1 + (col + 1) * self.square_size - 1, 1 + (row + 1) * self.square_size - 1,
width=0, fill=color)
def reset_click(self):
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.initialize_grid(False)
def maze_click(self):
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.initialize_grid(True)
def clear_click(self):
self.animation = False
self.realTime = False
for but in self.buttons:
but.configure(state="normal")
self.buttons[3].configure(fg="BLACK") # Real-Time button
self.slider.configure(state="normal")
for but in self.radio_buttons:
but.configure(state="normal")
self.diagonalBtn.configure(state="normal")
self.drawArrowsBtn.configure(state="normal")
self.fill_grid()
def real_time_click(self):
if self.realTime:
return
self.realTime = True
self.searching = True
# The Dijkstra's initialization should be done just before the
if self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.buttons[3].configure(fg="RED")
self.slider.configure(state="disabled")
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.real_Time_action()
def real_Time_action(self):
while not self.endOfSearch:
self.check_termination()
def step_by_step_click(self):
if self.found or self.endOfSearch:
return
if not self.searching and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.animation = False
self.searching = True
self.message.configure(text=self.MSG_SELECT_STEP_BY_STEP_ETC)
self.buttons[3].configure(state="disabled")
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.check_termination()
def animation_click(self):
self.animation = True
if not self.searching and self.selected_algo == "Dijkstra":
self.initialize_dijkstra()
self.searching = True
self.message.configure(text=self.MSG_SELECT_STEP_BY_STEP_ETC)
self.buttons[3].configure(state="disabled")
for but in self.radio_buttons:
but.configure(state="disabled")
self.diagonalBtn.configure(state="disabled")
self.drawArrowsBtn.configure(state="disabled")
self.delay = self.slider.get()
self.animation_action()
def animation_action(self):
if self.animation:
self.check_termination()
if self.endOfSearch:
return
self.canvas.after(self.delay, self.animation_action)
def about_click(self):
about_box = Toplevel(master=app)
about_box.title("")
about_box.geometry("340x160")
about_box.resizable(False, False)
self.center(about_box)
about_box.transient(app)
about_box.grab_set()
title = Label(about_box, text="Maze", width=20, anchor='center', fg='SANDY BROWN', font=("Helvetica", 20))
title.place(x=0, y=0)
version = Label(about_box, text="Version: 5.1", width=35, anchor='center', font=("Helvetica", 11, 'bold'))
version.place(x=0, y=35)
programmer = Label(about_box, text="Designer: Nikos Kanargias", width=35, anchor='center',
font=("Helvetica", 12))
programmer.place(x=0, y=60)
email = Label(about_box, text="E-mail: nkana@tee.gr", width=40, anchor='center', font=("Helvetica", 10))
email.place(x=0, y=80)
source_code = Label(about_box, text="Code and documentation", fg="blue", cursor="hand2", width=35,
anchor='center',
font=("Helvetica", 12))
f = font.Font(source_code, source_code.cget("font"))
f.configure(underline=True)
source_code.configure(font=f)
source_code.place(x=0, y=100)
source_code.bind("<Button-1>", self.source_code_callback)
self.CreateToolTip(source_code, "Click this link to retrieve code and documentation from DropBox")
video = Label(about_box, text="Watch demo video on YouTube", fg="blue", cursor="hand2", width=35,
anchor='center')
video.configure(font=f)
video.place(x=0, y=125)
video.bind("<Button-1>", self.video_callback)
self.CreateToolTip(video, "Click this link to watch a demo video on YouTube")
def check_termination(self):
if (self.selected_algo == "Dijkstra" and not self.graph) or\
self.selected_algo != "Dijkstra" and not self.openSet:
self.endOfSearch = True
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.message.configure(text=self.MSG_NO_SOLUTION)
self.buttons[4].configure(state="disabled")
self.buttons[5].configure(state="disabled")
self.slider.configure(state="disabled")
self.repaint()
if self.drawArrows.get():
self.draw_arrows()
else:
self.expand_node()
if self.found:
self.endOfSearch = True
self.plot_route()
self.buttons[4].configure(state="disabled")
self.buttons[5].configure(state="disabled")
self.slider.configure(state="disabled")
def expand_node(self):
if self.selected_algo == "Dijkstra":
# 11: while Q is not empty:
if not self.graph:
return
# 12: u := vertex in Q (graph) with smallest distance in dist[] ;
# 13: remove u from Q (graph);
u = self.graph.pop(0)
# Add vertex u in closed set
self.closedSet.append(u)
# If target has been found ...
if u == self.targetPos:
self.found = True
return
# Counts nodes that have expanded.
self.expanded += 1
# Update the color of the cell
self.grid[u.row][u.col] = self.CLOSED
# paint the cell
self.paint_cell(u.row, u.col, "CYAN")
# 14: if dist[u] = infinity:
if u.dist == self.INFINITY:
# ... then there is no solution.
# 15: break;
return
# 16: end if
# Create the neighbors of u
neighbors = self.create_successors(u, False)
# 18: for each neighbor v of u:
for v in neighbors:
# 20: alt := dist[u] + dist_between(u, v) ;
alt = u.dist + self.dist_between(u, v)
# 21: if alt < dist[v]:
if alt < v.dist:
# 22: dist[v] := alt ;
v.dist = alt
# 23: previous[v] := u ;
v.prev = u
# Update the color of the cell
self.grid[v.row][v.col] = self.FRONTIER
# paint the cell
self.paint_cell(v.row, v.col, "BLUE")
# 24: decrease-key v in Q;
# (sort list of nodes with respect to dist)
self.graph.sort(key=attrgetter("dist"))
# The handling of the other four algorithms
else:
if self.selected_algo in ["DFS", "BFS"]:
# Here is the 3rd step of the algorithms DFS and BFS
# 3. Remove the first state, Si, from OPEN SET ...
current = self.openSet.pop(0)
else:
# Here is the 3rd step of the algorithms A* and Greedy
# 3. Remove the first state, Si, from OPEN SET,
# for which f(Si) ≤ f(Sj) for all other
# open states Sj ...
# (sort first OPEN SET list with respect to 'f')
self.openSet.sort(key=attrgetter("f"))
current = self.openSet.pop(0)
# ... and add it to CLOSED SET.
self.closedSet.insert(0, current)
# Update the color of the cell
self.grid[current.row][current.col] = self.CLOSED
# paint the cell
self.paint_cell(current.row, current.col, "CYAN")
# If the selected node is the target ...
if current == self.targetPos:
# ... then terminate etc
last = self.targetPos
last.prev = current.prev
self.closedSet.append(last)
self.found = True
return
# Count nodes that have been expanded.
self.expanded += 1
# Here is the 4rd step of the algorithms
# 4. Create the successors of Si, based on actions
# that can be implemented on Si.
# Each successor has a pointer to the Si, as its predecessor.
# In the case of DFS and BFS algorithms, successors should not
# belong neither to the OPEN SET nor the CLOSED SET.
successors = self.create_successors(current, False)
# Here is the 5th step of the algorithms
# 5. For each successor of Si, ...
for cell in successors:
# ... if we are running DFS ...
if self.selected_algo == "DFS":
# ... add the successor at the beginning of the list OPEN SET
self.openSet.insert(0, cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if we are runnig BFS ...
elif self.selected_algo == "BFS":
# ... add the successor at the end of the list OPEN SET
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if we are running A* or Greedy algorithms (step 5 of A* algorithm) ...
elif self.selected_algo in ["A*", "Greedy"]:
# ... calculate the value f(Sj) ...
dxg = current.col - cell.col
dyg = current.row - cell.row
dxh = self.targetPos.col - cell.col
dyh = self.targetPos.row - cell.row
if self.diagonal.get():
# with diagonal movements, calculate the Euclidean distance
if self.selected_algo == "Greedy":
# especially for the Greedy ...
cell.g = 0
else:
cell.g = current.g + math.sqrt(dxg*dxg + dyg*dyg)
cell.h = math.sqrt(dxh*dxh + dyh*dyh)
else:
# without diagonal movements, calculate the Manhattan distance
if self.selected_algo == "Greedy":
# especially for the Greedy ...
cell.g = 0
else:
cell.g = current.g + abs(dxg) + abs(dyg)
cell.h = abs(dxh) + abs(dyh)
cell.f = cell.g+cell.h
# ... If Sj is neither in the OPEN SET nor in the CLOSED SET states ...
if cell not in self.openSet and cell not in self.closedSet:
# ... then add Sj in the OPEN SET ...
# ... evaluated as f(Sj)
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# Else ...
else:
# ... if already belongs to the OPEN SET, then ...
if cell in self.openSet:
open_index = self.openSet.index(cell)
# ... compare the new value assessment with the old one.
# If old <= new ...
if self.openSet[open_index].f <= cell.f:
# ... then eject the new node with state Sj.
# (ie do nothing for this node).
pass
# Else, ...
else:
# ... remove the element (Sj, old) from the list
# to which it belongs ...
self.openSet.pop(open_index)
# ... and add the item (Sj, new) to the OPEN SET.
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
# ... if already belongs to the CLOSED SET, then ...
elif cell in self.closedSet:
closed_index = self.closedSet.index(cell)
# ... compare the new value assessment with the old one.
# If old <= new ...
if self.closedSet[closed_index].f <= cell.f:
# ... then eject the new node with state Sj.
# (ie do nothing for this node).
pass
# Else, ...
else:
# ... remove the element (Sj, old) from the list
# to which it belongs ...
self.closedSet.pop(closed_index)
# ... and add the item (Sj, new) to the OPEN SET.
self.openSet.append(cell)
# Update the color of the cell
self.grid[cell.row][cell.col] = self.FRONTIER
# paint the cell
self.paint_cell(cell.row, cell.col, "BLUE")
def create_successors(self, current, make_connected):
r = current.row
c = current.col
# We create an empty list for the successors of the current cell.
temp = []
# With diagonal movements priority is:
# 1: Up 2: Up-right 3: Right 4: Down-right
# 5: Down 6: Down-left 7: Left 8: Up-left
# Without diagonal movements the priority is:
# 1: Up 2: Right 3: Down 4: Left
# If not at the topmost limit of the grid
# and the up-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r > 0 and self.grid[r-1][c] != self.OBST and\
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c) in self.openSet and not self.Cell(r-1, c) in self.closedSet)):
cell = self.Cell(r-1, c)
# In the case of Dijkstra's algorithm we can not append to
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-side cell so it points the current one ...
cell.prev = current
# ... and add the up-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the topmost nor at the rightmost border of the grid
# and the up-right-side cell is not an obstacle
# and one of the upper side or right side cells are not obstacles
# (because it is not reasonable to allow the robot to pass through a "slot")
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor CLOSED SET ...
if r > 0 and c < self.columns-1 and self.grid[r-1][c+1] != self.OBST and \
(self.grid[r-1][c] != self.OBST or self.grid[r][c+1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c+1) in self.openSet and not self.Cell(r-1, c+1) in self.closedSet)):
cell = self.Cell(r-1, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-right-side cell so it points the current one ...
cell.prev = current
# ... and add the up-right-side cell to the successors of the current one.
temp.append(cell)
# If not at the rightmost limit of the grid
# and the right-side cell is not an obstacle ...
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if c < self.columns-1 and self.grid[r][c+1] != self.OBST and\
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r, c+1) in self.openSet and not self.Cell(r, c+1) in self.closedSet)):
cell = self.Cell(r, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the right-side cell so it points the current one ...
cell.prev = current
# ... and add the right-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the lowermost nor at the rightmost border of the grid
# and the down-right-side cell is not an obstacle
# and one of the down-side or right-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and c < self.columns-1 and self.grid[r+1][c+1] != self.OBST and \
(self.grid[r+1][c] != self.OBST or self.grid[r][c+1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c+1) in self.openSet and not self.Cell(r+1, c+1) in self.closedSet)):
cell = self.Cell(r+1, c+1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the downr-right-side cell so it points the current one ...
cell.prev = current
# ... and add the down-right-side cell to the successors of the current one.
temp.append(cell)
# If not at the lowermost limit of the grid
# and the down-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and self.grid[r+1][c] != self.OBST and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c) in self.openSet and not self.Cell(r+1, c) in self.closedSet)):
cell = self.Cell(r+1, c)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the down-side cell so it points the current one ...
cell.prev = current
# ... and add the down-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the lowermost nor at the leftmost border of the grid
# and the down-left-side cell is not an obstacle
# and one of the down-side or left-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r < self.rows-1 and c > 0 and self.grid[r+1][c-1] != self.OBST and \
(self.grid[r+1][c] != self.OBST or self.grid[r][c-1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r+1, c-1) in self.openSet and not self.Cell(r+1, c-1) in self.closedSet)):
cell = self.Cell(r+1, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the down-left-side cell so it points the current one ...
cell.prev = current
# ... and add the down-left-side cell to the successors of the current one.
temp.append(cell)
# If not at the leftmost limit of the grid
# and the left-side cell is not an obstacle
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if c > 0 and self.grid[r][c-1] != self.OBST and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r, c-1) in self.openSet and not self.Cell(r, c-1) in self.closedSet)):
cell = self.Cell(r, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the left-side cell so it points the current one ...
cell.prev = current
# ... and add the left-side cell to the successors of the current one.
temp.append(cell)
if self.diagonal.get():
# If we are not even at the topmost nor at the leftmost border of the grid
# and the up-left-side cell is not an obstacle
# and one of the up-side or left-side cells are not obstacles
# and (only in the case are not running the A* or Greedy)
# not already belongs neither to the OPEN SET nor to the CLOSED SET ...
if r > 0 and c > 0 and self.grid[r-1][c-1] != self.OBST and \
(self.grid[r-1][c] != self.OBST or self.grid[r][c-1] != self.OBST) and \
(self.selected_algo in ["A*", "Greedy", "Dijkstra"] or
(self.selected_algo in ["DFS", "BFS"]
and not self.Cell(r-1, c-1) in self.openSet and not self.Cell(r-1, c-1) in self.closedSet)):
cell = self.Cell(r-1, c-1)
if self.selected_algo == "Dijkstra":
if make_connected:
temp.append(cell)
elif cell in self.graph:
graph_index = self.graph.index(cell)
temp.append(self.graph[graph_index])
else:
# ... update the pointer of the up-left-side cell so it points the current one ...
cell.prev = current
# ... and add the up-left-side cell to the successors of the current one.
temp.append(cell)
# When DFS algorithm is in use, cells are added one by one at the beginning of the
# OPEN SET list. Because of this, we must reverse the order of successors formed,
# so the successor corresponding to the highest priority, to be placed the first in the list.
# For the Greedy, A* and Dijkstra's no issue, because the list is sorted
if self.selected_algo == "DFS":
return reversed(temp)
else:
return temp
def dist_between(self, u, v):
dx = u.col - v.col
dy = u.row - v.row
if self.diagonal.get():
return math.sqrt(dx*dx + dy*dy)
else:
return abs(dx) + abs(dy)
def plot_route(self):
self.repaint()
self.searching = False
steps = 0
distance = 0.0
index = self.closedSet.index(self.targetPos)
cur = self.closedSet[index]
self.grid[cur.row][cur.col] = self.TARGET
self.paint_cell(cur.row, cur.col, "GREEN")
while cur != self.robotStart:
steps += 1
if self.diagonal.get():
dx = cur.col - cur.prev.col
dy = cur.row - cur.prev.row
distance += math.sqrt(dx*dx + dy*dy)
else:
distance += 1
cur = cur.prev
self.grid[cur.row][cur.col] = self.ROUTE
self.paint_cell(cur.row, cur.col, "YELLOW")
self.grid[self.robotStart.row][self.robotStart.col] = self.ROBOT
self.paint_cell(self.robotStart.row, self.robotStart.col, "RED")
if self.drawArrows.get():
self.draw_arrows()
msg = "Nodes expanded: {0}, Steps: {1}, Distance: {2:.3f}".format(self.expanded, steps, distance)
self.message.configure(text=msg)
def find_connected_component(self, v):
stack = [v]
self.graph.append(v)
while stack:
v = stack.pop()
successors = self.create_successors(v, True)
for c in successors:
if c not in self.graph:
stack.append(c)
self.graph.append(c)
def initialize_dijkstra(self):
self.graph.clear()
self.find_connected_component(self.robotStart)
# 2: for each vertex v in Graph;
for v in self.graph:
# 3: dist[v] := infinity ;
v.dist = self.INFINITY
# 5: previous[v] := undefined ;
v.prev = None
# 8: dist[source] := 0;
self.graph[self.graph.index(self.robotStart)].dist = 0
# 9: Q := the set of all nodes in Graph;
# Instead of the variable Q we will use the list
# 'graph' itself, which has already been initialised.
# Sorts the list of nodes with respect to 'dist'.
self.graph.sort(key=attrgetter("dist"))
# Initializes the list of closed nodes
self.closedSet.clear()
def draw_arrows(self):
# We draw black arrows from each open or closed state to its predecessor.
for r in range(self.rows):
for c in range(self.columns):
tail = head = cell = self.Cell(r, c)
# If the current cell is an open state, or is a closed state
# but not the initial position of the robot
if self.grid[r][c] in [self.FRONTIER, self.CLOSED] and not cell == self.robotStart:
# The tail of the arrow is the current cell, while
# the arrowhead is the predecessor cell.
if self.grid[r][c] == self.FRONTIER:
if self.selected_algo == "Dijkstra":
tail = self.graph[self.graph.index(cell)]
head = tail.prev
else:
tail = self.openSet[self.openSet.index(cell)]
head = tail.prev
elif self.grid[r][c] == self.CLOSED:
tail = self.closedSet[self.closedSet.index(cell)]
head = tail.prev
self.draw_arrow(tail, head, self.arrow_size, "BLACK", 2 if self.square_size >= 25 else 1)
if self.found:
# We draw red arrows along the path from robotStart to targetPos.
# index = self.closedSet.index(self.targetPos)
cur = self.closedSet[self.closedSet.index(self.targetPos)]
while cur != self.robotStart:
head = cur
cur = cur.prev
tail = cur
self.draw_arrow(tail, head, self.arrow_size, "RED", 2 if self.square_size >= 25 else 1)
def draw_arrow(self, tail, head, a, color, width):
# The coordinates of the center of the tail cell
x1 = 1 + tail.col * self.square_size + self.square_size / 2
y1 = 1 + tail.row * self.square_size + self.square_size / 2
# The coordinates of the center of the head cell
x2 = 1 + head.col * self.square_size + self.square_size / 2
y2 = 1 + head.row * self.square_size + self.square_size / 2
sin20 = math.sin(20*math.pi/180)
cos20 = math.cos(20*math.pi/180)
sin25 = math.sin(25*math.pi/180)
cos25 = math.cos(25*math.pi/180)
u3 = v3 = u4 = v4 = 0
if x1 == x2 and y1 > y2: # up
u3 = x2 - a*sin20
v3 = y2 + a*cos20
u4 = x2 + a*sin20
v4 = v3
elif x1 < x2 and y1 > y2: # up-right
u3 = x2 - a*cos25
v3 = y2 + a*sin25
u4 = x2 - a*sin25
v4 = y2 + a*cos25
elif x1 < x2 and y1 == y2: # right
u3 = x2 - a*cos20
v3 = y2 - a*sin20
u4 = u3
v4 = y2 + a*sin20
elif x1 < x2 and y1 < y2: # righr-down
u3 = x2 - a*cos25
v3 = y2 - a*sin25
u4 = x2 - a*sin25
v4 = y2 - a*cos25
elif x1 == x2 and y1 < y2: # down
u3 = x2 - a*sin20
v3 = y2 - a*cos20
u4 = x2 + a*sin20
v4 = v3
elif x1 > x2 and y1 < y2: # left-down
u3 = x2 + a*sin25
v3 = y2 - a*cos25
u4 = x2 + a*cos25
v4 = y2 - a*sin25
elif x1 > x2 and y1 == y2: # left
u3 = x2 + a*cos20
v3 = y2 - a*sin20
u4 = u3
v4 = y2 + a*sin20
elif x1 > x2 and y1 > y2: # left-up
u3 = x2 + a*sin25
v3 = y2 + a*cos25
u4 = x2 + a*cos25
v4 = y2 + a*sin25
self.canvas.create_line(x1, y1, x2, y2, fill=color, width=width)
self.canvas.create_line(x2, y2, u3, v3, fill=color, width=width)
self.canvas.create_line(x2, y2, u4, v4, fill=color, width=width)
@staticmethod
def center(window):
window.update_idletasks()
w = window.winfo_screenwidth()
h = window.winfo_screenheight()
size = tuple(int(_) for _ in window.geometry().split('+')[0].split('x'))
x = w / 2 - size[0] / 2
y = h / 2 - size[1] / 2
window.geometry("%dx%d+%d+%d" % (size + (x, y)))
@staticmethod
def source_code_callback(self):
webbrowser.open_new(r"https://goo.gl/tRaLfe")
@staticmethod
def video_callback(self):
webbrowser.open_new(r"https://youtu.be/7GLqy61X2oU")
def on_closing():
if messagebox.askokcancel("Quit", "Do you want to quit?"):
os._exit(0)
if __name__ == '__main__':
app = Tk()
app.protocol("WM_DELETE_WINDOW", on_closing)
app.title("Maze 5.1")
app.geometry("693x545")
app.resizable(False, False)
Maze51(app)
app.mainloop()
| true | true |
f7fe8c1d16ac56938049fc68ef9d8ee45457eee9 | 6,942 | py | Python | clinicaldg/eicu/data.py | MLforHealth/ClinicalDG | 2de4a8e155231f07d80036504a6f49b50004654e | [
"MIT"
] | 18 | 2021-03-23T07:45:56.000Z | 2022-03-29T00:42:04.000Z | clinicaldg/eicu/data.py | MLforHealth/ClinicalDG | 2de4a8e155231f07d80036504a6f49b50004654e | [
"MIT"
] | 2 | 2022-03-20T16:57:28.000Z | 2022-03-22T03:56:46.000Z | clinicaldg/eicu/data.py | MLforHealth/ClinicalDG | 2de4a8e155231f07d80036504a6f49b50004654e | [
"MIT"
] | 1 | 2022-03-17T19:03:15.000Z | 2022-03-17T19:03:15.000Z | import pandas as pd
pd.options.mode.chained_assignment = None
import numpy as np
from clinicaldg.eicu.data_extraction.data_extraction_mortality import data_extraction_mortality
import clinicaldg.eicu.Constants as Constants
from sklearn.preprocessing import StandardScaler, LabelEncoder
from torch.utils.data import ConcatDataset, Dataset
hospitals = pd.read_csv((Constants.eicu_dir/'hospital.csv'))
hospitals['region'] = hospitals['region'].fillna('Missing')
patients = pd.read_csv((Constants.eicu_dir/'patient.csv'))[['patientunitstayid', 'hospitalid', 'gender']]
class LabelEncoderExt(object):
'''
Label encoder, but when encountering an unseen label on the test set, will set to "Missing"
'''
def __init__(self):
self.label_encoder = LabelEncoder()
def fit(self, data_list):
self.label_encoder = self.label_encoder.fit(list(map(str, list(data_list))) + ['Missing'])
self.classes_ = self.label_encoder.classes_
return self
def transform(self, data_list):
data_list = list(map(str, list(data_list)))
for unique_item in np.unique(data_list):
if unique_item not in self.label_encoder.classes_:
data_list = ['Missing' if x==unique_item else x for x in data_list]
return self.label_encoder.transform(data_list)
class AugmentedDataset():
def __init__(self, augs = [], train_pct = 0.7, val_pct = 0.1):
self.reg_mort, self.reg_pat, self.scalers, self.labelencoders = self._get_mortality_data(train_pct, val_pct)
for a in augs:
a.augment(self.reg_mort, self.reg_pat)
def get_torch_dataset(self, envs, dset):
'''
envs: a list of region names
dset: one of ['train', 'val', 'test']. For the test environment, use "test" for dset
'''
datasets = []
for r in envs:
datasets.append(eICUDataset(self.reg_mort[r][self.reg_mort[r]['fold'] == dset], self.reg_pat[r][self.reg_pat[r]['fold'] == dset]))
return ConcatDataset(datasets)
def get_num_levels(self):
return ({i: len(self.labelencoders[i].classes_) for i in Constants.ts_cat_features},
{i: len(self.labelencoders[i].classes_) for i in Constants.static_cat_features},
)
def _get_mortality_data(self, train_pct, val_pct):
mort_df = data_extraction_mortality(str(Constants.benchmark_dir))
targets = mort_df.groupby('patientunitstayid').agg({'hospitaldischargestatus': 'first'}).reset_index()
pat_df = pd.merge(patients, hospitals, on = 'hospitalid', how = 'left')
pat_df = pd.merge(pat_df, targets, on = 'patientunitstayid', how = 'inner').rename(columns = {'hospitaldischargestatus': 'target'})
pat_df = pat_df[pat_df.patientunitstayid.isin(mort_df.patientunitstayid)].sample(frac = 1) # shuffle
pat_df['fold'] = ''
pat_df['fold'].iloc[:int(len(pat_df)*train_pct)] = 'train'
pat_df['fold'].iloc[int(len(pat_df)*train_pct):int(len(pat_df)*(train_pct + val_pct))] = 'val'
pat_df['fold'].iloc[int(len(pat_df)*(train_pct + val_pct)):] = 'test'
mort_df = mort_df.merge(pat_df[['patientunitstayid', 'fold']], on = 'patientunitstayid')
# make sure everyone has exactly 48h hours of data
## make multiindex with 48h
## groupby and ffill
## fill any remaining missing features with normal_values
iterables = [np.unique(mort_df['patientunitstayid']), list(range(1, mort_df.itemoffset.max()+1))]
multiind = pd.MultiIndex.from_product(iterables, names = ['patientunitstayid', 'itemoffset'])
ind_df = pd.DataFrame(index = multiind)
mort_df = pd.merge(ind_df, mort_df, left_index = True, right_on = ['patientunitstayid', 'itemoffset'], how = 'left')
mort_df = mort_df.set_index(['patientunitstayid', 'itemoffset']).sort_index().groupby('patientunitstayid').ffill()
for back_col in ['hospitaldischargestatus', 'fold'] + Constants.static_cont_features + Constants.static_cat_features:
mort_df[back_col] = mort_df[back_col].fillna(method = 'backfill')
for feat, val in Constants.normal_values.items():
mort_df[feat] = mort_df[feat].fillna(val)
# scale continuous and static ts features
scalers = {}
for feat in Constants.ts_cont_features + Constants.static_cont_features:
scalers[feat] = StandardScaler().fit(mort_df.loc[mort_df.fold == 'train', feat].values.reshape(-1, 1))
mort_df[feat] = scalers[feat].transform(mort_df[feat].values.reshape(-1, 1))[:, 0]
# encode continuous and static cat features
labelencoders, num_encodings = {}, {}
for feat in Constants.ts_cat_features + Constants.static_cat_features:
mort_df[feat] = mort_df[feat].fillna('Missing')
labelencoders[feat] = LabelEncoderExt().fit(mort_df.loc[mort_df.fold == 'train', feat])
mort_df[feat] = labelencoders[feat].transform(mort_df[feat])
num_encodings[feat] = len(labelencoders[feat].classes_)
reg_mort, reg_pat = {}, {}
for reg in pat_df.region.unique():
sub_pat = pat_df[pat_df.region == reg]
sub = mort_df[mort_df.index.get_level_values(0).isin(sub_pat.patientunitstayid)]
reg_mort[reg] = sub
reg_pat[reg] = sub_pat.set_index('patientunitstayid')
return reg_mort, reg_pat, scalers, labelencoders
class eICUDataset(Dataset):
def __init__(self, mort_df, pat_df):
self.mort_df = mort_df
self.pat_df = pat_df
def __len__(self):
return self.pat_df.shape[0]
def __getitem__(self, idx):
pat_id = self.pat_df.index[idx]
mort_data = self.mort_df.loc[pat_id]
ts_cont_feats = mort_data[Constants.ts_cont_features].values
ts_cat_feats = mort_data[Constants.ts_cat_features].values
static_not_in_mort = [i for i in Constants.static_cont_features if i not in self.mort_df]
static_in_mort = [i for i in Constants.static_cont_features if i in self.mort_df]
static_cont_feats = np.concatenate((mort_data[static_in_mort].iloc[0].values, self.pat_df.loc[pat_id, static_not_in_mort].values)).astype(float)
static_cat_feats = mort_data[Constants.static_cat_features].iloc[0].values
return ({'pat_id': pat_id,
'ts_cont_feats': ts_cont_feats,
'ts_cat_feats': ts_cat_feats,
'static_cont_feats': static_cont_feats,
'static_cat_feats': static_cat_feats,
'gender': int(self.pat_df.loc[pat_id, 'gender'].strip() == 'Male')},
self.pat_df.loc[pat_id, 'target']) | 49.942446 | 152 | 0.644771 | import pandas as pd
pd.options.mode.chained_assignment = None
import numpy as np
from clinicaldg.eicu.data_extraction.data_extraction_mortality import data_extraction_mortality
import clinicaldg.eicu.Constants as Constants
from sklearn.preprocessing import StandardScaler, LabelEncoder
from torch.utils.data import ConcatDataset, Dataset
hospitals = pd.read_csv((Constants.eicu_dir/'hospital.csv'))
hospitals['region'] = hospitals['region'].fillna('Missing')
patients = pd.read_csv((Constants.eicu_dir/'patient.csv'))[['patientunitstayid', 'hospitalid', 'gender']]
class LabelEncoderExt(object):
def __init__(self):
self.label_encoder = LabelEncoder()
def fit(self, data_list):
self.label_encoder = self.label_encoder.fit(list(map(str, list(data_list))) + ['Missing'])
self.classes_ = self.label_encoder.classes_
return self
def transform(self, data_list):
data_list = list(map(str, list(data_list)))
for unique_item in np.unique(data_list):
if unique_item not in self.label_encoder.classes_:
data_list = ['Missing' if x==unique_item else x for x in data_list]
return self.label_encoder.transform(data_list)
class AugmentedDataset():
def __init__(self, augs = [], train_pct = 0.7, val_pct = 0.1):
self.reg_mort, self.reg_pat, self.scalers, self.labelencoders = self._get_mortality_data(train_pct, val_pct)
for a in augs:
a.augment(self.reg_mort, self.reg_pat)
def get_torch_dataset(self, envs, dset):
datasets = []
for r in envs:
datasets.append(eICUDataset(self.reg_mort[r][self.reg_mort[r]['fold'] == dset], self.reg_pat[r][self.reg_pat[r]['fold'] == dset]))
return ConcatDataset(datasets)
def get_num_levels(self):
return ({i: len(self.labelencoders[i].classes_) for i in Constants.ts_cat_features},
{i: len(self.labelencoders[i].classes_) for i in Constants.static_cat_features},
)
def _get_mortality_data(self, train_pct, val_pct):
mort_df = data_extraction_mortality(str(Constants.benchmark_dir))
targets = mort_df.groupby('patientunitstayid').agg({'hospitaldischargestatus': 'first'}).reset_index()
pat_df = pd.merge(patients, hospitals, on = 'hospitalid', how = 'left')
pat_df = pd.merge(pat_df, targets, on = 'patientunitstayid', how = 'inner').rename(columns = {'hospitaldischargestatus': 'target'})
pat_df = pat_df[pat_df.patientunitstayid.isin(mort_df.patientunitstayid)].sample(frac = 1)
pat_df['fold'] = ''
pat_df['fold'].iloc[:int(len(pat_df)*train_pct)] = 'train'
pat_df['fold'].iloc[int(len(pat_df)*train_pct):int(len(pat_df)*(train_pct + val_pct))] = 'val'
pat_df['fold'].iloc[int(len(pat_df)*(train_pct + val_pct)):] = 'test'
mort_df = mort_df.merge(pat_df[['patientunitstayid', 'fold']], on = 'patientunitstayid')
f.itemoffset.max()+1))]
multiind = pd.MultiIndex.from_product(iterables, names = ['patientunitstayid', 'itemoffset'])
ind_df = pd.DataFrame(index = multiind)
mort_df = pd.merge(ind_df, mort_df, left_index = True, right_on = ['patientunitstayid', 'itemoffset'], how = 'left')
mort_df = mort_df.set_index(['patientunitstayid', 'itemoffset']).sort_index().groupby('patientunitstayid').ffill()
for back_col in ['hospitaldischargestatus', 'fold'] + Constants.static_cont_features + Constants.static_cat_features:
mort_df[back_col] = mort_df[back_col].fillna(method = 'backfill')
for feat, val in Constants.normal_values.items():
mort_df[feat] = mort_df[feat].fillna(val)
scalers = {}
for feat in Constants.ts_cont_features + Constants.static_cont_features:
scalers[feat] = StandardScaler().fit(mort_df.loc[mort_df.fold == 'train', feat].values.reshape(-1, 1))
mort_df[feat] = scalers[feat].transform(mort_df[feat].values.reshape(-1, 1))[:, 0]
labelencoders, num_encodings = {}, {}
for feat in Constants.ts_cat_features + Constants.static_cat_features:
mort_df[feat] = mort_df[feat].fillna('Missing')
labelencoders[feat] = LabelEncoderExt().fit(mort_df.loc[mort_df.fold == 'train', feat])
mort_df[feat] = labelencoders[feat].transform(mort_df[feat])
num_encodings[feat] = len(labelencoders[feat].classes_)
reg_mort, reg_pat = {}, {}
for reg in pat_df.region.unique():
sub_pat = pat_df[pat_df.region == reg]
sub = mort_df[mort_df.index.get_level_values(0).isin(sub_pat.patientunitstayid)]
reg_mort[reg] = sub
reg_pat[reg] = sub_pat.set_index('patientunitstayid')
return reg_mort, reg_pat, scalers, labelencoders
class eICUDataset(Dataset):
def __init__(self, mort_df, pat_df):
self.mort_df = mort_df
self.pat_df = pat_df
def __len__(self):
return self.pat_df.shape[0]
def __getitem__(self, idx):
pat_id = self.pat_df.index[idx]
mort_data = self.mort_df.loc[pat_id]
ts_cont_feats = mort_data[Constants.ts_cont_features].values
ts_cat_feats = mort_data[Constants.ts_cat_features].values
static_not_in_mort = [i for i in Constants.static_cont_features if i not in self.mort_df]
static_in_mort = [i for i in Constants.static_cont_features if i in self.mort_df]
static_cont_feats = np.concatenate((mort_data[static_in_mort].iloc[0].values, self.pat_df.loc[pat_id, static_not_in_mort].values)).astype(float)
static_cat_feats = mort_data[Constants.static_cat_features].iloc[0].values
return ({'pat_id': pat_id,
'ts_cont_feats': ts_cont_feats,
'ts_cat_feats': ts_cat_feats,
'static_cont_feats': static_cont_feats,
'static_cat_feats': static_cat_feats,
'gender': int(self.pat_df.loc[pat_id, 'gender'].strip() == 'Male')},
self.pat_df.loc[pat_id, 'target']) | true | true |
f7fe8c4804d16ffd1db3a338967955f15498fe1f | 28,269 | py | Python | src/opencmiss/neon/ui/mainwindow.py | hsorby/neon | 0fcbddfca8baf50d8ecc310a7cb393ffdec88431 | [
"Apache-2.0"
] | null | null | null | src/opencmiss/neon/ui/mainwindow.py | hsorby/neon | 0fcbddfca8baf50d8ecc310a7cb393ffdec88431 | [
"Apache-2.0"
] | 2 | 2016-01-15T04:17:35.000Z | 2016-02-26T04:01:02.000Z | src/opencmiss/neon/ui/mainwindow.py | hsorby/neon | 0fcbddfca8baf50d8ecc310a7cb393ffdec88431 | [
"Apache-2.0"
] | 6 | 2015-11-29T20:57:16.000Z | 2021-06-08T04:02:26.000Z | """
Copyright 2015 University of Auckland
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import os.path
from PySide2 import QtCore, QtWidgets
from opencmiss.neon.ui.ui_mainwindow import Ui_MainWindow
from opencmiss.neon.undoredo.commands import CommandEmpty
from opencmiss.neon.ui.views.visualisationview import VisualisationView
from opencmiss.neon.ui.dialogs.aboutdialog import AboutDialog
from opencmiss.neon.ui.editors.loggereditorwidget import LoggerEditorWidget
from opencmiss.zincwidgets.regioneditorwidget import RegionEditorWidget
from opencmiss.zincwidgets.materialeditorwidget import MaterialEditorWidget
from opencmiss.zincwidgets.modelsourceseditorwidget import ModelSourcesEditorWidget, ModelSourcesModel
from opencmiss.zincwidgets.sceneviewereditorwidget import SceneviewerEditorWidget
from opencmiss.zincwidgets.sceneeditorwidget import SceneEditorWidget
from opencmiss.zincwidgets.spectrumeditorwidget import SpectrumEditorWidget
from opencmiss.zincwidgets.tessellationeditorwidget import TessellationEditorWidget
from opencmiss.zincwidgets.timeeditorwidget import TimeEditorWidget
from opencmiss.zincwidgets.fieldlisteditorwidget import FieldListEditorWidget
from opencmiss.neon.settings.mainsettings import VERSION_MAJOR
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, model):
super(MainWindow, self).__init__()
self._model = model
self._ui = Ui_MainWindow()
self._ui.setupUi(self)
self._visualisation_view_state_update_pending = False
# List of possible views
self._visualisation_view = VisualisationView(self)
self._visualisation_view_ready = False
self._view_states = {self._visualisation_view: ''}
# self._view_states[self._problem_view] = ''
# self._view_states[self._simulation_view] = ''
view_list = [self._visualisation_view]
self._location = None # The last location/directory used by the application
self._current_view = None
self._undoRedoStack = QtWidgets.QUndoStack(self)
# Pre-create dialogs
#self._createDialogs()
self._setupEditors()
self._registerEditors()
self._setupViews(view_list)
self._setupOtherWindows()
self._registerOtherWindows()
self._addDockWidgets()
self._makeConnections()
# Set the undo redo stack state
self._undoRedoStack.push(CommandEmpty())
self._undoRedoStack.clear()
self._updateUi()
self._readSettings()
self._onDocumentChanged()
def _makeConnections(self):
self._ui.action_Quit.triggered.connect(self.close)
self._ui.action_New.triggered.connect(self._newTriggered)
self._ui.action_Open.triggered.connect(self._openTriggered)
self._ui.action_About.triggered.connect(self._aboutTriggered)
self._ui.action_Save.triggered.connect(self._saveTriggered)
self._ui.action_Save_As.triggered.connect(self._saveAsTriggered)
self._ui.action_Snapshot.triggered.connect(self._snapshotTriggered)
self._ui.actionPreferences.triggered.connect(self._preferencesTriggered)
self._ui.action_Clear.triggered.connect(self._clearTriggered)
self._undoRedoStack.indexChanged.connect(self._undoRedoStackIndexChanged)
self._undoRedoStack.canUndoChanged.connect(self._ui.action_Undo.setEnabled)
self._undoRedoStack.canRedoChanged.connect(self._ui.action_Redo.setEnabled)
self._visualisation_view.graphicsInitialized.connect(self._visualisationViewReady)
# self._snapshot_dialog.sceneviewerInitialized.connect(self._snapshotDialogReady)
self.dockWidgetContentsRegionEditor.regionSelected.connect(self._regionSelected)
# self.dockWidgetContentsProblemEditor.runClicked.connect(self._runSimulationClicked)
# self.dockWidgetContentsSimulationEditor.visualiseClicked.connect(self._visualiseSimulationClicked)
self._model.documentChanged.connect(self._onDocumentChanged)
def _updateUi(self):
modified = self._model.isModified()
self._ui.action_Save.setEnabled(modified)
recents = self._model.getRecents()
self._ui.action_Clear.setEnabled(len(recents))
def _addDockWidgets(self):
self.addDockWidget(QtCore.Qt.LeftDockWidgetArea, self.dockWidgetModelSourcesEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetTessellationEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSpectrumEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetMaterialEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSceneEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetRegionEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSceneviewerEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetFieldEditor)
self.addDockWidget(QtCore.Qt.BottomDockWidgetArea, self.dockWidgetLoggerEditor)
self.tabifyDockWidget(self.dockWidgetLoggerEditor, self.dockWidgetTimeEditor)
def _setupEditors(self):
self.dockWidgetRegionEditor = QtWidgets.QDockWidget(self)
self.dockWidgetRegionEditor.setWindowTitle('Region Editor')
self.dockWidgetRegionEditor.setObjectName("dockWidgetRegionEditor")
self.dockWidgetContentsRegionEditor = RegionEditorWidget()
self.dockWidgetContentsRegionEditor.setObjectName("dockWidgetContentsRegionEditor")
self.dockWidgetRegionEditor.setWidget(self.dockWidgetContentsRegionEditor)
self.dockWidgetRegionEditor.setHidden(True)
self.dockWidgetMaterialEditor = QtWidgets.QDockWidget(self)
self.dockWidgetMaterialEditor.setWindowTitle('Material Editor')
self.dockWidgetMaterialEditor.setObjectName("dockWidgetMaterialEditor")
self.dockWidgetContentsMaterialEditor = MaterialEditorWidget()
self.dockWidgetContentsMaterialEditor.setObjectName("dockWidgetContentsMaterialEditor")
self.dockWidgetMaterialEditor.setWidget(self.dockWidgetContentsMaterialEditor)
self.dockWidgetMaterialEditor.setHidden(True)
self.dockWidgetModelSourcesEditor = QtWidgets.QDockWidget(self)
self.dockWidgetModelSourcesEditor.setWindowTitle('Model Sources Editor')
self.dockWidgetModelSourcesEditor.setObjectName("dockWidgetModelSourcesEditor")
self.dockWidgetContentsModelSourcesEditor = ModelSourcesEditorWidget()
self.dockWidgetContentsModelSourcesEditor.setObjectName("dockWidgetContentsModelSourcesEditor")
self.dockWidgetModelSourcesEditor.setWidget(self.dockWidgetContentsModelSourcesEditor)
self.dockWidgetModelSourcesEditor.setHidden(False)
self.dockWidgetSceneEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSceneEditor.setWindowTitle('Scene Editor')
self.dockWidgetSceneEditor.setObjectName("dockWidgetSceneEditor")
self.dockWidgetContentsSceneEditor = SceneEditorWidget()
self.dockWidgetContentsSceneEditor.setObjectName("dockWidgetContentsSceneEditor")
self.dockWidgetSceneEditor.setWidget(self.dockWidgetContentsSceneEditor)
self.dockWidgetSceneEditor.setHidden(True)
self.dockWidgetSceneviewerEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSceneviewerEditor.setWindowTitle('Sceneviewer Editor')
self.dockWidgetSceneviewerEditor.setObjectName("dockWidgetSceneviewerEditor")
self.dockWidgetContentsSceneviewerEditor = SceneviewerEditorWidget(self.dockWidgetSceneviewerEditor)
self.dockWidgetContentsSceneviewerEditor.setObjectName("dockWidgetContentsSceneviewerEditor")
self.dockWidgetSceneviewerEditor.setWidget(self.dockWidgetContentsSceneviewerEditor)
self.dockWidgetSceneviewerEditor.setHidden(True)
self.dockWidgetSceneviewerEditor.visibilityChanged.connect(self.dockWidgetContentsSceneviewerEditor.setEnableUpdates)
self.dockWidgetSpectrumEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSpectrumEditor.setWindowTitle('Spectrum Editor')
self.dockWidgetSpectrumEditor.setObjectName("dockWidgetSpectrumEditor")
self.dockWidgetContentsSpectrumEditor = SpectrumEditorWidget(self.dockWidgetSpectrumEditor)
self.dockWidgetContentsSpectrumEditor.setObjectName("dockWidgetContentsSpectrumEditor")
self.dockWidgetSpectrumEditor.setWidget(self.dockWidgetContentsSpectrumEditor)
self.dockWidgetSpectrumEditor.setHidden(True)
self.dockWidgetTessellationEditor = QtWidgets.QDockWidget(self)
self.dockWidgetTessellationEditor.setWindowTitle('Tessellation Editor')
self.dockWidgetTessellationEditor.setObjectName("dockWidgetTessellationEditor")
self.dockWidgetContentsTessellationEditor = TessellationEditorWidget()
self.dockWidgetContentsTessellationEditor.setObjectName("dockWidgetContentsTessellationEditor")
self.dockWidgetTessellationEditor.setWidget(self.dockWidgetContentsTessellationEditor)
self.dockWidgetTessellationEditor.setHidden(True)
self.dockWidgetTimeEditor = QtWidgets.QDockWidget(self)
self.dockWidgetTimeEditor.setWindowTitle('Time Editor')
self.dockWidgetTimeEditor.setObjectName("dockWidgetTimeEditor")
self.dockWidgetContentsTimeEditor = TimeEditorWidget()
self.dockWidgetContentsTimeEditor.setObjectName("dockWidgetContentsTimeEditor")
self.dockWidgetTimeEditor.setWidget(self.dockWidgetContentsTimeEditor)
self.dockWidgetTimeEditor.setHidden(True)
self.dockWidgetFieldEditor = QtWidgets.QDockWidget(self)
self.dockWidgetFieldEditor.setWindowTitle('Field Editor')
self.dockWidgetFieldEditor.setObjectName("dockWidgetFieldEditor")
self.dockWidgetContentsFieldEditor = FieldListEditorWidget()
self.dockWidgetContentsFieldEditor.setObjectName("dockWidgetContentsFieldEditor")
self.dockWidgetFieldEditor.setWidget(self.dockWidgetContentsFieldEditor)
self.dockWidgetFieldEditor.setHidden(True)
def _registerEditors(self):
# self._registerEditor(self._problem_view, self.dockWidgetProblemEditor)
# self._registerEditor(self._simulation_view, self.dockWidgetSimulationEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetRegionEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetMaterialEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetModelSourcesEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSceneEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSceneviewerEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSpectrumEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetTessellationEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetTimeEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetFieldEditor)
self._ui.menu_View.addSeparator()
def _registerEditor(self, view, editor):
action_name = getEditorMenuName(view)
action = self._getEditorAction(action_name)
if action is None:
menu = self._ui.menu_View.addMenu(action_name)
menu.setEnabled(False)
else:
menu = action.menu()
toggle_action = editor.toggleViewAction()
toggle_action.triggered.connect(self._view_dock_widget)
menu.addAction(toggle_action)
view.registerDependentEditor(editor)
def _view_dock_widget(self, show):
"""
If we are showing the dock widget we will make it current i.e. make sure it is visible if tabbed.
