fumiyau/python_comments_free_500000 · Datasets at Hugging Face

f738cf24af7138d988dffecb2ef44f559fc23734

925

py

Python

password-generator.py

AkashSDas/Mini-Projects

908cea6df6ef6c62abdfe05585634b786e60b812

[ "MIT" ]

null

password-generator.py

AkashSDas/Mini-Projects

908cea6df6ef6c62abdfe05585634b786e60b812

[ "MIT" ]

null

password-generator.py

AkashSDas/Mini-Projects

908cea6df6ef6c62abdfe05585634b786e60b812

[ "MIT" ]

null

import random import string # Generating characters for password def generate_password_characters(): alphabets = string.ascii_letters alphabets = [alphabet for alphabet in alphabets] numbers = string.digits numbers = [number for number in numbers] special_characters = string.punctuation special_characters = [ special_character for special_character in special_characters] return [alphabets, numbers, special_characters] # Creating a 15 character random password def password_generator(): characters = generate_password_characters() password = [] for _ in range(15): character_list = characters[random.randint(0, len(characters)-1)] password_character = character_list[random.randint( 0, len(character_list)-1)] password.append(password_character) password = "".join(password) return password print(password_generator())

25.694444

73

0.726486

import random import string def generate_password_characters(): alphabets = string.ascii_letters alphabets = [alphabet for alphabet in alphabets] numbers = string.digits numbers = [number for number in numbers] special_characters = string.punctuation special_characters = [ special_character for special_character in special_characters] return [alphabets, numbers, special_characters] def password_generator(): characters = generate_password_characters() password = [] for _ in range(15): character_list = characters[random.randint(0, len(characters)-1)] password_character = character_list[random.randint( 0, len(character_list)-1)] password.append(password_character) password = "".join(password) return password print(password_generator())

true

f738cf63d0defe7800ee62d77cb5f24a10290e99

2,560

py

Python

test/functional/ncc_state_root.py

nccproject/ncc

068ccc82a73d28136546095261ad8ccef7e541a3

[ "MIT" ]

null

test/functional/ncc_state_root.py

nccproject/ncc

068ccc82a73d28136546095261ad8ccef7e541a3

[ "MIT" ]

null

test/functional/ncc_state_root.py

nccproject/ncc

068ccc82a73d28136546095261ad8ccef7e541a3

[ "MIT" ]

null

#!/usr/bin/env python3 # Copyright (c) 2015-2016 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. from test_framework.test_framework import BitcoinTestFramework from test_framework.util import * from test_framework.script import * from test_framework.mininode import * from test_framework.messages import COIN from test_framework.nccconfig import * import sys class StateRootTest(BitcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 1 def skip_test_if_missing_module(self): self.skip_if_no_wallet() # verify that the state hash is not 0 on genesis def verify_not_null_test(self): block_hash = self.node.getblockhash(0) block = self.node.getblock(block_hash) assert(int(block['hashStateRoot'], 16) != 0) # verify that the state hash changes on contract creation def verify_state_hash_changes(self): amount = 20000*COIN self.node.generate(COINBASE_MATURITY+50) block_hash_a = self.node.getblockhash(COINBASE_MATURITY+50) block_a = self.node.getblock(block_hash_a) """ pragma solidity ^0.4.10; contract Example { function () payable {} } """ self.node.createcontract("60606040523415600b57fe5b5b60398060196000396000f30060606040525b600b5b5b565b0000a165627a7a7230582092926a9814888ff08700cbd86cf4ff8c50052f5fd894e794570d9551733591d60029") self.node.generate(1) block_hash_b = self.node.getblockhash(COINBASE_MATURITY+51) block_b = self.node.getblock(block_hash_b) assert(block_a['hashStateRoot'] != block_b['hashStateRoot']) # verify that the state hash remains the same on restart def verify_state_hash_remains_on_restart(self): block_hash_a = self.node.getblockhash(COINBASE_MATURITY+51) block_a = self.node.getblock(block_hash_a) self.stop_nodes() self.start_nodes() self.node = self.nodes[0] self.node.generate(1) block_hash_b = self.node.getblockhash(COINBASE_MATURITY+52) block_b = self.node.getblock(block_hash_b) assert(block_a['hashStateRoot'] == block_b['hashStateRoot']) def run_test(self): self.node = self.nodes[0] self.verify_not_null_test() self.verify_state_hash_changes() self.verify_state_hash_remains_on_restart() if __name__ == '__main__': StateRootTest().main()

38.787879

200

0.715625

from test_framework.test_framework import BitcoinTestFramework from test_framework.util import * from test_framework.script import * from test_framework.mininode import * from test_framework.messages import COIN from test_framework.nccconfig import * import sys class StateRootTest(BitcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 1 def skip_test_if_missing_module(self): self.skip_if_no_wallet() def verify_not_null_test(self): block_hash = self.node.getblockhash(0) block = self.node.getblock(block_hash) assert(int(block['hashStateRoot'], 16) != 0) def verify_state_hash_changes(self): amount = 20000*COIN self.node.generate(COINBASE_MATURITY+50) block_hash_a = self.node.getblockhash(COINBASE_MATURITY+50) block_a = self.node.getblock(block_hash_a) self.node.createcontract("60606040523415600b57fe5b5b60398060196000396000f30060606040525b600b5b5b565b0000a165627a7a7230582092926a9814888ff08700cbd86cf4ff8c50052f5fd894e794570d9551733591d60029") self.node.generate(1) block_hash_b = self.node.getblockhash(COINBASE_MATURITY+51) block_b = self.node.getblock(block_hash_b) assert(block_a['hashStateRoot'] != block_b['hashStateRoot']) def verify_state_hash_remains_on_restart(self): block_hash_a = self.node.getblockhash(COINBASE_MATURITY+51) block_a = self.node.getblock(block_hash_a) self.stop_nodes() self.start_nodes() self.node = self.nodes[0] self.node.generate(1) block_hash_b = self.node.getblockhash(COINBASE_MATURITY+52) block_b = self.node.getblock(block_hash_b) assert(block_a['hashStateRoot'] == block_b['hashStateRoot']) def run_test(self): self.node = self.nodes[0] self.verify_not_null_test() self.verify_state_hash_changes() self.verify_state_hash_remains_on_restart() if __name__ == '__main__': StateRootTest().main()

true

f738cf941c2a8ecc9a7e38fe3c49971fe26c72c6

65,550

py

Python

glance_store/tests/unit/test_swift_store.py

redhat-openstack/glance_store

c816b38d9f12be75d989409cbab6dfefa8f49dc3

[ "Apache-2.0" ]

null

glance_store/tests/unit/test_swift_store.py

redhat-openstack/glance_store

c816b38d9f12be75d989409cbab6dfefa8f49dc3

[ "Apache-2.0" ]

null

glance_store/tests/unit/test_swift_store.py

redhat-openstack/glance_store

c816b38d9f12be75d989409cbab6dfefa8f49dc3

[ "Apache-2.0" ]

null

# Copyright 2011 OpenStack Foundation # 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. """Tests the Swift backend store""" import copy import fixtures import hashlib import mock import tempfile import uuid from oslo_config import cfg from oslo_utils import units from oslotest import moxstubout import requests_mock import six from six import moves from six.moves import http_client # NOTE(jokke): simplified transition to py3, behaves like py2 xrange from six.moves import range import swiftclient from glance_store._drivers.swift import store as swift from glance_store import backend from glance_store import BackendException from glance_store import capabilities from glance_store.common import auth from glance_store.common import utils from glance_store import exceptions from glance_store import location from glance_store.tests import base from glance_store.tests.unit import test_store_capabilities CONF = cfg.CONF FAKE_UUID = lambda: str(uuid.uuid4()) FAKE_UUID2 = lambda: str(uuid.uuid4()) Store = swift.Store FIVE_KB = 5 * units.Ki FIVE_GB = 5 * units.Gi MAX_SWIFT_OBJECT_SIZE = FIVE_GB SWIFT_PUT_OBJECT_CALLS = 0 SWIFT_CONF = {'swift_store_auth_address': 'localhost:8080', 'swift_store_container': 'glance', 'swift_store_user': 'user', 'swift_store_key': 'key', 'swift_store_auth_address': 'localhost:8080', 'swift_store_container': 'glance', 'swift_store_retry_get_count': 1, 'default_swift_reference': 'ref1' } # We stub out as little as possible to ensure that the code paths # between swift and swiftclient are tested # thoroughly def stub_out_swiftclient(stubs, swift_store_auth_version): fixture_containers = ['glance'] fixture_container_headers = {} fixture_headers = { 'glance/%s' % FAKE_UUID: { 'content-length': FIVE_KB, 'etag': 'c2e5db72bd7fd153f53ede5da5a06de3' }, 'glance/%s' % FAKE_UUID2: {'x-static-large-object': 'true', }, } fixture_objects = {'glance/%s' % FAKE_UUID: six.BytesIO(b"*" * FIVE_KB), 'glance/%s' % FAKE_UUID2: six.BytesIO(b"*" * FIVE_KB), } def fake_head_container(url, token, container, **kwargs): if container not in fixture_containers: msg = "No container %s found" % container status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) return fixture_container_headers def fake_put_container(url, token, container, **kwargs): fixture_containers.append(container) def fake_post_container(url, token, container, headers, http_conn=None): for key, value in six.iteritems(headers): fixture_container_headers[key] = value def fake_put_object(url, token, container, name, contents, **kwargs): # PUT returns the ETag header for the newly-added object # Large object manifest... global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS += 1 CHUNKSIZE = 64 * units.Ki fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: if kwargs.get('headers'): etag = kwargs['headers']['ETag'] manifest = kwargs.get('headers').get('X-Object-Manifest') fixture_headers[fixture_key] = {'manifest': True, 'etag': etag, 'x-object-manifest': manifest} fixture_objects[fixture_key] = None return etag if hasattr(contents, 'read'): fixture_object = six.BytesIO() read_len = 0 chunk = contents.read(CHUNKSIZE) checksum = hashlib.md5() while chunk: fixture_object.write(chunk) read_len += len(chunk) checksum.update(chunk) chunk = contents.read(CHUNKSIZE) etag = checksum.hexdigest() else: fixture_object = six.BytesIO(contents) read_len = len(contents) etag = hashlib.md5(fixture_object.getvalue()).hexdigest() if read_len > MAX_SWIFT_OBJECT_SIZE: msg = ('Image size:%d exceeds Swift max:%d' % (read_len, MAX_SWIFT_OBJECT_SIZE)) raise swiftclient.ClientException( msg, http_status=http_client.REQUEST_ENTITY_TOO_LARGE) fixture_objects[fixture_key] = fixture_object fixture_headers[fixture_key] = { 'content-length': read_len, 'etag': etag} return etag else: msg = ("Object PUT failed - Object with key %s already exists" % fixture_key) raise swiftclient.ClientException(msg, http_status=http_client.CONFLICT) def fake_get_object(url, token, container, name, **kwargs): # GET returns the tuple (list of headers, file object) fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: msg = "Object GET failed" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) byte_range = None headers = kwargs.get('headers', dict()) if headers is not None: headers = dict((k.lower(), v) for k, v in six.iteritems(headers)) if 'range' in headers: byte_range = headers.get('range') fixture = fixture_headers[fixture_key] if 'manifest' in fixture: # Large object manifest... we return a file containing # all objects with prefix of this fixture key chunk_keys = sorted([k for k in fixture_headers.keys() if k.startswith(fixture_key) and k != fixture_key]) result = six.BytesIO() for key in chunk_keys: result.write(fixture_objects[key].getvalue()) else: result = fixture_objects[fixture_key] if byte_range is not None: start = int(byte_range.split('=')[1].strip('-')) result = six.BytesIO(result.getvalue()[start:]) fixture_headers[fixture_key]['content-length'] = len( result.getvalue()) return fixture_headers[fixture_key], result def fake_head_object(url, token, container, name, **kwargs): # HEAD returns the list of headers for an object try: fixture_key = "%s/%s" % (container, name) return fixture_headers[fixture_key] except KeyError: msg = "Object HEAD failed - Object does not exist" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) def fake_delete_object(url, token, container, name, **kwargs): # DELETE returns nothing fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: msg = "Object DELETE failed - Object does not exist" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) else: del fixture_headers[fixture_key] del fixture_objects[fixture_key] def fake_http_connection(*args, **kwargs): return None def fake_get_auth(url, user, key, auth_version, **kwargs): if url is None: return None, None if 'http' in url and '://' not in url: raise ValueError('Invalid url %s' % url) # Check the auth version against the configured value if swift_store_auth_version != auth_version: msg = 'AUTHENTICATION failed (version mismatch)' raise swiftclient.ClientException(msg) return None, None stubs.Set(swiftclient.client, 'head_container', fake_head_container) stubs.Set(swiftclient.client, 'put_container', fake_put_container) stubs.Set(swiftclient.client, 'post_container', fake_post_container) stubs.Set(swiftclient.client, 'put_object', fake_put_object) stubs.Set(swiftclient.client, 'delete_object', fake_delete_object) stubs.Set(swiftclient.client, 'head_object', fake_head_object) stubs.Set(swiftclient.client, 'get_object', fake_get_object) stubs.Set(swiftclient.client, 'get_auth', fake_get_auth) stubs.Set(swiftclient.client, 'http_connection', fake_http_connection) class SwiftTests(object): @property def swift_store_user(self): return 'tenant:user1' def test_get_size(self): """ Test that we can get the size of an object in the swift store """ uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) image_size = self.store.get_size(loc) self.assertEqual(image_size, 5120) def test_get_size_with_multi_tenant_on(self): """Test that single tenant uris work with multi tenant on.""" uri = ("swift://%s:key@auth_address/glance/%s" % (self.swift_store_user, FAKE_UUID)) self.config(swift_store_multi_tenant=True) # NOTE(markwash): ensure the image is found ctxt = mock.MagicMock() size = backend.get_size_from_backend(uri, context=ctxt) self.assertEqual(size, 5120) def test_get(self): """Test a "normal" retrieval of an image in chunks.""" uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) (image_swift, image_size) = self.store.get(loc) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_with_retry(self): """ Test a retrieval where Swift does not get the full image in a single request. """ uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) ctxt = mock.MagicMock() (image_swift, image_size) = self.store.get(loc, context=ctxt) resp_full = b''.join([chunk for chunk in image_swift.wrapped]) resp_half = resp_full[:len(resp_full) // 2] resp_half = six.BytesIO(resp_half) image_swift.wrapped = swift.swift_retry_iter(resp_half, image_size, self.store, loc.store_location, ctxt) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_with_http_auth(self): """ Test a retrieval from Swift with an HTTP authurl. This is specified either via a Location header with swift+http:// or using http:// in the swift_store_auth_address config value """ loc = location.get_location_from_uri( "swift+http://%s:key@auth_address/glance/%s" % (self.swift_store_user, FAKE_UUID), conf=self.conf) ctxt = mock.MagicMock() (image_swift, image_size) = self.store.get(loc, context=ctxt) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_non_existing(self): """ Test that trying to retrieve a swift that doesn't exist raises an error """ loc = location.get_location_from_uri( "swift://%s:key@authurl/glance/noexist" % (self.swift_store_user), conf=self.conf) self.assertRaises(exceptions.NotFound, self.store.get, loc) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=False)) def test_add(self): """Test that we can add an image via the swift backend.""" moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = "swift+https://tenant%%3Auser1:key@localhost:8080/glance/%s" expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) # Expecting a single object to be created on Swift i.e. no chunking. self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_multi_store(self): conf = copy.deepcopy(SWIFT_CONF) conf['default_swift_reference'] = 'store_2' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_image_id = str(uuid.uuid4()) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 loc = 'swift+config://store_2/glance/%s' expected_location = loc % (expected_image_id) location, size, checksum, arg = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, location) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_auth_url_variations(self): """ Test that we can add an image via the swift backend with a variety of different auth_address values """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) variations = { 'store_4': 'swift+config://store_4/glance/%s', 'store_5': 'swift+config://store_5/glance/%s', 'store_6': 'swift+config://store_6/glance/%s' } for variation, expected_location in variations.items(): image_id = str(uuid.uuid4()) expected_location = expected_location % image_id expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = \ hashlib.md5(expected_swift_contents).hexdigest() image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf['default_swift_reference'] = variation self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_no_container_no_create(self): """ Tests that adding an image with a non-existing container raises an appropriate exception """ conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = False conf['swift_store_container'] = 'noexist' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 # We check the exception text to ensure the container # missing text is found in it, otherwise, we would have # simply used self.assertRaises here exception_caught = False try: self.store.add(str(uuid.uuid4()), image_swift, 0) except BackendException as e: exception_caught = True self.assertIn("container noexist does not exist " "in Swift", utils.exception_to_str(e)) self.assertTrue(exception_caught) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 0) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_create(self): """ Tests that adding an image with a non-existing container creates the container automatically if flag is set """ expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/noexist/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = True conf['swift_store_container'] = 'noexist' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_multiple_containers_create(self): """ Tests that adding an image with a non-existing container while using multi containers will create the container automatically if flag is set """ expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) container = 'randomname_' + expected_image_id[:2] loc = 'swift+config://ref1/%s/%s' expected_location = loc % (container, expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = True conf['swift_store_container'] = 'randomname' conf['swift_store_multiple_containers_seed'] = 2 self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_multiple_containers_no_create(self): """ Tests that adding an image with a non-existing container while using multiple containers raises an appropriate exception """ conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = False conf['swift_store_container'] = 'randomname' conf['swift_store_multiple_containers_seed'] = 2 self.config(**conf) moves.reload_module(swift) expected_image_id = str(uuid.uuid4()) expected_container = 'randomname_' + expected_image_id[:2] self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 # We check the exception text to ensure the container # missing text is found in it, otherwise, we would have # simply used self.assertRaises here exception_caught = False try: self.store.add(expected_image_id, image_swift, 0) except BackendException as e: exception_caught = True expected_msg = "container %s does not exist in Swift" expected_msg = expected_msg % expected_container self.assertIn(expected_msg, utils.exception_to_str(e)) self.assertTrue(exception_caught) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 0) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=False)) def test_multi_container_doesnt_impact_multi_tenant_add(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_image_id = str(uuid.uuid4()) expected_container = 'container_' + expected_image_id loc = 'swift+https://some_endpoint/%s/%s' expected_location = loc % (expected_container, expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 self.config(swift_store_container='container') self.config(swift_store_create_container_on_put=True) self.config(swift_store_multiple_containers_seed=2) fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location, size, checksum, _ = store.add(expected_image_id, image_swift, expected_swift_size, context=ctxt) self.assertEqual(expected_location, location) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_large_object(self): """ Tests that adding a very large image. We simulate the large object by setting store.large_object_size to a small number and then verify that there have been a number of calls to put_object()... """ expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/glance/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 self.store = Store(self.conf) self.store.configure() orig_max_size = self.store.large_object_size orig_temp_size = self.store.large_object_chunk_size try: self.store.large_object_size = units.Ki self.store.large_object_chunk_size = units.Ki loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) finally: self.store.large_object_chunk_size = orig_temp_size self.store.large_object_size = orig_max_size self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) # Expecting 6 objects to be created on Swift -- 5 chunks and 1 # manifest. self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 6) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_contents) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_large_object_zero_size(self): """ Tests that adding an image to Swift which has both an unknown size and exceeds Swift's maximum limit of 5GB is correctly uploaded. We avoid the overhead of creating a 5GB object for this test by temporarily setting MAX_SWIFT_OBJECT_SIZE to 1KB, and then adding an object of 5KB. Bug lp:891738 """ # Set up a 'large' image of 5KB expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/glance/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 # Temporarily set Swift MAX_SWIFT_OBJECT_SIZE to 1KB and add our image, # explicitly setting the image_length to 0 self.store = Store(self.conf) self.store.configure() orig_max_size = self.store.large_object_size orig_temp_size = self.store.large_object_chunk_size global MAX_SWIFT_OBJECT_SIZE orig_max_swift_object_size = MAX_SWIFT_OBJECT_SIZE try: MAX_SWIFT_OBJECT_SIZE = units.Ki self.store.large_object_size = units.Ki self.store.large_object_chunk_size = units.Ki loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, 0) finally: self.store.large_object_chunk_size = orig_temp_size self.store.large_object_size = orig_max_size MAX_SWIFT_OBJECT_SIZE = orig_max_swift_object_size self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) # Expecting 7 calls to put_object -- 5 chunks, a zero chunk which is # then deleted, and the manifest. Note the difference with above # where the image_size is specified in advance (there's no zero chunk # in that case). self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 7) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_contents) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_already_existing(self): """ Tests that adding an image with an existing identifier raises an appropriate exception """ self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") self.assertRaises(exceptions.Duplicate, self.store.add, FAKE_UUID, image_swift, 0) def _option_required(self, key): conf = self.getConfig() conf[key] = None try: self.config(**conf) self.store = Store(self.conf) return not self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS) except Exception: return False return False def test_no_store_credentials(self): """ Tests that options without a valid credentials disables the add method """ self.store = Store(self.conf) self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'user': '', 'key': ''}} self.store.configure() self.assertFalse(self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS)) def test_no_auth_address(self): """ Tests that options without auth address disables the add method """ self.store = Store(self.conf) self.store.ref_params = {'ref1': {'auth_address': '', 'user': 'user1', 'key': 'key1'}} self.store.configure() self.assertFalse(self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS)) def test_delete(self): """ Test we can delete an existing image in the swift store """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertRaises(exceptions.NotFound, self.store.get, loc) @mock.patch.object(swiftclient.client, 'delete_object') def test_delete_slo(self, mock_del_obj): """ Test we can delete an existing image stored as SLO, static large object """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % (self.swift_store_user, FAKE_UUID2) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertEqual(1, mock_del_obj.call_count) _, kwargs = mock_del_obj.call_args self.assertEqual('multipart-manifest=delete', kwargs.get('query_string')) @mock.patch.object(swiftclient.client, 'delete_object') def test_delete_nonslo_not_deleted_as_slo(self, mock_del_obj): """ Test that non-SLOs are not being deleted the SLO way """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % (self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertEqual(1, mock_del_obj.call_count) _, kwargs = mock_del_obj.call_args self.assertEqual(None, kwargs.get('query_string')) def test_delete_with_reference_params(self): """ Test we can delete an existing image in the swift store """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift+config://ref1/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertRaises(exceptions.NotFound, self.store.get, loc) def test_delete_non_existing(self): """ Test that trying to delete a swift that doesn't exist raises an error """ conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc = location.get_location_from_uri( "swift://%s:key@authurl/glance/noexist" % (self.swift_store_user), conf=self.conf) self.assertRaises(exceptions.NotFound, self.store.delete, loc) def test_delete_with_some_segments_failing(self): """ Tests that delete of a segmented object recovers from error(s) while deleting one or more segments. To test this we add a segmented object first and then delete it, while simulating errors on one or more segments. """ test_image_id = str(uuid.uuid4()) def fake_head_object(container, object_name): object_manifest = '/'.join([container, object_name]) + '-' return {'x-object-manifest': object_manifest} def fake_get_container(container, **kwargs): # Returning 5 fake segments return None, [{'name': '%s-%03d' % (test_image_id, x)} for x in range(1, 6)] def fake_delete_object(container, object_name): # Simulate error on 1st and 3rd segments global SWIFT_DELETE_OBJECT_CALLS SWIFT_DELETE_OBJECT_CALLS += 1 if object_name.endswith('-001') or object_name.endswith('-003'): raise swiftclient.ClientException('Object DELETE failed') else: pass conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc_uri = "swift+https://%s:key@localhost:8080/glance/%s" loc_uri = loc_uri % (self.swift_store_user, test_image_id) loc = location.get_location_from_uri(loc_uri) conn = self.store.get_connection(loc.store_location) conn.delete_object = fake_delete_object conn.head_object = fake_head_object conn.get_container = fake_get_container global SWIFT_DELETE_OBJECT_CALLS SWIFT_DELETE_OBJECT_CALLS = 0 self.store.delete(loc, connection=conn) # Expecting 6 delete calls, 5 for the segments and 1 for the manifest self.assertEqual(SWIFT_DELETE_OBJECT_CALLS, 6) def test_read_acl_public(self): """ Test that we can set a public read acl. """ self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) ctxt = mock.MagicMock() store.set_acls(loc, public=True, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Read'], "*:*") def test_read_acl_tenants(self): """ Test that we can set read acl for tenants. """ self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) read_tenants = ['matt', 'mark'] ctxt = mock.MagicMock() store.set_acls(loc, read_tenants=read_tenants, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Read'], 'matt:*,mark:*') def test_write_acls(self): """ Test that we can set write acl for tenants. """ self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) read_tenants = ['frank', 'jim'] ctxt = mock.MagicMock() store.set_acls(loc, write_tenants=read_tenants, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Write'], 'frank:*,jim:*') class TestStoreAuthV1(base.StoreBaseTest, SwiftTests, test_store_capabilities.TestStoreCapabilitiesChecking): _CONF = cfg.CONF def getConfig(self): conf = SWIFT_CONF.copy() conf['swift_store_auth_version'] = '1' conf['swift_store_user'] = 'tenant:user1' return conf def setUp(self): """Establish a clean test environment.""" super(TestStoreAuthV1, self).setUp() conf = self.getConfig() conf_file = 'glance-swift.conf' self.swift_config_file = self.copy_data_file(conf_file, self.test_dir) conf.update({'swift_store_config_file': self.swift_config_file}) moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs stub_out_swiftclient(self.stubs, conf['swift_store_auth_version']) self.store = Store(self.conf) self.config(**conf) self.store.configure() self.register_store_schemes(self.store, 'swift') self.addCleanup(self.conf.reset) class TestStoreAuthV2(TestStoreAuthV1): def getConfig(self): conf = super(TestStoreAuthV2, self).getConfig() conf['swift_store_auth_version'] = '2' conf['swift_store_user'] = 'tenant:user1' return conf def test_v2_with_no_tenant(self): uri = "swift://failme:key@auth_address/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.assertRaises(exceptions.BadStoreUri, self.store.get, loc) def test_v2_multi_tenant_location(self): conf = self.getConfig() conf['swift_store_multi_tenant'] = True uri = "swift://auth_address/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.assertEqual('swift', loc.store_name) class TestStoreAuthV3(TestStoreAuthV1): def getConfig(self): conf = super(TestStoreAuthV3, self).getConfig() conf['swift_store_auth_version'] = '3' conf['swift_store_user'] = 'tenant:user1' return conf class FakeConnection(object): def __init__(self, authurl, user, key, retries=5, preauthurl=None, preauthtoken=None, starting_backoff=1, tenant_name=None, os_options=None, auth_version="1", insecure=False, ssl_compression=True, cacert=None): if os_options is None: os_options = {} self.authurl = authurl self.user = user self.key = key self.preauthurl = preauthurl self.preauthtoken = preauthtoken self.tenant_name = tenant_name self.os_options = os_options self.auth_version = auth_version self.insecure = insecure self.cacert = cacert class TestSingleTenantStoreConnections(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestSingleTenantStoreConnections, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs self.stubs.Set(swiftclient, 'Connection', FakeConnection) self.store = swift.SingleTenantStore(self.conf) self.store.configure() specs = {'scheme': 'swift', 'auth_or_store_url': 'example.com/v2/', 'user': 'tenant:user1', 'key': 'key1', 'container': 'cont', 'obj': 'object'} self.location = swift.StoreLocation(specs, self.conf) self.addCleanup(self.conf.reset) def test_basic_connection(self): connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertIsNone(connection.preauthurl) self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_conf_endpoint(self): ctx = mock.MagicMock(user='tenant:user1', tenant='tenant') self.config(swift_store_endpoint='https://internal.com') self.store.configure() connection = self.store.get_connection(self.location, context=ctx) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertEqual(connection.preauthurl, 'https://internal.com') self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_conf_endpoint_no_context(self): self.config(swift_store_endpoint='https://internal.com') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertEqual(connection.preauthurl, 'https://internal.com') self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_no_trailing_slash(self): self.location.auth_or_store_url = 'example.com/v2' connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') def test_connection_insecure(self): self.config(swift_store_auth_insecure=True) self.store.configure() connection = self.store.get_connection(self.location) self.assertTrue(connection.insecure) def test_connection_with_auth_v1(self): self.config(swift_store_auth_version='1') self.store.configure() self.location.user = 'auth_v1_user' connection = self.store.get_connection(self.location) self.assertEqual(connection.auth_version, '1') self.assertEqual(connection.user, 'auth_v1_user') self.assertIsNone(connection.tenant_name) def test_connection_invalid_user(self): self.store.configure() self.location.user = 'invalid:format:user' self.assertRaises(exceptions.BadStoreUri, self.store.get_connection, self.location) def test_connection_missing_user(self): self.store.configure() self.location.user = None self.assertRaises(exceptions.BadStoreUri, self.store.get_connection, self.location) def test_connection_with_region(self): self.config(swift_store_region='Sahara') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'region_name': 'Sahara', 'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_service_type(self): self.config(swift_store_service_type='shoe-store') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'service_type': 'shoe-store', 'endpoint_type': 'publicURL'}) def test_connection_with_endpoint_type(self): self.config(swift_store_endpoint_type='internalURL') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'internalURL'}) def test_bad_location_uri(self): self.store.configure() self.location.uri = 'http://bad_uri://' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_bad_location_uri_invalid_credentials(self): self.store.configure() self.location.uri = 'swift://bad_creds@uri/cont/obj' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_bad_location_uri_invalid_object_path(self): self.store.configure() self.location.uri = 'swift://user:key@uri/cont' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_ref_overrides_defaults(self): self.config(swift_store_auth_version='2', swift_store_user='testuser', swift_store_key='testpass', swift_store_auth_address='testaddress', swift_store_endpoint_type='internalURL', swift_store_config_file='somefile') self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'auth_version': '3', 'user': 'user:pass', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}} self.store.configure() self.assertEqual('user:pass', self.store.user) self.assertEqual('3', self.store.auth_version) self.assertEqual('authurl.com', self.store.auth_address) self.assertEqual('default', self.store.user_domain_id) self.assertEqual('ignored', self.store.user_domain_name) self.assertEqual('default', self.store.project_domain_id) self.assertEqual('ignored', self.store.project_domain_name) def test_with_v3_auth(self): self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'auth_version': '3', 'user': 'user:pass', 'key': 'password', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}} self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual('3', connection.auth_version) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}) class TestMultiTenantStoreConnections(base.StoreBaseTest): def setUp(self): super(TestMultiTenantStoreConnections, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs self.stubs.Set(swiftclient, 'Connection', FakeConnection) self.context = mock.MagicMock( user='tenant:user1', tenant='tenant', auth_token='0123') self.store = swift.MultiTenantStore(self.conf) specs = {'scheme': 'swift', 'auth_or_store_url': 'example.com', 'container': 'cont', 'obj': 'object'} self.location = swift.StoreLocation(specs, self.conf) self.addCleanup(self.conf.reset) def test_basic_connection(self): self.store.configure() connection = self.store.get_connection(self.location, context=self.context) self.assertIsNone(connection.authurl) self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'tenant:user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertIsNone(connection.key) self.assertEqual(connection.preauthurl, 'https://example.com') self.assertEqual(connection.preauthtoken, '0123') self.assertEqual(connection.os_options, {}) class TestMultiTenantStoreContext(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): """Establish a clean test environment.""" super(TestMultiTenantStoreContext, self).setUp() conf = SWIFT_CONF.copy() self.store = Store(self.conf) self.config(**conf) self.store.configure() self.register_store_schemes(self.store, 'swift') self.service_catalog = [{ "name": "Object Storage", "type": "object-store", "endpoints": [{ "publicURL": "http://127.0.0.1:0", "region": "region1", "versionId": "1.0", }] }] self.addCleanup(self.conf.reset) @requests_mock.mock() def test_download_context(self, m): """Verify context (ie token) is passed to swift on download.""" self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://127.0.0.1/glance_123/123" loc = location.get_location_from_uri(uri, conf=self.conf) ctx = mock.MagicMock( service_catalog=self.service_catalog, user='tenant:user1', tenant='tenant', auth_token='0123') m.get("http://127.0.0.1/glance_123/123") store.get(loc, context=ctx) self.assertEqual(b'0123', m.last_request.headers['X-Auth-Token']) @requests_mock.mock() def test_upload_context(self, m): """Verify context (ie token) is passed to swift on upload.""" head_req = m.head("http://127.0.0.1/glance_123", text='Some data', status_code=201) put_req = m.put("http://127.0.0.1/glance_123/123") self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() content = b'Some data' pseudo_file = six.BytesIO(content) ctx = mock.MagicMock( service_catalog=self.service_catalog, user='tenant:user1', tenant='tenant', auth_token='0123') store.add('123', pseudo_file, len(content), context=ctx) self.assertEqual(b'0123', head_req.last_request.headers['X-Auth-Token']) self.assertEqual(b'0123', put_req.last_request.headers['X-Auth-Token']) class FakeGetEndpoint(object): def __init__(self, response): self.response = response def __call__(self, service_catalog, service_type=None, endpoint_region=None, endpoint_type=None): self.service_type = service_type self.endpoint_region = endpoint_region self.endpoint_type = endpoint_type return self.response class TestCreatingLocations(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestCreatingLocations, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs conf = copy.deepcopy(SWIFT_CONF) self.store = Store(self.conf) self.config(**conf) moves.reload_module(swift) self.addCleanup(self.conf.reset) def test_single_tenant_location(self): conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_container'] = 'container' conf_file = "glance-swift.conf" self.swift_config_file = self.copy_data_file(conf_file, self.test_dir) conf.update({'swift_store_config_file': self.swift_config_file}) conf['default_swift_reference'] = 'ref1' self.config(**conf) moves.reload_module(swift) store = swift.SingleTenantStore(self.conf) store.configure() location = store.create_location('image-id') self.assertEqual(location.scheme, 'swift+https') self.assertEqual(location.swift_url, 'https://example.com') self.assertEqual(location.container, 'container') self.assertEqual(location.obj, 'image-id') self.assertEqual(location.user, 'tenant:user1') self.assertEqual(location.key, 'key1') def test_single_tenant_location_http(self): conf_file = "glance-swift.conf" test_dir = self.useFixture(fixtures.TempDir()).path self.swift_config_file = self.copy_data_file(conf_file, test_dir) self.config(swift_store_container='container', default_swift_reference='ref2', swift_store_config_file=self.swift_config_file) store = swift.SingleTenantStore(self.conf) store.configure() location = store.create_location('image-id') self.assertEqual(location.scheme, 'swift+http') self.assertEqual(location.swift_url, 'http://example.com') def test_multi_tenant_location(self): self.config(swift_store_container='container') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location = store.create_location('image-id', context=ctxt) self.assertEqual(location.scheme, 'swift+https') self.assertEqual(location.swift_url, 'https://some_endpoint') self.assertEqual(location.container, 'container_image-id') self.assertEqual(location.obj, 'image-id') self.assertIsNone(location.user) self.assertIsNone(location.key) self.assertEqual(fake_get_endpoint.service_type, 'object-store') def test_multi_tenant_location_http(self): fake_get_endpoint = FakeGetEndpoint('http://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location = store.create_location('image-id', context=ctxt) self.assertEqual(location.scheme, 'swift+http') self.assertEqual(location.swift_url, 'http://some_endpoint') def test_multi_tenant_location_with_region(self): self.config(swift_store_region='WestCarolina') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.endpoint_region, 'WestCarolina') def test_multi_tenant_location_custom_service_type(self): self.config(swift_store_service_type='toy-store') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.service_type, 'toy-store') def test_multi_tenant_location_custom_endpoint_type(self): self.config(swift_store_endpoint_type='InternalURL') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.endpoint_type, 'InternalURL') class TestChunkReader(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestChunkReader, self).setUp() conf = copy.deepcopy(SWIFT_CONF) Store(self.conf) self.config(**conf) def test_read_all_data(self): """ Replicate what goes on in the Swift driver with the repeated creation of the ChunkReader object """ CHUNKSIZE = 100 checksum = hashlib.md5() data_file = tempfile.NamedTemporaryFile() data_file.write(b'*' * units.Ki) data_file.flush() infile = open(data_file.name, 'rb') bytes_read = 0 while True: cr = swift.ChunkReader(infile, checksum, CHUNKSIZE) chunk = cr.read(CHUNKSIZE) bytes_read += len(chunk) if not chunk: break self.assertEqual(units.Ki, bytes_read) data_file.close() infile.close() class TestMultipleContainers(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestMultipleContainers, self).setUp() self.config(swift_store_multiple_containers_seed=3) self.store = swift.SingleTenantStore(self.conf) self.store.configure() def test_get_container_name_happy_path_with_seed_three(self): test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_fda' self.assertEqual(expected, actual) def test_get_container_name_with_negative_seed(self): self.config(swift_store_multiple_containers_seed=-1) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'random_id' self.assertRaises(exceptions.BadStoreConfiguration, self.store.get_container_name, test_image_id, 'default_container') def test_get_container_name_with_seed_beyond_max(self): self.config(swift_store_multiple_containers_seed=33) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'random_id' self.assertRaises(exceptions.BadStoreConfiguration, self.store.get_container_name, test_image_id, 'default_container') def test_get_container_name_with_max_seed(self): self.config(swift_store_multiple_containers_seed=32) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + test_image_id self.assertEqual(expected, actual) def test_get_container_name_with_dash(self): self.config(swift_store_multiple_containers_seed=10) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + 'fdae39a1-ba' self.assertEqual(expected, actual) def test_get_container_name_with_min_seed(self): self.config(swift_store_multiple_containers_seed=1) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + 'f' self.assertEqual(expected, actual) def test_get_container_name_with_multiple_containers_turned_off(self): self.config(swift_store_multiple_containers_seed=0) self.store.configure() test_image_id = 'random_id' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container' self.assertEqual(expected, actual)

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import copy import fixtures import hashlib import mock import tempfile import uuid from oslo_config import cfg from oslo_utils import units from oslotest import moxstubout import requests_mock import six from six import moves from six.moves import http_client from six.moves import range import swiftclient from glance_store._drivers.swift import store as swift from glance_store import backend from glance_store import BackendException from glance_store import capabilities from glance_store.common import auth from glance_store.common import utils from glance_store import exceptions from glance_store import location from glance_store.tests import base from glance_store.tests.unit import test_store_capabilities CONF = cfg.CONF FAKE_UUID = lambda: str(uuid.uuid4()) FAKE_UUID2 = lambda: str(uuid.uuid4()) Store = swift.Store FIVE_KB = 5 * units.Ki FIVE_GB = 5 * units.Gi MAX_SWIFT_OBJECT_SIZE = FIVE_GB SWIFT_PUT_OBJECT_CALLS = 0 SWIFT_CONF = {'swift_store_auth_address': 'localhost:8080', 'swift_store_container': 'glance', 'swift_store_user': 'user', 'swift_store_key': 'key', 'swift_store_auth_address': 'localhost:8080', 'swift_store_container': 'glance', 'swift_store_retry_get_count': 1, 'default_swift_reference': 'ref1' } def stub_out_swiftclient(stubs, swift_store_auth_version): fixture_containers = ['glance'] fixture_container_headers = {} fixture_headers = { 'glance/%s' % FAKE_UUID: { 'content-length': FIVE_KB, 'etag': 'c2e5db72bd7fd153f53ede5da5a06de3' }, 'glance/%s' % FAKE_UUID2: {'x-static-large-object': 'true', }, } fixture_objects = {'glance/%s' % FAKE_UUID: six.BytesIO(b"*" * FIVE_KB), 'glance/%s' % FAKE_UUID2: six.BytesIO(b"*" * FIVE_KB), } def fake_head_container(url, token, container, **kwargs): if container not in fixture_containers: msg = "No container %s found" % container status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) return fixture_container_headers def fake_put_container(url, token, container, **kwargs): fixture_containers.append(container) def fake_post_container(url, token, container, headers, http_conn=None): for key, value in six.iteritems(headers): fixture_container_headers[key] = value def fake_put_object(url, token, container, name, contents, **kwargs): global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS += 1 CHUNKSIZE = 64 * units.Ki fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: if kwargs.get('headers'): etag = kwargs['headers']['ETag'] manifest = kwargs.get('headers').get('X-Object-Manifest') fixture_headers[fixture_key] = {'manifest': True, 'etag': etag, 'x-object-manifest': manifest} fixture_objects[fixture_key] = None return etag if hasattr(contents, 'read'): fixture_object = six.BytesIO() read_len = 0 chunk = contents.read(CHUNKSIZE) checksum = hashlib.md5() while chunk: fixture_object.write(chunk) read_len += len(chunk) checksum.update(chunk) chunk = contents.read(CHUNKSIZE) etag = checksum.hexdigest() else: fixture_object = six.BytesIO(contents) read_len = len(contents) etag = hashlib.md5(fixture_object.getvalue()).hexdigest() if read_len > MAX_SWIFT_OBJECT_SIZE: msg = ('Image size:%d exceeds Swift max:%d' % (read_len, MAX_SWIFT_OBJECT_SIZE)) raise swiftclient.ClientException( msg, http_status=http_client.REQUEST_ENTITY_TOO_LARGE) fixture_objects[fixture_key] = fixture_object fixture_headers[fixture_key] = { 'content-length': read_len, 'etag': etag} return etag else: msg = ("Object PUT failed - Object with key %s already exists" % fixture_key) raise swiftclient.ClientException(msg, http_status=http_client.CONFLICT) def fake_get_object(url, token, container, name, **kwargs): fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: msg = "Object GET failed" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) byte_range = None headers = kwargs.get('headers', dict()) if headers is not None: headers = dict((k.lower(), v) for k, v in six.iteritems(headers)) if 'range' in headers: byte_range = headers.get('range') fixture = fixture_headers[fixture_key] if 'manifest' in fixture: chunk_keys = sorted([k for k in fixture_headers.keys() if k.startswith(fixture_key) and k != fixture_key]) result = six.BytesIO() for key in chunk_keys: result.write(fixture_objects[key].getvalue()) else: result = fixture_objects[fixture_key] if byte_range is not None: start = int(byte_range.split('=')[1].strip('-')) result = six.BytesIO(result.getvalue()[start:]) fixture_headers[fixture_key]['content-length'] = len( result.getvalue()) return fixture_headers[fixture_key], result def fake_head_object(url, token, container, name, **kwargs): try: fixture_key = "%s/%s" % (container, name) return fixture_headers[fixture_key] except KeyError: msg = "Object HEAD failed - Object does not exist" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) def fake_delete_object(url, token, container, name, **kwargs): fixture_key = "%s/%s" % (container, name) if fixture_key not in fixture_headers: msg = "Object DELETE failed - Object does not exist" status = http_client.NOT_FOUND raise swiftclient.ClientException(msg, http_status=status) else: del fixture_headers[fixture_key] del fixture_objects[fixture_key] def fake_http_connection(*args, **kwargs): return None def fake_get_auth(url, user, key, auth_version, **kwargs): if url is None: return None, None if 'http' in url and '://' not in url: raise ValueError('Invalid url %s' % url) if swift_store_auth_version != auth_version: msg = 'AUTHENTICATION failed (version mismatch)' raise swiftclient.ClientException(msg) return None, None stubs.Set(swiftclient.client, 'head_container', fake_head_container) stubs.Set(swiftclient.client, 'put_container', fake_put_container) stubs.Set(swiftclient.client, 'post_container', fake_post_container) stubs.Set(swiftclient.client, 'put_object', fake_put_object) stubs.Set(swiftclient.client, 'delete_object', fake_delete_object) stubs.Set(swiftclient.client, 'head_object', fake_head_object) stubs.Set(swiftclient.client, 'get_object', fake_get_object) stubs.Set(swiftclient.client, 'get_auth', fake_get_auth) stubs.Set(swiftclient.client, 'http_connection', fake_http_connection) class SwiftTests(object): @property def swift_store_user(self): return 'tenant:user1' def test_get_size(self): uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) image_size = self.store.get_size(loc) self.assertEqual(image_size, 5120) def test_get_size_with_multi_tenant_on(self): uri = ("swift://%s:key@auth_address/glance/%s" % (self.swift_store_user, FAKE_UUID)) self.config(swift_store_multi_tenant=True) ctxt = mock.MagicMock() size = backend.get_size_from_backend(uri, context=ctxt) self.assertEqual(size, 5120) def test_get(self): uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) (image_swift, image_size) = self.store.get(loc) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_with_retry(self): uri = "swift://%s:key@auth_address/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) ctxt = mock.MagicMock() (image_swift, image_size) = self.store.get(loc, context=ctxt) resp_full = b''.join([chunk for chunk in image_swift.wrapped]) resp_half = resp_full[:len(resp_full) // 2] resp_half = six.BytesIO(resp_half) image_swift.wrapped = swift.swift_retry_iter(resp_half, image_size, self.store, loc.store_location, ctxt) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_with_http_auth(self): loc = location.get_location_from_uri( "swift+http://%s:key@auth_address/glance/%s" % (self.swift_store_user, FAKE_UUID), conf=self.conf) ctxt = mock.MagicMock() (image_swift, image_size) = self.store.get(loc, context=ctxt) self.assertEqual(image_size, 5120) expected_data = b"*" * FIVE_KB data = b"" for chunk in image_swift: data += chunk self.assertEqual(expected_data, data) def test_get_non_existing(self): loc = location.get_location_from_uri( "swift://%s:key@authurl/glance/noexist" % (self.swift_store_user), conf=self.conf) self.assertRaises(exceptions.NotFound, self.store.get, loc) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=False)) def test_add(self): moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = "swift+https://tenant%%3Auser1:key@localhost:8080/glance/%s" expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_multi_store(self): conf = copy.deepcopy(SWIFT_CONF) conf['default_swift_reference'] = 'store_2' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_image_id = str(uuid.uuid4()) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 loc = 'swift+config://store_2/glance/%s' expected_location = loc % (expected_image_id) location, size, checksum, arg = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, location) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_auth_url_variations(self): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) variations = { 'store_4': 'swift+config://store_4/glance/%s', 'store_5': 'swift+config://store_5/glance/%s', 'store_6': 'swift+config://store_6/glance/%s' } for variation, expected_location in variations.items(): image_id = str(uuid.uuid4()) expected_location = expected_location % image_id expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = \ hashlib.md5(expected_swift_contents).hexdigest() image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf['default_swift_reference'] = variation self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_no_container_no_create(self): conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = False conf['swift_store_container'] = 'noexist' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 exception_caught = False try: self.store.add(str(uuid.uuid4()), image_swift, 0) except BackendException as e: exception_caught = True self.assertIn("container noexist does not exist " "in Swift", utils.exception_to_str(e)) self.assertTrue(exception_caught) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 0) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_create(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/noexist/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = True conf['swift_store_container'] = 'noexist' self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_multiple_containers_create(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) container = 'randomname_' + expected_image_id[:2] loc = 'swift+config://ref1/%s/%s' expected_location = loc % (container, expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = True conf['swift_store_container'] = 'randomname' conf['swift_store_multiple_containers_seed'] = 2 self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 1) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_swift) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_no_container_and_multiple_containers_no_create(self): conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_user'] = 'tenant:user' conf['swift_store_create_container_on_put'] = False conf['swift_store_container'] = 'randomname' conf['swift_store_multiple_containers_seed'] = 2 self.config(**conf) moves.reload_module(swift) expected_image_id = str(uuid.uuid4()) expected_container = 'randomname_' + expected_image_id[:2] self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 exception_caught = False try: self.store.add(expected_image_id, image_swift, 0) except BackendException as e: exception_caught = True expected_msg = "container %s does not exist in Swift" expected_msg = expected_msg % expected_container self.assertIn(expected_msg, utils.exception_to_str(e)) self.assertTrue(exception_caught) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 0) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=False)) def test_multi_container_doesnt_impact_multi_tenant_add(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_image_id = str(uuid.uuid4()) expected_container = 'container_' + expected_image_id loc = 'swift+https://some_endpoint/%s/%s' expected_location = loc % (expected_container, expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 self.config(swift_store_container='container') self.config(swift_store_create_container_on_put=True) self.config(swift_store_multiple_containers_seed=2) fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location, size, checksum, _ = store.add(expected_image_id, image_swift, expected_swift_size, context=ctxt) self.assertEqual(expected_location, location) @mock.patch('glance_store._drivers.swift.utils' '.is_multiple_swift_store_accounts_enabled', mock.Mock(return_value=True)) def test_add_large_object(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/glance/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 self.store = Store(self.conf) self.store.configure() orig_max_size = self.store.large_object_size orig_temp_size = self.store.large_object_chunk_size try: self.store.large_object_size = units.Ki self.store.large_object_chunk_size = units.Ki loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, expected_swift_size) finally: self.store.large_object_chunk_size = orig_temp_size self.store.large_object_size = orig_max_size self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 6) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_contents) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_large_object_zero_size(self): expected_swift_size = FIVE_KB expected_swift_contents = b"*" * expected_swift_size expected_checksum = hashlib.md5(expected_swift_contents).hexdigest() expected_image_id = str(uuid.uuid4()) loc = 'swift+config://ref1/glance/%s' expected_location = loc % (expected_image_id) image_swift = six.BytesIO(expected_swift_contents) global SWIFT_PUT_OBJECT_CALLS SWIFT_PUT_OBJECT_CALLS = 0 self.store = Store(self.conf) self.store.configure() orig_max_size = self.store.large_object_size orig_temp_size = self.store.large_object_chunk_size global MAX_SWIFT_OBJECT_SIZE orig_max_swift_object_size = MAX_SWIFT_OBJECT_SIZE try: MAX_SWIFT_OBJECT_SIZE = units.Ki self.store.large_object_size = units.Ki self.store.large_object_chunk_size = units.Ki loc, size, checksum, _ = self.store.add(expected_image_id, image_swift, 0) finally: self.store.large_object_chunk_size = orig_temp_size self.store.large_object_size = orig_max_size MAX_SWIFT_OBJECT_SIZE = orig_max_swift_object_size self.assertEqual(expected_location, loc) self.assertEqual(expected_swift_size, size) self.assertEqual(expected_checksum, checksum) # in that case). self.assertEqual(SWIFT_PUT_OBJECT_CALLS, 7) loc = location.get_location_from_uri(expected_location, conf=self.conf) (new_image_swift, new_image_size) = self.store.get(loc) new_image_contents = b''.join([chunk for chunk in new_image_swift]) new_image_swift_size = len(new_image_contents) self.assertEqual(expected_swift_contents, new_image_contents) self.assertEqual(expected_swift_size, new_image_swift_size) def test_add_already_existing(self): self.store = Store(self.conf) self.store.configure() image_swift = six.BytesIO(b"nevergonnamakeit") self.assertRaises(exceptions.Duplicate, self.store.add, FAKE_UUID, image_swift, 0) def _option_required(self, key): conf = self.getConfig() conf[key] = None try: self.config(**conf) self.store = Store(self.conf) return not self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS) except Exception: return False return False def test_no_store_credentials(self): self.store = Store(self.conf) self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'user': '', 'key': ''}} self.store.configure() self.assertFalse(self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS)) def test_no_auth_address(self): self.store = Store(self.conf) self.store.ref_params = {'ref1': {'auth_address': '', 'user': 'user1', 'key': 'key1'}} self.store.configure() self.assertFalse(self.store.is_capable( capabilities.BitMasks.WRITE_ACCESS)) def test_delete(self): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % ( self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertRaises(exceptions.NotFound, self.store.get, loc) @mock.patch.object(swiftclient.client, 'delete_object') def test_delete_slo(self, mock_del_obj): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % (self.swift_store_user, FAKE_UUID2) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertEqual(1, mock_del_obj.call_count) _, kwargs = mock_del_obj.call_args self.assertEqual('multipart-manifest=delete', kwargs.get('query_string')) @mock.patch.object(swiftclient.client, 'delete_object') def test_delete_nonslo_not_deleted_as_slo(self, mock_del_obj): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift://%s:key@authurl/glance/%s" % (self.swift_store_user, FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertEqual(1, mock_del_obj.call_count) _, kwargs = mock_del_obj.call_args self.assertEqual(None, kwargs.get('query_string')) def test_delete_with_reference_params(self): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() uri = "swift+config://ref1/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.store.delete(loc) self.assertRaises(exceptions.NotFound, self.store.get, loc) def test_delete_non_existing(self): conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc = location.get_location_from_uri( "swift://%s:key@authurl/glance/noexist" % (self.swift_store_user), conf=self.conf) self.assertRaises(exceptions.NotFound, self.store.delete, loc) def test_delete_with_some_segments_failing(self): test_image_id = str(uuid.uuid4()) def fake_head_object(container, object_name): object_manifest = '/'.join([container, object_name]) + '-' return {'x-object-manifest': object_manifest} def fake_get_container(container, **kwargs): # Returning 5 fake segments return None, [{'name': '%s-%03d' % (test_image_id, x)} for x in range(1, 6)] def fake_delete_object(container, object_name): # Simulate error on 1st and 3rd segments global SWIFT_DELETE_OBJECT_CALLS SWIFT_DELETE_OBJECT_CALLS += 1 if object_name.endswith('-001') or object_name.endswith('-003'): raise swiftclient.ClientException('Object DELETE failed') else: pass conf = copy.deepcopy(SWIFT_CONF) self.config(**conf) moves.reload_module(swift) self.store = Store(self.conf) self.store.configure() loc_uri = "swift+https://%s:key@localhost:8080/glance/%s" loc_uri = loc_uri % (self.swift_store_user, test_image_id) loc = location.get_location_from_uri(loc_uri) conn = self.store.get_connection(loc.store_location) conn.delete_object = fake_delete_object conn.head_object = fake_head_object conn.get_container = fake_get_container global SWIFT_DELETE_OBJECT_CALLS SWIFT_DELETE_OBJECT_CALLS = 0 self.store.delete(loc, connection=conn) # Expecting 6 delete calls, 5 for the segments and 1 for the manifest self.assertEqual(SWIFT_DELETE_OBJECT_CALLS, 6) def test_read_acl_public(self): self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) ctxt = mock.MagicMock() store.set_acls(loc, public=True, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Read'], "*:*") def test_read_acl_tenants(self): self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) read_tenants = ['matt', 'mark'] ctxt = mock.MagicMock() store.set_acls(loc, read_tenants=read_tenants, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Read'], 'matt:*,mark:*') def test_write_acls(self): self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://storeurl/glance/%s" % FAKE_UUID loc = location.get_location_from_uri(uri, conf=self.conf) read_tenants = ['frank', 'jim'] ctxt = mock.MagicMock() store.set_acls(loc, write_tenants=read_tenants, context=ctxt) container_headers = swiftclient.client.head_container('x', 'y', 'glance') self.assertEqual(container_headers['X-Container-Write'], 'frank:*,jim:*') class TestStoreAuthV1(base.StoreBaseTest, SwiftTests, test_store_capabilities.TestStoreCapabilitiesChecking): _CONF = cfg.CONF def getConfig(self): conf = SWIFT_CONF.copy() conf['swift_store_auth_version'] = '1' conf['swift_store_user'] = 'tenant:user1' return conf def setUp(self): super(TestStoreAuthV1, self).setUp() conf = self.getConfig() conf_file = 'glance-swift.conf' self.swift_config_file = self.copy_data_file(conf_file, self.test_dir) conf.update({'swift_store_config_file': self.swift_config_file}) moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs stub_out_swiftclient(self.stubs, conf['swift_store_auth_version']) self.store = Store(self.conf) self.config(**conf) self.store.configure() self.register_store_schemes(self.store, 'swift') self.addCleanup(self.conf.reset) class TestStoreAuthV2(TestStoreAuthV1): def getConfig(self): conf = super(TestStoreAuthV2, self).getConfig() conf['swift_store_auth_version'] = '2' conf['swift_store_user'] = 'tenant:user1' return conf def test_v2_with_no_tenant(self): uri = "swift://failme:key@auth_address/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.assertRaises(exceptions.BadStoreUri, self.store.get, loc) def test_v2_multi_tenant_location(self): conf = self.getConfig() conf['swift_store_multi_tenant'] = True uri = "swift://auth_address/glance/%s" % (FAKE_UUID) loc = location.get_location_from_uri(uri, conf=self.conf) self.assertEqual('swift', loc.store_name) class TestStoreAuthV3(TestStoreAuthV1): def getConfig(self): conf = super(TestStoreAuthV3, self).getConfig() conf['swift_store_auth_version'] = '3' conf['swift_store_user'] = 'tenant:user1' return conf class FakeConnection(object): def __init__(self, authurl, user, key, retries=5, preauthurl=None, preauthtoken=None, starting_backoff=1, tenant_name=None, os_options=None, auth_version="1", insecure=False, ssl_compression=True, cacert=None): if os_options is None: os_options = {} self.authurl = authurl self.user = user self.key = key self.preauthurl = preauthurl self.preauthtoken = preauthtoken self.tenant_name = tenant_name self.os_options = os_options self.auth_version = auth_version self.insecure = insecure self.cacert = cacert class TestSingleTenantStoreConnections(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestSingleTenantStoreConnections, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs self.stubs.Set(swiftclient, 'Connection', FakeConnection) self.store = swift.SingleTenantStore(self.conf) self.store.configure() specs = {'scheme': 'swift', 'auth_or_store_url': 'example.com/v2/', 'user': 'tenant:user1', 'key': 'key1', 'container': 'cont', 'obj': 'object'} self.location = swift.StoreLocation(specs, self.conf) self.addCleanup(self.conf.reset) def test_basic_connection(self): connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertIsNone(connection.preauthurl) self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_conf_endpoint(self): ctx = mock.MagicMock(user='tenant:user1', tenant='tenant') self.config(swift_store_endpoint='https://internal.com') self.store.configure() connection = self.store.get_connection(self.location, context=ctx) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertEqual(connection.preauthurl, 'https://internal.com') self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_conf_endpoint_no_context(self): self.config(swift_store_endpoint='https://internal.com') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertEqual(connection.key, 'key1') self.assertEqual(connection.preauthurl, 'https://internal.com') self.assertFalse(connection.insecure) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_no_trailing_slash(self): self.location.auth_or_store_url = 'example.com/v2' connection = self.store.get_connection(self.location) self.assertEqual(connection.authurl, 'https://example.com/v2/') def test_connection_insecure(self): self.config(swift_store_auth_insecure=True) self.store.configure() connection = self.store.get_connection(self.location) self.assertTrue(connection.insecure) def test_connection_with_auth_v1(self): self.config(swift_store_auth_version='1') self.store.configure() self.location.user = 'auth_v1_user' connection = self.store.get_connection(self.location) self.assertEqual(connection.auth_version, '1') self.assertEqual(connection.user, 'auth_v1_user') self.assertIsNone(connection.tenant_name) def test_connection_invalid_user(self): self.store.configure() self.location.user = 'invalid:format:user' self.assertRaises(exceptions.BadStoreUri, self.store.get_connection, self.location) def test_connection_missing_user(self): self.store.configure() self.location.user = None self.assertRaises(exceptions.BadStoreUri, self.store.get_connection, self.location) def test_connection_with_region(self): self.config(swift_store_region='Sahara') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'region_name': 'Sahara', 'service_type': 'object-store', 'endpoint_type': 'publicURL'}) def test_connection_with_service_type(self): self.config(swift_store_service_type='shoe-store') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'service_type': 'shoe-store', 'endpoint_type': 'publicURL'}) def test_connection_with_endpoint_type(self): self.config(swift_store_endpoint_type='internalURL') self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'internalURL'}) def test_bad_location_uri(self): self.store.configure() self.location.uri = 'http://bad_uri://' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_bad_location_uri_invalid_credentials(self): self.store.configure() self.location.uri = 'swift://bad_creds@uri/cont/obj' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_bad_location_uri_invalid_object_path(self): self.store.configure() self.location.uri = 'swift://user:key@uri/cont' self.assertRaises(exceptions.BadStoreUri, self.location.parse_uri, self.location.uri) def test_ref_overrides_defaults(self): self.config(swift_store_auth_version='2', swift_store_user='testuser', swift_store_key='testpass', swift_store_auth_address='testaddress', swift_store_endpoint_type='internalURL', swift_store_config_file='somefile') self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'auth_version': '3', 'user': 'user:pass', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}} self.store.configure() self.assertEqual('user:pass', self.store.user) self.assertEqual('3', self.store.auth_version) self.assertEqual('authurl.com', self.store.auth_address) self.assertEqual('default', self.store.user_domain_id) self.assertEqual('ignored', self.store.user_domain_name) self.assertEqual('default', self.store.project_domain_id) self.assertEqual('ignored', self.store.project_domain_name) def test_with_v3_auth(self): self.store.ref_params = {'ref1': {'auth_address': 'authurl.com', 'auth_version': '3', 'user': 'user:pass', 'key': 'password', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}} self.store.configure() connection = self.store.get_connection(self.location) self.assertEqual('3', connection.auth_version) self.assertEqual(connection.os_options, {'service_type': 'object-store', 'endpoint_type': 'publicURL', 'user_domain_id': 'default', 'user_domain_name': 'ignored', 'project_domain_id': 'default', 'project_domain_name': 'ignored'}) class TestMultiTenantStoreConnections(base.StoreBaseTest): def setUp(self): super(TestMultiTenantStoreConnections, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs self.stubs.Set(swiftclient, 'Connection', FakeConnection) self.context = mock.MagicMock( user='tenant:user1', tenant='tenant', auth_token='0123') self.store = swift.MultiTenantStore(self.conf) specs = {'scheme': 'swift', 'auth_or_store_url': 'example.com', 'container': 'cont', 'obj': 'object'} self.location = swift.StoreLocation(specs, self.conf) self.addCleanup(self.conf.reset) def test_basic_connection(self): self.store.configure() connection = self.store.get_connection(self.location, context=self.context) self.assertIsNone(connection.authurl) self.assertEqual(connection.auth_version, '2') self.assertEqual(connection.user, 'tenant:user1') self.assertEqual(connection.tenant_name, 'tenant') self.assertIsNone(connection.key) self.assertEqual(connection.preauthurl, 'https://example.com') self.assertEqual(connection.preauthtoken, '0123') self.assertEqual(connection.os_options, {}) class TestMultiTenantStoreContext(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestMultiTenantStoreContext, self).setUp() conf = SWIFT_CONF.copy() self.store = Store(self.conf) self.config(**conf) self.store.configure() self.register_store_schemes(self.store, 'swift') self.service_catalog = [{ "name": "Object Storage", "type": "object-store", "endpoints": [{ "publicURL": "http://127.0.0.1:0", "region": "region1", "versionId": "1.0", }] }] self.addCleanup(self.conf.reset) @requests_mock.mock() def test_download_context(self, m): self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() uri = "swift+http://127.0.0.1/glance_123/123" loc = location.get_location_from_uri(uri, conf=self.conf) ctx = mock.MagicMock( service_catalog=self.service_catalog, user='tenant:user1', tenant='tenant', auth_token='0123') m.get("http://127.0.0.1/glance_123/123") store.get(loc, context=ctx) self.assertEqual(b'0123', m.last_request.headers['X-Auth-Token']) @requests_mock.mock() def test_upload_context(self, m): head_req = m.head("http://127.0.0.1/glance_123", text='Some data', status_code=201) put_req = m.put("http://127.0.0.1/glance_123/123") self.config(swift_store_multi_tenant=True) store = Store(self.conf) store.configure() content = b'Some data' pseudo_file = six.BytesIO(content) ctx = mock.MagicMock( service_catalog=self.service_catalog, user='tenant:user1', tenant='tenant', auth_token='0123') store.add('123', pseudo_file, len(content), context=ctx) self.assertEqual(b'0123', head_req.last_request.headers['X-Auth-Token']) self.assertEqual(b'0123', put_req.last_request.headers['X-Auth-Token']) class FakeGetEndpoint(object): def __init__(self, response): self.response = response def __call__(self, service_catalog, service_type=None, endpoint_region=None, endpoint_type=None): self.service_type = service_type self.endpoint_region = endpoint_region self.endpoint_type = endpoint_type return self.response class TestCreatingLocations(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestCreatingLocations, self).setUp() moxfixture = self.useFixture(moxstubout.MoxStubout()) self.stubs = moxfixture.stubs conf = copy.deepcopy(SWIFT_CONF) self.store = Store(self.conf) self.config(**conf) moves.reload_module(swift) self.addCleanup(self.conf.reset) def test_single_tenant_location(self): conf = copy.deepcopy(SWIFT_CONF) conf['swift_store_container'] = 'container' conf_file = "glance-swift.conf" self.swift_config_file = self.copy_data_file(conf_file, self.test_dir) conf.update({'swift_store_config_file': self.swift_config_file}) conf['default_swift_reference'] = 'ref1' self.config(**conf) moves.reload_module(swift) store = swift.SingleTenantStore(self.conf) store.configure() location = store.create_location('image-id') self.assertEqual(location.scheme, 'swift+https') self.assertEqual(location.swift_url, 'https://example.com') self.assertEqual(location.container, 'container') self.assertEqual(location.obj, 'image-id') self.assertEqual(location.user, 'tenant:user1') self.assertEqual(location.key, 'key1') def test_single_tenant_location_http(self): conf_file = "glance-swift.conf" test_dir = self.useFixture(fixtures.TempDir()).path self.swift_config_file = self.copy_data_file(conf_file, test_dir) self.config(swift_store_container='container', default_swift_reference='ref2', swift_store_config_file=self.swift_config_file) store = swift.SingleTenantStore(self.conf) store.configure() location = store.create_location('image-id') self.assertEqual(location.scheme, 'swift+http') self.assertEqual(location.swift_url, 'http://example.com') def test_multi_tenant_location(self): self.config(swift_store_container='container') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location = store.create_location('image-id', context=ctxt) self.assertEqual(location.scheme, 'swift+https') self.assertEqual(location.swift_url, 'https://some_endpoint') self.assertEqual(location.container, 'container_image-id') self.assertEqual(location.obj, 'image-id') self.assertIsNone(location.user) self.assertIsNone(location.key) self.assertEqual(fake_get_endpoint.service_type, 'object-store') def test_multi_tenant_location_http(self): fake_get_endpoint = FakeGetEndpoint('http://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() location = store.create_location('image-id', context=ctxt) self.assertEqual(location.scheme, 'swift+http') self.assertEqual(location.swift_url, 'http://some_endpoint') def test_multi_tenant_location_with_region(self): self.config(swift_store_region='WestCarolina') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.endpoint_region, 'WestCarolina') def test_multi_tenant_location_custom_service_type(self): self.config(swift_store_service_type='toy-store') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.service_type, 'toy-store') def test_multi_tenant_location_custom_endpoint_type(self): self.config(swift_store_endpoint_type='InternalURL') fake_get_endpoint = FakeGetEndpoint('https://some_endpoint') self.stubs.Set(auth, 'get_endpoint', fake_get_endpoint) ctxt = mock.MagicMock( user='user', tenant='tenant', auth_token='123', service_catalog={}) store = swift.MultiTenantStore(self.conf) store.configure() store._get_endpoint(ctxt) self.assertEqual(fake_get_endpoint.endpoint_type, 'InternalURL') class TestChunkReader(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestChunkReader, self).setUp() conf = copy.deepcopy(SWIFT_CONF) Store(self.conf) self.config(**conf) def test_read_all_data(self): CHUNKSIZE = 100 checksum = hashlib.md5() data_file = tempfile.NamedTemporaryFile() data_file.write(b'*' * units.Ki) data_file.flush() infile = open(data_file.name, 'rb') bytes_read = 0 while True: cr = swift.ChunkReader(infile, checksum, CHUNKSIZE) chunk = cr.read(CHUNKSIZE) bytes_read += len(chunk) if not chunk: break self.assertEqual(units.Ki, bytes_read) data_file.close() infile.close() class TestMultipleContainers(base.StoreBaseTest): _CONF = cfg.CONF def setUp(self): super(TestMultipleContainers, self).setUp() self.config(swift_store_multiple_containers_seed=3) self.store = swift.SingleTenantStore(self.conf) self.store.configure() def test_get_container_name_happy_path_with_seed_three(self): test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_fda' self.assertEqual(expected, actual) def test_get_container_name_with_negative_seed(self): self.config(swift_store_multiple_containers_seed=-1) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'random_id' self.assertRaises(exceptions.BadStoreConfiguration, self.store.get_container_name, test_image_id, 'default_container') def test_get_container_name_with_seed_beyond_max(self): self.config(swift_store_multiple_containers_seed=33) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'random_id' self.assertRaises(exceptions.BadStoreConfiguration, self.store.get_container_name, test_image_id, 'default_container') def test_get_container_name_with_max_seed(self): self.config(swift_store_multiple_containers_seed=32) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + test_image_id self.assertEqual(expected, actual) def test_get_container_name_with_dash(self): self.config(swift_store_multiple_containers_seed=10) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + 'fdae39a1-ba' self.assertEqual(expected, actual) def test_get_container_name_with_min_seed(self): self.config(swift_store_multiple_containers_seed=1) self.store = swift.SingleTenantStore(self.conf) test_image_id = 'fdae39a1-bac5-4238-aba4-69bcc726e848' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container_' + 'f' self.assertEqual(expected, actual) def test_get_container_name_with_multiple_containers_turned_off(self): self.config(swift_store_multiple_containers_seed=0) self.store.configure() test_image_id = 'random_id' actual = self.store.get_container_name(test_image_id, 'default_container') expected = 'default_container' self.assertEqual(expected, actual)

true

f738d1cc691e5e7835df1f29f63efb94f2ce77a6

1,149

py

Python

src/scrapy_redis_loadbalancing/tools.py

EchoShoot/scrapy-redis-loadbalancing

d5c7ff76dc842f201dcaa68928dd27c24be4acb8

[ "MIT" ]

3

2019-03-05T02:30:19.000Z

2020-03-13T13:29:34.000Z

src/scrapy_redis_loadbalancing/tools.py

EchoShoot/scrapy-redis-loadbalancing

d5c7ff76dc842f201dcaa68928dd27c24be4acb8

[ "MIT" ]

null

src/scrapy_redis_loadbalancing/tools.py

EchoShoot/scrapy-redis-loadbalancing

d5c7ff76dc842f201dcaa68928dd27c24be4acb8

[ "MIT" ]

3

2019-12-20T04:41:04.000Z

2020-07-12T22:26:27.000Z

class Color(object): """ 输出各种颜色,方便 shell观察 """ @staticmethod def black(text): """ 黑色 """ return '\033[90m{content}\033[0m'.format(content=text) @staticmethod def red(text): """ 红色 """ return '\033[91m{content}\033[0m'.format(content=text) @staticmethod def green(text): """ 绿色 """ return '\033[92m{content}\033[0m'.format(content=text) @staticmethod def yellow(text): """ 黄色 """ return '\033[93m{content}\033[0m'.format(content=text) @staticmethod def violet(text): """ 紫罗兰色 """ return '\033[94m{content}\033[0m'.format(content=text) @staticmethod def purple(text): """ 紫色 """ return '\033[95m{content}\033[0m'.format(content=text) @staticmethod def cyan(text): """ 青色 """ return '\033[96m{content}\033[0m'.format(content=text) @staticmethod def white(text): """ 白色 """ return '\033[97m{content}\033[0m'.format(content=text) @staticmethod def gray(text): """ 灰色 """ return '\033[98m{content}\033[0m'.format(content=text)

24.446809

62

0.552654

class Color(object): @staticmethod def black(text): return '\033[90m{content}\033[0m'.format(content=text) @staticmethod def red(text): return '\033[91m{content}\033[0m'.format(content=text) @staticmethod def green(text): return '\033[92m{content}\033[0m'.format(content=text) @staticmethod def yellow(text): return '\033[93m{content}\033[0m'.format(content=text) @staticmethod def violet(text): return '\033[94m{content}\033[0m'.format(content=text) @staticmethod def purple(text): return '\033[95m{content}\033[0m'.format(content=text) @staticmethod def cyan(text): return '\033[96m{content}\033[0m'.format(content=text) @staticmethod def white(text): return '\033[97m{content}\033[0m'.format(content=text) @staticmethod def gray(text): return '\033[98m{content}\033[0m'.format(content=text)

true

f738d27a767e8d05f94578173bcb4472c4c89b20

4,332

py

Python

stream_alert_cli/terraform/cloudtrail.py

yutiansut/streamalert

7d198a3273781f66465420e90886a3ce53ec7559

[ "Apache-2.0" ]

2

2018-01-18T14:09:24.000Z

2021-11-02T10:45:23.000Z

stream_alert_cli/terraform/cloudtrail.py

revaniki/streamalert

7d198a3273781f66465420e90886a3ce53ec7559

[ "Apache-2.0" ]

null

stream_alert_cli/terraform/cloudtrail.py

revaniki/streamalert

7d198a3273781f66465420e90886a3ce53ec7559

[ "Apache-2.0" ]

null

""" Copyright 2017-present, Airbnb Inc. 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 json from stream_alert.shared.logger import get_logger LOGGER = get_logger(__name__) def generate_cloudtrail(cluster_name, cluster_dict, config): """Add the CloudTrail module to the Terraform cluster dict. Args: cluster_name (str): The name of the currently generating cluster cluster_dict (defaultdict): The dict containing all Terraform config for a given cluster. config (dict): The loaded config from the 'conf/' directory Returns: bool: Result of applying the cloudtrail module """ modules = config['clusters'][cluster_name]['modules'] cloudtrail_module = 'cloudtrail_{}'.format(cluster_name) enabled_legacy = modules['cloudtrail'].get('enabled') cloudtrail_enabled = modules['cloudtrail'].get('enable_logging', True) kinesis_enabled = modules['cloudtrail'].get('enable_kinesis', True) send_to_cloudwatch = modules['cloudtrail'].get('send_to_cloudwatch', False) exclude_home_region = modules['cloudtrail'].get('exclude_home_region_events', False) account_ids = list( set([config['global']['account']['aws_account_id']] + modules['cloudtrail'].get( 'cross_account_ids', []))) # Allow for backwards compatibility if enabled_legacy: del config['clusters'][cluster_name]['modules']['cloudtrail']['enabled'] config['clusters'][cluster_name]['modules']['cloudtrail']['enable_logging'] = True config['clusters'][cluster_name]['modules']['cloudtrail']['enable_kinesis'] = True LOGGER.info('Converting legacy CloudTrail config') config.write() kinesis_enabled = True cloudtrail_enabled = True existing_trail = modules['cloudtrail'].get('existing_trail', False) is_global_trail = modules['cloudtrail'].get('is_global_trail', True) region = config['global']['account']['region'] event_pattern_default = {'account': [config['global']['account']['aws_account_id']]} event_pattern = modules['cloudtrail'].get('event_pattern', event_pattern_default) # From here: http://amzn.to/2zF7CS0 valid_event_pattern_keys = { 'version', 'id', 'detail-type', 'source', 'account', 'time', 'region', 'resources', 'detail' } if not set(event_pattern.keys()).issubset(valid_event_pattern_keys): LOGGER.error('Config Error: Invalid CloudWatch Event Pattern!') return False module_info = { 'source': 'modules/tf_stream_alert_cloudtrail', 'primary_account_id': config['global']['account']['aws_account_id'], 'account_ids': account_ids, 'cluster': cluster_name, 'prefix': config['global']['account']['prefix'], 'enable_logging': cloudtrail_enabled, 'enable_kinesis': kinesis_enabled, 's3_logging_bucket': config['global']['s3_access_logging']['logging_bucket'], 'existing_trail': existing_trail, 'send_to_cloudwatch': send_to_cloudwatch, 'exclude_home_region_events': exclude_home_region, 'region': region, 'is_global_trail': is_global_trail } # use the kinesis output from the kinesis streams module if kinesis_enabled: module_info['kinesis_arn'] = '${{module.kinesis_{}.arn}}'.format(cluster_name) module_info['event_pattern'] = json.dumps(event_pattern) if send_to_cloudwatch: destination_arn = modules['cloudtrail'].get( 'cloudwatch_destination_arn', '${{module.cloudwatch_{}_{}.cloudwatch_destination_arn}}'.format(cluster_name, region) ) module_info['cloudwatch_destination_arn'] = destination_arn cluster_dict['module'][cloudtrail_module] = module_info return True

41.257143

100

0.686288

import json from stream_alert.shared.logger import get_logger LOGGER = get_logger(__name__) def generate_cloudtrail(cluster_name, cluster_dict, config): modules = config['clusters'][cluster_name]['modules'] cloudtrail_module = 'cloudtrail_{}'.format(cluster_name) enabled_legacy = modules['cloudtrail'].get('enabled') cloudtrail_enabled = modules['cloudtrail'].get('enable_logging', True) kinesis_enabled = modules['cloudtrail'].get('enable_kinesis', True) send_to_cloudwatch = modules['cloudtrail'].get('send_to_cloudwatch', False) exclude_home_region = modules['cloudtrail'].get('exclude_home_region_events', False) account_ids = list( set([config['global']['account']['aws_account_id']] + modules['cloudtrail'].get( 'cross_account_ids', []))) if enabled_legacy: del config['clusters'][cluster_name]['modules']['cloudtrail']['enabled'] config['clusters'][cluster_name]['modules']['cloudtrail']['enable_logging'] = True config['clusters'][cluster_name]['modules']['cloudtrail']['enable_kinesis'] = True LOGGER.info('Converting legacy CloudTrail config') config.write() kinesis_enabled = True cloudtrail_enabled = True existing_trail = modules['cloudtrail'].get('existing_trail', False) is_global_trail = modules['cloudtrail'].get('is_global_trail', True) region = config['global']['account']['region'] event_pattern_default = {'account': [config['global']['account']['aws_account_id']]} event_pattern = modules['cloudtrail'].get('event_pattern', event_pattern_default) valid_event_pattern_keys = { 'version', 'id', 'detail-type', 'source', 'account', 'time', 'region', 'resources', 'detail' } if not set(event_pattern.keys()).issubset(valid_event_pattern_keys): LOGGER.error('Config Error: Invalid CloudWatch Event Pattern!') return False module_info = { 'source': 'modules/tf_stream_alert_cloudtrail', 'primary_account_id': config['global']['account']['aws_account_id'], 'account_ids': account_ids, 'cluster': cluster_name, 'prefix': config['global']['account']['prefix'], 'enable_logging': cloudtrail_enabled, 'enable_kinesis': kinesis_enabled, 's3_logging_bucket': config['global']['s3_access_logging']['logging_bucket'], 'existing_trail': existing_trail, 'send_to_cloudwatch': send_to_cloudwatch, 'exclude_home_region_events': exclude_home_region, 'region': region, 'is_global_trail': is_global_trail } if kinesis_enabled: module_info['kinesis_arn'] = '${{module.kinesis_{}.arn}}'.format(cluster_name) module_info['event_pattern'] = json.dumps(event_pattern) if send_to_cloudwatch: destination_arn = modules['cloudtrail'].get( 'cloudwatch_destination_arn', '${{module.cloudwatch_{}_{}.cloudwatch_destination_arn}}'.format(cluster_name, region) ) module_info['cloudwatch_destination_arn'] = destination_arn cluster_dict['module'][cloudtrail_module] = module_info return True

true

f738d34b0b45fa9d7ce0797c816edf87cad25272

7,402

py

Python

src/dials/util/batch_handling.py

dials-src/dials

25055c1f6164dc33e672e7c5c6a9c5a35e870660

[ "BSD-3-Clause" ]

1

2021-12-10T17:28:16.000Z

src/dials/util/batch_handling.py

dials-src/dials

25055c1f6164dc33e672e7c5c6a9c5a35e870660

[ "BSD-3-Clause" ]

null

src/dials/util/batch_handling.py

dials-src/dials

25055c1f6164dc33e672e7c5c6a9c5a35e870660

[ "BSD-3-Clause" ]

1

2021-12-07T12:39:04.000Z

""" Functions to help with calculating batch properties for experiments objects. """ from __future__ import annotations import logging from dials.array_family import flex logger = logging.getLogger("dials") class batch_manager: def __init__(self, batches, batch_params): # batch params is a list of dicts with "id" and "range" - used to be # a 'scope extract' object self.batch_params = sorted(batch_params, key=lambda b: b["range"][0]) self.batches = batches self.reduced_batches, self._batch_increments = self._reduce() def _reduce(self): reduced_batches = flex.int(self.batches) batch_increments = [] incr = 0 for batch in self.batch_params: sel = (reduced_batches >= batch["range"][0]) & ( reduced_batches <= batch["range"][1] ) reduced_batches.set_selected( sel, reduced_batches.select(sel) - (batch["range"][0] - incr) + 1 ) batch_increments.append(incr) incr += batch["range"][1] - batch["range"][0] + 1 assert len(set(reduced_batches)) == len(reduced_batches) return list(reduced_batches), batch_increments def batch_plot_shapes_and_annotations(self): light_grey = "#d3d3d3" grey = "#808080" shapes = [] annotations = [] batches = flex.int(self.batches) text = flex.std_string(batches.size()) for i, batch in enumerate(self.batch_params): fillcolor = [light_grey, grey][i % 2] # alternate colours shapes.append( { "type": "rect", # x-reference is assigned to the x-values "xref": "x", # y-reference is assigned to the plot paper [0,1] "yref": "paper", "x0": self._batch_increments[i], "y0": 0, "x1": self._batch_increments[i] + (batch["range"][1] - batch["range"][0]), "y1": 1, "fillcolor": fillcolor, "opacity": 0.2, "line": {"width": 0}, } ) annotations.append( { # x-reference is assigned to the x-values "xref": "x", # y-reference is assigned to the plot paper [0,1] "yref": "paper", "x": self._batch_increments[i] + (batch["range"][1] - batch["range"][0]) / 2, "y": 1, "text": f"{batch['id']}", "showarrow": False, "yshift": 20, # 'arrowhead': 7, # 'ax': 0, # 'ay': -40 } ) sel = (batches >= batch["range"][0]) & (batches <= batch["range"][1]) text.set_selected( sel, flex.std_string( [ f"{batch['id']}: {j - batch['range'][0] + 1}" for j in batches.select(sel) ] ), ) return shapes, annotations, list(text) def assign_batches_to_reflections(reflections, batch_offsets): """Assign a 'batch' column to the reflection table""" for batch_offset, refl in zip(batch_offsets, reflections): xdet, ydet, zdet = [flex.double(x) for x in refl["xyzobs.px.value"].parts()] # compute BATCH values - floor() to get (fortran) image captured within # +1 because FORTRAN counting; zdet+1=image_index # +off because image_index+o=batch refl["batch"] = (flex.floor(zdet).iround() + 1) + batch_offset return reflections def get_batch_ranges(experiments, batch_offsets): """Get batch ranges for a list of experiments and offsets""" batch_ranges = [] assert len(experiments) == len(batch_offsets) image_ranges = get_image_ranges(experiments) for batch_offset, image_range in zip(batch_offsets, image_ranges): batch_ranges.append( (image_range[0] + batch_offset, image_range[1] + batch_offset) ) return batch_ranges def get_image_ranges(experiments): """Get image ranges for a list of experiments (including scanless exp.)""" # Note, if set to 1,1,for scanless experiments then first batch offset in # _calculate_batch_offsets is zero below, bad! return [e.scan.get_image_range() if e.scan else (0, 0) for e in experiments] def calculate_batch_offsets(experiment_list): """Take a list of experiments and resolve and return the batch offsets. First adds an image_range property as not all experiments have scans.""" image_ranges = get_image_ranges(experiment_list) offsets = _calculate_batch_offsets(image_ranges) return offsets def set_batch_offsets(experiment_list, batch_offsets): """Set batch offsets in scan objects. Don't need to set anything for scanless experiments, as these are not used with the batch system.""" for exp, offset in zip(experiment_list, batch_offsets): if exp.scan: exp.scan.set_batch_offset(offset) def _calculate_batch_offsets(image_ranges): """Take a list of (modified) experiments and resolve and return the batch offsets. This is the number added to the image number to give the batch number, such that: - Each experiment has a unique, nonoverlapping, nonconsecutive range - None are zero - Image number ranges are kept if at all possible """ experiments_to_shift = [] existing_ranges = set() maximum_batch_number = 0 batch_offsets = [0] * len(image_ranges) # Handle zeroth shifts and kept ranges for i, image_range in enumerate(image_ranges): ilow, ihigh = image_range # Check assumptions assert ilow <= ihigh, "Inverted image order!?" assert ilow >= 0, "Negative image indices are not expected" # Don't emit zero: Causes problems with C/fortran number conversion if ilow == 0: ilow, ihigh = ilow + 1, ihigh + 1 # If we overlap with anything, then process later if any(ilow < high + 1 and ihigh >= low - 1 for low, high in existing_ranges): experiments_to_shift.append((i, image_range)) else: batch_offsets[i] = ilow - image_range[0] existing_ranges.add((ilow, ihigh)) maximum_batch_number = max(maximum_batch_number, ihigh) # Now handle all the experiments that overlapped by pushing them higher for i, image_range in experiments_to_shift: start_number = _next_epoch(maximum_batch_number) range_width = image_range[1] - image_range[0] + 1 end_number = start_number + range_width - 1 batch_offsets[i] = start_number - image_range[0] maximum_batch_number = end_number return batch_offsets def _next_epoch(val): """Find the next number above the existing value that ends in 1, that is not consecutive with the current value.""" if val % 100 == 99: return val + 2 elif val % 100 == 0: return val + 101 else: rem = val % 100 return val - rem + 101

38.552083

86

0.579168

from __future__ import annotations import logging from dials.array_family import flex logger = logging.getLogger("dials") class batch_manager: def __init__(self, batches, batch_params): self.batch_params = sorted(batch_params, key=lambda b: b["range"][0]) self.batches = batches self.reduced_batches, self._batch_increments = self._reduce() def _reduce(self): reduced_batches = flex.int(self.batches) batch_increments = [] incr = 0 for batch in self.batch_params: sel = (reduced_batches >= batch["range"][0]) & ( reduced_batches <= batch["range"][1] ) reduced_batches.set_selected( sel, reduced_batches.select(sel) - (batch["range"][0] - incr) + 1 ) batch_increments.append(incr) incr += batch["range"][1] - batch["range"][0] + 1 assert len(set(reduced_batches)) == len(reduced_batches) return list(reduced_batches), batch_increments def batch_plot_shapes_and_annotations(self): light_grey = "#d3d3d3" grey = "#808080" shapes = [] annotations = [] batches = flex.int(self.batches) text = flex.std_string(batches.size()) for i, batch in enumerate(self.batch_params): fillcolor = [light_grey, grey][i % 2] shapes.append( { "type": "rect", "xref": "x", "yref": "paper", "x0": self._batch_increments[i], "y0": 0, "x1": self._batch_increments[i] + (batch["range"][1] - batch["range"][0]), "y1": 1, "fillcolor": fillcolor, "opacity": 0.2, "line": {"width": 0}, } ) annotations.append( { "xref": "x", "yref": "paper", "x": self._batch_increments[i] + (batch["range"][1] - batch["range"][0]) / 2, "y": 1, "text": f"{batch['id']}", "showarrow": False, "yshift": 20, } ) sel = (batches >= batch["range"][0]) & (batches <= batch["range"][1]) text.set_selected( sel, flex.std_string( [ f"{batch['id']}: {j - batch['range'][0] + 1}" for j in batches.select(sel) ] ), ) return shapes, annotations, list(text) def assign_batches_to_reflections(reflections, batch_offsets): for batch_offset, refl in zip(batch_offsets, reflections): xdet, ydet, zdet = [flex.double(x) for x in refl["xyzobs.px.value"].parts()] refl["batch"] = (flex.floor(zdet).iround() + 1) + batch_offset return reflections def get_batch_ranges(experiments, batch_offsets): batch_ranges = [] assert len(experiments) == len(batch_offsets) image_ranges = get_image_ranges(experiments) for batch_offset, image_range in zip(batch_offsets, image_ranges): batch_ranges.append( (image_range[0] + batch_offset, image_range[1] + batch_offset) ) return batch_ranges def get_image_ranges(experiments): return [e.scan.get_image_range() if e.scan else (0, 0) for e in experiments] def calculate_batch_offsets(experiment_list): image_ranges = get_image_ranges(experiment_list) offsets = _calculate_batch_offsets(image_ranges) return offsets def set_batch_offsets(experiment_list, batch_offsets): for exp, offset in zip(experiment_list, batch_offsets): if exp.scan: exp.scan.set_batch_offset(offset) def _calculate_batch_offsets(image_ranges): experiments_to_shift = [] existing_ranges = set() maximum_batch_number = 0 batch_offsets = [0] * len(image_ranges) for i, image_range in enumerate(image_ranges): ilow, ihigh = image_range assert ilow <= ihigh, "Inverted image order!?" assert ilow >= 0, "Negative image indices are not expected" if ilow == 0: ilow, ihigh = ilow + 1, ihigh + 1 # If we overlap with anything, then process later if any(ilow < high + 1 and ihigh >= low - 1 for low, high in existing_ranges): experiments_to_shift.append((i, image_range)) else: batch_offsets[i] = ilow - image_range[0] existing_ranges.add((ilow, ihigh)) maximum_batch_number = max(maximum_batch_number, ihigh) # Now handle all the experiments that overlapped by pushing them higher for i, image_range in experiments_to_shift: start_number = _next_epoch(maximum_batch_number) range_width = image_range[1] - image_range[0] + 1 end_number = start_number + range_width - 1 batch_offsets[i] = start_number - image_range[0] maximum_batch_number = end_number return batch_offsets def _next_epoch(val): if val % 100 == 99: return val + 2 elif val % 100 == 0: return val + 101 else: rem = val % 100 return val - rem + 101

true

f738d3546b92ea29140748d9f8745f245cb5fc8e

33,002

py

Python

salt/modules/rh_ip.py

wikimedia/operations-debs-salt

be6342abc7401ff92f67ed59f7834f1359f35314

[ "Apache-2.0" ]

null

salt/modules/rh_ip.py

wikimedia/operations-debs-salt

be6342abc7401ff92f67ed59f7834f1359f35314

[ "Apache-2.0" ]

null

salt/modules/rh_ip.py

wikimedia/operations-debs-salt

be6342abc7401ff92f67ed59f7834f1359f35314

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- ''' The networking module for RHEL/Fedora based distros ''' # Import python libs import logging import os.path import os import StringIO # Import third party libs import jinja2 import jinja2.exceptions # Import salt libs import salt.utils import salt.utils.templates import salt.utils.validate.net # Set up logging log = logging.getLogger(__name__) # Set up template environment JINJA = jinja2.Environment( loader=jinja2.FileSystemLoader( os.path.join(salt.utils.templates.TEMPLATE_DIRNAME, 'rh_ip') ) ) # Define the module's virtual name __virtualname__ = 'ip' def __virtual__(): ''' Confine this module to RHEL/Fedora based distros ''' if __grains__['os_family'] == 'RedHat': return __virtualname__ return False # Setup networking attributes _ETHTOOL_CONFIG_OPTS = [ 'autoneg', 'speed', 'duplex', 'rx', 'tx', 'sg', 'tso', 'ufo', 'gso', 'gro', 'lro' ] _RH_CONFIG_OPTS = [ 'domain', 'peerdns', 'defroute', 'mtu', 'static-routes', 'gateway' ] _RH_CONFIG_BONDING_OPTS = [ 'mode', 'miimon', 'arp_interval', 'arp_ip_target', 'downdelay', 'updelay', 'use_carrier', 'lacp_rate', 'hashing-algorithm', 'max_bonds', 'tx_queues', 'num_grat_arp', 'num_unsol_na', 'primary', 'primary_reselect', 'ad_select', 'xmit_hash_policy', 'arp_validate', 'fail_over_mac', 'all_slaves_active', 'resend_igmp' ] _RH_NETWORK_SCRIPT_DIR = '/etc/sysconfig/network-scripts' _RH_NETWORK_FILE = '/etc/sysconfig/network' _RH_NETWORK_CONF_FILES = '/etc/modprobe.d' _CONFIG_TRUE = ['yes', 'on', 'true', '1', True] _CONFIG_FALSE = ['no', 'off', 'false', '0', False] _IFACE_TYPES = [ 'eth', 'bond', 'alias', 'clone', 'ipsec', 'dialup', 'bridge', 'slave', 'vlan', ] def _error_msg_iface(iface, option, expected): ''' Build an appropriate error message from a given option and a list of expected values. ''' msg = 'Invalid option -- Interface: {0}, Option: {1}, Expected: [{2}]' return msg.format(iface, option, '|'.join(expected)) def _error_msg_routes(iface, option, expected): ''' Build an appropriate error message from a given option and a list of expected values. ''' msg = 'Invalid option -- Route interface: {0}, Option: {1}, Expected: [{2}]' return msg.format(iface, option, expected) def _log_default_iface(iface, opt, value): msg = 'Using default option -- Interface: {0} Option: {1} Value: {2}' log.info(msg.format(iface, opt, value)) def _error_msg_network(option, expected): ''' Build an appropriate error message from a given option and a list of expected values. ''' msg = 'Invalid network setting -- Setting: {0}, Expected: [{1}]' return msg.format(option, '|'.join(expected)) def _log_default_network(opt, value): msg = 'Using existing setting -- Setting: {0} Value: {1}' log.info(msg.format(opt, value)) def _parse_rh_config(path): rh_config = _read_file(path) cv_rh_config = {} if rh_config: for line in rh_config: line = line.strip() if len(line) == 0 or line.startswith('!') or line.startswith('#'): continue pair = [p.rstrip() for p in line.split('=', 1)] if len(pair) != 2: continue name, value = pair cv_rh_config[name.upper()] = value return cv_rh_config def _parse_ethtool_opts(opts, iface): ''' Filters given options and outputs valid settings for ETHTOOLS_OPTS If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' config = {} if 'autoneg' in opts: if opts['autoneg'] in _CONFIG_TRUE: config.update({'autoneg': 'on'}) elif opts['autoneg'] in _CONFIG_FALSE: config.update({'autoneg': 'off'}) else: _raise_error_iface(iface, 'autoneg', _CONFIG_TRUE + _CONFIG_FALSE) if 'duplex' in opts: valid = ['full', 'half'] if opts['duplex'] in valid: config.update({'duplex': opts['duplex']}) else: _raise_error_iface(iface, 'duplex', valid) if 'speed' in opts: valid = ['10', '100', '1000', '10000'] if str(opts['speed']) in valid: config.update({'speed': opts['speed']}) else: _raise_error_iface(iface, opts['speed'], valid) valid = _CONFIG_TRUE + _CONFIG_FALSE for option in ('rx', 'tx', 'sg', 'tso', 'ufo', 'gso', 'gro', 'lro'): if option in opts: if opts[option] in _CONFIG_TRUE: config.update({option: 'on'}) elif opts[option] in _CONFIG_FALSE: config.update({option: 'off'}) else: _raise_error_iface(iface, option, valid) return config def _parse_settings_bond(opts, iface): ''' Filters given options and outputs valid settings for requested operation. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond_def = { # 803.ad aggregation selection logic # 0 for stable (default) # 1 for bandwidth # 2 for count 'ad_select': '0', # Max number of transmit queues (default = 16) 'tx_queues': '16', # Link monitoring in milliseconds. Most NICs support this 'miimon': '100', # ARP interval in milliseconds 'arp_interval': '250', # Delay before considering link down in milliseconds (miimon * 2) 'downdelay': '200', # lacp_rate 0: Slow - every 30 seconds # lacp_rate 1: Fast - every 1 second 'lacp_rate': '0', # Max bonds for this driver 'max_bonds': '1', # Specifies the time, in milliseconds, to wait before # enabling a slave after a link recovery has been # detected. Only used with miimon. 'updelay': '0', # Used with miimon. # On: driver sends mii # Off: ethtool sends mii 'use_carrier': 'on', # Default. Don't change unless you know what you are doing. 'xmit_hash_policy': 'layer2', } if opts['mode'] in ['balance-rr', '0']: log.info( 'Device: {0} Bonding Mode: load balancing (round-robin)'.format( iface ) ) return _parse_settings_bond_0(opts, iface, bond_def) elif opts['mode'] in ['active-backup', '1']: log.info( 'Device: {0} Bonding Mode: fault-tolerance (active-backup)'.format( iface ) ) return _parse_settings_bond_1(opts, iface, bond_def) elif opts['mode'] in ['balance-xor', '2']: log.info( 'Device: {0} Bonding Mode: load balancing (xor)'.format(iface) ) return _parse_settings_bond_2(opts, iface, bond_def) elif opts['mode'] in ['broadcast', '3']: log.info( 'Device: {0} Bonding Mode: fault-tolerance (broadcast)'.format( iface ) ) return _parse_settings_bond_3(opts, iface, bond_def) elif opts['mode'] in ['802.3ad', '4']: log.info( 'Device: {0} Bonding Mode: IEEE 802.3ad Dynamic link ' 'aggregation'.format(iface) ) return _parse_settings_bond_4(opts, iface, bond_def) elif opts['mode'] in ['balance-tlb', '5']: log.info( 'Device: {0} Bonding Mode: transmit load balancing'.format(iface) ) return _parse_settings_bond_5(opts, iface, bond_def) elif opts['mode'] in ['balance-alb', '6']: log.info( 'Device: {0} Bonding Mode: adaptive load balancing'.format(iface) ) return _parse_settings_bond_6(opts, iface, bond_def) else: valid = [ '0', '1', '2', '3', '4', '5', '6', 'balance-rr', 'active-backup', 'balance-xor', 'broadcast', '802.3ad', 'balance-tlb', 'balance-alb' ] _raise_error_iface(iface, 'mode', valid) def _parse_settings_bond_0(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond0. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '0'} # ARP targets in n.n.n.n form valid = ['list of ips (up to 16)'] if 'arp_ip_target' in opts: if isinstance(opts['arp_ip_target'], list): if 1 <= len(opts['arp_ip_target']) <= 16: bond.update({'arp_ip_target': []}) for ip in opts['arp_ip_target']: # pylint: disable=C0103 bond['arp_ip_target'].append(ip) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) if 'arp_interval' in opts: try: int(opts['arp_interval']) bond.update({'arp_interval': opts['arp_interval']}) except Exception: _raise_error_iface(iface, 'arp_interval', ['integer']) else: _log_default_iface(iface, 'arp_interval', bond_def['arp_interval']) bond.update({'arp_interval': bond_def['arp_interval']}) return bond def _parse_settings_bond_1(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond1. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '1'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_2(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond2. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '2'} valid = ['list of ips (up to 16)'] if 'arp_ip_target' in opts: if isinstance(opts['arp_ip_target'], list): if 1 <= len(opts['arp_ip_target']) <= 16: bond.update({'arp_ip_target': []}) for ip in opts['arp_ip_target']: # pylint: disable=C0103 bond['arp_ip_target'].append(ip) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) if 'arp_interval' in opts: try: int(opts['arp_interval']) bond.update({'arp_interval': opts['arp_interval']}) except Exception: _raise_error_iface(iface, 'arp_interval', ['integer']) else: _log_default_iface(iface, 'arp_interval', bond_def['arp_interval']) bond.update({'arp_interval': bond_def['arp_interval']}) if 'primary' in opts: bond.update({'primary': opts['primary']}) if 'hashing-algorithm' in opts: valid = ['layer2', 'layer2+3', 'layer3+4'] if opts['hashing-algorithm'] in valid: bond.update({'xmit_hash_policy': opts['hashing-algorithm']}) else: _raise_error_iface(iface, 'hashing-algorithm', valid) return bond def _parse_settings_bond_3(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond3. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '3'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_4(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond4. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '4'} for binding in ['miimon', 'downdelay', 'updelay', 'lacp_rate', 'ad_select']: if binding in opts: if binding == 'lacp_rate': if opts[binding] == 'fast': opts.update({binding: '1'}) if opts[binding] == 'slow': opts.update({binding: '0'}) valid = ['fast', '1', 'slow', '0'] else: valid = ['integer'] try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, valid) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) if 'hashing-algorithm' in opts: valid = ['layer2', 'layer2+3', 'layer3+4'] if opts['hashing-algorithm'] in valid: bond.update({'xmit_hash_policy': opts['hashing-algorithm']}) else: _raise_error_iface(iface, 'hashing-algorithm', valid) return bond def _parse_settings_bond_5(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond5. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '5'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_6(opts, iface, bond_def): ''' Filters given options and outputs valid settings for bond6. If an option has a value that is not expected, this function will log what the Interface, Setting and what it was expecting. ''' bond = {'mode': '6'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_eth(opts, iface_type, enabled, iface): ''' Filters given options and outputs valid settings for a network interface. ''' result = {'name': iface} if 'proto' in opts: valid = ['none', 'bootp', 'dhcp'] if opts['proto'] in valid: result['proto'] = opts['proto'] else: _raise_error_iface(iface, opts['proto'], valid) if 'dns' in opts: result['dns'] = opts['dns'] result['peerdns'] = 'yes' if 'mtu' in opts: try: result['mtu'] = int(opts['mtu']) except Exception: _raise_error_iface(iface, 'mtu', ['integer']) if iface_type not in ['bridge']: ethtool = _parse_ethtool_opts(opts, iface) if ethtool: result['ethtool'] = ethtool if iface_type == 'slave': result['proto'] = 'none' if iface_type == 'bond': bonding = _parse_settings_bond(opts, iface) if bonding: result['bonding'] = bonding if iface_type not in ['bond', 'vlan', 'bridge']: if 'addr' in opts: if salt.utils.validate.net.mac(opts['addr']): result['addr'] = opts['addr'] else: _raise_error_iface(iface, opts['addr'], ['AA:BB:CC:DD:EE:FF']) else: # If interface type is slave for bond, not setting hwaddr if iface_type != 'slave': ifaces = __salt__['network.interfaces']() if iface in ifaces and 'hwaddr' in ifaces[iface]: result['addr'] = ifaces[iface]['hwaddr'] if iface_type == 'bridge': result['devtype'] = 'Bridge' bypassfirewall = True valid = _CONFIG_TRUE + _CONFIG_FALSE for opt in ['bypassfirewall']: if opt in opts: if opts[opt] in _CONFIG_TRUE: bypassfirewall = True elif opts[opt] in _CONFIG_FALSE: bypassfirewall = False else: _raise_error_iface(iface, opts[opt], valid) if bypassfirewall: __salt__['sysctl.persist']('net.bridge.bridge-nf-call-ip6tables', '0') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-iptables', '0') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-arptables', '0') else: __salt__['sysctl.persist']('net.bridge.bridge-nf-call-ip6tables', '1') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-iptables', '1') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-arptables', '1') else: if 'bridge' in opts: result['bridge'] = opts['bridge'] for opt in ['ipaddr', 'master', 'netmask', 'srcaddr', 'delay', 'domain', 'gateway']: if opt in opts: result[opt] = opts[opt] for opt in ['ipv6addr', 'ipv6gateway']: if opt in opts: result[opt] = opts[opt] if 'ipv6_autoconf' in opts: result['ipv6_autoconf'] = opts['ipv6_autoconf'] if 'enable_ipv6' in opts: result['enable_ipv6'] = opts['enable_ipv6'] valid = _CONFIG_TRUE + _CONFIG_FALSE for opt in ['onparent', 'peerdns', 'slave', 'vlan', 'defroute', 'stp']: if opt in opts: if opts[opt] in _CONFIG_TRUE: result[opt] = 'yes' elif opts[opt] in _CONFIG_FALSE: result[opt] = 'no' else: _raise_error_iface(iface, opts[opt], valid) if 'onboot' in opts: log.warning( 'The \'onboot\' option is controlled by the \'enabled\' option. ' 'Interface: {0} Enabled: {1}'.format(iface, enabled) ) if enabled: result['onboot'] = 'yes' else: result['onboot'] = 'no' # If the interface is defined then we want to always take # control away from non-root users; unless the administrator # wants to allow non-root users to control the device. if 'userctl' in opts: if opts['userctl'] in _CONFIG_TRUE: result['userctl'] = 'yes' elif opts['userctl'] in _CONFIG_FALSE: result['userctl'] = 'no' else: _raise_error_iface(iface, opts['userctl'], valid) else: result['userctl'] = 'no' return result def _parse_routes(iface, opts): ''' Filters given options and outputs valid settings for the route settings file. ''' # Normalize keys opts = dict((k.lower(), v) for (k, v) in opts.iteritems()) result = {} if 'routes' not in opts: _raise_error_routes(iface, 'routes', 'List of routes') for opt in opts: result[opt] = opts[opt] return result def _parse_network_settings(opts, current): ''' Filters given options and outputs valid settings for the global network settings file. ''' # Normalize keys opts = dict((k.lower(), v) for (k, v) in opts.iteritems()) current = dict((k.lower(), v) for (k, v) in current.iteritems()) result = {} valid = _CONFIG_TRUE + _CONFIG_FALSE if 'enabled' not in opts: try: opts['networking'] = current['networking'] _log_default_network('networking', current['networking']) except ValueError: _raise_error_network('networking', valid) else: opts['networking'] = opts['enabled'] if opts['networking'] in valid: if opts['networking'] in _CONFIG_TRUE: result['networking'] = 'yes' elif opts['networking'] in _CONFIG_FALSE: result['networking'] = 'no' else: _raise_error_network('networking', valid) if 'hostname' not in opts: try: opts['hostname'] = current['hostname'] _log_default_network('hostname', current['hostname']) except Exception: _raise_error_network('hostname', ['server1.example.com']) if opts['hostname']: result['hostname'] = opts['hostname'] else: _raise_error_network('hostname', ['server1.example.com']) if 'nozeroconf' in opts: if opts['nozeroconf'] in valid: if opts['nozeroconf'] in _CONFIG_TRUE: result['nozeroconf'] = 'true' elif opts['nozeroconf'] in _CONFIG_FALSE: result['nozeroconf'] = 'false' else: _raise_error_network('nozeroconf', valid) for opt in opts: if opt not in ['networking', 'hostname', 'nozeroconf']: result[opt] = opts[opt] return result def _raise_error_iface(iface, option, expected): ''' Log and raise an error with a logical formatted message. ''' msg = _error_msg_iface(iface, option, expected) log.error(msg) raise AttributeError(msg) def _raise_error_network(option, expected): ''' Log and raise an error with a logical formatted message. ''' msg = _error_msg_network(option, expected) log.error(msg) raise AttributeError(msg) def _raise_error_routes(iface, option, expected): ''' Log and raise an error with a logical formatted message. ''' msg = _error_msg_routes(iface, option, expected) log.error(msg) raise AttributeError(msg) def _read_file(path): ''' Reads and returns the contents of a file ''' try: with salt.utils.fopen(path, 'rb') as contents: # without newlines character. http://stackoverflow.com/questions/12330522/reading-a-file-without-newlines return contents.read().splitlines() except Exception: return '' def _write_file_iface(iface, data, folder, pattern): ''' Writes a file to disk ''' filename = os.path.join(folder, pattern.format(iface)) if not os.path.exists(folder): msg = '{0} cannot be written. {1} does not exist' msg = msg.format(filename, folder) log.error(msg) raise AttributeError(msg) fout = salt.utils.fopen(filename, 'w') fout.write(data) fout.close() def _write_file_network(data, filename): ''' Writes a file to disk ''' fout = salt.utils.fopen(filename, 'w') fout.write(data) fout.close() def _read_temp(data): tout = StringIO.StringIO() tout.write(data) tout.seek(0) output = tout.read().splitlines() # Discard newlines tout.close() return output def build_bond(iface, **settings): ''' Create a bond script in /etc/modprobe.d with the passed settings and load the bonding kernel module. CLI Example: .. code-block:: bash salt '*' ip.build_bond bond0 mode=balance-alb ''' rh_major = __grains__['osrelease'][:1] opts = _parse_settings_bond(settings, iface) try: template = JINJA.get_template('conf.jinja') except jinja2.exceptions.TemplateNotFound: log.error('Could not load template conf.jinja') return '' data = template.render({'name': iface, 'bonding': opts}) _write_file_iface(iface, data, _RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) path = os.path.join(_RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) if rh_major == '5': __salt__['cmd.run']( 'sed -i -e "/^alias\\s{0}.*/d" /etc/modprobe.conf'.format(iface), python_shell=False ) __salt__['cmd.run']( 'sed -i -e "/^options\\s{0}.*/d" /etc/modprobe.conf'.format(iface), python_shell=False ) __salt__['file.append']('/etc/modprobe.conf', path) __salt__['kmod.load']('bonding') if settings['test']: return _read_temp(data) return _read_file(path) def build_interface(iface, iface_type, enabled, **settings): ''' Build an interface script for a network interface. CLI Example: .. code-block:: bash salt '*' ip.build_interface eth0 eth <settings> ''' if __grains__['os'] == 'Fedora': rh_major = '6' else: rh_major = __grains__['osrelease'][:1] iface = iface.lower() iface_type = iface_type.lower() if iface_type not in _IFACE_TYPES: _raise_error_iface(iface, iface_type, _IFACE_TYPES) if iface_type == 'slave': settings['slave'] = 'yes' if 'master' not in settings: msg = 'master is a required setting for slave interfaces' log.error(msg) raise AttributeError(msg) if iface_type == 'vlan': settings['vlan'] = 'yes' if iface_type == 'bridge': __salt__['pkg.install']('bridge-utils') if iface_type in ['eth', 'bond', 'bridge', 'slave', 'vlan']: opts = _parse_settings_eth(settings, iface_type, enabled, iface) try: template = JINJA.get_template('rh{0}_eth.jinja'.format(rh_major)) except jinja2.exceptions.TemplateNotFound: log.error( 'Could not load template rh{0}_eth.jinja'.format( rh_major ) ) return '' ifcfg = template.render(opts) if 'test' in settings and settings['test']: return _read_temp(ifcfg) _write_file_iface(iface, ifcfg, _RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}') path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}'.format(iface)) return _read_file(path) def build_routes(iface, **settings): ''' Build a route script for a network interface. CLI Example: .. code-block:: bash salt '*' ip.build_routes eth0 <settings> ''' iface = iface.lower() opts = _parse_routes(iface, settings) try: template = JINJA.get_template('route_eth.jinja') except jinja2.exceptions.TemplateNotFound: log.error( 'Could not load template route_eth.jinja' ) return '' routecfg = template.render(routes=opts['routes']) if settings['test']: return _read_temp(routecfg) _write_file_iface(iface, routecfg, _RH_NETWORK_SCRIPT_DIR, 'route-{0}') path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'route-{0}'.format(iface)) return _read_file(path) def down(iface, iface_type): ''' Shutdown a network interface CLI Example: .. code-block:: bash salt '*' ip.down eth0 ''' # Slave devices are controlled by the master. if iface_type not in ['slave']: return __salt__['cmd.run']('ifdown {0}'.format(iface)) return None def get_bond(iface): ''' Return the content of a bond script CLI Example: .. code-block:: bash salt '*' ip.get_bond bond0 ''' path = os.path.join(_RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) return _read_file(path) def get_interface(iface): ''' Return the contents of an interface script CLI Example: .. code-block:: bash salt '*' ip.get_interface eth0 ''' path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}'.format(iface)) return _read_file(path) def up(iface, iface_type): # pylint: disable=C0103 ''' Start up a network interface CLI Example: .. code-block:: bash salt '*' ip.up eth0 ''' # Slave devices are controlled by the master. if iface_type not in ['slave']: return __salt__['cmd.run']('ifup {0}'.format(iface)) return None def get_routes(iface): ''' Return the contents of the interface routes script. CLI Example: .. code-block:: bash salt '*' ip.get_routes eth0 ''' path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'route-{0}'.format(iface)) return _read_file(path) def get_network_settings(): ''' Return the contents of the global network script. CLI Example: .. code-block:: bash salt '*' ip.get_network_settings ''' return _read_file(_RH_NETWORK_FILE) def apply_network_settings(**settings): ''' Apply global network configuration. CLI Example: .. code-block:: bash salt '*' ip.apply_network_settings ''' if 'require_reboot' not in settings: settings['require_reboot'] = False if settings['require_reboot'] in _CONFIG_TRUE: log.warning( 'The network state sls is requiring a reboot of the system to ' 'properly apply network configuration.' ) return True else: return __salt__['service.restart']('network') def build_network_settings(**settings): ''' Build the global network script. CLI Example: .. code-block:: bash salt '*' ip.build_network_settings <settings> ''' # Read current configuration and store default values current_network_settings = _parse_rh_config(_RH_NETWORK_FILE) # Build settings opts = _parse_network_settings(settings, current_network_settings) try: template = JINJA.get_template('network.jinja') except jinja2.exceptions.TemplateNotFound: log.error('Could not load template network.jinja') return '' network = template.render(opts) if settings['test']: return _read_temp(network) # Write settings _write_file_network(network, _RH_NETWORK_FILE) return _read_file(_RH_NETWORK_FILE)

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import logging import os.path import os import StringIO import jinja2 import jinja2.exceptions import salt.utils import salt.utils.templates import salt.utils.validate.net log = logging.getLogger(__name__) JINJA = jinja2.Environment( loader=jinja2.FileSystemLoader( os.path.join(salt.utils.templates.TEMPLATE_DIRNAME, 'rh_ip') ) ) __virtualname__ = 'ip' def __virtual__(): if __grains__['os_family'] == 'RedHat': return __virtualname__ return False # Setup networking attributes _ETHTOOL_CONFIG_OPTS = [ 'autoneg', 'speed', 'duplex', 'rx', 'tx', 'sg', 'tso', 'ufo', 'gso', 'gro', 'lro' ] _RH_CONFIG_OPTS = [ 'domain', 'peerdns', 'defroute', 'mtu', 'static-routes', 'gateway' ] _RH_CONFIG_BONDING_OPTS = [ 'mode', 'miimon', 'arp_interval', 'arp_ip_target', 'downdelay', 'updelay', 'use_carrier', 'lacp_rate', 'hashing-algorithm', 'max_bonds', 'tx_queues', 'num_grat_arp', 'num_unsol_na', 'primary', 'primary_reselect', 'ad_select', 'xmit_hash_policy', 'arp_validate', 'fail_over_mac', 'all_slaves_active', 'resend_igmp' ] _RH_NETWORK_SCRIPT_DIR = '/etc/sysconfig/network-scripts' _RH_NETWORK_FILE = '/etc/sysconfig/network' _RH_NETWORK_CONF_FILES = '/etc/modprobe.d' _CONFIG_TRUE = ['yes', 'on', 'true', '1', True] _CONFIG_FALSE = ['no', 'off', 'false', '0', False] _IFACE_TYPES = [ 'eth', 'bond', 'alias', 'clone', 'ipsec', 'dialup', 'bridge', 'slave', 'vlan', ] def _error_msg_iface(iface, option, expected): msg = 'Invalid option -- Interface: {0}, Option: {1}, Expected: [{2}]' return msg.format(iface, option, '|'.join(expected)) def _error_msg_routes(iface, option, expected): msg = 'Invalid option -- Route interface: {0}, Option: {1}, Expected: [{2}]' return msg.format(iface, option, expected) def _log_default_iface(iface, opt, value): msg = 'Using default option -- Interface: {0} Option: {1} Value: {2}' log.info(msg.format(iface, opt, value)) def _error_msg_network(option, expected): msg = 'Invalid network setting -- Setting: {0}, Expected: [{1}]' return msg.format(option, '|'.join(expected)) def _log_default_network(opt, value): msg = 'Using existing setting -- Setting: {0} Value: {1}' log.info(msg.format(opt, value)) def _parse_rh_config(path): rh_config = _read_file(path) cv_rh_config = {} if rh_config: for line in rh_config: line = line.strip() if len(line) == 0 or line.startswith('!') or line.startswith(' continue pair = [p.rstrip() for p in line.split('=', 1)] if len(pair) != 2: continue name, value = pair cv_rh_config[name.upper()] = value return cv_rh_config def _parse_ethtool_opts(opts, iface): config = {} if 'autoneg' in opts: if opts['autoneg'] in _CONFIG_TRUE: config.update({'autoneg': 'on'}) elif opts['autoneg'] in _CONFIG_FALSE: config.update({'autoneg': 'off'}) else: _raise_error_iface(iface, 'autoneg', _CONFIG_TRUE + _CONFIG_FALSE) if 'duplex' in opts: valid = ['full', 'half'] if opts['duplex'] in valid: config.update({'duplex': opts['duplex']}) else: _raise_error_iface(iface, 'duplex', valid) if 'speed' in opts: valid = ['10', '100', '1000', '10000'] if str(opts['speed']) in valid: config.update({'speed': opts['speed']}) else: _raise_error_iface(iface, opts['speed'], valid) valid = _CONFIG_TRUE + _CONFIG_FALSE for option in ('rx', 'tx', 'sg', 'tso', 'ufo', 'gso', 'gro', 'lro'): if option in opts: if opts[option] in _CONFIG_TRUE: config.update({option: 'on'}) elif opts[option] in _CONFIG_FALSE: config.update({option: 'off'}) else: _raise_error_iface(iface, option, valid) return config def _parse_settings_bond(opts, iface): bond_def = { # 803.ad aggregation selection logic # 0 for stable (default) # 1 for bandwidth # 2 for count 'ad_select': '0', # Max number of transmit queues (default = 16) 'tx_queues': '16', # Link monitoring in milliseconds. Most NICs support this 'miimon': '100', # ARP interval in milliseconds 'arp_interval': '250', # Delay before considering link down in milliseconds (miimon * 2) 'downdelay': '200', # lacp_rate 0: Slow - every 30 seconds # lacp_rate 1: Fast - every 1 second 'lacp_rate': '0', # Max bonds for this driver 'max_bonds': '1', # Specifies the time, in milliseconds, to wait before # enabling a slave after a link recovery has been # detected. Only used with miimon. 'updelay': '0', # Used with miimon. # On: driver sends mii # Off: ethtool sends mii 'use_carrier': 'on', # Default. Don't change unless you know what you are doing. 'xmit_hash_policy': 'layer2', } if opts['mode'] in ['balance-rr', '0']: log.info( 'Device: {0} Bonding Mode: load balancing (round-robin)'.format( iface ) ) return _parse_settings_bond_0(opts, iface, bond_def) elif opts['mode'] in ['active-backup', '1']: log.info( 'Device: {0} Bonding Mode: fault-tolerance (active-backup)'.format( iface ) ) return _parse_settings_bond_1(opts, iface, bond_def) elif opts['mode'] in ['balance-xor', '2']: log.info( 'Device: {0} Bonding Mode: load balancing (xor)'.format(iface) ) return _parse_settings_bond_2(opts, iface, bond_def) elif opts['mode'] in ['broadcast', '3']: log.info( 'Device: {0} Bonding Mode: fault-tolerance (broadcast)'.format( iface ) ) return _parse_settings_bond_3(opts, iface, bond_def) elif opts['mode'] in ['802.3ad', '4']: log.info( 'Device: {0} Bonding Mode: IEEE 802.3ad Dynamic link ' 'aggregation'.format(iface) ) return _parse_settings_bond_4(opts, iface, bond_def) elif opts['mode'] in ['balance-tlb', '5']: log.info( 'Device: {0} Bonding Mode: transmit load balancing'.format(iface) ) return _parse_settings_bond_5(opts, iface, bond_def) elif opts['mode'] in ['balance-alb', '6']: log.info( 'Device: {0} Bonding Mode: adaptive load balancing'.format(iface) ) return _parse_settings_bond_6(opts, iface, bond_def) else: valid = [ '0', '1', '2', '3', '4', '5', '6', 'balance-rr', 'active-backup', 'balance-xor', 'broadcast', '802.3ad', 'balance-tlb', 'balance-alb' ] _raise_error_iface(iface, 'mode', valid) def _parse_settings_bond_0(opts, iface, bond_def): bond = {'mode': '0'} valid = ['list of ips (up to 16)'] if 'arp_ip_target' in opts: if isinstance(opts['arp_ip_target'], list): if 1 <= len(opts['arp_ip_target']) <= 16: bond.update({'arp_ip_target': []}) for ip in opts['arp_ip_target']: bond['arp_ip_target'].append(ip) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) if 'arp_interval' in opts: try: int(opts['arp_interval']) bond.update({'arp_interval': opts['arp_interval']}) except Exception: _raise_error_iface(iface, 'arp_interval', ['integer']) else: _log_default_iface(iface, 'arp_interval', bond_def['arp_interval']) bond.update({'arp_interval': bond_def['arp_interval']}) return bond def _parse_settings_bond_1(opts, iface, bond_def): bond = {'mode': '1'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_2(opts, iface, bond_def): bond = {'mode': '2'} valid = ['list of ips (up to 16)'] if 'arp_ip_target' in opts: if isinstance(opts['arp_ip_target'], list): if 1 <= len(opts['arp_ip_target']) <= 16: bond.update({'arp_ip_target': []}) for ip in opts['arp_ip_target']: bond['arp_ip_target'].append(ip) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) else: _raise_error_iface(iface, 'arp_ip_target', valid) if 'arp_interval' in opts: try: int(opts['arp_interval']) bond.update({'arp_interval': opts['arp_interval']}) except Exception: _raise_error_iface(iface, 'arp_interval', ['integer']) else: _log_default_iface(iface, 'arp_interval', bond_def['arp_interval']) bond.update({'arp_interval': bond_def['arp_interval']}) if 'primary' in opts: bond.update({'primary': opts['primary']}) if 'hashing-algorithm' in opts: valid = ['layer2', 'layer2+3', 'layer3+4'] if opts['hashing-algorithm'] in valid: bond.update({'xmit_hash_policy': opts['hashing-algorithm']}) else: _raise_error_iface(iface, 'hashing-algorithm', valid) return bond def _parse_settings_bond_3(opts, iface, bond_def): bond = {'mode': '3'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_4(opts, iface, bond_def): bond = {'mode': '4'} for binding in ['miimon', 'downdelay', 'updelay', 'lacp_rate', 'ad_select']: if binding in opts: if binding == 'lacp_rate': if opts[binding] == 'fast': opts.update({binding: '1'}) if opts[binding] == 'slow': opts.update({binding: '0'}) valid = ['fast', '1', 'slow', '0'] else: valid = ['integer'] try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, valid) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) if 'hashing-algorithm' in opts: valid = ['layer2', 'layer2+3', 'layer3+4'] if opts['hashing-algorithm'] in valid: bond.update({'xmit_hash_policy': opts['hashing-algorithm']}) else: _raise_error_iface(iface, 'hashing-algorithm', valid) return bond def _parse_settings_bond_5(opts, iface, bond_def): bond = {'mode': '5'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_bond_6(opts, iface, bond_def): bond = {'mode': '6'} for binding in ['miimon', 'downdelay', 'updelay']: if binding in opts: try: int(opts[binding]) bond.update({binding: opts[binding]}) except Exception: _raise_error_iface(iface, binding, ['integer']) else: _log_default_iface(iface, binding, bond_def[binding]) bond.update({binding: bond_def[binding]}) if 'use_carrier' in opts: if opts['use_carrier'] in _CONFIG_TRUE: bond.update({'use_carrier': 'on'}) elif opts['use_carrier'] in _CONFIG_FALSE: bond.update({'use_carrier': 'off'}) else: valid = _CONFIG_TRUE + _CONFIG_FALSE _raise_error_iface(iface, 'use_carrier', valid) else: _log_default_iface(iface, 'use_carrier', bond_def['use_carrier']) bond.update({'use_carrier': bond_def['use_carrier']}) return bond def _parse_settings_eth(opts, iface_type, enabled, iface): result = {'name': iface} if 'proto' in opts: valid = ['none', 'bootp', 'dhcp'] if opts['proto'] in valid: result['proto'] = opts['proto'] else: _raise_error_iface(iface, opts['proto'], valid) if 'dns' in opts: result['dns'] = opts['dns'] result['peerdns'] = 'yes' if 'mtu' in opts: try: result['mtu'] = int(opts['mtu']) except Exception: _raise_error_iface(iface, 'mtu', ['integer']) if iface_type not in ['bridge']: ethtool = _parse_ethtool_opts(opts, iface) if ethtool: result['ethtool'] = ethtool if iface_type == 'slave': result['proto'] = 'none' if iface_type == 'bond': bonding = _parse_settings_bond(opts, iface) if bonding: result['bonding'] = bonding if iface_type not in ['bond', 'vlan', 'bridge']: if 'addr' in opts: if salt.utils.validate.net.mac(opts['addr']): result['addr'] = opts['addr'] else: _raise_error_iface(iface, opts['addr'], ['AA:BB:CC:DD:EE:FF']) else: if iface_type != 'slave': ifaces = __salt__['network.interfaces']() if iface in ifaces and 'hwaddr' in ifaces[iface]: result['addr'] = ifaces[iface]['hwaddr'] if iface_type == 'bridge': result['devtype'] = 'Bridge' bypassfirewall = True valid = _CONFIG_TRUE + _CONFIG_FALSE for opt in ['bypassfirewall']: if opt in opts: if opts[opt] in _CONFIG_TRUE: bypassfirewall = True elif opts[opt] in _CONFIG_FALSE: bypassfirewall = False else: _raise_error_iface(iface, opts[opt], valid) if bypassfirewall: __salt__['sysctl.persist']('net.bridge.bridge-nf-call-ip6tables', '0') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-iptables', '0') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-arptables', '0') else: __salt__['sysctl.persist']('net.bridge.bridge-nf-call-ip6tables', '1') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-iptables', '1') __salt__['sysctl.persist']('net.bridge.bridge-nf-call-arptables', '1') else: if 'bridge' in opts: result['bridge'] = opts['bridge'] for opt in ['ipaddr', 'master', 'netmask', 'srcaddr', 'delay', 'domain', 'gateway']: if opt in opts: result[opt] = opts[opt] for opt in ['ipv6addr', 'ipv6gateway']: if opt in opts: result[opt] = opts[opt] if 'ipv6_autoconf' in opts: result['ipv6_autoconf'] = opts['ipv6_autoconf'] if 'enable_ipv6' in opts: result['enable_ipv6'] = opts['enable_ipv6'] valid = _CONFIG_TRUE + _CONFIG_FALSE for opt in ['onparent', 'peerdns', 'slave', 'vlan', 'defroute', 'stp']: if opt in opts: if opts[opt] in _CONFIG_TRUE: result[opt] = 'yes' elif opts[opt] in _CONFIG_FALSE: result[opt] = 'no' else: _raise_error_iface(iface, opts[opt], valid) if 'onboot' in opts: log.warning( 'The \'onboot\' option is controlled by the \'enabled\' option. ' 'Interface: {0} Enabled: {1}'.format(iface, enabled) ) if enabled: result['onboot'] = 'yes' else: result['onboot'] = 'no' if 'userctl' in opts: if opts['userctl'] in _CONFIG_TRUE: result['userctl'] = 'yes' elif opts['userctl'] in _CONFIG_FALSE: result['userctl'] = 'no' else: _raise_error_iface(iface, opts['userctl'], valid) else: result['userctl'] = 'no' return result def _parse_routes(iface, opts): opts = dict((k.lower(), v) for (k, v) in opts.iteritems()) result = {} if 'routes' not in opts: _raise_error_routes(iface, 'routes', 'List of routes') for opt in opts: result[opt] = opts[opt] return result def _parse_network_settings(opts, current): opts = dict((k.lower(), v) for (k, v) in opts.iteritems()) current = dict((k.lower(), v) for (k, v) in current.iteritems()) result = {} valid = _CONFIG_TRUE + _CONFIG_FALSE if 'enabled' not in opts: try: opts['networking'] = current['networking'] _log_default_network('networking', current['networking']) except ValueError: _raise_error_network('networking', valid) else: opts['networking'] = opts['enabled'] if opts['networking'] in valid: if opts['networking'] in _CONFIG_TRUE: result['networking'] = 'yes' elif opts['networking'] in _CONFIG_FALSE: result['networking'] = 'no' else: _raise_error_network('networking', valid) if 'hostname' not in opts: try: opts['hostname'] = current['hostname'] _log_default_network('hostname', current['hostname']) except Exception: _raise_error_network('hostname', ['server1.example.com']) if opts['hostname']: result['hostname'] = opts['hostname'] else: _raise_error_network('hostname', ['server1.example.com']) if 'nozeroconf' in opts: if opts['nozeroconf'] in valid: if opts['nozeroconf'] in _CONFIG_TRUE: result['nozeroconf'] = 'true' elif opts['nozeroconf'] in _CONFIG_FALSE: result['nozeroconf'] = 'false' else: _raise_error_network('nozeroconf', valid) for opt in opts: if opt not in ['networking', 'hostname', 'nozeroconf']: result[opt] = opts[opt] return result def _raise_error_iface(iface, option, expected): msg = _error_msg_iface(iface, option, expected) log.error(msg) raise AttributeError(msg) def _raise_error_network(option, expected): msg = _error_msg_network(option, expected) log.error(msg) raise AttributeError(msg) def _raise_error_routes(iface, option, expected): msg = _error_msg_routes(iface, option, expected) log.error(msg) raise AttributeError(msg) def _read_file(path): try: with salt.utils.fopen(path, 'rb') as contents: return contents.read().splitlines() except Exception: return '' def _write_file_iface(iface, data, folder, pattern): filename = os.path.join(folder, pattern.format(iface)) if not os.path.exists(folder): msg = '{0} cannot be written. {1} does not exist' msg = msg.format(filename, folder) log.error(msg) raise AttributeError(msg) fout = salt.utils.fopen(filename, 'w') fout.write(data) fout.close() def _write_file_network(data, filename): fout = salt.utils.fopen(filename, 'w') fout.write(data) fout.close() def _read_temp(data): tout = StringIO.StringIO() tout.write(data) tout.seek(0) output = tout.read().splitlines() tout.close() return output def build_bond(iface, **settings): rh_major = __grains__['osrelease'][:1] opts = _parse_settings_bond(settings, iface) try: template = JINJA.get_template('conf.jinja') except jinja2.exceptions.TemplateNotFound: log.error('Could not load template conf.jinja') return '' data = template.render({'name': iface, 'bonding': opts}) _write_file_iface(iface, data, _RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) path = os.path.join(_RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) if rh_major == '5': __salt__['cmd.run']( 'sed -i -e "/^alias\\s{0}.*/d" /etc/modprobe.conf'.format(iface), python_shell=False ) __salt__['cmd.run']( 'sed -i -e "/^options\\s{0}.*/d" /etc/modprobe.conf'.format(iface), python_shell=False ) __salt__['file.append']('/etc/modprobe.conf', path) __salt__['kmod.load']('bonding') if settings['test']: return _read_temp(data) return _read_file(path) def build_interface(iface, iface_type, enabled, **settings): if __grains__['os'] == 'Fedora': rh_major = '6' else: rh_major = __grains__['osrelease'][:1] iface = iface.lower() iface_type = iface_type.lower() if iface_type not in _IFACE_TYPES: _raise_error_iface(iface, iface_type, _IFACE_TYPES) if iface_type == 'slave': settings['slave'] = 'yes' if 'master' not in settings: msg = 'master is a required setting for slave interfaces' log.error(msg) raise AttributeError(msg) if iface_type == 'vlan': settings['vlan'] = 'yes' if iface_type == 'bridge': __salt__['pkg.install']('bridge-utils') if iface_type in ['eth', 'bond', 'bridge', 'slave', 'vlan']: opts = _parse_settings_eth(settings, iface_type, enabled, iface) try: template = JINJA.get_template('rh{0}_eth.jinja'.format(rh_major)) except jinja2.exceptions.TemplateNotFound: log.error( 'Could not load template rh{0}_eth.jinja'.format( rh_major ) ) return '' ifcfg = template.render(opts) if 'test' in settings and settings['test']: return _read_temp(ifcfg) _write_file_iface(iface, ifcfg, _RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}') path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}'.format(iface)) return _read_file(path) def build_routes(iface, **settings): iface = iface.lower() opts = _parse_routes(iface, settings) try: template = JINJA.get_template('route_eth.jinja') except jinja2.exceptions.TemplateNotFound: log.error( 'Could not load template route_eth.jinja' ) return '' routecfg = template.render(routes=opts['routes']) if settings['test']: return _read_temp(routecfg) _write_file_iface(iface, routecfg, _RH_NETWORK_SCRIPT_DIR, 'route-{0}') path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'route-{0}'.format(iface)) return _read_file(path) def down(iface, iface_type): if iface_type not in ['slave']: return __salt__['cmd.run']('ifdown {0}'.format(iface)) return None def get_bond(iface): path = os.path.join(_RH_NETWORK_CONF_FILES, '{0}.conf'.format(iface)) return _read_file(path) def get_interface(iface): path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'ifcfg-{0}'.format(iface)) return _read_file(path) def up(iface, iface_type): if iface_type not in ['slave']: return __salt__['cmd.run']('ifup {0}'.format(iface)) return None def get_routes(iface): path = os.path.join(_RH_NETWORK_SCRIPT_DIR, 'route-{0}'.format(iface)) return _read_file(path) def get_network_settings(): return _read_file(_RH_NETWORK_FILE) def apply_network_settings(**settings): if 'require_reboot' not in settings: settings['require_reboot'] = False if settings['require_reboot'] in _CONFIG_TRUE: log.warning( 'The network state sls is requiring a reboot of the system to ' 'properly apply network configuration.' ) return True else: return __salt__['service.restart']('network') def build_network_settings(**settings): current_network_settings = _parse_rh_config(_RH_NETWORK_FILE) opts = _parse_network_settings(settings, current_network_settings) try: template = JINJA.get_template('network.jinja') except jinja2.exceptions.TemplateNotFound: log.error('Could not load template network.jinja') return '' network = template.render(opts) if settings['test']: return _read_temp(network) _write_file_network(network, _RH_NETWORK_FILE) return _read_file(_RH_NETWORK_FILE)

true

f738d5716ac500af9359849c11832bf0363239e6

991

py

Python

problems/predictingofficespaceprice/submissions/accepted/stefan2.py

stoman/CompetitiveProgramming

0000b64369b50e31c6f48939e837bdf6cece8ce4

[ "MIT" ]

2

2020-12-22T13:21:25.000Z

2021-12-12T22:26:26.000Z

problems/predictingofficespaceprice/submissions/accepted/stefan2.py

stoman/CompetitiveProgramming

0000b64369b50e31c6f48939e837bdf6cece8ce4

[ "MIT" ]

null

problems/predictingofficespaceprice/submissions/accepted/stefan2.py

stoman/CompetitiveProgramming

0000b64369b50e31c6f48939e837bdf6cece8ce4

[ "MIT" ]

null

#!/usr/bin/env python2 #Author: Stefan Toman import itertools import numpy as np from operator import mul from sklearn.linear_model import LinearRegression if __name__ == '__main__': #read input f, n = map(int, raw_input().split()) X = [] y = [] for _ in range(n): line = raw_input().split() X.append([float(x) for x in line[:-1]]) y.append([float(line[-1])]) q = int(raw_input()) Xt = [] for _ in range(q): Xt.append([float(x) for x in raw_input().split()]) #add new features as monomials of degree <= 3 X = np.array(X) Xt = np.array(Xt) for i in range(2, 4): for var in itertools.product(range(f), repeat=i): X = np.hstack((X, reduce(mul, [X[:, j] for j in var]).reshape(-1, 1))) Xt = np.hstack((Xt, reduce(mul, [Xt[:, j] for j in var]).reshape(-1, 1))) #use sklearn to compute output for yt in LinearRegression().fit(X, y).predict(Xt): print(yt[0])

30.030303

85

0.572149

import itertools import numpy as np from operator import mul from sklearn.linear_model import LinearRegression if __name__ == '__main__': f, n = map(int, raw_input().split()) X = [] y = [] for _ in range(n): line = raw_input().split() X.append([float(x) for x in line[:-1]]) y.append([float(line[-1])]) q = int(raw_input()) Xt = [] for _ in range(q): Xt.append([float(x) for x in raw_input().split()]) X = np.array(X) Xt = np.array(Xt) for i in range(2, 4): for var in itertools.product(range(f), repeat=i): X = np.hstack((X, reduce(mul, [X[:, j] for j in var]).reshape(-1, 1))) Xt = np.hstack((Xt, reduce(mul, [Xt[:, j] for j in var]).reshape(-1, 1))) for yt in LinearRegression().fit(X, y).predict(Xt): print(yt[0])

true

f738d5b0215c5883ba81ab9a0ea08660d6114dd6

584

py

Python

examples/plotting/server/iris.py

rothnic/bokeh

8da5e16b260a75caa8e7ef4caf215bb93dd784db

[ "BSD-3-Clause" ]

1

2015-07-17T13:57:01.000Z

examples/plotting/server/iris.py

evidation-health/bokeh

2c580d93419033b962d36e3c46d7606cc2f24606

[ "BSD-3-Clause" ]

null

examples/plotting/server/iris.py

evidation-health/bokeh

2c580d93419033b962d36e3c46d7606cc2f24606

[ "BSD-3-Clause" ]

1

2016-03-18T03:01:59.000Z

# The plot server must be running # Go to http://localhost:5006/bokeh to view this plot from bokeh.sampledata.iris import flowers from bokeh.plotting import figure, show, output_server colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'} flowers['color'] = flowers['species'].map(lambda x: colormap[x]) output_server("iris") p = figure(title = "Iris Morphology") p.xaxis.axis_label = 'Petal Length' p.yaxis.axis_label = 'Petal Width' p.circle(flowers["petal_length"], flowers["petal_width"], color=flowers["color"], fill_alpha=0.2, size=10, ) show(p)

30.736842

72

0.715753

from bokeh.sampledata.iris import flowers from bokeh.plotting import figure, show, output_server colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'} flowers['color'] = flowers['species'].map(lambda x: colormap[x]) output_server("iris") p = figure(title = "Iris Morphology") p.xaxis.axis_label = 'Petal Length' p.yaxis.axis_label = 'Petal Width' p.circle(flowers["petal_length"], flowers["petal_width"], color=flowers["color"], fill_alpha=0.2, size=10, ) show(p)

true

f738d5eb525196b32ef354d702e313f16b6ed068

1,464

py

Python

binarytree.py

sanofi2104/algorithms

a331a143aa51837df876b93993e1e1930d823331

[ "MIT" ]