"""
if show:
sender_text = self.sender().text()
for tab_bar in self.findChildren(QtWidgets.QTabBar):
for index in range(tab_bar.count()):
tab_text = tab_bar.tabText(index)
if tab_text == sender_text:
tab_bar.setCurrentIndex(index)
return
def _getEditorAction(self, action_name):
action = None
actions = self._ui.menu_View.actions()
existing_actions = [a for a in actions if a.text() == action_name]
if existing_actions:
action = existing_actions[0]
return action
# def _createDialogs(self):
# self._snapshot_dialog = SnapshotDialog(self, self._ui.one_gl_widget_to_rule_them_all)
# self._snapshot_dialog.setZincContext(self._model.getZincContext())
# self._preferences_dialog = PreferencesDialog(self)
def _writeSettings(self):
settings = QtCore.QSettings()
settings.beginGroup('MainWindow')
settings.setValue('location', self._location)
settings.setValue('geometry', self.saveGeometry())
settings.setValue('current_view', self._ui.viewStackedWidget.currentIndex())
settings.beginWriteArray('recents')
recents = self._model.getRecents()
for i, r in enumerate(recents):
settings.setArrayIndex(i)
settings.setValue('item', r)
settings.endArray()
settings.endGroup()
settings.beginGroup('views')
self._storeCurrentView() # needed in case user never changed view
for key in self._view_states:
settings.setValue(key.getName(), self._view_states[key])
settings.endGroup()
settings.beginGroup('SnapshotDialog')
# settings.setValue('state', self._snapshot_dialog.serialize())
settings.endGroup()
settings.beginGroup('Problems')
# settings.setValue('state', self._problem_view.serialize())
settings.endGroup()
def _readSettings(self):
settings = QtCore.QSettings()
settings.beginGroup('MainWindow')
geometry = settings.value('geometry')
if geometry is not None:
self.restoreGeometry(geometry)
self._location = settings.value('location', QtCore.QDir.homePath())
size = settings.beginReadArray('recents')
for i in range(size):
settings.setArrayIndex(i)
self._addRecent(settings.value('item'))
settings.endArray()
currentViewIndex = settings.value('current_view', '0')
settings.endGroup()
settings.beginGroup('views')
for key in self._view_states:
state = settings.value(key.getName(), '')
self._view_states[key] = state
settings.endGroup()
self._setCurrentView(currentViewIndex)
self._postChangeView()
settings.beginGroup('SnapshotDialog')
# self._snapshot_dialog.deserialize(settings.value('state', ''))
settings.endGroup()
settings.beginGroup('Problems')
# self._problem_view.deserialize(settings.value('state', ''))
settings.endGroup()
self._updateUi()
def _addRecent(self, recent):
actions = self._ui.menu_Open_recent.actions()
insert_before_action = actions[0]
self._model.addRecent(recent)
recent_action = QtWidgets.QAction(self._ui.menu_Open_recent)
recent_action.setText(recent)
self._ui.menu_Open_recent.insertAction(insert_before_action, recent_action)
recent_action.triggered.connect(self._open)
def _setCurrentView(self, index):
v = self._ui.viewStackedWidget.widget(int(index))
self._changeView(v)
self._postChangeView()
actions = self._ui.menu_View.actions()
for action in actions:
if action.data() == v:
action.setChecked(True)
def _storeCurrentView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
view_state = self.saveState(VERSION_MAJOR)
self._view_states[current_view] = view_state
def _preChangeView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
dependent_editors = current_view.getDependentEditors()
view_state = self.saveState(VERSION_MAJOR)
self._view_states[current_view] = view_state
for ed in dependent_editors:
ed.setHidden(True)
action_name = getEditorMenuName(current_view)
action = self._getEditorAction(action_name)
if action is not None:
menu = action.menu()
menu.setEnabled(False)
def _changeView(self, view):
self._ui.viewStackedWidget.setCurrentWidget(view)
def _postChangeView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
view_state = self._view_states[current_view]
# self.restoreState(view_state, VERSION_MAJOR)
action_name = getEditorMenuName(current_view)
action = self._getEditorAction(action_name)
if action is not None:
menu = action.menu()
menu.setEnabled(True)
def _setupOtherWindows(self):
self.dockWidgetLoggerEditor = QtWidgets.QDockWidget("Log Viewer", self)
# self.dockWidgetLoggerEditor.setWindowTitle('Logger')
self.dockWidgetLoggerEditor.setObjectName("dockWidgetLoggerEditor")
logger_widget = LoggerEditorWidget(self.dockWidgetLoggerEditor)
# logger_widget.setObjectName("dockWidgetContentsLoggerEditor")
self.dockWidgetLoggerEditor.setWidget(logger_widget)
self.dockWidgetLoggerEditor.setHidden(True)
def _registerOtherWindows(self):
self._registerOtherWindow(self.dockWidgetLoggerEditor)
def _registerOtherWindow(self, editor):
action = self._getEditorAction("Other Windows")
if action is None:
menu = self._ui.menu_View.addMenu("Other Windows")
menu.setEnabled(True)
else:
menu = action.menu()
toggle_action = editor.toggleViewAction()
toggle_action.triggered.connect(self._view_dock_widget)
menu.addAction(toggle_action)
def _setupViews(self, views):
action_group = QtWidgets.QActionGroup(self)
zincContext = self._model.getZincContext()
for v in views:
self._ui.viewStackedWidget.addWidget(v)
v.setZincContext(zincContext)
action_view = QtWidgets.QAction(v.getName(), self)
action_view.setData(v)
action_view.setCheckable(True)
action_view.setActionGroup(action_group)
action_view.triggered.connect(self._viewTriggered)
self._ui.menu_View.addAction(action_view)
self._ui.menu_View.addSeparator()
def _runSimulationClicked(self):
sender = self.sender()
if sender == self.dockWidgetContentsProblemEditor:
actions = self._ui.menu_View.actions()
simulate_action = [a for a in actions if a.text() == self._simulation_view.getName()][0]
simulate_action.activate(QtWidgets.QAction.ActionEvent.Trigger)
problem = self._model.getDocument().getProject().getProblem()
if problem.validate():
self._simulation_view.setProblem(problem)
self._simulation_view.setPreferences(self._model.getPreferences())
self._simulation_view.run()
else:
print('pop up error box')
def _visualiseSimulationClicked(self):
sender = self.sender()
if sender == self.dockWidgetContentsSimulationEditor:
actions = self._ui.menu_View.actions()
visualise_action = [a for a in actions if a.text() == self._visualisation_view.getName()][0]
visualise_action.activate(QtWidgets.QAction.ActionEvent.Trigger)
simulation = self._simulation_view.getSimulation()
if simulation.validate():
self._model.visualiseSimulation(simulation)
else:
print('pop up error box')
def _viewTriggered(self):
v = self.sender().data()
self._preChangeView()
self._changeView(v)
self._postChangeView()
def _regionChange(self, changedRegion, treeChange):
"""
Notifies sceneviewer if affected by tree change i.e. needs new scene.
:param changedRegion: The top region changed
:param treeChange: True if structure of tree, or zinc objects reconstructed
"""
# following may need changing once sceneviewer can look at sub scenes, since resets to root scene:
if treeChange and (changedRegion is self._model.getDocument().getRootRegion()):
zincRootRegion = changedRegion.getZincRegion()
self._visualisation_view.setScene(zincRootRegion.getScene())
def _onDocumentChanged(self):
document = self._model.getDocument()
rootRegion = document.getRootRegion()
rootRegion.connectRegionChange(self._regionChange)
zincRootRegion = rootRegion.getZincRegion()
# need to pass new Zinc context to dialogs and widgets using global modules
zincContext = document.getZincContext()
self._visualisation_view.setZincContext(zincContext)
# self._simulation_view.setZincContext(zincContext)
self.dockWidgetContentsSpectrumEditor.setSpectrums(document.getSpectrums())
self.dockWidgetContentsMaterialEditor.setMaterials(document.getMaterials())
self.dockWidgetContentsTessellationEditor.setTessellations(document.getTessellations())
self.dockWidgetContentsTimeEditor.setZincContext(zincContext)
# self._snapshot_dialog.setZincContext(zincContext)
model_sources_model = ModelSourcesModel(document, [])
self.dockWidgetContentsModelSourcesEditor.setModelSourcesModel(zincRootRegion, model_sources_model)
# need to pass new root region to the following
self.dockWidgetContentsRegionEditor.setRootRegion(rootRegion)
self.dockWidgetContentsSceneEditor.setZincRootRegion(zincRootRegion)
self.dockWidgetContentsFieldEditor.setRootArgonRegion(rootRegion)
self.dockWidgetContentsFieldEditor.setTimekeeper(zincContext.getTimekeepermodule().getDefaultTimekeeper())
if self._visualisation_view_ready:
self._restoreSceneviewerState()
else:
self._visualisation_view_state_update_pending = True
# project = document.getProject()
# index = self._model.getProjectModel().getIndex(project)
# self._problem_view.setCurrentIndex(index.row())
# self._simulation_view.setCurrentIndex(index.row())
# self._problem_view.setProblem(project.getProblem())
def _regionSelected(self, region):
# self.dockWidgetContentsModelSourcesEditor.setRegion(region)
zincRegion = region.getZincRegion()
# scene = zincRegion.getScene()
# self.dockWidgetContentsSceneEditor.setScene(scene)
self.dockWidgetContentsFieldEditor.setFieldmodule(zincRegion.getFieldmodule())
self.dockWidgetContentsFieldEditor.setArgonRegion(region)
def _visualisationViewReady(self):
self._visualisation_view_ready = True
if self._visualisation_view_state_update_pending:
self._restoreSceneviewerState()
def _saveTriggered(self):
if self._model.getLocation() is None:
self._saveAsTriggered()
else:
self._recordSceneviewerState()
self._model.save()
def _saveAsTriggered(self):
filename, _ = QtWidgets.QFileDialog.getSaveFileName(self, caption='Choose file ...', dir=self._location, filter="Neon Files (*.neon *.json);;All (*.*)")
if filename:
self._location = os.path.dirname(filename)
self._model.setLocation(filename)
self._recordSceneviewerState()
self._model.save()
def _restoreSceneviewerState(self):
document = self._model.getDocument()
sceneviewer_state = document.getSceneviewer().serialize()
self._visualisation_view.setSceneviewerState(sceneviewer_state)
self.dockWidgetContentsSceneviewerEditor.setSceneviewer(self._visualisation_view.getSceneviewer())
self._visualisation_view_state_update_pending = False
def _recordSceneviewerState(self):
sceneviewer_state = self._visualisation_view.getSceneviewerState()
document = self._model.getDocument()
document.getSceneviewer().deserialize(sceneviewer_state)
def _undoRedoStackIndexChanged(self, index):
self._model.setCurrentUndoRedoIndex(index)
def _aboutTriggered(self):
d = AboutDialog(self)
d.exec_()
def _snapshotDialogReady(self):
document = self._model.getDocument()
rootRegion = document.getRootRegion()
zincRootRegion = rootRegion.getZincRegion()
scene = zincRootRegion.getScene()
self._snapshot_dialog.setScene(scene)
def _snapshotTriggered(self):
if self._snapshot_dialog.getLocation() is None and self._location is not None:
self._snapshot_dialog.setLocation(self._location)
if self._snapshot_dialog.exec_():
if self._location is None:
self._location = self._snapshot_dialog.getLocation()
filename = self._snapshot_dialog.getFilename()
wysiwyg = self._snapshot_dialog.getWYSIWYG()
width = self._snapshot_dialog.getWidth()
height = self._snapshot_dialog.getHeight()
self._visualisation_view.saveImage(filename, wysiwyg, width, height)
def _preferencesTriggered(self):
if self._preferences_dialog.exec_():
pass # Save the state
def _newTriggered(self):
self._model.new()
def _openModel(self, filename):
success = self._model.load(filename)
if success:
self._location = os.path.dirname(filename)
self._addRecent(filename)
else:
QtWidgets.QMessageBox.warning(self, "Load failure", "Failed to load file " + filename + ". Refer to logger window for more details", QtWidgets.QMessageBox.Ok)
self._model.new() # in case document half constructed; emits documentChanged
self._updateUi()
def _openTriggered(self):
filename, _ = QtWidgets.QFileDialog.getOpenFileName(self, caption='Choose file ...', dir=self._location, filter="Neon Files (*.neon *.json);;All (*.*)")
if filename:
self._openModel(filename)
def _open(self):
"""
Open a model from a recent file.
"""
filename = self.sender().text()
self._ui.menu_Open_recent.removeAction(self.sender())
self._model.removeRecent(filename)
self._openModel(filename)
def _clearTriggered(self):
self._model.clearRecents()
actions = self._ui.menu_Open_recent.actions()
for action in actions[:-2]:
self._ui.menu_Open_recent.removeAction(action)
self._updateUi()
def confirmClose(self):
# Check to see if the Workflow is in a saved state.
if self._model.isModified():
ret = QtWidgets.QMessageBox.warning(self, 'Unsaved Changes', 'You have unsaved changes, would you like to save these changes now?',
QtWidgets.QMessageBox.Yes | QtWidgets.QMessageBox.No)
if ret == QtWidgets.QMessageBox.Yes:
self._saveTriggered()
def _quitApplication(self):
self.confirmClose()
# self._setCurrentView('0')
self._writeSettings()
def closeEvent(self, event):
self._quitApplication()
super(MainWindow, self).closeEvent(event)
def getEditorMenuName(view):
return view.getName() + ' Editors'
| 44.871429 | 170 | 0.718738 | import os.path
from PySide2 import QtCore, QtWidgets
from opencmiss.neon.ui.ui_mainwindow import Ui_MainWindow
from opencmiss.neon.undoredo.commands import CommandEmpty
from opencmiss.neon.ui.views.visualisationview import VisualisationView
from opencmiss.neon.ui.dialogs.aboutdialog import AboutDialog
from opencmiss.neon.ui.editors.loggereditorwidget import LoggerEditorWidget
from opencmiss.zincwidgets.regioneditorwidget import RegionEditorWidget
from opencmiss.zincwidgets.materialeditorwidget import MaterialEditorWidget
from opencmiss.zincwidgets.modelsourceseditorwidget import ModelSourcesEditorWidget, ModelSourcesModel
from opencmiss.zincwidgets.sceneviewereditorwidget import SceneviewerEditorWidget
from opencmiss.zincwidgets.sceneeditorwidget import SceneEditorWidget
from opencmiss.zincwidgets.spectrumeditorwidget import SpectrumEditorWidget
from opencmiss.zincwidgets.tessellationeditorwidget import TessellationEditorWidget
from opencmiss.zincwidgets.timeeditorwidget import TimeEditorWidget
from opencmiss.zincwidgets.fieldlisteditorwidget import FieldListEditorWidget
from opencmiss.neon.settings.mainsettings import VERSION_MAJOR
class MainWindow(QtWidgets.QMainWindow):
def __init__(self, model):
super(MainWindow, self).__init__()
self._model = model
self._ui = Ui_MainWindow()
self._ui.setupUi(self)
self._visualisation_view_state_update_pending = False
self._visualisation_view = VisualisationView(self)
self._visualisation_view_ready = False
self._view_states = {self._visualisation_view: ''}
view_list = [self._visualisation_view]
self._location = None
self._current_view = None
self._undoRedoStack = QtWidgets.QUndoStack(self)
self._setupEditors()
self._registerEditors()
self._setupViews(view_list)
self._setupOtherWindows()
self._registerOtherWindows()
self._addDockWidgets()
self._makeConnections()
self._undoRedoStack.push(CommandEmpty())
self._undoRedoStack.clear()
self._updateUi()
self._readSettings()
self._onDocumentChanged()
def _makeConnections(self):
self._ui.action_Quit.triggered.connect(self.close)
self._ui.action_New.triggered.connect(self._newTriggered)
self._ui.action_Open.triggered.connect(self._openTriggered)
self._ui.action_About.triggered.connect(self._aboutTriggered)
self._ui.action_Save.triggered.connect(self._saveTriggered)
self._ui.action_Save_As.triggered.connect(self._saveAsTriggered)
self._ui.action_Snapshot.triggered.connect(self._snapshotTriggered)
self._ui.actionPreferences.triggered.connect(self._preferencesTriggered)
self._ui.action_Clear.triggered.connect(self._clearTriggered)
self._undoRedoStack.indexChanged.connect(self._undoRedoStackIndexChanged)
self._undoRedoStack.canUndoChanged.connect(self._ui.action_Undo.setEnabled)
self._undoRedoStack.canRedoChanged.connect(self._ui.action_Redo.setEnabled)
self._visualisation_view.graphicsInitialized.connect(self._visualisationViewReady)
self.dockWidgetContentsRegionEditor.regionSelected.connect(self._regionSelected)
self._model.documentChanged.connect(self._onDocumentChanged)
def _updateUi(self):
modified = self._model.isModified()
self._ui.action_Save.setEnabled(modified)
recents = self._model.getRecents()
self._ui.action_Clear.setEnabled(len(recents))
def _addDockWidgets(self):
self.addDockWidget(QtCore.Qt.LeftDockWidgetArea, self.dockWidgetModelSourcesEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetTessellationEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSpectrumEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetMaterialEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSceneEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetRegionEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetSceneviewerEditor)
self.tabifyDockWidget(self.dockWidgetModelSourcesEditor, self.dockWidgetFieldEditor)
self.addDockWidget(QtCore.Qt.BottomDockWidgetArea, self.dockWidgetLoggerEditor)
self.tabifyDockWidget(self.dockWidgetLoggerEditor, self.dockWidgetTimeEditor)
def _setupEditors(self):
self.dockWidgetRegionEditor = QtWidgets.QDockWidget(self)
self.dockWidgetRegionEditor.setWindowTitle('Region Editor')
self.dockWidgetRegionEditor.setObjectName("dockWidgetRegionEditor")
self.dockWidgetContentsRegionEditor = RegionEditorWidget()
self.dockWidgetContentsRegionEditor.setObjectName("dockWidgetContentsRegionEditor")
self.dockWidgetRegionEditor.setWidget(self.dockWidgetContentsRegionEditor)
self.dockWidgetRegionEditor.setHidden(True)
self.dockWidgetMaterialEditor = QtWidgets.QDockWidget(self)
self.dockWidgetMaterialEditor.setWindowTitle('Material Editor')
self.dockWidgetMaterialEditor.setObjectName("dockWidgetMaterialEditor")
self.dockWidgetContentsMaterialEditor = MaterialEditorWidget()
self.dockWidgetContentsMaterialEditor.setObjectName("dockWidgetContentsMaterialEditor")
self.dockWidgetMaterialEditor.setWidget(self.dockWidgetContentsMaterialEditor)
self.dockWidgetMaterialEditor.setHidden(True)
self.dockWidgetModelSourcesEditor = QtWidgets.QDockWidget(self)
self.dockWidgetModelSourcesEditor.setWindowTitle('Model Sources Editor')
self.dockWidgetModelSourcesEditor.setObjectName("dockWidgetModelSourcesEditor")
self.dockWidgetContentsModelSourcesEditor = ModelSourcesEditorWidget()
self.dockWidgetContentsModelSourcesEditor.setObjectName("dockWidgetContentsModelSourcesEditor")
self.dockWidgetModelSourcesEditor.setWidget(self.dockWidgetContentsModelSourcesEditor)
self.dockWidgetModelSourcesEditor.setHidden(False)
self.dockWidgetSceneEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSceneEditor.setWindowTitle('Scene Editor')
self.dockWidgetSceneEditor.setObjectName("dockWidgetSceneEditor")
self.dockWidgetContentsSceneEditor = SceneEditorWidget()
self.dockWidgetContentsSceneEditor.setObjectName("dockWidgetContentsSceneEditor")
self.dockWidgetSceneEditor.setWidget(self.dockWidgetContentsSceneEditor)
self.dockWidgetSceneEditor.setHidden(True)
self.dockWidgetSceneviewerEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSceneviewerEditor.setWindowTitle('Sceneviewer Editor')
self.dockWidgetSceneviewerEditor.setObjectName("dockWidgetSceneviewerEditor")
self.dockWidgetContentsSceneviewerEditor = SceneviewerEditorWidget(self.dockWidgetSceneviewerEditor)
self.dockWidgetContentsSceneviewerEditor.setObjectName("dockWidgetContentsSceneviewerEditor")
self.dockWidgetSceneviewerEditor.setWidget(self.dockWidgetContentsSceneviewerEditor)
self.dockWidgetSceneviewerEditor.setHidden(True)
self.dockWidgetSceneviewerEditor.visibilityChanged.connect(self.dockWidgetContentsSceneviewerEditor.setEnableUpdates)
self.dockWidgetSpectrumEditor = QtWidgets.QDockWidget(self)
self.dockWidgetSpectrumEditor.setWindowTitle('Spectrum Editor')
self.dockWidgetSpectrumEditor.setObjectName("dockWidgetSpectrumEditor")
self.dockWidgetContentsSpectrumEditor = SpectrumEditorWidget(self.dockWidgetSpectrumEditor)
self.dockWidgetContentsSpectrumEditor.setObjectName("dockWidgetContentsSpectrumEditor")
self.dockWidgetSpectrumEditor.setWidget(self.dockWidgetContentsSpectrumEditor)
self.dockWidgetSpectrumEditor.setHidden(True)
self.dockWidgetTessellationEditor = QtWidgets.QDockWidget(self)
self.dockWidgetTessellationEditor.setWindowTitle('Tessellation Editor')
self.dockWidgetTessellationEditor.setObjectName("dockWidgetTessellationEditor")
self.dockWidgetContentsTessellationEditor = TessellationEditorWidget()
self.dockWidgetContentsTessellationEditor.setObjectName("dockWidgetContentsTessellationEditor")
self.dockWidgetTessellationEditor.setWidget(self.dockWidgetContentsTessellationEditor)
self.dockWidgetTessellationEditor.setHidden(True)
self.dockWidgetTimeEditor = QtWidgets.QDockWidget(self)
self.dockWidgetTimeEditor.setWindowTitle('Time Editor')
self.dockWidgetTimeEditor.setObjectName("dockWidgetTimeEditor")
self.dockWidgetContentsTimeEditor = TimeEditorWidget()
self.dockWidgetContentsTimeEditor.setObjectName("dockWidgetContentsTimeEditor")
self.dockWidgetTimeEditor.setWidget(self.dockWidgetContentsTimeEditor)
self.dockWidgetTimeEditor.setHidden(True)
self.dockWidgetFieldEditor = QtWidgets.QDockWidget(self)
self.dockWidgetFieldEditor.setWindowTitle('Field Editor')
self.dockWidgetFieldEditor.setObjectName("dockWidgetFieldEditor")
self.dockWidgetContentsFieldEditor = FieldListEditorWidget()
self.dockWidgetContentsFieldEditor.setObjectName("dockWidgetContentsFieldEditor")
self.dockWidgetFieldEditor.setWidget(self.dockWidgetContentsFieldEditor)
self.dockWidgetFieldEditor.setHidden(True)
def _registerEditors(self):
self._registerEditor(self._visualisation_view, self.dockWidgetRegionEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetMaterialEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetModelSourcesEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSceneEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSceneviewerEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetSpectrumEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetTessellationEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetTimeEditor)
self._registerEditor(self._visualisation_view, self.dockWidgetFieldEditor)
self._ui.menu_View.addSeparator()
def _registerEditor(self, view, editor):
action_name = getEditorMenuName(view)
action = self._getEditorAction(action_name)
if action is None:
menu = self._ui.menu_View.addMenu(action_name)
menu.setEnabled(False)
else:
menu = action.menu()
toggle_action = editor.toggleViewAction()
toggle_action.triggered.connect(self._view_dock_widget)
menu.addAction(toggle_action)
view.registerDependentEditor(editor)
def _view_dock_widget(self, show):
if show:
sender_text = self.sender().text()
for tab_bar in self.findChildren(QtWidgets.QTabBar):
for index in range(tab_bar.count()):
tab_text = tab_bar.tabText(index)
if tab_text == sender_text:
tab_bar.setCurrentIndex(index)
return
def _getEditorAction(self, action_name):
action = None
actions = self._ui.menu_View.actions()
existing_actions = [a for a in actions if a.text() == action_name]
if existing_actions:
action = existing_actions[0]
return action
def _writeSettings(self):
settings = QtCore.QSettings()
settings.beginGroup('MainWindow')
settings.setValue('location', self._location)
settings.setValue('geometry', self.saveGeometry())
settings.setValue('current_view', self._ui.viewStackedWidget.currentIndex())
settings.beginWriteArray('recents')
recents = self._model.getRecents()
for i, r in enumerate(recents):
settings.setArrayIndex(i)
settings.setValue('item', r)
settings.endArray()
settings.endGroup()
settings.beginGroup('views')
self._storeCurrentView()
for key in self._view_states:
settings.setValue(key.getName(), self._view_states[key])
settings.endGroup()
settings.beginGroup('SnapshotDialog')
settings.endGroup()
settings.beginGroup('Problems')
settings.endGroup()
def _readSettings(self):
settings = QtCore.QSettings()
settings.beginGroup('MainWindow')
geometry = settings.value('geometry')
if geometry is not None:
self.restoreGeometry(geometry)
self._location = settings.value('location', QtCore.QDir.homePath())
size = settings.beginReadArray('recents')
for i in range(size):
settings.setArrayIndex(i)
self._addRecent(settings.value('item'))
settings.endArray()
currentViewIndex = settings.value('current_view', '0')
settings.endGroup()
settings.beginGroup('views')
for key in self._view_states:
state = settings.value(key.getName(), '')
self._view_states[key] = state
settings.endGroup()
self._setCurrentView(currentViewIndex)
self._postChangeView()
settings.beginGroup('SnapshotDialog')
settings.endGroup()
settings.beginGroup('Problems')
settings.endGroup()
self._updateUi()
def _addRecent(self, recent):
actions = self._ui.menu_Open_recent.actions()
insert_before_action = actions[0]
self._model.addRecent(recent)
recent_action = QtWidgets.QAction(self._ui.menu_Open_recent)
recent_action.setText(recent)
self._ui.menu_Open_recent.insertAction(insert_before_action, recent_action)
recent_action.triggered.connect(self._open)
def _setCurrentView(self, index):
v = self._ui.viewStackedWidget.widget(int(index))
self._changeView(v)
self._postChangeView()
actions = self._ui.menu_View.actions()
for action in actions:
if action.data() == v:
action.setChecked(True)
def _storeCurrentView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
view_state = self.saveState(VERSION_MAJOR)
self._view_states[current_view] = view_state
def _preChangeView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
dependent_editors = current_view.getDependentEditors()
view_state = self.saveState(VERSION_MAJOR)
self._view_states[current_view] = view_state
for ed in dependent_editors:
ed.setHidden(True)
action_name = getEditorMenuName(current_view)
action = self._getEditorAction(action_name)
if action is not None:
menu = action.menu()
menu.setEnabled(False)
def _changeView(self, view):
self._ui.viewStackedWidget.setCurrentWidget(view)
def _postChangeView(self):
current_view = self._ui.viewStackedWidget.currentWidget()
view_state = self._view_states[current_view]
action_name = getEditorMenuName(current_view)
action = self._getEditorAction(action_name)
if action is not None:
menu = action.menu()
menu.setEnabled(True)
def _setupOtherWindows(self):
self.dockWidgetLoggerEditor = QtWidgets.QDockWidget("Log Viewer", self)
self.dockWidgetLoggerEditor.setObjectName("dockWidgetLoggerEditor")
logger_widget = LoggerEditorWidget(self.dockWidgetLoggerEditor)
self.dockWidgetLoggerEditor.setWidget(logger_widget)
self.dockWidgetLoggerEditor.setHidden(True)
def _registerOtherWindows(self):
self._registerOtherWindow(self.dockWidgetLoggerEditor)
def _registerOtherWindow(self, editor):
action = self._getEditorAction("Other Windows")
if action is None:
menu = self._ui.menu_View.addMenu("Other Windows")
menu.setEnabled(True)
else:
menu = action.menu()
toggle_action = editor.toggleViewAction()
toggle_action.triggered.connect(self._view_dock_widget)
menu.addAction(toggle_action)
def _setupViews(self, views):
action_group = QtWidgets.QActionGroup(self)
zincContext = self._model.getZincContext()
for v in views:
self._ui.viewStackedWidget.addWidget(v)
v.setZincContext(zincContext)
action_view = QtWidgets.QAction(v.getName(), self)
action_view.setData(v)
action_view.setCheckable(True)
action_view.setActionGroup(action_group)
action_view.triggered.connect(self._viewTriggered)
self._ui.menu_View.addAction(action_view)
self._ui.menu_View.addSeparator()
def _runSimulationClicked(self):
sender = self.sender()
if sender == self.dockWidgetContentsProblemEditor:
actions = self._ui.menu_View.actions()
simulate_action = [a for a in actions if a.text() == self._simulation_view.getName()][0]
simulate_action.activate(QtWidgets.QAction.ActionEvent.Trigger)
problem = self._model.getDocument().getProject().getProblem()
if problem.validate():
self._simulation_view.setProblem(problem)
self._simulation_view.setPreferences(self._model.getPreferences())
self._simulation_view.run()
else:
print('pop up error box')
def _visualiseSimulationClicked(self):
sender = self.sender()
if sender == self.dockWidgetContentsSimulationEditor:
actions = self._ui.menu_View.actions()
visualise_action = [a for a in actions if a.text() == self._visualisation_view.getName()][0]
visualise_action.activate(QtWidgets.QAction.ActionEvent.Trigger)
simulation = self._simulation_view.getSimulation()
if simulation.validate():
self._model.visualiseSimulation(simulation)
else:
print('pop up error box')
def _viewTriggered(self):
v = self.sender().data()
self._preChangeView()
self._changeView(v)
self._postChangeView()
def _regionChange(self, changedRegion, treeChange):
if treeChange and (changedRegion is self._model.getDocument().getRootRegion()):
zincRootRegion = changedRegion.getZincRegion()
self._visualisation_view.setScene(zincRootRegion.getScene())
def _onDocumentChanged(self):
document = self._model.getDocument()
rootRegion = document.getRootRegion()
rootRegion.connectRegionChange(self._regionChange)
zincRootRegion = rootRegion.getZincRegion()
zincContext = document.getZincContext()
self._visualisation_view.setZincContext(zincContext)
self.dockWidgetContentsSpectrumEditor.setSpectrums(document.getSpectrums())
self.dockWidgetContentsMaterialEditor.setMaterials(document.getMaterials())
self.dockWidgetContentsTessellationEditor.setTessellations(document.getTessellations())
self.dockWidgetContentsTimeEditor.setZincContext(zincContext)
model_sources_model = ModelSourcesModel(document, [])
self.dockWidgetContentsModelSourcesEditor.setModelSourcesModel(zincRootRegion, model_sources_model)
self.dockWidgetContentsRegionEditor.setRootRegion(rootRegion)
self.dockWidgetContentsSceneEditor.setZincRootRegion(zincRootRegion)
self.dockWidgetContentsFieldEditor.setRootArgonRegion(rootRegion)
self.dockWidgetContentsFieldEditor.setTimekeeper(zincContext.getTimekeepermodule().getDefaultTimekeeper())
if self._visualisation_view_ready:
self._restoreSceneviewerState()
else:
self._visualisation_view_state_update_pending = True
def _regionSelected(self, region):
zincRegion = region.getZincRegion()
self.dockWidgetContentsFieldEditor.setFieldmodule(zincRegion.getFieldmodule())
self.dockWidgetContentsFieldEditor.setArgonRegion(region)
def _visualisationViewReady(self):
self._visualisation_view_ready = True
if self._visualisation_view_state_update_pending:
self._restoreSceneviewerState()
def _saveTriggered(self):
if self._model.getLocation() is None:
self._saveAsTriggered()
else:
self._recordSceneviewerState()
self._model.save()
def _saveAsTriggered(self):
filename, _ = QtWidgets.QFileDialog.getSaveFileName(self, caption='Choose file ...', dir=self._location, filter="Neon Files (*.neon *.json);;All (*.*)")
if filename:
self._location = os.path.dirname(filename)
self._model.setLocation(filename)
self._recordSceneviewerState()
self._model.save()
def _restoreSceneviewerState(self):
document = self._model.getDocument()
sceneviewer_state = document.getSceneviewer().serialize()
self._visualisation_view.setSceneviewerState(sceneviewer_state)
self.dockWidgetContentsSceneviewerEditor.setSceneviewer(self._visualisation_view.getSceneviewer())
self._visualisation_view_state_update_pending = False
def _recordSceneviewerState(self):
sceneviewer_state = self._visualisation_view.getSceneviewerState()
document = self._model.getDocument()
document.getSceneviewer().deserialize(sceneviewer_state)
def _undoRedoStackIndexChanged(self, index):
self._model.setCurrentUndoRedoIndex(index)
def _aboutTriggered(self):
d = AboutDialog(self)
d.exec_()
def _snapshotDialogReady(self):
document = self._model.getDocument()
rootRegion = document.getRootRegion()
zincRootRegion = rootRegion.getZincRegion()
scene = zincRootRegion.getScene()
self._snapshot_dialog.setScene(scene)
def _snapshotTriggered(self):
if self._snapshot_dialog.getLocation() is None and self._location is not None:
self._snapshot_dialog.setLocation(self._location)
if self._snapshot_dialog.exec_():
if self._location is None:
self._location = self._snapshot_dialog.getLocation()
filename = self._snapshot_dialog.getFilename()
wysiwyg = self._snapshot_dialog.getWYSIWYG()
width = self._snapshot_dialog.getWidth()
height = self._snapshot_dialog.getHeight()
self._visualisation_view.saveImage(filename, wysiwyg, width, height)
def _preferencesTriggered(self):
if self._preferences_dialog.exec_():
pass
def _newTriggered(self):
self._model.new()
def _openModel(self, filename):
success = self._model.load(filename)
if success:
self._location = os.path.dirname(filename)
self._addRecent(filename)
else:
QtWidgets.QMessageBox.warning(self, "Load failure", "Failed to load file " + filename + ". Refer to logger window for more details", QtWidgets.QMessageBox.Ok)
self._model.new()
self._updateUi()
def _openTriggered(self):
filename, _ = QtWidgets.QFileDialog.getOpenFileName(self, caption='Choose file ...', dir=self._location, filter="Neon Files (*.neon *.json);;All (*.*)")
if filename:
self._openModel(filename)
def _open(self):
filename = self.sender().text()
self._ui.menu_Open_recent.removeAction(self.sender())
self._model.removeRecent(filename)
self._openModel(filename)
def _clearTriggered(self):
self._model.clearRecents()
actions = self._ui.menu_Open_recent.actions()
for action in actions[:-2]:
self._ui.menu_Open_recent.removeAction(action)
self._updateUi()
def confirmClose(self):
if self._model.isModified():
ret = QtWidgets.QMessageBox.warning(self, 'Unsaved Changes', 'You have unsaved changes, would you like to save these changes now?',
QtWidgets.QMessageBox.Yes | QtWidgets.QMessageBox.No)
if ret == QtWidgets.QMessageBox.Yes:
self._saveTriggered()
def _quitApplication(self):
self.confirmClose()
self._writeSettings()
def closeEvent(self, event):
self._quitApplication()
super(MainWindow, self).closeEvent(event)
def getEditorMenuName(view):
return view.getName() + ' Editors'
| true | true |
f7fe8c9b0817d1ea9a115995a0048e191acfeb38 | 143 | py | Python | web/frontend/urls.py | Comp-490-SeniorProject/site | 031a1c25a3cc901fa764d408d795ed12dfebdb00 | [
"MIT"
] | null | null | null | web/frontend/urls.py | Comp-490-SeniorProject/site | 031a1c25a3cc901fa764d408d795ed12dfebdb00 | [
"MIT"
] | 38 | 2021-10-12T21:49:57.000Z | 2022-03-29T22:53:26.000Z | web/frontend/urls.py | Comp-490-SeniorProject/site | 031a1c25a3cc901fa764d408d795ed12dfebdb00 | [
"MIT"
] | 1 | 2021-12-07T03:49:49.000Z | 2021-12-07T03:49:49.000Z | from django.urls import path
from web.frontend import views
app_name = "frontend"
urlpatterns = [
path("", views.index, name="index"),
]
| 15.888889 | 40 | 0.699301 | from django.urls import path
from web.frontend import views
app_name = "frontend"
urlpatterns = [
path("", views.index, name="index"),
]
| true | true |
f7fe8ce8eddcdb18d69171a8b4ebc832e2c2dee9 | 10,123 | py | Python | tests/integration/backward_compatible/proxy/ringbuffer_test.py | tonytheonlypony/hazelcast-python-client | 3aafeaf2ebc05aee4f2386c62c079db496a7c81f | [
"Apache-2.0"
] | 98 | 2015-12-08T14:26:27.000Z | 2022-03-23T17:44:11.000Z | tests/integration/backward_compatible/proxy/ringbuffer_test.py | tonytheonlypony/hazelcast-python-client | 3aafeaf2ebc05aee4f2386c62c079db496a7c81f | [
"Apache-2.0"
] | 396 | 2016-02-23T11:07:55.000Z | 2022-03-31T14:26:34.000Z | tests/integration/backward_compatible/proxy/ringbuffer_test.py | tonytheonlypony/hazelcast-python-client | 3aafeaf2ebc05aee4f2386c62c079db496a7c81f | [
"Apache-2.0"
] | 62 | 2015-12-09T11:20:53.000Z | 2022-01-28T01:30:54.000Z | import os
import time
import unittest
from hazelcast.proxy.ringbuffer import OVERFLOW_POLICY_FAIL, MAX_BATCH_SIZE
from hazelcast.serialization.api import IdentifiedDataSerializable
from tests.base import SingleMemberTestCase
from tests.util import random_string, compare_client_version
CAPACITY = 10
class RingBufferTest(SingleMemberTestCase):
@classmethod
def configure_client(cls, config):
config["cluster_name"] = cls.cluster.id
return config
@classmethod
def configure_cluster(cls):
path = os.path.abspath(__file__)
dir_path = os.path.dirname(path)
with open(os.path.join(dir_path, "hazelcast.xml")) as f:
return f.read()
def setUp(self):
self.ringbuffer = self.client.get_ringbuffer(
"ClientRingbufferTestWithTTL-" + random_string()
).blocking()
def tearDown(self):
self.ringbuffer.destroy()
def test_capacity(self):
self.assertEqual(self.ringbuffer.capacity(), CAPACITY)
def test_add_size(self):
self.assertEqual(0, self.ringbuffer.add("value"))
self.assertEqual(1, self.ringbuffer.add("value"))
self.assertEqual(2, self.ringbuffer.add("value"))
self.assertEqual(3, self.ringbuffer.size())
def test_add_when_full(self):
self.fill_ringbuffer()
self.assertEqual(-1, self.ringbuffer.add(CAPACITY + 1, OVERFLOW_POLICY_FAIL))
def test_add_all(self):
self.assertEqual(CAPACITY - 1, self.ringbuffer.add_all(list(range(0, CAPACITY))))
def test_add_all_when_full(self):
self.assertEqual(
-1, self.ringbuffer.add_all(list(range(0, CAPACITY * 2)), OVERFLOW_POLICY_FAIL)
)
def test_add_all_when_empty_list(self):
with self.assertRaises(AssertionError):
self.ringbuffer.add_all([])
def test_add_all_when_too_large_batch(self):
with self.assertRaises(AssertionError):
self.ringbuffer.add_all(list(range(0, MAX_BATCH_SIZE + 1)))
def test_head_sequence(self):
self.fill_ringbuffer(CAPACITY * 2)
self.assertEqual(CAPACITY, self.ringbuffer.head_sequence())
def test_tail_sequence(self):
self.fill_ringbuffer(CAPACITY * 2)
self.assertEqual(CAPACITY * 2 - 1, self.ringbuffer.tail_sequence())
def test_remaining_capacity(self):
self.fill_ringbuffer(CAPACITY // 2)
self.assertEqual(CAPACITY // 2, self.ringbuffer.remaining_capacity())
def test_read_one(self):
self.ringbuffer.add("item")
self.ringbuffer.add("item-2")
self.ringbuffer.add("item-3")
self.assertEqual("item", self.ringbuffer.read_one(0))
self.assertEqual("item-2", self.ringbuffer.read_one(1))
self.assertEqual("item-3", self.ringbuffer.read_one(2))
def test_read_one_negative_sequence(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_one(-1)
def test_read_many(self):
self.fill_ringbuffer(CAPACITY)
items = self.ringbuffer.read_many(0, 0, CAPACITY)
self.assertEqual(items, list(range(0, CAPACITY)))
def test_read_many_when_negative_start_seq(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(-1, 0, CAPACITY)
def test_read_many_when_min_count_greater_than_max_count(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, CAPACITY, 0)
def test_read_many_when_min_count_greater_than_capacity(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, CAPACITY + 1, CAPACITY + 1)
def test_read_many_when_max_count_greater_than_batch_size(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, 0, MAX_BATCH_SIZE + 1)
def fill_ringbuffer(self, n=CAPACITY):
for x in range(0, n):
self.ringbuffer.add(x)
def test_str(self):
self.assertTrue(str(self.ringbuffer).startswith("Ringbuffer"))
@unittest.skipIf(
compare_client_version("4.1") < 0, "Tests the features added in 4.1 version of the client"
)
class RingbufferReadManyTest(SingleMemberTestCase):
@classmethod
def configure_client(cls, config):
config["cluster_name"] = cls.cluster.id
return config
@classmethod
def configure_cluster(cls):
path = os.path.abspath(__file__)
dir_path = os.path.dirname(path)
with open(os.path.join(dir_path, "hazelcast.xml")) as f:
return f.read()
def setUp(self):
self.ringbuffer = self.client.get_ringbuffer(
"ClientRingbufferTestWithTTL-" + random_string()
).blocking()
def tearDown(self):
self.ringbuffer.destroy()
def test_when_start_sequence_is_no_longer_available_gets_clamped(self):
self.fill_ringbuffer(item_count=CAPACITY + 1)
result_set = self.ringbuffer.read_many(0, 1, CAPACITY)
self.assertEqual(CAPACITY, result_set.read_count)
self.assertEqual(CAPACITY, result_set.size)
self.assertEqual(CAPACITY + 1, result_set.next_sequence_to_read_from)
for i in range(1, CAPACITY + 1):
self.assertEqual(i, result_set[i - 1])
self.assertEqual(i, result_set.get_sequence(i - 1))
def test_when_start_sequence_is_equal_to_tail_sequence(self):
self.fill_ringbuffer()
result_set = self.ringbuffer.read_many(CAPACITY - 1, 1, CAPACITY)
self.assertEqual(1, result_set.read_count)
self.assertEqual(1, result_set.size)
self.assertEqual(CAPACITY, result_set.next_sequence_to_read_from)
self.assertEqual(CAPACITY - 1, result_set[0])
self.assertEqual(CAPACITY - 1, result_set.get_sequence(0))
def test_when_start_sequence_is_beyond_tail_sequence_then_blocks(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY + 1, 1, CAPACITY)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
def test_when_min_count_items_are_not_available_then_blocks(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY - 1, 2, 3)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
def test_when_some_waiting_needed(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY - 1, 2, 3)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
self.ringbuffer.add(CAPACITY)
self.assertTrueEventually(lambda: self.assertTrue(result_set_future.done()))
result_set = result_set_future.result()
self.assertEqual(2, result_set.read_count)
self.assertEqual(2, result_set.size)
self.assertEqual(CAPACITY + 1, result_set.next_sequence_to_read_from)
self.assertEqual(CAPACITY - 1, result_set[0])
self.assertEqual(CAPACITY - 1, result_set.get_sequence(0))
self.assertEqual(CAPACITY, result_set[1])
self.assertEqual(CAPACITY, result_set.get_sequence(1))
def test_min_zero_when_item_available(self):
self.fill_ringbuffer()
result_set = self.ringbuffer.read_many(0, 0, 1)
self.assertEqual(1, result_set.read_count)
self.assertEqual(1, result_set.size)
def test_min_zero_when_no_item_available(self):
result_set = self.ringbuffer.read_many(0, 0, 1)
self.assertEqual(0, result_set.read_count)
self.assertEqual(0, result_set.size)
def test_max_count(self):
# If more results are available than needed, the surplus results
# should not be read.
self.fill_ringbuffer()
max_count = CAPACITY // 2
result_set = self.ringbuffer.read_many(0, 0, max_count)
self.assertEqual(max_count, result_set.read_count)
self.assertEqual(max_count, result_set.size)
self.assertEqual(max_count, result_set.next_sequence_to_read_from)
for i in range(max_count):
self.assertEqual(i, result_set[i])
self.assertEqual(i, result_set.get_sequence(i))
def test_filter(self):
def item_factory(i):
if i % 2 == 0:
return "good%s" % i
return "bad%s" % i
self.fill_ringbuffer(item_factory)
expected_size = CAPACITY // 2
result_set = self.ringbuffer.read_many(0, 0, CAPACITY, PrefixFilter("good"))
self.assertEqual(CAPACITY, result_set.read_count)
self.assertEqual(expected_size, result_set.size)
self.assertEqual(CAPACITY, result_set.next_sequence_to_read_from)
for i in range(expected_size):
self.assertEqual(item_factory(i * 2), result_set[i])
self.assertEqual(i * 2, result_set.get_sequence(i))
def test_filter_with_max_count(self):
def item_factory(i):
if i % 2 == 0:
return "good%s" % i
return "bad%s" % i
self.fill_ringbuffer(item_factory)
expected_size = 3
result_set = self.ringbuffer.read_many(0, 0, expected_size, PrefixFilter("good"))
self.assertEqual(expected_size * 2 - 1, result_set.read_count)
self.assertEqual(expected_size, result_set.size)
self.assertEqual(expected_size * 2 - 1, result_set.next_sequence_to_read_from)
for i in range(expected_size):
self.assertEqual(item_factory(i * 2), result_set[i])
self.assertEqual(i * 2, result_set.get_sequence(i))
def fill_ringbuffer(self, item_factory=lambda i: i, item_count=CAPACITY):
for i in range(0, item_count):
self.ringbuffer.add(item_factory(i))
class PrefixFilter(IdentifiedDataSerializable):
def __init__(self, prefix):
self.prefix = prefix
def write_data(self, object_data_output):
object_data_output.write_string(self.prefix)
def read_data(self, object_data_input):
self.prefix = object_data_input.read_string()
def get_factory_id(self):
return 666
def get_class_id(self):
return 14
| 35.149306 | 94 | 0.681122 | import os
import time
import unittest
from hazelcast.proxy.ringbuffer import OVERFLOW_POLICY_FAIL, MAX_BATCH_SIZE
from hazelcast.serialization.api import IdentifiedDataSerializable
from tests.base import SingleMemberTestCase
from tests.util import random_string, compare_client_version
CAPACITY = 10
class RingBufferTest(SingleMemberTestCase):
@classmethod
def configure_client(cls, config):
config["cluster_name"] = cls.cluster.id
return config
@classmethod
def configure_cluster(cls):
path = os.path.abspath(__file__)
dir_path = os.path.dirname(path)
with open(os.path.join(dir_path, "hazelcast.xml")) as f:
return f.read()
def setUp(self):
self.ringbuffer = self.client.get_ringbuffer(
"ClientRingbufferTestWithTTL-" + random_string()
).blocking()
def tearDown(self):
self.ringbuffer.destroy()
def test_capacity(self):
self.assertEqual(self.ringbuffer.capacity(), CAPACITY)
def test_add_size(self):
self.assertEqual(0, self.ringbuffer.add("value"))
self.assertEqual(1, self.ringbuffer.add("value"))
self.assertEqual(2, self.ringbuffer.add("value"))
self.assertEqual(3, self.ringbuffer.size())
def test_add_when_full(self):
self.fill_ringbuffer()
self.assertEqual(-1, self.ringbuffer.add(CAPACITY + 1, OVERFLOW_POLICY_FAIL))
def test_add_all(self):
self.assertEqual(CAPACITY - 1, self.ringbuffer.add_all(list(range(0, CAPACITY))))
def test_add_all_when_full(self):
self.assertEqual(
-1, self.ringbuffer.add_all(list(range(0, CAPACITY * 2)), OVERFLOW_POLICY_FAIL)
)
def test_add_all_when_empty_list(self):
with self.assertRaises(AssertionError):
self.ringbuffer.add_all([])
def test_add_all_when_too_large_batch(self):
with self.assertRaises(AssertionError):
self.ringbuffer.add_all(list(range(0, MAX_BATCH_SIZE + 1)))
def test_head_sequence(self):
self.fill_ringbuffer(CAPACITY * 2)
self.assertEqual(CAPACITY, self.ringbuffer.head_sequence())
def test_tail_sequence(self):
self.fill_ringbuffer(CAPACITY * 2)
self.assertEqual(CAPACITY * 2 - 1, self.ringbuffer.tail_sequence())
def test_remaining_capacity(self):
self.fill_ringbuffer(CAPACITY // 2)
self.assertEqual(CAPACITY // 2, self.ringbuffer.remaining_capacity())
def test_read_one(self):
self.ringbuffer.add("item")
self.ringbuffer.add("item-2")
self.ringbuffer.add("item-3")
self.assertEqual("item", self.ringbuffer.read_one(0))
self.assertEqual("item-2", self.ringbuffer.read_one(1))
self.assertEqual("item-3", self.ringbuffer.read_one(2))
def test_read_one_negative_sequence(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_one(-1)
def test_read_many(self):
self.fill_ringbuffer(CAPACITY)
items = self.ringbuffer.read_many(0, 0, CAPACITY)
self.assertEqual(items, list(range(0, CAPACITY)))
def test_read_many_when_negative_start_seq(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(-1, 0, CAPACITY)
def test_read_many_when_min_count_greater_than_max_count(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, CAPACITY, 0)
def test_read_many_when_min_count_greater_than_capacity(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, CAPACITY + 1, CAPACITY + 1)
def test_read_many_when_max_count_greater_than_batch_size(self):
with self.assertRaises(AssertionError):
self.ringbuffer.read_many(0, 0, MAX_BATCH_SIZE + 1)
def fill_ringbuffer(self, n=CAPACITY):
for x in range(0, n):
self.ringbuffer.add(x)
def test_str(self):
self.assertTrue(str(self.ringbuffer).startswith("Ringbuffer"))
@unittest.skipIf(
compare_client_version("4.1") < 0, "Tests the features added in 4.1 version of the client"
)
class RingbufferReadManyTest(SingleMemberTestCase):
@classmethod
def configure_client(cls, config):
config["cluster_name"] = cls.cluster.id
return config
@classmethod
def configure_cluster(cls):
path = os.path.abspath(__file__)
dir_path = os.path.dirname(path)
with open(os.path.join(dir_path, "hazelcast.xml")) as f:
return f.read()
def setUp(self):
self.ringbuffer = self.client.get_ringbuffer(
"ClientRingbufferTestWithTTL-" + random_string()
).blocking()
def tearDown(self):
self.ringbuffer.destroy()
def test_when_start_sequence_is_no_longer_available_gets_clamped(self):
self.fill_ringbuffer(item_count=CAPACITY + 1)
result_set = self.ringbuffer.read_many(0, 1, CAPACITY)
self.assertEqual(CAPACITY, result_set.read_count)
self.assertEqual(CAPACITY, result_set.size)
self.assertEqual(CAPACITY + 1, result_set.next_sequence_to_read_from)
for i in range(1, CAPACITY + 1):
self.assertEqual(i, result_set[i - 1])
self.assertEqual(i, result_set.get_sequence(i - 1))
def test_when_start_sequence_is_equal_to_tail_sequence(self):
self.fill_ringbuffer()
result_set = self.ringbuffer.read_many(CAPACITY - 1, 1, CAPACITY)
self.assertEqual(1, result_set.read_count)
self.assertEqual(1, result_set.size)
self.assertEqual(CAPACITY, result_set.next_sequence_to_read_from)
self.assertEqual(CAPACITY - 1, result_set[0])
self.assertEqual(CAPACITY - 1, result_set.get_sequence(0))
def test_when_start_sequence_is_beyond_tail_sequence_then_blocks(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY + 1, 1, CAPACITY)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
def test_when_min_count_items_are_not_available_then_blocks(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY - 1, 2, 3)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
def test_when_some_waiting_needed(self):
self.fill_ringbuffer()
result_set_future = self.ringbuffer._wrapped.read_many(CAPACITY - 1, 2, 3)
time.sleep(0.5)
self.assertFalse(result_set_future.done())
self.ringbuffer.add(CAPACITY)
self.assertTrueEventually(lambda: self.assertTrue(result_set_future.done()))
result_set = result_set_future.result()
self.assertEqual(2, result_set.read_count)
self.assertEqual(2, result_set.size)
self.assertEqual(CAPACITY + 1, result_set.next_sequence_to_read_from)
self.assertEqual(CAPACITY - 1, result_set[0])
self.assertEqual(CAPACITY - 1, result_set.get_sequence(0))
self.assertEqual(CAPACITY, result_set[1])
self.assertEqual(CAPACITY, result_set.get_sequence(1))
def test_min_zero_when_item_available(self):
self.fill_ringbuffer()
result_set = self.ringbuffer.read_many(0, 0, 1)
self.assertEqual(1, result_set.read_count)
self.assertEqual(1, result_set.size)
def test_min_zero_when_no_item_available(self):
result_set = self.ringbuffer.read_many(0, 0, 1)
self.assertEqual(0, result_set.read_count)
self.assertEqual(0, result_set.size)
def test_max_count(self):
self.fill_ringbuffer()
max_count = CAPACITY // 2
result_set = self.ringbuffer.read_many(0, 0, max_count)
self.assertEqual(max_count, result_set.read_count)
self.assertEqual(max_count, result_set.size)
self.assertEqual(max_count, result_set.next_sequence_to_read_from)
for i in range(max_count):
self.assertEqual(i, result_set[i])
self.assertEqual(i, result_set.get_sequence(i))
def test_filter(self):
def item_factory(i):
if i % 2 == 0:
return "good%s" % i
return "bad%s" % i
self.fill_ringbuffer(item_factory)
expected_size = CAPACITY // 2
result_set = self.ringbuffer.read_many(0, 0, CAPACITY, PrefixFilter("good"))
self.assertEqual(CAPACITY, result_set.read_count)
self.assertEqual(expected_size, result_set.size)
self.assertEqual(CAPACITY, result_set.next_sequence_to_read_from)
for i in range(expected_size):
self.assertEqual(item_factory(i * 2), result_set[i])
self.assertEqual(i * 2, result_set.get_sequence(i))
def test_filter_with_max_count(self):
def item_factory(i):
if i % 2 == 0:
return "good%s" % i
return "bad%s" % i
self.fill_ringbuffer(item_factory)
expected_size = 3
result_set = self.ringbuffer.read_many(0, 0, expected_size, PrefixFilter("good"))
self.assertEqual(expected_size * 2 - 1, result_set.read_count)
self.assertEqual(expected_size, result_set.size)
self.assertEqual(expected_size * 2 - 1, result_set.next_sequence_to_read_from)
for i in range(expected_size):
self.assertEqual(item_factory(i * 2), result_set[i])
self.assertEqual(i * 2, result_set.get_sequence(i))
def fill_ringbuffer(self, item_factory=lambda i: i, item_count=CAPACITY):
for i in range(0, item_count):
self.ringbuffer.add(item_factory(i))
class PrefixFilter(IdentifiedDataSerializable):
def __init__(self, prefix):
self.prefix = prefix
def write_data(self, object_data_output):
object_data_output.write_string(self.prefix)
def read_data(self, object_data_input):
self.prefix = object_data_input.read_string()
def get_factory_id(self):
return 666
def get_class_id(self):
return 14
| true | true |
f7fe8d28e8dc1fb58856177bde8fe5f919326feb | 6,780 | py | Python | bci_framework/framework/widgets/annotations.py | UN-GCPDS/bci-framework- | b51f530967561738dc34752acf6add20cbb02283 | [
"BSD-2-Clause"
] | null | null | null | bci_framework/framework/widgets/annotations.py | UN-GCPDS/bci-framework- | b51f530967561738dc34752acf6add20cbb02283 | [
"BSD-2-Clause"
] | null | null | null | bci_framework/framework/widgets/annotations.py | UN-GCPDS/bci-framework- | b51f530967561738dc34752acf6add20cbb02283 | [
"BSD-2-Clause"
] | null | null | null | """
===========
Annotations
===========
"""
from datetime import datetime
from typing import Optional
from PySide6.QtWidgets import QTableWidgetItem
########################################################################
class Annotations:
"""Widget connected with Kafka to stream messages."""
# ----------------------------------------------------------------------
def __init__(self, parent, core):
"""Constructor"""
self.parent_frame = parent
self.core = core
self.connect()
# ----------------------------------------------------------------------
def set_enable(self, enable):
""""""
self.parent_frame.pushButton_save_annotation.setEnabled(enable)
self.parent_frame.pushButton_save_marker.setEnabled(enable)
self.parent_frame.pushButton_save_command.setEnabled(enable)
# ----------------------------------------------------------------------
def connect(self) -> None:
"""Connect events."""
self.parent_frame.pushButton_save_annotation.clicked.connect(
self.save_annotation)
self.parent_frame.pushButton_save_marker.clicked.connect(
self.save_marker)
self.parent_frame.pushButton_save_command.clicked.connect(
self.save_command)
self.parent_frame.pushButton_remove_annotations.clicked.connect(lambda:
self.parent_frame.tableWidget_annotations.setRowCount(0))
self.parent_frame.pushButton_remove_markers.clicked.connect(lambda:
self.parent_frame.tableWidget_markers.setRowCount(0))
self.parent_frame.pushButton_remove_commands.clicked.connect(lambda:
self.parent_frame.tableWidget_commands.setRowCount(0))
# ----------------------------------------------------------------------
def save_annotation(self) -> None:
"""Write the annotation in the streaming."""
content = self.parent_frame.textEdit_annotations.toPlainText()
duration = self.parent_frame.doubleSpinBox_annotation_duration.value()
data_ = {'duration': duration,
'description': content,
'onset': datetime.now()}
self.core.thread_kafka.produser.send('annotation', data_)
# ----------------------------------------------------------------------
def save_marker(self) -> None:
"""Write the marker in the streaming."""
marker = self.parent_frame.lineEdit_marker.text()
data_ = {'marker': marker,
'datetime': datetime.now()}
self.core.thread_kafka.produser.send('marker', data_)
# ----------------------------------------------------------------------
def save_command(self) -> None:
"""Write the command in the streaming."""
command = self.parent_frame.lineEdit_command.text()
data_ = {'command': command,
'datetime': datetime.now()}
self.core.thread_kafka.produser.send('command', data_)
# ----------------------------------------------------------------------
def add_annotation(self, onset, duration: str, description: str, action: Optional[bool] = True) -> None:
"""Write the annotation in the GUI."""
row = self.parent_frame.tableWidget_annotations.rowCount()
self.parent_frame.tableWidget_annotations.insertRow(row)
item = QTableWidgetItem(onset.strftime("%x %X"))
self.parent_frame.tableWidget_annotations.setItem(row, 0, item)
item = QTableWidgetItem(f"{duration}")
self.parent_frame.tableWidget_annotations.setItem(row, 1, item)
item = QTableWidgetItem(description)
self.parent_frame.tableWidget_annotations.setItem(row, 2, item)
if description == 'start_record':
self.core.records.record_signal(True)
elif description == 'stop_record':
self.core.records.record_signal(False)
# ----------------------------------------------------------------------
def add_marker(self, onset: str, marker: str, timestamp: Optional[bool] = True) -> None:
"""Write the marker in the GUI."""
row = self.parent_frame.tableWidget_markers.rowCount()
self.parent_frame.tableWidget_markers.insertRow(row)
if timestamp:
item = QTableWidgetItem(onset.strftime("%x %X"))
else:
item = QTableWidgetItem(onset)
self.parent_frame.tableWidget_markers.setItem(row, 0, item)
item = QTableWidgetItem(f"{marker}")
self.parent_frame.tableWidget_markers.setItem(row, 1, item)
# ----------------------------------------------------------------------
def add_command(self, onset: str, command: str) -> None:
"""Write the command in the GUI."""
row = self.parent_frame.tableWidget_commands.rowCount()
self.parent_frame.tableWidget_commands.insertRow(row)
item = QTableWidgetItem(onset.strftime("%x %X"))
self.parent_frame.tableWidget_commands.setItem(row, 0, item)
item = QTableWidgetItem(f"{marker}")
self.parent_frame.tableWidget_commands.setItem(row, 1, item)
# ----------------------------------------------------------------------
def bulk_annotations(self, annotations):
""""""
columns = ['Onset', 'Duration', 'Description']
self.parent_frame.tableWidget_annotations.clear()
self.parent_frame.tableWidget_annotations.setRowCount(0)
self.parent_frame.tableWidget_annotations.setColumnCount(
len(columns))
self.parent_frame.tableWidget_annotations.setHorizontalHeaderLabels(
columns)
for onset, duration, description in annotations:
if not description in ['start_record', 'stop_record']:
self.add_annotation(
onset, duration, description, action=False)
self.parent_frame.tableWidget_annotations.sortByColumn(0)
# ----------------------------------------------------------------------
def bulk_markers(self, markers):
""""""
columns = ['Datetime', 'Marker']
self.parent_frame.tableWidget_markers.clear()
self.parent_frame.tableWidget_markers.setRowCount(0)
self.parent_frame.tableWidget_markers.setColumnCount(len(columns))
self.parent_frame.tableWidget_markers.setHorizontalHeaderLabels(
columns)
for marker in markers:
for onset in markers[marker]:
self.add_marker(f'{onset/1000:.2f} s',
marker, timestamp=False)
self.parent_frame.tableWidget_markers.sortByColumn(0)
| 45.503356 | 129 | 0.558112 | from datetime import datetime
from typing import Optional
from PySide6.QtWidgets import QTableWidgetItem
t_annotations.setItem(row, 0, item)
item = QTableWidgetItem(f"{duration}")
self.parent_frame.tableWidget_annotations.setItem(row, 1, item)
item = QTableWidgetItem(description)
self.parent_frame.tableWidget_annotations.setItem(row, 2, item)
if description == 'start_record':
self.core.records.record_signal(True)
elif description == 'stop_record':
self.core.records.record_signal(False)
def add_marker(self, onset: str, marker: str, timestamp: Optional[bool] = True) -> None:
row = self.parent_frame.tableWidget_markers.rowCount()
self.parent_frame.tableWidget_markers.insertRow(row)
if timestamp:
item = QTableWidgetItem(onset.strftime("%x %X"))
else:
item = QTableWidgetItem(onset)
self.parent_frame.tableWidget_markers.setItem(row, 0, item)
item = QTableWidgetItem(f"{marker}")
self.parent_frame.tableWidget_markers.setItem(row, 1, item)
def add_command(self, onset: str, command: str) -> None:
row = self.parent_frame.tableWidget_commands.rowCount()
self.parent_frame.tableWidget_commands.insertRow(row)
item = QTableWidgetItem(onset.strftime("%x %X"))
self.parent_frame.tableWidget_commands.setItem(row, 0, item)
item = QTableWidgetItem(f"{marker}")
self.parent_frame.tableWidget_commands.setItem(row, 1, item)
def bulk_annotations(self, annotations):
columns = ['Onset', 'Duration', 'Description']
self.parent_frame.tableWidget_annotations.clear()
self.parent_frame.tableWidget_annotations.setRowCount(0)
self.parent_frame.tableWidget_annotations.setColumnCount(
len(columns))
self.parent_frame.tableWidget_annotations.setHorizontalHeaderLabels(
columns)
for onset, duration, description in annotations:
if not description in ['start_record', 'stop_record']:
self.add_annotation(
onset, duration, description, action=False)
self.parent_frame.tableWidget_annotations.sortByColumn(0)
def bulk_markers(self, markers):
columns = ['Datetime', 'Marker']
self.parent_frame.tableWidget_markers.clear()
self.parent_frame.tableWidget_markers.setRowCount(0)
self.parent_frame.tableWidget_markers.setColumnCount(len(columns))
self.parent_frame.tableWidget_markers.setHorizontalHeaderLabels(
columns)
for marker in markers:
for onset in markers[marker]:
self.add_marker(f'{onset/1000:.2f} s',
marker, timestamp=False)
self.parent_frame.tableWidget_markers.sortByColumn(0)
| true | true |
f7fe8e6b1efe67b3a1d0bed83a9cbf8737d68a1d | 2,835 | py | Python | facebook_example/member/models.py | BeshoyAtef/StudentsPortal | 2df13b92ff3bfb84cc4d5aa8fd844339dabf4643 | [
"BSD-3-Clause"
] | null | null | null | facebook_example/member/models.py | BeshoyAtef/StudentsPortal | 2df13b92ff3bfb84cc4d5aa8fd844339dabf4643 | [
"BSD-3-Clause"
] | null | null | null | facebook_example/member/models.py | BeshoyAtef/StudentsPortal | 2df13b92ff3bfb84cc4d5aa8fd844339dabf4643 | [
"BSD-3-Clause"
] | null | null | null | from django.conf import settings
from django.db import models
from django.db.models.signals import post_save
from django.dispatch import receiver
from django_facebook.models import FacebookModel, get_user_model
from django_facebook.utils import get_profile_model
import logging
logger = logging.getLogger(__name__)
from django_facebook.models import *
from django.db import models
from django.dispatch.dispatcher import receiver
from django_facebook.models import FacebookModel
from django.db.models.signals import post_save
from django_facebook.utils import get_user_model, get_profile_model
from facebook_example import settings
try:
# There can only be one custom user model defined at the same time
if getattr(settings, 'AUTH_USER_MODEL', None) == 'member.CustomFacebookUser':
from django.contrib.auth.models import AbstractUser, UserManager
class CustomFacebookUser(AbstractUser, FacebookModel):
'''
The django 1.5 approach to adding the facebook related fields
'''
objects = UserManager()
# add any customizations you like
state = models.CharField(max_length=255, blank=True, null=True)
except ImportError as e:
logger.info('Couldnt setup FacebookUser, got error %s', e)
pass
# Create your models here.
class UserProfile(FacebookModel):
'''
Inherit the properties from django facebook
'''
mobilenumber = models.CharField(max_length=20 , null=True)
email2 = models.EmailField(max_length=254, unique=True)
user = models.IntegerField(blank=False,unique=True)
class MyCustomProfile(models.Model):
'''
Inherit the properties from django facebook
'''
user = models.OneToOneField(settings.AUTH_USER_MODEL, related_name="profile")
mobilenumber = models.CharField(max_length=20 , null=True)
email2 = models.EmailField(max_length=254, unique=True)
# user_id = models.IntegerField(blank=False,unique=True)
@receiver(post_save)
def create_profile(sender, instance, created, **kwargs):
"""Create a matching profile whenever a user object is created."""
if sender == get_user_model():
user = instance
profile_model = get_profile_model()
if profile_model == UserProfile and created:
profile, new = UserProfile.objects.get_or_create(user=instance)
# class MyCustomProfile(FacebookModel):
# user = models.OneToOneField(settings.AUTH_USER_MODEL)
# @receiver(post_save)
# def create_profile(sender, instance, created, **kwargs):
# # Create a matching profile whenever a user object is created.
# if sender == get_user_model():
# user = instance
# profile_model = get_profile_model()
# if profile_model == MyCustomProfile and created:
# profile, new = MyCustomProfile.objects.get_or_create(user=instance)
| 38.835616 | 81 | 0.736508 | from django.conf import settings
from django.db import models
from django.db.models.signals import post_save
from django.dispatch import receiver
from django_facebook.models import FacebookModel, get_user_model
from django_facebook.utils import get_profile_model
import logging
logger = logging.getLogger(__name__)
from django_facebook.models import *
from django.db import models
from django.dispatch.dispatcher import receiver
from django_facebook.models import FacebookModel
from django.db.models.signals import post_save
from django_facebook.utils import get_user_model, get_profile_model
from facebook_example import settings
try:
if getattr(settings, 'AUTH_USER_MODEL', None) == 'member.CustomFacebookUser':
from django.contrib.auth.models import AbstractUser, UserManager
class CustomFacebookUser(AbstractUser, FacebookModel):
objects = UserManager()
state = models.CharField(max_length=255, blank=True, null=True)
except ImportError as e:
logger.info('Couldnt setup FacebookUser, got error %s', e)
pass
class UserProfile(FacebookModel):
mobilenumber = models.CharField(max_length=20 , null=True)
email2 = models.EmailField(max_length=254, unique=True)
user = models.IntegerField(blank=False,unique=True)
class MyCustomProfile(models.Model):
user = models.OneToOneField(settings.AUTH_USER_MODEL, related_name="profile")
mobilenumber = models.CharField(max_length=20 , null=True)
email2 = models.EmailField(max_length=254, unique=True)
@receiver(post_save)
def create_profile(sender, instance, created, **kwargs):
if sender == get_user_model():
user = instance
profile_model = get_profile_model()
if profile_model == UserProfile and created:
profile, new = UserProfile.objects.get_or_create(user=instance)
| true | true |
f7fe905d5e78bb1dbb32471c4cb29305e6d41633 | 5,220 | py | Python | src/lactolyse/analyses/lactate_threshold.py | dblenkus/performance | bae6105812c2f2414d0c10ddd465bf589503f61a | [
"Apache-2.0"
] | 1 | 2020-01-14T20:23:34.000Z | 2020-01-14T20:23:34.000Z | src/lactolyse/analyses/lactate_threshold.py | dblenkus/performance | bae6105812c2f2414d0c10ddd465bf589503f61a | [
"Apache-2.0"
] | 13 | 2018-07-21T06:48:45.000Z | 2019-05-29T20:57:13.000Z | src/lactolyse/analyses/lactate_threshold.py | dblenkus/performance | bae6105812c2f2414d0c10ddd465bf589503f61a | [
"Apache-2.0"
] | null | null | null | """Lactate threshold analysis."""
import logging
import numpy as np
from .base import BaseAnalysis
from .utils import FittedPolynomial
logger = logging.getLogger(__name__)
class LactateThresholdAnalyses(BaseAnalysis):
"""Lactate threshold analysis."""
name = 'lactate_threshold'
template = 'lactate_treshold.tex'
def _calculate_dmax_context(self, inputs, lac_poly, hr_poly):
"""Calculate context for d-max method."""
# If polynomial has a local minimum on the interval (of
# measurments), take it as a minimum value.
if lac_poly.deriv_roots.size:
# If there are two roots, we know (based on the shape of the
# polynomial) that first one is maximum and second one is
# minimum.
min_x = max(lac_poly.deriv_roots)
# If the minimum is not on the interval (or it doesn't exist),
# we check for the inflection point and take it if it exists.
elif lac_poly.deriv_roots.size:
# Second derivation of third degree polynomial have exactly
# one root (the question is only if it is on the interval).
min_x = lac_poly.second_deriv_roots[0]
# If both conditions are false, we can just take the start of
# the interval, as we know that it is the "most flat" part of
# the polynomial on the interval.
else:
min_x = lac_poly.min_x
max_x = lac_poly.max_x
# Find the point where polynomial starts to raise - threshold is
# 0.3 - and take only real roots (hopefully there is only one).
roots = np.roots(lac_poly.poly - (lac_poly.poly(min_x) + 0.3))
roots = roots[np.logical_and(np.isreal(roots), roots > min_x, roots < max_x)]
start_x = max(roots).real
# Calculate the vector cross product.
v_x = np.poly1d(max_x - start_x)
v_y = np.poly1d(lac_poly.poly(max_x) - lac_poly.poly(start_x))
u_x = np.poly1d([1, -start_x])
u_y = lac_poly.poly - lac_poly.poly(start_x)
cross_z = v_x * u_y - v_y * u_x
ftp = np.roots(cross_z.deriv())
ftp = ftp[np.logical_and(ftp > start_x, ftp < max_x)]
ftp = ftp[0]
return {
'power': ftp,
'start_point': [start_x, lac_poly.poly(start_x)],
'end_point': [max_x, lac_poly.poly(max_x)],
'start_hr': hr_poly.poly(start_x),
'heart_rate': hr_poly.poly(ftp),
'lactate': lac_poly.poly(ftp),
}
def _calculate_cross_context(self, inputs, lac_poly, hr_poly):
"""Calculate context for cross method."""
if lac_poly.deriv_roots.size:
start_point = min(lac_poly.deriv_roots)
else:
start_point = inputs['power'][0]
max_x = lac_poly.max_x
start_line = np.poly1d(
np.polyfit(
[start_point, start_point + 5],
[lac_poly.poly(start_point), lac_poly.poly(start_point + 5)],
1,
)
)
end_line = np.poly1d(
np.polyfit(
[max_x - 5, max_x], [lac_poly.poly(max_x - 5), lac_poly.poly(max_x)], 1
)
)
cross = np.roots(start_line - end_line)
power = cross[0]
return {
'power': power,
'start_point': [start_point, lac_poly.poly(start_point)],
'end_point': [inputs['power'][-1], lac_poly.poly(inputs['power'][-1])],
'cross': [power, start_line(power)],
'heart_rate': hr_poly.poly(power),
'lactate': lac_poly.poly(power),
}
def _calculate_at_context(self, inputs, threshold, lac_poly, hr_poly):
"""Calculate context for at method."""
roots = np.roots(lac_poly.poly - threshold)
roots = roots[np.isreal(roots)]
roots = filter(
lambda val: inputs['power'][0] < val < inputs['power'][-1], roots
)
power = list(roots)[0].real
return {
'power': power,
'heart_rate': hr_poly.poly(power),
'lactate': lac_poly.poly(power),
}
def render_context(self, inputs):
"""Render the context."""
for attr in ['power', 'heart_rate', 'lactate']:
if attr not in inputs:
raise ValueError("Missing input '{}'.".format(attr))
lac_poly = FittedPolynomial(inputs['power'], inputs['lactate'])
hr_poly = FittedPolynomial(inputs['power'], inputs['heart_rate'])
return {
'inputs': inputs,
'lac_poly': lac_poly,
'dmax': self._calculate_dmax_context(inputs, lac_poly, hr_poly),
'cross': self._calculate_cross_context(inputs, lac_poly, hr_poly),
'at2': self._calculate_at_context(inputs, 2, lac_poly, hr_poly),
'at4': self._calculate_at_context(inputs, 4, lac_poly, hr_poly),
}
def get_results(self, context):
"""Return the result of the analysis."""