1

2015-10-11T11:54:07.000Z

binarytree.py

sanofi2104/algorithms

a331a143aa51837df876b93993e1e1930d823331

[ "MIT" ]

null

binarytree.py

sanofi2104/algorithms

a331a143aa51837df876b93993e1e1930d823331

[ "MIT" ]

null

import Queue class binary_node(object): def __init__(self, _value): self.value = _value self.left = None self.right = None ''' Breadth-First search ''' def breadth_first(_tree): if not _tree: return False result = [] queue = Queue.Queue() queue.put(_tree) while not queue.empty(): temp = queue.get() result.append(temp.value) if temp.left: queue.put(temp.left) if temp.right: queue.put(temp.right) return result ''' Depth-first search ''' # Pre-Order depth-first searching algorithm def pre_order(_node, result = None): if _node == None: return if result is None: result = [] result.append(_node.value) pre_order(_node.left, result) pre_order(_node.right, result) return result # In-Order depth-first searching algorithm def in_order(_node, result = None): if _node == None: return if result is None: result = [] in_order(_node.left, result) result.append(_node.value) in_order(_node.right, result) return result # Post-Order depth-first searching algorithm def post_order(_node, result = None): if _node == None: return if result is None: result = [] post_order(_node.left, result) post_order(_node.right, result) result.append(_node.value) return result

18.531646

44

0.594262

import Queue class binary_node(object): def __init__(self, _value): self.value = _value self.left = None self.right = None def breadth_first(_tree): if not _tree: return False result = [] queue = Queue.Queue() queue.put(_tree) while not queue.empty(): temp = queue.get() result.append(temp.value) if temp.left: queue.put(temp.left) if temp.right: queue.put(temp.right) return result def pre_order(_node, result = None): if _node == None: return if result is None: result = [] result.append(_node.value) pre_order(_node.left, result) pre_order(_node.right, result) return result def in_order(_node, result = None): if _node == None: return if result is None: result = [] in_order(_node.left, result) result.append(_node.value) in_order(_node.right, result) return result def post_order(_node, result = None): if _node == None: return if result is None: result = [] post_order(_node.left, result) post_order(_node.right, result) result.append(_node.value) return result

true

f738d63d673034757db9e2a842b937dc2fff5775

8,276

py

Python

azure-cosmosdb-table/azure/cosmosdb/table/sharedaccesssignature.py

bluca/azure-cosmos-table-python

25e99050f93b1f76f19bbd2534502955d0247aac

[ "Apache-2.0" ]

20

2018-10-03T04:36:03.000Z

2021-10-03T09:01:05.000Z

azure-cosmosdb-table/azure/cosmosdb/table/sharedaccesssignature.py

bluca/azure-cosmos-table-python

25e99050f93b1f76f19bbd2534502955d0247aac

[ "Apache-2.0" ]

25

2018-12-13T15:31:06.000Z

2021-12-13T19:29:36.000Z

azure-cosmosdb-table/azure/cosmosdb/table/sharedaccesssignature.py

bluca/azure-cosmos-table-python

25e99050f93b1f76f19bbd2534502955d0247aac

[ "Apache-2.0" ]

16

2019-01-19T09:04:26.000Z

2021-09-10T19:05:35.000Z

# ------------------------------------------------------------------------- # Copyright (c) Microsoft. 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 azure.cosmosdb.table.common._common_conversion import ( _sign_string, ) from azure.cosmosdb.table.common.sharedaccesssignature import ( SharedAccessSignature, _SharedAccessHelper, _QueryStringConstants, ) from ._constants import X_MS_VERSION class TableSharedAccessSignature(SharedAccessSignature): ''' Provides a factory for creating file and share access signature tokens with a common account name and account key. Users can either use the factory or can construct the appropriate service and use the generate_*_shared_access_signature method directly. ''' def __init__(self, account_name, account_key): ''' :param str account_name: The storage account name used to generate the shared access signatures. :param str account_key: The access key to generate the shares access signatures. ''' super(TableSharedAccessSignature, self).__init__(account_name, account_key, x_ms_version=X_MS_VERSION) def generate_table(self, table_name, permission=None, expiry=None, start=None, id=None, ip=None, protocol=None, start_pk=None, start_rk=None, end_pk=None, end_rk=None): ''' Generates a shared access signature for the table. Use the returned signature with the sas_token parameter of TableService. :param str table_name: Name of table. :param TablePermissions permission: The permissions associated with the shared access signature. The user is restricted to operations allowed by the permissions. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. :param expiry: The time at which the shared access signature becomes invalid. Required unless an id is given referencing a stored access policy which contains this field. This field must be omitted if it has been specified in an associated stored access policy. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type expiry: datetime or str :param start: The time at which the shared access signature becomes valid. If omitted, start time for this call is assumed to be the time when the storage service receives the request. Azure will always convert values to UTC. If a date is passed in without timezone info, it is assumed to be UTC. :type start: datetime or str :param str id: A unique value up to 64 characters in length that correlates to a stored access policy. To create a stored access policy, use set_table_service_properties. :param str ip: Specifies an IP address or a range of IP addresses from which to accept requests. If the IP address from which the request originates does not match the IP address or address range specified on the SAS token, the request is not authenticated. For example, specifying sip=168.1.5.65 or sip=168.1.5.60-168.1.5.70 on the SAS restricts the request to those IP addresses. :param str protocol: Specifies the protocol permitted for a request made. The default value is https,http. See :class:`~azure.cosmosdb.table.common.models.Protocol` for possible values. :param str start_pk: The minimum partition key accessible with this shared access signature. startpk must accompany startrk. Key values are inclusive. If omitted, there is no lower bound on the table entities that can be accessed. :param str start_rk: The minimum row key accessible with this shared access signature. startpk must accompany startrk. Key values are inclusive. If omitted, there is no lower bound on the table entities that can be accessed. :param str end_pk: The maximum partition key accessible with this shared access signature. endpk must accompany endrk. Key values are inclusive. If omitted, there is no upper bound on the table entities that can be accessed. :param str end_rk: The maximum row key accessible with this shared access signature. endpk must accompany endrk. Key values are inclusive. If omitted, there is no upper bound on the table entities that can be accessed. ''' sas = _TableSharedAccessHelper() sas.add_base(permission, expiry, start, ip, protocol, X_MS_VERSION) sas.add_id(id) sas.add_table_access_ranges(table_name, start_pk, start_rk, end_pk, end_rk) # Table names must be signed lower case resource_path = table_name.lower() sas.add_resource_signature(self.account_name, self.account_key, 'table', resource_path) return sas.get_token() class _TableQueryStringConstants( _QueryStringConstants): TABLE_NAME = 'tn' class _TableSharedAccessHelper(_SharedAccessHelper): def __init__(self): self.query_dict = {} def add_table_access_ranges(self, table_name, start_pk, start_rk, end_pk, end_rk): self._add_query(_TableQueryStringConstants.TABLE_NAME, table_name) self._add_query(_TableQueryStringConstants.START_PK, start_pk) self._add_query(_TableQueryStringConstants.START_RK, start_rk) self._add_query(_TableQueryStringConstants.END_PK, end_pk) self._add_query(_TableQueryStringConstants.END_RK, end_rk) def add_resource_signature(self, account_name, account_key, service, path): def get_value_to_append(query): return_value = self.query_dict.get(query) or '' return return_value + '\n' if path[0] != '/': path = '/' + path canonicalized_resource = '/' + service + '/' + account_name + path + '\n' # Form the string to sign from shared_access_policy and canonicalized # resource. The order of values is important. string_to_sign = \ (get_value_to_append(_QueryStringConstants.SIGNED_PERMISSION) + get_value_to_append(_QueryStringConstants.SIGNED_START) + get_value_to_append(_QueryStringConstants.SIGNED_EXPIRY) + canonicalized_resource + get_value_to_append(_QueryStringConstants.SIGNED_IDENTIFIER) + get_value_to_append(_QueryStringConstants.SIGNED_IP) + get_value_to_append(_QueryStringConstants.SIGNED_PROTOCOL) + get_value_to_append(_QueryStringConstants.SIGNED_VERSION)) string_to_sign += \ (get_value_to_append(_QueryStringConstants.START_PK) + get_value_to_append(_QueryStringConstants.START_RK) + get_value_to_append(_QueryStringConstants.END_PK) + get_value_to_append(_QueryStringConstants.END_RK)) # remove the trailing newline if string_to_sign[-1] == '\n': string_to_sign = string_to_sign[:-1] self._add_query(_QueryStringConstants.SIGNED_SIGNATURE, _sign_string(account_key, string_to_sign))

47.83815

110

0.666989

from azure.cosmosdb.table.common._common_conversion import ( _sign_string, ) from azure.cosmosdb.table.common.sharedaccesssignature import ( SharedAccessSignature, _SharedAccessHelper, _QueryStringConstants, ) from ._constants import X_MS_VERSION class TableSharedAccessSignature(SharedAccessSignature): def __init__(self, account_name, account_key): super(TableSharedAccessSignature, self).__init__(account_name, account_key, x_ms_version=X_MS_VERSION) def generate_table(self, table_name, permission=None, expiry=None, start=None, id=None, ip=None, protocol=None, start_pk=None, start_rk=None, end_pk=None, end_rk=None): sas = _TableSharedAccessHelper() sas.add_base(permission, expiry, start, ip, protocol, X_MS_VERSION) sas.add_id(id) sas.add_table_access_ranges(table_name, start_pk, start_rk, end_pk, end_rk) resource_path = table_name.lower() sas.add_resource_signature(self.account_name, self.account_key, 'table', resource_path) return sas.get_token() class _TableQueryStringConstants( _QueryStringConstants): TABLE_NAME = 'tn' class _TableSharedAccessHelper(_SharedAccessHelper): def __init__(self): self.query_dict = {} def add_table_access_ranges(self, table_name, start_pk, start_rk, end_pk, end_rk): self._add_query(_TableQueryStringConstants.TABLE_NAME, table_name) self._add_query(_TableQueryStringConstants.START_PK, start_pk) self._add_query(_TableQueryStringConstants.START_RK, start_rk) self._add_query(_TableQueryStringConstants.END_PK, end_pk) self._add_query(_TableQueryStringConstants.END_RK, end_rk) def add_resource_signature(self, account_name, account_key, service, path): def get_value_to_append(query): return_value = self.query_dict.get(query) or '' return return_value + '\n' if path[0] != '/': path = '/' + path canonicalized_resource = '/' + service + '/' + account_name + path + '\n' string_to_sign = \ (get_value_to_append(_QueryStringConstants.SIGNED_PERMISSION) + get_value_to_append(_QueryStringConstants.SIGNED_START) + get_value_to_append(_QueryStringConstants.SIGNED_EXPIRY) + canonicalized_resource + get_value_to_append(_QueryStringConstants.SIGNED_IDENTIFIER) + get_value_to_append(_QueryStringConstants.SIGNED_IP) + get_value_to_append(_QueryStringConstants.SIGNED_PROTOCOL) + get_value_to_append(_QueryStringConstants.SIGNED_VERSION)) string_to_sign += \ (get_value_to_append(_QueryStringConstants.START_PK) + get_value_to_append(_QueryStringConstants.START_RK) + get_value_to_append(_QueryStringConstants.END_PK) + get_value_to_append(_QueryStringConstants.END_RK)) if string_to_sign[-1] == '\n': string_to_sign = string_to_sign[:-1] self._add_query(_QueryStringConstants.SIGNED_SIGNATURE, _sign_string(account_key, string_to_sign))

true

f738d6c9152aaf0bc30172d9c59308cf84ce2746

2,011

py

Python

21-fs-ias-lec/16-nicknames-forward/subChat/Colorize.py

paultroeger/BACnet

855b931f2a0e9b64e9571f41de2a8cd71d7a01f4

[ "MIT" ]

8

2020-03-17T21:12:18.000Z

2021-12-12T15:55:54.000Z

21-fs-ias-lec/16-nicknames-forward/subChat/Colorize.py

paultroeger/BACnet

855b931f2a0e9b64e9571f41de2a8cd71d7a01f4

[ "MIT" ]

2

2021-07-19T06:18:43.000Z

2022-02-10T12:17:58.000Z

21-fs-ias-lec/16-nicknames-forward/subChat/Colorize.py

paultroeger/BACnet

855b931f2a0e9b64e9571f41de2a8cd71d7a01f4

[ "MIT" ]

25

2020-03-20T09:32:45.000Z

2021-07-18T18:12:59.000Z

#version 15:38 import random import string #name = 'zzz' set_off = 23 def convert(name): for i in range(len(name)): if name[i].lower() == 'i' or name[i].lower() == 'y' or name[i].lower() == '9': name = list(name) name[i] = 'g' name = ''.join(name) indx = 0 c=0 while len(name) < 6: if c >16: return '#ffb300' # just in case it goes into an infinate Loop (probability is very, very low) c +=1 new_letter = chr(65 + (ord(name[indx]) + set_off + (indx*6) )%25) # this keeps the char within the range of A-Z in the asci table and adds variation in case the letter is the same (indx*6) if new_letter.lower() != 'i' and new_letter.lower() != 'y' and new_letter != '9': name = name + new_letter #add the letter indx = (indx+1)%len(name) if len(name) > 6: name = name[:6] #cut name if too long name = list(name) # make it a list so we can edit it more easily for i in range(len(name)): Integer = (ord(name[i])+set_off)%16 Hex = Integer.to_bytes(((Integer.bit_length() + 7) // 8),"big").hex() #print("...."+Hex) Hex = Hex[1:] name[i] = Hex name = ''.join(name) color = '#' + name return color def name_to_color(name): color = convert(name) r = int(color[1:3], 16) g = int(color[3:5], 16) b = int(color[5:7], 16) if r<128 or g<128 or b<128 and len(name) == 7: return color else: return '#00f7ff' # some ord() chars aren't convertable. When we checked all, we found this to be the case with i, y and 9 which is why we prevent the program from outputting them. Just in case there are any other letters that we forgot to check, we added this clause. Should never get here but the presentation got us worried cuase if the color is not exactly 6 digits long, tkinter crashes.

38.673077

401

0.558429

import random import string set_off = 23 def convert(name): for i in range(len(name)): if name[i].lower() == 'i' or name[i].lower() == 'y' or name[i].lower() == '9': name = list(name) name[i] = 'g' name = ''.join(name) indx = 0 c=0 while len(name) < 6: if c >16: return '#ffb300' c +=1 new_letter = chr(65 + (ord(name[indx]) + set_off + (indx*6) )%25) if new_letter.lower() != 'i' and new_letter.lower() != 'y' and new_letter != '9': name = name + new_letter indx = (indx+1)%len(name) if len(name) > 6: name = name[:6] name = list(name) for i in range(len(name)): Integer = (ord(name[i])+set_off)%16 Hex = Integer.to_bytes(((Integer.bit_length() + 7) // 8),"big").hex() Hex = Hex[1:] name[i] = Hex name = ''.join(name) color = '#' + name return color def name_to_color(name): color = convert(name) r = int(color[1:3], 16) g = int(color[3:5], 16) b = int(color[5:7], 16) if r<128 or g<128 or b<128 and len(name) == 7: return color else: return '#00f7ff'

true

f738d788b59babbab994d85a7f5b2804becccbe1

14,640

py

Python

tests/integration/conftest.py

linsicai/peloton

4706ce094432f8fcdacdf7d8045a4aaa7f5259af

[ "Apache-2.0" ]

null

tests/integration/conftest.py

linsicai/peloton

4706ce094432f8fcdacdf7d8045a4aaa7f5259af

[ "Apache-2.0" ]

null

tests/integration/conftest.py

linsicai/peloton

4706ce094432f8fcdacdf7d8045a4aaa7f5259af

[ "Apache-2.0" ]

null

import logging import os import pytest import time import grpc import requests from docker import Client from tools.minicluster.main import setup, teardown, config as mc_config from tools.minicluster.minicluster import run_mesos_agent, teardown_mesos_agent from host import start_maintenance, complete_maintenance, wait_for_host_state from job import Job from job import query_jobs as batch_query_jobs from job import kill_jobs as batch_kill_jobs from stateless_job import StatelessJob from stateless_job import query_jobs as stateless_query_jobs from stateless_job import delete_jobs as stateless_delete_jobs from m3.client import M3 from m3.emitter import BatchedEmitter from peloton_client.pbgen.peloton.api.v0.host import host_pb2 from peloton_client.pbgen.peloton.api.v0.job import job_pb2 from conf_util import ( TERMINAL_JOB_STATES, ACTIVE_JOB_STATES, MESOS_MASTER, MESOS_AGENTS, ) import conf_util as util log = logging.getLogger(__name__) class TestMetrics(object): def __init__(self): self.failed = 0 self.passed = 0 self.duration = 0.0 def increment_passed(self, duration): self.passed += 1 self.duration += duration def increment_failed(self, duration): self.failed += 1 self.duration += duration collect_metrics = TestMetrics() # # Module scoped setup / teardown across test suites. # @pytest.fixture(scope="module", autouse=True) def setup_cluster(request): tests_failed_before_module = request.session.testsfailed setup_minicluster() def teardown_cluster(): dump_logs = False if (request.session.testsfailed - tests_failed_before_module) > 0: dump_logs = True teardown_minicluster(dump_logs) request.addfinalizer(teardown_cluster) @pytest.fixture(autouse=True) def run_around_tests(): # before each test yield # after each test cleanup_batch_jobs() @pytest.hookimpl(hookwrapper=True) def pytest_runtest_makereport(item, call): global collect_metrics outcome = yield rep = outcome.get_result() if rep.outcome == "passed" and rep.when == "call": collect_metrics.increment_passed(rep.duration) if rep.outcome == "failed" and rep.when == "call": collect_metrics.increment_failed(rep.duration) rep = outcome.get_result() setattr(item, "rep_" + rep.when, rep) if "incremental" in item.keywords: if call.excinfo is not None: parent = item.parent parent._previousfailed = item def pytest_sessionfinish(session, exitstatus): emitter = BatchedEmitter() m3 = M3( application_identifier="peloton", emitter=emitter, environment="production", default_tags={"result": "watchdog", "cluster": os.getenv("CLUSTER")}, ) if collect_metrics.failed > 0: m3.gauge("watchdog_result", 1) else: m3.gauge("watchdog_result", 0) m3.gauge("total_tests", collect_metrics.failed + collect_metrics.passed) m3.gauge("failed_tests", collect_metrics.failed) m3.gauge("passed_tests", collect_metrics.passed) m3.gauge("duration_tests", collect_metrics.duration) class Container(object): def __init__(self, names): self._cli = Client(base_url="unix://var/run/docker.sock") self._names = names def start(self): for name in self._names: self._cli.start(name) log.info("%s started", name) if self._names[0] in MESOS_MASTER: wait_for_mesos_master_leader() def stop(self): for name in self._names: self._cli.stop(name, timeout=0) log.info("%s stopped", name) def restart(self): for name in self._names: self._cli.restart(name, timeout=0) log.info("%s restarted", name) if self._names[0] in MESOS_MASTER: wait_for_mesos_master_leader() def get_container(container_name): return Container(container_name) def wait_for_mesos_master_leader( url="http://127.0.0.1:5050/state.json", timeout_secs=20 ): """ util method to wait for mesos master leader elected """ deadline = time.time() + timeout_secs while time.time() < deadline: try: resp = requests.get(url) if resp.status_code != 200: time.sleep(2) continue return except Exception: pass assert False, "timed out waiting for mesos master leader" def wait_for_all_agents_to_register( url="http://127.0.0.1:5050/state.json", timeout_secs=300, ): """ util method to wait for all agents to register """ deadline = time.time() + timeout_secs while time.time() < deadline: try: resp = requests.get(url) if resp.status_code == 200: registered_agents = 0 for a in resp.json()['slaves']: if a['active'] == True: registered_agents += 1 if registered_agents == 3: return time.sleep(10) except Exception: pass assert False, "timed out waiting for agents to register" def setup_minicluster(enable_k8s=False): """ setup minicluster """ log.info("setup cluster") if os.getenv("CLUSTER", ""): log.info("cluster mode") else: log.info("local minicluster mode") setup(enable_peloton=True, enable_k8s=enable_k8s) time.sleep(5) def teardown_minicluster(dump_logs=False): """ teardown minicluster """ log.info("\nteardown cluster") if os.getenv("CLUSTER", ""): log.info("cluster mode, no teardown actions") elif os.getenv("NO_TEARDOWN", ""): log.info("skip teardown") else: log.info("tearing down") # dump logs only if tests have failed in the current module if dump_logs: # stop containers so that log stream will not block teardown(stop=True) try: # TODO (varung): enable PE and mesos-master logs if needed cli = Client(base_url="unix://var/run/docker.sock") for c in ("peloton-jobmgr0", "peloton-resmgr0"): for l in cli.logs(c, stream=True): # remove newline character when logging log.info(l.rstrip()) except Exception as e: log.info(e) teardown() def cleanup_batch_jobs(): """ stop all batch jobs from minicluster """ jobs = batch_query_jobs() batch_kill_jobs(jobs) def cleanup_stateless_jobs(timeout_secs=10): """ delete all service jobs from minicluster """ jobs = stateless_query_jobs() # opportunistic delete for jobs, if not deleted within # timeout period, it will get cleanup in next test run. stateless_delete_jobs(jobs) # Wait for job deletion to complete. deadline = time.time() + timeout_secs while time.time() < deadline: try: jobs = stateless_query_jobs() if len(jobs) == 0: return time.sleep(2) except grpc.RpcError as e: # Catch "not-found" error here because QueryJobs endpoint does # two db queries in sequence: "QueryJobs" and "GetUpdate". # However, when we delete a job, updates are deleted first, # there is a slight chance QueryJobs will fail to query the # update, returning "not-found" error. if e.code() == grpc.StatusCode.NOT_FOUND: time.sleep(2) continue @pytest.fixture() def mesos_master(): return Container(MESOS_MASTER) @pytest.fixture() def mesos_agent(): # TODO: We need to pick up the count dynamically. return Container(MESOS_AGENTS) @pytest.fixture() def placement_engines(): return Container(util.PLACEMENT_ENGINES) @pytest.fixture() def jobmgr(): # TODO: We need to pick up the count dynamically. return Container(util.JOB_MGRS) @pytest.fixture() def resmgr(): # TODO: We need to pick up the count dynamically. return Container(util.RES_MGRS) @pytest.fixture() def hostmgr(): # TODO: We need to pick up the count dynamically. return Container(util.HOST_MGRS) @pytest.fixture() def aurorabridge(): # TODO: We need to pick up the count dynamically. return Container(util.AURORA_BRIDGE) @pytest.fixture def long_running_job(request): job = Job(job_file="long_running_job.yaml") # teardown def kill_long_running_job(): print("\nstopping long running job") job.stop() request.addfinalizer(kill_long_running_job) return job @pytest.fixture def stateless_job(request): job = StatelessJob() # teardown def kill_stateless_job(): print("\nstopping stateless job") job.stop() request.addfinalizer(kill_stateless_job) return job @pytest.fixture def host_affinity_job(request): job = Job(job_file="test_job_host_affinity_constraint.yaml") # Kill job def kill_host_affinity_job(): print("\nstopping host affinity job") job.stop() request.addfinalizer(kill_host_affinity_job) return job # For unit tests of update/restart running with in_place, it would # be tested with both in_place feature enabled and disabled @pytest.fixture(params=[True, False]) def in_place(request): return request.param @pytest.fixture def maintenance(request): draining_hosts = [] client = [None] # Use list to store a reference to the client object def update_client(new_client): client[0] = new_client def start(hosts): resp = start_maintenance(hosts) if not resp: log.error("Start maintenance failed:" + resp) return resp draining_hosts.extend(hosts) return resp def stop(hosts): resp = complete_maintenance(hosts) if not resp: log.error("Complete maintenance failed:" + resp) return resp # The mesos-agent containers needs to be started explicitly as they would # have been stopped when the agents transition to DOWN Container(hosts).start() del draining_hosts[:] return resp def clean_up(): # kill stateless jobs. This is needed since host draining # is done in SLA aware manner for stateless jobs. for j in stateless_query_jobs(client=client[0]): j.stop() if not draining_hosts: return for h in draining_hosts: wait_for_host_state(h, host_pb2.HOST_STATE_DOWN) stop(draining_hosts) request.addfinalizer(clean_up) response = dict() response["start"] = start response["stop"] = stop response["update_client"] = update_client return response """ Setup fixture for getting a dict of job objects per state """ @pytest.fixture def jobs_by_state(request): return util.create_job_config_by_state(_num_jobs_per_state=1) """ Setup/Cleanup fixture that starts a set of RUNNING, SUCCEEDED and FAILED jobs scoped per module. This is to give each module a set of active and completed jobs to test on. Returns: common salt identifier, respoolID and dict of created jobs """ @pytest.fixture(scope="module") def create_jobs(request): jobs_by_state = util.create_job_config_by_state() salt = jobs_by_state[0] jobs_dict = jobs_by_state[1] log.info("Create jobs") respoolID = None for state in TERMINAL_JOB_STATES: jobs = jobs_dict[state] for job in jobs: job.create() if state == "FAILED": job.wait_for_state( goal_state="FAILED", failed_state="SUCCEEDED" ) else: job.wait_for_state(goal_state=state) if respoolID is None: respoolID = job.get_config().respoolID def stop_jobs(): log.info("Stop jobs") for state in TERMINAL_JOB_STATES: jobs = jobs_dict[state] for job in jobs: state = job_pb2.JobState.Name(job.get_runtime().state) if state in ACTIVE_JOB_STATES: job.stop() job.wait_for_state(goal_state="KILLED") request.addfinalizer(stop_jobs) # Job Query accuracy depends on lucene index being up to date # lucene index refresh time is 10 seconds. Sleep for 12 sec. time.sleep(12) return salt, respoolID, jobs_dict """ Setup/Cleanup fixture for tasks query integ-tests. Within fixture parameter, a list of tuples, such as [(task_state, count)], is passed to give each test case a varied number of tasks to test on. Returns: The job id of the job created. """ @pytest.fixture def task_test_fixture(request): # task_states is a list of tuples, e.g. [('SUCCEEDED', 2)]. task_states = request.param assert task_states is not None if len(task_states) > 1: mixed_task_states = True else: mixed_task_states = False test_config = util.generate_job_config( file_name="test_task.yaml", task_states=task_states ) # Create job with customized tasks. job = Job(job_config=test_config) job.create() log.info("Job for task query is created: %s", job.job_id) # Determine terminating state. job_state = task_states[0][0] if not mixed_task_states else "FAILED" if job_state == "FAILED": job.wait_for_state(goal_state="FAILED", failed_state="SUCCEEDED") else: job.wait_for_state(goal_state=job_state) def stop_job(): state = job_pb2.JobState.Name(job.get_runtime().state) if state in ACTIVE_JOB_STATES: job.stop() job.wait_for_state(goal_state="KILLED") request.addfinalizer(stop_job) return job.job_id """ Setup/cleanup fixture that replaces a regular Mesos agent with another one that has "peloton/exclusive" attribute. Cleanup does the exact opposite. """ @pytest.fixture def exclusive_host(request): def clean_up(): teardown_mesos_agent(mc_config, 0, is_exclusive=True) run_mesos_agent(mc_config, 0, 0) time.sleep(5) # Remove agent #0 and instead create exclusive agent #0 teardown_mesos_agent(mc_config, 0) run_mesos_agent( mc_config, 0, 3, is_exclusive=True, exclusive_label_value="exclusive-test-label", ) time.sleep(5) request.addfinalizer(clean_up)

26.961326

81

0.647746

import logging import os import pytest import time import grpc import requests from docker import Client from tools.minicluster.main import setup, teardown, config as mc_config from tools.minicluster.minicluster import run_mesos_agent, teardown_mesos_agent from host import start_maintenance, complete_maintenance, wait_for_host_state from job import Job from job import query_jobs as batch_query_jobs from job import kill_jobs as batch_kill_jobs from stateless_job import StatelessJob from stateless_job import query_jobs as stateless_query_jobs from stateless_job import delete_jobs as stateless_delete_jobs from m3.client import M3 from m3.emitter import BatchedEmitter from peloton_client.pbgen.peloton.api.v0.host import host_pb2 from peloton_client.pbgen.peloton.api.v0.job import job_pb2 from conf_util import ( TERMINAL_JOB_STATES, ACTIVE_JOB_STATES, MESOS_MASTER, MESOS_AGENTS, ) import conf_util as util log = logging.getLogger(__name__) class TestMetrics(object): def __init__(self): self.failed = 0 self.passed = 0 self.duration = 0.0 def increment_passed(self, duration): self.passed += 1 self.duration += duration def increment_failed(self, duration): self.failed += 1 self.duration += duration collect_metrics = TestMetrics() @pytest.fixture(scope="module", autouse=True) def setup_cluster(request): tests_failed_before_module = request.session.testsfailed setup_minicluster() def teardown_cluster(): dump_logs = False if (request.session.testsfailed - tests_failed_before_module) > 0: dump_logs = True teardown_minicluster(dump_logs) request.addfinalizer(teardown_cluster) @pytest.fixture(autouse=True) def run_around_tests(): yield cleanup_batch_jobs() @pytest.hookimpl(hookwrapper=True) def pytest_runtest_makereport(item, call): global collect_metrics outcome = yield rep = outcome.get_result() if rep.outcome == "passed" and rep.when == "call": collect_metrics.increment_passed(rep.duration) if rep.outcome == "failed" and rep.when == "call": collect_metrics.increment_failed(rep.duration) rep = outcome.get_result() setattr(item, "rep_" + rep.when, rep) if "incremental" in item.keywords: if call.excinfo is not None: parent = item.parent parent._previousfailed = item def pytest_sessionfinish(session, exitstatus): emitter = BatchedEmitter() m3 = M3( application_identifier="peloton", emitter=emitter, environment="production", default_tags={"result": "watchdog", "cluster": os.getenv("CLUSTER")}, ) if collect_metrics.failed > 0: m3.gauge("watchdog_result", 1) else: m3.gauge("watchdog_result", 0) m3.gauge("total_tests", collect_metrics.failed + collect_metrics.passed) m3.gauge("failed_tests", collect_metrics.failed) m3.gauge("passed_tests", collect_metrics.passed) m3.gauge("duration_tests", collect_metrics.duration) class Container(object): def __init__(self, names): self._cli = Client(base_url="unix://var/run/docker.sock") self._names = names def start(self): for name in self._names: self._cli.start(name) log.info("%s started", name) if self._names[0] in MESOS_MASTER: wait_for_mesos_master_leader() def stop(self): for name in self._names: self._cli.stop(name, timeout=0) log.info("%s stopped", name) def restart(self): for name in self._names: self._cli.restart(name, timeout=0) log.info("%s restarted", name) if self._names[0] in MESOS_MASTER: wait_for_mesos_master_leader() def get_container(container_name): return Container(container_name) def wait_for_mesos_master_leader( url="http://127.0.0.1:5050/state.json", timeout_secs=20 ): deadline = time.time() + timeout_secs while time.time() < deadline: try: resp = requests.get(url) if resp.status_code != 200: time.sleep(2) continue return except Exception: pass assert False, "timed out waiting for mesos master leader" def wait_for_all_agents_to_register( url="http://127.0.0.1:5050/state.json", timeout_secs=300, ): deadline = time.time() + timeout_secs while time.time() < deadline: try: resp = requests.get(url) if resp.status_code == 200: registered_agents = 0 for a in resp.json()['slaves']: if a['active'] == True: registered_agents += 1 if registered_agents == 3: return time.sleep(10) except Exception: pass assert False, "timed out waiting for agents to register" def setup_minicluster(enable_k8s=False): log.info("setup cluster") if os.getenv("CLUSTER", ""): log.info("cluster mode") else: log.info("local minicluster mode") setup(enable_peloton=True, enable_k8s=enable_k8s) time.sleep(5) def teardown_minicluster(dump_logs=False): log.info("\nteardown cluster") if os.getenv("CLUSTER", ""): log.info("cluster mode, no teardown actions") elif os.getenv("NO_TEARDOWN", ""): log.info("skip teardown") else: log.info("tearing down") if dump_logs: teardown(stop=True) try: cli = Client(base_url="unix://var/run/docker.sock") for c in ("peloton-jobmgr0", "peloton-resmgr0"): for l in cli.logs(c, stream=True): log.info(l.rstrip()) except Exception as e: log.info(e) teardown() def cleanup_batch_jobs(): jobs = batch_query_jobs() batch_kill_jobs(jobs) def cleanup_stateless_jobs(timeout_secs=10): jobs = stateless_query_jobs() stateless_delete_jobs(jobs) deadline = time.time() + timeout_secs while time.time() < deadline: try: jobs = stateless_query_jobs() if len(jobs) == 0: return time.sleep(2) except grpc.RpcError as e: if e.code() == grpc.StatusCode.NOT_FOUND: time.sleep(2) continue @pytest.fixture() def mesos_master(): return Container(MESOS_MASTER) @pytest.fixture() def mesos_agent(): return Container(MESOS_AGENTS) @pytest.fixture() def placement_engines(): return Container(util.PLACEMENT_ENGINES) @pytest.fixture() def jobmgr(): return Container(util.JOB_MGRS) @pytest.fixture() def resmgr(): return Container(util.RES_MGRS) @pytest.fixture() def hostmgr(): return Container(util.HOST_MGRS) @pytest.fixture() def aurorabridge(): return Container(util.AURORA_BRIDGE) @pytest.fixture def long_running_job(request): job = Job(job_file="long_running_job.yaml") def kill_long_running_job(): print("\nstopping long running job") job.stop() request.addfinalizer(kill_long_running_job) return job @pytest.fixture def stateless_job(request): job = StatelessJob() def kill_stateless_job(): print("\nstopping stateless job") job.stop() request.addfinalizer(kill_stateless_job) return job @pytest.fixture def host_affinity_job(request): job = Job(job_file="test_job_host_affinity_constraint.yaml") def kill_host_affinity_job(): print("\nstopping host affinity job") job.stop() request.addfinalizer(kill_host_affinity_job) return job @pytest.fixture(params=[True, False]) def in_place(request): return request.param @pytest.fixture def maintenance(request): draining_hosts = [] client = [None] def update_client(new_client): client[0] = new_client def start(hosts): resp = start_maintenance(hosts) if not resp: log.error("Start maintenance failed:" + resp) return resp draining_hosts.extend(hosts) return resp def stop(hosts): resp = complete_maintenance(hosts) if not resp: log.error("Complete maintenance failed:" + resp) return resp Container(hosts).start() del draining_hosts[:] return resp def clean_up(): for j in stateless_query_jobs(client=client[0]): j.stop() if not draining_hosts: return for h in draining_hosts: wait_for_host_state(h, host_pb2.HOST_STATE_DOWN) stop(draining_hosts) request.addfinalizer(clean_up) response = dict() response["start"] = start response["stop"] = stop response["update_client"] = update_client return response @pytest.fixture def jobs_by_state(request): return util.create_job_config_by_state(_num_jobs_per_state=1) @pytest.fixture(scope="module") def create_jobs(request): jobs_by_state = util.create_job_config_by_state() salt = jobs_by_state[0] jobs_dict = jobs_by_state[1] log.info("Create jobs") respoolID = None for state in TERMINAL_JOB_STATES: jobs = jobs_dict[state] for job in jobs: job.create() if state == "FAILED": job.wait_for_state( goal_state="FAILED", failed_state="SUCCEEDED" ) else: job.wait_for_state(goal_state=state) if respoolID is None: respoolID = job.get_config().respoolID def stop_jobs(): log.info("Stop jobs") for state in TERMINAL_JOB_STATES: jobs = jobs_dict[state] for job in jobs: state = job_pb2.JobState.Name(job.get_runtime().state) if state in ACTIVE_JOB_STATES: job.stop() job.wait_for_state(goal_state="KILLED") request.addfinalizer(stop_jobs) time.sleep(12) return salt, respoolID, jobs_dict @pytest.fixture def task_test_fixture(request): task_states = request.param assert task_states is not None if len(task_states) > 1: mixed_task_states = True else: mixed_task_states = False test_config = util.generate_job_config( file_name="test_task.yaml", task_states=task_states ) job = Job(job_config=test_config) job.create() log.info("Job for task query is created: %s", job.job_id) job_state = task_states[0][0] if not mixed_task_states else "FAILED" if job_state == "FAILED": job.wait_for_state(goal_state="FAILED", failed_state="SUCCEEDED") else: job.wait_for_state(goal_state=job_state) def stop_job(): state = job_pb2.JobState.Name(job.get_runtime().state) if state in ACTIVE_JOB_STATES: job.stop() job.wait_for_state(goal_state="KILLED") request.addfinalizer(stop_job) return job.job_id @pytest.fixture def exclusive_host(request): def clean_up(): teardown_mesos_agent(mc_config, 0, is_exclusive=True) run_mesos_agent(mc_config, 0, 0) time.sleep(5) run_mesos_agent( mc_config, 0, 3, is_exclusive=True, exclusive_label_value="exclusive-test-label", ) time.sleep(5) request.addfinalizer(clean_up)

true

f738daab38d0ea2df36ed71b54b64b00c4cdf066

2,876

py

Python

google/cloud/securitycenter/v1/securitycenter-v1-py/google/cloud/securitycenter_v1/types/source.py

googleapis/googleapis-gen

d84824c78563d59b0e58d5664bfaa430e9ad7e7a

[ "Apache-2.0" ]

7

2021-02-21T10:39:41.000Z

2021-12-07T07:31:28.000Z

google/cloud/securitycenter/v1/securitycenter-v1-py/google/cloud/securitycenter_v1/types/source.py

googleapis/googleapis-gen

d84824c78563d59b0e58d5664bfaa430e9ad7e7a

[ "Apache-2.0" ]

6

2021-02-02T23:46:11.000Z

2021-11-15T01:46:02.000Z

google/cloud/securitycenter/v1/securitycenter-v1-py/google/cloud/securitycenter_v1/types/source.py

googleapis/googleapis-gen

d84824c78563d59b0e58d5664bfaa430e9ad7e7a

[ "Apache-2.0" ]

4

2021-01-28T23:25:45.000Z

2021-08-30T01:55:16.000Z

# -*- coding: utf-8 -*- # Copyright 2020 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 # # 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 proto # type: ignore __protobuf__ = proto.module( package='google.cloud.securitycenter.v1', manifest={ 'Source', }, ) class Source(proto.Message): r"""Security Command Center finding source. A finding source is an entity or a mechanism that can produce a finding. A source is like a container of findings that come from the same scanner, logger, monitor, and other tools. Attributes: name (str): The relative resource name of this source. See: https://cloud.google.com/apis/design/resource_names#relative_resource_name Example: "organizations/{organization_id}/sources/{source_id}". display_name (str): The source's display name. A source's display name must be unique amongst its siblings, for example, two sources with the same parent can't share the same display name. The display name must have a length between 1 and 64 characters (inclusive). description (str): The description of the source (max of 1024 characters). Example: "Web Security Scanner is a web security scanner for common vulnerabilities in App Engine applications. It can automatically scan and detect four common vulnerabilities, including cross-site-scripting (XSS), Flash injection, mixed content (HTTP in HTTPS), and outdated or insecure libraries.". canonical_name (str): The canonical name of the finding. It's either "organizations/{organization_id}/sources/{source_id}", "folders/{folder_id}/sources/{source_id}" or "projects/{project_number}/sources/{source_id}", depending on the closest CRM ancestor of the resource associated with the finding. """ name = proto.Field( proto.STRING, number=1, ) display_name = proto.Field( proto.STRING, number=2, ) description = proto.Field( proto.STRING, number=3, ) canonical_name = proto.Field( proto.STRING, number=14, ) __all__ = tuple(sorted(__protobuf__.manifest))

34.238095

86

0.645688

import proto __protobuf__ = proto.module( package='google.cloud.securitycenter.v1', manifest={ 'Source', }, ) class Source(proto.Message): name = proto.Field( proto.STRING, number=1, ) display_name = proto.Field( proto.STRING, number=2, ) description = proto.Field( proto.STRING, number=3, ) canonical_name = proto.Field( proto.STRING, number=14, ) __all__ = tuple(sorted(__protobuf__.manifest))

true

f738db5484d20dc4c77a6d9f4274781afffe802a

5,607

py

Python

recip/network/messages/extensions/types/Account.py

anthonybuckle/Reciprocity-Core

3254073f44e8fe2222aed9879885a2e609d4044a

[ "MIT" ]

null

recip/network/messages/extensions/types/Account.py

anthonybuckle/Reciprocity-Core

3254073f44e8fe2222aed9879885a2e609d4044a

[ "MIT" ]

null

recip/network/messages/extensions/types/Account.py

anthonybuckle/Reciprocity-Core

3254073f44e8fe2222aed9879885a2e609d4044a

[ "MIT" ]

null

from recip.network.messages.extensions.ExtMessage import ExtMessage from recip.network.messages.extensions import ExtMessageType from recip.core.Account import Account as CoreAccount from recip.core import AccountType from recip.storage import Accounts from recip.util import Address from recip.util import Crypto from recip.util import DataType from recip.util import JSONRPC from recip.util import Validator from recip.util import Units class Account(ExtMessage): def __init__(self): super().__init__() self.publicKeys = [] self.address = [] def validate(self): if self.address == None or self.publicKeys == None: return False for publicKey in self.publicKeys: if not Validator.public(publicKey): return False for addr in self.address: if not Validator.address(addr): return False return True def deserialize(self, payload): if self.validatePayload(payload): self.deserializePayload(payload) if self.validateParameters(): if self.isMultiSig(): for publicKey in self.params: publicKey = DataType.fromHex(publicKey) self.publicKeys.append(publicKey) else: for addr in self.params: addr = Address.toAddressBytes(addr) self.address.append(addr) if self.validate(): return True return False def onSuccess(self, callback = None): if ExtMessageType.CREATE_ATOMIC_SWAP_ACCOUNT == self.method: self.createAtomicSwapAccount(callback) elif ExtMessageType.CREATE_MULTISIG_ACCOUNT == self.method: self.createMultiSigAccount(callback) elif ExtMessageType.GET_ACCOUNTS == self.method: self.get(callback) elif ExtMessageType.GET_NEW_ACCOUNT == self.method: self.add(callback) elif ExtMessageType.DELETE_ACCOUNTS == self.method: self.remove(callback) else: self.onFailure(callback) def isMultiSig(self): if ExtMessageType.CREATE_MULTISIG_ACCOUNT == self.method: return True if ExtMessageType.CREATE_ATOMIC_SWAP_ACCOUNT == self.method: return True return False def createAtomicSwapAccount(self, callback = None): _address, _public, _private = Crypto.generateKeys() privateBytes = bytearray() privateBytes.extend(_address) privateBytes.extend(_public) privateBytes.extend(_private) privateKey = Crypto.generateHash(privateBytes) self.createNewMultiSigAccountType(AccountType.ATOMIC_SWAP, privateKey, callback) def createMultiSigAccount(self, callback = None): self.createNewMultiSigAccountType(AccountType.MULTISIGNATURE, None, callback) def createNewMultiSigAccountType(self, accountType, privateKey, callback = None): multiSigAddressBytes = bytearray() for publicKey in self.publicKeys: multiSigAddressBytes.extend(publicKey) multiSigAddress = Crypto.generateAddress(multiSigAddressBytes) account = CoreAccount(multiSigAddress, self.publicKeys, privateKey, accountType) Accounts.addAccount(account) multiSigAddress = Address.to0xAddress(multiSigAddress) callback( JSONRPC.createResultObject(multiSigAddress, self.id) ) def get(self, callback = None): accounts = [] # Account Types standard = [] multisig = [] atomicswap = [] for account in Accounts.getAccounts(): confirmedBalance = Accounts.getConfirmedBalanceByAddress(account.address) confirmedBalance = Units.toValue(confirmedBalance) confirmedBalance = DataType.asFloat(confirmedBalance) address = Address.to0xAddress(account.address) accountInfo = { 'address': address, 'type': account.type, 'balance': confirmedBalance } if account.type == AccountType.STANDARD: standard.append(accountInfo) elif account.type == AccountType.MULTISIGNATURE: multisig.append(accountInfo) elif account.type == AccountType.ATOMIC_SWAP: atomicswap.append(accountInfo) accounts.extend(standard) accounts.extend(multisig) accounts.extend(atomicswap) callback( JSONRPC.createResultObject(accounts, self.id) ) def add(self, callback = None): account = CoreAccount() Accounts.addAccount(account) address = Address.to0xAddress(account.address) callback( JSONRPC.createResultObject(address, self.id) ) def remove(self, callback = None): removed = False for addr in self.address: removed = Accounts.removeAccount(addr) if not removed: break if removed: callback( JSONRPC.createResultObject('accounts removed', self.id) ) else: callback( JSONRPC.createErrorObject(-32003, 'delete failed', 'failed to remove accounts', self.id) ) def onFailure(self, callback = None): callback( JSONRPC.createErrorObject(-32000, 'invalid message', 'invalid account request', self.id) )

38.142857

104

0.622258

from recip.network.messages.extensions.ExtMessage import ExtMessage from recip.network.messages.extensions import ExtMessageType from recip.core.Account import Account as CoreAccount from recip.core import AccountType from recip.storage import Accounts from recip.util import Address from recip.util import Crypto from recip.util import DataType from recip.util import JSONRPC from recip.util import Validator from recip.util import Units class Account(ExtMessage): def __init__(self): super().__init__() self.publicKeys = [] self.address = [] def validate(self): if self.address == None or self.publicKeys == None: return False for publicKey in self.publicKeys: if not Validator.public(publicKey): return False for addr in self.address: if not Validator.address(addr): return False return True def deserialize(self, payload): if self.validatePayload(payload): self.deserializePayload(payload) if self.validateParameters(): if self.isMultiSig(): for publicKey in self.params: publicKey = DataType.fromHex(publicKey) self.publicKeys.append(publicKey) else: for addr in self.params: addr = Address.toAddressBytes(addr) self.address.append(addr) if self.validate(): return True return False def onSuccess(self, callback = None): if ExtMessageType.CREATE_ATOMIC_SWAP_ACCOUNT == self.method: self.createAtomicSwapAccount(callback) elif ExtMessageType.CREATE_MULTISIG_ACCOUNT == self.method: self.createMultiSigAccount(callback) elif ExtMessageType.GET_ACCOUNTS == self.method: self.get(callback) elif ExtMessageType.GET_NEW_ACCOUNT == self.method: self.add(callback) elif ExtMessageType.DELETE_ACCOUNTS == self.method: self.remove(callback) else: self.onFailure(callback) def isMultiSig(self): if ExtMessageType.CREATE_MULTISIG_ACCOUNT == self.method: return True if ExtMessageType.CREATE_ATOMIC_SWAP_ACCOUNT == self.method: return True return False def createAtomicSwapAccount(self, callback = None): _address, _public, _private = Crypto.generateKeys() privateBytes = bytearray() privateBytes.extend(_address) privateBytes.extend(_public) privateBytes.extend(_private) privateKey = Crypto.generateHash(privateBytes) self.createNewMultiSigAccountType(AccountType.ATOMIC_SWAP, privateKey, callback) def createMultiSigAccount(self, callback = None): self.createNewMultiSigAccountType(AccountType.MULTISIGNATURE, None, callback) def createNewMultiSigAccountType(self, accountType, privateKey, callback = None): multiSigAddressBytes = bytearray() for publicKey in self.publicKeys: multiSigAddressBytes.extend(publicKey) multiSigAddress = Crypto.generateAddress(multiSigAddressBytes) account = CoreAccount(multiSigAddress, self.publicKeys, privateKey, accountType) Accounts.addAccount(account) multiSigAddress = Address.to0xAddress(multiSigAddress) callback( JSONRPC.createResultObject(multiSigAddress, self.id) ) def get(self, callback = None): accounts = [] standard = [] multisig = [] atomicswap = [] for account in Accounts.getAccounts(): confirmedBalance = Accounts.getConfirmedBalanceByAddress(account.address) confirmedBalance = Units.toValue(confirmedBalance) confirmedBalance = DataType.asFloat(confirmedBalance) address = Address.to0xAddress(account.address) accountInfo = { 'address': address, 'type': account.type, 'balance': confirmedBalance } if account.type == AccountType.STANDARD: standard.append(accountInfo) elif account.type == AccountType.MULTISIGNATURE: multisig.append(accountInfo) elif account.type == AccountType.ATOMIC_SWAP: atomicswap.append(accountInfo) accounts.extend(standard) accounts.extend(multisig) accounts.extend(atomicswap) callback( JSONRPC.createResultObject(accounts, self.id) ) def add(self, callback = None): account = CoreAccount() Accounts.addAccount(account) address = Address.to0xAddress(account.address) callback( JSONRPC.createResultObject(address, self.id) ) def remove(self, callback = None): removed = False for addr in self.address: removed = Accounts.removeAccount(addr) if not removed: break if removed: callback( JSONRPC.createResultObject('accounts removed', self.id) ) else: callback( JSONRPC.createErrorObject(-32003, 'delete failed', 'failed to remove accounts', self.id) ) def onFailure(self, callback = None): callback( JSONRPC.createErrorObject(-32000, 'invalid message', 'invalid account request', self.id) )

true

f738db80f9cc00ed7e5eb5f0b2d93c033d9219fc

6,378

py

Python

src/datasets/Fruits360/f360_dataset.py

JoseLuisRojasAranda/tfmodels

56dce0236f0cc03dd7031aecf305d470c9fb97a9

[ "MIT" ]

1

2020-06-05T23:25:03.000Z

src/datasets/Fruits360/f360_dataset.py

JoseLuisRojasAranda/tfmodels

56dce0236f0cc03dd7031aecf305d470c9fb97a9

[ "MIT" ]

null

src/datasets/Fruits360/f360_dataset.py

JoseLuisRojasAranda/tfmodels

56dce0236f0cc03dd7031aecf305d470c9fb97a9

[ "MIT" ]

null

import tensorflow as tf import cv2 from glob import glob import sys import os from os import path import json import random from datasets.datasets_features import bytes_feature # Metodo que regresa el dataset de f360 ya procesado a tfrecord # Los data set tiene el formato: # x: tensor con la imagen normalizada # y: tensor con onehot encoding de la categoria # Returns: # train_data: Dataset de entrenameinto # test_data: Dataset de pruebas def f360_load_dataset(path=None, resize=None, num_classes=None): train_path = "f360_train.tfrecord" test_path = "f360_test.tfrecord" if path == None: path = "" train_raw_data = tf.data.TFRecordDataset(path+train_path) test_raw_data = tf.data.TFRecordDataset(path+test_path) _format = { "x": tf.io.FixedLenFeature([], tf.string), "y": tf.io.FixedLenFeature([], tf.string) } def _parse_example(example): ex = tf.io.parse_single_example(example, _format) x = tf.io.parse_tensor(ex["x"], tf.float32) y = tf.io.parse_tensor(ex["y"], tf.float32) y = tf.reshape(y, [-1]) data_dict = { "x": x, "y": y } return x, y train_data = train_raw_data.map(_parse_example) test_data = test_raw_data.map(_parse_example) def _set_dataset_shape(x, y): x.set_shape([100, 100, 3]) return x, y train_data = train_data.map(_set_dataset_shape) test_data = test_data.map(_set_dataset_shape) if resize != None: def _resize_dataset(x, y): x = tf.image.resize(x, [resize, resize]) return x, y train_data = train_data.map(_resize_dataset) test_data = test_data.map(_resize_dataset) with open(path+"dataset_info.json", "r") as data: info = json.load(data) return train_data, test_data, info # Metodo que convierte el dataset de Fruits 360 a tfrecord, para despues usarlo # con el Dataset API de tensorflow # Args: # training_path: el path al dataset de training # test_path: el path al dataset de pruebas # num_imgs: numero de images a obtener, -1 para todas # result_path: el path donde se guarda el resultado def f360_create_dataset(training_path=None, test_path=None, num_imgs=-1, result_path=None, delta=1, offset=0): # Crea la carpeta por si no existe donde se va a guardar el resultado if not path.exists(result_path): os.makedirs(result_path) process_cats = ["Apple Golden 1", "Banana", "Orange"] """ process_cats = ["Apple Braeburn", "Apple Golden 1", "Avocado", "Lemon", "Limes", "Lychee", "Mandarine", "Banana", "Onion White", "Onion White", "Pear", "Orange", "Pineapple", "Potato White", "Strawberry", "Tomato 4"] """ onehot_depth = len(process_cats) onehot_dict = { } for i in range(len(process_cats)): cat = process_cats[i] onehot_dict[cat] = i # Obtiene todas las categorias que existen cats = [x[1] for x in os.walk(training_path)][0] # Writer al tfrecord train_writer = tf.io.TFRecordWriter(result_path+"f360_train.tfrecord") test_writer = tf.io.TFRecordWriter(result_path+"f360_test.tfrecord") train_size = 0 test_size = 0 total_train_size = 0 total_test_size = 0 categories_size = { } # funcion que escribe una imagen al tfrecord def encode_image_info(image, category, writer): # Convierte la imagen a un tensor y lo normaliza image_tensor = tf.convert_to_tensor(image) image_tensor /= 255 category = tf.one_hot([onehot_dict[category]], onehot_depth) # Genera los features para el example data = { "x": bytes_feature(tf.io.serialize_tensor(image_tensor)), "y": bytes_feature(tf.io.serialize_tensor(category)) } example = tf.train.Example(features=tf.train.Features(feature=data)) writer.write(example.SerializeToString()) print("[INFO] Writing dataset to tfrecord") # itera sobre todas las categorias a procesar for cat in process_cats: # si la categoria existe if cat in cats: print("[INFO] Writing {}...".format(cat)) train_size = test_size = 0 # obtiene los paths train_img_path = glob(training_path+cat+"/*.jpg") test_img_path = glob(test_path+cat+"/*.jpg") # Ordena los paths train_img_path = sorted(train_img_path) test_img_path = sorted(test_img_path) # el numero de imagenes a que se van a ciclar n_train = n_test = num_imgs if n_train == -1: n_train = len(train_img_path) n_test = len(test_img_path) i = offset j = 0 total = 0 # escribe training images """ for i in range(n_train): img_path = train_img_path[i] image = cv2.imread(img_path) encode_image_info(image, cat, train_writer) train_size += 1 """ while total < n_train: img_path = train_img_path[i] image = cv2.imread(img_path) encode_image_info(image, cat, train_writer) train_size += 1 #i += random.randint(10, 20) i += delta if i >= n_train: i = i - n_train total += delta # escribe test images for j in range(n_test): img_path = test_img_path[j] image = cv2.imread(img_path) encode_image_info(image, cat, test_writer) test_size += 1 categories_size[cat] = (train_size, test_size) total_train_size += train_size total_test_size += test_size train_writer.close() test_writer.close() dataset_info = { "name": "Fruits 360 dataset", "num_classes": len(process_cats), "delta": delta, "offset": offset, "categories": process_cats, "train_size": total_train_size, "test_size": total_test_size, "categories_size": categories_size } # Escribe el info del dataset with open(result_path+"dataset_info.json", "w") as writer: json.dump(dataset_info, writer, indent=4)

31.418719

80

0.611007

import tensorflow as tf import cv2 from glob import glob import sys import os from os import path import json import random from datasets.datasets_features import bytes_feature def f360_load_dataset(path=None, resize=None, num_classes=None): train_path = "f360_train.tfrecord" test_path = "f360_test.tfrecord" if path == None: path = "" train_raw_data = tf.data.TFRecordDataset(path+train_path) test_raw_data = tf.data.TFRecordDataset(path+test_path) _format = { "x": tf.io.FixedLenFeature([], tf.string), "y": tf.io.FixedLenFeature([], tf.string) } def _parse_example(example): ex = tf.io.parse_single_example(example, _format) x = tf.io.parse_tensor(ex["x"], tf.float32) y = tf.io.parse_tensor(ex["y"], tf.float32) y = tf.reshape(y, [-1]) data_dict = { "x": x, "y": y } return x, y train_data = train_raw_data.map(_parse_example) test_data = test_raw_data.map(_parse_example) def _set_dataset_shape(x, y): x.set_shape([100, 100, 3]) return x, y train_data = train_data.map(_set_dataset_shape) test_data = test_data.map(_set_dataset_shape) if resize != None: def _resize_dataset(x, y): x = tf.image.resize(x, [resize, resize]) return x, y train_data = train_data.map(_resize_dataset) test_data = test_data.map(_resize_dataset) with open(path+"dataset_info.json", "r") as data: info = json.load(data) return train_data, test_data, info def f360_create_dataset(training_path=None, test_path=None, num_imgs=-1, result_path=None, delta=1, offset=0): if not path.exists(result_path): os.makedirs(result_path) process_cats = ["Apple Golden 1", "Banana", "Orange"] onehot_depth = len(process_cats) onehot_dict = { } for i in range(len(process_cats)): cat = process_cats[i] onehot_dict[cat] = i cats = [x[1] for x in os.walk(training_path)][0] train_writer = tf.io.TFRecordWriter(result_path+"f360_train.tfrecord") test_writer = tf.io.TFRecordWriter(result_path+"f360_test.tfrecord") train_size = 0 test_size = 0 total_train_size = 0 total_test_size = 0 categories_size = { } def encode_image_info(image, category, writer): image_tensor = tf.convert_to_tensor(image) image_tensor /= 255 category = tf.one_hot([onehot_dict[category]], onehot_depth) data = { "x": bytes_feature(tf.io.serialize_tensor(image_tensor)), "y": bytes_feature(tf.io.serialize_tensor(category)) } example = tf.train.Example(features=tf.train.Features(feature=data)) writer.write(example.SerializeToString()) print("[INFO] Writing dataset to tfrecord") for cat in process_cats: if cat in cats: print("[INFO] Writing {}...".format(cat)) train_size = test_size = 0 train_img_path = glob(training_path+cat+"/*.jpg") test_img_path = glob(test_path+cat+"/*.jpg") train_img_path = sorted(train_img_path) test_img_path = sorted(test_img_path) n_train = n_test = num_imgs if n_train == -1: n_train = len(train_img_path) n_test = len(test_img_path) i = offset j = 0 total = 0 while total < n_train: img_path = train_img_path[i] image = cv2.imread(img_path) encode_image_info(image, cat, train_writer) train_size += 1 i += delta if i >= n_train: i = i - n_train total += delta for j in range(n_test): img_path = test_img_path[j] image = cv2.imread(img_path) encode_image_info(image, cat, test_writer) test_size += 1 categories_size[cat] = (train_size, test_size) total_train_size += train_size total_test_size += test_size train_writer.close() test_writer.close() dataset_info = { "name": "Fruits 360 dataset", "num_classes": len(process_cats), "delta": delta, "offset": offset, "categories": process_cats, "train_size": total_train_size, "test_size": total_test_size, "categories_size": categories_size } with open(result_path+"dataset_info.json", "w") as writer: json.dump(dataset_info, writer, indent=4)

true

f738dc133f66e48df7c43829949098c52214b42c

256

py

Python

src/airfly/_vendor/airflow/decorators/python.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

7

2021-09-27T11:38:48.000Z

2022-02-01T06:06:24.000Z

src/airfly/_vendor/airflow/decorators/python.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

src/airfly/_vendor/airflow/decorators/python.py

ryanchao2012/airfly

230ddd88885defc67485fa0c51f66c4a67ae98a9

[ "MIT" ]

null

# Auto generated by 'inv collect-airflow' from airfly._vendor.airflow.decorators.base import DecoratedOperator from airfly._vendor.airflow.operators.python import PythonOperator class _PythonDecoratedOperator(DecoratedOperator, PythonOperator): pass

32

68

0.84375

from airfly._vendor.airflow.decorators.base import DecoratedOperator from airfly._vendor.airflow.operators.python import PythonOperator class _PythonDecoratedOperator(DecoratedOperator, PythonOperator): pass

true

f738dc15aae4bc9e8704d6dc10a845408ad63b2e

1,759

py

Python

src/main/python/pybuilder/_vendor/virtualenv/seed/wheels/embed/__init__.py

arcivanov/pybuilder

419dd58cf52b1547ca1044e8e1f6b9faa47fadec

[ "Apache-2.0" ]

null

src/main/python/pybuilder/_vendor/virtualenv/seed/wheels/embed/__init__.py

arcivanov/pybuilder

419dd58cf52b1547ca1044e8e1f6b9faa47fadec

[ "Apache-2.0" ]

6

2021-09-05T06:00:20.000Z

2021-11-07T08:26:55.000Z

src/main/python/pybuilder/_vendor/virtualenv/seed/wheels/embed/__init__.py

ufo2011/pybuilder

9cb589c11f743e4f9e3a9051184471206b1d7c3b

[ "Apache-2.0" ]

1

2020-02-22T05:25:50.000Z

from __future__ import absolute_import, unicode_literals from ..util import Wheel from ....util.path import Path BUNDLE_FOLDER = Path(__file__).absolute().parent BUNDLE_SUPPORT = { "3.10": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.9": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.8": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.7": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.6": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.5": { "pip": "pip-20.3.4-py2.py3-none-any.whl", "setuptools": "setuptools-50.3.2-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "2.7": { "pip": "pip-20.3.4-py2.py3-none-any.whl", "setuptools": "setuptools-44.1.1-py2.py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, } MAX = "3.10" def get_embed_wheel(distribution, for_py_version): path = BUNDLE_FOLDER / (BUNDLE_SUPPORT.get(for_py_version, {}) or BUNDLE_SUPPORT[MAX]).get(distribution) return Wheel.from_path(path) __all__ = ( "get_embed_wheel", "BUNDLE_SUPPORT", "MAX", "BUNDLE_FOLDER", )

30.327586

108

0.572484

from __future__ import absolute_import, unicode_literals from ..util import Wheel from ....util.path import Path BUNDLE_FOLDER = Path(__file__).absolute().parent BUNDLE_SUPPORT = { "3.10": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.9": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.8": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.7": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.6": { "pip": "pip-21.3.1-py3-none-any.whl", "setuptools": "setuptools-58.3.0-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "3.5": { "pip": "pip-20.3.4-py2.py3-none-any.whl", "setuptools": "setuptools-50.3.2-py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, "2.7": { "pip": "pip-20.3.4-py2.py3-none-any.whl", "setuptools": "setuptools-44.1.1-py2.py3-none-any.whl", "wheel": "wheel-0.37.0-py2.py3-none-any.whl", }, } MAX = "3.10" def get_embed_wheel(distribution, for_py_version): path = BUNDLE_FOLDER / (BUNDLE_SUPPORT.get(for_py_version, {}) or BUNDLE_SUPPORT[MAX]).get(distribution) return Wheel.from_path(path) __all__ = ( "get_embed_wheel", "BUNDLE_SUPPORT", "MAX", "BUNDLE_FOLDER", )

true

f738dc24263c0009dbd5d4831b0b1b62ca5c82ef

309

py

Python

05/5.5.py

abe-101/ThinkPython-2

bcebb1e9b3cc63c403f59c3cc0f33017bb017363

[ "MIT" ]

1

2021-12-16T16:46:47.000Z

05/5.5.py

abe-101/ThinkPython-2

bcebb1e9b3cc63c403f59c3cc0f33017bb017363

[ "MIT" ]

null

05/5.5.py

abe-101/ThinkPython-2

bcebb1e9b3cc63c403f59c3cc0f33017bb017363

[ "MIT" ]

null

#!/usr/bin/python3 import turtle def draw(t, length, n): if n == 0: return angle = 50 t.fd(length*n) t.lt(angle) draw(t, length, n-1) t.rt(2*angle) draw(t, length, n-1) t.lt(angle) t.bk(length*n) bob = turtle.Turtle() print(bob) draw(bob, 7, 5) turtle.mainloop()

15.45

24

0.563107

import turtle def draw(t, length, n): if n == 0: return angle = 50 t.fd(length*n) t.lt(angle) draw(t, length, n-1) t.rt(2*angle) draw(t, length, n-1) t.lt(angle) t.bk(length*n) bob = turtle.Turtle() print(bob) draw(bob, 7, 5) turtle.mainloop()

true

f738dc71bfd7d43ffae7f7d4c2c4ec1081620eff

890

py

Python

tests/test_html_escaping.py

PureDreamer/lms

4e4c2030f4f51a552e1fbfe82c16dc837e95310c

[ "BSD-3-Clause" ]

85

2020-03-21T18:52:57.000Z

2022-03-22T06:33:38.000Z

tests/test_html_escaping.py

PureDreamer/lms

4e4c2030f4f51a552e1fbfe82c16dc837e95310c

[ "BSD-3-Clause" ]

210

2020-03-21T22:44:57.000Z

2022-01-06T22:47:50.000Z

tests/test_html_escaping.py

PureDreamer/lms

4e4c2030f4f51a552e1fbfe82c16dc837e95310c

[ "BSD-3-Clause" ]

27

2020-03-31T13:57:33.000Z

2022-03-06T15:57:32.000Z

from flask import json from lms.lmsdb.models import Solution, User from tests import conftest USER_COMMENT_BEFORE_ESCAPING = '<html><body>Welcome "LMS"</body></html>' USER_COMMENT_AFTER_ESCAPING = ( '<html><body>Welcome "LMS"' '</body></html>' ) class TestHtmlEscaping: @staticmethod def test_comment_text_escaping(student_user: User, solution: Solution): client = conftest.get_logged_user(student_user.username) comment_response = client.post('/comments', data=json.dumps({ 'fileId': solution.files[0].id, 'act': 'create', 'kind': 'text', 'comment': USER_COMMENT_BEFORE_ESCAPING, 'line': 1, }), content_type='application/json') assert comment_response.status_code == 200 assert solution.comments[0].comment.text == USER_COMMENT_AFTER_ESCAPING

35.6

79

0.689888

from flask import json from lms.lmsdb.models import Solution, User from tests import conftest USER_COMMENT_BEFORE_ESCAPING = '<html><body>Welcome "LMS"</body></html>' USER_COMMENT_AFTER_ESCAPING = ( '<html><body>Welcome "LMS"' '</body></html>' ) class TestHtmlEscaping: @staticmethod def test_comment_text_escaping(student_user: User, solution: Solution): client = conftest.get_logged_user(student_user.username) comment_response = client.post('/comments', data=json.dumps({ 'fileId': solution.files[0].id, 'act': 'create', 'kind': 'text', 'comment': USER_COMMENT_BEFORE_ESCAPING, 'line': 1, }), content_type='application/json') assert comment_response.status_code == 200 assert solution.comments[0].comment.text == USER_COMMENT_AFTER_ESCAPING

true

f738dce996b7b83b3e2c5c20eda0dab44a0f28d3

64

py

Python

numbers.py

Arif8099/myNewRepository

7fe087a5fa0ce6b81238c0a2a1229cc30ac21aa7

[ "MIT" ]

null

numbers.py

Arif8099/myNewRepository

7fe087a5fa0ce6b81238c0a2a1229cc30ac21aa7

[ "MIT" ]

null

numbers.py

Arif8099/myNewRepository

7fe087a5fa0ce6b81238c0a2a1229cc30ac21aa7

[ "MIT" ]

null

for i in range(1,11): print(str(i)) print(list(range(1,11)))

12.8

24

0.625

for i in range(1,11): print(str(i)) print(list(range(1,11)))

true

f738dd6ff6034d08207c1bcd65c39091e0e5c9fb

6,621

py

Python

src/kestrel/codegen/pattern.py

vincentywdeng/kestrel-lang

91e61c179bef433f5dc2e9fb6edf184d38ae6173

[ "Apache-2.0" ]

119

2021-06-04T15:40:10.000Z

2022-03-24T09:56:53.000Z

src/kestrel/codegen/pattern.py

vincentywdeng/kestrel-lang

91e61c179bef433f5dc2e9fb6edf184d38ae6173

[ "Apache-2.0" ]

76

2021-06-04T15:06:10.000Z

2022-03-20T21:03:13.000Z

src/kestrel/codegen/pattern.py

vincentywdeng/kestrel-lang

91e61c179bef433f5dc2e9fb6edf184d38ae6173

[ "Apache-2.0" ]