return {
'dmax': context['dmax']['power'],
'cross': context['cross']['power'],
'at2': context['at2']['power'],
'at4': context['at4']['power'],
}
| 35.753425 | 87 | 0.578544 | import logging
import numpy as np
from .base import BaseAnalysis
from .utils import FittedPolynomial
logger = logging.getLogger(__name__)
class LactateThresholdAnalyses(BaseAnalysis):
name = 'lactate_threshold'
template = 'lactate_treshold.tex'
def _calculate_dmax_context(self, inputs, lac_poly, hr_poly):
if lac_poly.deriv_roots.size:
min_x = max(lac_poly.deriv_roots)
# we check for the inflection point and take it if it exists.
elif lac_poly.deriv_roots.size:
# Second derivation of third degree polynomial have exactly
# one root (the question is only if it is on the interval).
min_x = lac_poly.second_deriv_roots[0]
# If both conditions are false, we can just take the start of
# the interval, as we know that it is the "most flat" part of
# the polynomial on the interval.
else:
min_x = lac_poly.min_x
max_x = lac_poly.max_x
# Find the point where polynomial starts to raise - threshold is
# 0.3 - and take only real roots (hopefully there is only one).
roots = np.roots(lac_poly.poly - (lac_poly.poly(min_x) + 0.3))
roots = roots[np.logical_and(np.isreal(roots), roots > min_x, roots < max_x)]
start_x = max(roots).real
# Calculate the vector cross product.
v_x = np.poly1d(max_x - start_x)
v_y = np.poly1d(lac_poly.poly(max_x) - lac_poly.poly(start_x))
u_x = np.poly1d([1, -start_x])
u_y = lac_poly.poly - lac_poly.poly(start_x)
cross_z = v_x * u_y - v_y * u_x
ftp = np.roots(cross_z.deriv())
ftp = ftp[np.logical_and(ftp > start_x, ftp < max_x)]
ftp = ftp[0]
return {
'power': ftp,
'start_point': [start_x, lac_poly.poly(start_x)],
'end_point': [max_x, lac_poly.poly(max_x)],
'start_hr': hr_poly.poly(start_x),
'heart_rate': hr_poly.poly(ftp),
'lactate': lac_poly.poly(ftp),
}
def _calculate_cross_context(self, inputs, lac_poly, hr_poly):
if lac_poly.deriv_roots.size:
start_point = min(lac_poly.deriv_roots)
else:
start_point = inputs['power'][0]
max_x = lac_poly.max_x
start_line = np.poly1d(
np.polyfit(
[start_point, start_point + 5],
[lac_poly.poly(start_point), lac_poly.poly(start_point + 5)],
1,
)
)
end_line = np.poly1d(
np.polyfit(
[max_x - 5, max_x], [lac_poly.poly(max_x - 5), lac_poly.poly(max_x)], 1
)
)
cross = np.roots(start_line - end_line)
power = cross[0]
return {
'power': power,
'start_point': [start_point, lac_poly.poly(start_point)],
'end_point': [inputs['power'][-1], lac_poly.poly(inputs['power'][-1])],
'cross': [power, start_line(power)],
'heart_rate': hr_poly.poly(power),
'lactate': lac_poly.poly(power),
}
def _calculate_at_context(self, inputs, threshold, lac_poly, hr_poly):
roots = np.roots(lac_poly.poly - threshold)
roots = roots[np.isreal(roots)]
roots = filter(
lambda val: inputs['power'][0] < val < inputs['power'][-1], roots
)
power = list(roots)[0].real
return {
'power': power,
'heart_rate': hr_poly.poly(power),
'lactate': lac_poly.poly(power),
}
def render_context(self, inputs):
for attr in ['power', 'heart_rate', 'lactate']:
if attr not in inputs:
raise ValueError("Missing input '{}'.".format(attr))
lac_poly = FittedPolynomial(inputs['power'], inputs['lactate'])
hr_poly = FittedPolynomial(inputs['power'], inputs['heart_rate'])
return {
'inputs': inputs,
'lac_poly': lac_poly,
'dmax': self._calculate_dmax_context(inputs, lac_poly, hr_poly),
'cross': self._calculate_cross_context(inputs, lac_poly, hr_poly),
'at2': self._calculate_at_context(inputs, 2, lac_poly, hr_poly),
'at4': self._calculate_at_context(inputs, 4, lac_poly, hr_poly),
}
def get_results(self, context):
return {
'dmax': context['dmax']['power'],
'cross': context['cross']['power'],
'at2': context['at2']['power'],
'at4': context['at4']['power'],
}
| true | true |
f7fe91bb7fea8e7716c174a498d3d5323bb31a62 | 5,183 | py | Python | recommender6_slopeone.py | nabeeltariq2/res-repo | faa4277b537e1075fa38d79c1a9fa31b0fd8c3af | [
"Apache-2.0"
] | null | null | null | recommender6_slopeone.py | nabeeltariq2/res-repo | faa4277b537e1075fa38d79c1a9fa31b0fd8c3af | [
"Apache-2.0"
] | null | null | null | recommender6_slopeone.py | nabeeltariq2/res-repo | faa4277b537e1075fa38d79c1a9fa31b0fd8c3af | [
"Apache-2.0"
] | null | null | null | # from __future__ import absolute_import, division, print_function, unicode_literals
# from surprise import evaluate, print_perf, dump, Reader, Dataset
#import algorithms from surprise
from surprise import evaluate, print_perf, Reader, Dataset, accuracy
# from surprise import KNNBasic, KNNWithMeans, KNNWithZScore, AlgoBase, SlopeOne, CoClustering, NormalPredictor,NMF, SVD, BaselineOnly
import time
start_time = time.time()
from surprise import SlopeOne
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
np.random.seed(101)
from collections import defaultdict
import os, io, sys
from sqlalchemy.orm import sessionmaker, scoped_session
from sqlalchemy import ForeignKey
from sqlalchemy.orm import relationship, backref
import config
# from surprise import dump
# from model import add_pageview
# algorithm = NMF(n_epochs=10)
def compute_recommendations(user_id, prediction_table, numeric_prediction_table):
algo = 'SlopeOne'
algorithm = SlopeOne()
# add_pageview(user_id=user_id, item_id=None, page="Model Predictions", activity_type="Initialize Predictions - " + algo, rating=None) #pageview
engine = create_engine(config.DB_URI, echo=True)
session = scoped_session(sessionmaker(bind=engine,
autocommit = False,
autoflush = False))
#reading in the database
df_ratings = pd.read_sql('SELECT * FROM ratings;', con = engine)
df_ratings=df_ratings[['user_id','item_id','rating']]
df_ratings = df_ratings.dropna()
df_ratings = df_ratings.drop_duplicates()
df_ratings2 = pd.read_csv('data/ratings.csv', low_memory=False)
df_ratings2 = df_ratings2.rename(columns = {'movie_id': 'item_id'})
df_ratings2 = df_ratings2[['user_id','item_id','rating']]
df_ratings2 = df_ratings2.dropna()
df_ratings2 = df_ratings2.drop_duplicates()
df_ratings = pd.concat([df_ratings, df_ratings2], axis=0)
reader = Reader(line_format='user item rating', sep=',', rating_scale=(1, 10))
data = Dataset.load_from_df(df_ratings, reader=reader)
trainset = data.build_full_trainset()
# algorithm = eval(algo + "()")# set the algorithm...............................................
algorithm.train(trainset)
items = pd.read_sql('SELECT distinct id FROM items;', con = engine)
df_user_items = df_ratings.loc[df_ratings['user_id'] == user_id]
total_items = items.id.unique()
user_items = df_user_items.item_id.unique()
# user_id = str(user_id)
prediction_items = [x for x in total_items if x not in user_items]
predictions = pd.DataFrame(columns=['user_id', 'item_id', 'prediction'])
predicted_ratings = []
for i in prediction_items:
a = user_id
b = i
est = algorithm.predict(a, b)
predicted_ratings.append(est[3])
predictions['item_id'] = prediction_items
predictions['user_id'] = pd.Series([user_id for x in range(len(predictions.index))], index=predictions.index)
predictions['prediction'] = predicted_ratings
predictions = predictions.sort_values('prediction', ascending=False)
test_prediction = predictions
predictions = predictions.head(n=10)
cols =['pred_1', 'pred_2','pred_3','pred_4',
'pred_5','pred_6','pred_7','pred_8',
'pred_9','pred_10']
df_pred = predictions[['item_id']].T
df_pred.columns = cols
df_pred['id'] = user_id
df_pred = df_pred[['id','pred_1', 'pred_2','pred_3','pred_4',
'pred_5','pred_6','pred_7','pred_8',
'pred_9','pred_10']]
df_pred['id'] = df_pred['id'].astype(int)
df_pred.to_sql(prediction_table, engine,if_exists='append', index=False)#if_exists='append'
session.commit()
df_num_ratings = test_prediction
df_num_ratings = df_num_ratings.head(n=20)
df_num_ratings['algorithm'] = algo
df_num_ratings.rename(columns={'prediction':'predicted_rating'}, inplace=True)
df_num_ratings.to_sql('numeric_predictions',engine,if_exists='append', index=False)#if_exists='append'
session.commit()
predcols =['num_1', 'num_2','num_3','num_4',
'num_5','num_6','num_7','num_8',
'num_9','num_10']
df_num_ratings_transpose = predictions[['prediction']].T
df_num_ratings_transpose.columns = predcols
df_num_ratings_transpose['id'] = user_id
df_num_ratings_transpose = df_num_ratings_transpose[['id','num_1', 'num_2','num_3','num_4',
'num_5','num_6','num_7','num_8',
'num_9','num_10']]
df_num_ratings_transpose['id'] = df_num_ratings_transpose['id'].astype(int)
df_num_ratings_transpose.to_sql(numeric_prediction_table,engine,if_exists='append', index=False)#if_exists='append'
session.commit()
# add_pageview(user_id=user_id, item_id=None, page="Model Predictions", activity_type="Finish Computing Predictions - " + algo, rating=None) #pageview
| 28.016216 | 154 | 0.65985 |
from surprise import evaluate, print_perf, Reader, Dataset, accuracy
import time
start_time = time.time()
from surprise import SlopeOne
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
np.random.seed(101)
from collections import defaultdict
import os, io, sys
from sqlalchemy.orm import sessionmaker, scoped_session
from sqlalchemy import ForeignKey
from sqlalchemy.orm import relationship, backref
import config
def compute_recommendations(user_id, prediction_table, numeric_prediction_table):
algo = 'SlopeOne'
algorithm = SlopeOne()
ngine = create_engine(config.DB_URI, echo=True)
session = scoped_session(sessionmaker(bind=engine,
autocommit = False,
autoflush = False))
df_ratings = pd.read_sql('SELECT * FROM ratings;', con = engine)
df_ratings=df_ratings[['user_id','item_id','rating']]
df_ratings = df_ratings.dropna()
df_ratings = df_ratings.drop_duplicates()
df_ratings2 = pd.read_csv('data/ratings.csv', low_memory=False)
df_ratings2 = df_ratings2.rename(columns = {'movie_id': 'item_id'})
df_ratings2 = df_ratings2[['user_id','item_id','rating']]
df_ratings2 = df_ratings2.dropna()
df_ratings2 = df_ratings2.drop_duplicates()
df_ratings = pd.concat([df_ratings, df_ratings2], axis=0)
reader = Reader(line_format='user item rating', sep=',', rating_scale=(1, 10))
data = Dataset.load_from_df(df_ratings, reader=reader)
trainset = data.build_full_trainset()
distinct id FROM items;', con = engine)
df_user_items = df_ratings.loc[df_ratings['user_id'] == user_id]
total_items = items.id.unique()
user_items = df_user_items.item_id.unique()
prediction_items = [x for x in total_items if x not in user_items]
predictions = pd.DataFrame(columns=['user_id', 'item_id', 'prediction'])
predicted_ratings = []
for i in prediction_items:
a = user_id
b = i
est = algorithm.predict(a, b)
predicted_ratings.append(est[3])
predictions['item_id'] = prediction_items
predictions['user_id'] = pd.Series([user_id for x in range(len(predictions.index))], index=predictions.index)
predictions['prediction'] = predicted_ratings
predictions = predictions.sort_values('prediction', ascending=False)
test_prediction = predictions
predictions = predictions.head(n=10)
cols =['pred_1', 'pred_2','pred_3','pred_4',
'pred_5','pred_6','pred_7','pred_8',
'pred_9','pred_10']
df_pred = predictions[['item_id']].T
df_pred.columns = cols
df_pred['id'] = user_id
df_pred = df_pred[['id','pred_1', 'pred_2','pred_3','pred_4',
'pred_5','pred_6','pred_7','pred_8',
'pred_9','pred_10']]
df_pred['id'] = df_pred['id'].astype(int)
df_pred.to_sql(prediction_table, engine,if_exists='append', index=False)
session.commit()
df_num_ratings = test_prediction
df_num_ratings = df_num_ratings.head(n=20)
df_num_ratings['algorithm'] = algo
df_num_ratings.rename(columns={'prediction':'predicted_rating'}, inplace=True)
df_num_ratings.to_sql('numeric_predictions',engine,if_exists='append', index=False)
session.commit()
predcols =['num_1', 'num_2','num_3','num_4',
'num_5','num_6','num_7','num_8',
'num_9','num_10']
df_num_ratings_transpose = predictions[['prediction']].T
df_num_ratings_transpose.columns = predcols
df_num_ratings_transpose['id'] = user_id
df_num_ratings_transpose = df_num_ratings_transpose[['id','num_1', 'num_2','num_3','num_4',
'num_5','num_6','num_7','num_8',
'num_9','num_10']]
df_num_ratings_transpose['id'] = df_num_ratings_transpose['id'].astype(int)
df_num_ratings_transpose.to_sql(numeric_prediction_table,engine,if_exists='append', index=False)
session.commit()
| true | true |
f7fe92de27e332ed4bde871e61045dabc3d46969 | 957 | py | Python | mmgen/datasets/__init__.py | HXWAndCL/mmgeneration | 9afb1d740bf56a4ecde5064d5bb2a4e2d777638b | [
"Apache-2.0"
] | 1 | 2021-09-29T02:57:18.000Z | 2021-09-29T02:57:18.000Z | mmgen/datasets/__init__.py | HXWAndCL/mmgeneration | 9afb1d740bf56a4ecde5064d5bb2a4e2d777638b | [
"Apache-2.0"
] | null | null | null | mmgen/datasets/__init__.py | HXWAndCL/mmgeneration | 9afb1d740bf56a4ecde5064d5bb2a4e2d777638b | [
"Apache-2.0"
] | null | null | null | from .builder import build_dataloader, build_dataset
from .dataset_wrappers import RepeatDataset
from .grow_scale_image_dataset import GrowScaleImgDataset
from .paired_image_dataset import PairedImageDataset
from .pipelines import (Collect, Compose, Flip, ImageToTensor,
LoadImageFromFile, Normalize, Resize, ToTensor)
from .quick_test_dataset import QuickTestImageDataset
from .samplers import DistributedSampler
from .singan_dataset import SinGANDataset
from .unconditional_image_dataset import UnconditionalImageDataset
from .unpaired_image_dataset import UnpairedImageDataset
__all__ = [
'build_dataloader', 'build_dataset', 'LoadImageFromFile',
'DistributedSampler', 'UnconditionalImageDataset', 'Compose', 'ToTensor',
'ImageToTensor', 'Collect', 'Flip', 'Resize', 'RepeatDataset', 'Normalize',
'GrowScaleImgDataset', 'SinGANDataset', 'PairedImageDataset',
'UnpairedImageDataset', 'QuickTestImageDataset'
]
| 47.85 | 79 | 0.800418 | from .builder import build_dataloader, build_dataset
from .dataset_wrappers import RepeatDataset
from .grow_scale_image_dataset import GrowScaleImgDataset
from .paired_image_dataset import PairedImageDataset
from .pipelines import (Collect, Compose, Flip, ImageToTensor,
LoadImageFromFile, Normalize, Resize, ToTensor)
from .quick_test_dataset import QuickTestImageDataset
from .samplers import DistributedSampler
from .singan_dataset import SinGANDataset
from .unconditional_image_dataset import UnconditionalImageDataset
from .unpaired_image_dataset import UnpairedImageDataset
__all__ = [
'build_dataloader', 'build_dataset', 'LoadImageFromFile',
'DistributedSampler', 'UnconditionalImageDataset', 'Compose', 'ToTensor',
'ImageToTensor', 'Collect', 'Flip', 'Resize', 'RepeatDataset', 'Normalize',
'GrowScaleImgDataset', 'SinGANDataset', 'PairedImageDataset',
'UnpairedImageDataset', 'QuickTestImageDataset'
]
| true | true |
f7fe937eb62cc9e180b385fc1e2890b36b572aed | 7,616 | py | Python | tutorials/misc/plot_ecog.py | mehdikuchi/mne-python | 864426c4839bab05fd0d142ee20938c336c0b78e | [
"BSD-3-Clause"
] | null | null | null | tutorials/misc/plot_ecog.py | mehdikuchi/mne-python | 864426c4839bab05fd0d142ee20938c336c0b78e | [
"BSD-3-Clause"
] | null | null | null | tutorials/misc/plot_ecog.py | mehdikuchi/mne-python | 864426c4839bab05fd0d142ee20938c336c0b78e | [
"BSD-3-Clause"
] | null | null | null | """
.. _tut_working_with_ecog:
======================
Working with ECoG data
======================
MNE supports working with more than just MEG and EEG data. Here we show some
of the functions that can be used to facilitate working with
electrocorticography (ECoG) data.
"""
# Authors: Eric Larson <larson.eric.d@gmail.com>
# Chris Holdgraf <choldgraf@gmail.com>
# Adam Li <adam2392@gmail.com>
#
# License: BSD (3-clause)
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import mne
from mne.viz import plot_alignment, snapshot_brain_montage
print(__doc__)
# paths to mne datasets - sample ECoG and FreeSurfer subject
misc_path = mne.datasets.misc.data_path()
sample_path = mne.datasets.sample.data_path()
subject = 'sample'
subjects_dir = sample_path + '/subjects'
###############################################################################
# Let's load some ECoG electrode locations and names, and turn them into
# a :class:`mne.channels.DigMontage` class.
# First, use pandas to read in the .tsv file.
# In this tutorial, the electrode coordinates are assumed to be in meters
elec_df = pd.read_csv(misc_path + '/ecog/sample_ecog_electrodes.tsv',
sep='\t', header=0, index_col=None)
ch_names = elec_df['name'].tolist()
ch_coords = elec_df[['x', 'y', 'z']].to_numpy(dtype=float)
ch_pos = dict(zip(ch_names, ch_coords))
# Ideally the nasion/LPA/RPA will also be present from the digitization, here
# we use fiducials estimated from the subject's FreeSurfer MNI transformation:
lpa, nasion, rpa = mne.coreg.get_mni_fiducials(
subject, subjects_dir=subjects_dir)
lpa, nasion, rpa = lpa['r'], nasion['r'], rpa['r']
###############################################################################
# Now we make a :class:`mne.channels.DigMontage` stating that the ECoG
# contacts are in the FreeSurfer surface RAS (i.e., MRI) coordinate system.
montage = mne.channels.make_dig_montage(
ch_pos, coord_frame='mri', nasion=nasion, lpa=lpa, rpa=rpa)
print('Created %s channel positions' % len(ch_names))
###############################################################################
# Now we get the :term:`trans` that transforms from our MRI coordinate system
# to the head coordinate frame. This transform will be applied to the
# data when applying the montage so that standard plotting functions like
# :func:`mne.viz.plot_evoked_topomap` will be aligned properly.
trans = mne.channels.compute_native_head_t(montage)
print(trans)
###############################################################################
# Now that we have our montage, we can load in our corresponding
# time-series data and set the montage to the raw data.
# first we'll load in the sample dataset
raw = mne.io.read_raw_edf(misc_path + '/ecog/sample_ecog.edf')
# drop bad channels
raw.info['bads'].extend([ch for ch in raw.ch_names if ch not in ch_names])
raw.load_data()
raw.drop_channels(raw.info['bads'])
raw.crop(0, 2) # just process 2 sec of data for speed
# attach montage
raw.set_montage(montage)
# set channel types to ECoG (instead of EEG)
raw.set_channel_types({ch_name: 'ecog' for ch_name in raw.ch_names})
###############################################################################
# We can then plot the locations of our electrodes on our subject's brain.
# We'll use :func:`~mne.viz.snapshot_brain_montage` to save the plot as image
# data (along with xy positions of each electrode in the image), so that later
# we can plot frequency band power on top of it.
#
# .. note:: These are not real electrodes for this subject, so they
# do not align to the cortical surface perfectly.
fig = plot_alignment(raw.info, subject=subject, subjects_dir=subjects_dir,
surfaces=['pial'], trans=trans, coord_frame='mri')
mne.viz.set_3d_view(fig, 200, 70, focalpoint=[0, -0.005, 0.03])
xy, im = snapshot_brain_montage(fig, montage)
###############################################################################
# Next, we'll compute the signal power in the gamma (30-90 Hz) and alpha
# (8-12 Hz) bands.
gamma_power_t = raw.copy().filter(30, 90).apply_hilbert(
envelope=True).get_data()
alpha_power_t = raw.copy().filter(8, 12).apply_hilbert(
envelope=True).get_data()
gamma_power = gamma_power_t.mean(axis=-1)
alpha_power = alpha_power_t.mean(axis=-1)
###############################################################################
# Now let's use matplotlib to overplot frequency band power onto the electrodes
# which can be plotted on top of the brain from
# :func:`~mne.viz.snapshot_brain_montage`.
# Convert from a dictionary to array to plot
xy_pts = np.vstack([xy[ch] for ch in raw.info['ch_names']])
# colormap to view spectral power
cmap = 'viridis'
# Create a 1x2 figure showing the average power in gamma and alpha bands.
fig, axs = plt.subplots(1, 2, figsize=(20, 10))
# choose a colormap range wide enough for both frequency bands
_gamma_alpha_power = np.concatenate((gamma_power, alpha_power)).flatten()
vmin, vmax = np.percentile(_gamma_alpha_power, [10, 90])
for ax, band_power, band in zip(axs,
[gamma_power, alpha_power],
['Gamma', 'Alpha']):
ax.imshow(im)
ax.set_axis_off()
sc = ax.scatter(*xy_pts.T, c=band_power, s=200,
cmap=cmap, vmin=vmin, vmax=vmax)
ax.set_title(f'{band} band power', size='x-large')
fig.colorbar(sc, ax=axs)
###############################################################################
# Say we want to visualize the evolution of the power in the gamma band,
# instead of just plotting the average. We can use
# `matplotlib.animation.FuncAnimation` to create an animation and apply this
# to the brain figure.
# create an initialization and animation function
# to pass to FuncAnimation
def init():
"""Create an empty frame."""
return paths,
def animate(i, activity):
"""Animate the plot."""
paths.set_array(activity[:, i])
return paths,
# create the figure and apply the animation of the
# gamma frequency band activity
fig, ax = plt.subplots(figsize=(10, 10))
ax.imshow(im)
ax.set_axis_off()
paths = ax.scatter(*xy_pts.T, c=np.zeros(len(xy_pts)), s=200,
cmap=cmap, vmin=vmin, vmax=vmax)
fig.colorbar(paths, ax=ax)
ax.set_title('Gamma frequency over time (Hilbert transform)',
size='large')
# avoid edge artifacts and decimate, showing just a short chunk
show_power = gamma_power_t[:, 100:150]
anim = animation.FuncAnimation(fig, animate, init_func=init,
fargs=(show_power,),
frames=show_power.shape[1],
interval=200, blit=True)
###############################################################################
# Alternatively, we can project the sensor data to the nearest locations on
# the pial surface and visualize that:
# sphinx_gallery_thumbnail_number = 4
evoked = mne.EvokedArray(gamma_power_t, raw.info)
stc = mne.stc_near_sensors(evoked, trans, subject, subjects_dir=subjects_dir)
clim = dict(kind='value', lims=[vmin * 0.9, vmin, vmax])
brain = stc.plot(surface='pial', hemi='both', initial_time=0.68,
colormap='viridis', clim=clim, views='parietal',
subjects_dir=subjects_dir, size=(600, 600))
# You can save a movie like the one on our documentation website with:
# brain.save_movie(time_dilation=20, tmin=0.62, tmax=0.72,
# interpolation='linear', framerate=5,
# time_viewer=True)
| 39.666667 | 79 | 0.63708 |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import mne
from mne.viz import plot_alignment, snapshot_brain_montage
print(__doc__)
misc_path = mne.datasets.misc.data_path()
sample_path = mne.datasets.sample.data_path()
subject = 'sample'
subjects_dir = sample_path + '/subjects'
| true | true |
f7fe93d37af27cc8887be6f6e40a9eb3b5215dc7 | 954 | py | Python | kubernetes_asyncio/test/test_admissionregistration_api.py | lsst-sqre/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | [
"Apache-2.0"
] | null | null | null | kubernetes_asyncio/test/test_admissionregistration_api.py | lsst-sqre/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | [
"Apache-2.0"
] | null | null | null | kubernetes_asyncio/test/test_admissionregistration_api.py | lsst-sqre/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | [
"Apache-2.0"
] | null | null | null | # coding: utf-8
"""
Kubernetes
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501
The version of the OpenAPI document: v1.19.15
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import unittest
import kubernetes_asyncio.client
from kubernetes_asyncio.client.api.admissionregistration_api import AdmissionregistrationApi # noqa: E501
from kubernetes_asyncio.client.rest import ApiException
class TestAdmissionregistrationApi(unittest.TestCase):
"""AdmissionregistrationApi unit test stubs"""
def setUp(self):
self.api = kubernetes_asyncio.client.api.admissionregistration_api.AdmissionregistrationApi() # noqa: E501
def tearDown(self):
pass
def test_get_api_group(self):
"""Test case for get_api_group
"""
pass
if __name__ == '__main__':
unittest.main()
| 23.85 | 124 | 0.737945 |
from __future__ import absolute_import
import unittest
import kubernetes_asyncio.client
from kubernetes_asyncio.client.api.admissionregistration_api import AdmissionregistrationApi
from kubernetes_asyncio.client.rest import ApiException
class TestAdmissionregistrationApi(unittest.TestCase):
def setUp(self):
self.api = kubernetes_asyncio.client.api.admissionregistration_api.AdmissionregistrationApi()
def tearDown(self):
pass
def test_get_api_group(self):
pass
if __name__ == '__main__':
unittest.main()
| true | true |
f7fe93f298d692c1154a36dc5858a9ef416e0f5f | 6,296 | py | Python | pyfr/integrators/steppers.py | jappa/PyFR | d99120c1db245c7a2a35c72dae51ea72c49efef5 | [
"BSD-3-Clause"
] | null | null | null | pyfr/integrators/steppers.py | jappa/PyFR | d99120c1db245c7a2a35c72dae51ea72c49efef5 | [
"BSD-3-Clause"
] | null | null | null | pyfr/integrators/steppers.py | jappa/PyFR | d99120c1db245c7a2a35c72dae51ea72c49efef5 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
from abc import abstractmethod
from pyfr.integrators.base import BaseIntegrator
from pyfr.util import proxylist
class BaseStepper(BaseIntegrator):
def __init__(self, *args, **kwargs):
super(BaseStepper, self).__init__(*args, **kwargs)
backend = self._backend
elemats = self._system.ele_banks
# Create a proxylist of matrix-banks for each storage register
self._regs = regs = []
self._regidx = regidx = []
for i in xrange(self._stepper_nregs):
b = proxylist([backend.matrix_bank(em, i) for em in elemats])
regs.append(b)
regidx.append(i)
# Add kernel cache
self._axnpby_kerns = {}
def collect_stats(self, stats):
super(BaseStepper, self).collect_stats(stats)
stats.set('solver-time-integrator', 'nsteps', self.nsteps)
stats.set('solver-time-integrator', 'nfevals', self._stepper_nfevals)
def _get_axnpby_kerns(self, n):
try:
return self._axnpby_kerns[n]
except KeyError:
k = self._kernel('axnpby', nargs=n)
# Cache and return
self._axnpby_kerns[n] = k
return k
def _add(self, *args):
# Get a suitable set of axnpby kernels
axnpby = self._get_axnpby_kerns(len(args)/2)
# Bank indices are in odd-numbered arguments
self._prepare_reg_banks(*args[1::2])
# Bind and run the axnpby kernels
self._queue % axnpby(*args[::2])
class EulerStepper(BaseStepper):
stepper_name = 'euler'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return self.nsteps
@property
def _stepper_nregs(self):
return 2
@property
def _stepper_order(self):
return 1
def step(self, t, dt):
add, negdivf = self._add, self._system
ut, f = self._regidx
negdivf(ut, f)
add(1.0, ut, dt, f)
return ut
class RK4Stepper(BaseStepper):
stepper_name = 'rk4'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return 4*self.nsteps
@property
def _stepper_nregs(self):
return 3
@property
def _stepper_order(self):
return 4
def step(self, t, dt):
add, negdivf = self._add, self._system
# Get the bank indices for each register
r0, r1, r2 = self._regidx
# Ensure r0 references the bank containing u(t)
if r0 != self._idxcurr:
r0, r1 = r1, r0
# First stage; r1 = -∇·f(r0)
negdivf(r0, r1)
# Second stage; r2 = r0 + dt/2*r1; r2 = -∇·f(r2)
add(0.0, r2, 1.0, r0, dt/2.0, r1)
negdivf(r2, r2)
# As no subsequent stages depend on the first stage we can
# reuse its register to start accumulating the solution with
# r1 = r0 + dt/6*r1 + dt/3*r2
add(dt/6.0, r1, 1.0, r0, dt/3.0, r2)
# Third stage; here we reuse the r2 register
# r2 = r0 + dt/2*r2
# r2 = -∇·f(r2)
add(dt/2.0, r2, 1.0, r0)
negdivf(r2, r2)
# Accumulate; r1 = r1 + dt/3*r2
add(1.0, r1, dt/3.0, r2)
# Fourth stage; again we reuse r2
# r2 = r0 + dt*r2
# r2 = -∇·f(r2)
add(dt, r2, 1.0, r0)
negdivf(r2, r2)
# Final accumulation r1 = r1 + dt/6*r2 = u(t + dt)
add(1.0, r1, dt/6.0, r2)
# Return the index of the bank containing u(t + dt)
return r1
class DOPRI5Stepper(BaseStepper):
stepper_name = 'dopri5'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return 6*self.nsteps + self.nrjctsteps + 1
@property
def _stepper_nregs(self):
return 7
@property
def _stepper_order(self):
return 5
def step(self, t, dt):
add, negdivf = self._add, self._system
# Register bank indices (r0 = u(t); r1..6 = temp RK 'k' stages)
r0, r1, r2, r3, r4, r5, r6 = self._regidx
# Usually the first stage, -∇·f(r0 = u(t)), is available in
# r1 (this is as the scheme is FSAL), except when the last step
# was rejected. In this case we compute it here.
if not self.nacptchain:
negdivf(r0, r1)
# Second stage; r2 = r0 + dt/5*r1; r2 = -∇·f(r2)
add(0.0, r2, 1.0, r0, dt/5.0, r1)
negdivf(r2, r2)
# Third stage; r3 = r0 + (3/40)*dt*r1 + (9/40)*dt*r2; r3 = -∇·f(r3)
add(0.0, r3, 1.0, r0, 3.0/40.0*dt, r1, 9.0/40.0*dt, r2)
negdivf(r3, r3)
# Fourth stage
# r4 = r0 + (44/45)*dt*r1 + (-56/15)*dt*r2 + (32/9)*dt*r3
# r4 = -∇·f(r4)
add(0.0, r4, 1.0, r0, 44.0/45.0*dt, r1, -56.0/15.0*dt, r2,
32.0/9.0*dt, r3)
negdivf(r4, r4)
# Fifth stage
# r5 = r0 + (19372/6561)*dt*r1 + (-25360/2187)*dt*r2
# + (64448/6561)*dt*r3 + (-212/729)*dt*r4
# r5 = -∇·f(r5)
add(0.0, r5, 1.0, r0, 19372.0/6561.0*dt, r1, -25360.0/2187.0*dt, r2,
64448.0/6561.0*dt, r3, -212.0/729.0*dt, r4)
negdivf(r5, r5)
# Sixth stage; as neither the seventh stage nor the solution
# coefficients depend on the second stage we are able to reuse its
# register here
# r2 = r0 + (9017/3168)*dt*r1 + (-355/33)*dt*r2 + (46732/5247)*dt*r3
# + (49/176)*dt*r4 + (-5103/18656)*dt*r5
# r2 = -∇·f(r2)
add(-355.0/33.0*dt, r2, 1.0, r0, 9017.0/3168.0*dt, r1,
46732.0/5247.0*dt, r3, 49.0/176.0*dt, r4, -5103.0/18656.0*dt, r5)
negdivf(r2, r2)
# Seventh stage; note that r2 contains the sixth stage
# r0 = r0 + (35/384)*dt*r1 + (500/1113)*dt*r3 + (125/192)*dt*r4
# + (-2187/6784)*dt*r5 + (11/84)*dt*r2
# r6 = -∇·f(r0)
add(1.0, r0, 35.0/384.0*dt, r1, 500.0/1113.0*dt, r3,
125.0/192.0*dt, r4, -2187.0/6784.0*dt, r5, 11.0/84.0*dt, r2)
negdivf(r0, r6)
# Swizzle r1 (first stage) and r6 (seventh stage)
self._regidx[1], self._regidx[6] = r6, r1
# Return the index of the bank containing u(t + dt)
return r0
| 28.233184 | 77 | 0.548761 |
from abc import abstractmethod
from pyfr.integrators.base import BaseIntegrator
from pyfr.util import proxylist
class BaseStepper(BaseIntegrator):
def __init__(self, *args, **kwargs):
super(BaseStepper, self).__init__(*args, **kwargs)
backend = self._backend
elemats = self._system.ele_banks
self._regs = regs = []
self._regidx = regidx = []
for i in xrange(self._stepper_nregs):
b = proxylist([backend.matrix_bank(em, i) for em in elemats])
regs.append(b)
regidx.append(i)
self._axnpby_kerns = {}
def collect_stats(self, stats):
super(BaseStepper, self).collect_stats(stats)
stats.set('solver-time-integrator', 'nsteps', self.nsteps)
stats.set('solver-time-integrator', 'nfevals', self._stepper_nfevals)
def _get_axnpby_kerns(self, n):
try:
return self._axnpby_kerns[n]
except KeyError:
k = self._kernel('axnpby', nargs=n)
self._axnpby_kerns[n] = k
return k
def _add(self, *args):
axnpby = self._get_axnpby_kerns(len(args)/2)
self._prepare_reg_banks(*args[1::2])
self._queue % axnpby(*args[::2])
class EulerStepper(BaseStepper):
stepper_name = 'euler'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return self.nsteps
@property
def _stepper_nregs(self):
return 2
@property
def _stepper_order(self):
return 1
def step(self, t, dt):
add, negdivf = self._add, self._system
ut, f = self._regidx
negdivf(ut, f)
add(1.0, ut, dt, f)
return ut
class RK4Stepper(BaseStepper):
stepper_name = 'rk4'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return 4*self.nsteps
@property
def _stepper_nregs(self):
return 3
@property
def _stepper_order(self):
return 4
def step(self, t, dt):
add, negdivf = self._add, self._system
r0, r1, r2 = self._regidx
if r0 != self._idxcurr:
r0, r1 = r1, r0
negdivf(r0, r1)
add(0.0, r2, 1.0, r0, dt/2.0, r1)
negdivf(r2, r2)
add(dt/6.0, r1, 1.0, r0, dt/3.0, r2)
add(dt/2.0, r2, 1.0, r0)
negdivf(r2, r2)
add(1.0, r1, dt/3.0, r2)
add(dt, r2, 1.0, r0)
negdivf(r2, r2)
add(1.0, r1, dt/6.0, r2)
return r1
class DOPRI5Stepper(BaseStepper):
stepper_name = 'dopri5'
@property
def _stepper_has_errest(self):
return False
@property
def _stepper_nfevals(self):
return 6*self.nsteps + self.nrjctsteps + 1
@property
def _stepper_nregs(self):
return 7
@property
def _stepper_order(self):
return 5
def step(self, t, dt):
add, negdivf = self._add, self._system
r0, r1, r2, r3, r4, r5, r6 = self._regidx
if not self.nacptchain:
negdivf(r0, r1)
add(0.0, r2, 1.0, r0, dt/5.0, r1)
negdivf(r2, r2)
add(0.0, r3, 1.0, r0, 3.0/40.0*dt, r1, 9.0/40.0*dt, r2)
negdivf(r3, r3)
add(0.0, r4, 1.0, r0, 44.0/45.0*dt, r1, -56.0/15.0*dt, r2,
32.0/9.0*dt, r3)
negdivf(r4, r4)
add(0.0, r5, 1.0, r0, 19372.0/6561.0*dt, r1, -25360.0/2187.0*dt, r2,
64448.0/6561.0*dt, r3, -212.0/729.0*dt, r4)
negdivf(r5, r5)
add(-355.0/33.0*dt, r2, 1.0, r0, 9017.0/3168.0*dt, r1,
46732.0/5247.0*dt, r3, 49.0/176.0*dt, r4, -5103.0/18656.0*dt, r5)
negdivf(r2, r2)
add(1.0, r0, 35.0/384.0*dt, r1, 500.0/1113.0*dt, r3,
125.0/192.0*dt, r4, -2187.0/6784.0*dt, r5, 11.0/84.0*dt, r2)
negdivf(r0, r6)
self._regidx[1], self._regidx[6] = r6, r1
return r0
| true | true |
f7fe9480e9caa5b2addbc0bbda880e1c1b74575c | 4,336 | py | Python | isi_sdk_8_0/isi_sdk_8_0/models/compatibilities_class_available_available_item.py | mohitjain97/isilon_sdk_python | a371f438f542568edb8cda35e929e6b300b1177c | [
"Unlicense"
] | 24 | 2018-06-22T14:13:23.000Z | 2022-03-23T01:21:26.000Z | isi_sdk_8_0/isi_sdk_8_0/models/compatibilities_class_available_available_item.py | mohitjain97/isilon_sdk_python | a371f438f542568edb8cda35e929e6b300b1177c | [
"Unlicense"
] | 46 | 2018-04-30T13:28:22.000Z | 2022-03-21T21:11:07.000Z | isi_sdk_8_0/isi_sdk_8_0/models/compatibilities_class_available_available_item.py | mohitjain97/isilon_sdk_python | a371f438f542568edb8cda35e929e6b300b1177c | [
"Unlicense"
] | 29 | 2018-06-19T00:14:04.000Z | 2022-02-08T17:51:19.000Z | # coding: utf-8
"""
Isilon SDK
Isilon SDK - Language bindings for the OneFS API # noqa: E501
OpenAPI spec version: 3
Contact: sdk@isilon.com
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
import pprint
import re # noqa: F401
import six
class CompatibilitiesClassAvailableAvailableItem(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
swagger_types = {
'class_1': 'str',
'class_2': 'str'
}
attribute_map = {
'class_1': 'class_1',
'class_2': 'class_2'
}
def __init__(self, class_1=None, class_2=None): # noqa: E501
"""CompatibilitiesClassAvailableAvailableItem - a model defined in Swagger""" # noqa: E501
self._class_1 = None
self._class_2 = None
self.discriminator = None
self.class_1 = class_1
self.class_2 = class_2
@property
def class_1(self):
"""Gets the class_1 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
The first class in an available compatibility # noqa: E501
:return: The class_1 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
:rtype: str
"""
return self._class_1
@class_1.setter
def class_1(self, class_1):
"""Sets the class_1 of this CompatibilitiesClassAvailableAvailableItem.
The first class in an available compatibility # noqa: E501
:param class_1: The class_1 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
:type: str
"""
if class_1 is None:
raise ValueError("Invalid value for `class_1`, must not be `None`") # noqa: E501
self._class_1 = class_1
@property
def class_2(self):
"""Gets the class_2 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
The second class in an available compatibility # noqa: E501
:return: The class_2 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
:rtype: str
"""
return self._class_2
@class_2.setter
def class_2(self, class_2):
"""Sets the class_2 of this CompatibilitiesClassAvailableAvailableItem.
The second class in an available compatibility # noqa: E501
:param class_2: The class_2 of this CompatibilitiesClassAvailableAvailableItem. # noqa: E501
:type: str
"""
if class_2 is None:
raise ValueError("Invalid value for `class_2`, must not be `None`") # noqa: E501
self._class_2 = class_2
def to_dict(self):
"""Returns the model properties as a dict"""
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
return result
def to_str(self):
"""Returns the string representation of the model"""
return pprint.pformat(self.to_dict())
def __repr__(self):
"""For `print` and `pprint`"""
return self.to_str()
def __eq__(self, other):
"""Returns true if both objects are equal"""
if not isinstance(other, CompatibilitiesClassAvailableAvailableItem):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other
| 29.903448 | 101 | 0.599631 |
import pprint
import re
import six
class CompatibilitiesClassAvailableAvailableItem(object):
swagger_types = {
'class_1': 'str',
'class_2': 'str'
}
attribute_map = {
'class_1': 'class_1',
'class_2': 'class_2'
}
def __init__(self, class_1=None, class_2=None):
self._class_1 = None
self._class_2 = None
self.discriminator = None
self.class_1 = class_1
self.class_2 = class_2
@property
def class_1(self):
return self._class_1
@class_1.setter
def class_1(self, class_1):
if class_1 is None:
raise ValueError("Invalid value for `class_1`, must not be `None`")
self._class_1 = class_1
@property
def class_2(self):
return self._class_2
@class_2.setter
def class_2(self, class_2):
if class_2 is None:
raise ValueError("Invalid value for `class_2`, must not be `None`")
self._class_2 = class_2
def to_dict(self):
result = {}
for attr, _ in six.iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
return result
def to_str(self):
return pprint.pformat(self.to_dict())
def __repr__(self):
return self.to_str()
def __eq__(self, other):
if not isinstance(other, CompatibilitiesClassAvailableAvailableItem):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other
| true | true |
f7fe9647502d58cc2c2378dd840d093c46e34c6a | 480 | py | Python | Python/118pascal's_triangle.py | Apocrypse/LeetCode | 3ada2605ce8c8f6dadebf37a30c9c00a0d1ede39 | [
"MIT"
] | 4 | 2020-03-17T03:08:51.000Z | 2022-03-14T17:33:28.000Z | Python/118pascal's_triangle.py | Apocrypse/LeetCode | 3ada2605ce8c8f6dadebf37a30c9c00a0d1ede39 | [
"MIT"
] | null | null | null | Python/118pascal's_triangle.py | Apocrypse/LeetCode | 3ada2605ce8c8f6dadebf37a30c9c00a0d1ede39 | [
"MIT"
] | 3 | 2021-04-29T16:51:02.000Z | 2022-03-19T17:37:56.000Z | class Solution:
def generate(self, numRows):
"""
:type numRows: int
:rtype: List[List[int]]
"""
if not numRows:
return []
pascal = [[1]]
row = 1
while row != numRows:
cur = pascal[-1]
tmp = [1]
for i in range(row-1):
tmp.append(cur[i]+cur[i+1])
tmp.append(1)
pascal.append(tmp)
row += 1
return pascal
| 24 | 43 | 0.410417 | class Solution:
def generate(self, numRows):
if not numRows:
return []
pascal = [[1]]
row = 1
while row != numRows:
cur = pascal[-1]
tmp = [1]
for i in range(row-1):
tmp.append(cur[i]+cur[i+1])
tmp.append(1)
pascal.append(tmp)
row += 1
return pascal
| true | true |
f7fe966c3b3d70911f2c02b9c929b27cbfc3d656 | 7,900 | py | Python | cms/appresolver.py | aleray/django-cms | 9604c580413eadbd746713e27216b33fdb4d9d62 | [
"BSD-3-Clause"
] | 2 | 2016-02-19T04:19:22.000Z | 2016-02-19T04:19:36.000Z | cms/appresolver.py | bhodorog/django-cms | 8b22b400f15b366749101d0041142e5529d5f2d4 | [
"BSD-3-Clause"
] | null | null | null | cms/appresolver.py | bhodorog/django-cms | 8b22b400f15b366749101d0041142e5529d5f2d4 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
from cms.apphook_pool import apphook_pool
from cms.exceptions import NoHomeFound
from cms.utils.moderator import get_page_queryset
from django.conf import settings
from django.conf.urls.defaults import patterns
from django.contrib.sites.models import Site
from django.core.exceptions import ImproperlyConfigured
from django.core.urlresolvers import RegexURLResolver, Resolver404, reverse, \
RegexURLPattern
from django.utils.importlib import import_module
APP_RESOLVERS = []
def clear_app_resolvers():
global APP_RESOLVERS
APP_RESOLVERS = []
def applications_page_check(request, current_page=None, path=None):
"""Tries to find if given path was resolved over application.
Applications have higher priority than other cms pages.
"""
if current_page:
return current_page
if path is None:
# We should get in this branch only if an apphook is active on /
# This removes the non-CMS part of the URL.
path = request.path.replace(reverse('pages-root'), '', 1)
# check if application resolver can resolve this
for resolver in APP_RESOLVERS:
try:
page_id = resolver.resolve_page_id(path)
# yes, it is application page
page = get_page_queryset(request).get(id=page_id)
# If current page was matched, then we have some override for content
# from cms, but keep current page. Otherwise return page to which was application assigned.
return page
except Resolver404:
# Raised if the page is not managed by an apphook
pass
return None
class AppRegexURLResolver(RegexURLResolver):
page_id = None
url_patterns = None
def resolve_page_id(self, path):
"""Resolves requested path similar way how resolve does, but instead
of return callback,.. returns page_id to which was application
assigned.
"""
tried = []
match = self.regex.search(path)
if match:
new_path = path[match.end():]
for pattern in self.url_patterns:
try:
sub_match = pattern.resolve(new_path)
except Resolver404, e:
if 'tried' in e.args[0]:
tried.extend([(pattern.regex.pattern + ' ' + t) for t in e.args[0]['tried']])
elif 'path' in e.args[0]:
tried.extend([(pattern.regex.pattern + ' ' + t) for t in e.args[0]['path']])
else:
if sub_match:
return pattern.page_id
tried.append(pattern.regex.pattern)
raise Resolver404, {'tried': tried, 'path': new_path}
def recurse_patterns(path, pattern_list, page_id):
"""
Recurse over a list of to-be-hooked patterns for a given path prefix
"""
newpatterns = []
for pattern in pattern_list:
app_pat = pattern.regex.pattern
if app_pat.startswith('^'):
app_pat = app_pat[1:]
regex = r'^%s%s' % (path, app_pat)
if isinstance(pattern, RegexURLResolver):
# this is an 'include', recurse!
resolver = RegexURLResolver(regex, 'cms_appresolver',
pattern.default_kwargs, pattern.app_name, pattern.namespace)
resolver.page_id = page_id
# see lines 243 and 236 of urlresolvers.py to understand the next line
resolver._urlconf_module = recurse_patterns(regex, pattern.url_patterns, page_id)
else:
# Re-do the RegexURLPattern with the new regular expression
resolver = RegexURLPattern(regex, pattern.callback,
pattern.default_args, pattern.name)
resolver.page_id = page_id
newpatterns.append(resolver)
return newpatterns
def _flatten_patterns(patterns):
flat = []
for pattern in patterns:
if isinstance(pattern, RegexURLResolver):
flat += _flatten_patterns(pattern.url_patterns)
else:
flat.append(pattern)
return flat
def get_app_urls(urls):
for urlconf in urls:
if isinstance(urlconf, basestring):
mod = import_module(urlconf)
if not hasattr(mod, 'urlpatterns'):
raise ImproperlyConfigured(
"URLConf `%s` has no urlpatterns attribute" % urlconf)
yield getattr(mod, 'urlpatterns')
else:
yield urlconf
def get_patterns_for_title(path, title):
"""
Resolve the urlconf module for a path+title combination
Returns a list of url objects.
"""
app = apphook_pool.get_apphook(title.application_urls)
patterns = []
for pattern_list in get_app_urls(app.urls):
if not path.endswith('/'):
path += '/'
page_id = title.page.id
patterns += recurse_patterns(path, pattern_list, page_id)
patterns = _flatten_patterns(patterns)
return patterns
def get_app_patterns():
"""
Get a list of patterns for all hooked apps.
How this works:
By looking through all titles with an app hook (application_urls) we find all
urlconf modules we have to hook into titles.
If we use the ML URL Middleware, we namespace those patterns with the title
language.
All 'normal' patterns from the urlconf get re-written by prefixing them with
the title path and then included into the cms url patterns.
"""
from cms.models import Title
try:
current_site = Site.objects.get_current()
except Site.DoesNotExist:
current_site = None
included = []
# we don't have a request here so get_page_queryset() can't be used,
# so, if CMS_MODERATOR, use, public() queryset, otherwise
# use draft(). This can be done, because url patterns are used just
# in frontend
is_draft = not settings.CMS_MODERATOR
title_qs = Title.objects.filter(page__publisher_is_draft=is_draft, page__site=current_site)
if 'cms.middleware.multilingual.MultilingualURLMiddleware' in settings.MIDDLEWARE_CLASSES:
use_namespaces = True
hooked_applications = {}
else:
use_namespaces = False
hooked_applications = []
# Loop over all titles with an application hooked to them
for title in title_qs.exclude(application_urls=None).exclude(application_urls='').select_related():
path = title.path
if use_namespaces:
mixid = "%s:%s:%s" % (path + "/", title.application_urls, title.language)
else:
mixid = "%s:%s" % (path + "/", title.application_urls)
if mixid in included:
# don't add the same thing twice
continue
if not settings.APPEND_SLASH:
path += '/'
if use_namespaces:
if title.language not in hooked_applications:
hooked_applications[title.language] = []
hooked_applications[title.language] += get_patterns_for_title(path, title)
else:
hooked_applications += get_patterns_for_title(path, title)
included.append(mixid)
# Build the app patterns to be included in the cms urlconfs
app_patterns = []
if use_namespaces:
for ns, currentpatterns in hooked_applications.items():
extra_patterns = patterns('', *currentpatterns)
resolver = AppRegexURLResolver(r'', 'app_resolver', namespace=ns)
resolver.url_patterns = extra_patterns
app_patterns.append(resolver)
APP_RESOLVERS.append(resolver)
else:
extra_patterns = patterns('', *hooked_applications)
resolver = AppRegexURLResolver(r'', 'app_resolver')
resolver.url_patterns = extra_patterns
app_patterns.append(resolver)
APP_RESOLVERS.append(resolver)
return app_patterns
| 38.349515 | 103 | 0.638101 |
from cms.apphook_pool import apphook_pool
from cms.exceptions import NoHomeFound
from cms.utils.moderator import get_page_queryset
from django.conf import settings
from django.conf.urls.defaults import patterns
from django.contrib.sites.models import Site
from django.core.exceptions import ImproperlyConfigured
from django.core.urlresolvers import RegexURLResolver, Resolver404, reverse, \
RegexURLPattern
from django.utils.importlib import import_module
APP_RESOLVERS = []
def clear_app_resolvers():
global APP_RESOLVERS
APP_RESOLVERS = []
def applications_page_check(request, current_page=None, path=None):
"""Tries to find if given path was resolved over application.
Applications have higher priority than other cms pages.
"""
if current_page:
return current_page
if path is None:
path = request.path.replace(reverse('pages-root'), '', 1)
for resolver in APP_RESOLVERS:
try:
page_id = resolver.resolve_page_id(path)
page = get_page_queryset(request).get(id=page_id)
return page
except Resolver404:
pass
return None
class AppRegexURLResolver(RegexURLResolver):
page_id = None
url_patterns = None
def resolve_page_id(self, path):
"""Resolves requested path similar way how resolve does, but instead
of return callback,.. returns page_id to which was application
assigned.
"""
tried = []
match = self.regex.search(path)
if match:
new_path = path[match.end():]
for pattern in self.url_patterns:
try:
sub_match = pattern.resolve(new_path)
except Resolver404, e:
if 'tried' in e.args[0]:
tried.extend([(pattern.regex.pattern + ' ' + t) for t in e.args[0]['tried']])
elif 'path' in e.args[0]:
tried.extend([(pattern.regex.pattern + ' ' + t) for t in e.args[0]['path']])
else:
if sub_match:
return pattern.page_id
tried.append(pattern.regex.pattern)
raise Resolver404, {'tried': tried, 'path': new_path}
def recurse_patterns(path, pattern_list, page_id):
"""
Recurse over a list of to-be-hooked patterns for a given path prefix
"""
newpatterns = []
for pattern in pattern_list:
app_pat = pattern.regex.pattern
if app_pat.startswith('^'):
app_pat = app_pat[1:]
regex = r'^%s%s' % (path, app_pat)
if isinstance(pattern, RegexURLResolver):
resolver = RegexURLResolver(regex, 'cms_appresolver',
pattern.default_kwargs, pattern.app_name, pattern.namespace)
resolver.page_id = page_id
resolver._urlconf_module = recurse_patterns(regex, pattern.url_patterns, page_id)
else:
resolver = RegexURLPattern(regex, pattern.callback,
pattern.default_args, pattern.name)
resolver.page_id = page_id
newpatterns.append(resolver)
return newpatterns
def _flatten_patterns(patterns):
flat = []
for pattern in patterns:
if isinstance(pattern, RegexURLResolver):
flat += _flatten_patterns(pattern.url_patterns)
else:
flat.append(pattern)
return flat
def get_app_urls(urls):
for urlconf in urls:
if isinstance(urlconf, basestring):
mod = import_module(urlconf)
if not hasattr(mod, 'urlpatterns'):
raise ImproperlyConfigured(
"URLConf `%s` has no urlpatterns attribute" % urlconf)
yield getattr(mod, 'urlpatterns')
else:
yield urlconf
def get_patterns_for_title(path, title):
"""
Resolve the urlconf module for a path+title combination
Returns a list of url objects.
"""
app = apphook_pool.get_apphook(title.application_urls)
patterns = []
for pattern_list in get_app_urls(app.urls):
if not path.endswith('/'):
path += '/'
page_id = title.page.id
patterns += recurse_patterns(path, pattern_list, page_id)
patterns = _flatten_patterns(patterns)
return patterns
def get_app_patterns():
"""
Get a list of patterns for all hooked apps.
How this works:
By looking through all titles with an app hook (application_urls) we find all
urlconf modules we have to hook into titles.
If we use the ML URL Middleware, we namespace those patterns with the title
language.
All 'normal' patterns from the urlconf get re-written by prefixing them with
the title path and then included into the cms url patterns.
"""
from cms.models import Title
try:
current_site = Site.objects.get_current()
except Site.DoesNotExist:
current_site = None
included = []
is_draft = not settings.CMS_MODERATOR
title_qs = Title.objects.filter(page__publisher_is_draft=is_draft, page__site=current_site)
if 'cms.middleware.multilingual.MultilingualURLMiddleware' in settings.MIDDLEWARE_CLASSES:
use_namespaces = True
hooked_applications = {}
else:
use_namespaces = False
hooked_applications = []
for title in title_qs.exclude(application_urls=None).exclude(application_urls='').select_related():
path = title.path
if use_namespaces:
mixid = "%s:%s:%s" % (path + "/", title.application_urls, title.language)
else:
mixid = "%s:%s" % (path + "/", title.application_urls)
if mixid in included:
continue
if not settings.APPEND_SLASH:
path += '/'
if use_namespaces:
if title.language not in hooked_applications:
hooked_applications[title.language] = []
hooked_applications[title.language] += get_patterns_for_title(path, title)
else:
hooked_applications += get_patterns_for_title(path, title)
included.append(mixid)
# Build the app patterns to be included in the cms urlconfs
app_patterns = []
if use_namespaces:
for ns, currentpatterns in hooked_applications.items():
extra_patterns = patterns('', *currentpatterns)
resolver = AppRegexURLResolver(r'', 'app_resolver', namespace=ns)
resolver.url_patterns = extra_patterns
app_patterns.append(resolver)
APP_RESOLVERS.append(resolver)
else:
extra_patterns = patterns('', *hooked_applications)
resolver = AppRegexURLResolver(r'', 'app_resolver')
resolver.url_patterns = extra_patterns
app_patterns.append(resolver)
APP_RESOLVERS.append(resolver)
return app_patterns
| false | true |
f7fe97ef8ffadbac248437d2b382b73b21f70d7c | 1,459 | py | Python | libweasyl/libweasyl/alembic/versions/eff79a07a88d_use_timestamp_column_for_latest_.py | greysteil/wzl-test | 0f863b9e7c58e5861437618bd590126ca323140c | [
"Apache-2.0"
] | 1 | 2019-02-15T04:21:48.000Z | 2019-02-15T04:21:48.000Z | libweasyl/libweasyl/alembic/versions/eff79a07a88d_use_timestamp_column_for_latest_.py | kfkitsune/wzl-test | 27297ccb42e24d652a29aa82f5a667c7d9a6d8de | [
"Apache-2.0"
] | 254 | 2017-12-23T19:36:43.000Z | 2020-04-14T21:46:13.000Z | libweasyl/libweasyl/alembic/versions/eff79a07a88d_use_timestamp_column_for_latest_.py | greysteil/wzl-test | 0f863b9e7c58e5861437618bd590126ca323140c | [
"Apache-2.0"
] | 1 | 2017-12-23T18:42:16.000Z | 2017-12-23T18:42:16.000Z | """Use TIMESTAMP column for latest submission
Revision ID: eff79a07a88d
Revises: 83e6b2a46191
Create Date: 2017-01-08 22:20:43.814375
"""
# revision identifiers, used by Alembic.
revision = 'eff79a07a88d'
down_revision = '83e6b2a46191'
from alembic import op
import sqlalchemy as sa
import libweasyl
from libweasyl.legacy import UNIXTIME_OFFSET
def upgrade():
op.alter_column(
'profile',
'latest_submission_time',
new_column_name='latest_submission_time_old',
)
op.add_column(
'profile',
sa.Column('latest_submission_time', libweasyl.models.helpers.ArrowColumn(), nullable=False, server_default='epoch'),
)
op.execute(
"UPDATE profile SET latest_submission_time = TIMESTAMP WITHOUT TIME ZONE 'epoch' + "
"(latest_submission_time_old - %d) * INTERVAL '1 second'" % (UNIXTIME_OFFSET,))
op.drop_column('profile', 'latest_submission_time_old')
def downgrade():
op.alter_column(
'profile',
'latest_submission_time',
new_column_name='latest_submission_time_new',
)
op.add_column(
'profile',
sa.Column('latest_submission_time', libweasyl.models.helpers.WeasylTimestampColumn(), nullable=False, server_default='0'),
)
op.execute(
"UPDATE profile SET latest_submission_time = extract(epoch from latest_submission_time_new) + %d" % (UNIXTIME_OFFSET,))
op.drop_column('profile', 'latest_submission_time_new')
| 29.77551 | 130 | 0.708019 |
revision = 'eff79a07a88d'
down_revision = '83e6b2a46191'
from alembic import op
import sqlalchemy as sa
import libweasyl
from libweasyl.legacy import UNIXTIME_OFFSET
def upgrade():
op.alter_column(
'profile',
'latest_submission_time',
new_column_name='latest_submission_time_old',
)
op.add_column(
'profile',
sa.Column('latest_submission_time', libweasyl.models.helpers.ArrowColumn(), nullable=False, server_default='epoch'),
)
op.execute(
"UPDATE profile SET latest_submission_time = TIMESTAMP WITHOUT TIME ZONE 'epoch' + "
"(latest_submission_time_old - %d) * INTERVAL '1 second'" % (UNIXTIME_OFFSET,))
op.drop_column('profile', 'latest_submission_time_old')
def downgrade():
op.alter_column(
'profile',
'latest_submission_time',
new_column_name='latest_submission_time_new',
)
op.add_column(
'profile',
sa.Column('latest_submission_time', libweasyl.models.helpers.WeasylTimestampColumn(), nullable=False, server_default='0'),
)
op.execute(
"UPDATE profile SET latest_submission_time = extract(epoch from latest_submission_time_new) + %d" % (UNIXTIME_OFFSET,))
op.drop_column('profile', 'latest_submission_time_new')
| true | true |
f7fe983d9f3c9724263133f0b77deed272534129 | 1,764 | py | Python | src/main/py/ltprg/game/color/properties/get_stim_embeddings.py | forkunited/ltprg | 4e40d3571d229023df0f845c68643024e04bc202 | [
"MIT"
] | 11 | 2017-08-03T15:42:19.000Z | 2021-02-04T12:43:35.000Z | src/main/py/ltprg/game/color/properties/get_stim_embeddings.py | forkunited/ltprg | 4e40d3571d229023df0f845c68643024e04bc202 | [
"MIT"
] | null | null | null | src/main/py/ltprg/game/color/properties/get_stim_embeddings.py | forkunited/ltprg | 4e40d3571d229023df0f845c68643024e04bc202 | [
"MIT"
] | 1 | 2021-02-04T12:43:37.000Z | 2021-02-04T12:43:37.000Z | from __future__ import division
import numpy as np
import sys
sys.path.append('../../../../../../../../Packages/mungpy/src/main/py/mung/')
import torch
import torch.nn as nn
from torch.autograd import Variable
import time
from data import DataSet
from alexnet import PartialAlexnet, rgb_to_alexnet_input
from colorspace_conversions import hsls_to_rgbs
def hsl_from_datum(datum, H_fieldname, S_fieldname, L_fieldname):
return [datum.get(H_fieldname), datum.get(S_fieldname),
datum.get(L_fieldname)]
def load_stim_hsls(data_path):
D = DataSet.load(data_path)
hsls = []
for i in range(len(D)):
# target = [pull_hsls(D[i]."state.sTargetH", D[i]."state.sTargetS",
# D[i]."state.sTargetL")]
colors_this_trial = [hsl_from_datum(D[i], "state.sH_0", "state.sS_0",
"state.sL_0"),
hsl_from_datum(D[i], "state.sH_1", "state.sS_1",
"state.sL_1"),
hsl_from_datum(D[i], "state.sH_2", "state.sS_2",
"state.sL_2")]
for c in colors_this_trial:
if not c == [None, None, None]:
c = map(int, c)
if c not in hsls:
hsls.append(c)
print '{} Colors'.format(len(hsls))
return hsls
def get_stim_alexnet_embeddings(stim_rgbs, stop_layer):
alexnet_to_fc6 = PartialAlexnet(stop_layer)
print alexnet_to_fc6.model
start_time = time.time()
embeddings = alexnet_to_fc6.forward(rgb_to_alexnet_input(stim_rgbs[0]))
for i in range(1, stim_rgbs.shape[0]):
embeddings = torch.cat([embeddings, alexnet_to_fc6.forward(
rgb_to_alexnet_input(stim_rgbs[i]))], 0)
print 'Time for dataset = {}'.format(time.time()-start_time)
embeddings = embeddings.data.numpy()
return embeddings
if __name__=='__main__':
hsls = load_stim_hsls()
rgbs = hsls_to_rgbs(hsls)
get_stim_alexnet_embeddings(rgbs, 'fc6')
| 33.283019 | 76 | 0.707483 | from __future__ import division
import numpy as np
import sys
sys.path.append('../../../../../../../../Packages/mungpy/src/main/py/mung/')
import torch
import torch.nn as nn
from torch.autograd import Variable
import time
from data import DataSet
from alexnet import PartialAlexnet, rgb_to_alexnet_input
from colorspace_conversions import hsls_to_rgbs
def hsl_from_datum(datum, H_fieldname, S_fieldname, L_fieldname):
return [datum.get(H_fieldname), datum.get(S_fieldname),
datum.get(L_fieldname)]
def load_stim_hsls(data_path):
D = DataSet.load(data_path)
hsls = []
for i in range(len(D)):
colors_this_trial = [hsl_from_datum(D[i], "state.sH_0", "state.sS_0",
"state.sL_0"),
hsl_from_datum(D[i], "state.sH_1", "state.sS_1",
"state.sL_1"),
hsl_from_datum(D[i], "state.sH_2", "state.sS_2",
"state.sL_2")]
for c in colors_this_trial:
if not c == [None, None, None]:
c = map(int, c)
if c not in hsls:
hsls.append(c)
print '{} Colors'.format(len(hsls))
return hsls
def get_stim_alexnet_embeddings(stim_rgbs, stop_layer):
alexnet_to_fc6 = PartialAlexnet(stop_layer)
print alexnet_to_fc6.model
start_time = time.time()
embeddings = alexnet_to_fc6.forward(rgb_to_alexnet_input(stim_rgbs[0]))
for i in range(1, stim_rgbs.shape[0]):
embeddings = torch.cat([embeddings, alexnet_to_fc6.forward(
rgb_to_alexnet_input(stim_rgbs[i]))], 0)
print 'Time for dataset = {}'.format(time.time()-start_time)
embeddings = embeddings.data.numpy()
return embeddings
if __name__=='__main__':
hsls = load_stim_hsls()
rgbs = hsls_to_rgbs(hsls)
get_stim_alexnet_embeddings(rgbs, 'fc6')
| false | true |
f7fe988d73b3edc4eb10a7f5ae08663502f160ce | 113 | py | Python | lib_secure_monitoring_service/report.py | jfuruness/lib_secure_monitoring_service | 80748c0be4944427e99f9f4c9ccd47a7fab93936 | [
"BSD-3-Clause"
] | null | null | null | lib_secure_monitoring_service/report.py | jfuruness/lib_secure_monitoring_service | 80748c0be4944427e99f9f4c9ccd47a7fab93936 | [
"BSD-3-Clause"
] | null | null | null | lib_secure_monitoring_service/report.py | jfuruness/lib_secure_monitoring_service | 80748c0be4944427e99f9f4c9ccd47a7fab93936 | [
"BSD-3-Clause"
] | null | null | null | from typing import NamedTuple
class Report(NamedTuple):
reporting_asn: int
prefix: str
as_path: list | 18.833333 | 29 | 0.734513 | from typing import NamedTuple
class Report(NamedTuple):
reporting_asn: int
prefix: str
as_path: list | true | true |
f7fe99031f3d741c5489abd7cc781ad091f717b3 | 4,347 | py | Python | quant/app/spread_trading/strategies/statistical_arbitrage_strategy.py | williamquant/quant | a5447a5211ac6dbe3f9515788ecb162b94e61418 | [
"MIT"
] | 1 | 2022-01-05T09:03:23.000Z | 2022-01-05T09:03:23.000Z | quant/app/spread_trading/strategies/statistical_arbitrage_strategy.py | williamquant/quant | a5447a5211ac6dbe3f9515788ecb162b94e61418 | [
"MIT"
] | null | null | null | quant/app/spread_trading/strategies/statistical_arbitrage_strategy.py | williamquant/quant | a5447a5211ac6dbe3f9515788ecb162b94e61418 | [
"MIT"
] | 2 | 2021-12-27T22:52:50.000Z | 2022-01-05T09:03:15.000Z | from quant.trader.utility import BarGenerator, ArrayManager
from quant.app.spread_trading import (
SpreadStrategyTemplate,
SpreadAlgoTemplate,
SpreadData,
OrderData,
TradeData,
TickData,
BarData
)
class StatisticalArbitrageStrategy(SpreadStrategyTemplate):
""""""
author = "用Python的交易员"
boll_window = 20
boll_dev = 2
max_pos = 10
payup = 10
interval = 5
spread_pos = 0.0
boll_up = 0.0
boll_down = 0.0
boll_mid = 0.0
parameters = [
"boll_window",
"boll_dev",
"max_pos",
"payup",
"interval"
]
variables = [
"spread_pos",
"boll_up",
"boll_down",
"boll_mid"
]
def __init__(
self,
strategy_engine,
strategy_name: str,
spread: SpreadData,
setting: dict
):
""""""
super().__init__(
strategy_engine, strategy_name, spread, setting
)
self.bg = BarGenerator(self.on_spread_bar)
self.am = ArrayManager()
def on_init(self):
"""
Callback when strategy is inited.
"""
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
"""
Callback when strategy is started.
"""
self.write_log("策略启动")
def on_stop(self):
"""
Callback when strategy is stopped.
"""
self.write_log("策略停止")
self.put_event()
def on_spread_data(self):
"""
Callback when spread price is updated.
"""
tick = self.get_spread_tick()
self.on_spread_tick(tick)
def on_spread_tick(self, tick: TickData):
"""
Callback when new spread tick data is generated.
"""
self.bg.update_tick(tick)
def on_spread_bar(self, bar: BarData):
"""
Callback when spread bar data is generated.
"""
self.stop_all_algos()
self.am.update_bar(bar)
if not self.am.inited:
return
self.boll_mid = self.am.sma(self.boll_window)
self.boll_up, self.boll_down = self.am.boll(
self.boll_window, self.boll_dev)
if not self.spread_pos:
if bar.close_price >= self.boll_up:
self.start_short_algo(
bar.close_price - 10,
self.max_pos,
payup=self.payup,
interval=self.interval
)
elif bar.close_price <= self.boll_down:
self.start_long_algo(
bar.close_price + 10,
self.max_pos,
payup=self.payup,
interval=self.interval
)
elif self.spread_pos < 0:
if bar.close_price <= self.boll_mid:
self.start_long_algo(
bar.close_price + 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval
)
else:
if bar.close_price >= self.boll_mid:
self.start_short_algo(
bar.close_price - 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval
)
self.put_event()
def on_spread_pos(self):
"""
Callback when spread position is updated.
"""
self.spread_pos = self.get_spread_pos()
self.put_event()
def on_spread_algo(self, algo: SpreadAlgoTemplate):
"""
Callback when algo status is updated.
"""
pass
def on_order(self, order: OrderData):
"""
Callback when order status is updated.
"""
pass
def on_trade(self, trade: TradeData):
"""
Callback when new trade data is received.
"""
pass
def stop_open_algos(self):
""""""
if self.buy_algoid:
self.stop_algo(self.buy_algoid)
if self.short_algoid:
self.stop_algo(self.short_algoid)
def stop_close_algos(self):
""""""
if self.sell_algoid:
self.stop_algo(self.sell_algoid)
if self.cover_algoid:
self.stop_algo(self.cover_algoid)
| 24.016575 | 59 | 0.520589 | from quant.trader.utility import BarGenerator, ArrayManager
from quant.app.spread_trading import (
SpreadStrategyTemplate,
SpreadAlgoTemplate,
SpreadData,
OrderData,
TradeData,
TickData,
BarData
)
class StatisticalArbitrageStrategy(SpreadStrategyTemplate):
author = "用Python的交易员"
boll_window = 20
boll_dev = 2
max_pos = 10
payup = 10
interval = 5
spread_pos = 0.0
boll_up = 0.0
boll_down = 0.0
boll_mid = 0.0
parameters = [
"boll_window",
"boll_dev",
"max_pos",
"payup",
"interval"
]
variables = [
"spread_pos",
"boll_up",
"boll_down",
"boll_mid"
]
def __init__(
self,
strategy_engine,
strategy_name: str,
spread: SpreadData,
setting: dict
):
super().__init__(
strategy_engine, strategy_name, spread, setting
)
self.bg = BarGenerator(self.on_spread_bar)
self.am = ArrayManager()
def on_init(self):
self.write_log("策略初始化")
self.load_bar(10)
def on_start(self):
self.write_log("策略启动")
def on_stop(self):
self.write_log("策略停止")
self.put_event()
def on_spread_data(self):
tick = self.get_spread_tick()
self.on_spread_tick(tick)
def on_spread_tick(self, tick: TickData):
self.bg.update_tick(tick)
def on_spread_bar(self, bar: BarData):
self.stop_all_algos()
self.am.update_bar(bar)
if not self.am.inited:
return
self.boll_mid = self.am.sma(self.boll_window)
self.boll_up, self.boll_down = self.am.boll(
self.boll_window, self.boll_dev)
if not self.spread_pos:
if bar.close_price >= self.boll_up:
self.start_short_algo(
bar.close_price - 10,
self.max_pos,
payup=self.payup,
interval=self.interval
)
elif bar.close_price <= self.boll_down:
self.start_long_algo(
bar.close_price + 10,
self.max_pos,
payup=self.payup,
interval=self.interval
)
elif self.spread_pos < 0:
if bar.close_price <= self.boll_mid:
self.start_long_algo(
bar.close_price + 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval
)
else:
if bar.close_price >= self.boll_mid:
self.start_short_algo(
bar.close_price - 10,
abs(self.spread_pos),
payup=self.payup,
interval=self.interval
)
self.put_event()
def on_spread_pos(self):
self.spread_pos = self.get_spread_pos()
self.put_event()
def on_spread_algo(self, algo: SpreadAlgoTemplate):
pass
def on_order(self, order: OrderData):
pass
def on_trade(self, trade: TradeData):
pass
def stop_open_algos(self):
if self.buy_algoid:
self.stop_algo(self.buy_algoid)
if self.short_algoid:
self.stop_algo(self.short_algoid)
def stop_close_algos(self):
if self.sell_algoid:
self.stop_algo(self.sell_algoid)
if self.cover_algoid:
self.stop_algo(self.cover_algoid)
| true | true |
f7fe997b27585a66134a2b95f421cc00774696e7 | 3,878 | py | Python | ge_websocket_to_udp.py | bpennypacker/ge_websocket_to_udp | 900dcd78c1f526ed0722590175c2d0f6b2e51cb0 | [
"MIT"
] | null | null | null | ge_websocket_to_udp.py | bpennypacker/ge_websocket_to_udp | 900dcd78c1f526ed0722590175c2d0f6b2e51cb0 | [
"MIT"
] | null | null | null | ge_websocket_to_udp.py | bpennypacker/ge_websocket_to_udp | 900dcd78c1f526ed0722590175c2d0f6b2e51cb0 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
import aiohttp
import asyncio
from typing import Any, Dict, Tuple
import configparser
import socket
import time
from gekitchen import (
EVENT_ADD_APPLIANCE,
EVENT_APPLIANCE_STATE_CHANGE,
EVENT_APPLIANCE_INITIAL_UPDATE,
EVENT_DISCONNECTED,
ErdApplianceType,
ErdCode,
ErdCodeType,
ErdOvenCookMode,
GeAppliance,
GeWebsocketClient
)
machine_status = {
0: 'Idle',
1: 'Standby',
2: 'Run',
3: 'Pause',
4: 'EOC',
5: 'DSMDelayRun',
6: 'DelayRun',
7: 'DelayPause',
8: 'DrainTimeout',
128: 'Clean Speak'
}
machine_type = {
ErdApplianceType.DRYER: "DRYER",
ErdApplianceType.WASHER: "WASHER"
}
class GEWebsocketToUDP:
def __init__(self):
self.sleeper = None
self.client = None
self.config = None
async def log_state_change(self, data: Tuple[GeAppliance, Dict[ErdCodeType, Any]]):
"""Send state changes via UDP if desireable"""
appliance, state_changes = data
if not appliance.appliance_type in machine_type:
return
machine = machine_type[appliance.appliance_type]
if not (machine in self.config and self.config[machine]['enabled']):
return
# state_changes['0x2000'] is machine status
if not '0x2000' in state_changes:
return
b = int.from_bytes(state_changes['0x2000'], "big")
ip = socket.gethostbyname(self.config[machine]['host'])
if 'prefix' in self.config[machine]:
msg = "{}{}".format(self.config[machine]['prefix'], machine_status[b])
else:
msg = machine_status[b]
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.sendto(bytes(msg, 'utf-8'), (ip, int(self.config[machine]['port'])))
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print ("{} : {} {}:{} {}".format(t, machine, self.config[machine]['host'], self.config[machine]['port'], msg))
async def do_event_disconnect(self, appliance: GeAppliance):
print ("Received disconnect...")
self.client.disconnect()
self.sleeper.cancel_all()
await self.sleeper(10)
async def main(self, loop):
self.config = configparser.ConfigParser()
self.config.read('ge_websocket_to_udp.ini')
self.client = GeWebsocketClient(loop, self.config['auth']['username'], self.config['auth']['password'])
self.client.add_event_handler(EVENT_APPLIANCE_STATE_CHANGE, self.log_state_change)
self.client.add_event_handler(EVENT_DISCONNECTED, self.do_event_disconnect)
session = aiohttp.ClientSession()
asyncio.ensure_future(self.client.async_get_credentials_and_run(session), loop=loop)
await self.sleeper(86400)
def make_sleep(self):
async def sleeper(delay, result=None, *, loop=None):
coro = asyncio.sleep(delay, result=result, loop=loop)
task = asyncio.ensure_future(coro)
sleeper.tasks.add(task)
try:
return await task
except asyncio.CancelledError:
return result
finally:
sleeper.tasks.remove(task)
sleeper.tasks = set()
sleeper.cancel_all = lambda: sum(task.cancel() for task in sleeper.tasks)
self.sleeper = sleeper
if __name__ == '__main__':
loop = asyncio.get_event_loop()
while True:
try:
obj = GEWebsocketToUDP()
obj.make_sleep()
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("{}: starting async loop...".format(t))
loop.run_until_complete(obj.main(loop))
except Exception as e:
print("Caught exception: {}".format(e))
pass
print("loop aborted. Sleeping 300 seconds...")
time.sleep(300)
| 30.535433 | 118 | 0.620165 |
import aiohttp
import asyncio
from typing import Any, Dict, Tuple
import configparser
import socket
import time
from gekitchen import (
EVENT_ADD_APPLIANCE,
EVENT_APPLIANCE_STATE_CHANGE,
EVENT_APPLIANCE_INITIAL_UPDATE,
EVENT_DISCONNECTED,
ErdApplianceType,
ErdCode,
ErdCodeType,
ErdOvenCookMode,
GeAppliance,
GeWebsocketClient
)
machine_status = {
0: 'Idle',
1: 'Standby',
2: 'Run',
3: 'Pause',
4: 'EOC',
5: 'DSMDelayRun',
6: 'DelayRun',
7: 'DelayPause',
8: 'DrainTimeout',
128: 'Clean Speak'
}
machine_type = {
ErdApplianceType.DRYER: "DRYER",
ErdApplianceType.WASHER: "WASHER"
}
class GEWebsocketToUDP:
def __init__(self):
self.sleeper = None
self.client = None
self.config = None
async def log_state_change(self, data: Tuple[GeAppliance, Dict[ErdCodeType, Any]]):
appliance, state_changes = data
if not appliance.appliance_type in machine_type:
return
machine = machine_type[appliance.appliance_type]
if not (machine in self.config and self.config[machine]['enabled']):
return
if not '0x2000' in state_changes:
return
b = int.from_bytes(state_changes['0x2000'], "big")
ip = socket.gethostbyname(self.config[machine]['host'])
if 'prefix' in self.config[machine]:
msg = "{}{}".format(self.config[machine]['prefix'], machine_status[b])
else:
msg = machine_status[b]
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.sendto(bytes(msg, 'utf-8'), (ip, int(self.config[machine]['port'])))
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print ("{} : {} {}:{} {}".format(t, machine, self.config[machine]['host'], self.config[machine]['port'], msg))
async def do_event_disconnect(self, appliance: GeAppliance):
print ("Received disconnect...")
self.client.disconnect()
self.sleeper.cancel_all()
await self.sleeper(10)
async def main(self, loop):
self.config = configparser.ConfigParser()
self.config.read('ge_websocket_to_udp.ini')
self.client = GeWebsocketClient(loop, self.config['auth']['username'], self.config['auth']['password'])
self.client.add_event_handler(EVENT_APPLIANCE_STATE_CHANGE, self.log_state_change)
self.client.add_event_handler(EVENT_DISCONNECTED, self.do_event_disconnect)
session = aiohttp.ClientSession()
asyncio.ensure_future(self.client.async_get_credentials_and_run(session), loop=loop)
await self.sleeper(86400)
def make_sleep(self):
async def sleeper(delay, result=None, *, loop=None):
coro = asyncio.sleep(delay, result=result, loop=loop)
task = asyncio.ensure_future(coro)
sleeper.tasks.add(task)
try:
return await task
except asyncio.CancelledError:
return result
finally:
sleeper.tasks.remove(task)
sleeper.tasks = set()
sleeper.cancel_all = lambda: sum(task.cancel() for task in sleeper.tasks)
self.sleeper = sleeper
if __name__ == '__main__':
loop = asyncio.get_event_loop()
while True:
try:
obj = GEWebsocketToUDP()
obj.make_sleep()
t = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
print("{}: starting async loop...".format(t))
loop.run_until_complete(obj.main(loop))
except Exception as e:
print("Caught exception: {}".format(e))
pass
print("loop aborted. Sleeping 300 seconds...")
time.sleep(300)
| true | true |
f7fe9aad01a1690a720368845f1e56dcab072722 | 965 | py | Python | qiskit/pulse/channels/pulse_channels.py | Sahar2/qiskit-terra | 19fbaeb68f2b279c9748384e919e1d1b006860f2 | [
"Apache-2.0"
] | 22 | 2019-08-15T04:39:15.000Z | 2022-03-06T05:17:04.000Z | qiskit/pulse/channels/pulse_channels.py | Sahar2/qiskit-terra | 19fbaeb68f2b279c9748384e919e1d1b006860f2 | [
"Apache-2.0"
] | 2 | 2020-10-26T07:12:12.000Z | 2021-12-09T16:22:51.000Z | qiskit/pulse/channels/pulse_channels.py | Sahar2/qiskit-terra | 19fbaeb68f2b279c9748384e919e1d1b006860f2 | [
"Apache-2.0"
] | 9 | 2019-09-05T05:33:00.000Z | 2021-10-09T16:04:53.000Z | # -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.
"""
Channels support signal output.