28

2021-06-05T07:27:15.000Z

2022-01-20T18:43:47.000Z

import dateutil.parser import datetime import logging import re from kestrel.utils import dedup_dicts from kestrel.semantics import get_entity_table from kestrel.syntax.paramstix import parse_extended_stix_pattern from kestrel.exceptions import ( InvalidAttribute, UnsupportedStixSyntax, KestrelInternalError, ) from firepit.exceptions import InvalidAttr _logger = logging.getLogger(__name__) def or_patterns(patterns): bodies = [] time_range = [] for pattern in patterns: if pattern: pieces = pattern.split() if len(pieces) > 4 and pieces[-4] == "START" and pieces[-2] == "STOP": time_range.append((pieces[-3], pieces[-1])) bodies.append("(" + " ".join(pieces[:-4]) + ")") else: bodies.append(pattern) if bodies: if time_range: start = min([t[0] for t in time_range]) end = max([t[1] for t in time_range]) final_pattern = ( "(" + " OR ".join(bodies) + ")" + " START " + start + " STOP " + end ) else: final_pattern = " OR ".join(bodies) _logger.debug(f"or pattern merged: {final_pattern}") else: final_pattern = None _logger.info(f"all None patterns input into or_patterns()") return final_pattern def build_pattern( raw_pattern_body, time_range, start_offset, end_offset, symtable, store ): """Dereference variables in a STIX pattern and output the unfolded pattern.""" references = parse_extended_stix_pattern(raw_pattern_body) pattern_body = raw_pattern_body _logger.debug(f"building pattern for: {raw_pattern_body}") if references: _logger.debug(f"references found: {list(references.keys())}") var_attr_to_vals_str = _dereference_multiple_variables( store, symtable, references ) for var_attr, vals_str in var_attr_to_vals_str.items(): pattern_body = _replace_ref_with_op(pattern_body, var_attr, vals_str) _logger.debug(f'pattern body dereferred: "{pattern_body}"') if pattern_body and not time_range: try: ref_var_time_ranges = [ _get_variable_time_range(store, symtable, var_name) for var_name in references.keys() ] start = min([t[0] for t in ref_var_time_ranges]) end = max([t[1] for t in ref_var_time_ranges]) start_adj = start + datetime.timedelta(seconds=start_offset) end_adj = end + datetime.timedelta(seconds=end_offset) start_stix = start_adj.strftime("%Y-%m-%dT%H:%M:%S.000Z") stop_stix = end_adj.strftime("%Y-%m-%dT%H:%M:%S.000Z") time_range = (start_stix, stop_stix) _logger.debug(f"pattern time range computed: {time_range}") except InvalidAttribute: time_range = None _logger.warning( f"pattern time range searching failed on variable {var_name}" ) if pattern_body: if time_range: pattern = ( f"({pattern_body}) START t'{time_range[0]}' STOP t'{time_range[1]}'" ) else: pattern = f"{pattern_body}" _logger.debug(f'final pattern assembled: "{pattern}"') else: pattern = None _logger.info(f"empty pattern assembled") return pattern def build_pattern_from_ids(return_type, ids): if ids: return "[" + return_type + ":id IN (" + ", ".join(map(_type_value, ids)) + ")]" else: return None def _dereference_multiple_variables(store, symtable, references): return { var + "." + attr: "(" + ", ".join(map(_type_value, vals)) + ")" for var, attrs in references.items() for attr, vals in _dereference_variable(store, symtable, var, attrs).items() } def _dereference_variable(store, symtable, var_name, attributes): attr_line = ",".join(attributes) _logger.debug(f'deref "{var_name}" with attributes "{attr_line}"') var_entity_table = get_entity_table(var_name, symtable) try: store_return = store.lookup(var_entity_table, attr_line) except InvalidAttr as e: _logger.warning(f"cannot deref {attr_line}. Invalid attribute in firepit.") raise InvalidAttribute(e.message) attr_to_values = {k: [] for k in attributes} for row in store_return: for k, v in row.items(): if v and v not in attr_to_values[k]: attr_to_values[k].append(v) for k, v in attr_to_values.items(): if not v: raise InvalidAttribute(var_name + "." + k) _logger.debug(f"deref results: {str(attr_to_values)}") return attr_to_values def _get_variable_time_range(store, symtable, var_name): """ Returns: start (datetime.datetime): the time any entities is observed first. end (datetime.datetime): the time any entities is observed last. """ time_attr_line = ",".join(["first_observed", "last_observed"]) var_entity_table = get_entity_table(var_name, symtable) try: store_return = store.lookup(var_entity_table, time_attr_line) except InvalidAttr as e: raise InvalidAttribute(e.message) life_span = dedup_dicts(store_return) start = min([dateutil.parser.isoparse(e["first_observed"]) for e in life_span]) end = max([dateutil.parser.isoparse(e["last_observed"]) for e in life_span]) return start, end def _type_value(value): if isinstance(value, str): return f"'{value}'" elif isinstance(value, int): return str(value) elif isinstance(value, float): # pandas dataframe and sqlite may save integers as floats return str(round(value)) else: return str(value) def _replace_ref_with_op(pattern, var_attr, vals_str): # avoid adhesive parans/ops that prevent correct splitting pattern = re.sub(r"([=><\[\]])", r" \1 ", pattern) pieces = pattern.split() try: ref_index = pieces.index(var_attr) except ValueError: err_msg = f'cannot find "{var_attr}" when assembling pattern "{pattern}"' _logger.error(err_msg) raise KestrelInternalError(err_msg) if pieces[ref_index - 1] == "=": pieces[ref_index - 1] = "IN" pieces[ref_index] = vals_str else: raise UnsupportedStixSyntax( 'only "=" is supported before referred variable in parameterized STIX' ) return " ".join(pieces)

33.105

87

0.622414

import dateutil.parser import datetime import logging import re from kestrel.utils import dedup_dicts from kestrel.semantics import get_entity_table from kestrel.syntax.paramstix import parse_extended_stix_pattern from kestrel.exceptions import ( InvalidAttribute, UnsupportedStixSyntax, KestrelInternalError, ) from firepit.exceptions import InvalidAttr _logger = logging.getLogger(__name__) def or_patterns(patterns): bodies = [] time_range = [] for pattern in patterns: if pattern: pieces = pattern.split() if len(pieces) > 4 and pieces[-4] == "START" and pieces[-2] == "STOP": time_range.append((pieces[-3], pieces[-1])) bodies.append("(" + " ".join(pieces[:-4]) + ")") else: bodies.append(pattern) if bodies: if time_range: start = min([t[0] for t in time_range]) end = max([t[1] for t in time_range]) final_pattern = ( "(" + " OR ".join(bodies) + ")" + " START " + start + " STOP " + end ) else: final_pattern = " OR ".join(bodies) _logger.debug(f"or pattern merged: {final_pattern}") else: final_pattern = None _logger.info(f"all None patterns input into or_patterns()") return final_pattern def build_pattern( raw_pattern_body, time_range, start_offset, end_offset, symtable, store ): references = parse_extended_stix_pattern(raw_pattern_body) pattern_body = raw_pattern_body _logger.debug(f"building pattern for: {raw_pattern_body}") if references: _logger.debug(f"references found: {list(references.keys())}") var_attr_to_vals_str = _dereference_multiple_variables( store, symtable, references ) for var_attr, vals_str in var_attr_to_vals_str.items(): pattern_body = _replace_ref_with_op(pattern_body, var_attr, vals_str) _logger.debug(f'pattern body dereferred: "{pattern_body}"') if pattern_body and not time_range: try: ref_var_time_ranges = [ _get_variable_time_range(store, symtable, var_name) for var_name in references.keys() ] start = min([t[0] for t in ref_var_time_ranges]) end = max([t[1] for t in ref_var_time_ranges]) start_adj = start + datetime.timedelta(seconds=start_offset) end_adj = end + datetime.timedelta(seconds=end_offset) start_stix = start_adj.strftime("%Y-%m-%dT%H:%M:%S.000Z") stop_stix = end_adj.strftime("%Y-%m-%dT%H:%M:%S.000Z") time_range = (start_stix, stop_stix) _logger.debug(f"pattern time range computed: {time_range}") except InvalidAttribute: time_range = None _logger.warning( f"pattern time range searching failed on variable {var_name}" ) if pattern_body: if time_range: pattern = ( f"({pattern_body}) START t'{time_range[0]}' STOP t'{time_range[1]}'" ) else: pattern = f"{pattern_body}" _logger.debug(f'final pattern assembled: "{pattern}"') else: pattern = None _logger.info(f"empty pattern assembled") return pattern def build_pattern_from_ids(return_type, ids): if ids: return "[" + return_type + ":id IN (" + ", ".join(map(_type_value, ids)) + ")]" else: return None def _dereference_multiple_variables(store, symtable, references): return { var + "." + attr: "(" + ", ".join(map(_type_value, vals)) + ")" for var, attrs in references.items() for attr, vals in _dereference_variable(store, symtable, var, attrs).items() } def _dereference_variable(store, symtable, var_name, attributes): attr_line = ",".join(attributes) _logger.debug(f'deref "{var_name}" with attributes "{attr_line}"') var_entity_table = get_entity_table(var_name, symtable) try: store_return = store.lookup(var_entity_table, attr_line) except InvalidAttr as e: _logger.warning(f"cannot deref {attr_line}. Invalid attribute in firepit.") raise InvalidAttribute(e.message) attr_to_values = {k: [] for k in attributes} for row in store_return: for k, v in row.items(): if v and v not in attr_to_values[k]: attr_to_values[k].append(v) for k, v in attr_to_values.items(): if not v: raise InvalidAttribute(var_name + "." + k) _logger.debug(f"deref results: {str(attr_to_values)}") return attr_to_values def _get_variable_time_range(store, symtable, var_name): time_attr_line = ",".join(["first_observed", "last_observed"]) var_entity_table = get_entity_table(var_name, symtable) try: store_return = store.lookup(var_entity_table, time_attr_line) except InvalidAttr as e: raise InvalidAttribute(e.message) life_span = dedup_dicts(store_return) start = min([dateutil.parser.isoparse(e["first_observed"]) for e in life_span]) end = max([dateutil.parser.isoparse(e["last_observed"]) for e in life_span]) return start, end def _type_value(value): if isinstance(value, str): return f"'{value}'" elif isinstance(value, int): return str(value) elif isinstance(value, float): return str(round(value)) else: return str(value) def _replace_ref_with_op(pattern, var_attr, vals_str): pattern = re.sub(r"([=><\[\]])", r" \1 ", pattern) pieces = pattern.split() try: ref_index = pieces.index(var_attr) except ValueError: err_msg = f'cannot find "{var_attr}" when assembling pattern "{pattern}"' _logger.error(err_msg) raise KestrelInternalError(err_msg) if pieces[ref_index - 1] == "=": pieces[ref_index - 1] = "IN" pieces[ref_index] = vals_str else: raise UnsupportedStixSyntax( 'only "=" is supported before referred variable in parameterized STIX' ) return " ".join(pieces)

true

f738ddd9c66d2ab195c75e9d45d2b52105e9e45c

10,263

py

Python

systolic/test/SystolicCL_test.py

pnnl/open-cgra

c19bc3a1baca3da659dc8f3cbfe32dd6003a2c65

[ "BSD-3-Clause" ]

13

2020-09-01T16:55:42.000Z

2021-09-01T16:39:44.000Z

systolic/test/SystolicCL_test.py

pnnl/open-cgra

c19bc3a1baca3da659dc8f3cbfe32dd6003a2c65

[ "BSD-3-Clause" ]

5

2020-08-19T05:40:01.000Z

2021-07-15T22:05:03.000Z

systolic/test/SystolicCL_test.py

pnnl/open-cgra

c19bc3a1baca3da659dc8f3cbfe32dd6003a2c65

[ "BSD-3-Clause" ]

4

2020-09-01T16:44:02.000Z

2021-07-11T04:40:05.000Z

""" ========================================================================== SystolicCL_test.py ========================================================================== Test cases for Systolic Array with CL data/config memory. Author : Cheng Tan Date : Dec 28, 2019 """ from pymtl3 import * from pymtl3.stdlib.test import TestSinkCL from pymtl3.stdlib.test.test_srcs import TestSrcRTL from ...lib.opt_type import * from ...lib.messages import * from ...lib.ctrl_helper import * from ...fu.flexible.FlexibleFuRTL import FlexibleFuRTL from ...fu.single.AdderRTL import AdderRTL from ...fu.single.MemUnitRTL import MemUnitRTL from ...fu.double.SeqMulAdderRTL import SeqMulAdderRTL from ..SystolicCL import SystolicCL import os #------------------------------------------------------------------------- # Test harness #------------------------------------------------------------------------- class TestHarness( Component ): def construct( s, DUT, FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, data_mem_size, src_opt, preload_data, preload_const, sink_out ): s.num_tiles = width * height AddrType = mk_bits( clog2( ctrl_mem_size ) ) s.sink_out = [ TestSinkCL( DataType, sink_out[i] ) for i in range( height-1 ) ] s.dut = DUT( FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, data_mem_size, ctrl_mem_size, src_opt, preload_data, preload_const ) for i in range( height-1 ): connect( s.dut.send_data[i], s.sink_out[i].recv ) def line_trace( s ): return s.dut.line_trace() def run_sim( test_harness, max_cycles=6 ): test_harness.elaborate() test_harness.apply( SimulationPass() ) test_harness.sim_reset() # Run simulation ncycles = 0 print() print( "{}:{}".format( ncycles, test_harness.line_trace() )) while ncycles < max_cycles: test_harness.tick() ncycles += 1 print( "----------------------------------------------------" ) print( "{}:{}".format( ncycles, test_harness.line_trace() )) # Check timeout # assert ncycles < max_cycles test_harness.tick() test_harness.tick() test_harness.tick() # ------------------------------------------------------------------ # To emulate systolic array # left bottom is 0, 0 # right top is 1, 1 # 1: North, 2: South, 3: West, 4: East # 5 - 8: registers # ------------------------------------------------------------------ def test_systolic_2x2(): num_tile_inports = 4 num_tile_outports = 4 num_xbar_inports = 6 num_xbar_outports = 8 ctrl_mem_size = 8 width = 2 height = 3 RouteType = mk_bits( clog2( num_xbar_inports + 1 ) ) AddrType = mk_bits( clog2( ctrl_mem_size ) ) num_tiles = width * height ctrl_mem_size = 8 data_mem_size = 2 # number of inputs of FU is fixed inside the tile num_fu_in = 4 DUT = SystolicCL FunctionUnit = FlexibleFuRTL FuList = [AdderRTL, MemUnitRTL, SeqMulAdderRTL] DataType = mk_data( 16, 1 ) PredicateType = mk_predicate( 1, 1 ) CtrlType = mk_ctrl( num_fu_in, num_xbar_inports, num_xbar_outports ) FuInType = mk_bits( clog2( num_fu_in + 1 ) ) pickRegister = [ FuInType( x+1 ) for x in range( num_fu_in ) ] src_opt = [[CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), ] ] preload_mem = [DataType(1, 1), DataType(2, 1), DataType(3, 1), DataType(4, 1)] preload_const = [[DataType(0, 1), DataType(1, 1)], [DataType(0, 0), DataType(2, 1), DataType(3, 1)], # offset address used for loading [DataType(2, 1)], [DataType(4, 1)], # preloaded data [DataType(6, 1)], [DataType(8, 1)]] # preloaded data """ 1 3 2 6 14 20 x = 2 4 4 8 30 44 """ sink_out = [[DataType(14, 1), DataType(20, 1)], [DataType(30, 1), DataType(44, 1)]] th = TestHarness( DUT, FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, len(preload_mem), src_opt, preload_mem, preload_const, sink_out ) run_sim( th )

48.871429

102

0.518952

from pymtl3 import * from pymtl3.stdlib.test import TestSinkCL from pymtl3.stdlib.test.test_srcs import TestSrcRTL from ...lib.opt_type import * from ...lib.messages import * from ...lib.ctrl_helper import * from ...fu.flexible.FlexibleFuRTL import FlexibleFuRTL from ...fu.single.AdderRTL import AdderRTL from ...fu.single.MemUnitRTL import MemUnitRTL from ...fu.double.SeqMulAdderRTL import SeqMulAdderRTL from ..SystolicCL import SystolicCL import os class TestHarness( Component ): def construct( s, DUT, FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, data_mem_size, src_opt, preload_data, preload_const, sink_out ): s.num_tiles = width * height AddrType = mk_bits( clog2( ctrl_mem_size ) ) s.sink_out = [ TestSinkCL( DataType, sink_out[i] ) for i in range( height-1 ) ] s.dut = DUT( FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, data_mem_size, ctrl_mem_size, src_opt, preload_data, preload_const ) for i in range( height-1 ): connect( s.dut.send_data[i], s.sink_out[i].recv ) def line_trace( s ): return s.dut.line_trace() def run_sim( test_harness, max_cycles=6 ): test_harness.elaborate() test_harness.apply( SimulationPass() ) test_harness.sim_reset() ncycles = 0 print() print( "{}:{}".format( ncycles, test_harness.line_trace() )) while ncycles < max_cycles: test_harness.tick() ncycles += 1 print( "----------------------------------------------------" ) print( "{}:{}".format( ncycles, test_harness.line_trace() )) test_harness.tick() test_harness.tick() test_harness.tick() def test_systolic_2x2(): num_tile_inports = 4 num_tile_outports = 4 num_xbar_inports = 6 num_xbar_outports = 8 ctrl_mem_size = 8 width = 2 height = 3 RouteType = mk_bits( clog2( num_xbar_inports + 1 ) ) AddrType = mk_bits( clog2( ctrl_mem_size ) ) num_tiles = width * height ctrl_mem_size = 8 data_mem_size = 2 num_fu_in = 4 DUT = SystolicCL FunctionUnit = FlexibleFuRTL FuList = [AdderRTL, MemUnitRTL, SeqMulAdderRTL] DataType = mk_data( 16, 1 ) PredicateType = mk_predicate( 1, 1 ) CtrlType = mk_ctrl( num_fu_in, num_xbar_inports, num_xbar_outports ) FuInType = mk_bits( clog2( num_fu_in + 1 ) ) pickRegister = [ FuInType( x+1 ) for x in range( num_fu_in ) ] src_opt = [[CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_LD_CONST, b1( 0 ), pickRegister, [ RouteType(5), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(2), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), CtrlType( OPT_MUL_CONST, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(0), RouteType(0)] ), ], [CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_NAH, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(0), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), CtrlType( OPT_MUL_CONST_ADD, b1( 0 ), pickRegister, [ RouteType(0), RouteType(0), RouteType(0), RouteType(5), RouteType(2), RouteType(0), RouteType(3), RouteType(0)] ), ] ] preload_mem = [DataType(1, 1), DataType(2, 1), DataType(3, 1), DataType(4, 1)] preload_const = [[DataType(0, 1), DataType(1, 1)], [DataType(0, 0), DataType(2, 1), DataType(3, 1)], [DataType(2, 1)], [DataType(4, 1)], [DataType(6, 1)], [DataType(8, 1)]] sink_out = [[DataType(14, 1), DataType(20, 1)], [DataType(30, 1), DataType(44, 1)]] th = TestHarness( DUT, FunctionUnit, FuList, DataType, PredicateType, CtrlType, width, height, ctrl_mem_size, len(preload_mem), src_opt, preload_mem, preload_const, sink_out ) run_sim( th )

true

f738df852121a8d04e083354e6672df79a7edc21

1,216

py

Python

Attic/migrations/0002_auto_20210508_1848.py

RemeoLong/Attic

8d9458b86a924b639001fe0bee052ba5be66dbce

[ "MIT" ]

null

Attic/migrations/0002_auto_20210508_1848.py

RemeoLong/Attic

8d9458b86a924b639001fe0bee052ba5be66dbce

[ "MIT" ]

null

Attic/migrations/0002_auto_20210508_1848.py

RemeoLong/Attic

8d9458b86a924b639001fe0bee052ba5be66dbce

[ "MIT" ]

null

# Generated by Django 2.2.16 on 2021-05-08 23:48 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('Attic', '0001_initial'), ] operations = [ migrations.AlterField( model_name='consultation', name='service', field=models.CharField(choices=[('Pest: Mice', 'Pest: Mice'), ('Pest: Rats', 'Pest: Rats'), ('Pest: Racoons', 'Pest: Racoons'), ('Pest: Squirrels', 'Pest: Squirrels'), ('Pest: Skunks', 'Pest: Skunks'), ('Pest: Opossums', 'Pest: Opossums'), ('Pest: Snakes', 'Pest: Snakes'), ('Pest: Bats', 'Pest: Bats'), ('Pest: Birds', 'Pest: Birds'), ('Pest: Insects', 'Pest: Insects'), ('Insulation Install', 'Insulation Install'), ('Roofing Repair', 'Roofing Repair'), ('Construction', 'Construction'), ('Sheet Rock', 'Sheet Rock'), ('Cement Small Jobs', 'Cement Small Jobs')], max_length=100), ), migrations.AlterField( model_name='consultation', name='status', field=models.CharField(choices=[('New', 'New'), ('Working', 'Working'), ('Pending Customer', 'Pending Customer'), ('Customer', 'Customer')], default='New', max_length=20), ), ]

50.666667

593

0.602796

from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('Attic', '0001_initial'), ] operations = [ migrations.AlterField( model_name='consultation', name='service', field=models.CharField(choices=[('Pest: Mice', 'Pest: Mice'), ('Pest: Rats', 'Pest: Rats'), ('Pest: Racoons', 'Pest: Racoons'), ('Pest: Squirrels', 'Pest: Squirrels'), ('Pest: Skunks', 'Pest: Skunks'), ('Pest: Opossums', 'Pest: Opossums'), ('Pest: Snakes', 'Pest: Snakes'), ('Pest: Bats', 'Pest: Bats'), ('Pest: Birds', 'Pest: Birds'), ('Pest: Insects', 'Pest: Insects'), ('Insulation Install', 'Insulation Install'), ('Roofing Repair', 'Roofing Repair'), ('Construction', 'Construction'), ('Sheet Rock', 'Sheet Rock'), ('Cement Small Jobs', 'Cement Small Jobs')], max_length=100), ), migrations.AlterField( model_name='consultation', name='status', field=models.CharField(choices=[('New', 'New'), ('Working', 'Working'), ('Pending Customer', 'Pending Customer'), ('Customer', 'Customer')], default='New', max_length=20), ), ]

true

f738e07889769bc26b37aa793f9905064e6a4642

6,970

py

Python

databricks_cli/pipelines/api.py

itaiw/databricks-cli

fdcb92499da5cda90c4436d5f09cdc697a8f46b9

[ "Apache-2.0" ]

null

databricks_cli/pipelines/api.py

itaiw/databricks-cli

fdcb92499da5cda90c4436d5f09cdc697a8f46b9

[ "Apache-2.0" ]

null

databricks_cli/pipelines/api.py

itaiw/databricks-cli

fdcb92499da5cda90c4436d5f09cdc697a8f46b9

[ "Apache-2.0" ]

null

# Databricks CLI # Copyright 2017 Databricks, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"), except # that the use of services to which certain application programming # interfaces (each, an "API") connect requires that the user first obtain # a license for the use of the APIs from Databricks, Inc. ("Databricks"), # by creating an account at www.databricks.com and agreeing to either (a) # the Community Edition Terms of Service, (b) the Databricks Terms of # Service, or (c) another written agreement between Licensee and Databricks # for the use of the APIs. # # 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 hashlib import sha1 import os from six.moves import urllib from databricks_cli.sdk import DeltaPipelinesService from databricks_cli.dbfs.api import DbfsApi from databricks_cli.dbfs.dbfs_path import DbfsPath BUFFER_SIZE = 1024 * 64 base_pipelines_dir = 'dbfs:/pipelines/code' supported_lib_types = {'jar', 'whl', 'maven'} class PipelinesApi(object): def __init__(self, api_client): self.client = DeltaPipelinesService(api_client) self.dbfs_client = DbfsApi(api_client) def deploy(self, spec, headers=None): lib_objects = LibraryObject.from_json(spec.get('libraries', [])) local_lib_objects, external_lib_objects = \ self._identify_local_libraries(lib_objects) spec['libraries'] = LibraryObject.to_json(external_lib_objects + self._upload_local_libraries(local_lib_objects)) pipeline_id = spec['id'] self.client.client.perform_query('PUT', '/pipelines/{}'.format(pipeline_id), data=spec, headers=headers) def delete(self, pipeline_id, headers=None): self.client.delete(pipeline_id, headers) def get(self, pipeline_id, headers=None): return self.client.get(pipeline_id, headers) def reset(self, pipeline_id, headers=None): self.client.reset(pipeline_id, headers) @staticmethod def _identify_local_libraries(lib_objects): """ Partitions the given set of libraries into local and those already present in dbfs/s3 etc. Local libraries are (currently) jar files with a file scheme or no scheme at all. All other libraries should be present in a supported external source. :param lib_objects: List[LibraryObject] :return: List[List[LibraryObject], List[LibraryObject]] ([Local, External]) """ local_lib_objects, external_lib_objects = [], [] for lib_object in lib_objects: if lib_object.lib_type == 'maven': external_lib_objects.append(lib_object) continue parsed_uri = urllib.parse.urlparse(lib_object.path) if lib_object.lib_type in supported_lib_types and parsed_uri.scheme == '': local_lib_objects.append(lib_object) elif lib_object.lib_type in supported_lib_types and parsed_uri.scheme.lower() == 'file': # exactly 1 or 3 if parsed_uri.path.startswith('//') or parsed_uri.netloc != '': raise RuntimeError('invalid file uri scheme, ' 'did you mean to use file:/ or file:///') local_lib_objects.append(LibraryObject(lib_object.lib_type, parsed_uri.path)) else: external_lib_objects.append(lib_object) return local_lib_objects, external_lib_objects def _upload_local_libraries(self, local_lib_objects): remote_lib_objects = [LibraryObject(llo.lib_type, self._get_hashed_path(llo.path)) for llo in local_lib_objects] transformed_remote_lib_objects = [LibraryObject(rlo.lib_type, DbfsPath(rlo.path)) for rlo in remote_lib_objects] upload_files = [llo_tuple for llo_tuple in zip(local_lib_objects, transformed_remote_lib_objects) if not self.dbfs_client.file_exists(llo_tuple[1].path)] for llo, rlo in upload_files: self.dbfs_client.put_file(llo.path, rlo.path, False) return remote_lib_objects @staticmethod def _get_hashed_path(path): """ Finds the corresponding dbfs file path for the file located at the supplied path by calculating its hash using SHA1. :param path: Local File Path :return: Remote Path (pipeline_base_dir + file_hash (dot) file_extension) """ hash_buffer = sha1() with open(path, 'rb') as f: while True: data = f.read(BUFFER_SIZE) if not data: break hash_buffer.update(data) file_hash = hash_buffer.hexdigest() # splitext includes the period in the extension extension = os.path.splitext(path)[1][1:] if extension == 'whl': # Wheels need to follow the format described in the PEP, so we simply # pre-pend the content hash to the wheel_name # basename in Python returns the extension as well wheel_name = os.path.basename(path) path = '{}/{}/{}'.format(base_pipelines_dir, file_hash, wheel_name) else: path = '{}/{}.{}'.format(base_pipelines_dir, file_hash, extension) return path class LibraryObject(object): def __init__(self, lib_type, lib_path): self.path = lib_path self.lib_type = lib_type @classmethod def from_json(cls, libraries): """ Serialize Libraries into LibraryObjects :param libraries: List[Dictionary{String, String}] :return: List[LibraryObject] """ lib_objects = [] for library in libraries: for lib_type, path in library.items(): lib_objects.append(LibraryObject(lib_type, path)) return lib_objects @classmethod def to_json(cls, lib_objects): """ Deserialize LibraryObjects :param lib_objects: List[LibraryObject] :return: List[Dictionary{String, String}] """ libraries = [] for lib_object in lib_objects: libraries.append({lib_object.lib_type: lib_object.path}) return libraries def __eq__(self, other): if not isinstance(other, LibraryObject): return NotImplemented return self.path == other.path and self.lib_type == other.lib_type

41

100

0.649785

from hashlib import sha1 import os from six.moves import urllib from databricks_cli.sdk import DeltaPipelinesService from databricks_cli.dbfs.api import DbfsApi from databricks_cli.dbfs.dbfs_path import DbfsPath BUFFER_SIZE = 1024 * 64 base_pipelines_dir = 'dbfs:/pipelines/code' supported_lib_types = {'jar', 'whl', 'maven'} class PipelinesApi(object): def __init__(self, api_client): self.client = DeltaPipelinesService(api_client) self.dbfs_client = DbfsApi(api_client) def deploy(self, spec, headers=None): lib_objects = LibraryObject.from_json(spec.get('libraries', [])) local_lib_objects, external_lib_objects = \ self._identify_local_libraries(lib_objects) spec['libraries'] = LibraryObject.to_json(external_lib_objects + self._upload_local_libraries(local_lib_objects)) pipeline_id = spec['id'] self.client.client.perform_query('PUT', '/pipelines/{}'.format(pipeline_id), data=spec, headers=headers) def delete(self, pipeline_id, headers=None): self.client.delete(pipeline_id, headers) def get(self, pipeline_id, headers=None): return self.client.get(pipeline_id, headers) def reset(self, pipeline_id, headers=None): self.client.reset(pipeline_id, headers) @staticmethod def _identify_local_libraries(lib_objects): local_lib_objects, external_lib_objects = [], [] for lib_object in lib_objects: if lib_object.lib_type == 'maven': external_lib_objects.append(lib_object) continue parsed_uri = urllib.parse.urlparse(lib_object.path) if lib_object.lib_type in supported_lib_types and parsed_uri.scheme == '': local_lib_objects.append(lib_object) elif lib_object.lib_type in supported_lib_types and parsed_uri.scheme.lower() == 'file': if parsed_uri.path.startswith('//') or parsed_uri.netloc != '': raise RuntimeError('invalid file uri scheme, ' 'did you mean to use file:/ or file:///') local_lib_objects.append(LibraryObject(lib_object.lib_type, parsed_uri.path)) else: external_lib_objects.append(lib_object) return local_lib_objects, external_lib_objects def _upload_local_libraries(self, local_lib_objects): remote_lib_objects = [LibraryObject(llo.lib_type, self._get_hashed_path(llo.path)) for llo in local_lib_objects] transformed_remote_lib_objects = [LibraryObject(rlo.lib_type, DbfsPath(rlo.path)) for rlo in remote_lib_objects] upload_files = [llo_tuple for llo_tuple in zip(local_lib_objects, transformed_remote_lib_objects) if not self.dbfs_client.file_exists(llo_tuple[1].path)] for llo, rlo in upload_files: self.dbfs_client.put_file(llo.path, rlo.path, False) return remote_lib_objects @staticmethod def _get_hashed_path(path): hash_buffer = sha1() with open(path, 'rb') as f: while True: data = f.read(BUFFER_SIZE) if not data: break hash_buffer.update(data) file_hash = hash_buffer.hexdigest() extension = os.path.splitext(path)[1][1:] if extension == 'whl': wheel_name = os.path.basename(path) path = '{}/{}/{}'.format(base_pipelines_dir, file_hash, wheel_name) else: path = '{}/{}.{}'.format(base_pipelines_dir, file_hash, extension) return path class LibraryObject(object): def __init__(self, lib_type, lib_path): self.path = lib_path self.lib_type = lib_type @classmethod def from_json(cls, libraries): lib_objects = [] for library in libraries: for lib_type, path in library.items(): lib_objects.append(LibraryObject(lib_type, path)) return lib_objects @classmethod def to_json(cls, lib_objects): libraries = [] for lib_object in lib_objects: libraries.append({lib_object.lib_type: lib_object.path}) return libraries def __eq__(self, other): if not isinstance(other, LibraryObject): return NotImplemented return self.path == other.path and self.lib_type == other.lib_type

true

f738e07fab3be3ad49fc0d2c35aa572ce82c17c9

3,616

py

Python

amical/_cli/commands/clean.py

tomasstolker/AMICAL

c9bbf8e4a468313efff3b349fffea7648c411a51

[ "MIT" ]

null

amical/_cli/commands/clean.py

tomasstolker/AMICAL

c9bbf8e4a468313efff3b349fffea7648c411a51

[ "MIT" ]

null

amical/_cli/commands/clean.py

tomasstolker/AMICAL

c9bbf8e4a468313efff3b349fffea7648c411a51

[ "MIT" ]

null

import os from datetime import datetime from glob import glob from pathlib import Path from astropy.io import fits from matplotlib import pyplot as plt from tabulate import tabulate from termcolor import cprint from tqdm import tqdm import amical def _select_data_file(args, process): """Show report with the data found and allow to select one to be treated.""" l_file = sorted(glob("%s/*.fits" % args.datadir)) if len(l_file) == 0: print("No fits files found in %s, check --datadir." % args.datadir) return 1 headers = ["FILENAME", "TARGET", "DATE", "INSTRUM", "INDEX"] index_file = [] d = [] for i, f in enumerate(l_file): with fits.open(f) as hdu: hdr = hdu[0].header target = hdr.get("OBJECT", None) date = hdr.get("DATE-OBS", None) ins = hdr.get("INSTRUME", None) index_file.append(i) filename = f.split("/")[-1] d.append([filename, target, date, ins, i]) print(tabulate(d, headers=headers)) if args.file >= 0: choosen_index = args.file else: choosen_index = int(input("\nWhich file to %s?\n" % process)) try: filename = l_file[choosen_index] except IndexError: print( "Selected index (%i) not valid (only %i files found)." % (choosen_index, len(l_file)) ) raise SystemExit else: with fits.open(filename) as hdul: hdr = hdul[0].header return filename, hdr def perform_clean(args): """Clean the data with AMICAL.""" cprint("---- AMICAL clean process ----", "cyan") clean_param = { "isz": args.isz, "r1": args.r1, "dr": args.dr, "apod": args.apod, "window": args.window, "f_kernel": args.kernel, } if not os.path.exists(args.datadir): print( "%s directory not found, check --datadir. AMICAL look for data only in this specified directory." % args.datadir ) return 1 l_file = sorted(glob("%s/*.fits" % args.datadir)) if len(l_file) == 0: print("No fits files found in %s, check --datadir." % args.datadir) return 1 if not args.all: filename, hdr = _select_data_file(args, process="clean") if args.check: amical.show_clean_params(filename, **clean_param) plt.show(block=True) return 0 if not os.path.exists(args.outdir): os.mkdir(args.outdir) clean_param["clip"] = args.clip clean_param["sky"] = args.sky if args.all: # Clean all files in --datadir for f in tqdm(l_file, ncols=100, desc="# files"): hdr = fits.open(f)[0].header hdr["HIERARCH AMICAL step"] = "CLEANED" cube = amical.select_clean_data(f, **clean_param, display=True) f_clean = os.path.join(args.outdir, Path(f).stem + "_cleaned.fits") fits.writeto(f_clean, cube, header=hdr, overwrite=True) else: # Or clean just the specified file (in --datadir) hdr["HIERARCH AMICAL step"] = "CLEANED" now = datetime.now() dt_string = now.strftime("%d/%m/%Y %H:%M:%S") hdr["HIERARCH AMICAL time"] = dt_string for k in clean_param: hdr["HIERARCH AMICAL params %s" % k] = clean_param[k] cube = amical.select_clean_data(filename, **clean_param, display=True) if args.plot: plt.show() f_clean = os.path.join(args.outdir, Path(filename).stem + "_cleaned.fits") fits.writeto(f_clean, cube, header=hdr, overwrite=True) return 0

30.386555

109

0.589878

import os from datetime import datetime from glob import glob from pathlib import Path from astropy.io import fits from matplotlib import pyplot as plt from tabulate import tabulate from termcolor import cprint from tqdm import tqdm import amical def _select_data_file(args, process): l_file = sorted(glob("%s/*.fits" % args.datadir)) if len(l_file) == 0: print("No fits files found in %s, check --datadir." % args.datadir) return 1 headers = ["FILENAME", "TARGET", "DATE", "INSTRUM", "INDEX"] index_file = [] d = [] for i, f in enumerate(l_file): with fits.open(f) as hdu: hdr = hdu[0].header target = hdr.get("OBJECT", None) date = hdr.get("DATE-OBS", None) ins = hdr.get("INSTRUME", None) index_file.append(i) filename = f.split("/")[-1] d.append([filename, target, date, ins, i]) print(tabulate(d, headers=headers)) if args.file >= 0: choosen_index = args.file else: choosen_index = int(input("\nWhich file to %s?\n" % process)) try: filename = l_file[choosen_index] except IndexError: print( "Selected index (%i) not valid (only %i files found)." % (choosen_index, len(l_file)) ) raise SystemExit else: with fits.open(filename) as hdul: hdr = hdul[0].header return filename, hdr def perform_clean(args): cprint("---- AMICAL clean process ----", "cyan") clean_param = { "isz": args.isz, "r1": args.r1, "dr": args.dr, "apod": args.apod, "window": args.window, "f_kernel": args.kernel, } if not os.path.exists(args.datadir): print( "%s directory not found, check --datadir. AMICAL look for data only in this specified directory." % args.datadir ) return 1 l_file = sorted(glob("%s/*.fits" % args.datadir)) if len(l_file) == 0: print("No fits files found in %s, check --datadir." % args.datadir) return 1 if not args.all: filename, hdr = _select_data_file(args, process="clean") if args.check: amical.show_clean_params(filename, **clean_param) plt.show(block=True) return 0 if not os.path.exists(args.outdir): os.mkdir(args.outdir) clean_param["clip"] = args.clip clean_param["sky"] = args.sky if args.all: for f in tqdm(l_file, ncols=100, desc="# files"): hdr = fits.open(f)[0].header hdr["HIERARCH AMICAL step"] = "CLEANED" cube = amical.select_clean_data(f, **clean_param, display=True) f_clean = os.path.join(args.outdir, Path(f).stem + "_cleaned.fits") fits.writeto(f_clean, cube, header=hdr, overwrite=True) else: hdr["HIERARCH AMICAL step"] = "CLEANED" now = datetime.now() dt_string = now.strftime("%d/%m/%Y %H:%M:%S") hdr["HIERARCH AMICAL time"] = dt_string for k in clean_param: hdr["HIERARCH AMICAL params %s" % k] = clean_param[k] cube = amical.select_clean_data(filename, **clean_param, display=True) if args.plot: plt.show() f_clean = os.path.join(args.outdir, Path(filename).stem + "_cleaned.fits") fits.writeto(f_clean, cube, header=hdr, overwrite=True) return 0

true

f738e084271100fae4934591514291316a9bafdd

1,500

py

Python

ui/mext.py

szymonkaliski/nott

fa85e64b570f71733ea199dddbd0bc0f013a613b

[ "MIT" ]

25

2019-07-01T14:58:48.000Z

2021-11-13T17:00:44.000Z

ui/mext.py

szymonkaliski/nott

fa85e64b570f71733ea199dddbd0bc0f013a613b

[ "MIT" ]

6

2019-12-30T02:50:19.000Z

2021-05-10T16:41:47.000Z

ui/mext.py

szymonkaliski/nott

fa85e64b570f71733ea199dddbd0bc0f013a613b

[ "MIT" ]

2

2020-01-05T13:02:07.000Z

2020-05-21T15:54:57.000Z

# FIXME: fix all "happy paths coding" issues import liblo from threading import Thread class Mext(object): device = None def __init__(self, device_port=5000): self.device_receiver = liblo.ServerThread(device_port) self.device_receiver.add_method("/monome/grid/key", "iii", self.on_grid_key) self.device_receiver.add_method( "/serialosc/device", "ssi", self.on_serialosc_device ) self.device_receiver.start() liblo.send(liblo.Address(12002), "/serialosc/list", "127.0.0.1", device_port) def set_grid_key_callback(self, fn): self.grid_key_callback = fn def set_led_level(self, x, y, value): Thread( target=( lambda: liblo.send( self.device, "/monome/grid/led/level/set", x, y, value ) ) ).start() def set_led_map(self, offset_x, offset_y, values): Thread( target=( lambda: liblo.send( self.device, "/monome/grid/led/level/map", offset_x, offset_y, *values ) ) ).start() def on_grid_key(self, path, args): x, y, edge = args if self.grid_key_callback: self.grid_key_callback(x, y, edge) def on_serialosc_device(self, path, args): _, sysId, port = args self.device = liblo.Address(port)

26.315789

85

0.544

import liblo from threading import Thread class Mext(object): device = None def __init__(self, device_port=5000): self.device_receiver = liblo.ServerThread(device_port) self.device_receiver.add_method("/monome/grid/key", "iii", self.on_grid_key) self.device_receiver.add_method( "/serialosc/device", "ssi", self.on_serialosc_device ) self.device_receiver.start() liblo.send(liblo.Address(12002), "/serialosc/list", "127.0.0.1", device_port) def set_grid_key_callback(self, fn): self.grid_key_callback = fn def set_led_level(self, x, y, value): Thread( target=( lambda: liblo.send( self.device, "/monome/grid/led/level/set", x, y, value ) ) ).start() def set_led_map(self, offset_x, offset_y, values): Thread( target=( lambda: liblo.send( self.device, "/monome/grid/led/level/map", offset_x, offset_y, *values ) ) ).start() def on_grid_key(self, path, args): x, y, edge = args if self.grid_key_callback: self.grid_key_callback(x, y, edge) def on_serialosc_device(self, path, args): _, sysId, port = args self.device = liblo.Address(port)

true

f738e0bea76b5ce7f1a12a4e6443af286201917a

33,549

py

Python

src/at/utils/_vendor/tomlkit/items.py

alextremblay/si-utils

1377ffd9dbefe63ac51efcca638fb583b2c89628

[ "MIT" ]

1

2021-08-21T03:26:14.000Z

src/at/utils/_vendor/tomlkit/items.py

alextremblay/si-utils

1377ffd9dbefe63ac51efcca638fb583b2c89628

[ "MIT" ]

null

src/at/utils/_vendor/tomlkit/items.py

alextremblay/si-utils

1377ffd9dbefe63ac51efcca638fb583b2c89628

[ "MIT" ]

null

from __future__ import unicode_literals import re import string from datetime import date from datetime import datetime from datetime import time from enum import Enum from typing import Any from typing import Dict from typing import Generator from typing import List from typing import Optional from typing import Union from ._compat import PY2 from ._compat import PY38 from ._compat import MutableMapping from ._compat import decode from ._compat import long from ._compat import unicode from ._utils import escape_string if PY2: from functools32 import lru_cache else: from functools import lru_cache def item(value, _parent=None, _sort_keys=False): from .container import Container if isinstance(value, Item): return value if isinstance(value, bool): return Bool(value, Trivia()) elif isinstance(value, int): return Integer(value, Trivia(), str(value)) elif isinstance(value, float): return Float(value, Trivia(), str(value)) elif isinstance(value, dict): val = Table(Container(), Trivia(), False) for k, v in sorted( value.items(), key=lambda i: (isinstance(i[1], dict), i[0] if _sort_keys else 1), ): val[k] = item(v, _parent=val, _sort_keys=_sort_keys) return val elif isinstance(value, list): if value and isinstance(value[0], dict): a = AoT([]) else: a = Array([], Trivia()) for v in value: if isinstance(v, dict): table = Table(Container(), Trivia(), True) for k, _v in sorted( v.items(), key=lambda i: (isinstance(i[1], dict), i[0] if _sort_keys else 1), ): i = item(_v, _sort_keys=_sort_keys) if isinstance(table, InlineTable): i.trivia.trail = "" table[k] = item(i, _sort_keys=_sort_keys) v = table a.append(v) return a elif isinstance(value, (str, unicode)): escaped = escape_string(value) return String(StringType.SLB, decode(value), escaped, Trivia()) elif isinstance(value, datetime): return DateTime( value.year, value.month, value.day, value.hour, value.minute, value.second, value.microsecond, value.tzinfo, Trivia(), value.isoformat().replace("+00:00", "Z"), ) elif isinstance(value, date): return Date(value.year, value.month, value.day, Trivia(), value.isoformat()) elif isinstance(value, time): return Time( value.hour, value.minute, value.second, value.microsecond, value.tzinfo, Trivia(), value.isoformat(), ) raise ValueError("Invalid type {}".format(type(value))) class StringType(Enum): # Single Line Basic SLB = '"' # Multi Line Basic MLB = '"""' # Single Line Literal SLL = "'" # Multi Line Literal MLL = "'''" @property @lru_cache(maxsize=None) def unit(self): # type: () -> str return self.value[0] @lru_cache(maxsize=None) def is_basic(self): # type: () -> bool return self in {StringType.SLB, StringType.MLB} @lru_cache(maxsize=None) def is_literal(self): # type: () -> bool return self in {StringType.SLL, StringType.MLL} @lru_cache(maxsize=None) def is_singleline(self): # type: () -> bool return self in {StringType.SLB, StringType.SLL} @lru_cache(maxsize=None) def is_multiline(self): # type: () -> bool return self in {StringType.MLB, StringType.MLL} @lru_cache(maxsize=None) def toggle(self): # type: () -> StringType return { StringType.SLB: StringType.MLB, StringType.MLB: StringType.SLB, StringType.SLL: StringType.MLL, StringType.MLL: StringType.SLL, }[self] class BoolType(Enum): TRUE = "true" FALSE = "false" @lru_cache(maxsize=None) def __bool__(self): return {BoolType.TRUE: True, BoolType.FALSE: False}[self] if PY2: __nonzero__ = __bool__ # for PY2 def __iter__(self): return iter(self.value) def __len__(self): return len(self.value) class Trivia: """ Trivia information (aka metadata). """ def __init__( self, indent=None, comment_ws=None, comment=None, trail=None ): # type: (str, str, str, str) -> None # Whitespace before a value. self.indent = indent or "" # Whitespace after a value, but before a comment. self.comment_ws = comment_ws or "" # Comment, starting with # character, or empty string if no comment. self.comment = comment or "" # Trailing newline. if trail is None: trail = "\n" self.trail = trail class KeyType(Enum): """ The type of a Key. Keys can be bare (unquoted), or quoted using basic ("), or literal (') quotes following the same escaping rules as single-line StringType. """ Bare = "" Basic = '"' Literal = "'" class Key: """ A key value. """ def __init__( self, k, t=None, sep=None, dotted=False, original=None ): # type: (str, Optional[KeyType], Optional[str], bool, Optional[str]) -> None if t is None: if any( [c not in string.ascii_letters + string.digits + "-" + "_" for c in k] ): t = KeyType.Basic else: t = KeyType.Bare self.t = t if sep is None: sep = " = " self.sep = sep self.key = k if original is None: original = k self._original = original self._dotted = dotted @property def delimiter(self): # type: () -> str return self.t.value def is_dotted(self): # type: () -> bool return self._dotted def is_bare(self): # type: () -> bool return self.t == KeyType.Bare def as_string(self): # type: () -> str return "{}{}{}".format(self.delimiter, self._original, self.delimiter) def __hash__(self): # type: () -> int return hash(self.key) def __eq__(self, other): # type: (Key) -> bool if isinstance(other, Key): return self.key == other.key return self.key == other def __str__(self): # type: () -> str return self.as_string() def __repr__(self): # type: () -> str return "<Key {}>".format(self.as_string()) class Item(object): """ An item within a TOML document. """ def __init__(self, trivia): # type: (Trivia) -> None self._trivia = trivia @property def trivia(self): # type: () -> Trivia return self._trivia @property def discriminant(self): # type: () -> int raise NotImplementedError() def as_string(self): # type: () -> str raise NotImplementedError() # Helpers def comment(self, comment): # type: (str) -> Item if not comment.strip().startswith("#"): comment = "# " + comment self._trivia.comment_ws = " " self._trivia.comment = comment return self def indent(self, indent): # type: (int) -> Item if self._trivia.indent.startswith("\n"): self._trivia.indent = "\n" + " " * indent else: self._trivia.indent = " " * indent return self def is_boolean(self): # type: () -> bool return isinstance(self, Bool) def is_table(self): # type: () -> bool return isinstance(self, Table) def is_inline_table(self): # type: () -> bool return isinstance(self, InlineTable) def is_aot(self): # type: () -> bool return isinstance(self, AoT) def _getstate(self, protocol=3): return (self._trivia,) def __reduce__(self): return self.__reduce_ex__(2) def __reduce_ex__(self, protocol): return self.__class__, self._getstate(protocol) class Whitespace(Item): """ A whitespace literal. """ def __init__(self, s, fixed=False): # type: (str, bool) -> None self._s = s self._fixed = fixed @property def s(self): # type: () -> str return self._s @property def value(self): # type: () -> str return self._s @property def trivia(self): # type: () -> Trivia raise RuntimeError("Called trivia on a Whitespace variant.") @property def discriminant(self): # type: () -> int return 0 def is_fixed(self): # type: () -> bool return self._fixed def as_string(self): # type: () -> str return self._s def __repr__(self): # type: () -> str return "<{} {}>".format(self.__class__.__name__, repr(self._s)) def _getstate(self, protocol=3): return self._s, self._fixed class Comment(Item): """ A comment literal. """ @property def discriminant(self): # type: () -> int return 1 def as_string(self): # type: () -> str return "{}{}{}".format( self._trivia.indent, decode(self._trivia.comment), self._trivia.trail ) def __str__(self): # type: () -> str return "{}{}".format(self._trivia.indent, decode(self._trivia.comment)) class Integer(long, Item): """ An integer literal. """ def __new__(cls, value, trivia, raw): # type: (int, Trivia, str) -> Integer return super(Integer, cls).__new__(cls, value) def __init__(self, _, trivia, raw): # type: (int, Trivia, str) -> None super(Integer, self).__init__(trivia) self._raw = raw self._sign = False if re.match(r"^[+\-]\d+$", raw): self._sign = True @property def discriminant(self): # type: () -> int return 2 @property def value(self): # type: () -> int return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): result = super(Integer, self).__add__(other) return self._new(result) def __radd__(self, other): result = super(Integer, self).__radd__(other) if isinstance(other, Integer): return self._new(result) return result def __sub__(self, other): result = super(Integer, self).__sub__(other) return self._new(result) def __rsub__(self, other): result = super(Integer, self).__rsub__(other) if isinstance(other, Integer): return self._new(result) return result def _new(self, result): raw = str(result) if self._sign: sign = "+" if result >= 0 else "-" raw = sign + raw return Integer(result, self._trivia, raw) def _getstate(self, protocol=3): return int(self), self._trivia, self._raw class Float(float, Item): """ A float literal. """ def __new__(cls, value, trivia, raw): # type: (float, Trivia, str) -> Integer return super(Float, cls).__new__(cls, value) def __init__(self, _, trivia, raw): # type: (float, Trivia, str) -> None super(Float, self).__init__(trivia) self._raw = raw self._sign = False if re.match(r"^[+\-].+$", raw): self._sign = True @property def discriminant(self): # type: () -> int return 3 @property def value(self): # type: () -> float return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): result = super(Float, self).__add__(other) return self._new(result) def __radd__(self, other): result = super(Float, self).__radd__(other) if isinstance(other, Float): return self._new(result) return result def __sub__(self, other): result = super(Float, self).__sub__(other) return self._new(result) def __rsub__(self, other): result = super(Float, self).__rsub__(other) if isinstance(other, Float): return self._new(result) return result def _new(self, result): raw = str(result) if self._sign: sign = "+" if result >= 0 else "-" raw = sign + raw return Float(result, self._trivia, raw) def _getstate(self, protocol=3): return float(self), self._trivia, self._raw class Bool(Item): """ A boolean literal. """ def __init__(self, t, trivia): # type: (int, Trivia) -> None super(Bool, self).__init__(trivia) self._value = bool(t) @property def discriminant(self): # type: () -> int return 4 @property def value(self): # type: () -> bool return self._value def as_string(self): # type: () -> str return str(self._value).lower() def _getstate(self, protocol=3): return self._value, self._trivia def __bool__(self): return self._value __nonzero__ = __bool__ def __eq__(self, other): if not isinstance(other, bool): return NotImplemented return other == self._value def __hash__(self): return hash(self._value) def __repr__(self): return repr(self._value) class DateTime(Item, datetime): """ A datetime literal. """ def __new__( cls, year, month, day, hour, minute, second, microsecond, tzinfo, trivia, raw, **kwargs ): # type: (int, int, int, int, int, int, int, Optional[datetime.tzinfo], Trivia, str, Any) -> datetime return datetime.__new__( cls, year, month, day, hour, minute, second, microsecond, tzinfo=tzinfo, **kwargs ) def __init__( self, year, month, day, hour, minute, second, microsecond, tzinfo, trivia, raw ): # type: (int, int, int, int, int, int, int, Optional[datetime.tzinfo], Trivia, str) -> None super(DateTime, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 5 @property def value(self): # type: () -> datetime return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): if PY38: result = datetime( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, ).__add__(other) else: result = super(DateTime, self).__add__(other) return self._new(result) def __sub__(self, other): if PY38: result = datetime( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, ).__sub__(other) else: result = super(DateTime, self).__sub__(other) if isinstance(result, datetime): result = self._new(result) return result def _new(self, result): raw = result.isoformat() return DateTime( result.year, result.month, result.day, result.hour, result.minute, result.second, result.microsecond, result.tzinfo, self._trivia, raw, ) def _getstate(self, protocol=3): return ( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, self._trivia, self._raw, ) class Date(Item, date): """ A date literal. """ def __new__(cls, year, month, day, *_): # type: (int, int, int, Any) -> date return date.__new__(cls, year, month, day) def __init__( self, year, month, day, trivia, raw ): # type: (int, int, int, Trivia, str) -> None super(Date, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 6 @property def value(self): # type: () -> date return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): if PY38: result = date(self.year, self.month, self.day).__add__(other) else: result = super(Date, self).__add__(other) return self._new(result) def __sub__(self, other): if PY38: result = date(self.year, self.month, self.day).__sub__(other) else: result = super(Date, self).__sub__(other) if isinstance(result, date): result = self._new(result) return result def _new(self, result): raw = result.isoformat() return Date(result.year, result.month, result.day, self._trivia, raw) def _getstate(self, protocol=3): return (self.year, self.month, self.day, self._trivia, self._raw) class Time(Item, time): """ A time literal. """ def __new__( cls, hour, minute, second, microsecond, tzinfo, *_ ): # type: (int, int, int, int, Optional[datetime.tzinfo], Any) -> time return time.__new__(cls, hour, minute, second, microsecond, tzinfo) def __init__( self, hour, minute, second, microsecond, tzinfo, trivia, raw ): # type: (int, int, int, int, Optional[datetime.tzinfo], Trivia, str) -> None super(Time, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 7 @property def value(self): # type: () -> time return self def as_string(self): # type: () -> str return self._raw def _getstate(self, protocol=3): return ( self.hour, self.minute, self.second, self.microsecond, self.tzinfo, self._trivia, self._raw, ) class Array(Item, list): """ An array literal """ def __init__( self, value, trivia, multiline=False ): # type: (list, Trivia, bool) -> None super(Array, self).__init__(trivia) list.__init__( self, [v.value for v in value if not isinstance(v, (Whitespace, Comment))] ) self._value = value self._multiline = multiline @property def discriminant(self): # type: () -> int return 8 @property def value(self): # type: () -> list return self def multiline(self, multiline): # type: (bool) -> self self._multiline = multiline return self def as_string(self): # type: () -> str if not self._multiline: return "[{}]".format("".join(v.as_string() for v in self._value)) s = "[\n" + self.trivia.indent + " " * 4 s += (",\n" + self.trivia.indent + " " * 4).join( v.as_string() for v in self._value if not isinstance(v, Whitespace) ) s += ",\n" s += "]" return s def append(self, _item): # type: (Any) -> None if self._value: self._value.append(Whitespace(", ")) it = item(_item) super(Array, self).append(it.value) self._value.append(it) if not PY2: def clear(self): super(Array, self).clear() self._value.clear() def __iadd__(self, other): # type: (list) -> Array if not isinstance(other, list): return NotImplemented for v in other: self.append(v) return self def __delitem__(self, key): super(Array, self).__delitem__(key) j = 0 if key >= 0 else -1 for i, v in enumerate(self._value if key >= 0 else reversed(self._value)): if key < 0: i = -i - 1 if isinstance(v, (Comment, Whitespace)): continue if j == key: del self._value[i] if i < 0 and abs(i) > len(self._value): i += 1 if i < len(self._value) - 1 and isinstance(self._value[i], Whitespace): del self._value[i] break j += 1 if key >= 0 else -1 def __str__(self): return str( [v.value for v in self._value if not isinstance(v, (Whitespace, Comment))] ) def __repr__(self): return str(self) def _getstate(self, protocol=3): return self._value, self._trivia class Table(Item, MutableMapping, dict): """ A table literal. """ def __init__( self, value, trivia, is_aot_element, is_super_table=False, name=None, display_name=None, ): # type: (tomlkit.container.Container, Trivia, bool, bool, Optional[str], Optional[str]) -> None super(Table, self).__init__(trivia) self.name = name self.display_name = display_name self._value = value self._is_aot_element = is_aot_element self._is_super_table = is_super_table for k, v in self._value.body: if k is not None: dict.__setitem__(self, k.key, v) @property def value(self): # type: () -> tomlkit.container.Container return self._value @property def discriminant(self): # type: () -> int return 9 def add(self, key, item=None): # type: (Union[Key, Item, str], Any) -> Item if item is None: if not isinstance(key, (Comment, Whitespace)): raise ValueError( "Non comment/whitespace items must have an associated key" ) key, item = None, key return self.append(key, item) def append(self, key, _item): # type: (Union[Key, str], Any) -> Table """ Appends a (key, item) to the table. """ if not isinstance(_item, Item): _item = item(_item) self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: return self indent = m.group(1) if not isinstance(_item, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", _item.trivia.indent) if not m: _item.trivia.indent = indent else: _item.trivia.indent = m.group(1) + indent + m.group(2) return self def raw_append(self, key, _item): # type: (Union[Key, str], Any) -> Table if not isinstance(_item, Item): _item = item(_item) self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) return self def remove(self, key): # type: (Union[Key, str]) -> Table self._value.remove(key) if isinstance(key, Key): key = key.key if key is not None: dict.__delitem__(self, key) return self def is_aot_element(self): # type: () -> bool return self._is_aot_element def is_super_table(self): # type: () -> bool return self._is_super_table def as_string(self): # type: () -> str return self._value.as_string() # Helpers def indent(self, indent): # type: (int) -> Table super(Table, self).indent(indent) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: indent = "" else: indent = m.group(1) for k, item in self._value.body: if not isinstance(item, Whitespace): item.trivia.indent = indent + item.trivia.indent return self def get(self, key, default=None): # type: (Any, Optional[Any]) -> Any return self._value.get(key, default) def setdefault( self, key, default=None ): # type: (Union[Key, str], Any) -> Union[Item, Container] super(Table, self).setdefault(key, default=default) return self[key] def __getitem__(self, key): # type: (Union[Key, str]) -> Item return self._value[key] def __setitem__(self, key, value): # type: (Union[Key, str], Any) -> None fix_indent = key not in self if not isinstance(value, Item): value = item(value) self._value[key] = value if key is not None: dict.__setitem__(self, key, value) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m or not fix_indent: return indent = m.group(1) if not isinstance(value, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", value.trivia.indent) if not m: value.trivia.indent = indent else: value.trivia.indent = m.group(1) + indent + m.group(2) def __delitem__(self, key): # type: (Union[Key, str]) -> None self.remove(key) def __len__(self): # type: () -> int return len(self._value) def __iter__(self): # type: () -> Iterator[str] return iter(self._value) def __repr__(self): # type: () -> str return repr(self._value) def _getstate(self, protocol=3): return ( self._value, self._trivia, self._is_aot_element, self._is_super_table, self.name, self.display_name, ) class InlineTable(Item, MutableMapping, dict): """ An inline table literal. """ def __init__( self, value, trivia, new=False ): # type: (tomlkit.container.Container, Trivia, bool) -> None super(InlineTable, self).__init__(trivia) self._value = value self._new = new for k, v in self._value.body: if k is not None: dict.__setitem__(self, k.key, v) @property def discriminant(self): # type: () -> int return 10 @property def value(self): # type: () -> Dict return self._value def append(self, key, _item): # type: (Union[Key, str], Any) -> InlineTable """ Appends a (key, item) to the table. """ if not isinstance(_item, Item): _item = item(_item) if not isinstance(_item, (Whitespace, Comment)): if not _item.trivia.indent and len(self._value) > 0 and not self._new: _item.trivia.indent = " " if _item.trivia.comment: _item.trivia.comment = "" self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) return self def remove(self, key): # type: (Union[Key, str]) -> InlineTable self._value.remove(key) if isinstance(key, Key): key = key.key if key is not None: dict.__delitem__(self, key) return self def as_string(self): # type: () -> str buf = "{" for i, (k, v) in enumerate(self._value.body): if k is None: if i == len(self._value.body) - 1: if self._new: buf = buf.rstrip(", ") else: buf = buf.rstrip(",") buf += v.as_string() continue buf += "{}{}{}{}{}{}".format( v.trivia.indent, k.as_string() + ("." if k.is_dotted() else ""), k.sep, v.as_string(), v.trivia.comment, v.trivia.trail.replace("\n", ""), ) if i != len(self._value.body) - 1: buf += "," if self._new: buf += " " buf += "}" return buf def get(self, key, default=None): # type: (Any, Optional[Any]) -> Any return self._value.get(key, default) def setdefault( self, key, default=None ): # type: (Union[Key, str], Any) -> Union[Item, Container] super(InlineTable, self).setdefault(key, default=default) return self[key] def __contains__(self, key): # type: (Union[Key, str]) -> bool return key in self._value def __getitem__(self, key): # type: (Union[Key, str]) -> Item return self._value[key] def __setitem__(self, key, value): # type: (Union[Key, str], Any) -> None if not isinstance(value, Item): value = item(value) self._value[key] = value if key is not None: dict.__setitem__(self, key, value) if value.trivia.comment: value.trivia.comment = "" m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: return indent = m.group(1) if not isinstance(value, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", value.trivia.indent) if not m: value.trivia.indent = indent else: value.trivia.indent = m.group(1) + indent + m.group(2) def __delitem__(self, key): # type: (Union[Key, str]) -> None self.remove(key) def __len__(self): # type: () -> int return len(self._value) def __iter__(self): # type: () -> Iterator[str] return iter(self._value) def __repr__(self): return repr(self._value) def _getstate(self, protocol=3): return (self._value, self._trivia) class String(unicode, Item): """ A string literal. """ def __new__(cls, t, value, original, trivia): return super(String, cls).__new__(cls, value) def __init__( self, t, _, original, trivia ): # type: (StringType, str, original, Trivia) -> None super(String, self).__init__(trivia) self._t = t self._original = original @property def discriminant(self): # type: () -> int return 11 @property def value(self): # type: () -> str return self def as_string(self): # type: () -> str return "{}{}{}".format(self._t.value, decode(self._original), self._t.value) def __add__(self, other): result = super(String, self).__add__(other) return self._new(result) def __sub__(self, other): result = super(String, self).__sub__(other) return self._new(result) def _new(self, result): return String(self._t, result, result, self._trivia) def _getstate(self, protocol=3): return self._t, unicode(self), self._original, self._trivia class AoT(Item, list): """ An array of table literal """ def __init__( self, body, name=None, parsed=False ): # type: (List[Table], Optional[str], bool) -> None self.name = name self._body = [] self._parsed = parsed super(AoT, self).__init__(Trivia(trail="")) for table in body: self.append(table) @property def body(self): # type: () -> List[Table] return self._body @property def discriminant(self): # type: () -> int return 12 @property def value(self): # type: () -> List[Dict[Any, Any]] return [v.value for v in self._body] def append(self, table): # type: (Table) -> Table m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if m: indent = m.group(1) m = re.match("(?s)^([^ ]*)(.*)$", table.trivia.indent) if not m: table.trivia.indent = indent else: table.trivia.indent = m.group(1) + indent + m.group(2) if not self._parsed and "\n" not in table.trivia.indent and self._body: table.trivia.indent = "\n" + table.trivia.indent self._body.append(table) super(AoT, self).append(table) return table def as_string(self): # type: () -> str b = "" for table in self._body: b += table.as_string() return b def __repr__(self): # type: () -> str return "<AoT {}>".format(self.value) def _getstate(self, protocol=3): return self._body, self.name, self._parsed class Null(Item): """ A null item. """ def __init__(self): # type: () -> None pass @property def discriminant(self): # type: () -> int return -1 @property def value(self): # type: () -> None return None def as_string(self): # type: () -> str return "" def _getstate(self, protocol=3): return tuple()

25.186937

108

0.534442

from __future__ import unicode_literals import re import string from datetime import date from datetime import datetime from datetime import time from enum import Enum from typing import Any from typing import Dict from typing import Generator from typing import List from typing import Optional from typing import Union from ._compat import PY2 from ._compat import PY38 from ._compat import MutableMapping from ._compat import decode from ._compat import long from ._compat import unicode from ._utils import escape_string if PY2: from functools32 import lru_cache else: from functools import lru_cache def item(value, _parent=None, _sort_keys=False): from .container import Container if isinstance(value, Item): return value if isinstance(value, bool): return Bool(value, Trivia()) elif isinstance(value, int): return Integer(value, Trivia(), str(value)) elif isinstance(value, float): return Float(value, Trivia(), str(value)) elif isinstance(value, dict): val = Table(Container(), Trivia(), False) for k, v in sorted( value.items(), key=lambda i: (isinstance(i[1], dict), i[0] if _sort_keys else 1), ): val[k] = item(v, _parent=val, _sort_keys=_sort_keys) return val elif isinstance(value, list): if value and isinstance(value[0], dict): a = AoT([]) else: a = Array([], Trivia()) for v in value: if isinstance(v, dict): table = Table(Container(), Trivia(), True) for k, _v in sorted( v.items(), key=lambda i: (isinstance(i[1], dict), i[0] if _sort_keys else 1), ): i = item(_v, _sort_keys=_sort_keys) if isinstance(table, InlineTable): i.trivia.trail = "" table[k] = item(i, _sort_keys=_sort_keys) v = table a.append(v) return a elif isinstance(value, (str, unicode)): escaped = escape_string(value) return String(StringType.SLB, decode(value), escaped, Trivia()) elif isinstance(value, datetime): return DateTime( value.year, value.month, value.day, value.hour, value.minute, value.second, value.microsecond, value.tzinfo, Trivia(), value.isoformat().replace("+00:00", "Z"), ) elif isinstance(value, date): return Date(value.year, value.month, value.day, Trivia(), value.isoformat()) elif isinstance(value, time): return Time( value.hour, value.minute, value.second, value.microsecond, value.tzinfo, Trivia(), value.isoformat(), ) raise ValueError("Invalid type {}".format(type(value))) class StringType(Enum): SLB = '"' # Multi Line Basic MLB = '"""' # Single Line Literal SLL = "'" # Multi Line Literal MLL = "'''" @property @lru_cache(maxsize=None) def unit(self): # type: () -> str return self.value[0] @lru_cache(maxsize=None) def is_basic(self): # type: () -> bool return self in {StringType.SLB, StringType.MLB} @lru_cache(maxsize=None) def is_literal(self): # type: () -> bool return self in {StringType.SLL, StringType.MLL} @lru_cache(maxsize=None) def is_singleline(self): # type: () -> bool return self in {StringType.SLB, StringType.SLL} @lru_cache(maxsize=None) def is_multiline(self): # type: () -> bool return self in {StringType.MLB, StringType.MLL} @lru_cache(maxsize=None) def toggle(self): # type: () -> StringType return { StringType.SLB: StringType.MLB, StringType.MLB: StringType.SLB, StringType.SLL: StringType.MLL, StringType.MLL: StringType.SLL, }[self] class BoolType(Enum): TRUE = "true" FALSE = "false" @lru_cache(maxsize=None) def __bool__(self): return {BoolType.TRUE: True, BoolType.FALSE: False}[self] if PY2: __nonzero__ = __bool__ # for PY2 def __iter__(self): return iter(self.value) def __len__(self): return len(self.value) class Trivia: def __init__( self, indent=None, comment_ws=None, comment=None, trail=None ): # type: (str, str, str, str) -> None # Whitespace before a value. self.indent = indent or "" # Whitespace after a value, but before a comment. self.comment_ws = comment_ws or "" # Comment, starting with # character, or empty string if no comment. self.comment = comment or "" # Trailing newline. if trail is None: trail = "\n" self.trail = trail class KeyType(Enum): Bare = "" Basic = '"' Literal = "'" class Key: def __init__( self, k, t=None, sep=None, dotted=False, original=None ): # type: (str, Optional[KeyType], Optional[str], bool, Optional[str]) -> None if t is None: if any( [c not in string.ascii_letters + string.digits + "-" + "_" for c in k] ): t = KeyType.Basic else: t = KeyType.Bare self.t = t if sep is None: sep = " = " self.sep = sep self.key = k if original is None: original = k self._original = original self._dotted = dotted @property def delimiter(self): # type: () -> str return self.t.value def is_dotted(self): # type: () -> bool return self._dotted def is_bare(self): # type: () -> bool return self.t == KeyType.Bare def as_string(self): # type: () -> str return "{}{}{}".format(self.delimiter, self._original, self.delimiter) def __hash__(self): # type: () -> int return hash(self.key) def __eq__(self, other): # type: (Key) -> bool if isinstance(other, Key): return self.key == other.key return self.key == other def __str__(self): # type: () -> str return self.as_string() def __repr__(self): # type: () -> str return "<Key {}>".format(self.as_string()) class Item(object): def __init__(self, trivia): # type: (Trivia) -> None self._trivia = trivia @property def trivia(self): # type: () -> Trivia return self._trivia @property def discriminant(self): # type: () -> int raise NotImplementedError() def as_string(self): # type: () -> str raise NotImplementedError() # Helpers def comment(self, comment): # type: (str) -> Item if not comment.strip().startswith("#"): comment = "# " + comment self._trivia.comment_ws = " " self._trivia.comment = comment return self def indent(self, indent): # type: (int) -> Item if self._trivia.indent.startswith("\n"): self._trivia.indent = "\n" + " " * indent else: self._trivia.indent = " " * indent return self def is_boolean(self): # type: () -> bool return isinstance(self, Bool) def is_table(self): # type: () -> bool return isinstance(self, Table) def is_inline_table(self): # type: () -> bool return isinstance(self, InlineTable) def is_aot(self): # type: () -> bool return isinstance(self, AoT) def _getstate(self, protocol=3): return (self._trivia,) def __reduce__(self): return self.__reduce_ex__(2) def __reduce_ex__(self, protocol): return self.__class__, self._getstate(protocol) class Whitespace(Item): def __init__(self, s, fixed=False): # type: (str, bool) -> None self._s = s self._fixed = fixed @property def s(self): # type: () -> str return self._s @property def value(self): # type: () -> str return self._s @property def trivia(self): # type: () -> Trivia raise RuntimeError("Called trivia on a Whitespace variant.") @property def discriminant(self): # type: () -> int return 0 def is_fixed(self): # type: () -> bool return self._fixed def as_string(self): # type: () -> str return self._s def __repr__(self): # type: () -> str return "<{} {}>".format(self.__class__.__name__, repr(self._s)) def _getstate(self, protocol=3): return self._s, self._fixed class Comment(Item): @property def discriminant(self): # type: () -> int return 1 def as_string(self): # type: () -> str return "{}{}{}".format( self._trivia.indent, decode(self._trivia.comment), self._trivia.trail ) def __str__(self): # type: () -> str return "{}{}".format(self._trivia.indent, decode(self._trivia.comment)) class Integer(long, Item): def __new__(cls, value, trivia, raw): # type: (int, Trivia, str) -> Integer return super(Integer, cls).__new__(cls, value) def __init__(self, _, trivia, raw): # type: (int, Trivia, str) -> None super(Integer, self).__init__(trivia) self._raw = raw self._sign = False if re.match(r"^[+\-]\d+$", raw): self._sign = True @property def discriminant(self): # type: () -> int return 2 @property def value(self): # type: () -> int return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): result = super(Integer, self).__add__(other) return self._new(result) def __radd__(self, other): result = super(Integer, self).__radd__(other) if isinstance(other, Integer): return self._new(result) return result def __sub__(self, other): result = super(Integer, self).__sub__(other) return self._new(result) def __rsub__(self, other): result = super(Integer, self).__rsub__(other) if isinstance(other, Integer): return self._new(result) return result def _new(self, result): raw = str(result) if self._sign: sign = "+" if result >= 0 else "-" raw = sign + raw return Integer(result, self._trivia, raw) def _getstate(self, protocol=3): return int(self), self._trivia, self._raw class Float(float, Item): def __new__(cls, value, trivia, raw): # type: (float, Trivia, str) -> Integer return super(Float, cls).__new__(cls, value) def __init__(self, _, trivia, raw): # type: (float, Trivia, str) -> None super(Float, self).__init__(trivia) self._raw = raw self._sign = False if re.match(r"^[+\-].+$", raw): self._sign = True @property def discriminant(self): # type: () -> int return 3 @property def value(self): # type: () -> float return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): result = super(Float, self).__add__(other) return self._new(result) def __radd__(self, other): result = super(Float, self).__radd__(other) if isinstance(other, Float): return self._new(result) return result def __sub__(self, other): result = super(Float, self).__sub__(other) return self._new(result) def __rsub__(self, other): result = super(Float, self).__rsub__(other) if isinstance(other, Float): return self._new(result) return result def _new(self, result): raw = str(result) if self._sign: sign = "+" if result >= 0 else "-" raw = sign + raw return Float(result, self._trivia, raw) def _getstate(self, protocol=3): return float(self), self._trivia, self._raw class Bool(Item): def __init__(self, t, trivia): # type: (int, Trivia) -> None super(Bool, self).__init__(trivia) self._value = bool(t) @property def discriminant(self): # type: () -> int return 4 @property def value(self): # type: () -> bool return self._value def as_string(self): # type: () -> str return str(self._value).lower() def _getstate(self, protocol=3): return self._value, self._trivia def __bool__(self): return self._value __nonzero__ = __bool__ def __eq__(self, other): if not isinstance(other, bool): return NotImplemented return other == self._value def __hash__(self): return hash(self._value) def __repr__(self): return repr(self._value) class DateTime(Item, datetime): def __new__( cls, year, month, day, hour, minute, second, microsecond, tzinfo, trivia, raw, **kwargs ): # type: (int, int, int, int, int, int, int, Optional[datetime.tzinfo], Trivia, str, Any) -> datetime return datetime.__new__( cls, year, month, day, hour, minute, second, microsecond, tzinfo=tzinfo, **kwargs ) def __init__( self, year, month, day, hour, minute, second, microsecond, tzinfo, trivia, raw ): # type: (int, int, int, int, int, int, int, Optional[datetime.tzinfo], Trivia, str) -> None super(DateTime, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 5 @property def value(self): # type: () -> datetime return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): if PY38: result = datetime( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, ).__add__(other) else: result = super(DateTime, self).__add__(other) return self._new(result) def __sub__(self, other): if PY38: result = datetime( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, ).__sub__(other) else: result = super(DateTime, self).__sub__(other) if isinstance(result, datetime): result = self._new(result) return result def _new(self, result): raw = result.isoformat() return DateTime( result.year, result.month, result.day, result.hour, result.minute, result.second, result.microsecond, result.tzinfo, self._trivia, raw, ) def _getstate(self, protocol=3): return ( self.year, self.month, self.day, self.hour, self.minute, self.second, self.microsecond, self.tzinfo, self._trivia, self._raw, ) class Date(Item, date): def __new__(cls, year, month, day, *_): # type: (int, int, int, Any) -> date return date.__new__(cls, year, month, day) def __init__( self, year, month, day, trivia, raw ): # type: (int, int, int, Trivia, str) -> None super(Date, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 6 @property def value(self): # type: () -> date return self def as_string(self): # type: () -> str return self._raw def __add__(self, other): if PY38: result = date(self.year, self.month, self.day).__add__(other) else: result = super(Date, self).__add__(other) return self._new(result) def __sub__(self, other): if PY38: result = date(self.year, self.month, self.day).__sub__(other) else: result = super(Date, self).__sub__(other) if isinstance(result, date): result = self._new(result) return result def _new(self, result): raw = result.isoformat() return Date(result.year, result.month, result.day, self._trivia, raw) def _getstate(self, protocol=3): return (self.year, self.month, self.day, self._trivia, self._raw) class Time(Item, time): def __new__( cls, hour, minute, second, microsecond, tzinfo, *_ ): # type: (int, int, int, int, Optional[datetime.tzinfo], Any) -> time return time.__new__(cls, hour, minute, second, microsecond, tzinfo) def __init__( self, hour, minute, second, microsecond, tzinfo, trivia, raw ): # type: (int, int, int, int, Optional[datetime.tzinfo], Trivia, str) -> None super(Time, self).__init__(trivia) self._raw = raw @property def discriminant(self): # type: () -> int return 7 @property def value(self): # type: () -> time return self def as_string(self): # type: () -> str return self._raw def _getstate(self, protocol=3): return ( self.hour, self.minute, self.second, self.microsecond, self.tzinfo, self._trivia, self._raw, ) class Array(Item, list): def __init__( self, value, trivia, multiline=False ): # type: (list, Trivia, bool) -> None super(Array, self).__init__(trivia) list.__init__( self, [v.value for v in value if not isinstance(v, (Whitespace, Comment))] ) self._value = value self._multiline = multiline @property def discriminant(self): # type: () -> int return 8 @property def value(self): # type: () -> list return self def multiline(self, multiline): # type: (bool) -> self self._multiline = multiline return self def as_string(self): # type: () -> str if not self._multiline: return "[{}]".format("".join(v.as_string() for v in self._value)) s = "[\n" + self.trivia.indent + " " * 4 s += (",\n" + self.trivia.indent + " " * 4).join( v.as_string() for v in self._value if not isinstance(v, Whitespace) ) s += ",\n" s += "]" return s def append(self, _item): # type: (Any) -> None if self._value: self._value.append(Whitespace(", ")) it = item(_item) super(Array, self).append(it.value) self._value.append(it) if not PY2: def clear(self): super(Array, self).clear() self._value.clear() def __iadd__(self, other): # type: (list) -> Array if not isinstance(other, list): return NotImplemented for v in other: self.append(v) return self def __delitem__(self, key): super(Array, self).__delitem__(key) j = 0 if key >= 0 else -1 for i, v in enumerate(self._value if key >= 0 else reversed(self._value)): if key < 0: i = -i - 1 if isinstance(v, (Comment, Whitespace)): continue if j == key: del self._value[i] if i < 0 and abs(i) > len(self._value): i += 1 if i < len(self._value) - 1 and isinstance(self._value[i], Whitespace): del self._value[i] break j += 1 if key >= 0 else -1 def __str__(self): return str( [v.value for v in self._value if not isinstance(v, (Whitespace, Comment))] ) def __repr__(self): return str(self) def _getstate(self, protocol=3): return self._value, self._trivia class Table(Item, MutableMapping, dict): def __init__( self, value, trivia, is_aot_element, is_super_table=False, name=None, display_name=None, ): # type: (tomlkit.container.Container, Trivia, bool, bool, Optional[str], Optional[str]) -> None super(Table, self).__init__(trivia) self.name = name self.display_name = display_name self._value = value self._is_aot_element = is_aot_element self._is_super_table = is_super_table for k, v in self._value.body: if k is not None: dict.__setitem__(self, k.key, v) @property def value(self): # type: () -> tomlkit.container.Container return self._value @property def discriminant(self): # type: () -> int return 9 def add(self, key, item=None): # type: (Union[Key, Item, str], Any) -> Item if item is None: if not isinstance(key, (Comment, Whitespace)): raise ValueError( "Non comment/whitespace items must have an associated key" ) key, item = None, key return self.append(key, item) def append(self, key, _item): # type: (Union[Key, str], Any) -> Table if not isinstance(_item, Item): _item = item(_item) self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: return self indent = m.group(1) if not isinstance(_item, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", _item.trivia.indent) if not m: _item.trivia.indent = indent else: _item.trivia.indent = m.group(1) + indent + m.group(2) return self def raw_append(self, key, _item): # type: (Union[Key, str], Any) -> Table if not isinstance(_item, Item): _item = item(_item) self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) return self def remove(self, key): # type: (Union[Key, str]) -> Table self._value.remove(key) if isinstance(key, Key): key = key.key if key is not None: dict.__delitem__(self, key) return self def is_aot_element(self): # type: () -> bool return self._is_aot_element def is_super_table(self): # type: () -> bool return self._is_super_table def as_string(self): # type: () -> str return self._value.as_string() # Helpers def indent(self, indent): # type: (int) -> Table super(Table, self).indent(indent) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: indent = "" else: indent = m.group(1) for k, item in self._value.body: if not isinstance(item, Whitespace): item.trivia.indent = indent + item.trivia.indent return self def get(self, key, default=None): # type: (Any, Optional[Any]) -> Any return self._value.get(key, default) def setdefault( self, key, default=None ): # type: (Union[Key, str], Any) -> Union[Item, Container] super(Table, self).setdefault(key, default=default) return self[key] def __getitem__(self, key): # type: (Union[Key, str]) -> Item return self._value[key] def __setitem__(self, key, value): # type: (Union[Key, str], Any) -> None fix_indent = key not in self if not isinstance(value, Item): value = item(value) self._value[key] = value if key is not None: dict.__setitem__(self, key, value) m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m or not fix_indent: return indent = m.group(1) if not isinstance(value, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", value.trivia.indent) if not m: value.trivia.indent = indent else: value.trivia.indent = m.group(1) + indent + m.group(2) def __delitem__(self, key): # type: (Union[Key, str]) -> None self.remove(key) def __len__(self): # type: () -> int return len(self._value) def __iter__(self): # type: () -> Iterator[str] return iter(self._value) def __repr__(self): # type: () -> str return repr(self._value) def _getstate(self, protocol=3): return ( self._value, self._trivia, self._is_aot_element, self._is_super_table, self.name, self.display_name, ) class InlineTable(Item, MutableMapping, dict): def __init__( self, value, trivia, new=False ): # type: (tomlkit.container.Container, Trivia, bool) -> None super(InlineTable, self).__init__(trivia) self._value = value self._new = new for k, v in self._value.body: if k is not None: dict.__setitem__(self, k.key, v) @property def discriminant(self): # type: () -> int return 10 @property def value(self): # type: () -> Dict return self._value def append(self, key, _item): # type: (Union[Key, str], Any) -> InlineTable if not isinstance(_item, Item): _item = item(_item) if not isinstance(_item, (Whitespace, Comment)): if not _item.trivia.indent and len(self._value) > 0 and not self._new: _item.trivia.indent = " " if _item.trivia.comment: _item.trivia.comment = "" self._value.append(key, _item) if isinstance(key, Key): key = key.key if key is not None: dict.__setitem__(self, key, _item) return self def remove(self, key): # type: (Union[Key, str]) -> InlineTable self._value.remove(key) if isinstance(key, Key): key = key.key if key is not None: dict.__delitem__(self, key) return self def as_string(self): # type: () -> str buf = "{" for i, (k, v) in enumerate(self._value.body): if k is None: if i == len(self._value.body) - 1: if self._new: buf = buf.rstrip(", ") else: buf = buf.rstrip(",") buf += v.as_string() continue buf += "{}{}{}{}{}{}".format( v.trivia.indent, k.as_string() + ("." if k.is_dotted() else ""), k.sep, v.as_string(), v.trivia.comment, v.trivia.trail.replace("\n", ""), ) if i != len(self._value.body) - 1: buf += "," if self._new: buf += " " buf += "}" return buf def get(self, key, default=None): # type: (Any, Optional[Any]) -> Any return self._value.get(key, default) def setdefault( self, key, default=None ): # type: (Union[Key, str], Any) -> Union[Item, Container] super(InlineTable, self).setdefault(key, default=default) return self[key] def __contains__(self, key): # type: (Union[Key, str]) -> bool return key in self._value def __getitem__(self, key): # type: (Union[Key, str]) -> Item return self._value[key] def __setitem__(self, key, value): # type: (Union[Key, str], Any) -> None if not isinstance(value, Item): value = item(value) self._value[key] = value if key is not None: dict.__setitem__(self, key, value) if value.trivia.comment: value.trivia.comment = "" m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if not m: return indent = m.group(1) if not isinstance(value, Whitespace): m = re.match("(?s)^([^ ]*)(.*)$", value.trivia.indent) if not m: value.trivia.indent = indent else: value.trivia.indent = m.group(1) + indent + m.group(2) def __delitem__(self, key): # type: (Union[Key, str]) -> None self.remove(key) def __len__(self): # type: () -> int return len(self._value) def __iter__(self): # type: () -> Iterator[str] return iter(self._value) def __repr__(self): return repr(self._value) def _getstate(self, protocol=3): return (self._value, self._trivia) class String(unicode, Item): def __new__(cls, t, value, original, trivia): return super(String, cls).__new__(cls, value) def __init__( self, t, _, original, trivia ): # type: (StringType, str, original, Trivia) -> None super(String, self).__init__(trivia) self._t = t self._original = original @property def discriminant(self): # type: () -> int return 11 @property def value(self): # type: () -> str return self def as_string(self): # type: () -> str return "{}{}{}".format(self._t.value, decode(self._original), self._t.value) def __add__(self, other): result = super(String, self).__add__(other) return self._new(result) def __sub__(self, other): result = super(String, self).__sub__(other) return self._new(result) def _new(self, result): return String(self._t, result, result, self._trivia) def _getstate(self, protocol=3): return self._t, unicode(self), self._original, self._trivia class AoT(Item, list): def __init__( self, body, name=None, parsed=False ): # type: (List[Table], Optional[str], bool) -> None self.name = name self._body = [] self._parsed = parsed super(AoT, self).__init__(Trivia(trail="")) for table in body: self.append(table) @property def body(self): # type: () -> List[Table] return self._body @property def discriminant(self): # type: () -> int return 12 @property def value(self): # type: () -> List[Dict[Any, Any]] return [v.value for v in self._body] def append(self, table): # type: (Table) -> Table m = re.match("(?s)^[^ ]*([ ]+).*$", self._trivia.indent) if m: indent = m.group(1) m = re.match("(?s)^([^ ]*)(.*)$", table.trivia.indent) if not m: table.trivia.indent = indent else: table.trivia.indent = m.group(1) + indent + m.group(2) if not self._parsed and "\n" not in table.trivia.indent and self._body: table.trivia.indent = "\n" + table.trivia.indent self._body.append(table) super(AoT, self).append(table) return table def as_string(self): # type: () -> str b = "" for table in self._body: b += table.as_string() return b def __repr__(self): # type: () -> str return "<AoT {}>".format(self.value) def _getstate(self, protocol=3): return self._body, self.name, self._parsed class Null(Item): def __init__(self): # type: () -> None pass @property def discriminant(self): # type: () -> int return -1 @property def value(self): # type: () -> None return None def as_string(self): # type: () -> str return "" def _getstate(self, protocol=3): return tuple()

true

f738e33442f8fe750877550660aea02e805f4126

646

py

Python

winlib/pyreadline/__init__.py

netsec/pytan

29a3484d21cb90d8896275febd1c535e4f3cdc7e

[ "MIT" ]

1

2019-01-29T21:22:06.000Z

winlib/pyreadline/__init__.py

c1rdan/pytan

5e537a6dcf4136e3b9c3905a39f073396e7f044f

[ "MIT" ]

null

winlib/pyreadline/__init__.py

c1rdan/pytan

5e537a6dcf4136e3b9c3905a39f073396e7f044f

[ "MIT" ]

null

# -*- coding: utf-8 -*- #***************************************************************************** # Copyright (C) 2003-2006 Gary Bishop. # Copyright (C) 2006 Jorgen Stenarson. <jorgen.stenarson@bostream.nu> # # Distributed under the terms of the BSD License. The full license is in # the file COPYING, distributed as part of this software. #***************************************************************************** from __future__ import print_function, unicode_literals, absolute_import from . import unicode_helper, logger, clipboard, lineeditor, modes, console from .rlmain import * from . import rlmain

46.142857

79

0.544892

from __future__ import print_function, unicode_literals, absolute_import from . import unicode_helper, logger, clipboard, lineeditor, modes, console from .rlmain import * from . import rlmain

true

f738e52b4e0b5f53940c8f7c5d99b58167225f41

5,934

py

Python

trustlab/lab/scenarios/basic_scenario.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

trustlab/lab/scenarios/basic_scenario.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

trustlab/lab/scenarios/basic_scenario.py

ValentinSiegert/aTLAS

a2e7521447f81add83a0c958d61846a1cbfbbe9c

[ "MIT" ]

null

""" This file was auto-generated by an ObjectFactory of aTLAS """ NAME = 'Basic Scenario' AGENTS = ['A', 'B', 'C', 'D'] OBSERVATIONS = [{'authors': ['A'], 'before': [], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Redecentralization_of_the_Web'}, 'message': 'Redecentralization of the Web', 'observation_id': 1, 'receiver': 'B', 'sender': 'A'}, {'authors': ['A'], 'before': [1], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web_of_Things'}, 'message': 'Web of Things', 'observation_id': 2, 'receiver': 'B', 'sender': 'A'}, {'authors': ['A'], 'before': [2], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web_Assembly'}, 'message': 'Web Assembly', 'observation_id': 3, 'receiver': 'B', 'sender': 'A'}, {'authors': ['C'], 'before': [3], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Semantic_Web_and_Linked_Open_Data'}, 'message': 'Semantic Web and Linked Open Data', 'observation_id': 4, 'receiver': 'B', 'sender': 'C'}, {'authors': ['C'], 'before': [4], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Redecentralization_of_the_Web'}, 'message': 'Redecentralization of the Web', 'observation_id': 5, 'receiver': 'B', 'sender': 'C'}, {'authors': ['C'], 'before': [5], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web-based_learning'}, 'message': 'Web-based learning', 'observation_id': 6, 'receiver': 'B', 'sender': 'C'}] HISTORY = {'A': [['B', 'http://example.com/Semantic_Web_and_Linked_Open_Data', 1.0], ['C', 'http://example.com/Web-based_learning', 1.0], ['D', 'http://example.com/Redecentralization_of_the_Web', 1.0]], 'B': [['A', 'http://example.com/Redecentralization_of_the_Web', 0.0], ['C', 'http://example.com/Web-based_learning', 0.0], ['D', 'http://example.com/Web_Assembly', 1.0]], 'C': [['A', 'http://example.com/Semantic_Web_and_Linked_Open_Data', 1.0], ['B', 'http://example.com/Web-based_learning', 1.0], ['D', 'http://example.com/Web_of_Things', 1.0]], 'D': [['A', 'http://example.com/Redecentralization_of_the_Web', 1.0], ['B', 'http://example.com/Redecentralization_of_the_Web', 1.0], ['C', 'http://example.com/Redecentralization_of_the_Web', 1.0]]} SCALES_PER_AGENT = {'A': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'B': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'C': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'D': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}} METRICS_PER_AGENT = {'A': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'B': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'C': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'D': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}} DESCRIPTION = 'This is a basic scenario with four agents.'

47.472

92

0.422144

NAME = 'Basic Scenario' AGENTS = ['A', 'B', 'C', 'D'] OBSERVATIONS = [{'authors': ['A'], 'before': [], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Redecentralization_of_the_Web'}, 'message': 'Redecentralization of the Web', 'observation_id': 1, 'receiver': 'B', 'sender': 'A'}, {'authors': ['A'], 'before': [1], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web_of_Things'}, 'message': 'Web of Things', 'observation_id': 2, 'receiver': 'B', 'sender': 'A'}, {'authors': ['A'], 'before': [2], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web_Assembly'}, 'message': 'Web Assembly', 'observation_id': 3, 'receiver': 'B', 'sender': 'A'}, {'authors': ['C'], 'before': [3], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Semantic_Web_and_Linked_Open_Data'}, 'message': 'Semantic Web and Linked Open Data', 'observation_id': 4, 'receiver': 'B', 'sender': 'C'}, {'authors': ['C'], 'before': [4], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Redecentralization_of_the_Web'}, 'message': 'Redecentralization of the Web', 'observation_id': 5, 'receiver': 'B', 'sender': 'C'}, {'authors': ['C'], 'before': [5], 'details': {'content_trust.topics': ['Web Engineering'], 'uri': 'http://example.com/Web-based_learning'}, 'message': 'Web-based learning', 'observation_id': 6, 'receiver': 'B', 'sender': 'C'}] HISTORY = {'A': [['B', 'http://example.com/Semantic_Web_and_Linked_Open_Data', 1.0], ['C', 'http://example.com/Web-based_learning', 1.0], ['D', 'http://example.com/Redecentralization_of_the_Web', 1.0]], 'B': [['A', 'http://example.com/Redecentralization_of_the_Web', 0.0], ['C', 'http://example.com/Web-based_learning', 0.0], ['D', 'http://example.com/Web_Assembly', 1.0]], 'C': [['A', 'http://example.com/Semantic_Web_and_Linked_Open_Data', 1.0], ['B', 'http://example.com/Web-based_learning', 1.0], ['D', 'http://example.com/Web_of_Things', 1.0]], 'D': [['A', 'http://example.com/Redecentralization_of_the_Web', 1.0], ['B', 'http://example.com/Redecentralization_of_the_Web', 1.0], ['C', 'http://example.com/Redecentralization_of_the_Web', 1.0]]} SCALES_PER_AGENT = {'A': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'B': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'C': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}, 'D': {'cooperation': 0.5, 'default': 0.0, 'forgivability': -0.5, 'maximum': 1.0, 'minimum': -1.0, 'name': 'Trust Scale by Marsh and Briggs (2009)', 'package': 'marsh_briggs_scale'}} METRICS_PER_AGENT = {'A': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'B': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'C': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}, 'D': {'__final__': {'name': 'weighted_average', 'weights': {}}, 'content_trust.direct_experience': {}, 'content_trust.popularity': {}, 'content_trust.recommendation': {}}} DESCRIPTION = 'This is a basic scenario with four agents.'

true

f738e53dae0449ebfaecf3213895f97f66501890

1,148

py

Python

scripts/gen__dfd_pyx.py

jgukelberger/fdint

0237323d6fd5d4161190ff7982811d8ae290f89e

[ "BSD-3-Clause" ]

11

2015-10-25T18:51:55.000Z

2021-02-26T13:05:07.000Z

scripts/gen__dfd_pyx.py

jgukelberger/fdint

0237323d6fd5d4161190ff7982811d8ae290f89e

[ "BSD-3-Clause" ]

19

2015-04-23T19:41:20.000Z

2017-08-01T02:04:04.000Z

scripts/gen__dfd_pyx.py

jgukelberger/fdint

0237323d6fd5d4161190ff7982811d8ae290f89e

[ "BSD-3-Clause" ]

10

2017-05-31T07:27:16.000Z

2021-08-28T15:34:09.000Z

# Copyright (c) 2015, Scott J Maddox. All rights reserved. # Use of this source code is governed by the BSD-3-Clause # license that can be found in the LICENSE file. import os import sys fpath = os.path.abspath(os.path.join(os.path.dirname(__file__), '../fdint/_dfd.pyx')) with open(fpath, 'w') as f: for i in range(-9,22,2)+range(0,21,2): a = str(i).replace('-','m') b = str(i+2).replace('-','m') c = (i+2)/2. f.write(""" @cython.cdivision(True) cdef inline double dfd{b}h(double phi): ''' First derivative of fd{b}h. ''' return {c}*fd{a}h(phi) """.format(a=a, b=b, c=repr(c))) for i in xrange(-9,22,2): a = str(i).replace('-','m') b = str(i+2).replace('-','m') c = (i+2)/2. for ext in ['lt_m2', 'm2_to_0', '0_to_2', '2_to_5', '5_to_10', '10_to_20', '20_to_40', 'gt_40']: f.write(""" @cython.cdivision(True) cdef inline double dfd{b}h_{ext}(double phi): ''' First derivative of fd{b}h_{ext}. ''' return {c}*fd{a}h_{ext}(phi) """.format(a=a, b=b, ext=ext, c=repr(c)))

31.888889

70

0.53223

import os import sys fpath = os.path.abspath(os.path.join(os.path.dirname(__file__), '../fdint/_dfd.pyx')) with open(fpath, 'w') as f: for i in range(-9,22,2)+range(0,21,2): a = str(i).replace('-','m') b = str(i+2).replace('-','m') c = (i+2)/2. f.write(""" @cython.cdivision(True) cdef inline double dfd{b}h(double phi): ''' First derivative of fd{b}h. ''' return {c}*fd{a}h(phi) """.format(a=a, b=b, c=repr(c))) for i in xrange(-9,22,2): a = str(i).replace('-','m') b = str(i+2).replace('-','m') c = (i+2)/2. for ext in ['lt_m2', 'm2_to_0', '0_to_2', '2_to_5', '5_to_10', '10_to_20', '20_to_40', 'gt_40']: f.write(""" @cython.cdivision(True) cdef inline double dfd{b}h_{ext}(double phi): ''' First derivative of fd{b}h_{ext}. ''' return {c}*fd{a}h_{ext}(phi) """.format(a=a, b=b, ext=ext, c=repr(c)))

true

f738e6f8d7b8453bcf33d0004fdbca2710d10727

463

py

Python

redditBotColorize/colorize_gif.py

ForeverRecompin/reddit_crawlers

e72b317dba5a8f2195de186f766192dfe873fbd4

[ "BSD-2-Clause" ]

422

2016-07-20T20:07:11.000Z

2022-02-22T18:58:11.000Z

redditBotColorize/colorize_gif.py

ForeverRecompin/reddit_crawlers

e72b317dba5a8f2195de186f766192dfe873fbd4

[ "BSD-2-Clause" ]

2

2016-08-05T15:20:04.000Z

2017-01-28T11:53:55.000Z

redditBotColorize/colorize_gif.py

ForeverRecompin/reddit_crawlers

e72b317dba5a8f2195de186f766192dfe873fbd4

[ "BSD-2-Clause" ]

61

2016-07-25T19:26:39.000Z

2021-12-17T17:23:06.000Z

import sys import cv2 import colorize import os colorize.loadDNN(False) gif_path = sys.argv[1] cam = cv2.VideoCapture(gif_path) counter = 0 while True: ret,img = cam.read() if not ret: break temp_img_path = '/tmp/%06d.jpg'%counter cv2.imwrite(temp_img_path,img) coloredImage = colorize.runDNN(temp_img_path) cv2.imwrite(temp_img_path,coloredImage) counter += 1 os.system('ffmpeg -i /tmp/\%06d.jpg colorized_%s'%gif_path)

18.52

59

0.701944

import sys import cv2 import colorize import os colorize.loadDNN(False) gif_path = sys.argv[1] cam = cv2.VideoCapture(gif_path) counter = 0 while True: ret,img = cam.read() if not ret: break temp_img_path = '/tmp/%06d.jpg'%counter cv2.imwrite(temp_img_path,img) coloredImage = colorize.runDNN(temp_img_path) cv2.imwrite(temp_img_path,coloredImage) counter += 1 os.system('ffmpeg -i /tmp/\%06d.jpg colorized_%s'%gif_path)

true

f738e719fb08c24a6742e31d1ec58bb25023459d

11,535

py

Python

dashboard/lib/flanker/addresslib/_parser/mailbox_or_url_parsetab.py

robertsimmons514/isthislegit

aa8f2b6cb2ac3de2b0fe03bb93dbceccc4c1f495

[ "BSD-3-Clause" ]

929

2015-01-01T11:14:21.000Z

2022-03-28T23:47:40.000Z

dashboard/lib/flanker/addresslib/_parser/mailbox_or_url_parsetab.py

robertsimmons514/isthislegit

aa8f2b6cb2ac3de2b0fe03bb93dbceccc4c1f495

[ "BSD-3-Clause" ]

141

2015-01-10T19:02:03.000Z

2021-07-26T18:04:14.000Z

dashboard/lib/flanker/addresslib/_parser/mailbox_or_url_parsetab.py

robertsimmons514/isthislegit

aa8f2b6cb2ac3de2b0fe03bb93dbceccc4c1f495

[ "BSD-3-Clause" ]

179

2015-01-01T18:42:46.000Z

2022-02-16T21:57:14.000Z

# mailbox_or_url_parsetab.py # This file is automatically generated. Do not edit. _tabversion = '3.10' _lr_method = 'LALR' _lr_signature = 'mailbox_or_urlFWSP AT DOT COMMA SEMICOLON LANGLE RANGLE ATOM DOT_ATOM LBRACKET RBRACKET DTEXT DQUOTE QTEXT QPAIR LPAREN RPAREN CTEXT URLmailbox_or_url_list : mailbox_or_url_list delim mailbox_or_url\n | mailbox_or_url_list delim\n | mailbox_or_urldelim : delim fwsp COMMA\n | delim fwsp SEMICOLON\n | COMMA\n | SEMICOLONmailbox_or_url : mailbox\n | urlurl : ofwsp URL ofwspmailbox : addr_spec\n | angle_addr\n | name_addrname_addr : ofwsp phrase angle_addrangle_addr : ofwsp LANGLE addr_spec RANGLE ofwspaddr_spec : ofwsp local_part AT domain ofwsplocal_part : DOT_ATOM\n | ATOM\n | quoted_stringdomain : DOT_ATOM\n | ATOM\n | domain_literalquoted_string : DQUOTE quoted_string_text DQUOTE\n | DQUOTE DQUOTEquoted_string_text : quoted_string_text QTEXT\n | quoted_string_text QPAIR\n | quoted_string_text fwsp\n | QTEXT\n | QPAIR\n | fwspdomain_literal : LBRACKET domain_literal_text RBRACKET\n | LBRACKET RBRACKETdomain_literal_text : domain_literal_text DTEXT\n | domain_literal_text fwsp\n | DTEXT\n | fwspcomment : LPAREN comment_text RPAREN\n | LPAREN RPARENcomment_text : comment_text CTEXT\n | comment_text fwsp\n | CTEXT\n | fwspphrase : phrase fwsp ATOM\n | phrase fwsp DOT_ATOM\n | phrase fwsp DOT\n | phrase fwsp quoted_string\n | phrase ATOM\n | phrase DOT_ATOM\n | phrase DOT\n | phrase quoted_string\n | ATOM\n | DOT_ATOM\n | DOT\n | quoted_stringofwsp : fwsp comment fwsp\n | fwsp comment\n | comment fwsp\n | comment\n | fwsp\n |fwsp : FWSP' _lr_action_items = {'FWSP':([0,2,7,11,12,14,15,17,18,19,20,21,22,23,24,25,26,32,33,34,35,36,40,41,42,43,44,45,46,50,51,52,53,54,55,56,57,58,59,60,61,62,63,66,67,68,69,70,71,72,],[7,7,-61,7,7,7,7,-51,7,-52,7,-54,-53,-42,7,-38,-41,-30,-29,-28,-24,7,-48,-47,-50,-49,-40,-37,-39,7,7,7,-20,-21,-22,-27,-26,-25,-23,-44,-43,-46,-45,-36,-35,7,-32,-34,-33,-31,]),'LANGLE':([0,1,2,4,7,12,13,17,19,20,21,22,25,27,35,37,38,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,14,-61,-56,-57,-51,-52,-60,-54,-53,-38,-55,-24,-59,14,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'QPAIR':([7,18,32,33,34,36,56,57,58,],[-61,33,-30,-29,-28,57,-27,-26,-25,]),'URL':([0,1,2,4,7,12,13,25,27,45,],[-60,-59,-58,15,-61,-56,-57,-38,-55,-37,]),'QTEXT':([7,18,32,33,34,36,56,57,58,],[-61,34,-30,-29,-28,58,-27,-26,-25,]),'DTEXT':([7,52,66,67,68,70,71,],[-61,67,-36,-35,71,-34,-33,]),'DQUOTE':([0,1,2,4,7,12,13,14,17,18,19,20,21,22,25,27,28,32,33,34,35,36,37,40,41,42,43,45,56,57,58,59,60,61,62,63,],[-60,-59,-58,18,-61,-56,-57,-60,-51,35,-52,18,-54,-53,-38,-55,18,-30,-29,-28,-24,59,18,-48,-47,-50,-49,-37,-27,-26,-25,-23,-44,-43,-46,-45,]),'LBRACKET':([31,],[52,]),'DOT_ATOM':([0,1,2,4,7,12,13,14,17,19,20,21,22,25,27,28,31,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,19,-61,-56,-57,-60,-51,-52,40,-54,-53,-38,-55,47,53,-24,60,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'RPAREN':([7,11,23,24,26,44,46,],[-61,25,-42,45,-41,-40,-39,]),'AT':([16,17,19,21,35,47,48,49,59,],[31,-18,-17,-19,-24,-17,-18,-19,-23,]),'LPAREN':([0,1,7,14,15,17,19,20,21,22,35,37,40,41,42,43,50,51,53,54,55,59,60,61,62,63,69,72,],[11,11,-61,11,11,-51,-52,11,-54,-53,-24,11,-48,-47,-50,-49,11,11,-20,-21,-22,-23,-44,-43,-46,-45,-32,-31,]),'ATOM':([0,1,2,4,7,12,13,14,17,19,20,21,22,25,27,28,31,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,17,-61,-56,-57,-60,-51,-52,41,-54,-53,-38,-55,48,54,-24,61,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'RANGLE':([1,2,7,12,13,25,27,29,45,51,53,54,55,65,69,72,],[-59,-58,-61,-56,-57,-38,-55,50,-37,-60,-20,-21,-22,-16,-32,-31,]),'RBRACKET':([7,52,66,67,68,70,71,],[-61,69,-36,-35,72,-34,-33,]),'CTEXT':([7,11,23,24,26,44,46,],[-61,26,-42,46,-41,-40,-39,]),'DOT':([0,1,2,4,7,12,13,17,19,20,21,22,25,27,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,22,-61,-56,-57,-51,-52,43,-54,-53,-38,-55,-24,63,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'$end':([1,2,3,5,6,7,8,9,10,12,13,15,25,27,30,39,45,50,51,53,54,55,64,65,69,72,],[-59,-58,-13,-12,0,-61,-8,-9,-11,-56,-57,-60,-38,-55,-10,-14,-37,-60,-60,-20,-21,-22,-15,-16,-32,-31,]),} _lr_action = {} for _k, _v in _lr_action_items.items(): for _x,_y in zip(_v[0],_v[1]): if not _x in _lr_action: _lr_action[_x] = {} _lr_action[_x][_k] = _y del _lr_action_items _lr_goto_items = {'fwsp':([0,2,11,12,14,15,18,20,24,36,50,51,52,68,],[1,13,23,27,1,1,32,37,44,56,1,1,66,70,]),'comment':([0,1,14,15,20,37,50,51,],[2,12,2,2,2,12,2,2,]),'domain':([31,],[51,]),'comment_text':([11,],[24,]),'name_addr':([0,],[3,]),'ofwsp':([0,14,15,20,50,51,],[4,28,30,38,64,65,]),'angle_addr':([0,20,],[5,39,]),'mailbox_or_url':([0,],[6,]),'local_part':([4,28,],[16,16,]),'domain_literal_text':([52,],[68,]),'mailbox':([0,],[8,]),'quoted_string_text':([18,],[36,]),'url':([0,],[9,]),'addr_spec':([0,14,],[10,29,]),'phrase':([4,],[20,]),'quoted_string':([4,20,28,37,],[21,42,49,62,]),'domain_literal':([31,],[55,]),} _lr_goto = {} for _k, _v in _lr_goto_items.items(): for _x, _y in zip(_v[0], _v[1]): if not _x in _lr_goto: _lr_goto[_x] = {} _lr_goto[_x][_k] = _y del _lr_goto_items _lr_productions = [ ("S' -> mailbox_or_url","S'",1,None,None,None), ('mailbox_or_url_list -> mailbox_or_url_list delim mailbox_or_url','mailbox_or_url_list',3,'p_expression_mailbox_or_url_list','parser.py',19), ('mailbox_or_url_list -> mailbox_or_url_list delim','mailbox_or_url_list',2,'p_expression_mailbox_or_url_list','parser.py',20), ('mailbox_or_url_list -> mailbox_or_url','mailbox_or_url_list',1,'p_expression_mailbox_or_url_list','parser.py',21), ('delim -> delim fwsp COMMA','delim',3,'p_delim','parser.py',30), ('delim -> delim fwsp SEMICOLON','delim',3,'p_delim','parser.py',31), ('delim -> COMMA','delim',1,'p_delim','parser.py',32), ('delim -> SEMICOLON','delim',1,'p_delim','parser.py',33), ('mailbox_or_url -> mailbox','mailbox_or_url',1,'p_expression_mailbox_or_url','parser.py',36), ('mailbox_or_url -> url','mailbox_or_url',1,'p_expression_mailbox_or_url','parser.py',37), ('url -> ofwsp URL ofwsp','url',3,'p_expression_url','parser.py',41), ('mailbox -> addr_spec','mailbox',1,'p_expression_mailbox','parser.py',45), ('mailbox -> angle_addr','mailbox',1,'p_expression_mailbox','parser.py',46), ('mailbox -> name_addr','mailbox',1,'p_expression_mailbox','parser.py',47), ('name_addr -> ofwsp phrase angle_addr','name_addr',3,'p_expression_name_addr','parser.py',51), ('angle_addr -> ofwsp LANGLE addr_spec RANGLE ofwsp','angle_addr',5,'p_expression_angle_addr','parser.py',55), ('addr_spec -> ofwsp local_part AT domain ofwsp','addr_spec',5,'p_expression_addr_spec','parser.py',59), ('local_part -> DOT_ATOM','local_part',1,'p_expression_local_part','parser.py',63), ('local_part -> ATOM','local_part',1,'p_expression_local_part','parser.py',64), ('local_part -> quoted_string','local_part',1,'p_expression_local_part','parser.py',65), ('domain -> DOT_ATOM','domain',1,'p_expression_domain','parser.py',69), ('domain -> ATOM','domain',1,'p_expression_domain','parser.py',70), ('domain -> domain_literal','domain',1,'p_expression_domain','parser.py',71), ('quoted_string -> DQUOTE quoted_string_text DQUOTE','quoted_string',3,'p_expression_quoted_string','parser.py',75), ('quoted_string -> DQUOTE DQUOTE','quoted_string',2,'p_expression_quoted_string','parser.py',76), ('quoted_string_text -> quoted_string_text QTEXT','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',83), ('quoted_string_text -> quoted_string_text QPAIR','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',84), ('quoted_string_text -> quoted_string_text fwsp','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',85), ('quoted_string_text -> QTEXT','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',86), ('quoted_string_text -> QPAIR','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',87), ('quoted_string_text -> fwsp','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',88), ('domain_literal -> LBRACKET domain_literal_text RBRACKET','domain_literal',3,'p_expression_domain_literal','parser.py',92), ('domain_literal -> LBRACKET RBRACKET','domain_literal',2,'p_expression_domain_literal','parser.py',93), ('domain_literal_text -> domain_literal_text DTEXT','domain_literal_text',2,'p_expression_domain_literal_text','parser.py',100), ('domain_literal_text -> domain_literal_text fwsp','domain_literal_text',2,'p_expression_domain_literal_text','parser.py',101), ('domain_literal_text -> DTEXT','domain_literal_text',1,'p_expression_domain_literal_text','parser.py',102), ('domain_literal_text -> fwsp','domain_literal_text',1,'p_expression_domain_literal_text','parser.py',103), ('comment -> LPAREN comment_text RPAREN','comment',3,'p_expression_comment','parser.py',107), ('comment -> LPAREN RPAREN','comment',2,'p_expression_comment','parser.py',108), ('comment_text -> comment_text CTEXT','comment_text',2,'p_expression_comment_text','parser.py',112), ('comment_text -> comment_text fwsp','comment_text',2,'p_expression_comment_text','parser.py',113), ('comment_text -> CTEXT','comment_text',1,'p_expression_comment_text','parser.py',114), ('comment_text -> fwsp','comment_text',1,'p_expression_comment_text','parser.py',115), ('phrase -> phrase fwsp ATOM','phrase',3,'p_expression_phrase','parser.py',119), ('phrase -> phrase fwsp DOT_ATOM','phrase',3,'p_expression_phrase','parser.py',120), ('phrase -> phrase fwsp DOT','phrase',3,'p_expression_phrase','parser.py',121), ('phrase -> phrase fwsp quoted_string','phrase',3,'p_expression_phrase','parser.py',122), ('phrase -> phrase ATOM','phrase',2,'p_expression_phrase','parser.py',123), ('phrase -> phrase DOT_ATOM','phrase',2,'p_expression_phrase','parser.py',124), ('phrase -> phrase DOT','phrase',2,'p_expression_phrase','parser.py',125), ('phrase -> phrase quoted_string','phrase',2,'p_expression_phrase','parser.py',126), ('phrase -> ATOM','phrase',1,'p_expression_phrase','parser.py',127), ('phrase -> DOT_ATOM','phrase',1,'p_expression_phrase','parser.py',128), ('phrase -> DOT','phrase',1,'p_expression_phrase','parser.py',129), ('phrase -> quoted_string','phrase',1,'p_expression_phrase','parser.py',130), ('ofwsp -> fwsp comment fwsp','ofwsp',3,'p_expression_ofwsp','parser.py',139), ('ofwsp -> fwsp comment','ofwsp',2,'p_expression_ofwsp','parser.py',140), ('ofwsp -> comment fwsp','ofwsp',2,'p_expression_ofwsp','parser.py',141), ('ofwsp -> comment','ofwsp',1,'p_expression_ofwsp','parser.py',142), ('ofwsp -> fwsp','ofwsp',1,'p_expression_ofwsp','parser.py',143), ('ofwsp -> <empty>','ofwsp',0,'p_expression_ofwsp','parser.py',144), ('fwsp -> FWSP','fwsp',1,'p_expression_fwsp','parser.py',148), ]

126.758242

2,514

0.638231

_tabversion = '3.10' _lr_method = 'LALR' _lr_signature = 'mailbox_or_urlFWSP AT DOT COMMA SEMICOLON LANGLE RANGLE ATOM DOT_ATOM LBRACKET RBRACKET DTEXT DQUOTE QTEXT QPAIR LPAREN RPAREN CTEXT URLmailbox_or_url_list : mailbox_or_url_list delim mailbox_or_url\n | mailbox_or_url_list delim\n | mailbox_or_urldelim : delim fwsp COMMA\n | delim fwsp SEMICOLON\n | COMMA\n | SEMICOLONmailbox_or_url : mailbox\n | urlurl : ofwsp URL ofwspmailbox : addr_spec\n | angle_addr\n | name_addrname_addr : ofwsp phrase angle_addrangle_addr : ofwsp LANGLE addr_spec RANGLE ofwspaddr_spec : ofwsp local_part AT domain ofwsplocal_part : DOT_ATOM\n | ATOM\n | quoted_stringdomain : DOT_ATOM\n | ATOM\n | domain_literalquoted_string : DQUOTE quoted_string_text DQUOTE\n | DQUOTE DQUOTEquoted_string_text : quoted_string_text QTEXT\n | quoted_string_text QPAIR\n | quoted_string_text fwsp\n | QTEXT\n | QPAIR\n | fwspdomain_literal : LBRACKET domain_literal_text RBRACKET\n | LBRACKET RBRACKETdomain_literal_text : domain_literal_text DTEXT\n | domain_literal_text fwsp\n | DTEXT\n | fwspcomment : LPAREN comment_text RPAREN\n | LPAREN RPARENcomment_text : comment_text CTEXT\n | comment_text fwsp\n | CTEXT\n | fwspphrase : phrase fwsp ATOM\n | phrase fwsp DOT_ATOM\n | phrase fwsp DOT\n | phrase fwsp quoted_string\n | phrase ATOM\n | phrase DOT_ATOM\n | phrase DOT\n | phrase quoted_string\n | ATOM\n | DOT_ATOM\n | DOT\n | quoted_stringofwsp : fwsp comment fwsp\n | fwsp comment\n | comment fwsp\n | comment\n | fwsp\n |fwsp : FWSP' _lr_action_items = {'FWSP':([0,2,7,11,12,14,15,17,18,19,20,21,22,23,24,25,26,32,33,34,35,36,40,41,42,43,44,45,46,50,51,52,53,54,55,56,57,58,59,60,61,62,63,66,67,68,69,70,71,72,],[7,7,-61,7,7,7,7,-51,7,-52,7,-54,-53,-42,7,-38,-41,-30,-29,-28,-24,7,-48,-47,-50,-49,-40,-37,-39,7,7,7,-20,-21,-22,-27,-26,-25,-23,-44,-43,-46,-45,-36,-35,7,-32,-34,-33,-31,]),'LANGLE':([0,1,2,4,7,12,13,17,19,20,21,22,25,27,35,37,38,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,14,-61,-56,-57,-51,-52,-60,-54,-53,-38,-55,-24,-59,14,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'QPAIR':([7,18,32,33,34,36,56,57,58,],[-61,33,-30,-29,-28,57,-27,-26,-25,]),'URL':([0,1,2,4,7,12,13,25,27,45,],[-60,-59,-58,15,-61,-56,-57,-38,-55,-37,]),'QTEXT':([7,18,32,33,34,36,56,57,58,],[-61,34,-30,-29,-28,58,-27,-26,-25,]),'DTEXT':([7,52,66,67,68,70,71,],[-61,67,-36,-35,71,-34,-33,]),'DQUOTE':([0,1,2,4,7,12,13,14,17,18,19,20,21,22,25,27,28,32,33,34,35,36,37,40,41,42,43,45,56,57,58,59,60,61,62,63,],[-60,-59,-58,18,-61,-56,-57,-60,-51,35,-52,18,-54,-53,-38,-55,18,-30,-29,-28,-24,59,18,-48,-47,-50,-49,-37,-27,-26,-25,-23,-44,-43,-46,-45,]),'LBRACKET':([31,],[52,]),'DOT_ATOM':([0,1,2,4,7,12,13,14,17,19,20,21,22,25,27,28,31,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,19,-61,-56,-57,-60,-51,-52,40,-54,-53,-38,-55,47,53,-24,60,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'RPAREN':([7,11,23,24,26,44,46,],[-61,25,-42,45,-41,-40,-39,]),'AT':([16,17,19,21,35,47,48,49,59,],[31,-18,-17,-19,-24,-17,-18,-19,-23,]),'LPAREN':([0,1,7,14,15,17,19,20,21,22,35,37,40,41,42,43,50,51,53,54,55,59,60,61,62,63,69,72,],[11,11,-61,11,11,-51,-52,11,-54,-53,-24,11,-48,-47,-50,-49,11,11,-20,-21,-22,-23,-44,-43,-46,-45,-32,-31,]),'ATOM':([0,1,2,4,7,12,13,14,17,19,20,21,22,25,27,28,31,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,17,-61,-56,-57,-60,-51,-52,41,-54,-53,-38,-55,48,54,-24,61,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'RANGLE':([1,2,7,12,13,25,27,29,45,51,53,54,55,65,69,72,],[-59,-58,-61,-56,-57,-38,-55,50,-37,-60,-20,-21,-22,-16,-32,-31,]),'RBRACKET':([7,52,66,67,68,70,71,],[-61,69,-36,-35,72,-34,-33,]),'CTEXT':([7,11,23,24,26,44,46,],[-61,26,-42,46,-41,-40,-39,]),'DOT':([0,1,2,4,7,12,13,17,19,20,21,22,25,27,35,37,40,41,42,43,45,59,60,61,62,63,],[-60,-59,-58,22,-61,-56,-57,-51,-52,43,-54,-53,-38,-55,-24,63,-48,-47,-50,-49,-37,-23,-44,-43,-46,-45,]),'$end':([1,2,3,5,6,7,8,9,10,12,13,15,25,27,30,39,45,50,51,53,54,55,64,65,69,72,],[-59,-58,-13,-12,0,-61,-8,-9,-11,-56,-57,-60,-38,-55,-10,-14,-37,-60,-60,-20,-21,-22,-15,-16,-32,-31,]),} _lr_action = {} for _k, _v in _lr_action_items.items(): for _x,_y in zip(_v[0],_v[1]): if not _x in _lr_action: _lr_action[_x] = {} _lr_action[_x][_k] = _y del _lr_action_items _lr_goto_items = {'fwsp':([0,2,11,12,14,15,18,20,24,36,50,51,52,68,],[1,13,23,27,1,1,32,37,44,56,1,1,66,70,]),'comment':([0,1,14,15,20,37,50,51,],[2,12,2,2,2,12,2,2,]),'domain':([31,],[51,]),'comment_text':([11,],[24,]),'name_addr':([0,],[3,]),'ofwsp':([0,14,15,20,50,51,],[4,28,30,38,64,65,]),'angle_addr':([0,20,],[5,39,]),'mailbox_or_url':([0,],[6,]),'local_part':([4,28,],[16,16,]),'domain_literal_text':([52,],[68,]),'mailbox':([0,],[8,]),'quoted_string_text':([18,],[36,]),'url':([0,],[9,]),'addr_spec':([0,14,],[10,29,]),'phrase':([4,],[20,]),'quoted_string':([4,20,28,37,],[21,42,49,62,]),'domain_literal':([31,],[55,]),} _lr_goto = {} for _k, _v in _lr_goto_items.items(): for _x, _y in zip(_v[0], _v[1]): if not _x in _lr_goto: _lr_goto[_x] = {} _lr_goto[_x][_k] = _y del _lr_goto_items _lr_productions = [ ("S' -> mailbox_or_url","S'",1,None,None,None), ('mailbox_or_url_list -> mailbox_or_url_list delim mailbox_or_url','mailbox_or_url_list',3,'p_expression_mailbox_or_url_list','parser.py',19), ('mailbox_or_url_list -> mailbox_or_url_list delim','mailbox_or_url_list',2,'p_expression_mailbox_or_url_list','parser.py',20), ('mailbox_or_url_list -> mailbox_or_url','mailbox_or_url_list',1,'p_expression_mailbox_or_url_list','parser.py',21), ('delim -> delim fwsp COMMA','delim',3,'p_delim','parser.py',30), ('delim -> delim fwsp SEMICOLON','delim',3,'p_delim','parser.py',31), ('delim -> COMMA','delim',1,'p_delim','parser.py',32), ('delim -> SEMICOLON','delim',1,'p_delim','parser.py',33), ('mailbox_or_url -> mailbox','mailbox_or_url',1,'p_expression_mailbox_or_url','parser.py',36), ('mailbox_or_url -> url','mailbox_or_url',1,'p_expression_mailbox_or_url','parser.py',37), ('url -> ofwsp URL ofwsp','url',3,'p_expression_url','parser.py',41), ('mailbox -> addr_spec','mailbox',1,'p_expression_mailbox','parser.py',45), ('mailbox -> angle_addr','mailbox',1,'p_expression_mailbox','parser.py',46), ('mailbox -> name_addr','mailbox',1,'p_expression_mailbox','parser.py',47), ('name_addr -> ofwsp phrase angle_addr','name_addr',3,'p_expression_name_addr','parser.py',51), ('angle_addr -> ofwsp LANGLE addr_spec RANGLE ofwsp','angle_addr',5,'p_expression_angle_addr','parser.py',55), ('addr_spec -> ofwsp local_part AT domain ofwsp','addr_spec',5,'p_expression_addr_spec','parser.py',59), ('local_part -> DOT_ATOM','local_part',1,'p_expression_local_part','parser.py',63), ('local_part -> ATOM','local_part',1,'p_expression_local_part','parser.py',64), ('local_part -> quoted_string','local_part',1,'p_expression_local_part','parser.py',65), ('domain -> DOT_ATOM','domain',1,'p_expression_domain','parser.py',69), ('domain -> ATOM','domain',1,'p_expression_domain','parser.py',70), ('domain -> domain_literal','domain',1,'p_expression_domain','parser.py',71), ('quoted_string -> DQUOTE quoted_string_text DQUOTE','quoted_string',3,'p_expression_quoted_string','parser.py',75), ('quoted_string -> DQUOTE DQUOTE','quoted_string',2,'p_expression_quoted_string','parser.py',76), ('quoted_string_text -> quoted_string_text QTEXT','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',83), ('quoted_string_text -> quoted_string_text QPAIR','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',84), ('quoted_string_text -> quoted_string_text fwsp','quoted_string_text',2,'p_expression_quoted_string_text','parser.py',85), ('quoted_string_text -> QTEXT','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',86), ('quoted_string_text -> QPAIR','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',87), ('quoted_string_text -> fwsp','quoted_string_text',1,'p_expression_quoted_string_text','parser.py',88), ('domain_literal -> LBRACKET domain_literal_text RBRACKET','domain_literal',3,'p_expression_domain_literal','parser.py',92), ('domain_literal -> LBRACKET RBRACKET','domain_literal',2,'p_expression_domain_literal','parser.py',93), ('domain_literal_text -> domain_literal_text DTEXT','domain_literal_text',2,'p_expression_domain_literal_text','parser.py',100), ('domain_literal_text -> domain_literal_text fwsp','domain_literal_text',2,'p_expression_domain_literal_text','parser.py',101), ('domain_literal_text -> DTEXT','domain_literal_text',1,'p_expression_domain_literal_text','parser.py',102), ('domain_literal_text -> fwsp','domain_literal_text',1,'p_expression_domain_literal_text','parser.py',103), ('comment -> LPAREN comment_text RPAREN','comment',3,'p_expression_comment','parser.py',107), ('comment -> LPAREN RPAREN','comment',2,'p_expression_comment','parser.py',108), ('comment_text -> comment_text CTEXT','comment_text',2,'p_expression_comment_text','parser.py',112), ('comment_text -> comment_text fwsp','comment_text',2,'p_expression_comment_text','parser.py',113), ('comment_text -> CTEXT','comment_text',1,'p_expression_comment_text','parser.py',114), ('comment_text -> fwsp','comment_text',1,'p_expression_comment_text','parser.py',115), ('phrase -> phrase fwsp ATOM','phrase',3,'p_expression_phrase','parser.py',119), ('phrase -> phrase fwsp DOT_ATOM','phrase',3,'p_expression_phrase','parser.py',120), ('phrase -> phrase fwsp DOT','phrase',3,'p_expression_phrase','parser.py',121), ('phrase -> phrase fwsp quoted_string','phrase',3,'p_expression_phrase','parser.py',122), ('phrase -> phrase ATOM','phrase',2,'p_expression_phrase','parser.py',123), ('phrase -> phrase DOT_ATOM','phrase',2,'p_expression_phrase','parser.py',124), ('phrase -> phrase DOT','phrase',2,'p_expression_phrase','parser.py',125), ('phrase -> phrase quoted_string','phrase',2,'p_expression_phrase','parser.py',126), ('phrase -> ATOM','phrase',1,'p_expression_phrase','parser.py',127), ('phrase -> DOT_ATOM','phrase',1,'p_expression_phrase','parser.py',128), ('phrase -> DOT','phrase',1,'p_expression_phrase','parser.py',129), ('phrase -> quoted_string','phrase',1,'p_expression_phrase','parser.py',130), ('ofwsp -> fwsp comment fwsp','ofwsp',3,'p_expression_ofwsp','parser.py',139), ('ofwsp -> fwsp comment','ofwsp',2,'p_expression_ofwsp','parser.py',140), ('ofwsp -> comment fwsp','ofwsp',2,'p_expression_ofwsp','parser.py',141), ('ofwsp -> comment','ofwsp',1,'p_expression_ofwsp','parser.py',142), ('ofwsp -> fwsp','ofwsp',1,'p_expression_ofwsp','parser.py',143), ('ofwsp -> <empty>','ofwsp',0,'p_expression_ofwsp','parser.py',144), ('fwsp -> FWSP','fwsp',1,'p_expression_fwsp','parser.py',148), ]

true

f738e78252750acaa726dff41bb06d29194b1d5d

1,556

py

Python

2018/7/7.py

kristianwiklund/AOC2019

a98affaccd53ca4ea2d3a8c3fa125680f1e8cc08

[ "MIT" ]

3

2020-12-02T18:18:05.000Z

2021-12-03T18:39:26.000Z

2018/7/7.py

kristianwiklund/AOC2019

a98affaccd53ca4ea2d3a8c3fa125680f1e8cc08

[ "MIT" ]

null

2018/7/7.py

kristianwiklund/AOC2019

a98affaccd53ca4ea2d3a8c3fa125680f1e8cc08

[ "MIT" ]

null

import networkx as nx import matplotlib.pyplot as plt G = nx.DiGraph() #with open ("shortinput.txt") as fd: with open ("input.txt") as fd: for line in fd: x = line.split(" ") before = x[1] after = x[7] G.add_edge(before, after, weight=ord(after)-64) nx.draw(G, with_labels=True) plt.savefig("maze.png") helalistan=list(nx.lexicographical_topological_sort(G)) print("7A :"+"".join(helalistan)) # --------------------- #ACHOQRXSEKUGMYIWDZLNBFTJVP time=0 workers = [0,0,0,0,0,0,0,0,0,0] doing = [None, None,None,None,None,None,None,None,None] while list(G.nodes()) != []: for i in range(0,6): if workers[i] <= 0: # finish what was done, then pull something if doing[i]: # print ("Worker "+str(i)+" is done with "+doing[i]) G.remove_node(doing[i]) doing[i] = None for j in helalistan: #print ("Trying to pull node "+j) if not j in doing: #print ("Nobody is working on "+j) if G.has_node(j) and list(G.predecessors(j)) == []: # print ("Worker "+str(i)+" pulls node "+j) doing[i] = j workers[i] = 60+ord(j)-65 break else: workers[i] = workers[i] - 1 # print("Tick: "+str(time) + " working on "+str(doing)) time=time+1 print("Total time for assembly: "+str(time-1))

24.3125

71

0.492288

import networkx as nx import matplotlib.pyplot as plt G = nx.DiGraph() with open ("input.txt") as fd: for line in fd: x = line.split(" ") before = x[1] after = x[7] G.add_edge(before, after, weight=ord(after)-64) nx.draw(G, with_labels=True) plt.savefig("maze.png") helalistan=list(nx.lexicographical_topological_sort(G)) print("7A :"+"".join(helalistan)) time=0 workers = [0,0,0,0,0,0,0,0,0,0] doing = [None, None,None,None,None,None,None,None,None] while list(G.nodes()) != []: for i in range(0,6): if workers[i] <= 0: if doing[i]: G.remove_node(doing[i]) doing[i] = None for j in helalistan: if not j in doing: if G.has_node(j) and list(G.predecessors(j)) == []: doing[i] = j workers[i] = 60+ord(j)-65 break else: workers[i] = workers[i] - 1 time=time+1 print("Total time for assembly: "+str(time-1))

true

f738e7edc1e0b3c55014c9a208313ddbb2ef668a

1,812

py

Python

api/main.py

MineiToshio/cryptongo

3cb1eddf45bf87a47a32597f7fa66eb8ac932f4a

[ "MIT" ]

2

2019-09-25T18:13:34.000Z

2020-02-13T16:54:13.000Z

api/main.py

MineiToshio/cryptongo

3cb1eddf45bf87a47a32597f7fa66eb8ac932f4a

[ "MIT" ]

null

api/main.py

MineiToshio/cryptongo

3cb1eddf45bf87a47a32597f7fa66eb8ac932f4a

[ "MIT" ]

null

import pymongo from flask import Flask, jsonify, request def get_db_connection(uri): client = pymongo.MongoClient(uri) return client.cryptongo app = Flask(__name__) db_connection = get_db_connection('mongodb://localhost:27017/') def get_documents(): params = {} name = request.args.get('name', '') limit = int(request.args.get('limit', 0)) if name: params.update({'name': name}) cursor = db_connection.tickers.find(params, {'_id':0, 'ticker_hash':0}).limit(limit) return list(cursor) def get_top20(): params = {} name = request.args.get('name', '') limit = int(request.args.get('limit', 0)) if name: params.update({'name': name}) params.update({'rank': {'$lte': 20}}) cursor = db_connection.tickers.find( params, {'_id': 0, 'ticker_hash': 0} ).limit(limit) return list(cursor) def remove_currency(): params = {} name = request.args.get('name', '') if name: params.update({'name': name}) else: return False return db_connection.tickers.delete_many(params).deleted_count #Correr el comando "FLASK_APP=main.py flask run" @app.route("/") def index(): return jsonify( { 'name': 'Cryptongo API' } ) @app.route('/tickers', methods=['GET', 'DELETE']) def tickers(): if request.method == 'GET': return jsonify(get_documents()) elif request.method == 'DELETE': result = remove_currency() if result > 0: return jsonify({ 'text': 'Documentos eliminados' }), 204 else: return jsonify({ 'error': 'No se encontraron los documentos' }), 404 @app.route("/top20", methods=['GET']) def top20(): return jsonify( get_top20() )

25.521127

88

0.587196

import pymongo from flask import Flask, jsonify, request def get_db_connection(uri): client = pymongo.MongoClient(uri) return client.cryptongo app = Flask(__name__) db_connection = get_db_connection('mongodb://localhost:27017/') def get_documents(): params = {} name = request.args.get('name', '') limit = int(request.args.get('limit', 0)) if name: params.update({'name': name}) cursor = db_connection.tickers.find(params, {'_id':0, 'ticker_hash':0}).limit(limit) return list(cursor) def get_top20(): params = {} name = request.args.get('name', '') limit = int(request.args.get('limit', 0)) if name: params.update({'name': name}) params.update({'rank': {'$lte': 20}}) cursor = db_connection.tickers.find( params, {'_id': 0, 'ticker_hash': 0} ).limit(limit) return list(cursor) def remove_currency(): params = {} name = request.args.get('name', '') if name: params.update({'name': name}) else: return False return db_connection.tickers.delete_many(params).deleted_count @app.route("/") def index(): return jsonify( { 'name': 'Cryptongo API' } ) @app.route('/tickers', methods=['GET', 'DELETE']) def tickers(): if request.method == 'GET': return jsonify(get_documents()) elif request.method == 'DELETE': result = remove_currency() if result > 0: return jsonify({ 'text': 'Documentos eliminados' }), 204 else: return jsonify({ 'error': 'No se encontraron los documentos' }), 404 @app.route("/top20", methods=['GET']) def top20(): return jsonify( get_top20() )

true

f738e8009f71e7b6b6f5602de347597c0a56c06c

1,302

py

Python

node_modules/_npm@6.14.9@npm/node_modules/node-gyp/gyp/gyp_main.py

TT555666/cms-server

8b8302af597615501743042163504987fb27269e

[ "MIT" ]

1,666

2017-01-12T03:58:44.000Z

2017-08-20T23:39:20.000Z

node_modules/node-gyp/gyp/gyp_main.py

BABY636-Guarda-CRUX/cli

abdf52879fcf0e0f534ad977931f6935f5d1dce3

[ "Artistic-2.0" ]

95

2017-08-21T07:38:56.000Z

2022-02-18T21:59:54.000Z

node_modules/node-gyp/gyp/gyp_main.py

mtdev2/cli

d73879893ca7c1d0ce2b5fcb2364200955febfc0

[ "Artistic-2.0" ]

161

2017-08-25T20:20:01.000Z

2022-02-08T02:59:03.000Z

#!/usr/bin/env python # Copyright (c) 2009 Google Inc. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import os import sys import subprocess PY3 = bytes != str # Below IsCygwin() function copied from pylib/gyp/common.py def IsCygwin(): try: out = subprocess.Popen("uname", stdout=subprocess.PIPE, stderr=subprocess.STDOUT) stdout, stderr = out.communicate() if PY3: stdout = stdout.decode("utf-8") return "CYGWIN" in str(stdout) except Exception: return False def UnixifyPath(path): try: if not IsCygwin(): return path out = subprocess.Popen(["cygpath", "-u", path], stdout=subprocess.PIPE, stderr=subprocess.STDOUT) stdout, _ = out.communicate() if PY3: stdout = stdout.decode("utf-8") return str(stdout) except Exception: return path # Make sure we're using the version of pylib in this repo, not one installed # elsewhere on the system. Also convert to Unix style path on Cygwin systems, # else the 'gyp' library will not be found path = UnixifyPath(sys.argv[0]) sys.path.insert(0, os.path.join(os.path.dirname(path), 'pylib')) import gyp if __name__ == '__main__': sys.exit(gyp.script_main())