"""
from abc import ABCMeta
from .channels import Channel
class PulseChannel(Channel, metaclass=ABCMeta):
"""Base class of Channel supporting pulse output."""
pass
class DriveChannel(PulseChannel):
"""Drive Channel."""
prefix = 'd'
class MeasureChannel(PulseChannel):
"""Measure Channel."""
prefix = 'm'
class ControlChannel(PulseChannel):
"""Control Channel."""
prefix = 'u'
| 21.931818 | 77 | 0.707772 |
from abc import ABCMeta
from .channels import Channel
class PulseChannel(Channel, metaclass=ABCMeta):
pass
class DriveChannel(PulseChannel):
prefix = 'd'
class MeasureChannel(PulseChannel):
prefix = 'm'
class ControlChannel(PulseChannel):
prefix = 'u'
| true | true |
f7fe9b079fcbf300b453522cdb00e7dbf5d3dd39 | 30,168 | py | Python | tests/statisticslearning_tests.py | vishalbelsare/abcpy | 72d0d31ae3fa531b69ea3fef39c96af6628ee76f | [
"BSD-3-Clause-Clear"
] | 89 | 2017-02-23T23:34:52.000Z | 2022-03-25T20:35:17.000Z | tests/statisticslearning_tests.py | vishalbelsare/abcpy | 72d0d31ae3fa531b69ea3fef39c96af6628ee76f | [
"BSD-3-Clause-Clear"
] | 35 | 2017-03-31T13:24:52.000Z | 2022-01-09T11:31:38.000Z | tests/statisticslearning_tests.py | vishalbelsare/abcpy | 72d0d31ae3fa531b69ea3fef39c96af6628ee76f | [
"BSD-3-Clause-Clear"
] | 32 | 2017-03-22T06:27:43.000Z | 2021-09-17T15:50:42.000Z | import unittest
import numpy as np
from abcpy.backends import BackendDummy as Backend
from abcpy.continuousmodels import Normal
from abcpy.continuousmodels import Uniform
from abcpy.statistics import Identity
from abcpy.statisticslearning import Semiautomatic, SemiautomaticNN, TripletDistanceLearning, \
ContrastiveDistanceLearning, ExponentialFamilyScoreMatching
try:
import torch
except ImportError:
has_torch = False
else:
has_torch = True
from abcpy.NN_utilities.networks import createDefaultNN
class SemiautomaticTests(unittest.TestCase):
def setUp(self):
# define prior and model
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
Y = Normal([mu, sigma])
# define backend
self.backend = Backend()
# define statistics
self.statistics_cal = Identity(degree=3, cross=False)
# Initialize statistics learning
self.statisticslearning = Semiautomatic([Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1)
def test_transformation(self):
# Transform statistics extraction
self.new_statistics_calculator = self.statisticslearning.get_statistics()
# Simulate observed data
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
# NOTE we cannot test this, since the linear regression used uses a random number generator (which we cannot access and is in C). Therefore, our results differ and testing might fail
# self.assertLess(extracted_statistics[0,0] - 0.00215507052338, 10e-2)
# self.assertLess(extracted_statistics[0,1] - (-0.0058023274456), 10e-2)
class SemiautomaticNNTests(unittest.TestCase):
def setUp(self):
# define prior and model
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
# define backend
self.backend = Backend()
# define statistics
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
# Initialize statistics learning
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=100,
n_samples_val=100, n_samples_per_param=1, seed=1, n_epochs=2,
scale_samples=False, use_tqdm=False)
self.statisticslearning2 = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=10,
n_samples_val=10, n_samples_per_param=1, seed=1, n_epochs=5,
scale_samples=False, use_tqdm=False)
# with sample scaler:
self.statisticslearning_with_scaler = SemiautomaticNN([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_per_param=1, seed=1,
n_epochs=2, scale_samples=True, use_tqdm=False)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, SemiautomaticNN, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
# Transform statistics extraction
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
# Simulate observed data
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_errors(self):
if has_torch:
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, parameters=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
embedding_net=createDefaultNN(1, 2))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, simulations=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, simulations=np.ones((100, 1)),
parameters=np.zeros((99, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1)),
parameters_val=np.zeros((99, 1)))
with self.assertRaises(TypeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters=[i for i in range(10)],
simulations=[i for i in range(10)])
with self.assertRaises(TypeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=[i for i in range(10)],
simulations_val=[i for i in range(10)])
with self.assertRaises(RuntimeError):
self.statisticslearning2.test_losses = [4, 2, 1]
self.statisticslearning2.plot_losses()
with self.assertRaises(NotImplementedError):
self.statisticslearning.plot_losses(which_losses="foo")
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class ContrastiveDistanceLearningTests(unittest.TestCase):
def setUp(self):
# define prior and model
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
# define backend
self.backend = Backend()
# define statistics
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
# Initialize statistics learning
self.statisticslearning = ContrastiveDistanceLearning([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_val=100,
n_samples_per_param=1, seed=1, n_epochs=2,
scale_samples=False, use_tqdm=False)
# with sample scaler:
self.statisticslearning_with_scaler = ContrastiveDistanceLearning([self.Y], self.statistics_cal,
self.backend, n_samples=100,
n_samples_per_param=1, seed=1,
n_epochs=2, scale_samples=True,
use_tqdm=False)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, ContrastiveDistanceLearning, [self.Y], self.statistics_cal,
self.backend)
def test_transformation(self):
if has_torch:
# Transform statistics extraction
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
# Simulate observed data
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class TripletDistanceLearningTests(unittest.TestCase):
def setUp(self):
# define prior and model
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
# define backend
self.backend = Backend()
# define statistics
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
# Initialize statistics learning
self.statisticslearning = TripletDistanceLearning([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_val=100, n_samples_per_param=1,
seed=1, n_epochs=2, scale_samples=False, use_tqdm=False)
# with sample scaler:
self.statisticslearning_with_scaler = TripletDistanceLearning([self.Y], self.statistics_cal, self.backend,
scale_samples=True, use_tqdm=False,
n_samples=100, n_samples_per_param=1, seed=1,
n_epochs=2)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, TripletDistanceLearning, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
# Transform statistics extraction
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
# Simulate observed data
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class ExponentialFamilyScoreMatchingTests(unittest.TestCase):
def setUp(self):
# define prior and model
sigma = Uniform([[1], [2]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
# define backend
self.backend = Backend()
# define statistics
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
self.statisticslearning_all_defaults = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False)
self.statisticslearning_no_sliced = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
sliced=False, use_tqdm=False)
self.statisticslearning_sphere_noise = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
noise_type="sphere")
self.statisticslearning_gaussian_noise = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
noise_type="gaussian")
self.statisticslearning_variance_reduction = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
variance_reduction=True)
self.statisticslearning_no_bn = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=4,
n_epochs=2, batch_norm=False, use_tqdm=False)
self.statisticslearning_provide_nets = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
simulations_net=createDefaultNN(3, 3)(),
parameters_net=createDefaultNN(2, 2)(),
use_tqdm=False)
self.statisticslearning_embedding_dim = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
embedding_dimension=4, use_tqdm=False)
self.statisticslearning_validation_early_stop = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal,
self.backend,
n_samples=4, n_epochs=20,
n_samples_val=20, early_stopping=True,
use_tqdm=False)
self.statisticslearning_scale = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, scale_samples=False,
scale_parameters=True, use_tqdm=False)
self.statisticslearning_bounds = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
lower_bound_simulations=np.array([-1000, -1000, -1000]),
upper_bound_simulations=np.array([1000, 1000, 1000]),
use_tqdm=False, seed=1)
self.statisticslearning_no_schedulers = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
scheduler_parameters=False,
scheduler_simulations=False, use_tqdm=False)
self.statisticslearning_lam = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False, sliced=False,
lam=0.1)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, ExponentialFamilyScoreMatching, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
self.new_statistics_calculator = self.statisticslearning_all_defaults.get_statistics()
# with no scaler on data:
self.new_statistics_calculator_no_scaler = self.statisticslearning_scale.get_statistics()
# with no rescaling of the statistics:
self.new_statistics_calculator_no_rescale = self.statisticslearning_all_defaults.get_statistics(
rescale_statistics=False)
# Simulate observed data
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
extracted_statistics_no_rescale = self.new_statistics_calculator_no_rescale.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics_no_rescale), (1, 2))
self.assertFalse(np.allclose(extracted_statistics_no_rescale, extracted_statistics))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
self.assertRaises(RuntimeError, self.new_statistics_calculator_no_scaler.statistics, [np.array([1, 2])])
def test_errors(self):
if has_torch:
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, parameters=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations_net=createDefaultNN(1, 3))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, parameters_net=createDefaultNN(1, 3))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, noise_type="ciao", use_tqdm=False)
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, noise_type="sphere", variance_reduction=True,
use_tqdm=False)
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations=np.ones((100, 1)),
parameters=np.zeros((99, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1)),
parameters_val=np.zeros((99, 1)))
with self.assertRaises(TypeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters=[i for i in range(10)],
simulations=[i for i in range(10)])
with self.assertRaises(TypeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=[i for i in range(10)],
simulations_val=[i for i in range(10)])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, lower_bound_simulations=[1, 2, 3])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, upper_bound_simulations=[1, 2, 3])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
lower_bound_simulations=np.array([-1000, -1000]), seed=1,
upper_bound_simulations=np.array([1000, 1000, 1000]))
with self.assertRaises(RuntimeError):
self.statisticslearning_all_defaults.test_losses = [4, 2, 1]
self.statisticslearning_all_defaults.plot_losses()
with self.assertRaises(NotImplementedError):
self.statisticslearning_all_defaults.plot_losses(which_losses="foo")
def test_plots(self):
if has_torch:
self.statisticslearning_all_defaults.plot_losses()
self.statisticslearning_all_defaults.plot_losses(which_losses="train")
self.statisticslearning_all_defaults.plot_losses(which_losses="test")
if __name__ == '__main__':
unittest.main()
| 66.157895 | 190 | 0.522905 | import unittest
import numpy as np
from abcpy.backends import BackendDummy as Backend
from abcpy.continuousmodels import Normal
from abcpy.continuousmodels import Uniform
from abcpy.statistics import Identity
from abcpy.statisticslearning import Semiautomatic, SemiautomaticNN, TripletDistanceLearning, \
ContrastiveDistanceLearning, ExponentialFamilyScoreMatching
try:
import torch
except ImportError:
has_torch = False
else:
has_torch = True
from abcpy.NN_utilities.networks import createDefaultNN
class SemiautomaticTests(unittest.TestCase):
def setUp(self):
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
Y = Normal([mu, sigma])
self.backend = Backend()
self.statistics_cal = Identity(degree=3, cross=False)
self.statisticslearning = Semiautomatic([Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1)
def test_transformation(self):
self.new_statistics_calculator = self.statisticslearning.get_statistics()
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
class SemiautomaticNNTests(unittest.TestCase):
def setUp(self):
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
self.backend = Backend()
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=100,
n_samples_val=100, n_samples_per_param=1, seed=1, n_epochs=2,
scale_samples=False, use_tqdm=False)
self.statisticslearning2 = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=10,
n_samples_val=10, n_samples_per_param=1, seed=1, n_epochs=5,
scale_samples=False, use_tqdm=False)
self.statisticslearning_with_scaler = SemiautomaticNN([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_per_param=1, seed=1,
n_epochs=2, scale_samples=True, use_tqdm=False)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, SemiautomaticNN, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_errors(self):
if has_torch:
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, parameters=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
embedding_net=createDefaultNN(1, 2))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, simulations=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1, simulations=np.ones((100, 1)),
parameters=np.zeros((99, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
simulations_val=np.ones((100, 1)),
parameters_val=np.zeros((99, 1)))
with self.assertRaises(TypeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters=[i for i in range(10)],
simulations=[i for i in range(10)])
with self.assertRaises(TypeError):
self.statisticslearning = SemiautomaticNN([self.Y], self.statistics_cal, self.backend, n_samples=1000,
n_samples_per_param=1, seed=1,
parameters_val=[i for i in range(10)],
simulations_val=[i for i in range(10)])
with self.assertRaises(RuntimeError):
self.statisticslearning2.test_losses = [4, 2, 1]
self.statisticslearning2.plot_losses()
with self.assertRaises(NotImplementedError):
self.statisticslearning.plot_losses(which_losses="foo")
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class ContrastiveDistanceLearningTests(unittest.TestCase):
def setUp(self):
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
self.backend = Backend()
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
self.statisticslearning = ContrastiveDistanceLearning([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_val=100,
n_samples_per_param=1, seed=1, n_epochs=2,
scale_samples=False, use_tqdm=False)
self.statisticslearning_with_scaler = ContrastiveDistanceLearning([self.Y], self.statistics_cal,
self.backend, n_samples=100,
n_samples_per_param=1, seed=1,
n_epochs=2, scale_samples=True,
use_tqdm=False)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, ContrastiveDistanceLearning, [self.Y], self.statistics_cal,
self.backend)
def test_transformation(self):
if has_torch:
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class TripletDistanceLearningTests(unittest.TestCase):
def setUp(self):
sigma = Uniform([[10], [20]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
self.backend = Backend()
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
self.statisticslearning = TripletDistanceLearning([self.Y], self.statistics_cal, self.backend,
n_samples=100, n_samples_val=100, n_samples_per_param=1,
seed=1, n_epochs=2, scale_samples=False, use_tqdm=False)
self.statisticslearning_with_scaler = TripletDistanceLearning([self.Y], self.statistics_cal, self.backend,
scale_samples=True, use_tqdm=False,
n_samples=100, n_samples_per_param=1, seed=1,
n_epochs=2)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, TripletDistanceLearning, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
self.new_statistics_calculator = self.statisticslearning.get_statistics()
self.new_statistics_calculator_with_scaler = self.statisticslearning_with_scaler.get_statistics()
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
extracted_statistics = self.new_statistics_calculator_with_scaler.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
self.assertRaises(RuntimeError, self.new_statistics_calculator_with_scaler.statistics, [np.array([1, 2])])
def test_plots(self):
if has_torch:
self.statisticslearning.plot_losses()
self.statisticslearning.plot_losses(which_losses="train")
self.statisticslearning.plot_losses(which_losses="test")
class ExponentialFamilyScoreMatchingTests(unittest.TestCase):
def setUp(self):
sigma = Uniform([[1], [2]])
mu = Normal([0, 1])
self.Y = Normal([mu, sigma])
self.backend = Backend()
self.statistics_cal = Identity(degree=3, cross=False)
if has_torch:
self.statisticslearning_all_defaults = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False)
self.statisticslearning_no_sliced = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
sliced=False, use_tqdm=False)
self.statisticslearning_sphere_noise = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
noise_type="sphere")
self.statisticslearning_gaussian_noise = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
noise_type="gaussian")
self.statisticslearning_variance_reduction = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False,
variance_reduction=True)
self.statisticslearning_no_bn = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=4,
n_epochs=2, batch_norm=False, use_tqdm=False)
self.statisticslearning_provide_nets = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
simulations_net=createDefaultNN(3, 3)(),
parameters_net=createDefaultNN(2, 2)(),
use_tqdm=False)
self.statisticslearning_embedding_dim = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
embedding_dimension=4, use_tqdm=False)
self.statisticslearning_validation_early_stop = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal,
self.backend,
n_samples=4, n_epochs=20,
n_samples_val=20, early_stopping=True,
use_tqdm=False)
self.statisticslearning_scale = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, scale_samples=False,
scale_parameters=True, use_tqdm=False)
self.statisticslearning_bounds = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
lower_bound_simulations=np.array([-1000, -1000, -1000]),
upper_bound_simulations=np.array([1000, 1000, 1000]),
use_tqdm=False, seed=1)
self.statisticslearning_no_schedulers = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2,
scheduler_parameters=False,
scheduler_simulations=False, use_tqdm=False)
self.statisticslearning_lam = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend,
n_samples=4, n_epochs=2, use_tqdm=False, sliced=False,
lam=0.1)
def test_initialization(self):
if not has_torch:
self.assertRaises(ImportError, ExponentialFamilyScoreMatching, [self.Y], self.statistics_cal, self.backend)
def test_transformation(self):
if has_torch:
self.new_statistics_calculator = self.statisticslearning_all_defaults.get_statistics()
self.new_statistics_calculator_no_scaler = self.statisticslearning_scale.get_statistics()
self.new_statistics_calculator_no_rescale = self.statisticslearning_all_defaults.get_statistics(
rescale_statistics=False)
Obs = Normal([2, 4])
y_obs = Obs.forward_simulate(Obs.get_input_values(), 1)[0].tolist()
extracted_statistics = self.new_statistics_calculator.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics), (1, 2))
extracted_statistics_no_rescale = self.new_statistics_calculator_no_rescale.statistics(y_obs)
self.assertEqual(np.shape(extracted_statistics_no_rescale), (1, 2))
self.assertFalse(np.allclose(extracted_statistics_no_rescale, extracted_statistics))
self.assertRaises(RuntimeError, self.new_statistics_calculator.statistics, [np.array([1, 2])])
self.assertRaises(RuntimeError, self.new_statistics_calculator_no_scaler.statistics, [np.array([1, 2])])
def test_errors(self):
if has_torch:
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, parameters=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations_net=createDefaultNN(1, 3))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, parameters_net=createDefaultNN(1, 3))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, noise_type="ciao", use_tqdm=False)
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, noise_type="sphere", variance_reduction=True,
use_tqdm=False)
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, simulations=np.ones((100, 1)),
parameters=np.zeros((99, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1, 3)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=np.ones((100, 1, 2)))
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
simulations_val=np.ones((100, 1)),
parameters_val=np.zeros((99, 1)))
with self.assertRaises(TypeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters=[i for i in range(10)],
simulations=[i for i in range(10)])
with self.assertRaises(TypeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1,
parameters_val=[i for i in range(10)],
simulations_val=[i for i in range(10)])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, lower_bound_simulations=[1, 2, 3])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
seed=1, upper_bound_simulations=[1, 2, 3])
with self.assertRaises(RuntimeError):
self.statisticslearning = ExponentialFamilyScoreMatching([self.Y], self.statistics_cal, self.backend, n_samples=1000,
lower_bound_simulations=np.array([-1000, -1000]), seed=1,
upper_bound_simulations=np.array([1000, 1000, 1000]))
with self.assertRaises(RuntimeError):
self.statisticslearning_all_defaults.test_losses = [4, 2, 1]
self.statisticslearning_all_defaults.plot_losses()
with self.assertRaises(NotImplementedError):
self.statisticslearning_all_defaults.plot_losses(which_losses="foo")
def test_plots(self):
if has_torch:
self.statisticslearning_all_defaults.plot_losses()
self.statisticslearning_all_defaults.plot_losses(which_losses="train")
self.statisticslearning_all_defaults.plot_losses(which_losses="test")
if __name__ == '__main__':
unittest.main()
| true | true |
f7fe9be20480f1b08ea8c20cbfbc51b9436b5905 | 2,173 | py | Python | tacker/vnfm/infra_drivers/noop.py | sungbogo28/tacker | a3f0b6d4e9e490ffeb6b3084705f38d962134fff | [
"Apache-2.0"
] | null | null | null | tacker/vnfm/infra_drivers/noop.py | sungbogo28/tacker | a3f0b6d4e9e490ffeb6b3084705f38d962134fff | [
"Apache-2.0"
] | null | null | null | tacker/vnfm/infra_drivers/noop.py | sungbogo28/tacker | a3f0b6d4e9e490ffeb6b3084705f38d962134fff | [
"Apache-2.0"
] | 1 | 2019-01-21T10:57:10.000Z | 2019-01-21T10:57:10.000Z | # Copyright 2013, 2014 Intel Corporation.
# All Rights Reserved.
#
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
# TODO(yamahata): once unittests are impletemted, move this there
from oslo_log import log as logging
from oslo_utils import uuidutils
from tacker.common import log
from tacker.vnfm.infra_drivers import abstract_driver
LOG = logging.getLogger(__name__)
class VnfNoop(abstract_driver.VnfAbstractDriver):
"""Noop driver of hosting vnf for tests."""
def __init__(self):
super(VnfNoop, self).__init__()
self._instances = set()
def get_type(self):
return 'noop'
def get_name(self):
return 'noop'
def get_description(self):
return 'Tacker infra noop driver'
@log.log
def create(self, **kwargs):
instance_id = uuidutils.generate_uuid()
self._instances.add(instance_id)
return instance_id
@log.log
def create_wait(self, plugin, context, vnf_dict, vnf_id):
pass
@log.log
def update(self, plugin, context, vnf_id, vnf_dict, vnf):
if vnf_id not in self._instances:
LOG.debug('not found')
raise ValueError('No instance %s' % vnf_id)
@log.log
def update_wait(self, plugin, context, vnf_id):
pass
@log.log
def delete(self, plugin, context, vnf_id):
self._instances.remove(vnf_id)
@log.log
def delete_wait(self, plugin, context, vnf_id):
pass
def get_resource_info(self, plugin, context, vnf_info, auth_attr,
region_name=None):
return {'noop': {'id': uuidutils.generate_uuid(), 'type': 'noop'}}
| 28.592105 | 78 | 0.670502 |
from oslo_log import log as logging
from oslo_utils import uuidutils
from tacker.common import log
from tacker.vnfm.infra_drivers import abstract_driver
LOG = logging.getLogger(__name__)
class VnfNoop(abstract_driver.VnfAbstractDriver):
def __init__(self):
super(VnfNoop, self).__init__()
self._instances = set()
def get_type(self):
return 'noop'
def get_name(self):
return 'noop'
def get_description(self):
return 'Tacker infra noop driver'
@log.log
def create(self, **kwargs):
instance_id = uuidutils.generate_uuid()
self._instances.add(instance_id)
return instance_id
@log.log
def create_wait(self, plugin, context, vnf_dict, vnf_id):
pass
@log.log
def update(self, plugin, context, vnf_id, vnf_dict, vnf):
if vnf_id not in self._instances:
LOG.debug('not found')
raise ValueError('No instance %s' % vnf_id)
@log.log
def update_wait(self, plugin, context, vnf_id):
pass
@log.log
def delete(self, plugin, context, vnf_id):
self._instances.remove(vnf_id)
@log.log
def delete_wait(self, plugin, context, vnf_id):
pass
def get_resource_info(self, plugin, context, vnf_info, auth_attr,
region_name=None):
return {'noop': {'id': uuidutils.generate_uuid(), 'type': 'noop'}}
| true | true |
f7fe9c52b15e986902a3ba00feebcc2a53eeaf4a | 9,075 | py | Python | test/test_pluginmanager.py | noralsydmp/icetea | b486cdc8e0d2211e118f1f8211aa4d284ca02422 | [
"Apache-2.0"
] | 6 | 2018-08-10T17:11:10.000Z | 2020-04-29T07:05:36.000Z | test/test_pluginmanager.py | noralsydmp/icetea | b486cdc8e0d2211e118f1f8211aa4d284ca02422 | [
"Apache-2.0"
] | 58 | 2018-08-13T08:36:08.000Z | 2021-07-07T08:32:52.000Z | test/test_pluginmanager.py | noralsydmp/icetea | b486cdc8e0d2211e118f1f8211aa4d284ca02422 | [
"Apache-2.0"
] | 7 | 2018-08-10T12:53:18.000Z | 2021-11-08T05:15:42.000Z | # pylint: disable=missing-docstring,protected-access
"""
Copyright 2017 ARM Limited
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import unittest
import os
import sys
import mock
from icetea_lib.Plugin.PluginManager import PluginManager, PluginException
from icetea_lib.Plugin.plugins.default_plugins import default_plugins
class PMTestcase(unittest.TestCase):
def test_load_defaults(self):
bench = mock.MagicMock(spec=[])
bench.logger = mock.MagicMock(return_value=mock.MagicMock())
resp_parser = mock.MagicMock()
resp_parser.append = mock.MagicMock()
resp_parser.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=bench, responseparser=resp_parser)
pluginmanager.load_default_tc_plugins()
pluginmanager.load_default_run_plugins()
length = len(default_plugins)
self.assertEqual(len(pluginmanager.registered_plugins), length)
def test_register_all_tc_types(self):
# Set up mocks
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
mock_bench_function = mock.MagicMock()
mock_parser = mock.MagicMock()
plugin_class.get_bench_api.return_value = {"mock_func": mock_bench_function}
plugin_class.get_external_services.return_value = {"mock_class": mock.MagicMock}
plugin_class.get_parsers.return_value = {"mock_parser": mock_parser}
mock_parsermanager = mock.MagicMock()
mock_parsermanager.add_parser = mock.MagicMock()
mock_parsermanager.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
# Asserts
self.assertEqual(len(pluginmanager.registered_plugins), 1)
self.assertEqual(pluginmanager.registered_plugins[0], "test_plugin")
self.assertEqual(len(pluginmanager._external_services), 1)
mock_parsermanager.has_parser.assert_called_once_with("mock_parser")
mock_parsermanager.add_parser.assert_called_once_with("mock_parser", mock_parser)
def test_register_and_start_service(self):
# Set up mocks
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mock_class = mock.MagicMock()
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
pluginmanager.start_external_service("mock_class")
self.assertEqual(len(pluginmanager._started_services), 1)
pluginmanager.stop_external_services()
self.assertEqual(len(pluginmanager._started_services), 0)
self.assertEqual(len(pluginmanager._external_services), 1)
mock_class.assert_called_once()
def test_start_service_raises_exception(self): # pylint: disable=invalid-name
# Set up mocks
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mocked_service = mock.MagicMock()
mock_class = mock.MagicMock(return_value=mocked_service)
mocked_service.start = mock.MagicMock()
mocked_service.start.side_effect = [PluginException]
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
with self.assertRaises(PluginException):
pluginmanager.start_external_service("mock_class")
mocked_service.start.assert_called_once()
def test_register_start_stop_service(self): # pylint: disable=invalid-name
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mocked_service = mock.MagicMock()
mocked_service.start = mock.MagicMock()
mocked_service.stop = mock.MagicMock(side_effect=[PluginException])
mock_class = mock.MagicMock(return_value=mocked_service)
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
pluginmanager.start_external_service("mock_class")
self.assertEqual(len(pluginmanager._started_services), 1)
pluginmanager.stop_external_services()
self.assertEqual(len(pluginmanager._started_services), 0)
self.assertEqual(len(pluginmanager._external_services), 1)
mock_class.assert_called_once()
def test_register_raises_pluginexception(self): # pylint: disable=invalid-name
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
mock_bench_function = mock.MagicMock()
plugin_class.get_bench_api.return_value = {"mock_func": mock_bench_function}
mock_parsermanager = mock.MagicMock()
mock_parsermanager.add_parser = mock.MagicMock()
mock_parsermanager.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.registered_plugins = ["test_plugin"]
with self.assertRaises(PluginException):
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
def test_load_custom_plugins(self): # pylint: disable=no-self-use
modules = sys.modules
mock_bench = mock.MagicMock(spec=[])
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins = mock.MagicMock()
pluginmanager.load_custom_tc_plugins(os.path.join(os.path.dirname(os.path.abspath(
__file__)), "test_plugin/load_test_plugins.py"))
sys.modules = modules
pluginmanager.register_tc_plugins.assert_called_once()
@mock.patch("icetea_lib.Plugin.PluginManager.importlib")
def test_load_custom_plugin_exception(self, mock_importer): # pylint: disable=invalid-name
mock_bench = mock.MagicMock(spec=[])
mock_parsermanager = mock.MagicMock()
mock_importer.import_module = mock.MagicMock(side_effect=[ImportError])
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
with self.assertRaises(PluginException):
pluginmanager.load_custom_tc_plugins(os.path.join(os.path.dirname(os.path.abspath(
__file__)), "test_plugin/load_test_plugins.py"))
if __name__ == '__main__':
unittest.main()
| 46.06599 | 95 | 0.729366 |
import unittest
import os
import sys
import mock
from icetea_lib.Plugin.PluginManager import PluginManager, PluginException
from icetea_lib.Plugin.plugins.default_plugins import default_plugins
class PMTestcase(unittest.TestCase):
def test_load_defaults(self):
bench = mock.MagicMock(spec=[])
bench.logger = mock.MagicMock(return_value=mock.MagicMock())
resp_parser = mock.MagicMock()
resp_parser.append = mock.MagicMock()
resp_parser.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=bench, responseparser=resp_parser)
pluginmanager.load_default_tc_plugins()
pluginmanager.load_default_run_plugins()
length = len(default_plugins)
self.assertEqual(len(pluginmanager.registered_plugins), length)
def test_register_all_tc_types(self):
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
mock_bench_function = mock.MagicMock()
mock_parser = mock.MagicMock()
plugin_class.get_bench_api.return_value = {"mock_func": mock_bench_function}
plugin_class.get_external_services.return_value = {"mock_class": mock.MagicMock}
plugin_class.get_parsers.return_value = {"mock_parser": mock_parser}
mock_parsermanager = mock.MagicMock()
mock_parsermanager.add_parser = mock.MagicMock()
mock_parsermanager.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
self.assertEqual(len(pluginmanager.registered_plugins), 1)
self.assertEqual(pluginmanager.registered_plugins[0], "test_plugin")
self.assertEqual(len(pluginmanager._external_services), 1)
mock_parsermanager.has_parser.assert_called_once_with("mock_parser")
mock_parsermanager.add_parser.assert_called_once_with("mock_parser", mock_parser)
def test_register_and_start_service(self):
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mock_class = mock.MagicMock()
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
pluginmanager.start_external_service("mock_class")
self.assertEqual(len(pluginmanager._started_services), 1)
pluginmanager.stop_external_services()
self.assertEqual(len(pluginmanager._started_services), 0)
self.assertEqual(len(pluginmanager._external_services), 1)
mock_class.assert_called_once()
def test_start_service_raises_exception(self):
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mocked_service = mock.MagicMock()
mock_class = mock.MagicMock(return_value=mocked_service)
mocked_service.start = mock.MagicMock()
mocked_service.start.side_effect = [PluginException]
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
with self.assertRaises(PluginException):
pluginmanager.start_external_service("mock_class")
mocked_service.start.assert_called_once()
def test_register_start_stop_service(self):
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
plugin_class.get_parsers = mock.MagicMock()
plugin_class.get_external_services = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
plugin_class.get_bench_api.return_value = None
mocked_service = mock.MagicMock()
mocked_service.start = mock.MagicMock()
mocked_service.stop = mock.MagicMock(side_effect=[PluginException])
mock_class = mock.MagicMock(return_value=mocked_service)
plugin_class.get_external_services.return_value = {"mock_class": mock_class}
plugin_class.get_parsers.return_value = None
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
pluginmanager.start_external_service("mock_class")
self.assertEqual(len(pluginmanager._started_services), 1)
pluginmanager.stop_external_services()
self.assertEqual(len(pluginmanager._started_services), 0)
self.assertEqual(len(pluginmanager._external_services), 1)
mock_class.assert_called_once()
def test_register_raises_pluginexception(self):
plugin_class = mock.MagicMock()
plugin_class.init = mock.MagicMock()
plugin_class.get_bench_api = mock.MagicMock()
mock_bench = mock.MagicMock(spec=[])
mock_bench.logger = mock.MagicMock(return_value=mock.MagicMock())
mock_bench_function = mock.MagicMock()
plugin_class.get_bench_api.return_value = {"mock_func": mock_bench_function}
mock_parsermanager = mock.MagicMock()
mock_parsermanager.add_parser = mock.MagicMock()
mock_parsermanager.has_parser = mock.MagicMock(return_value=False)
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.registered_plugins = ["test_plugin"]
with self.assertRaises(PluginException):
pluginmanager.register_tc_plugins("test_plugin", plugin_class)
def test_load_custom_plugins(self):
modules = sys.modules
mock_bench = mock.MagicMock(spec=[])
mock_parsermanager = mock.MagicMock()
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
pluginmanager.register_tc_plugins = mock.MagicMock()
pluginmanager.load_custom_tc_plugins(os.path.join(os.path.dirname(os.path.abspath(
__file__)), "test_plugin/load_test_plugins.py"))
sys.modules = modules
pluginmanager.register_tc_plugins.assert_called_once()
@mock.patch("icetea_lib.Plugin.PluginManager.importlib")
def test_load_custom_plugin_exception(self, mock_importer):
mock_bench = mock.MagicMock(spec=[])
mock_parsermanager = mock.MagicMock()
mock_importer.import_module = mock.MagicMock(side_effect=[ImportError])
pluginmanager = PluginManager(bench=mock_bench, responseparser=mock_parsermanager)
with self.assertRaises(PluginException):
pluginmanager.load_custom_tc_plugins(os.path.join(os.path.dirname(os.path.abspath(
__file__)), "test_plugin/load_test_plugins.py"))
if __name__ == '__main__':
unittest.main()
| true | true |
f7fe9c842b6fde00535088f166a52c9c7725826f | 286 | py | Python | 2021/day_11/test_solution.py | krother/advent_of_code | fd7d5199666b2f3a60c41c6cf24b747322ad88e5 | [
"MIT"
] | 3 | 2021-12-01T09:27:34.000Z | 2022-02-24T23:35:56.000Z | 2021/day_11/test_solution.py | krother/advent_of_code | fd7d5199666b2f3a60c41c6cf24b747322ad88e5 | [
"MIT"
] | null | null | null | 2021/day_11/test_solution.py | krother/advent_of_code | fd7d5199666b2f3a60c41c6cf24b747322ad88e5 | [
"MIT"
] | null | null | null | import pytest
from .solution import solve
INPUT = """5483143223
2745854711
5264556173
6141336146
6357385478
4167524645
2176841721
6882881134
4846848554
5283751526
"""
def test_solve():
assert solve(INPUT) == 1656
def test_solve2():
assert solve(INPUT, 999999999999) == 195
| 12.434783 | 44 | 0.762238 | import pytest
from .solution import solve
INPUT = """5483143223
2745854711
5264556173
6141336146
6357385478
4167524645
2176841721
6882881134
4846848554
5283751526
"""
def test_solve():
assert solve(INPUT) == 1656
def test_solve2():
assert solve(INPUT, 999999999999) == 195
| true | true |
f7fe9cb437273e5169b1c20580e73b1720f0ff50 | 668 | py | Python | components/Actuators/LowLevel/winch.py | Raptacon/Robot-2022 | f59c6a6ebd5779a2fd91181b65cbcd677507ca5d | [
"MIT"
] | 4 | 2022-01-31T14:05:31.000Z | 2022-03-26T14:12:45.000Z | components/Actuators/LowLevel/winch.py | Raptacon/Robot-2022 | f59c6a6ebd5779a2fd91181b65cbcd677507ca5d | [
"MIT"
] | 57 | 2022-01-13T02:41:31.000Z | 2022-03-26T14:50:42.000Z | components/Actuators/LowLevel/winch.py | Raptacon/Robot-2022 | f59c6a6ebd5779a2fd91181b65cbcd677507ca5d | [
"MIT"
] | null | null | null |
class Winch:
compatString = ["teapot"]
motors_winch: dict
def on_enable(self):
"""
Sets up the winch
"""
self.upSpeed = 0
self.winchMotor = self.motors_winch["winchMotor"]
self.logger.info("Lifter Component Created")
def setRaise(self):
"""
Sets the motor speed to .5 in order to reel in the winch
"""
self.upSpeed = .5
def setLower(self):
self.upSpeed = -1
def stop(self):
"""
Sets the motor speed to 0 in order to stop the winch
"""
self.upSpeed = 0
def execute(self):
self.winchMotor.set(self.upSpeed)
| 20.875 | 64 | 0.546407 |
class Winch:
compatString = ["teapot"]
motors_winch: dict
def on_enable(self):
self.upSpeed = 0
self.winchMotor = self.motors_winch["winchMotor"]
self.logger.info("Lifter Component Created")
def setRaise(self):
self.upSpeed = .5
def setLower(self):
self.upSpeed = -1
def stop(self):
self.upSpeed = 0
def execute(self):
self.winchMotor.set(self.upSpeed)
| true | true |
f7fe9d66d4c64174c063245c6d2cb2a4b7a1596d | 486 | py | Python | tests/conftest.py | Yasti4/python-aioddd | a0731e05a0133bf5636437ceb7625f7deaa100ab | [
"MIT"
] | 4 | 2020-07-28T12:34:02.000Z | 2021-02-11T09:57:20.000Z | tests/conftest.py | Yasti4/python-aioddd | a0731e05a0133bf5636437ceb7625f7deaa100ab | [
"MIT"
] | 2 | 2020-11-19T20:45:53.000Z | 2020-12-25T13:48:08.000Z | tests/conftest.py | ticdenis/python-aiodi | 4ad35145674f5ec0ed6324bec7dd186ab0a8bc33 | [
"MIT"
] | 1 | 2020-11-19T20:39:09.000Z | 2020-11-19T20:39:09.000Z | import sys
from asyncio import AbstractEventLoop, get_event_loop_policy
from unittest.mock import MagicMock
if sys.version_info >= (3, 8):
from unittest.mock import AsyncMock
else:
class AsyncMock(MagicMock):
async def __call__(self, *args, **kwargs):
return super(AsyncMock, self).__call__(*args, **kwargs)
from pytest import fixture