25.529412

77

0.672811

import os import sys import subprocess PY3 = bytes != str def IsCygwin(): try: out = subprocess.Popen("uname", stdout=subprocess.PIPE, stderr=subprocess.STDOUT) stdout, stderr = out.communicate() if PY3: stdout = stdout.decode("utf-8") return "CYGWIN" in str(stdout) except Exception: return False def UnixifyPath(path): try: if not IsCygwin(): return path out = subprocess.Popen(["cygpath", "-u", path], stdout=subprocess.PIPE, stderr=subprocess.STDOUT) stdout, _ = out.communicate() if PY3: stdout = stdout.decode("utf-8") return str(stdout) except Exception: return path # elsewhere on the system. Also convert to Unix style path on Cygwin systems, # else the 'gyp' library will not be found path = UnixifyPath(sys.argv[0]) sys.path.insert(0, os.path.join(os.path.dirname(path), 'pylib')) import gyp if __name__ == '__main__': sys.exit(gyp.script_main())

true

f738e865f19a3185e155cb3d9afeef9554d24a04

5,739

py

Python

data/anthro.py

WadhwaniAI/ESTRNN

4af8d53b0ebb1655c40aaf4f6950904580a34aa2

[ "MIT" ]

null

data/anthro.py

WadhwaniAI/ESTRNN

4af8d53b0ebb1655c40aaf4f6950904580a34aa2

[ "MIT" ]

null

data/anthro.py

WadhwaniAI/ESTRNN

4af8d53b0ebb1655c40aaf4f6950904580a34aa2

[ "MIT" ]

null

import os import random from os.path import join, basename, dirname import cv2 import numpy as np import torch from glob import glob import ipdb from torch.utils.data import Dataset, DataLoader from torchvision import transforms from utils import normalize, Crop, Flip, ToTensor class AnthroDeblurDataset(Dataset): """ Structure of self_.records: seq: frame: path of images -> {'Blur': <path>, 'Sharp': <path>} """ def __init__(self, path, frames, future_frames, past_frames, crop_size=(256, 256), data_format='RGB', centralize=True, normalize=True): assert frames - future_frames - past_frames >= 1 self.frames = frames self.num_ff = future_frames self.num_pf = past_frames self.data_format = data_format self.W = None self.H = None self.crop_h, self.crop_w = crop_size self.normalize = normalize self.centralize = centralize self.transform = transforms.Compose([Crop(crop_size), ToTensor()]) self._seq_length = 200 self._samples = self._generate_samples(path, data_format) def _generate_samples(self, dataset_path, data_format): samples = list() records = dict() seq = basename(dataset_path) records[seq] = list() frames = sorted(glob(join(dataset_path, '*.jpg'))) for frame in frames[:self._seq_length]: sample = dict() sample['Blur'] = frame sample['Sharp'] = frame records[seq].append(sample) self.H, self.W, _ = cv2.imread(frame).shape for seq_records in records.values(): temp_length = len(seq_records) - (self.frames - 1) if temp_length <= 0: raise IndexError('Exceed the maximum length of the video sequence') for idx in range(temp_length): samples.append(seq_records[idx:idx + self.frames]) return samples def __getitem__(self, item): top = random.randint(0, self.H - self.crop_h) left = random.randint(0, self.W - self.crop_w) flip_lr = random.randint(0, 1) flip_ud = random.randint(0, 1) sample = {'top': top, 'left': left, 'flip_lr': flip_lr, 'flip_ud': flip_ud} blur_imgs, sharp_imgs = [], [] for sample_dict in self._samples[item]: blur_img, sharp_img = self._load_sample(sample_dict, sample) blur_imgs.append(blur_img) sharp_imgs.append(sharp_img) sharp_imgs = sharp_imgs[self.num_pf:self.frames - self.num_ff] return [torch.cat(item, dim=0) for item in [blur_imgs, sharp_imgs]] def _load_sample(self, sample_dict, sample): if self.data_format == 'RGB': sample['image'] = cv2.imread(sample_dict['Blur']) sample['label'] = cv2.imread(sample_dict['Sharp']) else: raise NotImplementedError # elif self.data_format == 'RAW': # sample['image'] = cv2.imread(sample_dict['Blur'], -1)[..., np.newaxis].astype(np.int32) # sample['label'] = cv2.imread(sample_dict['Sharp'], -1)[..., np.newaxis].astype(np.int32) sample = self.transform(sample) val_range = 2.0 ** 8 - 1 if self.data_format == 'RGB' else 2.0 ** 16 - 1 blur_img = normalize(sample['image'], centralize=self.centralize, normalize=self.normalize, val_range=val_range) sharp_img = normalize(sample['label'], centralize=self.centralize, normalize=self.normalize, val_range=val_range) return blur_img, sharp_img def __len__(self): return len(self._samples) class Dataloader: def __init__(self, para, device_id, ds_type='train'): path = join(para.data_root, para.dataset) frames = para.frames dataset = AnthroDeblurDataset(path, frames, para.future_frames, para.past_frames, para.patch_size, para.data_format, para.centralize, para.normalize) gpus = para.num_gpus bs = para.batch_size ds_len = len(dataset) if para.trainer_mode == 'ddp': sampler = torch.utils.data.distributed.DistributedSampler( dataset, num_replicas=para.num_gpus, rank=device_id ) self.loader = DataLoader( dataset=dataset, batch_size=para.batch_size, shuffle=False, num_workers=para.threads, pin_memory=True, sampler=sampler, drop_last=True ) loader_len = np.ceil(ds_len / gpus) self.loader_len = int(np.ceil(loader_len / bs) * bs) elif para.trainer_mode == 'dp': self.loader = DataLoader( dataset=dataset, batch_size=para.batch_size, shuffle=True, num_workers=para.threads, pin_memory=True, drop_last=True ) self.loader_len = int(np.ceil(ds_len / bs) * bs) def __iter__(self): return iter(self.loader) def __len__(self): return self.loader_len if __name__ == '__main__': from para import Parameter para = Parameter().args para.data_format = 'RGB' para.data_root = '/home/users/aditya/projects/ESTRNN/data/' para.dataset = 'anthro/358129091084785_19032020105115/video_1_baby_chessboard_ruler_4046788426114666387/' dataloader = Dataloader(para, 0) for x, y in dataloader: print(x.shape, y.shape) break print(x.type(), y.type()) print(np.max(x.numpy()), np.min(x.numpy())) print(np.max(y.numpy()), np.min(y.numpy()))

35.208589

124

0.600453

import os import random from os.path import join, basename, dirname import cv2 import numpy as np import torch from glob import glob import ipdb from torch.utils.data import Dataset, DataLoader from torchvision import transforms from utils import normalize, Crop, Flip, ToTensor class AnthroDeblurDataset(Dataset): def __init__(self, path, frames, future_frames, past_frames, crop_size=(256, 256), data_format='RGB', centralize=True, normalize=True): assert frames - future_frames - past_frames >= 1 self.frames = frames self.num_ff = future_frames self.num_pf = past_frames self.data_format = data_format self.W = None self.H = None self.crop_h, self.crop_w = crop_size self.normalize = normalize self.centralize = centralize self.transform = transforms.Compose([Crop(crop_size), ToTensor()]) self._seq_length = 200 self._samples = self._generate_samples(path, data_format) def _generate_samples(self, dataset_path, data_format): samples = list() records = dict() seq = basename(dataset_path) records[seq] = list() frames = sorted(glob(join(dataset_path, '*.jpg'))) for frame in frames[:self._seq_length]: sample = dict() sample['Blur'] = frame sample['Sharp'] = frame records[seq].append(sample) self.H, self.W, _ = cv2.imread(frame).shape for seq_records in records.values(): temp_length = len(seq_records) - (self.frames - 1) if temp_length <= 0: raise IndexError('Exceed the maximum length of the video sequence') for idx in range(temp_length): samples.append(seq_records[idx:idx + self.frames]) return samples def __getitem__(self, item): top = random.randint(0, self.H - self.crop_h) left = random.randint(0, self.W - self.crop_w) flip_lr = random.randint(0, 1) flip_ud = random.randint(0, 1) sample = {'top': top, 'left': left, 'flip_lr': flip_lr, 'flip_ud': flip_ud} blur_imgs, sharp_imgs = [], [] for sample_dict in self._samples[item]: blur_img, sharp_img = self._load_sample(sample_dict, sample) blur_imgs.append(blur_img) sharp_imgs.append(sharp_img) sharp_imgs = sharp_imgs[self.num_pf:self.frames - self.num_ff] return [torch.cat(item, dim=0) for item in [blur_imgs, sharp_imgs]] def _load_sample(self, sample_dict, sample): if self.data_format == 'RGB': sample['image'] = cv2.imread(sample_dict['Blur']) sample['label'] = cv2.imread(sample_dict['Sharp']) else: raise NotImplementedError sample = self.transform(sample) val_range = 2.0 ** 8 - 1 if self.data_format == 'RGB' else 2.0 ** 16 - 1 blur_img = normalize(sample['image'], centralize=self.centralize, normalize=self.normalize, val_range=val_range) sharp_img = normalize(sample['label'], centralize=self.centralize, normalize=self.normalize, val_range=val_range) return blur_img, sharp_img def __len__(self): return len(self._samples) class Dataloader: def __init__(self, para, device_id, ds_type='train'): path = join(para.data_root, para.dataset) frames = para.frames dataset = AnthroDeblurDataset(path, frames, para.future_frames, para.past_frames, para.patch_size, para.data_format, para.centralize, para.normalize) gpus = para.num_gpus bs = para.batch_size ds_len = len(dataset) if para.trainer_mode == 'ddp': sampler = torch.utils.data.distributed.DistributedSampler( dataset, num_replicas=para.num_gpus, rank=device_id ) self.loader = DataLoader( dataset=dataset, batch_size=para.batch_size, shuffle=False, num_workers=para.threads, pin_memory=True, sampler=sampler, drop_last=True ) loader_len = np.ceil(ds_len / gpus) self.loader_len = int(np.ceil(loader_len / bs) * bs) elif para.trainer_mode == 'dp': self.loader = DataLoader( dataset=dataset, batch_size=para.batch_size, shuffle=True, num_workers=para.threads, pin_memory=True, drop_last=True ) self.loader_len = int(np.ceil(ds_len / bs) * bs) def __iter__(self): return iter(self.loader) def __len__(self): return self.loader_len if __name__ == '__main__': from para import Parameter para = Parameter().args para.data_format = 'RGB' para.data_root = '/home/users/aditya/projects/ESTRNN/data/' para.dataset = 'anthro/358129091084785_19032020105115/video_1_baby_chessboard_ruler_4046788426114666387/' dataloader = Dataloader(para, 0) for x, y in dataloader: print(x.shape, y.shape) break print(x.type(), y.type()) print(np.max(x.numpy()), np.min(x.numpy())) print(np.max(y.numpy()), np.min(y.numpy()))

true

f738e8964def8ab2e2e98eee4038f5f125d6f96c

3,594

py

Python

myapp/DeepSegmentor/data/__init__.py

AbelardoDV/crack-detector

c8f1ecf6eb617f1078c9bdf0ef7af89d95ba33ed

[ "MIT" ]

6

2021-02-14T00:46:58.000Z

2022-03-25T10:50:26.000Z

myapp/DeepSegmentor/data/__init__.py

AbelardoDV/crack-detector

c8f1ecf6eb617f1078c9bdf0ef7af89d95ba33ed

[ "MIT" ]

null

myapp/DeepSegmentor/data/__init__.py

AbelardoDV/crack-detector

c8f1ecf6eb617f1078c9bdf0ef7af89d95ba33ed

[ "MIT" ]

6

2021-05-09T12:44:53.000Z

2022-03-17T00:02:10.000Z

"""This package includes all the modules related to data loading and preprocessing To add a custom dataset class called 'dummy', you need to add a file called 'dummy_dataset.py' and define a subclass 'DummyDataset' inherited from BaseDataset. You need to implement four functions: -- <__init__>: initialize the class, first call BaseDataset.__init__(self, opt). -- <__len__>: return the size of dataset. -- <__getitem__>: get a data point from data loader. -- <modify_commandline_options>: (optionally) add dataset-specific options and set default options. Now you can use the dataset class by specifying flag '--dataset_mode dummy'. See our template dataset class 'template_dataset.py' for more details. """ import importlib import torch.utils.data from myapp.DeepSegmentor.data.base_dataset import BaseDataset def find_dataset_using_name(dataset_name): """Import the module "data/[dataset_name]_dataset.py". In the file, the class called DatasetNameDataset() will be instantiated. It has to be a subclass of BaseDataset, and it is case-insensitive. """ dataset_filename = "myapp.DeepSegmentor.data." + dataset_name + "_dataset" datasetlib = importlib.import_module(dataset_filename) dataset = None target_dataset_name = dataset_name.replace('_', '') + 'dataset' for name, cls in datasetlib.__dict__.items(): if name.lower() == target_dataset_name.lower() \ and issubclass(cls, BaseDataset): dataset = cls if dataset is None: raise NotImplementedError("In %s.py, there should be a subclass of BaseDataset with class name that matches %s in lowercase." % (dataset_filename, target_dataset_name)) return dataset def get_option_setter(dataset_name): """Return the static method <modify_commandline_options> of the dataset class.""" dataset_class = find_dataset_using_name(dataset_name) return dataset_class.modify_commandline_options def create_dataset(opt): """Create a dataset given the option. This function wraps the class CustomDatasetDataLoader. This is the main interface between this package and 'train.py'/'test.py' Example: >>> from data import create_dataset >>> dataset = create_dataset(opt) """ data_loader = CustomDatasetDataLoader(opt) dataset = data_loader.load_data() return dataset class CustomDatasetDataLoader(): """Wrapper class of Dataset class that performs multi-threaded data loading""" def __init__(self, opt): """Initialize this class Step 1: create a dataset instance given the name [dataset_mode] Step 2: create a multi-threaded data loader. """ self.opt = opt dataset_class = find_dataset_using_name(opt.dataset_mode) self.dataset = dataset_class(opt) print("dataset [%s] was created" % type(self.dataset).__name__) self.dataloader = torch.utils.data.DataLoader( self.dataset, batch_size=opt.batch_size, shuffle=not opt.serial_batches, num_workers=int(opt.num_threads)) def load_data(self): return self def __len__(self): """Return the number of data in the dataset""" return min(len(self.dataset), self.opt.max_dataset_size) def __iter__(self): """Return a batch of data""" for i, data in enumerate(self.dataloader): if i * self.opt.batch_size >= self.opt.max_dataset_size: break yield data

38.234043

176

0.684474

import importlib import torch.utils.data from myapp.DeepSegmentor.data.base_dataset import BaseDataset def find_dataset_using_name(dataset_name): dataset_filename = "myapp.DeepSegmentor.data." + dataset_name + "_dataset" datasetlib = importlib.import_module(dataset_filename) dataset = None target_dataset_name = dataset_name.replace('_', '') + 'dataset' for name, cls in datasetlib.__dict__.items(): if name.lower() == target_dataset_name.lower() \ and issubclass(cls, BaseDataset): dataset = cls if dataset is None: raise NotImplementedError("In %s.py, there should be a subclass of BaseDataset with class name that matches %s in lowercase." % (dataset_filename, target_dataset_name)) return dataset def get_option_setter(dataset_name): dataset_class = find_dataset_using_name(dataset_name) return dataset_class.modify_commandline_options def create_dataset(opt): data_loader = CustomDatasetDataLoader(opt) dataset = data_loader.load_data() return dataset class CustomDatasetDataLoader(): def __init__(self, opt): self.opt = opt dataset_class = find_dataset_using_name(opt.dataset_mode) self.dataset = dataset_class(opt) print("dataset [%s] was created" % type(self.dataset).__name__) self.dataloader = torch.utils.data.DataLoader( self.dataset, batch_size=opt.batch_size, shuffle=not opt.serial_batches, num_workers=int(opt.num_threads)) def load_data(self): return self def __len__(self): return min(len(self.dataset), self.opt.max_dataset_size) def __iter__(self): for i, data in enumerate(self.dataloader): if i * self.opt.batch_size >= self.opt.max_dataset_size: break yield data

true

f738e8ef5f24e0b2ca574e60daacbd4ce87ebfab

3,472

py

Python

tests/test_reduce_memory.py

nagomiso/komono

3158dc14ebaee724defe63d54c214d40065558d7

[ "MIT" ]

null

tests/test_reduce_memory.py

nagomiso/komono

3158dc14ebaee724defe63d54c214d40065558d7

[ "MIT" ]

null

tests/test_reduce_memory.py

nagomiso/komono

3158dc14ebaee724defe63d54c214d40065558d7

[ "MIT" ]

null

import pandas as pd import pytest from pandas.testing import assert_frame_equal, assert_series_equal import komono.pandas._reduce_memory as rd @pytest.fixture def base_data(): return { "int8": [-128, 127], "int16": [-129, 127], "Int8": [None, 127], "Str": ["foo", "bar"], } @pytest.fixture def base_dtype(): return { "int8": "int64", "int16": "int64", "Int8": "Int64", "Str": "string", } @pytest.fixture def base_dataframe(base_data, base_dtype) -> pd.DataFrame: return pd.DataFrame.from_dict(base_data).astype(base_dtype) @pytest.mark.parametrize( "min_,max_,expected_dtype", [ (-128, 127, "int8"), (-128, 128, "int16"), (-129, 127, "int16"), (-129, 128, "int16"), (-32_768, 32_767, "int16"), (-32_768, 32_768, "int32"), (-32_769, 32_767, "int32"), (-32_769, 32_768, "int32"), (-2_147_483_648, 2_147_483_647, "int32"), (-2_147_483_648, 2_147_483_648, "int64"), (-2_147_483_649, 2_147_483_647, "int64"), (-2_147_483_649, 2_147_483_648, "int64"), ], ) def test_reduce_integer_series_not_nullable(min_, max_, expected_dtype): series = pd.Series([min_, max_], dtype="int64") dtype = str(series.dtype) expected = pd.Series([min_, max_], dtype=expected_dtype) actual = rd._reduce_integer_series(series, dtype=dtype) assert_series_equal(actual, expected) @pytest.mark.parametrize( "min_,mid,max_,expected_dtype", [ (-128, None, 127, "Int8"), (-128, None, 128, "Int16"), (-129, None, 127, "Int16"), (-129, None, 128, "Int16"), (-32_768, None, 32_767, "Int16"), (-32_768, None, 32_768, "Int32"), (-32_769, None, 32_767, "Int32"), (-32_769, None, 32_768, "Int32"), (-2_147_483_648, None, 2_147_483_647, "Int32"), (-2_147_483_648, None, 2_147_483_648, "Int64"), (-2_147_483_649, None, 2_147_483_647, "Int64"), (-2_147_483_649, None, 2_147_483_648, "Int64"), ], ) def test_reduce_integer_series_nullable(min_, mid, max_, expected_dtype): series = pd.Series([min_, mid, max_], dtype="Int64") dtype = str(series.dtype) expected = pd.Series([min_, mid, max_], dtype=expected_dtype) actual = rd._reduce_integer_series(series, dtype=dtype) assert_series_equal(actual, expected) @pytest.mark.parametrize( "min_,max_,expected_dtype", [ (-65500.0, 65500.0, "float16"), (-65500.0, 65600.0, "float32"), (-65600.0, 65500.0, "float32"), (-65600.0, 65600.0, "float32"), (-3.4028e38, 3.4028e38, "float32"), (-3.4028235e38, 3.4028335e38, "float64"), (-3.4028335e38, 3.4028235e38, "float64"), (-3.4028335e38, 3.4028335e38, "float64"), ], ) def test_reduce_float_series(min_, max_, expected_dtype): series = pd.Series([min_, max_], dtype="float64") expected = pd.Series([min_, max_], dtype=expected_dtype) actual = rd._reduce_float_series(series) assert_series_equal(actual, expected) def test_reduce_memory_usage(base_data, base_dataframe): expected = pd.DataFrame.from_dict(data=base_data,).astype( { "int8": "int8", "int16": "int16", "Int8": "Int8", "Str": "string", } ) actual = rd.reduce_memory_usage(base_dataframe, verbose=True) assert_frame_equal(actual, expected)

30.45614

73

0.604839

import pandas as pd import pytest from pandas.testing import assert_frame_equal, assert_series_equal import komono.pandas._reduce_memory as rd @pytest.fixture def base_data(): return { "int8": [-128, 127], "int16": [-129, 127], "Int8": [None, 127], "Str": ["foo", "bar"], } @pytest.fixture def base_dtype(): return { "int8": "int64", "int16": "int64", "Int8": "Int64", "Str": "string", } @pytest.fixture def base_dataframe(base_data, base_dtype) -> pd.DataFrame: return pd.DataFrame.from_dict(base_data).astype(base_dtype) @pytest.mark.parametrize( "min_,max_,expected_dtype", [ (-128, 127, "int8"), (-128, 128, "int16"), (-129, 127, "int16"), (-129, 128, "int16"), (-32_768, 32_767, "int16"), (-32_768, 32_768, "int32"), (-32_769, 32_767, "int32"), (-32_769, 32_768, "int32"), (-2_147_483_648, 2_147_483_647, "int32"), (-2_147_483_648, 2_147_483_648, "int64"), (-2_147_483_649, 2_147_483_647, "int64"), (-2_147_483_649, 2_147_483_648, "int64"), ], ) def test_reduce_integer_series_not_nullable(min_, max_, expected_dtype): series = pd.Series([min_, max_], dtype="int64") dtype = str(series.dtype) expected = pd.Series([min_, max_], dtype=expected_dtype) actual = rd._reduce_integer_series(series, dtype=dtype) assert_series_equal(actual, expected) @pytest.mark.parametrize( "min_,mid,max_,expected_dtype", [ (-128, None, 127, "Int8"), (-128, None, 128, "Int16"), (-129, None, 127, "Int16"), (-129, None, 128, "Int16"), (-32_768, None, 32_767, "Int16"), (-32_768, None, 32_768, "Int32"), (-32_769, None, 32_767, "Int32"), (-32_769, None, 32_768, "Int32"), (-2_147_483_648, None, 2_147_483_647, "Int32"), (-2_147_483_648, None, 2_147_483_648, "Int64"), (-2_147_483_649, None, 2_147_483_647, "Int64"), (-2_147_483_649, None, 2_147_483_648, "Int64"), ], ) def test_reduce_integer_series_nullable(min_, mid, max_, expected_dtype): series = pd.Series([min_, mid, max_], dtype="Int64") dtype = str(series.dtype) expected = pd.Series([min_, mid, max_], dtype=expected_dtype) actual = rd._reduce_integer_series(series, dtype=dtype) assert_series_equal(actual, expected) @pytest.mark.parametrize( "min_,max_,expected_dtype", [ (-65500.0, 65500.0, "float16"), (-65500.0, 65600.0, "float32"), (-65600.0, 65500.0, "float32"), (-65600.0, 65600.0, "float32"), (-3.4028e38, 3.4028e38, "float32"), (-3.4028235e38, 3.4028335e38, "float64"), (-3.4028335e38, 3.4028235e38, "float64"), (-3.4028335e38, 3.4028335e38, "float64"), ], ) def test_reduce_float_series(min_, max_, expected_dtype): series = pd.Series([min_, max_], dtype="float64") expected = pd.Series([min_, max_], dtype=expected_dtype) actual = rd._reduce_float_series(series) assert_series_equal(actual, expected) def test_reduce_memory_usage(base_data, base_dataframe): expected = pd.DataFrame.from_dict(data=base_data,).astype( { "int8": "int8", "int16": "int16", "Int8": "Int8", "Str": "string", } ) actual = rd.reduce_memory_usage(base_dataframe, verbose=True) assert_frame_equal(actual, expected)

true

f738e8f3c2ffddb15e62af6c07e36ec6aa5f61fb

1,782

py

Python

easy_dict/tests/test_04_mods.py

cahoy/NestedDictionary

881f0ea8af36a60fcd1b9d7a84b1aec4cd7072b2

[ "MIT" ]

2

2021-02-13T03:58:59.000Z

2021-09-15T01:02:12.000Z

easy_dict/tests/test_04_mods.py

cahoy/NestedDictionary

881f0ea8af36a60fcd1b9d7a84b1aec4cd7072b2

[ "MIT" ]

1

2017-01-12T00:18:38.000Z

easy_dict/tests/test_04_mods.py

cahoy/NestedDictionary

881f0ea8af36a60fcd1b9d7a84b1aec4cd7072b2

[ "MIT" ]

1

2022-02-16T18:28:52.000Z

from pytest import fixture, raises import easy_dict as nd @fixture() def n(): return nd.NestedDict({'a': {'b': {'c': 123}}, 'd': {'e': 456}, 'f': {'e': 789}}) def test_mod_rooted_chain(n): n['a']['b']['c'] = 234 assert n == {'a': {'b': {'c': 234}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_floating_chain(n): n['b']['c'] = 345 assert n == {'a': {'b': {'c': 345}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_floating_single_key(n): n['c'] = 456 assert n == {'a': {'b': {'c': 456}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_rooted_slash(n): n['a/b/c'] = 567 assert n == {'a': {'b': {'c': 567}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_floating_slash(n): n['b/c'] = 678 assert n == {'a': {'b': {'c': 678}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_floating_list(n): n[['b', 'c']] = 789 assert n == {'a': {'b': {'c': 789}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_multiple_keys_multi_target(n): n['e'] = 234 assert n == {'a': {'b': {'c': 123}}, 'd': {'e': 234}, 'f': {'e': 234}} def test_mod_multiple_keys_single_target(n): n['d/e'] = 234 assert n == {'a': {'b': {'c': 123}}, 'd': {'e': 234}, 'f': {'e': 789}} def test_mod_one_out_of_many_keys(): k = nd.NestedDict({'a': {'b': {'c': {'e': 123}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}}) k['a/b/c/e'] = 234 assert k == {'a': {'b': {'c': {'e': 234}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}} k['b/c/e'] = 345 assert k == {'a': {'b': {'c': {'e': 345}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}} def test_mod_ambiguous_key(): k = nd.NestedDict({'a': {'b': {'c': {'e': 123}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}}) with raises(KeyError): k['c/e'] = 456

27

95

0.442761

from pytest import fixture, raises import easy_dict as nd @fixture() def n(): return nd.NestedDict({'a': {'b': {'c': 123}}, 'd': {'e': 456}, 'f': {'e': 789}}) def test_mod_rooted_chain(n): n['a']['b']['c'] = 234 assert n == {'a': {'b': {'c': 234}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_floating_chain(n): n['b']['c'] = 345 assert n == {'a': {'b': {'c': 345}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_floating_single_key(n): n['c'] = 456 assert n == {'a': {'b': {'c': 456}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_rooted_slash(n): n['a/b/c'] = 567 assert n == {'a': {'b': {'c': 567}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_floating_slash(n): n['b/c'] = 678 assert n == {'a': {'b': {'c': 678}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_with_floating_list(n): n[['b', 'c']] = 789 assert n == {'a': {'b': {'c': 789}}, 'd': {'e': 456}, 'f': {'e': 789}} def test_mod_multiple_keys_multi_target(n): n['e'] = 234 assert n == {'a': {'b': {'c': 123}}, 'd': {'e': 234}, 'f': {'e': 234}} def test_mod_multiple_keys_single_target(n): n['d/e'] = 234 assert n == {'a': {'b': {'c': 123}}, 'd': {'e': 234}, 'f': {'e': 789}} def test_mod_one_out_of_many_keys(): k = nd.NestedDict({'a': {'b': {'c': {'e': 123}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}}) k['a/b/c/e'] = 234 assert k == {'a': {'b': {'c': {'e': 234}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}} k['b/c/e'] = 345 assert k == {'a': {'b': {'c': {'e': 345}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}} def test_mod_ambiguous_key(): k = nd.NestedDict({'a': {'b': {'c': {'e': 123}}}, 'd': {'e': 123}, 'f': {'c': {'e': 123}}}) with raises(KeyError): k['c/e'] = 456

true

f738e8fe93b26fc4b1d67c654e45efdee0d4fc59

1,114

py

Python

app/service/auth/group_user.py

ryan4yin/flypy-backend

7fcc2971ac27d3b44e352dfed73acd12e1913d65

[ "MIT" ]

6

2019-03-14T02:39:17.000Z

2021-10-31T11:43:58.000Z

app/service/auth/group_user.py

ryan4yin/flypy-backend

7fcc2971ac27d3b44e352dfed73acd12e1913d65

[ "MIT" ]

null

app/service/auth/group_user.py

ryan4yin/flypy-backend

7fcc2971ac27d3b44e352dfed73acd12e1913d65

[ "MIT" ]

2

2020-02-04T07:44:37.000Z

2021-04-02T23:02:20.000Z

""" 群成员权限验证 """ from typing import Iterable, List from app import db from app.models import Group, GroupUser, MainUser, GroupUserRelation from app.utils.db import get_group def is_(role: List[str], main_user: MainUser, group_id, platform): """ 该用户是否是指定群组的管理员需要用户先绑定群组！ :param role: 群角色，可选 'admin' 或 'owner'，可多选 :param main_user: 用户对象 :param group_id: 群组 id :param platform: 群组所属平台 :return: boolean """ group = get_group(group_id, platform) # 查询到 main_user 绑定的属于该群的账号 group_users_id: Iterable[GroupUser.id] = db.session.query(GroupUser.id) \ .filter_by(platform=platform, main_user_id=main_user.id) group_user_relationship: Iterable[GroupUserRelation] = db.session.query(GroupUserRelation) \ .filter_by(platform=platform, group_db_id=group.id) \ .filter(GroupUserRelation.user_db_id.in_(group_users_id)) # 挨个检查各账号是否是 admin，是就返回 True for r in group_user_relationship: if 'admin' in role and r.is_admin: return True elif 'owner' in role and r.is_owner: return True return False

26.52381

96

0.691203

from typing import Iterable, List from app import db from app.models import Group, GroupUser, MainUser, GroupUserRelation from app.utils.db import get_group def is_(role: List[str], main_user: MainUser, group_id, platform): group = get_group(group_id, platform) group_users_id: Iterable[GroupUser.id] = db.session.query(GroupUser.id) \ .filter_by(platform=platform, main_user_id=main_user.id) group_user_relationship: Iterable[GroupUserRelation] = db.session.query(GroupUserRelation) \ .filter_by(platform=platform, group_db_id=group.id) \ .filter(GroupUserRelation.user_db_id.in_(group_users_id)) for r in group_user_relationship: if 'admin' in role and r.is_admin: return True elif 'owner' in role and r.is_owner: return True return False

true

f738e9ae1be3a751cceefa326d7426a350d1e65f

7,573

py

Python

Pipelines/ADNI_AV1451/ADNI_V1_AV1451.py

sulantha2006/Processing_Pipeline

fb135560b7db79d811177cf02ee96e6081ce3364

[ "Apache-2.0" ]

1

2015-08-11T17:39:26.000Z

Pipelines/ADNI_AV1451/ADNI_V1_AV1451.py

sulantha2006/Processing_Pipeline

fb135560b7db79d811177cf02ee96e6081ce3364

[ "Apache-2.0" ]

null

Pipelines/ADNI_AV1451/ADNI_V1_AV1451.py

sulantha2006/Processing_Pipeline

fb135560b7db79d811177cf02ee96e6081ce3364

[ "Apache-2.0" ]

2

2015-11-13T18:05:48.000Z

2020-01-17T17:28:08.000Z

__author__ = 'sulantha' from Utils.DbUtils import DbUtils import Config.PipelineConfig as pc from Pipelines.ADNI_T1.ADNI_T1_Helper import ADNI_T1_Helper from Utils.PipelineLogger import PipelineLogger import distutils.dir_util import distutils.file_util import shutil import subprocess from Manager.QSubJob import QSubJob from Manager.QSubJobHanlder import QSubJobHandler import socket,os import ast from Pipelines.Helpers.PETHelper import PETHelper class ProcessingItemObj: def __init__(self, processingItem): self.processing_rid = processingItem[0] self.study = processingItem[1] self.subject_rid = processingItem[2] self.modality = processingItem[3] self.scan_date = processingItem[4].strftime("%Y-%m-%d") self.scan_time = str(processingItem[5]) self.s_identifier = processingItem[6] self.i_identifier = processingItem[7] self.root_folder = processingItem[8] self.converted_folder = processingItem[9] self.version = processingItem[10] self.table_id = processingItem[17] self.parameters = processingItem[19] self.manual_xfm = processingItem[20] self.qc = processingItem[21] class ADNI_V1_AV1451: def __init__(self): self.DBClient = DbUtils() self.MatchDBClient = DbUtils(database=pc.ADNI_dataMatchDBName) self.PETHelper = PETHelper() def process(self, processingItem): processingItemObj = ProcessingItemObj(processingItem) matching_t1 = ADNI_T1_Helper().getMatchingT1(processingItemObj) if not matching_t1: PipelineLogger.log('root', 'error', 'PET cannot be processed no matching T1 found. - {0} - {1} - {2}.'.format(processingItemObj.subject_rid, processingItemObj.modality, processingItemObj.scan_date)) return 0 processed = ADNI_T1_Helper().checkProcessed(matching_t1) if not processed: PipelineLogger.log('root', 'error', 'PET cannot be processed due to matching T1 not being processed - {0}'.format(matching_t1)) return 0 else: PipelineLogger.log('root', 'INFO', '+++++++++ PET ready to be processed. Will check for xfm. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) if processingItemObj.manual_xfm == '': manualXFM = self.PETHelper.getManualXFM(processingItemObj, matching_t1) processingItemObj.manual_xfm = manualXFM elif processingItemObj.manual_xfm == 'Req_man_reg': coregDone = self.PETHelper.checkIfAlreadyDone(processingItemObj, matching_t1) if coregDone: manualXFM = coregDone setPPTableSQL = "UPDATE {0}_{1}_Pipeline SET MANUAL_XFM = '{2}' WHERE RECORD_ID = {3}".format(processingItemObj.study, processingItemObj.modality, manualXFM, processingItemObj.table_id) self.DBClient.executeNoResult(setPPTableSQL) else: self.PETHelper.requestCoreg(processingItemObj, matching_t1) PipelineLogger.log('root', 'INFO', 'Manual XFM was not found. Request to create one may have added. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) return 0 else: manualXFM = processingItemObj.manual_xfm if manualXFM: self.processPET(processingItemObj, processed) else: PipelineLogger.log('root', 'INFO', 'Manual XFM was not found. Request to create one may have added. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) return 0 def getScanType(self, processingItemObj): r = self.DBClient.executeAllResults("SELECT SCAN_TYPE FROM Conversion WHERE STUDY = '{0}' AND RID = '{1}' " "AND SCAN_DATE = '{2}' AND S_IDENTIFIER = '{3}' " "AND I_IDENTIFIER = '{4}'".format(processingItemObj.study, processingItemObj.subject_rid, processingItemObj.scan_date, processingItemObj.s_identifier, processingItemObj.i_identifier)) return r[0][0] def processPET(self, processingItemObj, matchT1Path): petFileName = '{0}/{1}_{2}{3}{4}{5}_{6}.mnc'.format(processingItemObj.converted_folder, processingItemObj.study, processingItemObj.subject_rid, processingItemObj.scan_date.replace('-', ''), processingItemObj.s_identifier, processingItemObj.i_identifier, self.getScanType(processingItemObj)) processedFolder = '{0}/processed'.format(processingItemObj.root_folder) logDir = '{0}/logs'.format(processingItemObj.root_folder) PipelineLogger.log('manager', 'info', 'PET processing starting for {0}'.format(petFileName)) try: distutils.dir_util.mkpath(logDir) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in creating log folder \n {0}'.format(e)) return 0 id = '{0}{1}{2}{3}'.format(processingItemObj.subject_rid, processingItemObj.scan_date.replace('-', ''), processingItemObj.s_identifier, processingItemObj.i_identifier) paramStrd = ast.literal_eval(processingItemObj.parameters) paramStrt = ' '.join(['[\"{0}\"]=\"{1}\"'.format(k, v) for k,v in paramStrd.items()]) paramStr = '({0})'.format(paramStrt) petCMD = "source /opt/minc-1.9.15/minc-toolkit-config.sh; Pipelines/ADNI_AV1451/ADNI_V1_AV1451_Process {0} {1} {2} {3} {4} {5} '{6}' {7} {8}".format(id, petFileName, processedFolder, matchT1Path, processingItemObj.manual_xfm, logDir, paramStr,socket.gethostname(), 50500) try: processedFolder_del = '{0}/processed_del'.format(processingItemObj.root_folder) os.rename(processedFolder, processedFolder_del) shutil.rmtree(processedFolder_del) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in deleting old processing folder. \n {0}'.format(e)) try: distutils.dir_util.mkpath(processedFolder) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in creating processing folder. \n {0}'.format(e)) return 0 ### This section is new for ADNI Pre processing - Per scanner type blurring. Only required if ### the images are aquired from different scanners and need to get to same PSF. blur_x, blur_y, blur_z = self.PETHelper.getBlurringParams(processingItemObj) ### End pre processing. PipelineLogger.log('manager', 'debug', 'Command : {0}'.format(petCMD)) p = subprocess.Popen(petCMD, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, executable='/bin/bash') out, err = p.communicate() PipelineLogger.log('manager', 'debug', 'Process Log Output : \n{0}'.format(out)) PipelineLogger.log('manager', 'debug', 'Process Log Err : \n{0}'.format(err)) QSubJobHandler.submittedJobs[id] = QSubJob(id, '02:00:00', processingItemObj, 'av1451') return 1

57.80916

279

0.628549

__author__ = 'sulantha' from Utils.DbUtils import DbUtils import Config.PipelineConfig as pc from Pipelines.ADNI_T1.ADNI_T1_Helper import ADNI_T1_Helper from Utils.PipelineLogger import PipelineLogger import distutils.dir_util import distutils.file_util import shutil import subprocess from Manager.QSubJob import QSubJob from Manager.QSubJobHanlder import QSubJobHandler import socket,os import ast from Pipelines.Helpers.PETHelper import PETHelper class ProcessingItemObj: def __init__(self, processingItem): self.processing_rid = processingItem[0] self.study = processingItem[1] self.subject_rid = processingItem[2] self.modality = processingItem[3] self.scan_date = processingItem[4].strftime("%Y-%m-%d") self.scan_time = str(processingItem[5]) self.s_identifier = processingItem[6] self.i_identifier = processingItem[7] self.root_folder = processingItem[8] self.converted_folder = processingItem[9] self.version = processingItem[10] self.table_id = processingItem[17] self.parameters = processingItem[19] self.manual_xfm = processingItem[20] self.qc = processingItem[21] class ADNI_V1_AV1451: def __init__(self): self.DBClient = DbUtils() self.MatchDBClient = DbUtils(database=pc.ADNI_dataMatchDBName) self.PETHelper = PETHelper() def process(self, processingItem): processingItemObj = ProcessingItemObj(processingItem) matching_t1 = ADNI_T1_Helper().getMatchingT1(processingItemObj) if not matching_t1: PipelineLogger.log('root', 'error', 'PET cannot be processed no matching T1 found. - {0} - {1} - {2}.'.format(processingItemObj.subject_rid, processingItemObj.modality, processingItemObj.scan_date)) return 0 processed = ADNI_T1_Helper().checkProcessed(matching_t1) if not processed: PipelineLogger.log('root', 'error', 'PET cannot be processed due to matching T1 not being processed - {0}'.format(matching_t1)) return 0 else: PipelineLogger.log('root', 'INFO', '+++++++++ PET ready to be processed. Will check for xfm. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) if processingItemObj.manual_xfm == '': manualXFM = self.PETHelper.getManualXFM(processingItemObj, matching_t1) processingItemObj.manual_xfm = manualXFM elif processingItemObj.manual_xfm == 'Req_man_reg': coregDone = self.PETHelper.checkIfAlreadyDone(processingItemObj, matching_t1) if coregDone: manualXFM = coregDone setPPTableSQL = "UPDATE {0}_{1}_Pipeline SET MANUAL_XFM = '{2}' WHERE RECORD_ID = {3}".format(processingItemObj.study, processingItemObj.modality, manualXFM, processingItemObj.table_id) self.DBClient.executeNoResult(setPPTableSQL) else: self.PETHelper.requestCoreg(processingItemObj, matching_t1) PipelineLogger.log('root', 'INFO', 'Manual XFM was not found. Request to create one may have added. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) return 0 else: manualXFM = processingItemObj.manual_xfm if manualXFM: self.processPET(processingItemObj, processed) else: PipelineLogger.log('root', 'INFO', 'Manual XFM was not found. Request to create one may have added. - {0} - {1}'.format(processingItemObj.subject_rid, processingItemObj.scan_date)) return 0 def getScanType(self, processingItemObj): r = self.DBClient.executeAllResults("SELECT SCAN_TYPE FROM Conversion WHERE STUDY = '{0}' AND RID = '{1}' " "AND SCAN_DATE = '{2}' AND S_IDENTIFIER = '{3}' " "AND I_IDENTIFIER = '{4}'".format(processingItemObj.study, processingItemObj.subject_rid, processingItemObj.scan_date, processingItemObj.s_identifier, processingItemObj.i_identifier)) return r[0][0] def processPET(self, processingItemObj, matchT1Path): petFileName = '{0}/{1}_{2}{3}{4}{5}_{6}.mnc'.format(processingItemObj.converted_folder, processingItemObj.study, processingItemObj.subject_rid, processingItemObj.scan_date.replace('-', ''), processingItemObj.s_identifier, processingItemObj.i_identifier, self.getScanType(processingItemObj)) processedFolder = '{0}/processed'.format(processingItemObj.root_folder) logDir = '{0}/logs'.format(processingItemObj.root_folder) PipelineLogger.log('manager', 'info', 'PET processing starting for {0}'.format(petFileName)) try: distutils.dir_util.mkpath(logDir) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in creating log folder \n {0}'.format(e)) return 0 id = '{0}{1}{2}{3}'.format(processingItemObj.subject_rid, processingItemObj.scan_date.replace('-', ''), processingItemObj.s_identifier, processingItemObj.i_identifier) paramStrd = ast.literal_eval(processingItemObj.parameters) paramStrt = ' '.join(['[\"{0}\"]=\"{1}\"'.format(k, v) for k,v in paramStrd.items()]) paramStr = '({0})'.format(paramStrt) petCMD = "source /opt/minc-1.9.15/minc-toolkit-config.sh; Pipelines/ADNI_AV1451/ADNI_V1_AV1451_Process {0} {1} {2} {3} {4} {5} '{6}' {7} {8}".format(id, petFileName, processedFolder, matchT1Path, processingItemObj.manual_xfm, logDir, paramStr,socket.gethostname(), 50500) try: processedFolder_del = '{0}/processed_del'.format(processingItemObj.root_folder) os.rename(processedFolder, processedFolder_del) shutil.rmtree(processedFolder_del) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in deleting old processing folder. \n {0}'.format(e)) try: distutils.dir_util.mkpath(processedFolder) except Exception as e: PipelineLogger.log('manager', 'error', 'Error in creating processing folder. \n {0}'.format(e)) return 0 bug', 'Process Log Output : \n{0}'.format(out)) PipelineLogger.log('manager', 'debug', 'Process Log Err : \n{0}'.format(err)) QSubJobHandler.submittedJobs[id] = QSubJob(id, '02:00:00', processingItemObj, 'av1451') return 1

true

f738ea5fe3f4affcffd0189bbf82496b2931a05e

1,893

py

Python

source/force.py

swyang50066/sun-jupiter-earth-orbit

c50012ff1a187485b717d86a24c25cfe6edd78a1

[ "MIT" ]

null

source/force.py

swyang50066/sun-jupiter-earth-orbit

c50012ff1a187485b717d86a24c25cfe6edd78a1

[ "MIT" ]

null

source/force.py

swyang50066/sun-jupiter-earth-orbit

c50012ff1a187485b717d86a24c25cfe6edd78a1

[ "MIT" ]

null

import numpy as np from allvar import * def _distance(r1, r2): """Return Euclidean _distance between positions""" return np.sqrt(np.sum((r1 - r2)**2.)) def drdt(r, v): """Return position derivative :param r: shape: (x_earth, y_earth, x_jupiter, y_jupiter)) :param v: shape: (vx_earth, vy_earth, vx_jupiter, vy_jupiter) :return: velocities """ return v def dvdt(r, v, eps=1.e-20): """Return position derivative Central star have fixed position at (0, 0) :param r: shape: (x_earth, y_earth, x_jupiter, y_jupiter) :param v: shape: (vx_earth, vy_earth, vx_jupiter, vy_jupiter) :return: accelerations """ # Geometric measurements r_se, r_sj, r_ej = r[:2], r[2:], r[2:] - r[:2] dist_se = _distance((0, 0), r_se) dist_sj = _distance((0, 0), r_sj) dist_ej = _distance(r_se, r_sj) theta_se = np.math.atan(np.abs(r_se[1])/(np.abs(r_se[0]) + eps)) theta_sj = np.math.atan(np.abs(r_sj[1])/(np.abs(r_sj[0]) + eps)) theta_ej = np.math.atan(np.abs(r_ej[1])/(np.abs(r_ej[0]) + eps)) # Unit force functionals const_se = GG*(EARTH_MASS/SOLAR_MASS) f_se = -np.sign(r_se)*const_se*np.array( [ np.cos(theta_se)/(dist_se + eps)**2., np.sin(theta_se)/(dist_se + eps)**2. ] ) const_sj = GG*(JUPITER_MASS/SOLAR_MASS) f_sj = -np.sign(r_sj)*const_sj*np.array( [ np.cos(theta_sj)/(dist_sj + eps)**2., np.sin(theta_sj)/(dist_sj + eps)**2. ] ) const_ej = GG*(EARTH_MASS*JUPITER_MASS/SOLAR_MASS**2.) f_ej = -np.sign(r_ej)*const_ej*np.array( [ np.cos(theta_ej)/(dist_ej + eps)**2., np.sin(theta_ej)/(dist_ej + eps)**2. ] ) return np.hstack([ (f_se - f_ej)/(EARTH_MASS/SOLAR_MASS), (f_sj + f_ej)/(JUPITER_MASS/SOLAR_MASS), ])

28.253731

68

0.578975

import numpy as np from allvar import * def _distance(r1, r2): return np.sqrt(np.sum((r1 - r2)**2.)) def drdt(r, v): return v def dvdt(r, v, eps=1.e-20): r_se, r_sj, r_ej = r[:2], r[2:], r[2:] - r[:2] dist_se = _distance((0, 0), r_se) dist_sj = _distance((0, 0), r_sj) dist_ej = _distance(r_se, r_sj) theta_se = np.math.atan(np.abs(r_se[1])/(np.abs(r_se[0]) + eps)) theta_sj = np.math.atan(np.abs(r_sj[1])/(np.abs(r_sj[0]) + eps)) theta_ej = np.math.atan(np.abs(r_ej[1])/(np.abs(r_ej[0]) + eps)) const_se = GG*(EARTH_MASS/SOLAR_MASS) f_se = -np.sign(r_se)*const_se*np.array( [ np.cos(theta_se)/(dist_se + eps)**2., np.sin(theta_se)/(dist_se + eps)**2. ] ) const_sj = GG*(JUPITER_MASS/SOLAR_MASS) f_sj = -np.sign(r_sj)*const_sj*np.array( [ np.cos(theta_sj)/(dist_sj + eps)**2., np.sin(theta_sj)/(dist_sj + eps)**2. ] ) const_ej = GG*(EARTH_MASS*JUPITER_MASS/SOLAR_MASS**2.) f_ej = -np.sign(r_ej)*const_ej*np.array( [ np.cos(theta_ej)/(dist_ej + eps)**2., np.sin(theta_ej)/(dist_ej + eps)**2. ] ) return np.hstack([ (f_se - f_ej)/(EARTH_MASS/SOLAR_MASS), (f_sj + f_ej)/(JUPITER_MASS/SOLAR_MASS), ])

true

f738eae3572e7241435ab4c22191359b1e9a5923

4,073

py

Python

tests/test_end2end.py

haojiepan1/CrossWOZ

6d7b4c4cfb73a528b76074764687906abecc90b6

[ "Apache-2.0" ]

1

2020-03-09T02:09:10.000Z

tests/test_end2end.py

haojiepan1/CrossWOZ

6d7b4c4cfb73a528b76074764687906abecc90b6

[ "Apache-2.0" ]

null

tests/test_end2end.py

haojiepan1/CrossWOZ

6d7b4c4cfb73a528b76074764687906abecc90b6

[ "Apache-2.0" ]

null

from convlab2.nlu.svm.multiwoz import SVMNLU from convlab2.nlu.jointBERT.multiwoz import BERTNLU from convlab2.nlu.milu.multiwoz import MILU from convlab2.dst.rule.multiwoz import RuleDST from convlab2.policy.rule.multiwoz import RulePolicy from convlab2.nlg.template.multiwoz import TemplateNLG from convlab2.dialog_agent import PipelineAgent, BiSession from convlab2.evaluator.multiwoz_eval import MultiWozEvaluator from pprint import pprint import random import numpy as np import torch sys_nlu = BERTNLU(mode='all', config_file='multiwoz_all.json', model_file='https://tatk-data.s3-ap-northeast-1.amazonaws.com/bert_multiwoz_all.zip') # sys_nlu = SVMNLU(mode='sys') # simple rule DST sys_dst = RuleDST() # rule policy sys_policy = RulePolicy(character='sys') # template NLG sys_nlg = TemplateNLG(is_user=False) # assemble sys_agent = PipelineAgent(sys_nlu, sys_dst, sys_policy, sys_nlg, 'sys') # user_nlu = sys_nlu # user_nlu = SVMNLU(mode='all') user_nlu = MILU(model_file="https://convlab.blob.core.windows.net/models/milu.tar.gz") # not use dst user_dst = None # rule policy user_policy = RulePolicy(character='usr') # template NLG user_nlg = TemplateNLG(is_user=True) # assemble user_agent = PipelineAgent(user_nlu, None, user_policy, user_nlg, 'user') evaluator = MultiWozEvaluator() sess = BiSession(sys_agent=sys_agent, user_agent=user_agent, kb_query=None, evaluator=evaluator) random.seed(20200131) np.random.seed(20190827) torch.manual_seed(20200131) sys_response = '' sess.init_session() print('init goal:') pprint(sess.evaluator.goal) print('-'*50) for i in range(40): sys_response, user_response, session_over, reward = sess.next_turn(sys_response) print('user:', user_response) print('sys:', sys_response) print() if session_over is True: print('task complete:', user_policy.policy.goal.task_complete()) print('task success:', sess.evaluator.task_success()) print('book rate:', sess.evaluator.book_rate()) print('inform precision/recall/f1:', sess.evaluator.inform_F1()) print('-'*50) print('final goal:') pprint(sess.evaluator.goal) print('='*100) break total_dialog = 10 random.seed(20200131) goal_seeds = [random.randint(1,100000) for _ in range(total_dialog)] precision = 0 recall = 0 f1 = 0 suc_num = 0 complete_num = 0 for j in range(total_dialog): sys_response = '' random.seed(goal_seeds[0]) np.random.seed(goal_seeds[0]) torch.manual_seed(goal_seeds[0]) goal_seeds.pop(0) sess.init_session() # print('init goal:') # pprint(sess.evaluator.goal) # print('-'*50) for i in range(40): sys_response, user_response, session_over, reward = sess.next_turn( sys_response) # print('user:', user_response) # print('sys:', sys_response) if session_over is True: if sess.evaluator.task_success() == 1: suc_num = suc_num+1 if user_policy.policy.goal.task_complete(): complete_num += 1 print('task complete:', user_policy.policy.goal.task_complete()) print('task success:', sess.evaluator.task_success()) print('book rate:', sess.evaluator.book_rate()) print('inform precision/recall/f1:', sess.evaluator.inform_F1()) stats = sess.evaluator.inform_F1() if(stats[0] != None): precision = precision+stats[0] if(stats[1] != None): recall = recall+stats[1] if(stats[2] != None): f1 = f1+stats[2] else: suc_num = suc_num-1 # print('-'*50) # print('final goal:') # pprint(sess.evaluator.goal) # print('='*100) break print("complete number of dialogs/tot:", complete_num/total_dialog) print("success number of dialogs/tot:", suc_num/total_dialog) print("average precision:", precision/total_dialog) print("average recall:", recall/total_dialog) print("average f1:", f1/total_dialog)

35.417391

103

0.674687

from convlab2.nlu.svm.multiwoz import SVMNLU from convlab2.nlu.jointBERT.multiwoz import BERTNLU from convlab2.nlu.milu.multiwoz import MILU from convlab2.dst.rule.multiwoz import RuleDST from convlab2.policy.rule.multiwoz import RulePolicy from convlab2.nlg.template.multiwoz import TemplateNLG from convlab2.dialog_agent import PipelineAgent, BiSession from convlab2.evaluator.multiwoz_eval import MultiWozEvaluator from pprint import pprint import random import numpy as np import torch sys_nlu = BERTNLU(mode='all', config_file='multiwoz_all.json', model_file='https://tatk-data.s3-ap-northeast-1.amazonaws.com/bert_multiwoz_all.zip') sys_dst = RuleDST() sys_policy = RulePolicy(character='sys') sys_nlg = TemplateNLG(is_user=False) sys_agent = PipelineAgent(sys_nlu, sys_dst, sys_policy, sys_nlg, 'sys') user_nlu = MILU(model_file="https://convlab.blob.core.windows.net/models/milu.tar.gz") user_dst = None user_policy = RulePolicy(character='usr') user_nlg = TemplateNLG(is_user=True) user_agent = PipelineAgent(user_nlu, None, user_policy, user_nlg, 'user') evaluator = MultiWozEvaluator() sess = BiSession(sys_agent=sys_agent, user_agent=user_agent, kb_query=None, evaluator=evaluator) random.seed(20200131) np.random.seed(20190827) torch.manual_seed(20200131) sys_response = '' sess.init_session() print('init goal:') pprint(sess.evaluator.goal) print('-'*50) for i in range(40): sys_response, user_response, session_over, reward = sess.next_turn(sys_response) print('user:', user_response) print('sys:', sys_response) print() if session_over is True: print('task complete:', user_policy.policy.goal.task_complete()) print('task success:', sess.evaluator.task_success()) print('book rate:', sess.evaluator.book_rate()) print('inform precision/recall/f1:', sess.evaluator.inform_F1()) print('-'*50) print('final goal:') pprint(sess.evaluator.goal) print('='*100) break total_dialog = 10 random.seed(20200131) goal_seeds = [random.randint(1,100000) for _ in range(total_dialog)] precision = 0 recall = 0 f1 = 0 suc_num = 0 complete_num = 0 for j in range(total_dialog): sys_response = '' random.seed(goal_seeds[0]) np.random.seed(goal_seeds[0]) torch.manual_seed(goal_seeds[0]) goal_seeds.pop(0) sess.init_session() for i in range(40): sys_response, user_response, session_over, reward = sess.next_turn( sys_response) if session_over is True: if sess.evaluator.task_success() == 1: suc_num = suc_num+1 if user_policy.policy.goal.task_complete(): complete_num += 1 print('task complete:', user_policy.policy.goal.task_complete()) print('task success:', sess.evaluator.task_success()) print('book rate:', sess.evaluator.book_rate()) print('inform precision/recall/f1:', sess.evaluator.inform_F1()) stats = sess.evaluator.inform_F1() if(stats[0] != None): precision = precision+stats[0] if(stats[1] != None): recall = recall+stats[1] if(stats[2] != None): f1 = f1+stats[2] else: suc_num = suc_num-1 break print("complete number of dialogs/tot:", complete_num/total_dialog) print("success number of dialogs/tot:", suc_num/total_dialog) print("average precision:", precision/total_dialog) print("average recall:", recall/total_dialog) print("average f1:", f1/total_dialog)

true

f738eb6ca204ada7a97361995987942b2201b0e0

5,821

py

Python

legacy/brats/original_unet_train.py

zjdcts/CSAM-U-Net

91fae3c6b4fc7247ba9ee2dc6e64b51da569bf2e

[ "MIT" ]

1

2021-07-28T03:36:34.000Z

legacy/brats/original_unet_train.py

zjdcts/CSAM-U-Net

91fae3c6b4fc7247ba9ee2dc6e64b51da569bf2e

[ "MIT" ]

null

legacy/brats/original_unet_train.py

zjdcts/CSAM-U-Net

91fae3c6b4fc7247ba9ee2dc6e64b51da569bf2e

[ "MIT" ]

1

2021-07-28T03:36:37.000Z

import os import glob from legacy.unet3dlegacy.data import write_data_to_file, open_data_file from legacy.unet3dlegacy.generator import get_training_and_validation_generators from legacy.unet3dlegacy.model import unet_model_3d from legacy.unet3dlegacy.training import load_old_model, train_model config = dict() config["pool_size"] = (2, 2, 2) # pool size for the max pooling operations config["image_shape"] = (144, 144, 144) # This determines what shape the images will be cropped/resampled to. config["patch_shape"] = (64, 64, 64) # switch to None to train on the whole image config["labels"] = (1, 2, 4) # the label numbers on the input image config["n_labels"] = len(config["labels"]) config["all_modalities"] = ["t1", "t1ce", "flair", "t2"] config["training_modalities"] = config["all_modalities"] # change this if you want to only use some of the modalities config["nb_channels"] = len(config["training_modalities"]) if "patch_shape" in config and config["patch_shape"] is not None: config["input_shape"] = tuple([config["nb_channels"]] + list(config["patch_shape"])) else: config["input_shape"] = tuple([config["nb_channels"]] + list(config["image_shape"])) config["truth_channel"] = config["nb_channels"] config["deconvolution"] = True # if False, will use upsampling instead of deconvolution config["batch_size"] = 6 config["validation_batch_size"] = 12 config["n_epochs"] = 500 # cutoff the training after this many epochs config["patience"] = 10 # learning rate will be reduced after this many epochs if the validation loss is not improving config["early_stop"] = 50 # training will be stopped after this many epochs without the validation loss improving config["initial_learning_rate"] = 0.00001 config["learning_rate_drop"] = 0.5 # factor by which the learning rate will be reduced config["validation_split"] = 0.8 # portion of the data that will be used for training config["flip"] = False # augments the data by randomly flipping an axis during config["permute"] = False # data shape must be a cube. Augments the data by permuting in various directions config["distort"] = None # switch to None if you want no distortion config["augment"] = config["flip"] or config["distort"] config["validation_patch_overlap"] = 0 # if > 0, during training, validation patches will be overlapping config["training_patch_start_offset"] = (16, 16, 16) # randomly offset the first patch index by up to this offset config["skip_blank"] = True # if True, then patches without any target will be skipped config["data_file"] = os.path.abspath("brats_data.h5") config["model_file"] = os.path.abspath("tumor_segmentation_model.h5") config["training_file"] = os.path.abspath("training_ids.pkl") config["validation_file"] = os.path.abspath("validation_ids.pkl") config["overwrite"] = False # If True, will previous files. If False, will use previously written files. def fetch_training_data_files(): training_data_files = list() for subject_dir in glob.glob(os.path.join(os.path.dirname(__file__), "data", "preprocessed", "*", "*")): subject_files = list() for modality in config["training_modalities"] + ["truth"]: subject_files.append(os.path.join(subject_dir, modality + ".nii.gz")) training_data_files.append(tuple(subject_files)) return training_data_files def main(overwrite=False): # convert input images into an hdf5 file if overwrite or not os.path.exists(config["data_file"]): training_files = fetch_training_data_files() write_data_to_file(training_files, config["data_file"], image_shape=config["image_shape"]) data_file_opened = open_data_file(config["data_file"]) if not overwrite and os.path.exists(config["model_file"]): model = load_old_model(config["model_file"]) else: # instantiate new model model = unet_model_3d(input_shape=config["input_shape"], pool_size=config["pool_size"], n_labels=config["n_labels"], initial_learning_rate=config["initial_learning_rate"], deconvolution=config["deconvolution"]) # get training and testing generators train_generator, validation_generator, n_train_steps, n_validation_steps = get_training_and_validation_generators( data_file_opened, batch_size=config["batch_size"], data_split=config["validation_split"], overwrite=overwrite, validation_keys_file=config["validation_file"], training_keys_file=config["training_file"], n_labels=config["n_labels"], labels=config["labels"], patch_shape=config["patch_shape"], validation_batch_size=config["validation_batch_size"], validation_patch_overlap=config["validation_patch_overlap"], training_patch_start_offset=config["training_patch_start_offset"], permute=config["permute"], augment=config["augment"], skip_blank=config["skip_blank"], augment_flip=config["flip"], augment_distortion_factor=config["distort"]) # run training train_model(model=model, model_file=config["model_file"], training_generator=train_generator, validation_generator=validation_generator, steps_per_epoch=n_train_steps, validation_steps=n_validation_steps, initial_learning_rate=config["initial_learning_rate"], learning_rate_drop=config["learning_rate_drop"], learning_rate_patience=config["patience"], early_stopping_patience=config["early_stop"], n_epochs=config["n_epochs"]) data_file_opened.close() if __name__ == "__main__": main(overwrite=config["overwrite"])

51.061404

119

0.706923

import os import glob from legacy.unet3dlegacy.data import write_data_to_file, open_data_file from legacy.unet3dlegacy.generator import get_training_and_validation_generators from legacy.unet3dlegacy.model import unet_model_3d from legacy.unet3dlegacy.training import load_old_model, train_model config = dict() config["pool_size"] = (2, 2, 2) config["image_shape"] = (144, 144, 144) config["patch_shape"] = (64, 64, 64) config["labels"] = (1, 2, 4) config["n_labels"] = len(config["labels"]) config["all_modalities"] = ["t1", "t1ce", "flair", "t2"] config["training_modalities"] = config["all_modalities"] config["nb_channels"] = len(config["training_modalities"]) if "patch_shape" in config and config["patch_shape"] is not None: config["input_shape"] = tuple([config["nb_channels"]] + list(config["patch_shape"])) else: config["input_shape"] = tuple([config["nb_channels"]] + list(config["image_shape"])) config["truth_channel"] = config["nb_channels"] config["deconvolution"] = True config["batch_size"] = 6 config["validation_batch_size"] = 12 config["n_epochs"] = 500 config["patience"] = 10 config["early_stop"] = 50 config["initial_learning_rate"] = 0.00001 config["learning_rate_drop"] = 0.5 config["validation_split"] = 0.8 config["flip"] = False config["permute"] = False config["distort"] = None config["augment"] = config["flip"] or config["distort"] config["validation_patch_overlap"] = 0 config["training_patch_start_offset"] = (16, 16, 16) config["skip_blank"] = True config["data_file"] = os.path.abspath("brats_data.h5") config["model_file"] = os.path.abspath("tumor_segmentation_model.h5") config["training_file"] = os.path.abspath("training_ids.pkl") config["validation_file"] = os.path.abspath("validation_ids.pkl") config["overwrite"] = False def fetch_training_data_files(): training_data_files = list() for subject_dir in glob.glob(os.path.join(os.path.dirname(__file__), "data", "preprocessed", "*", "*")): subject_files = list() for modality in config["training_modalities"] + ["truth"]: subject_files.append(os.path.join(subject_dir, modality + ".nii.gz")) training_data_files.append(tuple(subject_files)) return training_data_files def main(overwrite=False): if overwrite or not os.path.exists(config["data_file"]): training_files = fetch_training_data_files() write_data_to_file(training_files, config["data_file"], image_shape=config["image_shape"]) data_file_opened = open_data_file(config["data_file"]) if not overwrite and os.path.exists(config["model_file"]): model = load_old_model(config["model_file"]) else: model = unet_model_3d(input_shape=config["input_shape"], pool_size=config["pool_size"], n_labels=config["n_labels"], initial_learning_rate=config["initial_learning_rate"], deconvolution=config["deconvolution"]) train_generator, validation_generator, n_train_steps, n_validation_steps = get_training_and_validation_generators( data_file_opened, batch_size=config["batch_size"], data_split=config["validation_split"], overwrite=overwrite, validation_keys_file=config["validation_file"], training_keys_file=config["training_file"], n_labels=config["n_labels"], labels=config["labels"], patch_shape=config["patch_shape"], validation_batch_size=config["validation_batch_size"], validation_patch_overlap=config["validation_patch_overlap"], training_patch_start_offset=config["training_patch_start_offset"], permute=config["permute"], augment=config["augment"], skip_blank=config["skip_blank"], augment_flip=config["flip"], augment_distortion_factor=config["distort"]) train_model(model=model, model_file=config["model_file"], training_generator=train_generator, validation_generator=validation_generator, steps_per_epoch=n_train_steps, validation_steps=n_validation_steps, initial_learning_rate=config["initial_learning_rate"], learning_rate_drop=config["learning_rate_drop"], learning_rate_patience=config["patience"], early_stopping_patience=config["early_stop"], n_epochs=config["n_epochs"]) data_file_opened.close() if __name__ == "__main__": main(overwrite=config["overwrite"])

true

f738ec615bbc59a200166241a693db04f8899803

1,074

py

Python

bin/test-object-detector.py

ririko-nakamura/HOG-SVM-python

5baa2d715b7c7a69a33328ef01f67d0af3c0b682

[ "MIT" ]

44

2018-12-07T09:44:36.000Z

2022-03-08T02:43:13.000Z

bin/test-object-detector.py

deng88598424/HOG-SVM-python

5baa2d715b7c7a69a33328ef01f67d0af3c0b682

[ "MIT" ]

5

2019-06-04T13:26:29.000Z

2021-12-28T15:27:06.000Z

bin/test-object-detector.py

deng88598424/HOG-SVM-python

5baa2d715b7c7a69a33328ef01f67d0af3c0b682

[ "MIT" ]

29

2019-01-17T07:36:35.000Z

2022-03-22T12:59:23.000Z

#!/usr/bin/python import os # Link to the UIUC Car Database # http://l2r.cs.uiuc.edu/~cogcomp/Data/Car/CarData.tar.gz # dataset_url = "http://l2r.cs.uiuc.edu/~cogcomp/Data/Car/CarData.tar.gz" # dataset_path = "../data/dataset/CarData.tar.gz" # Fetch and extract the dataset # if not os.path.exists(dataset_path): # os.system("wget {} -O {}".format(dataset_url, dataset_path)) # os.system("tar -xvzf {} -C {}".format(dataset_path, os.path.split(dataset_path)[0])) # Extract the features # pos_path = "../data/dataset/CarData/pos" # neg_path = "../data/dataset/CarData/neg" # os.system("python ../object-detector/extract-features.py -p {} -n {}".format(pos_path, neg_path)) # Perform training # pos_feat_path = "../data/features/pos" # neg_feat_path = "../data/features/neg" # os.system("python ../object-detector/train-classifier.py -p {} -n {}".format(pos_feat_path, neg_feat_path)) # Perform testing test_im_path = "../data/dataset/CarData/TestImages/test-18.pgm" os.system("python ../object-detector/test-classifier.py -i {} -d {}".format(test_im_path,2))

39.777778

109

0.699255

import os test_im_path = "../data/dataset/CarData/TestImages/test-18.pgm" os.system("python ../object-detector/test-classifier.py -i {} -d {}".format(test_im_path,2))

true

f738ecb6bc186b66228336eb1ee27467d2b2701a

1,241

py

Python

crudProj/crudProj/urls.py

Dishant15/simform-crud

93a02898f6dc5e8fa509f324a1e6d4137d7d26ad

[ "Apache-2.0" ]

null

crudProj/crudProj/urls.py

Dishant15/simform-crud

93a02898f6dc5e8fa509f324a1e6d4137d7d26ad

[ "Apache-2.0" ]

null

crudProj/crudProj/urls.py

Dishant15/simform-crud

93a02898f6dc5e8fa509f324a1e6d4137d7d26ad

[ "Apache-2.0" ]

null

"""crudProj URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/3.0/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path from django.conf.urls import url, include from crudApp import views from django.conf.urls.static import static from django.conf import settings urlpatterns = [ path('admin/', admin.site.urls), url(r'^register/$', views.register, name='register'), url(r'^user_login/$', views.user_login, name='user_login'), url(r'^logout/$', views.user_logout, name='logout'), url(r'^', include('crudApp.urls')), ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

35.457143

77

0.701048

from django.contrib import admin from django.urls import path from django.conf.urls import url, include from crudApp import views from django.conf.urls.static import static from django.conf import settings urlpatterns = [ path('admin/', admin.site.urls), url(r'^register/$', views.register, name='register'), url(r'^user_login/$', views.user_login, name='user_login'), url(r'^logout/$', views.user_logout, name='logout'), url(r'^', include('crudApp.urls')), ] if settings.DEBUG: urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

true

f738ed20226c816f2abe1cbbc4bdbd9d9c9c81d1

2,904

py

Python

tests/on_policy_models/test_on_policy_model.py

HenryJia/lightning-baselines3

10d1a0eed6136978204323250e37d49915a12e14

[ "MIT" ]

3

2021-01-18T23:27:38.000Z

2021-10-04T12:07:16.000Z

tests/on_policy_models/test_on_policy_model.py

HenryJia/lightning-baselines3

10d1a0eed6136978204323250e37d49915a12e14

[ "MIT" ]

8

2021-01-21T03:29:29.000Z

2021-07-25T18:45:39.000Z

tests/on_policy_models/test_on_policy_model.py

HenryJia/lightning-baselines3

10d1a0eed6136978204323250e37d49915a12e14

[ "MIT" ]

null

from collections import OrderedDict import pytest import gym from gym import spaces import torch from torch import nn import torch.nn.functional as F from torch import distributions import pytorch_lightning as pl from lightning_baselines3.on_policy_models.on_policy_model import OnPolicyModel class DummyModel(OnPolicyModel): def __init__(self, *args, **kwargs): super(DummyModel, self).__init__(*args, **kwargs) if isinstance(self.action_space, spaces.Discrete): self.p = nn.Parameter(torch.ones(1, self.action_space.n) * 0.5) elif isinstance(self.action_space, spaces.Box): self.p = nn.Parameter(torch.ones(1, self.action_space.shape[0] * 2) * 0.5) else: raise Exception('Incompatible environment action space') def forward(self, x, **kwargs): p = self.p.expand(x.shape[0], self.p.shape[-1]) if isinstance(self.action_space, spaces.Discrete): dist = distributions.Categorical(probs=F.softmax(p, dim=1)) elif isinstance(self.action_space, spaces.Box): p = torch.chunk(p, 2, dim=1) dist = distributions.Normal(loc=p[0], scale=1 + p[1] ** 2) return dist, torch.ones_like(x)[:, :1] def predict(self, x, deterministic=True): p = self.p.expand(x.shape[0], self.p.shape[-1]) if deterministic: if isinstance(self.action_space, spaces.Discrete): out = torch.max(p, dim=1)[1] elif isinstance(self.action_space, spaces.Box): out = torch.chunk(p, 2, dim=1)[0] else: if isinstance(self.action_space, spaces.Discrete): out = distributions.Categorical(probs=F.softmax(p, dim=1)).sample() elif isinstance(self.action_space, spaces.Box): p = torch.chunk(p, 2, dim=1) out = distributions.Normal(loc=p[0], scale=1 + p[1] ** 2).sample() return out.cpu().numpy() def training_step(self, x, batch_idx): loss = self(x.observations)[0].entropy().mean() self.log('loss', loss) return loss def configure_optimizers(self): optimizer = torch.optim.Adam(self.parameters(), lr=1e-3) return optimizer @pytest.mark.parametrize("env_id", ["CartPole-v1", "MountainCar-v0", "MountainCarContinuous-v0"]) def test_on_policy_model(env_id): """ Check that environmnent integrated in Gym pass the test. :param env_id: (str) """ model = DummyModel( env_id, eval_env=env_id, buffer_length=512, num_rollouts=1, batch_size=32, epochs_per_rollout=10, num_eval_episodes=10, gamma=0.9, gae_lambda=0.95, use_sde=False, sde_sample_freq=-1, verbose=1, seed=1234) trainer = pl.Trainer(max_epochs=2, terminate_on_nan=True) trainer.fit(model)

30.893617

97

0.625

from collections import OrderedDict import pytest import gym from gym import spaces import torch from torch import nn import torch.nn.functional as F from torch import distributions import pytorch_lightning as pl from lightning_baselines3.on_policy_models.on_policy_model import OnPolicyModel class DummyModel(OnPolicyModel): def __init__(self, *args, **kwargs): super(DummyModel, self).__init__(*args, **kwargs) if isinstance(self.action_space, spaces.Discrete): self.p = nn.Parameter(torch.ones(1, self.action_space.n) * 0.5) elif isinstance(self.action_space, spaces.Box): self.p = nn.Parameter(torch.ones(1, self.action_space.shape[0] * 2) * 0.5) else: raise Exception('Incompatible environment action space') def forward(self, x, **kwargs): p = self.p.expand(x.shape[0], self.p.shape[-1]) if isinstance(self.action_space, spaces.Discrete): dist = distributions.Categorical(probs=F.softmax(p, dim=1)) elif isinstance(self.action_space, spaces.Box): p = torch.chunk(p, 2, dim=1) dist = distributions.Normal(loc=p[0], scale=1 + p[1] ** 2) return dist, torch.ones_like(x)[:, :1] def predict(self, x, deterministic=True): p = self.p.expand(x.shape[0], self.p.shape[-1]) if deterministic: if isinstance(self.action_space, spaces.Discrete): out = torch.max(p, dim=1)[1] elif isinstance(self.action_space, spaces.Box): out = torch.chunk(p, 2, dim=1)[0] else: if isinstance(self.action_space, spaces.Discrete): out = distributions.Categorical(probs=F.softmax(p, dim=1)).sample() elif isinstance(self.action_space, spaces.Box): p = torch.chunk(p, 2, dim=1) out = distributions.Normal(loc=p[0], scale=1 + p[1] ** 2).sample() return out.cpu().numpy() def training_step(self, x, batch_idx): loss = self(x.observations)[0].entropy().mean() self.log('loss', loss) return loss def configure_optimizers(self): optimizer = torch.optim.Adam(self.parameters(), lr=1e-3) return optimizer @pytest.mark.parametrize("env_id", ["CartPole-v1", "MountainCar-v0", "MountainCarContinuous-v0"]) def test_on_policy_model(env_id): model = DummyModel( env_id, eval_env=env_id, buffer_length=512, num_rollouts=1, batch_size=32, epochs_per_rollout=10, num_eval_episodes=10, gamma=0.9, gae_lambda=0.95, use_sde=False, sde_sample_freq=-1, verbose=1, seed=1234) trainer = pl.Trainer(max_epochs=2, terminate_on_nan=True) trainer.fit(model)

true

f738ee018a1e60522d6b78e953990ae94a7f8ee5

13,942

py

Python

vsts/vsts/vss_client.py

mariusvniekerk/vsts-python-api

db69b3bdb08d926ff64239c3d651741a2ae4ea87

[ "MIT" ]

null

vsts/vsts/vss_client.py

mariusvniekerk/vsts-python-api

db69b3bdb08d926ff64239c3d651741a2ae4ea87

[ "MIT" ]

null

vsts/vsts/vss_client.py

mariusvniekerk/vsts-python-api

db69b3bdb08d926ff64239c3d651741a2ae4ea87

[ "MIT" ]

null

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from __future__ import print_function import logging import os import re import uuid from msrest import Deserializer, Serializer from msrest.exceptions import DeserializationError, SerializationError from msrest.pipeline import ClientRequest from msrest.service_client import ServiceClient from .exceptions import VstsAuthenticationError, VstsClientRequestError, VstsServiceError from .vss_client_configuration import VssClientConfiguration from . import models from ._file_cache import OPTIONS_CACHE as OPTIONS_FILE_CACHE logger = logging.getLogger(__name__) class VssClient(object): """VssClient. :param str base_url: Service URL :param Authentication creds: Authenticated credentials. """ def __init__(self, base_url=None, creds=None): self.config = VssClientConfiguration(base_url) self._client = ServiceClient(creds, self.config) _base_client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} self._base_deserialize = Deserializer(_base_client_models) self._base_serialize = Serializer(_base_client_models) self._all_host_types_locations = None self._locations = None self._suppress_fedauth_redirect = True self.normalized_url = VssClient._normalize_url(base_url) def add_user_agent(self, user_agent): if user_agent is not None: self.config.add_user_agent(user_agent) def _send_request(self, request, headers=None, content=None, **operation_config): """Prepare and send request object according to configuration. :param ClientRequest request: The request object to be sent. :param dict headers: Any headers to add to the request. :param content: Any body data to add to the request. :param config: Any specific config overrides """ if TRACE_ENV_VAR in os.environ and os.environ[TRACE_ENV_VAR] == 'true': print(request.method + ' ' + request.url) logger.debug('%s %s', request.method, request.url) logger.debug('Request content: %s', content) response = self._client.send(request=request, headers=headers, content=content, **operation_config) logger.debug('Response content: %s', response.content) if response.status_code < 200 or response.status_code >= 300: self._handle_error(request, response) return response def _send(self, http_method, location_id, version, route_values=None, query_parameters=None, content=None, media_type='application/json', returns_collection=False): request = self._create_request_message(http_method=http_method, location_id=location_id, route_values=route_values, query_parameters=query_parameters) negotiated_version = self._negotiate_request_version( self._get_resource_location(location_id), version) if version != negotiated_version: logger.info("Negotiated api version from '%s' down to '%s'. This means the client is newer than the server.", version, negotiated_version) else: logger.debug("Api version '%s'", negotiated_version) # Construct headers headers = {'Content-Type': media_type + '; charset=utf-8', 'Accept': 'application/json;api-version=' + negotiated_version} if self.config.additional_headers is not None: for key in self.config.additional_headers: headers[key] = self.config.additional_headers[key] if self._suppress_fedauth_redirect: headers['X-TFS-FedAuthRedirect'] = 'Suppress' if VssClient._session_header_key in VssClient._session_data and VssClient._session_header_key not in headers: headers[VssClient._session_header_key] = VssClient._session_data[VssClient._session_header_key] response = self._send_request(request=request, headers=headers, content=content) if VssClient._session_header_key in response.headers: VssClient._session_data[VssClient._session_header_key] = response.headers[VssClient._session_header_key] if returns_collection: if response.headers.get("transfer-encoding") == 'chunked': wrapper = self._base_deserialize.deserialize_data(response.json(), 'VssJsonCollectionWrapper') else: wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) collection = wrapper.value return collection else: return response def _create_request_message(self, http_method, location_id, route_values=None, query_parameters=None): location = self._get_resource_location(location_id) if location is None: raise ValueError('API resource location ' + location_id + ' is not registered on ' + self.config.base_url + '.') if route_values is None: route_values = {} route_values['area'] = location.area route_values['resource'] = location.resource_name route_template = self._remove_optional_route_parameters(location.route_template, route_values) logger.debug('Route template: %s', location.route_template) url = self._client.format_url(route_template, **route_values) request = ClientRequest() request.url = self._client.format_url(url) if query_parameters: request.format_parameters(query_parameters) request.method = http_method return request @staticmethod def _remove_optional_route_parameters(route_template, route_values): new_template = '' route_template = route_template.replace('{*', '{') for path_segment in route_template.split('/'): if (len(path_segment) <= 2 or not path_segment[0] == '{' or not path_segment[len(path_segment) - 1] == '}' or path_segment[1:len(path_segment) - 1] in route_values): new_template = new_template + '/' + path_segment return new_template def _get_resource_location(self, location_id): if self.config.base_url not in VssClient._locations_cache: VssClient._locations_cache[self.config.base_url] = self._get_resource_locations(all_host_types=False) for location in VssClient._locations_cache[self.config.base_url]: if location.id == location_id: return location def _get_resource_locations(self, all_host_types): # Check local client's cached Options first if all_host_types: if self._all_host_types_locations is not None: return self._all_host_types_locations elif self._locations is not None: return self._locations # Next check for options cached on disk if not all_host_types and OPTIONS_FILE_CACHE[self.normalized_url]: try: logger.debug('File cache hit for options on: %s', self.normalized_url) self._locations = self._base_deserialize.deserialize_data(OPTIONS_FILE_CACHE[self.normalized_url], '[ApiResourceLocation]') return self._locations except DeserializationError as ex: logger.debug(ex, exc_info=True) else: logger.debug('File cache miss for options on: %s', self.normalized_url) # Last resort, make the call to the server options_uri = self._combine_url(self.config.base_url, '_apis') request = ClientRequest() request.url = self._client.format_url(options_uri) if all_host_types: query_parameters = {'allHostTypes': True} request.format_parameters(query_parameters) request.method = 'OPTIONS' headers = {'Accept': 'application/json'} if self._suppress_fedauth_redirect: headers['X-TFS-FedAuthRedirect'] = 'Suppress' response = self._send_request(request, headers=headers) wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) if wrapper is None: raise VstsClientRequestError("Failed to retrieve resource locations from: {}".format(options_uri)) collection = wrapper.value returned_locations = self._base_deserialize('[ApiResourceLocation]', collection) if all_host_types: self._all_host_types_locations = returned_locations else: self._locations = returned_locations try: OPTIONS_FILE_CACHE[self.normalized_url] = wrapper.value except SerializationError as ex: logger.debug(ex, exc_info=True) return returned_locations @staticmethod def _negotiate_request_version(location, version): if location is None or version is None: return version pattern = r'(\d+(\.\d)?)(-preview(.(\d+))?)?' match = re.match(pattern, version) requested_api_version = match.group(1) if requested_api_version is not None: requested_api_version = float(requested_api_version) if location.min_version > requested_api_version: # Client is older than the server. The server no longer supports this # resource (deprecated). return elif location.max_version < requested_api_version: # Client is newer than the server. Negotiate down to the latest version # on the server negotiated_version = str(location.max_version) if float(location.released_version) < location.max_version: negotiated_version += '-preview' return negotiated_version else: # We can send at the requested api version. Make sure the resource version # is not bigger than what the server supports negotiated_version = str(requested_api_version) is_preview = match.group(3) is not None if is_preview: negotiated_version += '-preview' if match.group(5) is not None: if location.resource_version < int(match.group(5)): negotiated_version += '.' + str(location.resource_version) else: negotiated_version += '.' + match.group(5) return negotiated_version @staticmethod def _combine_url(part1, part2): return part1.rstrip('/') + '/' + part2.strip('/') def _handle_error(self, request, response): content_type = response.headers.get('Content-Type') error_message = '' if content_type is None or content_type.find('text/plain') < 0: try: wrapped_exception = self._base_deserialize('WrappedException', response) if wrapped_exception is not None and wrapped_exception.message is not None: raise VstsServiceError(wrapped_exception) else: # System exceptions from controllers are not returning wrapped exceptions. # Following code is to handle this unusual exception json case. # TODO: dig into this. collection_wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) if collection_wrapper is not None and collection_wrapper.value is not None: wrapped_exception = self._base_deserialize('ImproperException', collection_wrapper.value) if wrapped_exception is not None and wrapped_exception.message is not None: raise VstsClientRequestError(wrapped_exception.message) # if we get here we still have not raised an exception, try to deserialize as a System Exception system_exception = self._base_deserialize('SystemException', response) if system_exception is not None and system_exception.message is not None: raise VstsClientRequestError(system_exception.message) except DeserializationError: pass elif response.content is not None: error_message = response.content.decode("utf-8") + ' ' if response.status_code == 401: full_message_format = '{error_message}The requested resource requires user authentication: {url}' raise VstsAuthenticationError(full_message_format.format(error_message=error_message, url=request.url)) else: full_message_format = '{error_message}Operation returned an invalid status code of {status_code}.' raise VstsClientRequestError(full_message_format.format(error_message=error_message, status_code=response.status_code)) @staticmethod def _normalize_url(url): return url.rstrip('/').lower() _locations_cache = {} _session_header_key = 'X-TFS-Session' _session_data = {_session_header_key: str(uuid.uuid4())} TRACE_ENV_VAR = 'vsts_python_print_urls'

50.698182

121

0.632047

from __future__ import print_function import logging import os import re import uuid from msrest import Deserializer, Serializer from msrest.exceptions import DeserializationError, SerializationError from msrest.pipeline import ClientRequest from msrest.service_client import ServiceClient from .exceptions import VstsAuthenticationError, VstsClientRequestError, VstsServiceError from .vss_client_configuration import VssClientConfiguration from . import models from ._file_cache import OPTIONS_CACHE as OPTIONS_FILE_CACHE logger = logging.getLogger(__name__) class VssClient(object): def __init__(self, base_url=None, creds=None): self.config = VssClientConfiguration(base_url) self._client = ServiceClient(creds, self.config) _base_client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)} self._base_deserialize = Deserializer(_base_client_models) self._base_serialize = Serializer(_base_client_models) self._all_host_types_locations = None self._locations = None self._suppress_fedauth_redirect = True self.normalized_url = VssClient._normalize_url(base_url) def add_user_agent(self, user_agent): if user_agent is not None: self.config.add_user_agent(user_agent) def _send_request(self, request, headers=None, content=None, **operation_config): if TRACE_ENV_VAR in os.environ and os.environ[TRACE_ENV_VAR] == 'true': print(request.method + ' ' + request.url) logger.debug('%s %s', request.method, request.url) logger.debug('Request content: %s', content) response = self._client.send(request=request, headers=headers, content=content, **operation_config) logger.debug('Response content: %s', response.content) if response.status_code < 200 or response.status_code >= 300: self._handle_error(request, response) return response def _send(self, http_method, location_id, version, route_values=None, query_parameters=None, content=None, media_type='application/json', returns_collection=False): request = self._create_request_message(http_method=http_method, location_id=location_id, route_values=route_values, query_parameters=query_parameters) negotiated_version = self._negotiate_request_version( self._get_resource_location(location_id), version) if version != negotiated_version: logger.info("Negotiated api version from '%s' down to '%s'. This means the client is newer than the server.", version, negotiated_version) else: logger.debug("Api version '%s'", negotiated_version) headers = {'Content-Type': media_type + '; charset=utf-8', 'Accept': 'application/json;api-version=' + negotiated_version} if self.config.additional_headers is not None: for key in self.config.additional_headers: headers[key] = self.config.additional_headers[key] if self._suppress_fedauth_redirect: headers['X-TFS-FedAuthRedirect'] = 'Suppress' if VssClient._session_header_key in VssClient._session_data and VssClient._session_header_key not in headers: headers[VssClient._session_header_key] = VssClient._session_data[VssClient._session_header_key] response = self._send_request(request=request, headers=headers, content=content) if VssClient._session_header_key in response.headers: VssClient._session_data[VssClient._session_header_key] = response.headers[VssClient._session_header_key] if returns_collection: if response.headers.get("transfer-encoding") == 'chunked': wrapper = self._base_deserialize.deserialize_data(response.json(), 'VssJsonCollectionWrapper') else: wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) collection = wrapper.value return collection else: return response def _create_request_message(self, http_method, location_id, route_values=None, query_parameters=None): location = self._get_resource_location(location_id) if location is None: raise ValueError('API resource location ' + location_id + ' is not registered on ' + self.config.base_url + '.') if route_values is None: route_values = {} route_values['area'] = location.area route_values['resource'] = location.resource_name route_template = self._remove_optional_route_parameters(location.route_template, route_values) logger.debug('Route template: %s', location.route_template) url = self._client.format_url(route_template, **route_values) request = ClientRequest() request.url = self._client.format_url(url) if query_parameters: request.format_parameters(query_parameters) request.method = http_method return request @staticmethod def _remove_optional_route_parameters(route_template, route_values): new_template = '' route_template = route_template.replace('{*', '{') for path_segment in route_template.split('/'): if (len(path_segment) <= 2 or not path_segment[0] == '{' or not path_segment[len(path_segment) - 1] == '}' or path_segment[1:len(path_segment) - 1] in route_values): new_template = new_template + '/' + path_segment return new_template def _get_resource_location(self, location_id): if self.config.base_url not in VssClient._locations_cache: VssClient._locations_cache[self.config.base_url] = self._get_resource_locations(all_host_types=False) for location in VssClient._locations_cache[self.config.base_url]: if location.id == location_id: return location def _get_resource_locations(self, all_host_types): if all_host_types: if self._all_host_types_locations is not None: return self._all_host_types_locations elif self._locations is not None: return self._locations # Next check for options cached on disk if not all_host_types and OPTIONS_FILE_CACHE[self.normalized_url]: try: logger.debug('File cache hit for options on: %s', self.normalized_url) self._locations = self._base_deserialize.deserialize_data(OPTIONS_FILE_CACHE[self.normalized_url], '[ApiResourceLocation]') return self._locations except DeserializationError as ex: logger.debug(ex, exc_info=True) else: logger.debug('File cache miss for options on: %s', self.normalized_url) # Last resort, make the call to the server options_uri = self._combine_url(self.config.base_url, '_apis') request = ClientRequest() request.url = self._client.format_url(options_uri) if all_host_types: query_parameters = {'allHostTypes': True} request.format_parameters(query_parameters) request.method = 'OPTIONS' headers = {'Accept': 'application/json'} if self._suppress_fedauth_redirect: headers['X-TFS-FedAuthRedirect'] = 'Suppress' response = self._send_request(request, headers=headers) wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) if wrapper is None: raise VstsClientRequestError("Failed to retrieve resource locations from: {}".format(options_uri)) collection = wrapper.value returned_locations = self._base_deserialize('[ApiResourceLocation]', collection) if all_host_types: self._all_host_types_locations = returned_locations else: self._locations = returned_locations try: OPTIONS_FILE_CACHE[self.normalized_url] = wrapper.value except SerializationError as ex: logger.debug(ex, exc_info=True) return returned_locations @staticmethod def _negotiate_request_version(location, version): if location is None or version is None: return version pattern = r'(\d+(\.\d)?)(-preview(.(\d+))?)?' match = re.match(pattern, version) requested_api_version = match.group(1) if requested_api_version is not None: requested_api_version = float(requested_api_version) if location.min_version > requested_api_version: # Client is older than the server. The server no longer supports this # resource (deprecated). return elif location.max_version < requested_api_version: # Client is newer than the server. Negotiate down to the latest version # on the server negotiated_version = str(location.max_version) if float(location.released_version) < location.max_version: negotiated_version += '-preview' return negotiated_version else: # We can send at the requested api version. Make sure the resource version # is not bigger than what the server supports negotiated_version = str(requested_api_version) is_preview = match.group(3) is not None if is_preview: negotiated_version += '-preview' if match.group(5) is not None: if location.resource_version < int(match.group(5)): negotiated_version += '.' + str(location.resource_version) else: negotiated_version += '.' + match.group(5) return negotiated_version @staticmethod def _combine_url(part1, part2): return part1.rstrip('/') + '/' + part2.strip('/') def _handle_error(self, request, response): content_type = response.headers.get('Content-Type') error_message = '' if content_type is None or content_type.find('text/plain') < 0: try: wrapped_exception = self._base_deserialize('WrappedException', response) if wrapped_exception is not None and wrapped_exception.message is not None: raise VstsServiceError(wrapped_exception) else: # System exceptions from controllers are not returning wrapped exceptions. # Following code is to handle this unusual exception json case. # TODO: dig into this. collection_wrapper = self._base_deserialize('VssJsonCollectionWrapper', response) if collection_wrapper is not None and collection_wrapper.value is not None: wrapped_exception = self._base_deserialize('ImproperException', collection_wrapper.value) if wrapped_exception is not None and wrapped_exception.message is not None: raise VstsClientRequestError(wrapped_exception.message) # if we get here we still have not raised an exception, try to deserialize as a System Exception system_exception = self._base_deserialize('SystemException', response) if system_exception is not None and system_exception.message is not None: raise VstsClientRequestError(system_exception.message) except DeserializationError: pass elif response.content is not None: error_message = response.content.decode("utf-8") + ' ' if response.status_code == 401: full_message_format = '{error_message}The requested resource requires user authentication: {url}' raise VstsAuthenticationError(full_message_format.format(error_message=error_message, url=request.url)) else: full_message_format = '{error_message}Operation returned an invalid status code of {status_code}.' raise VstsClientRequestError(full_message_format.format(error_message=error_message, status_code=response.status_code)) @staticmethod def _normalize_url(url): return url.rstrip('/').lower() _locations_cache = {} _session_header_key = 'X-TFS-Session' _session_data = {_session_header_key: str(uuid.uuid4())} TRACE_ENV_VAR = 'vsts_python_print_urls'

true

f738ee36d86611a0e4f64027426f2e2fee301bdd

1,505

py

Python

openapi/pagination/search.py

lendingblock/aio-openapi

cd274c618dfeb67c6e77b0293e6f5941e4c98f97

[ "BSD-3-Clause" ]

7

2018-05-22T16:15:32.000Z

2019-01-23T19:50:58.000Z

openapi/pagination/search.py

lendingblock/aio-openapi

cd274c618dfeb67c6e77b0293e6f5941e4c98f97

[ "BSD-3-Clause" ]

116

2018-05-17T21:55:02.000Z

2019-02-14T08:35:31.000Z

openapi/pagination/search.py

lendingblock/aio-openapi

cd274c618dfeb67c6e77b0293e6f5941e4c98f97

[ "BSD-3-Clause" ]

null

from dataclasses import dataclass from typing import Sequence from openapi.data.fields import str_field from openapi.utils import docjoin from .pagination import from_filters_and_dataclass class SearchVisitor: def apply_search(self, search: str, search_fields: Sequence[str]) -> None: raise NotImplementedError @dataclass class Search: @classmethod def create_search(cls, data: dict) -> "Search": return cls() def apply(self, visitor: SearchVisitor) -> None: pass def searchable(*searchable_fields) -> type: """Create a dataclass with `search_fields` class attribute and `search` field. The search field is a set of field which can be used for searching and it is used internally by the library, while the `search` field is the query string passed in the url. :param searchable_fields: fields which can be used for searching """ fields = docjoin(searchable_fields) @dataclass class Searchable(Search): search_fields = frozenset(searchable_fields) search: str = str_field( description=( "Search query string. " f"The search is performed on {fields} fields." ) ) @classmethod def create_search(cls, data: dict) -> "Searchable": return from_filters_and_dataclass(Searchable, data) def apply(self, visitor: SearchVisitor) -> None: visitor.apply_search(self.search, self.search_fields) return Searchable

28.942308

86

0.685714

from dataclasses import dataclass from typing import Sequence from openapi.data.fields import str_field from openapi.utils import docjoin from .pagination import from_filters_and_dataclass class SearchVisitor: def apply_search(self, search: str, search_fields: Sequence[str]) -> None: raise NotImplementedError @dataclass class Search: @classmethod def create_search(cls, data: dict) -> "Search": return cls() def apply(self, visitor: SearchVisitor) -> None: pass def searchable(*searchable_fields) -> type: fields = docjoin(searchable_fields) @dataclass class Searchable(Search): search_fields = frozenset(searchable_fields) search: str = str_field( description=( "Search query string. " f"The search is performed on {fields} fields." ) ) @classmethod def create_search(cls, data: dict) -> "Searchable": return from_filters_and_dataclass(Searchable, data) def apply(self, visitor: SearchVisitor) -> None: visitor.apply_search(self.search, self.search_fields) return Searchable

true

f738ee521433ce2b9bd1a33e489995858abb8aa1

670

py

Python

main/byacc/template.py

matu3ba/cports

deab766f255539c3679b78706ec4d194bc019dc9

[ "BSD-2-Clause" ]

46

2021-06-10T02:27:32.000Z

2022-03-27T11:33:24.000Z

main/byacc/template.py

matu3ba/cports

deab766f255539c3679b78706ec4d194bc019dc9

[ "BSD-2-Clause" ]

58

2021-07-03T13:58:20.000Z

2022-03-13T16:45:35.000Z

main/byacc/template.py

matu3ba/cports

deab766f255539c3679b78706ec4d194bc019dc9

[ "BSD-2-Clause" ]

6

2021-07-04T10:46:40.000Z

2022-01-09T00:03:59.000Z

pkgname = "byacc" pkgver = "20210808" pkgrel = 0 build_style = "gnu_configure" configure_args = ["--program-transform=s,^,b,"] pkgdesc = "Berkeley yacc, a LALR(1) parser generator" maintainer = "q66 <q66@chimera-linux.org>" license="custom:byacc" url = "http://invisible-island.net/byacc" source = f"ftp://ftp.invisible-island.net/{pkgname}/{pkgname}-{pkgver}.tgz" sha256 = "f158529be9d0594263c7f11a87616a49ea23e55ac63691252a2304fbbc7d3a83" options = ["bootstrap"] def post_install(self): self.install_license("README") self.install_license("LICENSE") self.install_link("byacc", "usr/bin/yacc") self.install_link("byacc.1", "usr/share/man/man1/yacc.1")

35.263158

75

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pkgname = "byacc" pkgver = "20210808" pkgrel = 0 build_style = "gnu_configure" configure_args = ["--program-transform=s,^,b,"] pkgdesc = "Berkeley yacc, a LALR(1) parser generator" maintainer = "q66 <q66@chimera-linux.org>" license="custom:byacc" url = "http://invisible-island.net/byacc" source = f"ftp://ftp.invisible-island.net/{pkgname}/{pkgname}-{pkgver}.tgz" sha256 = "f158529be9d0594263c7f11a87616a49ea23e55ac63691252a2304fbbc7d3a83" options = ["bootstrap"] def post_install(self): self.install_license("README") self.install_license("LICENSE") self.install_link("byacc", "usr/bin/yacc") self.install_link("byacc.1", "usr/share/man/man1/yacc.1")

true

f738ef9698057d4e6f0320a579c6146780b82dba

584

py

Python

odds/common/utils.py

conrad-evans/sports_betting_api

baa80df5608c1cc244f51be86ba29eaabd8f031e

[ "MIT" ]

null

odds/common/utils.py

conrad-evans/sports_betting_api

baa80df5608c1cc244f51be86ba29eaabd8f031e

[ "MIT" ]

null

odds/common/utils.py

conrad-evans/sports_betting_api

baa80df5608c1cc244f51be86ba29eaabd8f031e

[ "MIT" ]

null

import secrets import time class Utils: _instance = None def __init__(self) -> None: pass @staticmethod def generateRandomId(): """ Generates a random hexicdecimal string Returns: `str`: string with hexidecimal values >>> """ token = secrets.token_hex() now = time.time() id = now + token return id @staticmethod def getInstance(re_init=False): if Utils._instance is None or re_init: Utils._instance = Utils() return Utils._instance

18.83871

49

0.563356

import secrets import time class Utils: _instance = None def __init__(self) -> None: pass @staticmethod def generateRandomId(): token = secrets.token_hex() now = time.time() id = now + token return id @staticmethod def getInstance(re_init=False): if Utils._instance is None or re_init: Utils._instance = Utils() return Utils._instance

true

f738f3a02a6643116edf664e741054e24c835882

332

py

Python

sdk/python/pulumi_aws/ram/__init__.py

lemonade-hq/pulumi-aws

9ee22c65c7bad42d38b16879ccd56526d856a01a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/ram/__init__.py

lemonade-hq/pulumi-aws

9ee22c65c7bad42d38b16879ccd56526d856a01a

[ "ECL-2.0", "Apache-2.0" ]

null

sdk/python/pulumi_aws/ram/__init__.py

lemonade-hq/pulumi-aws

9ee22c65c7bad42d38b16879ccd56526d856a01a

[ "ECL-2.0", "Apache-2.0" ]

1

2021-03-08T15:05:29.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** # Export this package's modules as members: from .principal_association import * from .resource_association import * from .resource_share import *

36.888889

87

0.740964

# Export this package's modules as members: from .principal_association import * from .resource_association import * from .resource_share import *

true

f738f4f4e9aaf552abff28f5e76349433a08aac1

396

py

Python

trio-stuff/interleaved_output.py

bmintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-12T10:33:13.000Z

2019-02-24T05:01:40.000Z

trio-stuff/interleaved_output.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

null

trio-stuff/interleaved_output.py

iomintz/python-snippets

982861c173bf4bcd5d908514a9e8b1914a580a5d

[ "CC0-1.0" ]

2

2018-11-24T08:16:59.000Z

2019-02-24T04:41:30.000Z

#!/usr/bin/env python3 import trio async def a(): print('enter a') await trio.sleep(0) print('leave a') async def b(): print('enter b') await trio.sleep(0) print('leave b') async def main(): async with trio.open_nursery() as nursery: print(nursery.start_soon(a)) nursery.start_soon(b) # seems like the output order is non-deterministic if __name__ == '__main__': trio.run(main)

16.5

50

0.694444

import trio async def a(): print('enter a') await trio.sleep(0) print('leave a') async def b(): print('enter b') await trio.sleep(0) print('leave b') async def main(): async with trio.open_nursery() as nursery: print(nursery.start_soon(a)) nursery.start_soon(b) if __name__ == '__main__': trio.run(main)

true

f738f581a62bbf2ba1039ce79893ba2e39af5318

179

py

Python

fretboard/__init__.py

honorabel/python-fretboard

fb6a37e29bf6a19bee11940e9b42d58220c1306c

[ "MIT" ]

69

2016-11-18T02:11:01.000Z

2022-03-26T12:54:55.000Z

fretboard/__init__.py

honorabel/python-fretboard

fb6a37e29bf6a19bee11940e9b42d58220c1306c

[ "MIT" ]

3

2018-05-24T15:08:46.000Z

2020-09-19T21:49:36.000Z

fretboard/__init__.py

honorabel/python-fretboard

fb6a37e29bf6a19bee11940e9b42d58220c1306c

[ "MIT" ]

16

2018-06-12T10:34:26.000Z

2021-01-09T15:21:55.000Z

from .chord import Chord, BassChord, UkuleleChord from .fretboard import Fretboard __version__ = '1.0.0' __author__ = 'Derek Payton <derek.payton@gmail.com>' __license__ = 'MIT'

25.571429

52

0.765363

from .chord import Chord, BassChord, UkuleleChord from .fretboard import Fretboard __version__ = '1.0.0' __author__ = 'Derek Payton <derek.payton@gmail.com>' __license__ = 'MIT'

true

f738f63479f804d9170fe21b0f803e86f9f518c6

4,680

py

Python

tests/www/api/experimental/test_dag_runs_endpoint.py

rliuamzn/airflow

177dfbd12a42a5c229640c6c830f43f280ea5caa

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

3

2021-07-30T17:29:38.000Z

2022-03-06T08:44:23.000Z

tests/www/api/experimental/test_dag_runs_endpoint.py

rliuamzn/airflow

177dfbd12a42a5c229640c6c830f43f280ea5caa

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

210

2021-07-17T00:25:52.000Z

2021-12-29T00:44:48.000Z

tests/www/api/experimental/test_dag_runs_endpoint.py

rliuamzn/airflow

177dfbd12a42a5c229640c6c830f43f280ea5caa

[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]

3

2020-06-30T02:38:17.000Z

2022-01-19T06:14:08.000Z

# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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 json import pytest from airflow.api.common.experimental.trigger_dag import trigger_dag from airflow.models import DagBag, DagRun from airflow.models.serialized_dag import SerializedDagModel from airflow.settings import Session class TestDagRunsEndpoint: @pytest.fixture(scope="class", autouse=True) def _setup_session(self): session = Session() session.query(DagRun).delete() session.commit() session.close() dagbag = DagBag(include_examples=True) for dag in dagbag.dags.values(): dag.sync_to_db() SerializedDagModel.write_dag(dag) @pytest.fixture(autouse=True) def _reset_test_session(self, experiemental_api_app): self.app = experiemental_api_app.test_client() yield session = Session() session.query(DagRun).delete() session.commit() session.close() def test_get_dag_runs_success(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'example_bash_operator' # Create DagRun dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_state_parameter(self): url_template = '/api/experimental/dags/{}/dag_runs?state=running' dag_id = 'example_bash_operator' # Create DagRun dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_capital_state_parameter(self): url_template = '/api/experimental/dags/{}/dag_runs?state=RUNNING' dag_id = 'example_bash_operator' # Create DagRun dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_state_no_result(self): url_template = '/api/experimental/dags/{}/dag_runs?state=dummy' dag_id = 'example_bash_operator' # Create DagRun trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 0 def test_get_dag_runs_invalid_dag_id(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'DUMMY_DAG' response = self.app.get(url_template.format(dag_id)) assert 400 == response.status_code data = json.loads(response.data.decode('utf-8')) assert not isinstance(data, list) def test_get_dag_runs_no_runs(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'example_bash_operator' response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 0

36.850394

80

0.680556

import json import pytest from airflow.api.common.experimental.trigger_dag import trigger_dag from airflow.models import DagBag, DagRun from airflow.models.serialized_dag import SerializedDagModel from airflow.settings import Session class TestDagRunsEndpoint: @pytest.fixture(scope="class", autouse=True) def _setup_session(self): session = Session() session.query(DagRun).delete() session.commit() session.close() dagbag = DagBag(include_examples=True) for dag in dagbag.dags.values(): dag.sync_to_db() SerializedDagModel.write_dag(dag) @pytest.fixture(autouse=True) def _reset_test_session(self, experiemental_api_app): self.app = experiemental_api_app.test_client() yield session = Session() session.query(DagRun).delete() session.commit() session.close() def test_get_dag_runs_success(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'example_bash_operator' dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_state_parameter(self): url_template = '/api/experimental/dags/{}/dag_runs?state=running' dag_id = 'example_bash_operator' dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_capital_state_parameter(self): url_template = '/api/experimental/dags/{}/dag_runs?state=RUNNING' dag_id = 'example_bash_operator' dag_run = trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 1 assert data[0]['dag_id'] == dag_id assert data[0]['id'] == dag_run.id def test_get_dag_runs_success_with_state_no_result(self): url_template = '/api/experimental/dags/{}/dag_runs?state=dummy' dag_id = 'example_bash_operator' trigger_dag(dag_id=dag_id, run_id='test_get_dag_runs_success') response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 0 def test_get_dag_runs_invalid_dag_id(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'DUMMY_DAG' response = self.app.get(url_template.format(dag_id)) assert 400 == response.status_code data = json.loads(response.data.decode('utf-8')) assert not isinstance(data, list) def test_get_dag_runs_no_runs(self): url_template = '/api/experimental/dags/{}/dag_runs' dag_id = 'example_bash_operator' response = self.app.get(url_template.format(dag_id)) assert 200 == response.status_code data = json.loads(response.data.decode('utf-8')) assert isinstance(data, list) assert len(data) == 0

true

f738f6c80a1a23e674eb48045329f0dee12e3ee9

21,450

py

Python

salt/utils/templates.py

fake-name/salt

d8f04936e4407f51946e32e8166159778f6c31a5

[ "Apache-2.0" ]

null

salt/utils/templates.py

fake-name/salt

d8f04936e4407f51946e32e8166159778f6c31a5

[ "Apache-2.0" ]

null

salt/utils/templates.py

fake-name/salt

d8f04936e4407f51946e32e8166159778f6c31a5

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Template render systems """ from __future__ import absolute_import, print_function, unicode_literals # Import Python libs import codecs import logging import os import sys import tempfile import traceback # Import 3rd-party libs import jinja2 import jinja2.ext # Import Salt libs import salt.utils.data import salt.utils.dateutils import salt.utils.files import salt.utils.hashutils import salt.utils.http import salt.utils.jinja import salt.utils.network import salt.utils.platform import salt.utils.stringutils import salt.utils.yamlencoding from salt import __path__ as saltpath from salt.exceptions import CommandExecutionError, SaltInvocationError, SaltRenderError from salt.ext import six from salt.utils.decorators.jinja import JinjaFilter, JinjaGlobal, JinjaTest from salt.utils.odict import OrderedDict from salt.utils.versions import LooseVersion if sys.version_info[:2] >= (3, 5): import importlib.machinery # pylint: disable=no-name-in-module,import-error import importlib.util # pylint: disable=no-name-in-module,import-error USE_IMPORTLIB = True else: import imp USE_IMPORTLIB = False log = logging.getLogger(__name__) TEMPLATE_DIRNAME = os.path.join(saltpath[0], "templates") # FIXME: also in salt/template.py SLS_ENCODING = "utf-8" # this one has no BOM. SLS_ENCODER = codecs.getencoder(SLS_ENCODING) class AliasedLoader(object): """ Light wrapper around the LazyLoader to redirect 'cmd.run' calls to 'cmd.shell', for easy use of shellisms during templating calls Dotted aliases ('cmd.run') must resolve to another dotted alias (e.g. 'cmd.shell') Non-dotted aliases ('cmd') must resolve to a dictionary of function aliases for that module (e.g. {'run': 'shell'}) """ def __init__(self, wrapped): self.wrapped = wrapped def __getitem__(self, name): return self.wrapped[name] def __getattr__(self, name): return getattr(self.wrapped, name) def __contains__(self, name): return name in self.wrapped class AliasedModule(object): """ Light wrapper around module objects returned by the LazyLoader's getattr for the purposes of `salt.cmd.run()` syntax in templates Allows for aliasing specific functions, such as `run` to `shell` for easy use of shellisms during templating calls """ def __init__(self, wrapped, aliases): self.aliases = aliases self.wrapped = wrapped def __getattr__(self, name): return getattr(self.wrapped, name) def wrap_tmpl_func(render_str): def render_tmpl( tmplsrc, from_str=False, to_str=False, context=None, tmplpath=None, **kws ): if context is None: context = {} # Alias cmd.run to cmd.shell to make python_shell=True the default for # templated calls if "salt" in kws: kws["salt"] = AliasedLoader(kws["salt"]) # We want explicit context to overwrite the **kws kws.update(context) context = kws assert "opts" in context assert "saltenv" in context if "sls" in context: slspath = context["sls"].replace(".", "/") if tmplpath is not None: context["tplpath"] = tmplpath if not tmplpath.lower().replace("\\", "/").endswith("/init.sls"): slspath = os.path.dirname(slspath) template = tmplpath.replace("\\", "/") i = template.rfind(slspath.replace(".", "/")) if i != -1: template = template[i:] tpldir = os.path.dirname(template).replace("\\", "/") tpldata = { 'tplfile': template, 'tpldir': '.' if tpldir == '' else tpldir, 'tpldot': tpldir.replace('/', '.'), 'tplroot': tpldir.split('/')[0], } context.update(tpldata) context["slsdotpath"] = slspath.replace("/", ".") context["slscolonpath"] = slspath.replace("/", ":") context["sls_path"] = slspath.replace("/", "_") context["slspath"] = slspath if isinstance(tmplsrc, six.string_types): if from_str: tmplstr = tmplsrc else: try: if tmplpath is not None: tmplsrc = os.path.join(tmplpath, tmplsrc) with codecs.open(tmplsrc, "r", SLS_ENCODING) as _tmplsrc: tmplstr = _tmplsrc.read() except (UnicodeDecodeError, ValueError, OSError, IOError) as exc: if salt.utils.files.is_binary(tmplsrc): # Template is a bin file, return the raw file return dict(result=True, data=tmplsrc) log.error( "Exception occurred while reading file %s: %s", tmplsrc, exc, exc_info_on_loglevel=logging.DEBUG, ) six.reraise(*sys.exc_info()) else: # assume tmplsrc is file-like. tmplstr = tmplsrc.read() tmplsrc.close() try: output = render_str(tmplstr, context, tmplpath) if salt.utils.platform.is_windows(): newline = False if salt.utils.stringutils.to_unicode( output, encoding=SLS_ENCODING ).endswith(("\n", os.linesep)): newline = True # Write out with Windows newlines output = os.linesep.join(output.splitlines()) if newline: output += os.linesep except SaltRenderError as exc: log.exception("Rendering exception occurred") # return dict(result=False, data=six.text_type(exc)) raise except Exception: # pylint: disable=broad-except return dict(result=False, data=traceback.format_exc()) else: if to_str: # then render as string return dict(result=True, data=output) with tempfile.NamedTemporaryFile( "wb", delete=False, prefix=salt.utils.files.TEMPFILE_PREFIX ) as outf: outf.write( salt.utils.stringutils.to_bytes(output, encoding=SLS_ENCODING) ) # Note: If nothing is replaced or added by the rendering # function, then the contents of the output file will # be exactly the same as the input. return dict(result=True, data=outf.name) render_tmpl.render_str = render_str return render_tmpl def _get_jinja_error_slug(tb_data): """ Return the line number where the template error was found """ try: return [ x for x in tb_data if x[2] in ("top-level template code", "template", "<module>") ][-1] except IndexError: pass def _get_jinja_error_message(tb_data): """ Return an understandable message from jinja error output """ try: line = _get_jinja_error_slug(tb_data) return "{0}({1}):\n{3}".format(*line) except IndexError: pass return None def _get_jinja_error_line(tb_data): """ Return the line number where the template error was found """ try: return _get_jinja_error_slug(tb_data)[1] except IndexError: pass return None def _get_jinja_error(trace, context=None): """ Return the error line and error message output from a stacktrace. If we are in a macro, also output inside the message the exact location of the error in the macro """ if not context: context = {} out = "" error = _get_jinja_error_slug(trace) line = _get_jinja_error_line(trace) msg = _get_jinja_error_message(trace) # if we failed on a nested macro, output a little more info # to help debugging # if sls is not found in context, add output only if we can # resolve the filename add_log = False template_path = None if "sls" not in context: if (error[0] != "<unknown>") and os.path.exists(error[0]): template_path = error[0] add_log = True else: # the offender error is not from the called sls filen = context["sls"].replace(".", "/") if not error[0].endswith(filen) and os.path.exists(error[0]): add_log = True template_path = error[0] # if we add a log, format explicitly the exception here # by telling to output the macro context after the macro # error log place at the beginning if add_log: if template_path: out = "\n{0}\n".format(msg.splitlines()[0]) with salt.utils.files.fopen(template_path) as fp_: template_contents = salt.utils.stringutils.to_unicode(fp_.read()) out += salt.utils.stringutils.get_context( template_contents, line, marker=" <======================" ) else: out = "\n{0}\n".format(msg) line = 0 return line, out def render_jinja_tmpl(tmplstr, context, tmplpath=None): opts = context["opts"] saltenv = context["saltenv"] loader = None newline = False if tmplstr and not isinstance(tmplstr, six.text_type): # http://jinja.pocoo.org/docs/api/#unicode tmplstr = tmplstr.decode(SLS_ENCODING) if tmplstr.endswith(os.linesep): newline = os.linesep elif tmplstr.endswith("\n"): newline = "\n" if not saltenv: if tmplpath: loader = jinja2.FileSystemLoader(os.path.dirname(tmplpath)) else: loader = salt.utils.jinja.SaltCacheLoader( opts, saltenv, pillar_rend=context.get("_pillar_rend", False) ) env_args = {"extensions": [], "loader": loader} if hasattr(jinja2.ext, "with_"): env_args["extensions"].append("jinja2.ext.with_") if hasattr(jinja2.ext, "do"): env_args["extensions"].append("jinja2.ext.do") if hasattr(jinja2.ext, "loopcontrols"): env_args["extensions"].append("jinja2.ext.loopcontrols") env_args["extensions"].append(salt.utils.jinja.SerializerExtension) opt_jinja_env = opts.get("jinja_env", {}) opt_jinja_sls_env = opts.get("jinja_sls_env", {}) opt_jinja_env = opt_jinja_env if isinstance(opt_jinja_env, dict) else {} opt_jinja_sls_env = opt_jinja_sls_env if isinstance(opt_jinja_sls_env, dict) else {} # Pass through trim_blocks and lstrip_blocks Jinja parameters # trim_blocks removes newlines around Jinja blocks # lstrip_blocks strips tabs and spaces from the beginning of # line to the start of a block. if opts.get("jinja_trim_blocks", False): log.debug("Jinja2 trim_blocks is enabled") log.warning( "jinja_trim_blocks is deprecated and will be removed in a future release, please use jinja_env and/or jinja_sls_env instead" ) opt_jinja_env["trim_blocks"] = True opt_jinja_sls_env["trim_blocks"] = True if opts.get("jinja_lstrip_blocks", False): log.debug("Jinja2 lstrip_blocks is enabled") log.warning( "jinja_lstrip_blocks is deprecated and will be removed in a future release, please use jinja_env and/or jinja_sls_env instead" ) opt_jinja_env["lstrip_blocks"] = True opt_jinja_sls_env["lstrip_blocks"] = True def opt_jinja_env_helper(opts, optname): for k, v in six.iteritems(opts): k = k.lower() if hasattr(jinja2.defaults, k.upper()): log.debug("Jinja2 environment %s was set to %s by %s", k, v, optname) env_args[k] = v else: log.warning("Jinja2 environment %s is not recognized", k) if "sls" in context and context["sls"] != "": opt_jinja_env_helper(opt_jinja_sls_env, "jinja_sls_env") else: opt_jinja_env_helper(opt_jinja_env, "jinja_env") if opts.get("allow_undefined", False): jinja_env = jinja2.Environment(**env_args) else: jinja_env = jinja2.Environment(undefined=jinja2.StrictUndefined, **env_args) tojson_filter = jinja_env.filters.get("tojson") indent_filter = jinja_env.filters.get("indent") jinja_env.tests.update(JinjaTest.salt_jinja_tests) jinja_env.filters.update(JinjaFilter.salt_jinja_filters) if tojson_filter is not None: # Use the existing tojson filter, if present (jinja2 >= 2.9) jinja_env.filters["tojson"] = tojson_filter if salt.utils.jinja.JINJA_VERSION >= LooseVersion("2.11"): # Use the existing indent filter on Jinja versions where it's not broken jinja_env.filters["indent"] = indent_filter jinja_env.globals.update(JinjaGlobal.salt_jinja_globals) # globals jinja_env.globals["odict"] = OrderedDict jinja_env.globals["show_full_context"] = salt.utils.jinja.show_full_context jinja_env.tests["list"] = salt.utils.data.is_list decoded_context = {} for key, value in six.iteritems(context): if not isinstance(value, six.string_types): decoded_context[key] = value continue try: decoded_context[key] = salt.utils.stringutils.to_unicode( value, encoding=SLS_ENCODING ) except UnicodeDecodeError as ex: log.debug( "Failed to decode using default encoding (%s), trying system encoding", SLS_ENCODING, ) decoded_context[key] = salt.utils.data.decode(value) try: template = jinja_env.from_string(tmplstr) template.globals.update(decoded_context) output = template.render(**decoded_context) except jinja2.exceptions.UndefinedError as exc: trace = traceback.extract_tb(sys.exc_info()[2]) out = _get_jinja_error(trace, context=decoded_context)[1] tmplstr = "" # Don't include the line number, since it is misreported # https://github.com/mitsuhiko/jinja2/issues/276 raise SaltRenderError("Jinja variable {0}{1}".format(exc, out), buf=tmplstr) except ( jinja2.exceptions.TemplateRuntimeError, jinja2.exceptions.TemplateSyntaxError, ) as exc: trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" raise SaltRenderError( "Jinja syntax error: {0}{1}".format(exc, out), line, tmplstr ) except (SaltInvocationError, CommandExecutionError) as exc: trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" raise SaltRenderError( "Problem running salt function in Jinja template: {0}{1}".format(exc, out), line, tmplstr, ) except Exception as exc: # pylint: disable=broad-except tracestr = traceback.format_exc() trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" else: tmplstr += "\n{0}".format(tracestr) log.debug("Jinja Error") log.debug("Exception:", exc_info=True) log.debug("Out: %s", out) log.debug("Line: %s", line) log.debug("TmplStr: %s", tmplstr) log.debug("TraceStr: %s", tracestr) raise SaltRenderError( "Jinja error: {0}{1}".format(exc, out), line, tmplstr, trace=tracestr ) # Workaround a bug in Jinja that removes the final newline # (https://github.com/mitsuhiko/jinja2/issues/75) if newline: output += newline return output # pylint: disable=3rd-party-module-not-gated def render_mako_tmpl(tmplstr, context, tmplpath=None): import mako.exceptions # pylint: disable=no-name-in-module from mako.template import Template # pylint: disable=no-name-in-module from salt.utils.mako import SaltMakoTemplateLookup saltenv = context["saltenv"] lookup = None if not saltenv: if tmplpath: # i.e., the template is from a file outside the state tree from mako.lookup import TemplateLookup # pylint: disable=no-name-in-module lookup = TemplateLookup(directories=[os.path.dirname(tmplpath)]) else: lookup = SaltMakoTemplateLookup( context["opts"], saltenv, pillar_rend=context.get("_pillar_rend", False) ) try: return Template( tmplstr, strict_undefined=True, uri=context["sls"].replace(".", "/") if "sls" in context else None, lookup=lookup, ).render(**context) except Exception: # pylint: disable=broad-except raise SaltRenderError(mako.exceptions.text_error_template().render()) def render_wempy_tmpl(tmplstr, context, tmplpath=None): from wemplate.wemplate import TemplateParser as Template return Template(tmplstr).render(**context) def render_genshi_tmpl(tmplstr, context, tmplpath=None): """ Render a Genshi template. A method should be passed in as part of the context. If no method is passed in, xml is assumed. Valid methods are: .. code-block: - xml - xhtml - html - text - newtext - oldtext Note that the ``text`` method will call ``NewTextTemplate``. If ``oldtext`` is desired, it must be called explicitly """ method = context.get("method", "xml") if method == "text" or method == "newtext": from genshi.template import NewTextTemplate # pylint: disable=no-name-in-module tmpl = NewTextTemplate(tmplstr) elif method == "oldtext": from genshi.template import OldTextTemplate # pylint: disable=no-name-in-module tmpl = OldTextTemplate(tmplstr) else: from genshi.template import MarkupTemplate # pylint: disable=no-name-in-module tmpl = MarkupTemplate(tmplstr) return tmpl.generate(**context).render(method) def render_cheetah_tmpl(tmplstr, context, tmplpath=None): """ Render a Cheetah template. """ from Cheetah.Template import Template # Compile the template and render it into the class tclass = Template.compile(tmplstr) data = tclass(namespaces=[context]) # Figure out which method to call based on the type of tmplstr if six.PY3 and isinstance(tmplstr, six.string_types): # This should call .__unicode__() res = str(data) elif six.PY2 and isinstance(tmplstr, six.text_type): # Expicitly call .__unicode__() res = data.__unicode__() elif isinstance(tmplstr, six.binary_type): # This should call .__str() res = str(data) else: raise SaltRenderError( "Unknown type {!s} for Cheetah template while trying to render.".format( type(tmplstr) ) ) # Now we can decode it to the correct encoding return salt.utils.data.decode(res) # pylint: enable=3rd-party-module-not-gated def py(sfn, string=False, **kwargs): # pylint: disable=C0103 """ Render a template from a python source file Returns:: {'result': bool, 'data': <Error data or rendered file path>} """ if not os.path.isfile(sfn): return {} base_fname = os.path.basename(sfn) name = base_fname.split(".")[0] if USE_IMPORTLIB: # pylint: disable=no-member loader = importlib.machinery.SourceFileLoader(name, sfn) spec = importlib.util.spec_from_file_location(name, sfn, loader=loader) if spec is None: raise ImportError() mod = importlib.util.module_from_spec(spec) spec.loader.exec_module(mod) # pylint: enable=no-member sys.modules[name] = mod else: mod = imp.load_source(name, sfn) # File templates need these set as __var__ if "__env__" not in kwargs and "saltenv" in kwargs: setattr(mod, "__env__", kwargs["saltenv"]) builtins = ["salt", "grains", "pillar", "opts"] for builtin in builtins: arg = "__{0}__".format(builtin) setattr(mod, arg, kwargs[builtin]) for kwarg in kwargs: setattr(mod, kwarg, kwargs[kwarg]) try: data = mod.run() if string: return {"result": True, "data": data} tgt = salt.utils.files.mkstemp() with salt.utils.files.fopen(tgt, "w+") as target: target.write(salt.utils.stringutils.to_str(data)) return {"result": True, "data": tgt} except Exception: # pylint: disable=broad-except trb = traceback.format_exc() return {"result": False, "data": trb} JINJA = wrap_tmpl_func(render_jinja_tmpl) MAKO = wrap_tmpl_func(render_mako_tmpl) WEMPY = wrap_tmpl_func(render_wempy_tmpl) GENSHI = wrap_tmpl_func(render_genshi_tmpl) CHEETAH = wrap_tmpl_func(render_cheetah_tmpl) TEMPLATE_REGISTRY = { "jinja": JINJA, "mako": MAKO, "py": py, "wempy": WEMPY, "genshi": GENSHI, "cheetah": CHEETAH, }

34.265176

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0.619068

from __future__ import absolute_import, print_function, unicode_literals import codecs import logging import os import sys import tempfile import traceback import jinja2 import jinja2.ext import salt.utils.data import salt.utils.dateutils import salt.utils.files import salt.utils.hashutils import salt.utils.http import salt.utils.jinja import salt.utils.network import salt.utils.platform import salt.utils.stringutils import salt.utils.yamlencoding from salt import __path__ as saltpath from salt.exceptions import CommandExecutionError, SaltInvocationError, SaltRenderError from salt.ext import six from salt.utils.decorators.jinja import JinjaFilter, JinjaGlobal, JinjaTest from salt.utils.odict import OrderedDict from salt.utils.versions import LooseVersion if sys.version_info[:2] >= (3, 5): import importlib.machinery import importlib.util USE_IMPORTLIB = True else: import imp USE_IMPORTLIB = False log = logging.getLogger(__name__) TEMPLATE_DIRNAME = os.path.join(saltpath[0], "templates") SLS_ENCODING = "utf-8" SLS_ENCODER = codecs.getencoder(SLS_ENCODING) class AliasedLoader(object): def __init__(self, wrapped): self.wrapped = wrapped def __getitem__(self, name): return self.wrapped[name] def __getattr__(self, name): return getattr(self.wrapped, name) def __contains__(self, name): return name in self.wrapped class AliasedModule(object): def __init__(self, wrapped, aliases): self.aliases = aliases self.wrapped = wrapped def __getattr__(self, name): return getattr(self.wrapped, name) def wrap_tmpl_func(render_str): def render_tmpl( tmplsrc, from_str=False, to_str=False, context=None, tmplpath=None, **kws ): if context is None: context = {} if "salt" in kws: kws["salt"] = AliasedLoader(kws["salt"]) kws.update(context) context = kws assert "opts" in context assert "saltenv" in context if "sls" in context: slspath = context["sls"].replace(".", "/") if tmplpath is not None: context["tplpath"] = tmplpath if not tmplpath.lower().replace("\\", "/").endswith("/init.sls"): slspath = os.path.dirname(slspath) template = tmplpath.replace("\\", "/") i = template.rfind(slspath.replace(".", "/")) if i != -1: template = template[i:] tpldir = os.path.dirname(template).replace("\\", "/") tpldata = { 'tplfile': template, 'tpldir': '.' if tpldir == '' else tpldir, 'tpldot': tpldir.replace('/', '.'), 'tplroot': tpldir.split('/')[0], } context.update(tpldata) context["slsdotpath"] = slspath.replace("/", ".") context["slscolonpath"] = slspath.replace("/", ":") context["sls_path"] = slspath.replace("/", "_") context["slspath"] = slspath if isinstance(tmplsrc, six.string_types): if from_str: tmplstr = tmplsrc else: try: if tmplpath is not None: tmplsrc = os.path.join(tmplpath, tmplsrc) with codecs.open(tmplsrc, "r", SLS_ENCODING) as _tmplsrc: tmplstr = _tmplsrc.read() except (UnicodeDecodeError, ValueError, OSError, IOError) as exc: if salt.utils.files.is_binary(tmplsrc): return dict(result=True, data=tmplsrc) log.error( "Exception occurred while reading file %s: %s", tmplsrc, exc, exc_info_on_loglevel=logging.DEBUG, ) six.reraise(*sys.exc_info()) else: tmplstr = tmplsrc.read() tmplsrc.close() try: output = render_str(tmplstr, context, tmplpath) if salt.utils.platform.is_windows(): newline = False if salt.utils.stringutils.to_unicode( output, encoding=SLS_ENCODING ).endswith(("\n", os.linesep)): newline = True output = os.linesep.join(output.splitlines()) if newline: output += os.linesep except SaltRenderError as exc: log.exception("Rendering exception occurred") raise except Exception: return dict(result=False, data=traceback.format_exc()) else: if to_str: return dict(result=True, data=output) with tempfile.NamedTemporaryFile( "wb", delete=False, prefix=salt.utils.files.TEMPFILE_PREFIX ) as outf: outf.write( salt.utils.stringutils.to_bytes(output, encoding=SLS_ENCODING) ) return dict(result=True, data=outf.name) render_tmpl.render_str = render_str return render_tmpl def _get_jinja_error_slug(tb_data): try: return [ x for x in tb_data if x[2] in ("top-level template code", "template", "<module>") ][-1] except IndexError: pass def _get_jinja_error_message(tb_data): try: line = _get_jinja_error_slug(tb_data) return "{0}({1}):\n{3}".format(*line) except IndexError: pass return None def _get_jinja_error_line(tb_data): try: return _get_jinja_error_slug(tb_data)[1] except IndexError: pass return None def _get_jinja_error(trace, context=None): if not context: context = {} out = "" error = _get_jinja_error_slug(trace) line = _get_jinja_error_line(trace) msg = _get_jinja_error_message(trace) add_log = False template_path = None if "sls" not in context: if (error[0] != "<unknown>") and os.path.exists(error[0]): template_path = error[0] add_log = True else: filen = context["sls"].replace(".", "/") if not error[0].endswith(filen) and os.path.exists(error[0]): add_log = True template_path = error[0] if add_log: if template_path: out = "\n{0}\n".format(msg.splitlines()[0]) with salt.utils.files.fopen(template_path) as fp_: template_contents = salt.utils.stringutils.to_unicode(fp_.read()) out += salt.utils.stringutils.get_context( template_contents, line, marker=" <======================" ) else: out = "\n{0}\n".format(msg) line = 0 return line, out def render_jinja_tmpl(tmplstr, context, tmplpath=None): opts = context["opts"] saltenv = context["saltenv"] loader = None newline = False if tmplstr and not isinstance(tmplstr, six.text_type): tmplstr = tmplstr.decode(SLS_ENCODING) if tmplstr.endswith(os.linesep): newline = os.linesep elif tmplstr.endswith("\n"): newline = "\n" if not saltenv: if tmplpath: loader = jinja2.FileSystemLoader(os.path.dirname(tmplpath)) else: loader = salt.utils.jinja.SaltCacheLoader( opts, saltenv, pillar_rend=context.get("_pillar_rend", False) ) env_args = {"extensions": [], "loader": loader} if hasattr(jinja2.ext, "with_"): env_args["extensions"].append("jinja2.ext.with_") if hasattr(jinja2.ext, "do"): env_args["extensions"].append("jinja2.ext.do") if hasattr(jinja2.ext, "loopcontrols"): env_args["extensions"].append("jinja2.ext.loopcontrols") env_args["extensions"].append(salt.utils.jinja.SerializerExtension) opt_jinja_env = opts.get("jinja_env", {}) opt_jinja_sls_env = opts.get("jinja_sls_env", {}) opt_jinja_env = opt_jinja_env if isinstance(opt_jinja_env, dict) else {} opt_jinja_sls_env = opt_jinja_sls_env if isinstance(opt_jinja_sls_env, dict) else {} if opts.get("jinja_trim_blocks", False): log.debug("Jinja2 trim_blocks is enabled") log.warning( "jinja_trim_blocks is deprecated and will be removed in a future release, please use jinja_env and/or jinja_sls_env instead" ) opt_jinja_env["trim_blocks"] = True opt_jinja_sls_env["trim_blocks"] = True if opts.get("jinja_lstrip_blocks", False): log.debug("Jinja2 lstrip_blocks is enabled") log.warning( "jinja_lstrip_blocks is deprecated and will be removed in a future release, please use jinja_env and/or jinja_sls_env instead" ) opt_jinja_env["lstrip_blocks"] = True opt_jinja_sls_env["lstrip_blocks"] = True def opt_jinja_env_helper(opts, optname): for k, v in six.iteritems(opts): k = k.lower() if hasattr(jinja2.defaults, k.upper()): log.debug("Jinja2 environment %s was set to %s by %s", k, v, optname) env_args[k] = v else: log.warning("Jinja2 environment %s is not recognized", k) if "sls" in context and context["sls"] != "": opt_jinja_env_helper(opt_jinja_sls_env, "jinja_sls_env") else: opt_jinja_env_helper(opt_jinja_env, "jinja_env") if opts.get("allow_undefined", False): jinja_env = jinja2.Environment(**env_args) else: jinja_env = jinja2.Environment(undefined=jinja2.StrictUndefined, **env_args) tojson_filter = jinja_env.filters.get("tojson") indent_filter = jinja_env.filters.get("indent") jinja_env.tests.update(JinjaTest.salt_jinja_tests) jinja_env.filters.update(JinjaFilter.salt_jinja_filters) if tojson_filter is not None: jinja_env.filters["tojson"] = tojson_filter if salt.utils.jinja.JINJA_VERSION >= LooseVersion("2.11"): jinja_env.filters["indent"] = indent_filter jinja_env.globals.update(JinjaGlobal.salt_jinja_globals) # globals jinja_env.globals["odict"] = OrderedDict jinja_env.globals["show_full_context"] = salt.utils.jinja.show_full_context jinja_env.tests["list"] = salt.utils.data.is_list decoded_context = {} for key, value in six.iteritems(context): if not isinstance(value, six.string_types): decoded_context[key] = value continue try: decoded_context[key] = salt.utils.stringutils.to_unicode( value, encoding=SLS_ENCODING ) except UnicodeDecodeError as ex: log.debug( "Failed to decode using default encoding (%s), trying system encoding", SLS_ENCODING, ) decoded_context[key] = salt.utils.data.decode(value) try: template = jinja_env.from_string(tmplstr) template.globals.update(decoded_context) output = template.render(**decoded_context) except jinja2.exceptions.UndefinedError as exc: trace = traceback.extract_tb(sys.exc_info()[2]) out = _get_jinja_error(trace, context=decoded_context)[1] tmplstr = "" # Don't include the line number, since it is misreported raise SaltRenderError("Jinja variable {0}{1}".format(exc, out), buf=tmplstr) except ( jinja2.exceptions.TemplateRuntimeError, jinja2.exceptions.TemplateSyntaxError, ) as exc: trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" raise SaltRenderError( "Jinja syntax error: {0}{1}".format(exc, out), line, tmplstr ) except (SaltInvocationError, CommandExecutionError) as exc: trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" raise SaltRenderError( "Problem running salt function in Jinja template: {0}{1}".format(exc, out), line, tmplstr, ) except Exception as exc: tracestr = traceback.format_exc() trace = traceback.extract_tb(sys.exc_info()[2]) line, out = _get_jinja_error(trace, context=decoded_context) if not line: tmplstr = "" else: tmplstr += "\n{0}".format(tracestr) log.debug("Jinja Error") log.debug("Exception:", exc_info=True) log.debug("Out: %s", out) log.debug("Line: %s", line) log.debug("TmplStr: %s", tmplstr) log.debug("TraceStr: %s", tracestr) raise SaltRenderError( "Jinja error: {0}{1}".format(exc, out), line, tmplstr, trace=tracestr ) if newline: output += newline return output def render_mako_tmpl(tmplstr, context, tmplpath=None): import mako.exceptions from mako.template import Template from salt.utils.mako import SaltMakoTemplateLookup saltenv = context["saltenv"] lookup = None if not saltenv: if tmplpath: from mako.lookup import TemplateLookup lookup = TemplateLookup(directories=[os.path.dirname(tmplpath)]) else: lookup = SaltMakoTemplateLookup( context["opts"], saltenv, pillar_rend=context.get("_pillar_rend", False) ) try: return Template( tmplstr, strict_undefined=True, uri=context["sls"].replace(".", "/") if "sls" in context else None, lookup=lookup, ).render(**context) except Exception: raise SaltRenderError(mako.exceptions.text_error_template().render()) def render_wempy_tmpl(tmplstr, context, tmplpath=None): from wemplate.wemplate import TemplateParser as Template return Template(tmplstr).render(**context) def render_genshi_tmpl(tmplstr, context, tmplpath=None): method = context.get("method", "xml") if method == "text" or method == "newtext": from genshi.template import NewTextTemplate tmpl = NewTextTemplate(tmplstr) elif method == "oldtext": from genshi.template import OldTextTemplate tmpl = OldTextTemplate(tmplstr) else: from genshi.template import MarkupTemplate tmpl = MarkupTemplate(tmplstr) return tmpl.generate(**context).render(method) def render_cheetah_tmpl(tmplstr, context, tmplpath=None): from Cheetah.Template import Template tclass = Template.compile(tmplstr) data = tclass(namespaces=[context]) if six.PY3 and isinstance(tmplstr, six.string_types): res = str(data) elif six.PY2 and isinstance(tmplstr, six.text_type): res = data.__unicode__() elif isinstance(tmplstr, six.binary_type): res = str(data) else: raise SaltRenderError( "Unknown type {!s} for Cheetah template while trying to render.".format( type(tmplstr) ) ) return salt.utils.data.decode(res) def py(sfn, string=False, **kwargs): if not os.path.isfile(sfn): return {} base_fname = os.path.basename(sfn) name = base_fname.split(".")[0] if USE_IMPORTLIB: loader = importlib.machinery.SourceFileLoader(name, sfn) spec = importlib.util.spec_from_file_location(name, sfn, loader=loader) if spec is None: raise ImportError() mod = importlib.util.module_from_spec(spec) spec.loader.exec_module(mod) sys.modules[name] = mod else: mod = imp.load_source(name, sfn) if "__env__" not in kwargs and "saltenv" in kwargs: setattr(mod, "__env__", kwargs["saltenv"]) builtins = ["salt", "grains", "pillar", "opts"] for builtin in builtins: arg = "__{0}__".format(builtin) setattr(mod, arg, kwargs[builtin]) for kwarg in kwargs: setattr(mod, kwarg, kwargs[kwarg]) try: data = mod.run() if string: return {"result": True, "data": data} tgt = salt.utils.files.mkstemp() with salt.utils.files.fopen(tgt, "w+") as target: target.write(salt.utils.stringutils.to_str(data)) return {"result": True, "data": tgt} except Exception: trb = traceback.format_exc() return {"result": False, "data": trb} JINJA = wrap_tmpl_func(render_jinja_tmpl) MAKO = wrap_tmpl_func(render_mako_tmpl) WEMPY = wrap_tmpl_func(render_wempy_tmpl) GENSHI = wrap_tmpl_func(render_genshi_tmpl) CHEETAH = wrap_tmpl_func(render_cheetah_tmpl) TEMPLATE_REGISTRY = { "jinja": JINJA, "mako": MAKO, "py": py, "wempy": WEMPY, "genshi": GENSHI, "cheetah": CHEETAH, }

true

f738f711c7c8087a0ebd860809e2161fd2425045

49,489

py

Python

test/backend/test_node.py

golunovas/onnx-tensorflow

b6340b3e66aa08af1ea4382e98257c2098177371

[ "Apache-2.0" ]

null

test/backend/test_node.py

golunovas/onnx-tensorflow

b6340b3e66aa08af1ea4382e98257c2098177371

[ "Apache-2.0" ]