@fixture(scope='session')
def event_loop() -> AbstractEventLoop:
return get_event_loop_policy().new_event_loop()
| 24.3 | 67 | 0.734568 | import sys
from asyncio import AbstractEventLoop, get_event_loop_policy
from unittest.mock import MagicMock
if sys.version_info >= (3, 8):
from unittest.mock import AsyncMock
else:
class AsyncMock(MagicMock):
async def __call__(self, *args, **kwargs):
return super(AsyncMock, self).__call__(*args, **kwargs)
from pytest import fixture
@fixture(scope='session')
def event_loop() -> AbstractEventLoop:
return get_event_loop_policy().new_event_loop()
| true | true |
f7fe9e40ca2bd2c5da645db6823f7967d370514f | 12,777 | py | Python | kd_splicing/kd_splicing/helpers.py | konovalovdmitry/catsnap | d5f1d7c37dcee1ad3fee2cdc12a3b44b56f4c63f | [
"MIT"
] | null | null | null | kd_splicing/kd_splicing/helpers.py | konovalovdmitry/catsnap | d5f1d7c37dcee1ad3fee2cdc12a3b44b56f4c63f | [
"MIT"
] | null | null | null | kd_splicing/kd_splicing/helpers.py | konovalovdmitry/catsnap | d5f1d7c37dcee1ad3fee2cdc12a3b44b56f4c63f | [
"MIT"
] | 1 | 2021-09-30T08:06:20.000Z | 2021-09-30T08:06:20.000Z | import os
import uuid
from collections import defaultdict
from itertools import chain
from typing import Dict, List, Mapping, Optional, Tuple
import pandas as pd
from kd_common import excel, logutil, pathutil
from kd_splicing import as_type, blast, database, features, ml, performance, pipeline
from kd_splicing.dataset.models import Dataset
from kd_splicing.dump import dump
from kd_splicing.models import FormattedResults, IsoformTuple, Match, SimpleMatch, Queries
from kd_splicing.models import SearchStatus
import itertools
from tqdm import tqdm
import json
_logger = logutil.get_logger(__name__)
def find_in_queries(
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
db: database.models.DB,
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]]
) -> Optional[IsoformTuple]:
tup = str_to_isoform_tuple(db, protein_ids_str)
for a in isoforms_to_duplicates[tup.a]:
for b in isoforms_to_duplicates[tup.b]:
dup = IsoformTuple(a,b)
if dup in matches_dict:
return dup
return None
#############
# Common
#############
def str_to_isoform_tuple(db: database.models.DB, protein_ids_str: str) -> IsoformTuple:
protein_ids = [protein_id.strip()
for protein_id in protein_ids_str.split(",")]
assert len(protein_ids) == 2
return IsoformTuple(
db.protein_id_to_isoform[protein_ids[0]], db.protein_id_to_isoform[protein_ids[1]])
def isoform_tuple_to_protein_ids(db: database.models.DB, iso_tuple: IsoformTuple) -> str:
return f"{db.isoforms[iso_tuple.a].protein_id},{db.isoforms[iso_tuple.b].protein_id}"
def tuples_to_queries(tuples: List[IsoformTuple], num_groups: int = 20) -> Queries:
isoforms = sorted(list(set(chain.from_iterable(
(query_isoforms.a, query_isoforms.b)
for query_isoforms in tuples
))))
group_count = itertools.cycle(range(0, num_groups))
isoform_to_group = {}
isoform_to_idx = {}
group_size: Dict[int, int] = defaultdict(int)
for iso in isoforms:
group = next(group_count)
isoform_to_group[iso] = group
isoform_to_idx[iso] = group_size[group]
group_size[group] += 1
return Queries(
tuples=tuples,
isoforms=isoforms,
isoform_to_idx=isoform_to_idx,
isoform_to_group=isoform_to_group,
)
def best_match_per_organism(matches: List[Match]) -> List[Match]:
query_organism_to_match: Dict[Tuple[IsoformTuple, str], Match] = {}
for m in matches:
key = (m.query_isoforms, m.hit_organism)
best_match = query_organism_to_match.get(key)
if not best_match or best_match.predicted_positive_probability < m.predicted_positive_probability:
query_organism_to_match[key] = m
return list(query_organism_to_match.values())
#############
# Stats
#############
def count_isoforms_per_organism(db: database.models.DB) -> None:
organism_to_isoform_count: Dict[str, int] = defaultdict(int)
for isoform in db.isoforms.values():
gene = db.genes[isoform.gene_uuid]
record = db.records[gene.record_uuid]
organism_to_isoform_count[record.organism] += 1
for key, value in sorted(organism_to_isoform_count.items(), key=lambda p: p[1]):
print(key, ",", value)
def calc_performance(matches: List[Match]) -> None:
predicted = [m.predicted_positive for m in matches]
correct = [m.positive for m in matches]
_logger.info(
f"Performance:\n{pd.Series(performance.binary_y_performance(correct, predicted))}")
def db_organisms_stats(db: database.models.DB, db_folder: str) -> None:
df = database.utils.to_df(db)
d1 = df["organism"].value_counts().reset_index()
excel.write(d1, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms.xlsx"))
d2 = df[df["db_name"] == "refseq"]["organism"].value_counts().reset_index()
excel.write(d2, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_refseq.xlsx"))
d3 = df[df["db_name"] == "genbank"]["organism"].value_counts().reset_index()
excel.write(d3, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_genbank.xlsx"))
d4 = df[df["db_name_src"] == "refseq"]["organism"].value_counts().reset_index()
excel.write(d4, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_refseq_src.xlsx"))
d5 = df[df["db_name_src"] == "genbank"]["organism"].value_counts().reset_index()
excel.write(d5, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_genbank_src.xlsx"))
def db_missed_files(p: pipeline.Pipeline) -> None:
def prepare(s: str) -> str:
s = os.path.basename(s)
s = ".".join(s.split(".")[:-1])
return s
files = pathutil.file_list(p.folder_archive, p.archive_extension)
extracted = pathutil.file_list(p.folder_extracted)
files.sort()
extracted = [prepare(f) for f in extracted]
files = [prepare(f) for f in files]
print(sorted(list(set(files) - set(extracted))))
#############
# Dumps
#############
def single_cross_validation_and_dump(db: database.models.DB, launch_folder: str, ds: List[Match], test_protein_ids: str) -> None:
protein_ids = test_protein_ids.split(",")
assert len(protein_ids) == 2
protein_id_to_isoform = {
i.protein_id: i.uuid for i in db.isoforms.values()}
test_query_isoforms = IsoformTuple(
protein_id_to_isoform[protein_ids[0]], protein_id_to_isoform[protein_ids[1]])
train_ds = [m for m in ds if m.query_isoforms != test_query_isoforms]
test_ds = [m for m in ds if m.query_isoforms == test_query_isoforms]
d = ml.Detector()
d.fit(train_ds)
d.transform(test_ds)
calc_performance(test_ds)
folder = pathutil.create_folder(launch_folder, "cross_validation")
dump(db, folder, test_ds)
def dump_single_query_simple_matches(
db: database.models.DB,
launch_folder: str,
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]],
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
) -> None:
query_isoforms = find_in_queries(protein_ids_str, isoforms_to_duplicates, db, matches_dict)
if not query_isoforms:
print("No such query in precalculated queries")
return
simple_matches = matches_dict[query_isoforms]
matches = features.convert_matches({query_isoforms: simple_matches})
dump(db, pathutil.create_folder(launch_folder,
"matches_simple_single", protein_ids_str), matches)
def calc_features_and_dump_single(
db: database.models.DB,
launch_folder: str,
queries: Queries,
detector: ml.Detector,
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]],
) -> List[Match]:
query_isoforms = find_in_queries(protein_ids_str, isoforms_to_duplicates, db, matches_dict)
if not query_isoforms:
print("No such query in precalculated queries")
return
matches = features.calc(db, launch_folder, queries, [query_isoforms])
detector.transform(matches)
dump(db, pathutil.create_folder(launch_folder,
"matches_single", protein_ids_str), matches)
return matches
#############
# Search
#############
def search(
db: database.models.DB,
p: pipeline.Pipeline,
detector: ml.Detector,
query_protein_ids_str: List[str],
blast_db_path: str,
status: SearchStatus = SearchStatus.construct(progress = 0, description = ""),
isoforms_to_duplicates: Optional[Mapping[uuid.UUID, List[uuid.UUID]]] = None,
) -> str:
status.set(0, "Preparing queries")
tuples = [str_to_isoform_tuple(db, query_proteins) for query_proteins in query_protein_ids_str]
queries = tuples_to_queries(tuples, num_groups=1)
name = ";".join(query_protein_ids_str)
return search_queries(db, p, detector, queries, name, blast_db_path, status, isoforms_to_duplicates)
def search_queries(
db: database.models.DB,
p: pipeline.Pipeline,
detector: ml.Detector,
queries: Queries,
name: str,
blast_db_path: str,
status: SearchStatus,
isoforms_to_duplicates: Optional[Mapping[uuid.UUID, List[uuid.UUID]]] = None,
) -> str:
status.set(10, "BLAST running")
blast.create_queires(db, queries, p.launch_folder)
blast.run(p.launch_folder, blast_db_path, parallel = False)
status.set(20, "Reading BLAST results")
queries.isoform_to_file = get_isoforms_to_file(p.launch_folder)
status.set(30, "Calculating features")
matches = features.calc(db, p.launch_folder, queries)
status.set(40, "Running ml model")
detector.transform(matches)
result_folder = pathutil.create_folder(p.launch_folder, "search_single", name)
status.set(50, "Preparing results")
dump(db, result_folder, matches, isoforms_to_duplicates)
return result_folder
def matches_to_df(
db: database.models.DB,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
matches: List[Match],
) -> pd.DataFrame:
data = []
for m in tqdm(matches):
q_iso_a = db.isoforms[m.query_isoforms.a]
q_iso_b = db.isoforms[m.query_isoforms.b]
q_gene = db.genes[q_iso_a.gene_uuid]
q_record = db.records[q_gene.record_uuid]
q_file = db.files[q_record.file_uuid]
h_iso_a = db.isoforms[m.hit_isoforms.a]
h_iso_b = db.isoforms[m.hit_isoforms.b]
h_gene = db.genes[h_iso_a.gene_uuid]
h_record = db.records[h_gene.record_uuid]
h_file = db.files[h_record.file_uuid]
hit_as_types = as_type.get_isoforms_as_types(db, isoforms_to_duplicates, h_iso_a.uuid, h_iso_b.uuid)
query_as_types = as_type.get_isoforms_as_types(db, isoforms_to_duplicates, q_iso_a.uuid, q_iso_b.uuid)
intersection_as_types = hit_as_types & query_as_types
row = {
"query_isoforms": m.query_isoforms,
"hit_isoforms": m.hit_isoforms,
"hit_organism": m.hit_organism,
"hit_db_name": m.hit_db_name,
"hit_gene_uuid": h_iso_a.gene_uuid,
"hit_protein_ids": f"{h_iso_a.protein_id}, {h_iso_b.protein_id}",
"hit_locus_tag": h_gene.locus_tag,
"hit_gene_id": h_gene.gene_id,
"hit_db_xref": h_gene.db_xref,
"hit_as_types": hit_as_types,
"hit_as_types_max": max([len(as_type) for as_type in hit_as_types], default=0),
"positive": m.positive,
"predicted_positive": m.predicted_positive,
"predicted_positive_probability": m.predicted_positive_probability,
"isoform_blast_score": m.isoform_blast_score,
"splicing_difference": m.splicing_difference,
"splicing_similarity": m.splicing_similarity,
"splicing_dissimilarity": m.splicing_dissimilarity,
"query_gene_uuid": q_iso_a.gene_uuid,
"query_protein_ids": f"{q_iso_a.protein_id}, {q_iso_b.protein_id}",
"query_locus_tag": q_gene.locus_tag,
"query_gene_id": q_gene.gene_id,
"query_db_xref": q_gene.db_xref,
"query_as_types": query_as_types,
"query_as_types_max": max([len(as_type) for as_type in query_as_types], default=0),
"intersection_as_types": intersection_as_types,
"intersection_as_types_len": len(intersection_as_types),
"conservative": int(m.predicted_positive),
"conservative_probability": m.predicted_positive_probability,
"db_name": q_file.db_name,
}
data.append(row)
df = pd.DataFrame(data)
return df
def get_isoforms_to_file(launch_folder: str) -> Mapping[uuid.UUID, str]:
results_folder = pathutil.create_folder(launch_folder, "blast_results")
isoforms_to_file: Dict[uuid.UUID, str] = {}
for group_folder in tqdm(pathutil.get_sub_directories(results_folder)):
for result_file in pathutil.file_list(group_folder, ".json"):
with open(result_file, "r") as f:
try:
data = json.load(f)
except Exception as e:
_logger.exception("exception in file result file")
continue
query_iso_str = data["BlastOutput2"]["report"]["results"]["search"]["query_title"]
isoforms_to_file[uuid.UUID(query_iso_str)] = result_file
return isoforms_to_file | 39.435185 | 129 | 0.681146 | import os
import uuid
from collections import defaultdict
from itertools import chain
from typing import Dict, List, Mapping, Optional, Tuple
import pandas as pd
from kd_common import excel, logutil, pathutil
from kd_splicing import as_type, blast, database, features, ml, performance, pipeline
from kd_splicing.dataset.models import Dataset
from kd_splicing.dump import dump
from kd_splicing.models import FormattedResults, IsoformTuple, Match, SimpleMatch, Queries
from kd_splicing.models import SearchStatus
import itertools
from tqdm import tqdm
import json
_logger = logutil.get_logger(__name__)
def find_in_queries(
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
db: database.models.DB,
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]]
) -> Optional[IsoformTuple]:
tup = str_to_isoform_tuple(db, protein_ids_str)
for a in isoforms_to_duplicates[tup.a]:
for b in isoforms_to_duplicates[tup.b]:
dup = IsoformTuple(a,b)
if dup in matches_dict:
return dup
return None
tein_id in protein_ids_str.split(",")]
assert len(protein_ids) == 2
return IsoformTuple(
db.protein_id_to_isoform[protein_ids[0]], db.protein_id_to_isoform[protein_ids[1]])
def isoform_tuple_to_protein_ids(db: database.models.DB, iso_tuple: IsoformTuple) -> str:
return f"{db.isoforms[iso_tuple.a].protein_id},{db.isoforms[iso_tuple.b].protein_id}"
def tuples_to_queries(tuples: List[IsoformTuple], num_groups: int = 20) -> Queries:
isoforms = sorted(list(set(chain.from_iterable(
(query_isoforms.a, query_isoforms.b)
for query_isoforms in tuples
))))
group_count = itertools.cycle(range(0, num_groups))
isoform_to_group = {}
isoform_to_idx = {}
group_size: Dict[int, int] = defaultdict(int)
for iso in isoforms:
group = next(group_count)
isoform_to_group[iso] = group
isoform_to_idx[iso] = group_size[group]
group_size[group] += 1
return Queries(
tuples=tuples,
isoforms=isoforms,
isoform_to_idx=isoform_to_idx,
isoform_to_group=isoform_to_group,
)
def best_match_per_organism(matches: List[Match]) -> List[Match]:
query_organism_to_match: Dict[Tuple[IsoformTuple, str], Match] = {}
for m in matches:
key = (m.query_isoforms, m.hit_organism)
best_match = query_organism_to_match.get(key)
if not best_match or best_match.predicted_positive_probability < m.predicted_positive_probability:
query_organism_to_match[key] = m
return list(query_organism_to_match.values())
isoforms.values():
gene = db.genes[isoform.gene_uuid]
record = db.records[gene.record_uuid]
organism_to_isoform_count[record.organism] += 1
for key, value in sorted(organism_to_isoform_count.items(), key=lambda p: p[1]):
print(key, ",", value)
def calc_performance(matches: List[Match]) -> None:
predicted = [m.predicted_positive for m in matches]
correct = [m.positive for m in matches]
_logger.info(
f"Performance:\n{pd.Series(performance.binary_y_performance(correct, predicted))}")
def db_organisms_stats(db: database.models.DB, db_folder: str) -> None:
df = database.utils.to_df(db)
d1 = df["organism"].value_counts().reset_index()
excel.write(d1, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms.xlsx"))
d2 = df[df["db_name"] == "refseq"]["organism"].value_counts().reset_index()
excel.write(d2, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_refseq.xlsx"))
d3 = df[df["db_name"] == "genbank"]["organism"].value_counts().reset_index()
excel.write(d3, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_genbank.xlsx"))
d4 = df[df["db_name_src"] == "refseq"]["organism"].value_counts().reset_index()
excel.write(d4, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_refseq_src.xlsx"))
d5 = df[df["db_name_src"] == "genbank"]["organism"].value_counts().reset_index()
excel.write(d5, os.path.join(pathutil.create_folder(
db_folder, "stats"), os.path.basename(db_folder) + "_db_organisms_genbank_src.xlsx"))
def db_missed_files(p: pipeline.Pipeline) -> None:
def prepare(s: str) -> str:
s = os.path.basename(s)
s = ".".join(s.split(".")[:-1])
return s
files = pathutil.file_list(p.folder_archive, p.archive_extension)
extracted = pathutil.file_list(p.folder_extracted)
files.sort()
extracted = [prepare(f) for f in extracted]
files = [prepare(f) for f in files]
print(sorted(list(set(files) - set(extracted))))
t_protein_ids.split(",")
assert len(protein_ids) == 2
protein_id_to_isoform = {
i.protein_id: i.uuid for i in db.isoforms.values()}
test_query_isoforms = IsoformTuple(
protein_id_to_isoform[protein_ids[0]], protein_id_to_isoform[protein_ids[1]])
train_ds = [m for m in ds if m.query_isoforms != test_query_isoforms]
test_ds = [m for m in ds if m.query_isoforms == test_query_isoforms]
d = ml.Detector()
d.fit(train_ds)
d.transform(test_ds)
calc_performance(test_ds)
folder = pathutil.create_folder(launch_folder, "cross_validation")
dump(db, folder, test_ds)
def dump_single_query_simple_matches(
db: database.models.DB,
launch_folder: str,
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]],
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
) -> None:
query_isoforms = find_in_queries(protein_ids_str, isoforms_to_duplicates, db, matches_dict)
if not query_isoforms:
print("No such query in precalculated queries")
return
simple_matches = matches_dict[query_isoforms]
matches = features.convert_matches({query_isoforms: simple_matches})
dump(db, pathutil.create_folder(launch_folder,
"matches_simple_single", protein_ids_str), matches)
def calc_features_and_dump_single(
db: database.models.DB,
launch_folder: str,
queries: Queries,
detector: ml.Detector,
protein_ids_str: str,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
matches_dict: Mapping[IsoformTuple, List[SimpleMatch]],
) -> List[Match]:
query_isoforms = find_in_queries(protein_ids_str, isoforms_to_duplicates, db, matches_dict)
if not query_isoforms:
print("No such query in precalculated queries")
return
matches = features.calc(db, launch_folder, queries, [query_isoforms])
detector.transform(matches)
dump(db, pathutil.create_folder(launch_folder,
"matches_single", protein_ids_str), matches)
return matches
r,
status: SearchStatus = SearchStatus.construct(progress = 0, description = ""),
isoforms_to_duplicates: Optional[Mapping[uuid.UUID, List[uuid.UUID]]] = None,
) -> str:
status.set(0, "Preparing queries")
tuples = [str_to_isoform_tuple(db, query_proteins) for query_proteins in query_protein_ids_str]
queries = tuples_to_queries(tuples, num_groups=1)
name = ";".join(query_protein_ids_str)
return search_queries(db, p, detector, queries, name, blast_db_path, status, isoforms_to_duplicates)
def search_queries(
db: database.models.DB,
p: pipeline.Pipeline,
detector: ml.Detector,
queries: Queries,
name: str,
blast_db_path: str,
status: SearchStatus,
isoforms_to_duplicates: Optional[Mapping[uuid.UUID, List[uuid.UUID]]] = None,
) -> str:
status.set(10, "BLAST running")
blast.create_queires(db, queries, p.launch_folder)
blast.run(p.launch_folder, blast_db_path, parallel = False)
status.set(20, "Reading BLAST results")
queries.isoform_to_file = get_isoforms_to_file(p.launch_folder)
status.set(30, "Calculating features")
matches = features.calc(db, p.launch_folder, queries)
status.set(40, "Running ml model")
detector.transform(matches)
result_folder = pathutil.create_folder(p.launch_folder, "search_single", name)
status.set(50, "Preparing results")
dump(db, result_folder, matches, isoforms_to_duplicates)
return result_folder
def matches_to_df(
db: database.models.DB,
isoforms_to_duplicates: Mapping[uuid.UUID, List[uuid.UUID]],
matches: List[Match],
) -> pd.DataFrame:
data = []
for m in tqdm(matches):
q_iso_a = db.isoforms[m.query_isoforms.a]
q_iso_b = db.isoforms[m.query_isoforms.b]
q_gene = db.genes[q_iso_a.gene_uuid]
q_record = db.records[q_gene.record_uuid]
q_file = db.files[q_record.file_uuid]
h_iso_a = db.isoforms[m.hit_isoforms.a]
h_iso_b = db.isoforms[m.hit_isoforms.b]
h_gene = db.genes[h_iso_a.gene_uuid]
h_record = db.records[h_gene.record_uuid]
h_file = db.files[h_record.file_uuid]
hit_as_types = as_type.get_isoforms_as_types(db, isoforms_to_duplicates, h_iso_a.uuid, h_iso_b.uuid)
query_as_types = as_type.get_isoforms_as_types(db, isoforms_to_duplicates, q_iso_a.uuid, q_iso_b.uuid)
intersection_as_types = hit_as_types & query_as_types
row = {
"query_isoforms": m.query_isoforms,
"hit_isoforms": m.hit_isoforms,
"hit_organism": m.hit_organism,
"hit_db_name": m.hit_db_name,
"hit_gene_uuid": h_iso_a.gene_uuid,
"hit_protein_ids": f"{h_iso_a.protein_id}, {h_iso_b.protein_id}",
"hit_locus_tag": h_gene.locus_tag,
"hit_gene_id": h_gene.gene_id,
"hit_db_xref": h_gene.db_xref,
"hit_as_types": hit_as_types,
"hit_as_types_max": max([len(as_type) for as_type in hit_as_types], default=0),
"positive": m.positive,
"predicted_positive": m.predicted_positive,
"predicted_positive_probability": m.predicted_positive_probability,
"isoform_blast_score": m.isoform_blast_score,
"splicing_difference": m.splicing_difference,
"splicing_similarity": m.splicing_similarity,
"splicing_dissimilarity": m.splicing_dissimilarity,
"query_gene_uuid": q_iso_a.gene_uuid,
"query_protein_ids": f"{q_iso_a.protein_id}, {q_iso_b.protein_id}",
"query_locus_tag": q_gene.locus_tag,
"query_gene_id": q_gene.gene_id,
"query_db_xref": q_gene.db_xref,
"query_as_types": query_as_types,
"query_as_types_max": max([len(as_type) for as_type in query_as_types], default=0),
"intersection_as_types": intersection_as_types,
"intersection_as_types_len": len(intersection_as_types),
"conservative": int(m.predicted_positive),
"conservative_probability": m.predicted_positive_probability,
"db_name": q_file.db_name,
}
data.append(row)
df = pd.DataFrame(data)
return df
def get_isoforms_to_file(launch_folder: str) -> Mapping[uuid.UUID, str]:
results_folder = pathutil.create_folder(launch_folder, "blast_results")
isoforms_to_file: Dict[uuid.UUID, str] = {}
for group_folder in tqdm(pathutil.get_sub_directories(results_folder)):
for result_file in pathutil.file_list(group_folder, ".json"):
with open(result_file, "r") as f:
try:
data = json.load(f)
except Exception as e:
_logger.exception("exception in file result file")
continue
query_iso_str = data["BlastOutput2"]["report"]["results"]["search"]["query_title"]
isoforms_to_file[uuid.UUID(query_iso_str)] = result_file
return isoforms_to_file | true | true |
f7fe9edce30814d34454bfea14b8ac92cf00915e | 22,646 | py | Python | efficientdet/anchors.py | HyunjiEllenPak/automl | fedf04adf12c5fd11045ea06e2f5c11a5a5490c4 | [
"Apache-2.0"
] | null | null | null | efficientdet/anchors.py | HyunjiEllenPak/automl | fedf04adf12c5fd11045ea06e2f5c11a5a5490c4 | [
"Apache-2.0"
] | null | null | null | efficientdet/anchors.py | HyunjiEllenPak/automl | fedf04adf12c5fd11045ea06e2f5c11a5a5490c4 | [
"Apache-2.0"
] | null | null | null | # Lint as: python3
# Copyright 2020 Google Research. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Anchor definition.
This module is borrowed from TPU RetinaNet implementation:
https://github.com/tensorflow/tpu/blob/master/models/official/retinanet/anchors.py
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
from absl import logging
import numpy as np
import tensorflow.compat.v1 as tf
import utils
from object_detection import argmax_matcher
from object_detection import box_list
from object_detection import faster_rcnn_box_coder
from object_detection import region_similarity_calculator
from object_detection import target_assigner
# The minimum score to consider a logit for identifying detections.
MIN_CLASS_SCORE = -5.0
# The score for a dummy detection
_DUMMY_DETECTION_SCORE = -1e5
# The maximum number of (anchor,class) pairs to keep for non-max suppression.
MAX_DETECTION_POINTS = 5000
# The maximum number of detections per image.
MAX_DETECTIONS_PER_IMAGE = 100
# The minimal score threshold.
MIN_SCORE_THRESH = 0.4
def sigmoid(x):
"""Sigmoid function for use with Numpy for CPU evaluation."""
return 1 / (1 + np.exp(-x))
def decode_box_outputs(rel_codes, anchors):
"""Transforms relative regression coordinates to absolute positions.
Network predictions are normalized and relative to a given anchor; this
reverses the transformation and outputs absolute coordinates for the input
image.
Args:
rel_codes: box regression targets.
anchors: anchors on all feature levels.
Returns:
outputs: bounding boxes.
"""
ycenter_a = (anchors[0] + anchors[2]) / 2
xcenter_a = (anchors[1] + anchors[3]) / 2
ha = anchors[2] - anchors[0]
wa = anchors[3] - anchors[1]
ty, tx, th, tw = rel_codes
w = np.exp(tw) * wa
h = np.exp(th) * ha
ycenter = ty * ha + ycenter_a
xcenter = tx * wa + xcenter_a
ymin = ycenter - h / 2.
xmin = xcenter - w / 2.
ymax = ycenter + h / 2.
xmax = xcenter + w / 2.
return np.column_stack([ymin, xmin, ymax, xmax])
def decode_box_outputs_tf(rel_codes, anchors):
"""Transforms relative regression coordinates to absolute positions.
Network predictions are normalized and relative to a given anchor; this
reverses the transformation and outputs absolute coordinates for the input
image.
Args:
rel_codes: box regression targets.
anchors: anchors on all feature levels.
Returns:
outputs: bounding boxes.
"""
ycenter_a = (anchors[0] + anchors[2]) / 2
xcenter_a = (anchors[1] + anchors[3]) / 2
ha = anchors[2] - anchors[0]
wa = anchors[3] - anchors[1]
ty, tx, th, tw = tf.unstack(rel_codes, num=4)
w = tf.math.exp(tw) * wa
h = tf.math.exp(th) * ha
ycenter = ty * ha + ycenter_a
xcenter = tx * wa + xcenter_a
ymin = ycenter - h / 2.
xmin = xcenter - w / 2.
ymax = ycenter + h / 2.
xmax = xcenter + w / 2.
return tf.stack([ymin, xmin, ymax, xmax], axis=1)
@tf.autograph.to_graph
def nms_tf(dets, thresh):
"""Non-maximum suppression with tf graph mode."""
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
order = tf.argsort(scores, direction='DESCENDING')
keep = tf.TensorArray(tf.int32, size=0, dynamic_size=True)
index = 0
while tf.size(order) > 0:
i = order[0]
keep = keep.write(index, i)
xx1 = tf.maximum(x1[i], tf.gather(x1, order[1:]))
yy1 = tf.maximum(y1[i], tf.gather(y1, order[1:]))
xx2 = tf.minimum(x2[i], tf.gather(x2, order[1:]))
yy2 = tf.minimum(y2[i], tf.gather(y2, order[1:]))
w = tf.maximum(0.0, xx2 - xx1 + 1)
h = tf.maximum(0.0, yy2 - yy1 + 1)
intersection = w * h
overlap = intersection / (
areas[i] + tf.gather(areas, order[1:]) - intersection)
inds = tf.where_v2(overlap <= thresh)
order = tf.concat(tf.gather(order, inds + 1), axis=1)
order = tf.squeeze(order, axis=-1)
index += 1
return keep.stack()
def nms(dets, thresh):
"""Non-maximum suppression."""
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
i = order[0]
keep.append(i)
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
w = np.maximum(0.0, xx2 - xx1 + 1)
h = np.maximum(0.0, yy2 - yy1 + 1)
intersection = w * h
overlap = intersection / (areas[i] + areas[order[1:]] - intersection)
inds = np.where(overlap <= thresh)[0]
order = order[inds + 1]
return keep
def _generate_anchor_configs(feat_sizes, min_level, max_level, num_scales,
aspect_ratios):
"""Generates mapping from output level to a list of anchor configurations.
A configuration is a tuple of (num_anchors, scale, aspect_ratio).
Args:
feat_sizes: list of dict of integer numbers of feature map sizes.
min_level: integer number of minimum level of the output feature pyramid.
max_level: integer number of maximum level of the output feature pyramid.
num_scales: integer number representing intermediate scales added
on each level. For instances, num_scales=2 adds two additional
anchor scales [2^0, 2^0.5] on each level.
aspect_ratios: list of tuples representing the aspect ratio anchors added
on each level. For instances, aspect_ratios =
[(1, 1), (1.4, 0.7), (0.7, 1.4)] adds three anchors on each level.
Returns:
anchor_configs: a dictionary with keys as the levels of anchors and
values as a list of anchor configuration.
"""
anchor_configs = {}
for level in range(min_level, max_level + 1):
anchor_configs[level] = []
for scale_octave in range(num_scales):
for aspect in aspect_ratios:
anchor_configs[level].append(
((feat_sizes[0]['height'] / float(feat_sizes[level]['height']),
feat_sizes[0]['width'] / float(feat_sizes[level]['width'])),
scale_octave / float(num_scales), aspect))
return anchor_configs
def _generate_anchor_boxes(image_size, anchor_scale, anchor_configs):
"""Generates multiscale anchor boxes.
Args:
image_size: tuple of integer numbers of input image size.
anchor_scale: float number representing the scale of size of the base
anchor to the feature stride 2^level.
anchor_configs: a dictionary with keys as the levels of anchors and
values as a list of anchor configuration.
Returns:
anchor_boxes: a numpy array with shape [N, 4], which stacks anchors on all
feature levels.
Raises:
ValueError: input size must be the multiple of largest feature stride.
"""
boxes_all = []
for _, configs in anchor_configs.items():
boxes_level = []
for config in configs:
stride, octave_scale, aspect = config
base_anchor_size_x = anchor_scale * stride[1] * 2**octave_scale
base_anchor_size_y = anchor_scale * stride[0] * 2**octave_scale
anchor_size_x_2 = base_anchor_size_x * aspect[0] / 2.0
anchor_size_y_2 = base_anchor_size_y * aspect[1] / 2.0
x = np.arange(stride[1] / 2, image_size[1], stride[1])
y = np.arange(stride[0] / 2, image_size[0], stride[0])
xv, yv = np.meshgrid(x, y)
xv = xv.reshape(-1)
yv = yv.reshape(-1)
boxes = np.vstack((yv - anchor_size_y_2, xv - anchor_size_x_2,
yv + anchor_size_y_2, xv + anchor_size_x_2))
boxes = np.swapaxes(boxes, 0, 1)
boxes_level.append(np.expand_dims(boxes, axis=1))
# concat anchors on the same level to the reshape NxAx4
boxes_level = np.concatenate(boxes_level, axis=1)
boxes_all.append(boxes_level.reshape([-1, 4]))
anchor_boxes = np.vstack(boxes_all)
return anchor_boxes
def _generate_detections_tf(cls_outputs,
box_outputs,
anchor_boxes,
indices,
classes,
image_id,
image_scale,
min_score_thresh=MIN_SCORE_THRESH,
max_boxes_to_draw=MAX_DETECTIONS_PER_IMAGE,
soft_nms_sigma=0.0,
iou_threshold=0.5,
use_native_nms=True):
"""Generates detections with model outputs and anchors.
Args:
cls_outputs: a numpy array with shape [N, 1], which has the highest class
scores on all feature levels. The N is the number of selected
top-K total anchors on all levels. (k being MAX_DETECTION_POINTS)
box_outputs: a numpy array with shape [N, 4], which stacks box regression
outputs on all feature levels. The N is the number of selected top-k
total anchors on all levels. (k being MAX_DETECTION_POINTS)
anchor_boxes: a numpy array with shape [N, 4], which stacks anchors on all
feature levels. The N is the number of selected top-k total anchors on
all levels.
indices: a numpy array with shape [N], which is the indices from top-k
selection.
classes: a numpy array with shape [N], which represents the class
prediction on all selected anchors from top-k selection.
image_id: an integer number to specify the image id.
image_scale: a float tensor representing the scale between original image
and input image for the detector. It is used to rescale detections for
evaluating with the original groundtruth annotations.
min_score_thresh: A float representing the threshold for deciding when to
remove boxes based on score.
max_boxes_to_draw: Max number of boxes to draw.
soft_nms_sigma: A scalar float representing the Soft NMS sigma parameter;
See Bodla et al, https://arxiv.org/abs/1704.04503). When
`soft_nms_sigma=0.0` (which is default), we fall back to standard (hard)
NMS.
iou_threshold: A float representing the threshold for deciding whether boxes
overlap too much with respect to IOU.
use_native_nms: a bool that indicates whether to use native nms.
Returns:
detections: detection results in a tensor with each row representing
[image_id, y, x, height, width, score, class]
"""
logging.info('Using tf version of post-processing.')
anchor_boxes = tf.gather(anchor_boxes, indices)
scores = tf.math.sigmoid(cls_outputs)
# apply bounding box regression to anchors
boxes = decode_box_outputs_tf(
tf.transpose(box_outputs, [1, 0]), tf.transpose(anchor_boxes, [1, 0]))
if use_native_nms:
logging.info('Using native nms.')
top_detection_idx, scores = tf.image.non_max_suppression_with_scores(
boxes,
scores,
max_boxes_to_draw,
iou_threshold=iou_threshold,
score_threshold=min_score_thresh,
soft_nms_sigma=soft_nms_sigma)
boxes = tf.gather(boxes, top_detection_idx)
else:
logging.info('Using customized nms.')
scores = tf.expand_dims(scores, axis=1)
all_detections = tf.concat([boxes, scores], axis=1)
top_detection_idx = nms_tf(all_detections, iou_threshold)
detections = tf.gather(all_detections, top_detection_idx)
scores = detections[:, 4]
boxes = detections[:, :4]
height = boxes[:, 2] - boxes[:, 0]
width = boxes[:, 3] - boxes[:, 1]
detections = tf.stack([
tf.cast(tf.repeat(image_id, tf.size(top_detection_idx)), tf.float32),
boxes[:, 0] * image_scale,
boxes[:, 1] * image_scale,
height * image_scale,
width * image_scale,
scores,
tf.cast(tf.gather(classes, top_detection_idx) + 1, tf.float32)
], axis=1)
return detections
def _generate_detections(cls_outputs, box_outputs, anchor_boxes, indices,
classes, image_id, image_scale, num_classes,
max_boxes_to_draw):
"""Generates detections with model outputs and anchors.
Args:
cls_outputs: a numpy array with shape [N, 1], which has the highest class
scores on all feature levels. The N is the number of selected
top-K total anchors on all levels. (k being MAX_DETECTION_POINTS)
box_outputs: a numpy array with shape [N, 4], which stacks box regression
outputs on all feature levels. The N is the number of selected top-k
total anchors on all levels. (k being MAX_DETECTION_POINTS)
anchor_boxes: a numpy array with shape [N, 4], which stacks anchors on all
feature levels. The N is the number of selected top-k total anchors on
all levels.
indices: a numpy array with shape [N], which is the indices from top-k
selection.
classes: a numpy array with shape [N], which represents the class
prediction on all selected anchors from top-k selection.
image_id: an integer number to specify the image id.
image_scale: a float tensor representing the scale between original image
and input image for the detector. It is used to rescale detections for
evaluating with the original groundtruth annotations.
num_classes: a integer that indicates the number of classes.
max_boxes_to_draw: max number of boxes to draw per image.
Returns:
detections: detection results in a tensor with each row representing
[image_id, x, y, width, height, score, class]
"""
logging.info('Using numpy version of post-processing.')
anchor_boxes = anchor_boxes[indices, :]
scores = sigmoid(cls_outputs)
# apply bounding box regression to anchors
boxes = decode_box_outputs(
box_outputs.swapaxes(0, 1), anchor_boxes.swapaxes(0, 1))
boxes = boxes[:, [1, 0, 3, 2]]
# run class-wise nms
detections = []
for c in range(num_classes):
indices = np.where(classes == c)[0]
if indices.shape[0] == 0:
continue
boxes_cls = boxes[indices, :]
scores_cls = scores[indices]
# Select top-scoring boxes in each class and apply non-maximum suppression
# (nms) for boxes in the same class. The selected boxes from each class are
# then concatenated for the final detection outputs.
all_detections_cls = np.column_stack((boxes_cls, scores_cls))
top_detection_idx = nms(all_detections_cls, 0.5)
top_detections_cls = all_detections_cls[top_detection_idx]
top_detections_cls[:, 2] -= top_detections_cls[:, 0]
top_detections_cls[:, 3] -= top_detections_cls[:, 1]
top_detections_cls = np.column_stack(
(np.repeat(image_id, len(top_detection_idx)),
top_detections_cls,
np.repeat(c + 1, len(top_detection_idx)))
)
detections.append(top_detections_cls)
def _generate_dummy_detections(number):
detections_dummy = np.zeros((number, 7), dtype=np.float32)
detections_dummy[:, 0] = image_id[0]
detections_dummy[:, 5] = _DUMMY_DETECTION_SCORE
return detections_dummy
if detections:
detections = np.vstack(detections)
# take final 100 detections
indices = np.argsort(-detections[:, -2])
detections = np.array(
detections[indices[0:max_boxes_to_draw]], dtype=np.float32)
# Add dummy detections to fill up to 100 detections
n = max(max_boxes_to_draw - len(detections), 0)
detections_dummy = _generate_dummy_detections(n)
detections = np.vstack([detections, detections_dummy])
else:
detections = _generate_dummy_detections(max_boxes_to_draw)
detections[:, 1:5] *= image_scale
return detections
class Anchors(object):
"""RetinaNet Anchors class."""
def __init__(self, min_level, max_level, num_scales, aspect_ratios,
anchor_scale, image_size):
"""Constructs multiscale RetinaNet anchors.
Args:
min_level: integer number of minimum level of the output feature pyramid.
max_level: integer number of maximum level of the output feature pyramid.
num_scales: integer number representing intermediate scales added
on each level. For instances, num_scales=2 adds two additional
anchor scales [2^0, 2^0.5] on each level.
aspect_ratios: list of tuples representing the aspect ratio anchors added
on each level. For instances, aspect_ratios =
[(1, 1), (1.4, 0.7), (0.7, 1.4)] adds three anchors on each level.
anchor_scale: float number representing the scale of size of the base
anchor to the feature stride 2^level.
image_size: integer number or tuple of integer number of input image size.
"""
self.min_level = min_level
self.max_level = max_level
self.num_scales = num_scales
self.aspect_ratios = aspect_ratios
self.anchor_scale = anchor_scale
if isinstance(image_size, int):
self.image_size = (image_size, image_size)
else:
self.image_size = image_size
self.feat_sizes = utils.get_feat_sizes(image_size, max_level)
self.config = self._generate_configs()
self.boxes = self._generate_boxes()
def _generate_configs(self):
"""Generate configurations of anchor boxes."""
return _generate_anchor_configs(self.feat_sizes, self.min_level,
self.max_level, self.num_scales,
self.aspect_ratios)
def _generate_boxes(self):
"""Generates multiscale anchor boxes."""
boxes = _generate_anchor_boxes(self.image_size, self.anchor_scale,
self.config)
boxes = tf.convert_to_tensor(boxes, dtype=tf.float32)
return boxes
def get_anchors_per_location(self):
return self.num_scales * len(self.aspect_ratios)
class AnchorLabeler(object):
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors.
Args:
anchors: an instance of class Anchors.
num_classes: integer number representing number of classes in the dataset.
match_threshold: float number between 0 and 1 representing the threshold
to assign positive labels for anchors.
"""
similarity_calc = region_similarity_calculator.IouSimilarity()
matcher = argmax_matcher.ArgMaxMatcher(
match_threshold,
unmatched_threshold=match_threshold,
negatives_lower_than_unmatched=True,
force_match_for_each_row=True)
box_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()
self._target_assigner = target_assigner.TargetAssigner(
similarity_calc, matcher, box_coder)
self._anchors = anchors
self._match_threshold = match_threshold
self._num_classes = num_classes
def _unpack_labels(self, labels):
"""Unpacks an array of labels into multiscales labels."""
labels_unpacked = collections.OrderedDict()
anchors = self._anchors
count = 0
for level in range(anchors.min_level, anchors.max_level + 1):
feat_size = anchors.feat_sizes[level]
steps = feat_size['height'] * feat_size[
'width'] * anchors.get_anchors_per_location()
indices = tf.range(count, count + steps)
count += steps
labels_unpacked[level] = tf.reshape(
tf.gather(labels, indices),
[feat_size['height'], feat_size['width'], -1])
return labels_unpacked
def label_anchors(self, gt_boxes, gt_labels):
"""Labels anchors with ground truth inputs.
Args:
gt_boxes: A float tensor with shape [N, 4] representing groundtruth boxes.
For each row, it stores [y0, x0, y1, x1] for four corners of a box.
gt_labels: A integer tensor with shape [N, 1] representing groundtruth
classes.
Returns:
cls_targets_dict: ordered dictionary with keys
[min_level, min_level+1, ..., max_level]. The values are tensor with
shape [height_l, width_l, num_anchors]. The height_l and width_l
represent the dimension of class logits at l-th level.
box_targets_dict: ordered dictionary with keys
[min_level, min_level+1, ..., max_level]. The values are tensor with
shape [height_l, width_l, num_anchors * 4]. The height_l and
width_l represent the dimension of bounding box regression output at
l-th level.
num_positives: scalar tensor storing number of positives in an image.
"""
gt_box_list = box_list.BoxList(gt_boxes)
anchor_box_list = box_list.BoxList(self._anchors.boxes)
# cls_weights, box_weights are not used
cls_targets, _, box_targets, _, matches = self._target_assigner.assign(
anchor_box_list, gt_box_list, gt_labels)
# class labels start from 1 and the background class = -1
cls_targets -= 1
cls_targets = tf.cast(cls_targets, tf.int32)
# Unpack labels.
cls_targets_dict = self._unpack_labels(cls_targets)
box_targets_dict = self._unpack_labels(box_targets)
num_positives = tf.reduce_sum(
tf.cast(tf.not_equal(matches.match_results, -1), tf.float32))
return cls_targets_dict, box_targets_dict, num_positives
def generate_detections(self,
cls_outputs,
box_outputs,
indices,
classes,
image_id,
image_scale,
min_score_thresh=MIN_SCORE_THRESH,
max_boxes_to_draw=MAX_DETECTIONS_PER_IMAGE,
disable_pyfun=None):
"""Generate detections based on class and box predictions."""
if disable_pyfun:
return _generate_detections_tf(
cls_outputs,
box_outputs,
self._anchors.boxes,
indices,
classes,
image_id,
image_scale,
min_score_thresh=min_score_thresh,
max_boxes_to_draw=max_boxes_to_draw)
else:
return tf.py_func(_generate_detections, [
cls_outputs, box_outputs, self._anchors.boxes, indices, classes,
image_id, image_scale, self._num_classes, max_boxes_to_draw,
], tf.float32)
| 38.318105 | 82 | 0.675307 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
from absl import logging
import numpy as np
import tensorflow.compat.v1 as tf
import utils
from object_detection import argmax_matcher
from object_detection import box_list
from object_detection import faster_rcnn_box_coder
from object_detection import region_similarity_calculator
from object_detection import target_assigner
MIN_CLASS_SCORE = -5.0
_DUMMY_DETECTION_SCORE = -1e5
MAX_DETECTION_POINTS = 5000
MAX_DETECTIONS_PER_IMAGE = 100
MIN_SCORE_THRESH = 0.4
def sigmoid(x):
return 1 / (1 + np.exp(-x))
def decode_box_outputs(rel_codes, anchors):
ycenter_a = (anchors[0] + anchors[2]) / 2
xcenter_a = (anchors[1] + anchors[3]) / 2
ha = anchors[2] - anchors[0]
wa = anchors[3] - anchors[1]
ty, tx, th, tw = rel_codes
w = np.exp(tw) * wa
h = np.exp(th) * ha
ycenter = ty * ha + ycenter_a
xcenter = tx * wa + xcenter_a
ymin = ycenter - h / 2.
xmin = xcenter - w / 2.
ymax = ycenter + h / 2.
xmax = xcenter + w / 2.
return np.column_stack([ymin, xmin, ymax, xmax])
def decode_box_outputs_tf(rel_codes, anchors):
ycenter_a = (anchors[0] + anchors[2]) / 2
xcenter_a = (anchors[1] + anchors[3]) / 2
ha = anchors[2] - anchors[0]
wa = anchors[3] - anchors[1]
ty, tx, th, tw = tf.unstack(rel_codes, num=4)
w = tf.math.exp(tw) * wa
h = tf.math.exp(th) * ha
ycenter = ty * ha + ycenter_a
xcenter = tx * wa + xcenter_a
ymin = ycenter - h / 2.
xmin = xcenter - w / 2.
ymax = ycenter + h / 2.
xmax = xcenter + w / 2.
return tf.stack([ymin, xmin, ymax, xmax], axis=1)
@tf.autograph.to_graph
def nms_tf(dets, thresh):
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
order = tf.argsort(scores, direction='DESCENDING')
keep = tf.TensorArray(tf.int32, size=0, dynamic_size=True)
index = 0
while tf.size(order) > 0:
i = order[0]
keep = keep.write(index, i)
xx1 = tf.maximum(x1[i], tf.gather(x1, order[1:]))
yy1 = tf.maximum(y1[i], tf.gather(y1, order[1:]))
xx2 = tf.minimum(x2[i], tf.gather(x2, order[1:]))
yy2 = tf.minimum(y2[i], tf.gather(y2, order[1:]))
w = tf.maximum(0.0, xx2 - xx1 + 1)
h = tf.maximum(0.0, yy2 - yy1 + 1)
intersection = w * h
overlap = intersection / (
areas[i] + tf.gather(areas, order[1:]) - intersection)
inds = tf.where_v2(overlap <= thresh)
order = tf.concat(tf.gather(order, inds + 1), axis=1)
order = tf.squeeze(order, axis=-1)
index += 1
return keep.stack()
def nms(dets, thresh):
x1 = dets[:, 0]
y1 = dets[:, 1]
x2 = dets[:, 2]
y2 = dets[:, 3]
scores = dets[:, 4]
areas = (x2 - x1 + 1) * (y2 - y1 + 1)
order = scores.argsort()[::-1]
keep = []
while order.size > 0:
i = order[0]
keep.append(i)
xx1 = np.maximum(x1[i], x1[order[1:]])
yy1 = np.maximum(y1[i], y1[order[1:]])
xx2 = np.minimum(x2[i], x2[order[1:]])
yy2 = np.minimum(y2[i], y2[order[1:]])
w = np.maximum(0.0, xx2 - xx1 + 1)
h = np.maximum(0.0, yy2 - yy1 + 1)
intersection = w * h
overlap = intersection / (areas[i] + areas[order[1:]] - intersection)
inds = np.where(overlap <= thresh)[0]
order = order[inds + 1]
return keep
def _generate_anchor_configs(feat_sizes, min_level, max_level, num_scales,
aspect_ratios):
anchor_configs = {}
for level in range(min_level, max_level + 1):
anchor_configs[level] = []
for scale_octave in range(num_scales):
for aspect in aspect_ratios:
anchor_configs[level].append(
((feat_sizes[0]['height'] / float(feat_sizes[level]['height']),
feat_sizes[0]['width'] / float(feat_sizes[level]['width'])),
scale_octave / float(num_scales), aspect))
return anchor_configs
def _generate_anchor_boxes(image_size, anchor_scale, anchor_configs):
boxes_all = []
for _, configs in anchor_configs.items():
boxes_level = []
for config in configs:
stride, octave_scale, aspect = config
base_anchor_size_x = anchor_scale * stride[1] * 2**octave_scale
base_anchor_size_y = anchor_scale * stride[0] * 2**octave_scale
anchor_size_x_2 = base_anchor_size_x * aspect[0] / 2.0
anchor_size_y_2 = base_anchor_size_y * aspect[1] / 2.0
x = np.arange(stride[1] / 2, image_size[1], stride[1])
y = np.arange(stride[0] / 2, image_size[0], stride[0])
xv, yv = np.meshgrid(x, y)
xv = xv.reshape(-1)
yv = yv.reshape(-1)
boxes = np.vstack((yv - anchor_size_y_2, xv - anchor_size_x_2,
yv + anchor_size_y_2, xv + anchor_size_x_2))
boxes = np.swapaxes(boxes, 0, 1)
boxes_level.append(np.expand_dims(boxes, axis=1))
boxes_level = np.concatenate(boxes_level, axis=1)
boxes_all.append(boxes_level.reshape([-1, 4]))
anchor_boxes = np.vstack(boxes_all)
return anchor_boxes
def _generate_detections_tf(cls_outputs,
box_outputs,
anchor_boxes,
indices,
classes,
image_id,
image_scale,
min_score_thresh=MIN_SCORE_THRESH,
max_boxes_to_draw=MAX_DETECTIONS_PER_IMAGE,
soft_nms_sigma=0.0,
iou_threshold=0.5,
use_native_nms=True):
logging.info('Using tf version of post-processing.')
anchor_boxes = tf.gather(anchor_boxes, indices)
scores = tf.math.sigmoid(cls_outputs)
boxes = decode_box_outputs_tf(
tf.transpose(box_outputs, [1, 0]), tf.transpose(anchor_boxes, [1, 0]))
if use_native_nms:
logging.info('Using native nms.')
top_detection_idx, scores = tf.image.non_max_suppression_with_scores(
boxes,
scores,
max_boxes_to_draw,
iou_threshold=iou_threshold,
score_threshold=min_score_thresh,
soft_nms_sigma=soft_nms_sigma)
boxes = tf.gather(boxes, top_detection_idx)
else:
logging.info('Using customized nms.')
scores = tf.expand_dims(scores, axis=1)
all_detections = tf.concat([boxes, scores], axis=1)
top_detection_idx = nms_tf(all_detections, iou_threshold)
detections = tf.gather(all_detections, top_detection_idx)
scores = detections[:, 4]
boxes = detections[:, :4]
height = boxes[:, 2] - boxes[:, 0]
width = boxes[:, 3] - boxes[:, 1]
detections = tf.stack([
tf.cast(tf.repeat(image_id, tf.size(top_detection_idx)), tf.float32),
boxes[:, 0] * image_scale,
boxes[:, 1] * image_scale,
height * image_scale,
width * image_scale,
scores,
tf.cast(tf.gather(classes, top_detection_idx) + 1, tf.float32)
], axis=1)
return detections
def _generate_detections(cls_outputs, box_outputs, anchor_boxes, indices,
classes, image_id, image_scale, num_classes,
max_boxes_to_draw):
logging.info('Using numpy version of post-processing.')
anchor_boxes = anchor_boxes[indices, :]
scores = sigmoid(cls_outputs)
boxes = decode_box_outputs(
box_outputs.swapaxes(0, 1), anchor_boxes.swapaxes(0, 1))
boxes = boxes[:, [1, 0, 3, 2]]
detections = []
for c in range(num_classes):
indices = np.where(classes == c)[0]
if indices.shape[0] == 0:
continue
boxes_cls = boxes[indices, :]
scores_cls = scores[indices]
all_detections_cls = np.column_stack((boxes_cls, scores_cls))
top_detection_idx = nms(all_detections_cls, 0.5)
top_detections_cls = all_detections_cls[top_detection_idx]
top_detections_cls[:, 2] -= top_detections_cls[:, 0]
top_detections_cls[:, 3] -= top_detections_cls[:, 1]
top_detections_cls = np.column_stack(
(np.repeat(image_id, len(top_detection_idx)),
top_detections_cls,
np.repeat(c + 1, len(top_detection_idx)))
)
detections.append(top_detections_cls)
def _generate_dummy_detections(number):
detections_dummy = np.zeros((number, 7), dtype=np.float32)
detections_dummy[:, 0] = image_id[0]
detections_dummy[:, 5] = _DUMMY_DETECTION_SCORE
return detections_dummy
if detections:
detections = np.vstack(detections)
indices = np.argsort(-detections[:, -2])
detections = np.array(
detections[indices[0:max_boxes_to_draw]], dtype=np.float32)
n = max(max_boxes_to_draw - len(detections), 0)
detections_dummy = _generate_dummy_detections(n)
detections = np.vstack([detections, detections_dummy])
else:
detections = _generate_dummy_detections(max_boxes_to_draw)
detections[:, 1:5] *= image_scale
return detections
class Anchors(object):
def __init__(self, min_level, max_level, num_scales, aspect_ratios,
anchor_scale, image_size):
self.min_level = min_level
self.max_level = max_level
self.num_scales = num_scales
self.aspect_ratios = aspect_ratios
self.anchor_scale = anchor_scale
if isinstance(image_size, int):
self.image_size = (image_size, image_size)
else:
self.image_size = image_size
self.feat_sizes = utils.get_feat_sizes(image_size, max_level)
self.config = self._generate_configs()
self.boxes = self._generate_boxes()
def _generate_configs(self):
return _generate_anchor_configs(self.feat_sizes, self.min_level,
self.max_level, self.num_scales,
self.aspect_ratios)
def _generate_boxes(self):
boxes = _generate_anchor_boxes(self.image_size, self.anchor_scale,
self.config)
boxes = tf.convert_to_tensor(boxes, dtype=tf.float32)
return boxes
def get_anchors_per_location(self):
return self.num_scales * len(self.aspect_ratios)
class AnchorLabeler(object):
def __init__(self, anchors, num_classes, match_threshold=0.5):
similarity_calc = region_similarity_calculator.IouSimilarity()
matcher = argmax_matcher.ArgMaxMatcher(
match_threshold,
unmatched_threshold=match_threshold,
negatives_lower_than_unmatched=True,
force_match_for_each_row=True)
box_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()
self._target_assigner = target_assigner.TargetAssigner(
similarity_calc, matcher, box_coder)
self._anchors = anchors
self._match_threshold = match_threshold
self._num_classes = num_classes
def _unpack_labels(self, labels):
labels_unpacked = collections.OrderedDict()
anchors = self._anchors
count = 0
for level in range(anchors.min_level, anchors.max_level + 1):
feat_size = anchors.feat_sizes[level]
steps = feat_size['height'] * feat_size[
'width'] * anchors.get_anchors_per_location()
indices = tf.range(count, count + steps)
count += steps
labels_unpacked[level] = tf.reshape(
tf.gather(labels, indices),
[feat_size['height'], feat_size['width'], -1])
return labels_unpacked
def label_anchors(self, gt_boxes, gt_labels):
gt_box_list = box_list.BoxList(gt_boxes)
anchor_box_list = box_list.BoxList(self._anchors.boxes)
cls_targets, _, box_targets, _, matches = self._target_assigner.assign(
anchor_box_list, gt_box_list, gt_labels)
cls_targets -= 1
cls_targets = tf.cast(cls_targets, tf.int32)
cls_targets_dict = self._unpack_labels(cls_targets)
box_targets_dict = self._unpack_labels(box_targets)
num_positives = tf.reduce_sum(
tf.cast(tf.not_equal(matches.match_results, -1), tf.float32))
return cls_targets_dict, box_targets_dict, num_positives
def generate_detections(self,
cls_outputs,
box_outputs,
indices,
classes,
image_id,
image_scale,
min_score_thresh=MIN_SCORE_THRESH,
max_boxes_to_draw=MAX_DETECTIONS_PER_IMAGE,
disable_pyfun=None):
if disable_pyfun:
return _generate_detections_tf(
cls_outputs,
box_outputs,
self._anchors.boxes,
indices,
classes,
image_id,
image_scale,
min_score_thresh=min_score_thresh,
max_boxes_to_draw=max_boxes_to_draw)
else:
return tf.py_func(_generate_detections, [
cls_outputs, box_outputs, self._anchors.boxes, indices, classes,
image_id, image_scale, self._num_classes, max_boxes_to_draw,
], tf.float32)
| true | true |
f7fe9f026c543b5570b877a9844e11b56cd87aa7 | 3,898 | py | Python | openGaussBase/testcase/GUC/WAL/Opengauss_Function_Guc_WAL_Case0052.py | opengauss-mirror/Yat | aef107a8304b94e5d99b4f1f36eb46755eb8919e | [
"MulanPSL-1.0"
] | null | null | null | openGaussBase/testcase/GUC/WAL/Opengauss_Function_Guc_WAL_Case0052.py | opengauss-mirror/Yat | aef107a8304b94e5d99b4f1f36eb46755eb8919e | [
"MulanPSL-1.0"
] | null | null | null | openGaussBase/testcase/GUC/WAL/Opengauss_Function_Guc_WAL_Case0052.py | opengauss-mirror/Yat | aef107a8304b94e5d99b4f1f36eb46755eb8919e | [
"MulanPSL-1.0"
] | null | null | null | """
Copyright (c) 2022 Huawei Technologies Co.,Ltd.
openGauss is licensed under Mulan PSL v2.
You can use this software according to the terms and conditions of the Mulan PSL v2.
You may obtain a copy of Mulan PSL v2 at:
http://license.coscl.org.cn/MulanPSL2
THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
See the Mulan PSL v2 for more details.
"""
"""
Case Type : GUC
Case Name : 修改enable_double_write为off，观察预期结果；
Description :
1、查询enable_double_write默认值；
show enable_double_write;
2、修改enable_double_write为off，重启使其生效，并校验其预期结果；
gs_guc set -D {cluster/dn1} -c "enable_double_write=off"
gs_om -t stop && gs_om -t start
show enable_double_write;
3、重启后做简单DML
4、恢复默认值；
Expect :
1、显示默认值；
2、参数修改成功，校验修改后系统参数值为off；
3、DML无报错
4、恢复默认值成功；
History :
"""
import unittest
from testcase.utils.CommonSH import CommonSH
from testcase.utils.Constant import Constant
from testcase.utils.Logger import Logger
logger = Logger()
COMMONSH = CommonSH('PrimaryDbUser')
class Guctestcase(unittest.TestCase):
def setUp(self):
logger.info("==Opengauss_Function_Guc_WAL_Case0052开始执行==")
self.constant = Constant()
is_started = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in is_started or "Normal" in is_started)
def test_guc_wal(self):
logger.info("查询enable_double_write 期望：默认值on")
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
logger.info(sql_cmd)
self.assertIn(self.constant.OPEN_STATUS_MSG[0], sql_cmd)
logger.info("方式一修改enable_double_write为off，"
"重启使其生效，期望：设置成功")
result = COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=off')
self.assertTrue(result)
logger.info("期望：重启后查询结果为off")
COMMONSH.restart_db_cluster()
status = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in status or "Normal" in status)
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
logger.info(sql_cmd)
self.assertIn(self.constant.CLOSE_STATUS_MSG[0], sql_cmd)
logger.info("创建表，期望：创建成功")
sql_cmd = COMMONSH.execut_db_sql("drop table if exists test;"
"create table test(x int);")
logger.info(sql_cmd)
self.assertNotIn(self.constant.SQL_WRONG_MSG[1], sql_cmd)
self.assertIn(self.constant.CREATE_TABLE_SUCCESS, sql_cmd)
logger.info("恢复默认值")
logger.info("删除表")
sql_cmd = COMMONSH.execut_db_sql("drop table test cascade;")
logger.info(sql_cmd)
self.assertIn(self.constant.DROP_TABLE_SUCCESS, sql_cmd)
result = COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=on')
self.assertTrue(result)
COMMONSH.restart_db_cluster()
result = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in result or "Normal" in result)
def tearDown(self):
logger.info("恢复默认值")
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
if "on" != sql_cmd.split("\n")[-2].strip():
COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=on')
COMMONSH.restart_db_cluster()
is_started = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in is_started or "Normal" in is_started)
logger.info("==Opengauss_Function_Guc_WAL_Case0052执行结束==")
| 37.480769 | 84 | 0.651873 |
import unittest
from testcase.utils.CommonSH import CommonSH
from testcase.utils.Constant import Constant
from testcase.utils.Logger import Logger
logger = Logger()
COMMONSH = CommonSH('PrimaryDbUser')
class Guctestcase(unittest.TestCase):
def setUp(self):
logger.info("==Opengauss_Function_Guc_WAL_Case0052开始执行==")
self.constant = Constant()
is_started = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in is_started or "Normal" in is_started)
def test_guc_wal(self):
logger.info("查询enable_double_write 期望：默认值on")
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
logger.info(sql_cmd)
self.assertIn(self.constant.OPEN_STATUS_MSG[0], sql_cmd)
logger.info("方式一修改enable_double_write为off，"
"重启使其生效，期望：设置成功")
result = COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=off')
self.assertTrue(result)
logger.info("期望：重启后查询结果为off")
COMMONSH.restart_db_cluster()
status = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in status or "Normal" in status)
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
logger.info(sql_cmd)
self.assertIn(self.constant.CLOSE_STATUS_MSG[0], sql_cmd)
logger.info("创建表，期望：创建成功")
sql_cmd = COMMONSH.execut_db_sql("drop table if exists test;"
"create table test(x int);")
logger.info(sql_cmd)
self.assertNotIn(self.constant.SQL_WRONG_MSG[1], sql_cmd)
self.assertIn(self.constant.CREATE_TABLE_SUCCESS, sql_cmd)
logger.info("恢复默认值")
logger.info("删除表")
sql_cmd = COMMONSH.execut_db_sql("drop table test cascade;")
logger.info(sql_cmd)
self.assertIn(self.constant.DROP_TABLE_SUCCESS, sql_cmd)
result = COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=on')
self.assertTrue(result)
COMMONSH.restart_db_cluster()
result = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in result or "Normal" in result)
def tearDown(self):
logger.info("恢复默认值")
sql_cmd = COMMONSH.execut_db_sql("show enable_double_write;")
if "on" != sql_cmd.split("\n")[-2].strip():
COMMONSH.execute_gsguc("set",
self.constant.GSGUC_SUCCESS_MSG,
'enable_double_write=on')
COMMONSH.restart_db_cluster()
is_started = COMMONSH.get_db_cluster_status()
self.assertTrue("Degraded" in is_started or "Normal" in is_started)
logger.info("==Opengauss_Function_Guc_WAL_Case0052执行结束==")
| true | true |
f7fe9f1fecdc08f89d9fc996cf962b5f9a2c49b5 | 8,623 | py | Python | sympy/physics/quantum/tests/test_cg.py | ovolve/sympy | 0a15782f20505673466b940454b33b8014a25c13 | [
"BSD-3-Clause"
] | 8 | 2019-05-29T09:38:30.000Z | 2021-01-20T03:36:59.000Z | sympy/physics/quantum/tests/test_cg.py | ovolve/sympy | 0a15782f20505673466b940454b33b8014a25c13 | [
"BSD-3-Clause"
] | 12 | 2021-03-09T03:01:16.000Z | 2022-03-11T23:59:36.000Z | sympy/physics/quantum/tests/test_cg.py | ovolve/sympy | 0a15782f20505673466b940454b33b8014a25c13 | [
"BSD-3-Clause"
] | 1 | 2018-10-22T09:17:11.000Z | 2018-10-22T09:17:11.000Z | from __future__ import division
from sympy import S, sqrt, Sum, symbols
from sympy.physics.quantum.cg import Wigner3j, Wigner6j, Wigner9j, CG, cg_simp
from sympy.functions.special.tensor_functions import KroneckerDelta
from sympy.utilities.pytest import slow
@slow
def test_cg_simp_add():
j, m1, m1p, m2, m2p = symbols('j m1 m1p m2 m2p')
# Test Varshalovich 8.7.1 Eq 1
a = CG(S(1)/2, S(1)/2, 0, 0, S(1)/2, S(1)/2)
b = CG(S(1)/2, -S(1)/2, 0, 0, S(1)/2, -S(1)/2)
c = CG(1, 1, 0, 0, 1, 1)
d = CG(1, 0, 0, 0, 1, 0)
e = CG(1, -1, 0, 0, 1, -1)
assert cg_simp(a + b) == 2
assert cg_simp(c + d + e) == 3
assert cg_simp(a + b + c + d + e) == 5
assert cg_simp(a + b + c) == 2 + c
assert cg_simp(2*a + b) == 2 + a
assert cg_simp(2*c + d + e) == 3 + c
assert cg_simp(5*a + 5*b) == 10
assert cg_simp(5*c + 5*d + 5*e) == 15
assert cg_simp(-a - b) == -2
assert cg_simp(-c - d - e) == -3
assert cg_simp(-6*a - 6*b) == -12
assert cg_simp(-4*c - 4*d - 4*e) == -12
a = CG(S(1)/2, S(1)/2, j, 0, S(1)/2, S(1)/2)
b = CG(S(1)/2, -S(1)/2, j, 0, S(1)/2, -S(1)/2)
c = CG(1, 1, j, 0, 1, 1)
d = CG(1, 0, j, 0, 1, 0)
e = CG(1, -1, j, 0, 1, -1)
assert cg_simp(a + b) == 2*KroneckerDelta(j, 0)
assert cg_simp(c + d + e) == 3*KroneckerDelta(j, 0)
assert cg_simp(a + b + c + d + e) == 5*KroneckerDelta(j, 0)
assert cg_simp(a + b + c) == 2*KroneckerDelta(j, 0) + c
assert cg_simp(2*a + b) == 2*KroneckerDelta(j, 0) + a
assert cg_simp(2*c + d + e) == 3*KroneckerDelta(j, 0) + c
assert cg_simp(5*a + 5*b) == 10*KroneckerDelta(j, 0)
assert cg_simp(5*c + 5*d + 5*e) == 15*KroneckerDelta(j, 0)
assert cg_simp(-a - b) == -2*KroneckerDelta(j, 0)
assert cg_simp(-c - d - e) == -3*KroneckerDelta(j, 0)
assert cg_simp(-6*a - 6*b) == -12*KroneckerDelta(j, 0)
assert cg_simp(-4*c - 4*d - 4*e) == -12*KroneckerDelta(j, 0)
# Test Varshalovich 8.7.1 Eq 2
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 0, 0)
b = CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 0, 0)
c = CG(1, 1, 1, -1, 0, 0)
d = CG(1, 0, 1, 0, 0, 0)
e = CG(1, -1, 1, 1, 0, 0)
assert cg_simp(a - b) == sqrt(2)
assert cg_simp(c - d + e) == sqrt(3)
assert cg_simp(a - b + c - d + e) == sqrt(2) + sqrt(3)
assert cg_simp(a - b + c) == sqrt(2) + c
assert cg_simp(2*a - b) == sqrt(2) + a
assert cg_simp(2*c - d + e) == sqrt(3) + c
assert cg_simp(5*a - 5*b) == 5*sqrt(2)
assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)
assert cg_simp(-a + b) == -sqrt(2)
assert cg_simp(-c + d - e) == -sqrt(3)
assert cg_simp(-6*a + 6*b) == -6*sqrt(2)
assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, j, 0)
b = CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, j, 0)
c = CG(1, 1, 1, -1, j, 0)
d = CG(1, 0, 1, 0, j, 0)
e = CG(1, -1, 1, 1, j, 0)
assert cg_simp(a - b) == sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(c - d + e) == sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(a - b + c - d + e) == sqrt(
2)*KroneckerDelta(j, 0) + sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(a - b + c) == sqrt(2)*KroneckerDelta(j, 0) + c
assert cg_simp(2*a - b) == sqrt(2)*KroneckerDelta(j, 0) + a
assert cg_simp(2*c - d + e) == sqrt(3)*KroneckerDelta(j, 0) + c
assert cg_simp(5*a - 5*b) == 5*sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(-a + b) == -sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(-c + d - e) == -sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(-6*a + 6*b) == -6*sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)*KroneckerDelta(j, 0)
# Test Varshalovich 8.7.2 Eq 9
# alpha=alphap,beta=betap case
# numerical
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 1, 0)**2
b = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 0, 0)**2
c = CG(1, 0, 1, 1, 1, 1)**2
d = CG(1, 0, 1, 1, 2, 1)**2
assert cg_simp(a + b) == 1
assert cg_simp(c + d) == 1
assert cg_simp(a + b + c + d) == 2
assert cg_simp(4*a + 4*b) == 4
assert cg_simp(4*c + 4*d) == 4
assert cg_simp(5*a + 3*b) == 3 + 2*a
assert cg_simp(5*c + 3*d) == 3 + 2*c
assert cg_simp(-a - b) == -1
assert cg_simp(-c - d) == -1
# symbolic
a = CG(S(1)/2, m1, S(1)/2, m2, 1, 1)**2
b = CG(S(1)/2, m1, S(1)/2, m2, 1, 0)**2
c = CG(S(1)/2, m1, S(1)/2, m2, 1, -1)**2
d = CG(S(1)/2, m1, S(1)/2, m2, 0, 0)**2
assert cg_simp(a + b + c + d) == 1
assert cg_simp(4*a + 4*b + 4*c + 4*d) == 4
assert cg_simp(3*a + 5*b + 3*c + 4*d) == 3 + 2*b + d
assert cg_simp(-a - b - c - d) == -1
a = CG(1, m1, 1, m2, 2, 2)**2
b = CG(1, m1, 1, m2, 2, 1)**2
c = CG(1, m1, 1, m2, 2, 0)**2
d = CG(1, m1, 1, m2, 2, -1)**2
e = CG(1, m1, 1, m2, 2, -2)**2
f = CG(1, m1, 1, m2, 1, 1)**2
g = CG(1, m1, 1, m2, 1, 0)**2
h = CG(1, m1, 1, m2, 1, -1)**2
i = CG(1, m1, 1, m2, 0, 0)**2
assert cg_simp(a + b + c + d + e + f + g + h + i) == 1
assert cg_simp(4*(a + b + c + d + e + f + g + h + i)) == 4
assert cg_simp(a + b + 2*c + d + 4*e + f + g + h + i) == 1 + c + 3*e
assert cg_simp(-a - b - c - d - e - f - g - h - i) == -1
# alpha!=alphap or beta!=betap case
# numerical
a = CG(S(1)/2, S(
1)/2, S(1)/2, -S(1)/2, 1, 0)*CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 1, 0)
b = CG(S(1)/2, S(
1)/2, S(1)/2, -S(1)/2, 0, 0)*CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 0, 0)
c = CG(1, 1, 1, 0, 2, 1)*CG(1, 0, 1, 1, 2, 1)
d = CG(1, 1, 1, 0, 1, 1)*CG(1, 0, 1, 1, 1, 1)
assert cg_simp(a + b) == 0
assert cg_simp(c + d) == 0
# symbolic
a = CG(S(1)/2, m1, S(1)/2, m2, 1, 1)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, 1)
b = CG(S(1)/2, m1, S(1)/2, m2, 1, 0)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, 0)
c = CG(S(1)/2, m1, S(1)/2, m2, 1, -1)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, -1)
d = CG(S(1)/2, m1, S(1)/2, m2, 0, 0)*CG(S(1)/2, m1p, S(1)/2, m2p, 0, 0)
assert cg_simp(a + b + c + d) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
a = CG(1, m1, 1, m2, 2, 2)*CG(1, m1p, 1, m2p, 2, 2)
b = CG(1, m1, 1, m2, 2, 1)*CG(1, m1p, 1, m2p, 2, 1)
c = CG(1, m1, 1, m2, 2, 0)*CG(1, m1p, 1, m2p, 2, 0)
d = CG(1, m1, 1, m2, 2, -1)*CG(1, m1p, 1, m2p, 2, -1)
e = CG(1, m1, 1, m2, 2, -2)*CG(1, m1p, 1, m2p, 2, -2)
f = CG(1, m1, 1, m2, 1, 1)*CG(1, m1p, 1, m2p, 1, 1)
g = CG(1, m1, 1, m2, 1, 0)*CG(1, m1p, 1, m2p, 1, 0)
h = CG(1, m1, 1, m2, 1, -1)*CG(1, m1p, 1, m2p, 1, -1)
i = CG(1, m1, 1, m2, 0, 0)*CG(1, m1p, 1, m2p, 0, 0)
assert cg_simp(
a + b + c + d + e + f + g + h + i) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
def test_cg_simp_sum():
x, a, b, c, cp, alpha, beta, gamma, gammap = symbols(
'x a b c cp alpha beta gamma gammap')
# Varshalovich 8.7.1 Eq 1
assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)
)) == x*(2*a + 1)*KroneckerDelta(b, 0)
assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)) + CG(1, 0, 1, 0, 1, 0)) == x*(2*a + 1)*KroneckerDelta(b, 0) + CG(1, 0, 1, 0, 1, 0)
assert cg_simp(2 * Sum(CG(1, alpha, 0, 0, 1, alpha), (alpha, -1, 1))) == 6
# Varshalovich 8.7.1 Eq 2
assert cg_simp(x*Sum((-1)**(a - alpha) * CG(a, alpha, a, -alpha, c,
0), (alpha, -a, a))) == x*sqrt(2*a + 1)*KroneckerDelta(c, 0)
assert cg_simp(3*Sum((-1)**(2 - alpha) * CG(
2, alpha, 2, -alpha, 0, 0), (alpha, -2, 2))) == 3*sqrt(5)
# Varshalovich 8.7.2 Eq 4
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)*KroneckerDelta(gamma, gammap)
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, c, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(gamma, gammap)
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gamma), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)
assert cg_simp(Sum(CG(
a, alpha, b, beta, c, gamma)**2, (alpha, -a, a), (beta, -b, b))) == 1
assert cg_simp(Sum(CG(2, alpha, 1, beta, 2, gamma)*CG(2, alpha, 1, beta, 2, gammap), (alpha, -2, 2), (beta, -1, 1))) == KroneckerDelta(gamma, gammap)
def test_doit():
assert Wigner3j(1/2, -1/2, 1/2, 1/2, 0, 0).doit() == -sqrt(2)/2
assert Wigner6j(1, 2, 3, 2, 1, 2).doit() == sqrt(21)/105
assert Wigner6j(3, 1, 2, 2, 2, 1).doit() == sqrt(21) / 105
assert Wigner9j(
2, 1, 1, S(3)/2, S(1)/2, 1, S(1)/2, S(1)/2, 0).doit() == sqrt(2)/12
assert CG(1/2, 1/2, 1/2, -1/2, 1, 0).doit() == sqrt(2)/2
| 48.44382 | 176 | 0.491824 | from __future__ import division
from sympy import S, sqrt, Sum, symbols
from sympy.physics.quantum.cg import Wigner3j, Wigner6j, Wigner9j, CG, cg_simp
from sympy.functions.special.tensor_functions import KroneckerDelta
from sympy.utilities.pytest import slow
@slow
def test_cg_simp_add():
j, m1, m1p, m2, m2p = symbols('j m1 m1p m2 m2p')
a = CG(S(1)/2, S(1)/2, 0, 0, S(1)/2, S(1)/2)
b = CG(S(1)/2, -S(1)/2, 0, 0, S(1)/2, -S(1)/2)
c = CG(1, 1, 0, 0, 1, 1)
d = CG(1, 0, 0, 0, 1, 0)
e = CG(1, -1, 0, 0, 1, -1)
assert cg_simp(a + b) == 2
assert cg_simp(c + d + e) == 3
assert cg_simp(a + b + c + d + e) == 5
assert cg_simp(a + b + c) == 2 + c
assert cg_simp(2*a + b) == 2 + a
assert cg_simp(2*c + d + e) == 3 + c
assert cg_simp(5*a + 5*b) == 10
assert cg_simp(5*c + 5*d + 5*e) == 15
assert cg_simp(-a - b) == -2
assert cg_simp(-c - d - e) == -3
assert cg_simp(-6*a - 6*b) == -12
assert cg_simp(-4*c - 4*d - 4*e) == -12
a = CG(S(1)/2, S(1)/2, j, 0, S(1)/2, S(1)/2)
b = CG(S(1)/2, -S(1)/2, j, 0, S(1)/2, -S(1)/2)
c = CG(1, 1, j, 0, 1, 1)
d = CG(1, 0, j, 0, 1, 0)
e = CG(1, -1, j, 0, 1, -1)
assert cg_simp(a + b) == 2*KroneckerDelta(j, 0)
assert cg_simp(c + d + e) == 3*KroneckerDelta(j, 0)
assert cg_simp(a + b + c + d + e) == 5*KroneckerDelta(j, 0)
assert cg_simp(a + b + c) == 2*KroneckerDelta(j, 0) + c
assert cg_simp(2*a + b) == 2*KroneckerDelta(j, 0) + a
assert cg_simp(2*c + d + e) == 3*KroneckerDelta(j, 0) + c
assert cg_simp(5*a + 5*b) == 10*KroneckerDelta(j, 0)
assert cg_simp(5*c + 5*d + 5*e) == 15*KroneckerDelta(j, 0)
assert cg_simp(-a - b) == -2*KroneckerDelta(j, 0)
assert cg_simp(-c - d - e) == -3*KroneckerDelta(j, 0)
assert cg_simp(-6*a - 6*b) == -12*KroneckerDelta(j, 0)
assert cg_simp(-4*c - 4*d - 4*e) == -12*KroneckerDelta(j, 0)
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 0, 0)
b = CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 0, 0)
c = CG(1, 1, 1, -1, 0, 0)
d = CG(1, 0, 1, 0, 0, 0)
e = CG(1, -1, 1, 1, 0, 0)
assert cg_simp(a - b) == sqrt(2)
assert cg_simp(c - d + e) == sqrt(3)
assert cg_simp(a - b + c - d + e) == sqrt(2) + sqrt(3)
assert cg_simp(a - b + c) == sqrt(2) + c
assert cg_simp(2*a - b) == sqrt(2) + a
assert cg_simp(2*c - d + e) == sqrt(3) + c
assert cg_simp(5*a - 5*b) == 5*sqrt(2)
assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)
assert cg_simp(-a + b) == -sqrt(2)
assert cg_simp(-c + d - e) == -sqrt(3)
assert cg_simp(-6*a + 6*b) == -6*sqrt(2)
assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, j, 0)
b = CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, j, 0)
c = CG(1, 1, 1, -1, j, 0)
d = CG(1, 0, 1, 0, j, 0)
e = CG(1, -1, 1, 1, j, 0)
assert cg_simp(a - b) == sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(c - d + e) == sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(a - b + c - d + e) == sqrt(
2)*KroneckerDelta(j, 0) + sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(a - b + c) == sqrt(2)*KroneckerDelta(j, 0) + c
assert cg_simp(2*a - b) == sqrt(2)*KroneckerDelta(j, 0) + a
assert cg_simp(2*c - d + e) == sqrt(3)*KroneckerDelta(j, 0) + c
assert cg_simp(5*a - 5*b) == 5*sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(5*c - 5*d + 5*e) == 5*sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(-a + b) == -sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(-c + d - e) == -sqrt(3)*KroneckerDelta(j, 0)
assert cg_simp(-6*a + 6*b) == -6*sqrt(2)*KroneckerDelta(j, 0)
assert cg_simp(-4*c + 4*d - 4*e) == -4*sqrt(3)*KroneckerDelta(j, 0)
a = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 1, 0)**2
b = CG(S(1)/2, S(1)/2, S(1)/2, -S(1)/2, 0, 0)**2
c = CG(1, 0, 1, 1, 1, 1)**2
d = CG(1, 0, 1, 1, 2, 1)**2
assert cg_simp(a + b) == 1
assert cg_simp(c + d) == 1
assert cg_simp(a + b + c + d) == 2
assert cg_simp(4*a + 4*b) == 4
assert cg_simp(4*c + 4*d) == 4
assert cg_simp(5*a + 3*b) == 3 + 2*a
assert cg_simp(5*c + 3*d) == 3 + 2*c
assert cg_simp(-a - b) == -1
assert cg_simp(-c - d) == -1
a = CG(S(1)/2, m1, S(1)/2, m2, 1, 1)**2
b = CG(S(1)/2, m1, S(1)/2, m2, 1, 0)**2
c = CG(S(1)/2, m1, S(1)/2, m2, 1, -1)**2
d = CG(S(1)/2, m1, S(1)/2, m2, 0, 0)**2
assert cg_simp(a + b + c + d) == 1
assert cg_simp(4*a + 4*b + 4*c + 4*d) == 4
assert cg_simp(3*a + 5*b + 3*c + 4*d) == 3 + 2*b + d
assert cg_simp(-a - b - c - d) == -1
a = CG(1, m1, 1, m2, 2, 2)**2
b = CG(1, m1, 1, m2, 2, 1)**2
c = CG(1, m1, 1, m2, 2, 0)**2
d = CG(1, m1, 1, m2, 2, -1)**2
e = CG(1, m1, 1, m2, 2, -2)**2
f = CG(1, m1, 1, m2, 1, 1)**2
g = CG(1, m1, 1, m2, 1, 0)**2
h = CG(1, m1, 1, m2, 1, -1)**2
i = CG(1, m1, 1, m2, 0, 0)**2
assert cg_simp(a + b + c + d + e + f + g + h + i) == 1
assert cg_simp(4*(a + b + c + d + e + f + g + h + i)) == 4
assert cg_simp(a + b + 2*c + d + 4*e + f + g + h + i) == 1 + c + 3*e
assert cg_simp(-a - b - c - d - e - f - g - h - i) == -1
a = CG(S(1)/2, S(
1)/2, S(1)/2, -S(1)/2, 1, 0)*CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 1, 0)
b = CG(S(1)/2, S(
1)/2, S(1)/2, -S(1)/2, 0, 0)*CG(S(1)/2, -S(1)/2, S(1)/2, S(1)/2, 0, 0)
c = CG(1, 1, 1, 0, 2, 1)*CG(1, 0, 1, 1, 2, 1)
d = CG(1, 1, 1, 0, 1, 1)*CG(1, 0, 1, 1, 1, 1)
assert cg_simp(a + b) == 0
assert cg_simp(c + d) == 0
a = CG(S(1)/2, m1, S(1)/2, m2, 1, 1)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, 1)
b = CG(S(1)/2, m1, S(1)/2, m2, 1, 0)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, 0)
c = CG(S(1)/2, m1, S(1)/2, m2, 1, -1)*CG(S(1)/2, m1p, S(1)/2, m2p, 1, -1)
d = CG(S(1)/2, m1, S(1)/2, m2, 0, 0)*CG(S(1)/2, m1p, S(1)/2, m2p, 0, 0)
assert cg_simp(a + b + c + d) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
a = CG(1, m1, 1, m2, 2, 2)*CG(1, m1p, 1, m2p, 2, 2)
b = CG(1, m1, 1, m2, 2, 1)*CG(1, m1p, 1, m2p, 2, 1)
c = CG(1, m1, 1, m2, 2, 0)*CG(1, m1p, 1, m2p, 2, 0)
d = CG(1, m1, 1, m2, 2, -1)*CG(1, m1p, 1, m2p, 2, -1)
e = CG(1, m1, 1, m2, 2, -2)*CG(1, m1p, 1, m2p, 2, -2)
f = CG(1, m1, 1, m2, 1, 1)*CG(1, m1p, 1, m2p, 1, 1)
g = CG(1, m1, 1, m2, 1, 0)*CG(1, m1p, 1, m2p, 1, 0)
h = CG(1, m1, 1, m2, 1, -1)*CG(1, m1p, 1, m2p, 1, -1)
i = CG(1, m1, 1, m2, 0, 0)*CG(1, m1p, 1, m2p, 0, 0)
assert cg_simp(
a + b + c + d + e + f + g + h + i) == KroneckerDelta(m1, m1p)*KroneckerDelta(m2, m2p)
def test_cg_simp_sum():
x, a, b, c, cp, alpha, beta, gamma, gammap = symbols(
'x a b c cp alpha beta gamma gammap')
assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)
)) == x*(2*a + 1)*KroneckerDelta(b, 0)
assert cg_simp(x * Sum(CG(a, alpha, b, 0, a, alpha), (alpha, -a, a)) + CG(1, 0, 1, 0, 1, 0)) == x*(2*a + 1)*KroneckerDelta(b, 0) + CG(1, 0, 1, 0, 1, 0)
assert cg_simp(2 * Sum(CG(1, alpha, 0, 0, 1, alpha), (alpha, -1, 1))) == 6
assert cg_simp(x*Sum((-1)**(a - alpha) * CG(a, alpha, a, -alpha, c,
0), (alpha, -a, a))) == x*sqrt(2*a + 1)*KroneckerDelta(c, 0)
assert cg_simp(3*Sum((-1)**(2 - alpha) * CG(
2, alpha, 2, -alpha, 0, 0), (alpha, -2, 2))) == 3*sqrt(5)
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)*KroneckerDelta(gamma, gammap)
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, c, gammap), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(gamma, gammap)
assert cg_simp(Sum(CG(a, alpha, b, beta, c, gamma)*CG(a, alpha, b, beta, cp, gamma), (alpha, -a, a), (beta, -b, b))) == KroneckerDelta(c, cp)
assert cg_simp(Sum(CG(
a, alpha, b, beta, c, gamma)**2, (alpha, -a, a), (beta, -b, b))) == 1
assert cg_simp(Sum(CG(2, alpha, 1, beta, 2, gamma)*CG(2, alpha, 1, beta, 2, gammap), (alpha, -2, 2), (beta, -1, 1))) == KroneckerDelta(gamma, gammap)
def test_doit():
assert Wigner3j(1/2, -1/2, 1/2, 1/2, 0, 0).doit() == -sqrt(2)/2
assert Wigner6j(1, 2, 3, 2, 1, 2).doit() == sqrt(21)/105
assert Wigner6j(3, 1, 2, 2, 2, 1).doit() == sqrt(21) / 105
assert Wigner9j(
2, 1, 1, S(3)/2, S(1)/2, 1, S(1)/2, S(1)/2, 0).doit() == sqrt(2)/12
assert CG(1/2, 1/2, 1/2, -1/2, 1, 0).doit() == sqrt(2)/2
| true | true |
f7fea1418f16facb361a8885f258c589f1582d5e | 710 | py | Python | tardis/default_settings/localisation.py | keithschulze/mytardis | 8ed3562574ce990d42bfe96133185a82c31c27d4 | [
"Apache-2.0"
] | null | null | null | tardis/default_settings/localisation.py | keithschulze/mytardis | 8ed3562574ce990d42bfe96133185a82c31c27d4 | [
"Apache-2.0"
] | null | null | null | tardis/default_settings/localisation.py | keithschulze/mytardis | 8ed3562574ce990d42bfe96133185a82c31c27d4 | [
"Apache-2.0"
] | null | null | null | USE_TZ = True
# Local time zone for this installation. Choices can be found here:
# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name
# although not all choices may be available on all operating systems.
# If running in a Windows environment this must be set to the same as your
# system time zone.
TIME_ZONE = 'Australia/Melbourne'
# Language code for this installation. All choices can be found here:
# http://www.i18nguy.com/unicode/language-identifiers.html
LANGUAGE_CODE = 'en-us'
# Date format to use by default. ("jS F Y" => "8th March 2012")
# https://docs.djangoproject.com/en/1.3/ref/templates/builtins/#std:templatefilter-date # noqa
DATE_FORMAT = "jS F Y"
DATETIME_FORMAT = "jS F Y H:i"
| 33.809524 | 95 | 0.750704 | USE_TZ = True
TIME_ZONE = 'Australia/Melbourne'
LANGUAGE_CODE = 'en-us'
AT = "jS F Y H:i"
| true | true |
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