null

test/backend/test_node.py

golunovas/onnx-tensorflow

b6340b3e66aa08af1ea4382e98257c2098177371

[ "Apache-2.0" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import math import unittest import numpy as np import tensorflow as tf from onnx_tf.backend import run_node from onnx_tf.common import supports_device from onnx_tf.common.legacy import legacy_onnx_pre_ver, legacy_opset_pre_ver from onnx import helper from onnx import TensorProto from onnx import defs class TestNode(unittest.TestCase): """ Tests for nodes """ def _get_rnd_float32(self, low=-1.0, high=1.0, shape=None): output = np.random.uniform(low, high, shape) if shape == None: return np.float32(output) else: return output.astype(np.float32) def _get_rnd_int(self, low, high=None, shape=None, dtype=np.int32): return np.random.randint(low, high, size=shape, dtype=dtype) def _elu(self, x): # f(x) = alpha * (exp(x) - 1.) for x < 0, # f(x) = x for x >= 0 if x < 0.: return np.expm1(x) return x def _leaky_relu(self, x, alpha): # f(x) = alpha * x for x < 0, # f(x) = x for x >= 0 if x < 0.: return alpha * x return x def test_abs(self): node_def = helper.make_node("Abs", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.abs(x)) def test_acosh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Acosh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Acosh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arccosh(x)) def test_add(self): node_def = helper.make_node("Add", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 10, 5, 5]) y = self._get_rnd_float32(shape=[10, 1, 1]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.add(x, y.reshape([1, 10, 1, 1]))) # node_def = helper.make_node("Add", ["A", "B"], ["C"], broadcast=1) # a = self._get_rnd([10, 10]) # b = self._get_rnd([10, 10]) # output = run_node(node_def, [a, b]) # np.testing.assert_almost_equal(output["C"], np.add(a, b)) # node_def = helper.make_node("Add", ["A", "B"], ["C"], broadcast=1) # a = self._get_rnd([10, 10]) # b = self._get_rnd([10,]) # output = run_node(node_def, [a, b]) # np.testing.assert_almost_equal(output["C"], np.add(a, b)) def test_arg_max(self): # TODO: need to fix this test return for axis in [0, 1]: node_def = helper.make_node( "ArgMax", ["data"], ["reduced"], axis=axis, keepdims=0) data = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [data]) np.testing.assert_almost_equal(output["reduced"], np.argmax(data, axis=axis)) def test_arg_min(self): # TODO: need to fix this test return for axis in [0, 1]: node_def = helper.make_node( "ArgMin", ["data"], ["reduced"], axis=axis, keepdims=0) data = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [data]) np.testing.assert_almost_equal(output["reduced"], np.argmin(data, axis=axis)) def test_asinh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Asinh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Asinh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arcsinh(x)) def test_atanh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Atanh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Atanh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arctanh(x)) def test_average_pool(self): # TODO: fix this test return device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) shape = [1, 1, 40, 40] node_def = helper.make_node( "AveragePool", ["X"], ["Y"], kernel_shape=[1, 2], pads=[1, 1], strides=[1, 1]) x = self._get_rnd_float32(shape=shape) output = run_node(node_def, [x], device=device) test_output = np.zeros(shape) for i1 in range(0, shape[0]): for i2 in range(0, shape[1]): for j1 in range(0, shape[2]): for j2 in range(0, shape[3]): test_output[i1][i2][j1][j2] = 0 count = 0 for k in range(j2, min(j2 + 2, shape[3])): test_output[i1][i2][j1][j2] += x[i1][i2][j1][k] count += 1 test_output[i1][i2][j1][j2] /= count np.testing.assert_almost_equal(output["Y"], test_output) def _batch_normalization(self, x, mean, variance, bias, scale, variance_epsilon): inv = np.reciprocal(np.sqrt(variance + variance_epsilon)) if scale is not None: inv *= scale return x * inv + (bias - mean * inv if bias is not None else -mean * inv) def test_batch_normalization(self): if legacy_opset_pre_ver(6): raise unittest.SkipTest("Backend doesn't support consumed flag") node_def = helper.make_node( "BatchNormalization", ["X", "scale", "bias", "mean", "var"], ["Y"], epsilon=0.001) x_shape = [3, 5, 4, 2] param_shape = [5] _param_shape = [1, 5, 1, 1] x = self._get_rnd_float32(0, 1, shape=x_shape) m = self._get_rnd_float32(0, 1, shape=param_shape) _m = m.reshape(_param_shape) v = self._get_rnd_float32(0, 1, shape=param_shape) _v = v.reshape(_param_shape) scale = self._get_rnd_float32(0, 1, shape=param_shape) _scale = scale.reshape(_param_shape) bias = self._get_rnd_float32(0, 1, shape=param_shape) _bias = bias.reshape(_param_shape) golden = self._batch_normalization(x, _m, _v, _bias, _scale, 0.001) output = run_node(node_def, [x, scale, bias, m, v]) np.testing.assert_almost_equal(output["Y"], golden, decimal=5) def test_cast(self): if legacy_onnx_pre_ver(1, 2) or legacy_opset_pre_ver(6): test_cases = [("FLOAT", tf.float32), ("UINT8", tf.uint8), ("INT8", tf.int8), ("UINT16", tf.uint16), ("INT16", tf.int16), ("INT32", tf.int32), ("INT64", tf.int64), ("BOOL", tf.bool), ("FLOAT16", tf.float16), ("DOUBLE", tf.float64), ("COMPLEX64", tf.complex64), ("COMPLEX128", tf.complex128)] else: test_cases = [(TensorProto.FLOAT, tf.float32), (TensorProto.UINT8, tf.uint8), (TensorProto.INT8, tf.int8), (TensorProto.UINT16, tf.uint16), (TensorProto.INT16, tf.int16), (TensorProto.INT32, tf.int32), (TensorProto.INT64, tf.int64), (TensorProto.BOOL, tf.bool), (TensorProto.FLOAT16, tf.float16), (TensorProto.DOUBLE, tf.float64), (TensorProto.COMPLEX64, tf.complex64), (TensorProto.COMPLEX128, tf.complex128)] if not legacy_opset_pre_ver(9): test_cases.append((TensorProto.STRING, tf.string)) for ty, tf_type in test_cases: node_def = helper.make_node("Cast", ["input"], ["output"], to=ty) vector = [2, 3] output = run_node(node_def, [vector]) np.testing.assert_equal(output["output"].dtype, tf_type) if not legacy_opset_pre_ver(9): test_cases2 = [(TensorProto.FLOAT, tf.float32), (TensorProto.INT32, tf.int32), (TensorProto.INT64, tf.int64), (TensorProto.DOUBLE, tf.float64)] for ty, tf_type in test_cases2: node_def = helper.make_node("Cast", ["input"], ["output"], to=ty) vector = ['2', '3'] output = run_node(node_def, [vector]) np.testing.assert_equal(output["output"].dtype, tf_type) def test_ceil(self): node_def = helper.make_node("Ceil", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.ceil(x)) def test_compress(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't support Compress.".format( defs.onnx_opset_version())) axis = 1 node_def = helper.make_node( "Compress", inputs=['X', 'condition'], outputs=['Y'], axis=axis) x = self._get_rnd_float32(shape=[5, 5, 5]) cond = np.array([1, 0, 1]) output = run_node(node_def, inputs=[x, cond]) np.testing.assert_almost_equal(output['Y'], np.compress(cond, x, axis=axis)) def test_concat(self): shape = [10, 20, 5] for axis in range(len(shape)): node_def = helper.make_node("Concat", ["X1", "X2"], ["Y"], axis=axis) x1 = self._get_rnd_float32(shape=shape) x2 = self._get_rnd_float32(shape=shape) output = run_node(node_def, [x1, x2]) np.testing.assert_almost_equal(output["Y"], np.concatenate((x1, x2), axis)) def test_constant(self): shape = [16, 16] values = np.random.randn(*shape).flatten().astype(float) const2_onnx = helper.make_tensor("const2", TensorProto.DOUBLE, shape, values) node_def = helper.make_node("Constant", [], ["Y"], value=const2_onnx) output = run_node(node_def, []) np.testing.assert_equal(output["Y"].shape, shape) np.testing.assert_almost_equal(output["Y"].flatten(), values) # test sparse tensor if not legacy_opset_pre_ver(11): expected = np.array([[1, 0, 0, 0], [0, 0, 2, 0], [0, 0, 0, 0]]) x = np.array([[0, 0], [1, 2]]).flatten().astype(np.int64) values = helper.make_tensor("values", TensorProto.INT32, [2], [1, 2]) indices = helper.make_tensor("indices", TensorProto.INT64, [2, 2], x) a = helper.make_sparse_tensor(values, indices,[3, 4]) node_def = helper.make_node("Constant", [], ["Y"], sparse_value=a) output = run_node(node_def, []) b = tf.sparse_to_dense(output["Y"].indices, output["Y"].dense_shape, output["Y"].values) result = b.eval(session=tf.Session()) np.testing.assert_equal(result, expected) def test_constant_fill(self): if not legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't support ConstantFill.".format( defs.onnx_opset_version())) shape = [1, 2, 3, 4] extra_shape = [5, 6] value = 3. node_def = helper.make_node( "ConstantFill", ["X"], ["Y"], value=value, extra_shape=extra_shape, dtype=1, ) x = self._get_rnd_float32(shape=shape) y = np.zeros(shape + extra_shape) y.fill(value) output = run_node(node_def, [x]) np.testing.assert_equal(output["Y"].dtype, tf.float32) np.testing.assert_equal(output["Y"], y) def test_constant_of_shape(self): if defs.onnx_opset_version() < 9: raise unittest.SkipTest( "ONNX version {} doesn't support ConstantOfShape.".format( defs.onnx_opset_version())) v = helper.make_tensor("value", TensorProto.FLOAT, [1], [1]) node_def = helper.make_node("ConstantOfShape", ["X"], ["Y"], value=v) x = np.array([4, 3, 2]) output = run_node(node_def, inputs=[x]) np.testing.assert_almost_equal(output["Y"], np.ones(x, dtype=np.float32)) v = helper.make_tensor("value", TensorProto.INT32, [1], [0]) node_def = helper.make_node("ConstantOfShape", ["X"], ["Y"], value=v) x = np.array([10, 6]) output = run_node(node_def, inputs=[x]) np.testing.assert_almost_equal(output["Y"], np.zeros(x, dtype=np.int32)) def test_conv(self): device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) N, C, H, W = 4, 3, 5, 5 x_shape = [N, C, H, W] K, kH, kW = 6, 3, 3 weight_shape = [K, C, kH, kW] node_def = helper.make_node( "Conv", ["X", "weights"], ["Y"], pads=[1, 1, 1, 1], kernel_shape=[kH, kW]) x = self._get_rnd_float32(shape=x_shape) weights = self._get_rnd_float32(shape=weight_shape) output = run_node(node_def, [x, weights], device=device) out_shape = [N, K, H, W] test_output = np.zeros(out_shape) for n in range(N): for c in range(C): for h in range(H): for w in range(W): for k in range(K): for kh in range(kH): for kw in range(kW): h_in_range = (h - kH // 2 + kh) < H and ( h - kH // 2 + kh) >= 0 w_in_range = (w - kW // 2 + kw) < W and ( w - kW // 2 + kw) >= 0 if h_in_range and w_in_range: test_output[n][k][h][w] += (x[n][c][h - kH // 2 + kh][ w - kW // 2 + kw] * weights[k][c][kh][kw]) np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_conv_transpose(self): # Fix test in the future. return device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) node_def = helper.make_node( "ConvTranspose", ["X", "weights"], ["Y"], pads=[1, 1]) x_shape = [1, 5, 4] x = self._get_rnd(x_shape) weight_shape = [5, 3, 2] weights = self._get_rnd_float32(shape=weight_shape) output = run_node(node_def, [x, weights], device=device) out_shape = [x_shape[0], weight_shape[1], x_shape[2]] test_output = np.zeros(out_shape) for b in range(0, x_shape[0]): for m in range(0, weight_shape[1]): for h in range(0, x_shape[2]): v = 0 for c in range(0, x_shape[1]): for k in range(h, min(h + weight_shape[2], x_shape[2])): v += x[b][c][k] * weights[c][m][k - h] test_output[b][m][h] = v np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_cosh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Cosh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Cosh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.cosh(x)) def test_depth_to_space(self): node_def = helper.make_node("DepthToSpace", ["X"], ["Y"], blocksize=2) x_shape = [1, 12, 1, 1] x = self._get_rnd_float32(shape=x_shape) output = run_node(node_def, [x]) x = np.transpose(x, (0, 2, 3, 1)) y = np.reshape(np.swapaxes(x.reshape(1, 1, 1, 2, 2, 3), 2, 3), (1, 2, 2, 3)) y = np.transpose(y, (0, 3, 1, 2)) np.testing.assert_almost_equal(output["Y"], y, decimal=5) def test_dequantize_linear(self): node_def = helper.make_node("DequantizeLinear", ["x", "x_scale", "x_zero_point"], ["y"]) for x, x_zero_point in [ [ self._get_rnd_int(-128, 127, [2, 6], np.int8), self._get_rnd_int(-128, 127, dtype=np.int8) ], [ self._get_rnd_int(0, 255, [2, 6], np.uint8), self._get_rnd_int(0, 255, dtype=np.uint8) ], [ self._get_rnd_int(-512, 512, [2, 6]), np.int32(0) ] ]: x_scale = self._get_rnd_float32(-10., 10) y = np.subtract(np.float32(x), np.float32(x_zero_point)) y = np.multiply(y, x_scale) output = run_node(node_def, [x, x_scale, x_zero_point]) np.testing.assert_almost_equal(output["y"], y) def test_div(self): node_def = helper.make_node("Div", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.divide(x, y)) def test_dropout(self): # Since current ONNX only support inference and # dropout at inference mode is a no-op, # therefore dropout is always a no-op operator # in ONNX. node_def = helper.make_node("Dropout", ["X"], ["Y"]) if legacy_opset_pre_ver(7): # at inference mode, is_test is always set to 1 node_def = helper.make_node("Dropout", ["X"], ["Y"], is_test=1) x = self._get_rnd_float32(shape=[3, 4, 5]) y = x output = run_node(node_def, [x]) np.testing.assert_equal(output["Y"], y) def test_dot(self): # this op is removed # remove this test in the future return node_def = helper.make_node("Dot", ["X", "Y"], ["Z"]) x = np.floor(self._get_rnd_float32(shape=[10, 10])) y = np.floor(self._get_rnd_float32(shape=[10, 10])) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.dot(x, y)) def test_elu(self): node_def = helper.make_node("Elu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) output = run_node(node_def, [x]) test_output = [self._elu(a) for a in x] np.testing.assert_almost_equal(output["Y"], test_output) def test_equal(self): node_def = helper.make_node("Equal", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 3, 3, 2]) y = self._get_rnd_float32(shape=[3, 3, 1]) output = run_node(node_def, [x, y]) np.testing.assert_equal(output["Z"], np.equal(x, np.reshape( y, [1, 3, 3, 1]))) def test_erf(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Erf.".format( defs.onnx_opset_version())) node_def = helper.make_node("Erf", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) exp_output = np.vectorize(math.erf)(x).astype(np.float32) np.testing.assert_almost_equal(output["Y"], exp_output) def test_exp(self): node_def = helper.make_node("Exp", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) x = x - 3.6 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.exp(x)) def test_eye_like(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support EyeLike.".format( defs.onnx_opset_version())) for shape in [[6, 10], [10, 6]]: for off_diagonal_offset in [-10, -6, -3, 0, 3, 6, 7, 10]: node_def = helper.make_node( "EyeLike", ['x'], ['y'], dtype=1, k=off_diagonal_offset) x = self._get_rnd_int(0, 100, shape=shape) y = np.eye(shape[0], shape[1], k=off_diagonal_offset, dtype=np.float32) output = run_node(node_def, [x]) np.testing.assert_equal(output['y'], y) def test_flatten(self): # If input tensor has shape (d_0, d_1, ... d_n) then the # output will have shape: # # (d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn) # # TODO: pass axis attribute which is supported in newer # versions of onnx node_def = helper.make_node("Flatten", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 2, 3, 4, 5]) output = run_node(node_def, [x]) # TODO: pass axis=3 and uncomment the line below # np.testing.assert_almost_equal(output["Y"], x.reshape([60, 20])) np.testing.assert_almost_equal(output["Y"], x.reshape([10, 120])) def test_gather(self): node_def = helper.make_node("Gather", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = [[0, 1], [1, 2]] output = run_node(node_def, [x, y]) test_output = np.zeros((2, 2, 10)) for i in range(0, 2): for j in range(0, 10): test_output[0][i][j] = x[i][j] for i in range(0, 2): for j in range(0, 10): test_output[1][i][j] = x[i + 1][j] np.testing.assert_almost_equal(output["Z"], test_output) def test_gemm(self): # Compute Y = alpha * A * B + beta * C node_def = helper.make_node( "Gemm", ["A", "B", "C"], ["Y"], transA=0, transB=0, alpha=1.0, beta=1.0) x = np.floor(self._get_rnd_float32(shape=[10, 10])) y = np.floor(self._get_rnd_float32(shape=[10, 10])) z = np.floor(self._get_rnd_float32(shape=[10, 10])) output = run_node(node_def, [x, y, z]) test_output = np.matmul(x, y) + z np.testing.assert_almost_equal(output["Y"], test_output) def test_global_average_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalAveragePool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): sum = 0 for j1 in range(0, 2): for j2 in range(0, 3): sum += x[i1][i2][j1][j2] test_output[i1][i2][0][0] = sum / 6. np.testing.assert_almost_equal(output["Y"], test_output) def test_image_sacler(self): # Input: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # Scale: (flout, default 1.0) the scale to apply # Bias: applied to each channel, same size as C # Output has same shape and type as input x = self._get_rnd_float32(shape=[1, 3, 224, 224]) #random distribution over [0,1), so add 0.1 scale = np.random.rand(1)[0] + 0.1 bias = np.random.rand(3) node_def = helper.make_node( "ImageScaler", ["X"], ["Y"], scale=scale, bias=bias) output = run_node(node_def, [x]) test_out = np.multiply(x, scale) test_out = np.transpose(test_out, [0, 2, 3, 1]) test_out = np.add(test_out, bias) test_out = np.transpose(test_out, [0, 3, 1, 2]) np.testing.assert_almost_equal(output["Y"], test_out) def test_is_inf(self): if legacy_opset_pre_ver(10): raise unittest.SkipTest("ONNX version {} doesn't support IsInf.".format( defs.onnx_opset_version())) input = np.array( [-1.2, np.nan, np.inf, 2.8, np.NINF, np.inf], dtype=np.float32) expected_output = { "node_def": np.isinf(input), "node_def_neg_false": np.isposinf(input), "node_def_pos_false": np.isneginf(input) } node_defs = { "node_def": helper.make_node("IsInf", ["X"], ["Y"]), "node_def_neg_false": helper.make_node("IsInf", ["X"], ["Y"], detect_negative=0), "node_def_pos_false": helper.make_node("IsInf", ["X"], ["Y"], detect_positive=0) } for key in node_defs: output = run_node(node_defs[key], [input]) np.testing.assert_equal(output["Y"], expected_output[key]) def test_isnan(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support IsNaN.".format( defs.onnx_opset_version())) node_def = helper.make_node("IsNaN", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 3]) x[0][1] = x[1][0] = x[2][2] = np.nan output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.isnan(x)) def test_global_lp_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalLpPool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): tmp = np.zeros([2, 3]) for j1 in range(0, 2): for j2 in range(0, 3): tmp[j1][j2] = x[i1][i2][j1][j2] test_output[i1][i2][0][0] = np.linalg.norm(tmp) np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_global_max_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalMaxPool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): max = x[i1][i2][0][0] for j1 in range(0, 2): for j2 in range(0, 3): if max < x[i1][i2][j1][j2]: max = x[i1][i2][j1][j2] test_output[i1][i2][0][0] = max np.testing.assert_almost_equal(output["Y"], test_output) def test_less(self): node_def = helper.make_node("Less", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 3, 3, 2]) y = self._get_rnd_float32(shape=[3, 3, 1]) output = run_node(node_def, [x, y]) np.testing.assert_equal(output["Z"], np.less(x, np.reshape(y, [1, 3, 3, 1]))) def test_lp_normalization(self): for ordr in range(1, 3): node_def = helper.make_node("LpNormalization", ["X"], ["Y"], p=ordr) x = self._get_rnd([2, 2, 3, 2]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], x / np.expand_dims(np.linalg.norm(x, axis=-1, ord=ordr), -1), rtol=1e-3) def test_l_r_n(self): # Each input value is divided by: # # (bias+(alpha/size)*sum(xi^2 for every xi in the local region))^beta alpha = 2.0 beta = 1.0 bias = 5.0 size = 3 node_def = helper.make_node( "LRN", ["X"], ["Y"], alpha=alpha, beta=beta, bias=bias, size=size) x = self._get_rnd_float32(shape=[10, 2, 10, 10]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 10, 2]) x = np.transpose(x, axes=[0, 2, 3, 1]) for i1 in range(0, 10): for i2 in range(0, 10): for j1 in range(0, 10): for j2 in range(0, 2): sqr_sum = 0. # size of 3 means radius 1 in TF speak # i.e. the immediate neighbouring values # if "previous" neighbour exists if j2 > 0: sqr_sum += x[i1][i2][j1][j2 - 1] * x[i1][i2][j1][j2 - 1] # current value sqr_sum += x[i1][i2][j1][j2] * x[i1][i2][j1][j2] # if "next" neighbour exists if j2 < 2 - 1: sqr_sum += x[i1][i2][j1][j2 + 1] * x[i1][i2][j1][j2 + 1] test_output[i1][i2][j1][j2] = \ x[i1][i2][j1][j2] / ((bias + (alpha * 1. / size) * sqr_sum) ** beta) test_output = np.transpose(test_output, axes=[0, 3, 1, 2]) np.testing.assert_almost_equal(output["Y"], test_output) def test_floor(self): node_def = helper.make_node("Floor", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.floor(x)) def test_leakyrelu(self): node_def = helper.make_node("LeakyRelu", ["X"], ["Y"], alpha=0.8) x = np.floor(self._get_rnd_float32(shape=[100])) output = run_node(node_def, [x]) test_output = [self._leaky_relu(a, 0.8) for a in x] np.testing.assert_almost_equal(output["Y"], test_output) def test_log(self): node_def = helper.make_node("Log", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) x = x + 3.6 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.log(x)) def test_max(self): node_def = helper.make_node("Max", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = np.maximum(np.maximum(np.maximum(x1, x2), x3), x4) np.testing.assert_almost_equal(output["Z"], test_output) def test_max_pool(self): return node_def = helper.make_node( "MaxPool", ["X"], ["Y"], dilations=[1, 1], kernel_shape=[1, 2], pads=[0, 0], strides=[1, 2]) x = self._get_rnd_float32(shape=[10, 10, 4, 4]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 4, 2]) for i1 in range(0, 10): for i2 in range(0, 10): for j1 in range(0, 4): for j2 in range(0, 2): test_output[i1][i2][j1][j2] = \ max(x[i1][i2][j1][2*j2], x[i1][i2][j1][2*j2 + 1]) np.testing.assert_almost_equal(output["Y"], test_output) def test_mean_variance_normalization(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't have test for MeanVarianceNormalization" .format(defs.onnx_opset_version())) input_data = self._get_rnd_float32(shape=[2,2,2,2]) # Calculate expected output data using formula: # (Input - Mean)/SD mean = np.mean(input_data, keepdims=1, axis=(0,2,3)) std = np.std(input_data, keepdims=1, axis=(0,2,3)) expected_output = (input_data - mean) / std # Testing without "axes" argument should default to axes=[0,2,3] node_def = helper.make_node("MeanVarianceNormalization", ["X"], ["Y"]) output = run_node(node_def, [input_data]) np.testing.assert_almost_equal(output["Y"], expected_output, decimal=5) def test_min(self): node_def = helper.make_node("Min", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = np.minimum(np.minimum(np.minimum(x1, x2), x3), x4) np.testing.assert_almost_equal(output["Z"], test_output) def test_mul(self): node_def = helper.make_node("Mul", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 10, 5, 5]) y = self._get_rnd_float32(shape=[10, 1, 1]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.multiply(x, y.reshape([1, 10, 1, 1]))) def test_mod(self): if legacy_opset_pre_ver(10): raise unittest.SkipTest("ONNX version {} doesn't support Mod.".format( defs.onnx_opset_version())) x = self._get_rnd_float32(shape=[5, 5]) y = self._get_rnd_float32(shape=[5, 5]) node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=0) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.mod(x, y)) node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=1) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.fmod(x, y)) def test_neg(self): node_def = helper.make_node("Neg", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.negative(x)) def test_non_zero(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support NonZero.".format( defs.onnx_opset_version())) node_def = helper.make_node("NonZero", ["x"], ["y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) y = np.array(np.nonzero(x)) output = run_node(node_def, [x]) np.testing.assert_equal(output["y"], y) def test_onehot(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support OneHot.".format( defs.onnx_opset_version())) indices = np.array([[0, 2], [1, 2], [0, 1]]) depth = np.int32(5) on_value = 6.0 off_value = 2.0 values = np.array([off_value, on_value]) node_def = helper.make_node( 'OneHot', inputs=['indices', 'depth', 'values'], outputs=['y'], axis=-1) y = (np.arange(depth) == indices[..., None]).astype(int) y = y * (on_value - off_value) + off_value output = run_node(node_def, inputs=[indices, depth, values]) np.testing.assert_equal(output['y'], y) def test_range(self): if legacy_opset_pre_ver(11): raise unittest.SkipTest("ONNX version {} doesn't support Range.".format( defs.onnx_opset_version())) node_def = helper.make_node( "Range", ['start', 'limit', 'delta'], ['y']) # test positive_delta start = self._get_rnd_int(low=0, high=3) limit = self._get_rnd_int(low=10, high=30) delta = np.int32(3) output = run_node(node_def, [start, limit, delta]) np.testing.assert_equal(output['y'], range(start, limit, delta)) # test negative_delta start = self._get_rnd_int(low=20, high=30) limit = self._get_rnd_int(low=1, high=5) delta = np.int32(-2) output = run_node(node_def, [start, limit, delta]) np.testing.assert_equal(output['y'], range(start, limit, delta)) def test_round(self): if legacy_opset_pre_ver(11): raise unittest.SkipTest("ONNX version {} doesn't support Round.".format( defs.onnx_opset_version())) node_def = helper.make_node("Round", ["X"], ["Y"]) x = self._get_rnd_float32(-20.0, 20.0, shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.round(x)) def test_relu(self): node_def = helper.make_node("Relu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.maximum(x, 0)) def test_pad(self): node_def = helper.make_node( "Pad", ["X"], ["Y"], mode="constant", pads=[1, 1, 1, 1], value=2.0) x = self._get_rnd_float32(shape=[100, 100]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.lib.pad( x, ((1, 1), (1, 1)), 'constant', constant_values=(2, 2))) def test_quantize_linear(self): node_def = helper.make_node("QuantizeLinear", ["x", "y_scale", "y_zero_point"], ["y"]) for x in [ self._get_rnd_float32(-512., 512., [2, 6]), self._get_rnd_int(-512, 512, [2, 6]) ]: y_scale = self._get_rnd_float32(-10., 10.) for y_zero_point in [ self._get_rnd_int(-128, 127, dtype=np.int8), self._get_rnd_int(0, 255, dtype=np.uint8) ]: y = np.divide(x, y_scale) y = np.round(y) y = np.add(y, y_zero_point) if y_zero_point.dtype.type is np.int8: y = np.clip(y, -128, 127).astype(np.int8) else: y = np.clip(y, 0, 255).astype(np.uint8) output = run_node(node_def, [x, y_scale, y_zero_point]) np.testing.assert_almost_equal(output["y"], y) def test_reciprocal(self): node_def = helper.make_node("Reciprocal", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], 1.0 / x) def test_reduce_l1(self): node_def = helper.make_node("ReduceL1", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.linalg.norm(x, 1, (1, 2), True)) def test_reduce_log_sum_exp(self): node_def = helper.make_node("ReduceLogSumExp", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.log(np.sum(np.exp(x), axis=(1, 2), keepdims=True)), rtol=1e-3) def test_reduce_max(self): node_def = helper.make_node("ReduceMax", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.max(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_mean(self): node_def = helper.make_node("ReduceMean", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.mean(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_min(self): node_def = helper.make_node("ReduceMin", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.min(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_prod(self): node_def = helper.make_node("ReduceProd", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[1, 5, 5, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.prod(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_sum(self): node_def = helper.make_node("ReduceSum", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.sum(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_sum_square(self): node_def = helper.make_node("ReduceSumSquare", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.sum(np.square(x), (1, 2), keepdims=True), rtol=1e-3) def test_pow(self): node_def = helper.make_node("Pow", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=1000) / 2.0 + 0.5 y = self._get_rnd_float32(shape=1000) / 2.0 + 0.5 output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.power(x, y)) def test_reshape(self): x = self._get_rnd_float32(shape=100) shape = [10, 10] if defs.onnx_opset_version() < 5: node_def = helper.make_node("Reshape", ["X"], ["Z"], shape=shape) output = run_node(node_def, [x]) else: node_def = helper.make_node("Reshape", ["X", "Y"], ["Z"]) output = run_node(node_def, [x, shape]) np.testing.assert_almost_equal(output["Z"], x.reshape([10, 10])) def test_reshape_with_copy(self): x = self._get_rnd_float32(shape=[10, 20 * 30]) shape = [0, 20, 30] if defs.onnx_opset_version() < 5: node_def = helper.make_node("Reshape", ["X"], ["Z"], shape=shape) output = run_node(node_def, [x]) else: node_def = helper.make_node("Reshape", ["X", "Y"], ["Z"]) output = run_node(node_def, [x, shape]) np.testing.assert_almost_equal(output["Z"], x.reshape([10, 20, 30])) def test_selu(self): node_def = helper.make_node("Selu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) alpha = 1.6732 gamma = 1.0507 x[x <= 0] = gamma * (alpha * np.exp(x[x <= 0]) - alpha) x[x > 0] = gamma * x[x > 0] np.testing.assert_allclose(output["Y"], x, rtol=1e-3, atol=1e-7) def test_shape(self): node_def = helper.make_node("Shape", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose(output["Y"], np.shape(x)) def test_shrink(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Shrink.".format( defs.onnx_opset_version())) node_def = helper.make_node("Shrink", ["X"], ["Y"], bias=1.5, lambd=1.5) X = np.arange(-2.0, 2.1, dtype=np.float32) Y = np.array([-0.5, 0, 0, 0, 0.5], dtype=np.float32) output = run_node(node_def, [X]) np.testing.assert_almost_equal(output["Y"], Y) def test_sigmoid(self): node_def = helper.make_node("Sigmoid", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], 1 / (1 + np.exp(-x))) def test_sign(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Sign.".format( defs.onnx_opset_version())) node_def = helper.make_node("Sign", ["X"], ["Y"]) x = self._get_rnd_float32(-10, 10, [3, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sign(x)) def test_sinh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Sinh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Sinh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sinh(x)) def test_size(self): node_def = helper.make_node("Size", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.size(x)) def test_slice(self): # test case 1 with normal inputs axes = [0, 1, 2] starts = [0, 0, 0] ends = [2, 2, 2] steps = [1, 1, 1] if legacy_opset_pre_ver(10): node_def = helper.make_node( "Slice", ["X"], ["S"], axes=axes, starts=starts, ends=ends) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["S"], x[0:2, 0:2, 0:2]) else: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes", "steps"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes, steps]) np.testing.assert_almost_equal(output["S"], x[0:2, 0:2, 0:2]) # test case 2 with negative, out-of-bound and default inputs axes = [0, 2] starts = [0, -7] ends = [-8, 20] if legacy_opset_pre_ver(10): node_def = helper.make_node( "Slice", ["X"], ["S"], axes=axes, starts=starts, ends=ends) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["S"], x[0:-8, :, -7:20]) else: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes]) np.testing.assert_almost_equal(output["S"], x[0:-8, :, -7:20]) # test case 3 with non-default steps axes = [0, 1, 2] starts = [0, 0, 0] ends = [2, 2, 2] steps = [2, -2, -1] if legacy_opset_pre_ver(10) == False: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes", "steps"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes, steps]) np.testing.assert_almost_equal(output["S"], x[0:2:2, 0:2:-2, 0:2:-1]) def test_softplus(self): node_def = helper.make_node("Softplus", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.log(np.exp(x) + 1)) def test_softsign(self): node_def = helper.make_node("Softsign", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], x / (1 + np.abs(x))) def test_space_to_depth(self): node_def = helper.make_node("SpaceToDepth", ["X"], ["Y"], blocksize=2) x_shape = [1, 3, 2, 2] x = self._get_rnd_float32(shape=x_shape) output = run_node(node_def, [x]) x = np.transpose(x, (0, 2, 3, 1)) y = np.reshape( np.swapaxes(x.reshape(1, 1, 1, 1, 1, 12), 2, 3), (1, 1, 1, 12)) y = np.transpose(y, (0, 3, 1, 2)) np.testing.assert_allclose(output["Y"], y, rtol=1e-3) def test_split(self): split = [3, 3, 4] node_def = helper.make_node( "Split", ["X"], ["Z%i" % i for i in range(len(split))], axis=0, split=split) x = self._get_rnd_float32(shape=[100]).reshape([10, 10]) output = run_node(node_def, [x]) for a, b in zip(list(output), np.split(x, np.cumsum(split))[:-1]): np.testing.assert_almost_equal(a, b) def test_sqrt(self): node_def = helper.make_node("Sqrt", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) + 1.0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sqrt(x), decimal=5) def test_squeeze(self): node_def = helper.make_node("Squeeze", ["X"], ["Y"], axes=[2]) x = np.array([[[0], [1], [2]]]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.squeeze(x, axis=2)) def test_sub(self): node_def = helper.make_node("Sub", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.subtract(x, y)) def test_sum(self): node_def = helper.make_node("Sum", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = x1 + x2 + x3 + x4 np.testing.assert_almost_equal(output["Z"], test_output) def test_tanh(self): node_def = helper.make_node("Tanh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) + 1.0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.tanh(x), decimal=5) def test_thresholded_relu(self): alpha = 2.0 node_def = helper.make_node( "ThresholdedRelu", ["X"], ["Y"], alpha=alpha) x = self._get_rnd_float32(-3.0, 3.0, [10]) y = np.clip(x, alpha, np.inf) y[y == alpha] = 0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], y) def test_tile(self): if legacy_onnx_pre_ver(1, 2): raise unittest.SkipTest( "The current version of ONNX does not record correctly the opset of Tile." ) node_def = helper.make_node("Tile", ["X1", "X2"], ["Z"]) x = self._get_rnd_float32(shape=[3, 5, 5, 3]) repeats = [1, 1, 2, 1] output = run_node(node_def, [x, repeats]) np.testing.assert_allclose(output["Z"], np.tile(x, repeats), rtol=1e-3) def test_transpose(self): node_def = helper.make_node("Transpose", ["X"], ["Y"], perm=[0, 2, 1]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.transpose(x, (0, 2, 1))) def test_topk(self): x = np.arange(15, dtype=np.float32).reshape(3, 5) values = np.array([[4, 3], [9, 8], [14, 13]], dtype=np.float32) indices = np.array([[4, 3], [4, 3], [4, 3]], dtype=np.int64) if legacy_opset_pre_ver(10): # for opset = 1 node_def = helper.make_node("TopK", ["x"], ["values", "indices"], k=2) output = run_node(node_def, [x]) elif legacy_opset_pre_ver(11): # for opset = 10 k = np.array([2], dtype=np.int64) node_def = helper.make_node("TopK", ["x", "k"], ["values", "indices"]) output = run_node(node_def, [x, k]) else: # for opset = 11 x = np.array([[3, 2, 5, 10, 7], [12, 15, 10, 7, 20], [21, 16, 5, 3, 6]], dtype=np.float32) values = np.array([[3, 2], [10, 7], [5, 3]], dtype=np.float32) indices = np.array([[0, 1], [2, 3], [2, 3]], dtype=np.int64) k = np.array([2], dtype=np.int64) node_def = helper.make_node( "TopK", ["x", "k"], ["values", "indices"], largest=0, sorted=0) output = run_node(node_def, [x, k]) np.testing.assert_almost_equal(output["values"], values) np.testing.assert_almost_equal(output["indices"], indices) def test_where(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Where.".format( defs.onnx_opset_version())) node_def = helper.make_node("Where", ["C", "X", "Y"], ["Z"]) c = np.array([[1, 0], [1, 1]], dtype=np.bool) x = np.array([[1, 2], [3, 4]], dtype=np.float32) y = np.array([[9, 8], [7, 6]], dtype=np.float32) output = run_node(node_def, [c, x, y]) np.testing.assert_almost_equal(output["Z"], np.where(c, x, y)) if __name__ == '__main__': unittest.main()

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from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import math import unittest import numpy as np import tensorflow as tf from onnx_tf.backend import run_node from onnx_tf.common import supports_device from onnx_tf.common.legacy import legacy_onnx_pre_ver, legacy_opset_pre_ver from onnx import helper from onnx import TensorProto from onnx import defs class TestNode(unittest.TestCase): def _get_rnd_float32(self, low=-1.0, high=1.0, shape=None): output = np.random.uniform(low, high, shape) if shape == None: return np.float32(output) else: return output.astype(np.float32) def _get_rnd_int(self, low, high=None, shape=None, dtype=np.int32): return np.random.randint(low, high, size=shape, dtype=dtype) def _elu(self, x): if x < 0.: return np.expm1(x) return x def _leaky_relu(self, x, alpha): if x < 0.: return alpha * x return x def test_abs(self): node_def = helper.make_node("Abs", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.abs(x)) def test_acosh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Acosh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Acosh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arccosh(x)) def test_add(self): node_def = helper.make_node("Add", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 10, 5, 5]) y = self._get_rnd_float32(shape=[10, 1, 1]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.add(x, y.reshape([1, 10, 1, 1]))) # node_def = helper.make_node("Add", ["A", "B"], ["C"], broadcast=1) # a = self._get_rnd([10, 10]) # b = self._get_rnd([10, 10]) # output = run_node(node_def, [a, b]) # np.testing.assert_almost_equal(output["C"], np.add(a, b)) # node_def = helper.make_node("Add", ["A", "B"], ["C"], broadcast=1) # a = self._get_rnd([10, 10]) # b = self._get_rnd([10,]) # output = run_node(node_def, [a, b]) # np.testing.assert_almost_equal(output["C"], np.add(a, b)) def test_arg_max(self): # TODO: need to fix this test return for axis in [0, 1]: node_def = helper.make_node( "ArgMax", ["data"], ["reduced"], axis=axis, keepdims=0) data = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [data]) np.testing.assert_almost_equal(output["reduced"], np.argmax(data, axis=axis)) def test_arg_min(self): # TODO: need to fix this test return for axis in [0, 1]: node_def = helper.make_node( "ArgMin", ["data"], ["reduced"], axis=axis, keepdims=0) data = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [data]) np.testing.assert_almost_equal(output["reduced"], np.argmin(data, axis=axis)) def test_asinh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Asinh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Asinh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arcsinh(x)) def test_atanh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Atanh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Atanh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.arctanh(x)) def test_average_pool(self): # TODO: fix this test return device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) shape = [1, 1, 40, 40] node_def = helper.make_node( "AveragePool", ["X"], ["Y"], kernel_shape=[1, 2], pads=[1, 1], strides=[1, 1]) x = self._get_rnd_float32(shape=shape) output = run_node(node_def, [x], device=device) test_output = np.zeros(shape) for i1 in range(0, shape[0]): for i2 in range(0, shape[1]): for j1 in range(0, shape[2]): for j2 in range(0, shape[3]): test_output[i1][i2][j1][j2] = 0 count = 0 for k in range(j2, min(j2 + 2, shape[3])): test_output[i1][i2][j1][j2] += x[i1][i2][j1][k] count += 1 test_output[i1][i2][j1][j2] /= count np.testing.assert_almost_equal(output["Y"], test_output) def _batch_normalization(self, x, mean, variance, bias, scale, variance_epsilon): inv = np.reciprocal(np.sqrt(variance + variance_epsilon)) if scale is not None: inv *= scale return x * inv + (bias - mean * inv if bias is not None else -mean * inv) def test_batch_normalization(self): if legacy_opset_pre_ver(6): raise unittest.SkipTest("Backend doesn't support consumed flag") node_def = helper.make_node( "BatchNormalization", ["X", "scale", "bias", "mean", "var"], ["Y"], epsilon=0.001) x_shape = [3, 5, 4, 2] param_shape = [5] _param_shape = [1, 5, 1, 1] x = self._get_rnd_float32(0, 1, shape=x_shape) m = self._get_rnd_float32(0, 1, shape=param_shape) _m = m.reshape(_param_shape) v = self._get_rnd_float32(0, 1, shape=param_shape) _v = v.reshape(_param_shape) scale = self._get_rnd_float32(0, 1, shape=param_shape) _scale = scale.reshape(_param_shape) bias = self._get_rnd_float32(0, 1, shape=param_shape) _bias = bias.reshape(_param_shape) golden = self._batch_normalization(x, _m, _v, _bias, _scale, 0.001) output = run_node(node_def, [x, scale, bias, m, v]) np.testing.assert_almost_equal(output["Y"], golden, decimal=5) def test_cast(self): if legacy_onnx_pre_ver(1, 2) or legacy_opset_pre_ver(6): test_cases = [("FLOAT", tf.float32), ("UINT8", tf.uint8), ("INT8", tf.int8), ("UINT16", tf.uint16), ("INT16", tf.int16), ("INT32", tf.int32), ("INT64", tf.int64), ("BOOL", tf.bool), ("FLOAT16", tf.float16), ("DOUBLE", tf.float64), ("COMPLEX64", tf.complex64), ("COMPLEX128", tf.complex128)] else: test_cases = [(TensorProto.FLOAT, tf.float32), (TensorProto.UINT8, tf.uint8), (TensorProto.INT8, tf.int8), (TensorProto.UINT16, tf.uint16), (TensorProto.INT16, tf.int16), (TensorProto.INT32, tf.int32), (TensorProto.INT64, tf.int64), (TensorProto.BOOL, tf.bool), (TensorProto.FLOAT16, tf.float16), (TensorProto.DOUBLE, tf.float64), (TensorProto.COMPLEX64, tf.complex64), (TensorProto.COMPLEX128, tf.complex128)] if not legacy_opset_pre_ver(9): test_cases.append((TensorProto.STRING, tf.string)) for ty, tf_type in test_cases: node_def = helper.make_node("Cast", ["input"], ["output"], to=ty) vector = [2, 3] output = run_node(node_def, [vector]) np.testing.assert_equal(output["output"].dtype, tf_type) if not legacy_opset_pre_ver(9): test_cases2 = [(TensorProto.FLOAT, tf.float32), (TensorProto.INT32, tf.int32), (TensorProto.INT64, tf.int64), (TensorProto.DOUBLE, tf.float64)] for ty, tf_type in test_cases2: node_def = helper.make_node("Cast", ["input"], ["output"], to=ty) vector = ['2', '3'] output = run_node(node_def, [vector]) np.testing.assert_equal(output["output"].dtype, tf_type) def test_ceil(self): node_def = helper.make_node("Ceil", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.ceil(x)) def test_compress(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't support Compress.".format( defs.onnx_opset_version())) axis = 1 node_def = helper.make_node( "Compress", inputs=['X', 'condition'], outputs=['Y'], axis=axis) x = self._get_rnd_float32(shape=[5, 5, 5]) cond = np.array([1, 0, 1]) output = run_node(node_def, inputs=[x, cond]) np.testing.assert_almost_equal(output['Y'], np.compress(cond, x, axis=axis)) def test_concat(self): shape = [10, 20, 5] for axis in range(len(shape)): node_def = helper.make_node("Concat", ["X1", "X2"], ["Y"], axis=axis) x1 = self._get_rnd_float32(shape=shape) x2 = self._get_rnd_float32(shape=shape) output = run_node(node_def, [x1, x2]) np.testing.assert_almost_equal(output["Y"], np.concatenate((x1, x2), axis)) def test_constant(self): shape = [16, 16] values = np.random.randn(*shape).flatten().astype(float) const2_onnx = helper.make_tensor("const2", TensorProto.DOUBLE, shape, values) node_def = helper.make_node("Constant", [], ["Y"], value=const2_onnx) output = run_node(node_def, []) np.testing.assert_equal(output["Y"].shape, shape) np.testing.assert_almost_equal(output["Y"].flatten(), values) if not legacy_opset_pre_ver(11): expected = np.array([[1, 0, 0, 0], [0, 0, 2, 0], [0, 0, 0, 0]]) x = np.array([[0, 0], [1, 2]]).flatten().astype(np.int64) values = helper.make_tensor("values", TensorProto.INT32, [2], [1, 2]) indices = helper.make_tensor("indices", TensorProto.INT64, [2, 2], x) a = helper.make_sparse_tensor(values, indices,[3, 4]) node_def = helper.make_node("Constant", [], ["Y"], sparse_value=a) output = run_node(node_def, []) b = tf.sparse_to_dense(output["Y"].indices, output["Y"].dense_shape, output["Y"].values) result = b.eval(session=tf.Session()) np.testing.assert_equal(result, expected) def test_constant_fill(self): if not legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't support ConstantFill.".format( defs.onnx_opset_version())) shape = [1, 2, 3, 4] extra_shape = [5, 6] value = 3. node_def = helper.make_node( "ConstantFill", ["X"], ["Y"], value=value, extra_shape=extra_shape, dtype=1, ) x = self._get_rnd_float32(shape=shape) y = np.zeros(shape + extra_shape) y.fill(value) output = run_node(node_def, [x]) np.testing.assert_equal(output["Y"].dtype, tf.float32) np.testing.assert_equal(output["Y"], y) def test_constant_of_shape(self): if defs.onnx_opset_version() < 9: raise unittest.SkipTest( "ONNX version {} doesn't support ConstantOfShape.".format( defs.onnx_opset_version())) v = helper.make_tensor("value", TensorProto.FLOAT, [1], [1]) node_def = helper.make_node("ConstantOfShape", ["X"], ["Y"], value=v) x = np.array([4, 3, 2]) output = run_node(node_def, inputs=[x]) np.testing.assert_almost_equal(output["Y"], np.ones(x, dtype=np.float32)) v = helper.make_tensor("value", TensorProto.INT32, [1], [0]) node_def = helper.make_node("ConstantOfShape", ["X"], ["Y"], value=v) x = np.array([10, 6]) output = run_node(node_def, inputs=[x]) np.testing.assert_almost_equal(output["Y"], np.zeros(x, dtype=np.int32)) def test_conv(self): device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) N, C, H, W = 4, 3, 5, 5 x_shape = [N, C, H, W] K, kH, kW = 6, 3, 3 weight_shape = [K, C, kH, kW] node_def = helper.make_node( "Conv", ["X", "weights"], ["Y"], pads=[1, 1, 1, 1], kernel_shape=[kH, kW]) x = self._get_rnd_float32(shape=x_shape) weights = self._get_rnd_float32(shape=weight_shape) output = run_node(node_def, [x, weights], device=device) out_shape = [N, K, H, W] test_output = np.zeros(out_shape) for n in range(N): for c in range(C): for h in range(H): for w in range(W): for k in range(K): for kh in range(kH): for kw in range(kW): h_in_range = (h - kH // 2 + kh) < H and ( h - kH // 2 + kh) >= 0 w_in_range = (w - kW // 2 + kw) < W and ( w - kW // 2 + kw) >= 0 if h_in_range and w_in_range: test_output[n][k][h][w] += (x[n][c][h - kH // 2 + kh][ w - kW // 2 + kw] * weights[k][c][kh][kw]) np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_conv_transpose(self): # Fix test in the future. return device = "CUDA" if not supports_device(device): raise unittest.SkipTest( "Backend doesn't support device {}".format(device)) node_def = helper.make_node( "ConvTranspose", ["X", "weights"], ["Y"], pads=[1, 1]) x_shape = [1, 5, 4] x = self._get_rnd(x_shape) weight_shape = [5, 3, 2] weights = self._get_rnd_float32(shape=weight_shape) output = run_node(node_def, [x, weights], device=device) out_shape = [x_shape[0], weight_shape[1], x_shape[2]] test_output = np.zeros(out_shape) for b in range(0, x_shape[0]): for m in range(0, weight_shape[1]): for h in range(0, x_shape[2]): v = 0 for c in range(0, x_shape[1]): for k in range(h, min(h + weight_shape[2], x_shape[2])): v += x[b][c][k] * weights[c][m][k - h] test_output[b][m][h] = v np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_cosh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Cosh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Cosh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.cosh(x)) def test_depth_to_space(self): node_def = helper.make_node("DepthToSpace", ["X"], ["Y"], blocksize=2) x_shape = [1, 12, 1, 1] x = self._get_rnd_float32(shape=x_shape) output = run_node(node_def, [x]) x = np.transpose(x, (0, 2, 3, 1)) y = np.reshape(np.swapaxes(x.reshape(1, 1, 1, 2, 2, 3), 2, 3), (1, 2, 2, 3)) y = np.transpose(y, (0, 3, 1, 2)) np.testing.assert_almost_equal(output["Y"], y, decimal=5) def test_dequantize_linear(self): node_def = helper.make_node("DequantizeLinear", ["x", "x_scale", "x_zero_point"], ["y"]) for x, x_zero_point in [ [ self._get_rnd_int(-128, 127, [2, 6], np.int8), self._get_rnd_int(-128, 127, dtype=np.int8) ], [ self._get_rnd_int(0, 255, [2, 6], np.uint8), self._get_rnd_int(0, 255, dtype=np.uint8) ], [ self._get_rnd_int(-512, 512, [2, 6]), np.int32(0) ] ]: x_scale = self._get_rnd_float32(-10., 10) y = np.subtract(np.float32(x), np.float32(x_zero_point)) y = np.multiply(y, x_scale) output = run_node(node_def, [x, x_scale, x_zero_point]) np.testing.assert_almost_equal(output["y"], y) def test_div(self): node_def = helper.make_node("Div", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.divide(x, y)) def test_dropout(self): # Since current ONNX only support inference and # dropout at inference mode is a no-op, # therefore dropout is always a no-op operator # in ONNX. node_def = helper.make_node("Dropout", ["X"], ["Y"]) if legacy_opset_pre_ver(7): # at inference mode, is_test is always set to 1 node_def = helper.make_node("Dropout", ["X"], ["Y"], is_test=1) x = self._get_rnd_float32(shape=[3, 4, 5]) y = x output = run_node(node_def, [x]) np.testing.assert_equal(output["Y"], y) def test_dot(self): # this op is removed # remove this test in the future return node_def = helper.make_node("Dot", ["X", "Y"], ["Z"]) x = np.floor(self._get_rnd_float32(shape=[10, 10])) y = np.floor(self._get_rnd_float32(shape=[10, 10])) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.dot(x, y)) def test_elu(self): node_def = helper.make_node("Elu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) output = run_node(node_def, [x]) test_output = [self._elu(a) for a in x] np.testing.assert_almost_equal(output["Y"], test_output) def test_equal(self): node_def = helper.make_node("Equal", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 3, 3, 2]) y = self._get_rnd_float32(shape=[3, 3, 1]) output = run_node(node_def, [x, y]) np.testing.assert_equal(output["Z"], np.equal(x, np.reshape( y, [1, 3, 3, 1]))) def test_erf(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Erf.".format( defs.onnx_opset_version())) node_def = helper.make_node("Erf", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) exp_output = np.vectorize(math.erf)(x).astype(np.float32) np.testing.assert_almost_equal(output["Y"], exp_output) def test_exp(self): node_def = helper.make_node("Exp", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) x = x - 3.6 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.exp(x)) def test_eye_like(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support EyeLike.".format( defs.onnx_opset_version())) for shape in [[6, 10], [10, 6]]: for off_diagonal_offset in [-10, -6, -3, 0, 3, 6, 7, 10]: node_def = helper.make_node( "EyeLike", ['x'], ['y'], dtype=1, k=off_diagonal_offset) x = self._get_rnd_int(0, 100, shape=shape) y = np.eye(shape[0], shape[1], k=off_diagonal_offset, dtype=np.float32) output = run_node(node_def, [x]) np.testing.assert_equal(output['y'], y) def test_flatten(self): # If input tensor has shape (d_0, d_1, ... d_n) then the # output will have shape: # # (d_0 X d_1 ... d_(axis-1), d_axis X d_(axis+1) ... X dn) # # TODO: pass axis attribute which is supported in newer # versions of onnx node_def = helper.make_node("Flatten", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 2, 3, 4, 5]) output = run_node(node_def, [x]) # TODO: pass axis=3 and uncomment the line below # np.testing.assert_almost_equal(output["Y"], x.reshape([60, 20])) np.testing.assert_almost_equal(output["Y"], x.reshape([10, 120])) def test_gather(self): node_def = helper.make_node("Gather", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = [[0, 1], [1, 2]] output = run_node(node_def, [x, y]) test_output = np.zeros((2, 2, 10)) for i in range(0, 2): for j in range(0, 10): test_output[0][i][j] = x[i][j] for i in range(0, 2): for j in range(0, 10): test_output[1][i][j] = x[i + 1][j] np.testing.assert_almost_equal(output["Z"], test_output) def test_gemm(self): # Compute Y = alpha * A * B + beta * C node_def = helper.make_node( "Gemm", ["A", "B", "C"], ["Y"], transA=0, transB=0, alpha=1.0, beta=1.0) x = np.floor(self._get_rnd_float32(shape=[10, 10])) y = np.floor(self._get_rnd_float32(shape=[10, 10])) z = np.floor(self._get_rnd_float32(shape=[10, 10])) output = run_node(node_def, [x, y, z]) test_output = np.matmul(x, y) + z np.testing.assert_almost_equal(output["Y"], test_output) def test_global_average_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalAveragePool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): sum = 0 for j1 in range(0, 2): for j2 in range(0, 3): sum += x[i1][i2][j1][j2] test_output[i1][i2][0][0] = sum / 6. np.testing.assert_almost_equal(output["Y"], test_output) def test_image_sacler(self): # Input: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # Scale: (flout, default 1.0) the scale to apply # Bias: applied to each channel, same size as C # Output has same shape and type as input x = self._get_rnd_float32(shape=[1, 3, 224, 224]) #random distribution over [0,1), so add 0.1 scale = np.random.rand(1)[0] + 0.1 bias = np.random.rand(3) node_def = helper.make_node( "ImageScaler", ["X"], ["Y"], scale=scale, bias=bias) output = run_node(node_def, [x]) test_out = np.multiply(x, scale) test_out = np.transpose(test_out, [0, 2, 3, 1]) test_out = np.add(test_out, bias) test_out = np.transpose(test_out, [0, 3, 1, 2]) np.testing.assert_almost_equal(output["Y"], test_out) def test_is_inf(self): if legacy_opset_pre_ver(10): raise unittest.SkipTest("ONNX version {} doesn't support IsInf.".format( defs.onnx_opset_version())) input = np.array( [-1.2, np.nan, np.inf, 2.8, np.NINF, np.inf], dtype=np.float32) expected_output = { "node_def": np.isinf(input), "node_def_neg_false": np.isposinf(input), "node_def_pos_false": np.isneginf(input) } node_defs = { "node_def": helper.make_node("IsInf", ["X"], ["Y"]), "node_def_neg_false": helper.make_node("IsInf", ["X"], ["Y"], detect_negative=0), "node_def_pos_false": helper.make_node("IsInf", ["X"], ["Y"], detect_positive=0) } for key in node_defs: output = run_node(node_defs[key], [input]) np.testing.assert_equal(output["Y"], expected_output[key]) def test_isnan(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support IsNaN.".format( defs.onnx_opset_version())) node_def = helper.make_node("IsNaN", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 3]) x[0][1] = x[1][0] = x[2][2] = np.nan output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.isnan(x)) def test_global_lp_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalLpPool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): tmp = np.zeros([2, 3]) for j1 in range(0, 2): for j2 in range(0, 3): tmp[j1][j2] = x[i1][i2][j1][j2] test_output[i1][i2][0][0] = np.linalg.norm(tmp) np.testing.assert_almost_equal(output["Y"], test_output, decimal=5) def test_global_max_pool(self): # Image case: (N x C x H x W), where N is the batch size, # C is the number of channels, and H and W are the height # and the width of the data # # Non-image case: (N x C x D1 x D2 ... Dn) # # Output data tensor from pooling across the input tensor. # Dimensions will be N x C x 1 x 1 node_def = helper.make_node("GlobalMaxPool", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[10, 10, 2, 3]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 1, 1]) for i1 in range(0, 10): for i2 in range(0, 10): max = x[i1][i2][0][0] for j1 in range(0, 2): for j2 in range(0, 3): if max < x[i1][i2][j1][j2]: max = x[i1][i2][j1][j2] test_output[i1][i2][0][0] = max np.testing.assert_almost_equal(output["Y"], test_output) def test_less(self): node_def = helper.make_node("Less", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 3, 3, 2]) y = self._get_rnd_float32(shape=[3, 3, 1]) output = run_node(node_def, [x, y]) np.testing.assert_equal(output["Z"], np.less(x, np.reshape(y, [1, 3, 3, 1]))) def test_lp_normalization(self): for ordr in range(1, 3): node_def = helper.make_node("LpNormalization", ["X"], ["Y"], p=ordr) x = self._get_rnd([2, 2, 3, 2]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], x / np.expand_dims(np.linalg.norm(x, axis=-1, ord=ordr), -1), rtol=1e-3) def test_l_r_n(self): # Each input value is divided by: # # (bias+(alpha/size)*sum(xi^2 for every xi in the local region))^beta alpha = 2.0 beta = 1.0 bias = 5.0 size = 3 node_def = helper.make_node( "LRN", ["X"], ["Y"], alpha=alpha, beta=beta, bias=bias, size=size) x = self._get_rnd_float32(shape=[10, 2, 10, 10]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 10, 2]) x = np.transpose(x, axes=[0, 2, 3, 1]) for i1 in range(0, 10): for i2 in range(0, 10): for j1 in range(0, 10): for j2 in range(0, 2): sqr_sum = 0. # size of 3 means radius 1 in TF speak # i.e. the immediate neighbouring values # if "previous" neighbour exists if j2 > 0: sqr_sum += x[i1][i2][j1][j2 - 1] * x[i1][i2][j1][j2 - 1] # current value sqr_sum += x[i1][i2][j1][j2] * x[i1][i2][j1][j2] # if "next" neighbour exists if j2 < 2 - 1: sqr_sum += x[i1][i2][j1][j2 + 1] * x[i1][i2][j1][j2 + 1] test_output[i1][i2][j1][j2] = \ x[i1][i2][j1][j2] / ((bias + (alpha * 1. / size) * sqr_sum) ** beta) test_output = np.transpose(test_output, axes=[0, 3, 1, 2]) np.testing.assert_almost_equal(output["Y"], test_output) def test_floor(self): node_def = helper.make_node("Floor", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.floor(x)) def test_leakyrelu(self): node_def = helper.make_node("LeakyRelu", ["X"], ["Y"], alpha=0.8) x = np.floor(self._get_rnd_float32(shape=[100])) output = run_node(node_def, [x]) test_output = [self._leaky_relu(a, 0.8) for a in x] np.testing.assert_almost_equal(output["Y"], test_output) def test_log(self): node_def = helper.make_node("Log", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[100]) x = x + 3.6 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.log(x)) def test_max(self): node_def = helper.make_node("Max", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = np.maximum(np.maximum(np.maximum(x1, x2), x3), x4) np.testing.assert_almost_equal(output["Z"], test_output) def test_max_pool(self): return node_def = helper.make_node( "MaxPool", ["X"], ["Y"], dilations=[1, 1], kernel_shape=[1, 2], pads=[0, 0], strides=[1, 2]) x = self._get_rnd_float32(shape=[10, 10, 4, 4]) output = run_node(node_def, [x]) test_output = np.zeros([10, 10, 4, 2]) for i1 in range(0, 10): for i2 in range(0, 10): for j1 in range(0, 4): for j2 in range(0, 2): test_output[i1][i2][j1][j2] = \ max(x[i1][i2][j1][2*j2], x[i1][i2][j1][2*j2 + 1]) np.testing.assert_almost_equal(output["Y"], test_output) def test_mean_variance_normalization(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest( "ONNX version {} doesn't have test for MeanVarianceNormalization" .format(defs.onnx_opset_version())) input_data = self._get_rnd_float32(shape=[2,2,2,2]) mean = np.mean(input_data, keepdims=1, axis=(0,2,3)) std = np.std(input_data, keepdims=1, axis=(0,2,3)) expected_output = (input_data - mean) / std node_def = helper.make_node("MeanVarianceNormalization", ["X"], ["Y"]) output = run_node(node_def, [input_data]) np.testing.assert_almost_equal(output["Y"], expected_output, decimal=5) def test_min(self): node_def = helper.make_node("Min", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = np.minimum(np.minimum(np.minimum(x1, x2), x3), x4) np.testing.assert_almost_equal(output["Z"], test_output) def test_mul(self): node_def = helper.make_node("Mul", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[5, 10, 5, 5]) y = self._get_rnd_float32(shape=[10, 1, 1]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.multiply(x, y.reshape([1, 10, 1, 1]))) def test_mod(self): if legacy_opset_pre_ver(10): raise unittest.SkipTest("ONNX version {} doesn't support Mod.".format( defs.onnx_opset_version())) x = self._get_rnd_float32(shape=[5, 5]) y = self._get_rnd_float32(shape=[5, 5]) node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=0) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.mod(x, y)) node_def = helper.make_node("Mod", ["X", "Y"], ["Z"], fmod=1) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.fmod(x, y)) def test_neg(self): node_def = helper.make_node("Neg", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.negative(x)) def test_non_zero(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support NonZero.".format( defs.onnx_opset_version())) node_def = helper.make_node("NonZero", ["x"], ["y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) y = np.array(np.nonzero(x)) output = run_node(node_def, [x]) np.testing.assert_equal(output["y"], y) def test_onehot(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support OneHot.".format( defs.onnx_opset_version())) indices = np.array([[0, 2], [1, 2], [0, 1]]) depth = np.int32(5) on_value = 6.0 off_value = 2.0 values = np.array([off_value, on_value]) node_def = helper.make_node( 'OneHot', inputs=['indices', 'depth', 'values'], outputs=['y'], axis=-1) y = (np.arange(depth) == indices[..., None]).astype(int) y = y * (on_value - off_value) + off_value output = run_node(node_def, inputs=[indices, depth, values]) np.testing.assert_equal(output['y'], y) def test_range(self): if legacy_opset_pre_ver(11): raise unittest.SkipTest("ONNX version {} doesn't support Range.".format( defs.onnx_opset_version())) node_def = helper.make_node( "Range", ['start', 'limit', 'delta'], ['y']) start = self._get_rnd_int(low=0, high=3) limit = self._get_rnd_int(low=10, high=30) delta = np.int32(3) output = run_node(node_def, [start, limit, delta]) np.testing.assert_equal(output['y'], range(start, limit, delta)) start = self._get_rnd_int(low=20, high=30) limit = self._get_rnd_int(low=1, high=5) delta = np.int32(-2) output = run_node(node_def, [start, limit, delta]) np.testing.assert_equal(output['y'], range(start, limit, delta)) def test_round(self): if legacy_opset_pre_ver(11): raise unittest.SkipTest("ONNX version {} doesn't support Round.".format( defs.onnx_opset_version())) node_def = helper.make_node("Round", ["X"], ["Y"]) x = self._get_rnd_float32(-20.0, 20.0, shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.round(x)) def test_relu(self): node_def = helper.make_node("Relu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.maximum(x, 0)) def test_pad(self): node_def = helper.make_node( "Pad", ["X"], ["Y"], mode="constant", pads=[1, 1, 1, 1], value=2.0) x = self._get_rnd_float32(shape=[100, 100]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.lib.pad( x, ((1, 1), (1, 1)), 'constant', constant_values=(2, 2))) def test_quantize_linear(self): node_def = helper.make_node("QuantizeLinear", ["x", "y_scale", "y_zero_point"], ["y"]) for x in [ self._get_rnd_float32(-512., 512., [2, 6]), self._get_rnd_int(-512, 512, [2, 6]) ]: y_scale = self._get_rnd_float32(-10., 10.) for y_zero_point in [ self._get_rnd_int(-128, 127, dtype=np.int8), self._get_rnd_int(0, 255, dtype=np.uint8) ]: y = np.divide(x, y_scale) y = np.round(y) y = np.add(y, y_zero_point) if y_zero_point.dtype.type is np.int8: y = np.clip(y, -128, 127).astype(np.int8) else: y = np.clip(y, 0, 255).astype(np.uint8) output = run_node(node_def, [x, y_scale, y_zero_point]) np.testing.assert_almost_equal(output["y"], y) def test_reciprocal(self): node_def = helper.make_node("Reciprocal", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], 1.0 / x) def test_reduce_l1(self): node_def = helper.make_node("ReduceL1", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.linalg.norm(x, 1, (1, 2), True)) def test_reduce_log_sum_exp(self): node_def = helper.make_node("ReduceLogSumExp", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.log(np.sum(np.exp(x), axis=(1, 2), keepdims=True)), rtol=1e-3) def test_reduce_max(self): node_def = helper.make_node("ReduceMax", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.max(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_mean(self): node_def = helper.make_node("ReduceMean", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.mean(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_min(self): node_def = helper.make_node("ReduceMin", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.min(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_prod(self): node_def = helper.make_node("ReduceProd", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[1, 5, 5, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.prod(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_sum(self): node_def = helper.make_node("ReduceSum", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.sum(x, (1, 2), keepdims=True), rtol=1e-3) def test_reduce_sum_square(self): node_def = helper.make_node("ReduceSumSquare", ["X"], ["Y"], axes=[1, 2]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose( output["Y"], np.sum(np.square(x), (1, 2), keepdims=True), rtol=1e-3) def test_pow(self): node_def = helper.make_node("Pow", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=1000) / 2.0 + 0.5 y = self._get_rnd_float32(shape=1000) / 2.0 + 0.5 output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.power(x, y)) def test_reshape(self): x = self._get_rnd_float32(shape=100) shape = [10, 10] if defs.onnx_opset_version() < 5: node_def = helper.make_node("Reshape", ["X"], ["Z"], shape=shape) output = run_node(node_def, [x]) else: node_def = helper.make_node("Reshape", ["X", "Y"], ["Z"]) output = run_node(node_def, [x, shape]) np.testing.assert_almost_equal(output["Z"], x.reshape([10, 10])) def test_reshape_with_copy(self): x = self._get_rnd_float32(shape=[10, 20 * 30]) shape = [0, 20, 30] if defs.onnx_opset_version() < 5: node_def = helper.make_node("Reshape", ["X"], ["Z"], shape=shape) output = run_node(node_def, [x]) else: node_def = helper.make_node("Reshape", ["X", "Y"], ["Z"]) output = run_node(node_def, [x, shape]) np.testing.assert_almost_equal(output["Z"], x.reshape([10, 20, 30])) def test_selu(self): node_def = helper.make_node("Selu", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) alpha = 1.6732 gamma = 1.0507 x[x <= 0] = gamma * (alpha * np.exp(x[x <= 0]) - alpha) x[x > 0] = gamma * x[x > 0] np.testing.assert_allclose(output["Y"], x, rtol=1e-3, atol=1e-7) def test_shape(self): node_def = helper.make_node("Shape", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_allclose(output["Y"], np.shape(x)) def test_shrink(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Shrink.".format( defs.onnx_opset_version())) node_def = helper.make_node("Shrink", ["X"], ["Y"], bias=1.5, lambd=1.5) X = np.arange(-2.0, 2.1, dtype=np.float32) Y = np.array([-0.5, 0, 0, 0, 0.5], dtype=np.float32) output = run_node(node_def, [X]) np.testing.assert_almost_equal(output["Y"], Y) def test_sigmoid(self): node_def = helper.make_node("Sigmoid", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], 1 / (1 + np.exp(-x))) def test_sign(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Sign.".format( defs.onnx_opset_version())) node_def = helper.make_node("Sign", ["X"], ["Y"]) x = self._get_rnd_float32(-10, 10, [3, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sign(x)) def test_sinh(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Sinh.".format( defs.onnx_opset_version())) node_def = helper.make_node("Sinh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sinh(x)) def test_size(self): node_def = helper.make_node("Size", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[5, 10, 10, 3]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.size(x)) def test_slice(self): axes = [0, 1, 2] starts = [0, 0, 0] ends = [2, 2, 2] steps = [1, 1, 1] if legacy_opset_pre_ver(10): node_def = helper.make_node( "Slice", ["X"], ["S"], axes=axes, starts=starts, ends=ends) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["S"], x[0:2, 0:2, 0:2]) else: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes", "steps"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes, steps]) np.testing.assert_almost_equal(output["S"], x[0:2, 0:2, 0:2]) axes = [0, 2] starts = [0, -7] ends = [-8, 20] if legacy_opset_pre_ver(10): node_def = helper.make_node( "Slice", ["X"], ["S"], axes=axes, starts=starts, ends=ends) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["S"], x[0:-8, :, -7:20]) else: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes]) np.testing.assert_almost_equal(output["S"], x[0:-8, :, -7:20]) axes = [0, 1, 2] starts = [0, 0, 0] ends = [2, 2, 2] steps = [2, -2, -1] if legacy_opset_pre_ver(10) == False: node_def = helper.make_node( "Slice", ["X", "starts", "ends", "axes", "steps"], ["S"]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x, starts, ends, axes, steps]) np.testing.assert_almost_equal(output["S"], x[0:2:2, 0:2:-2, 0:2:-1]) def test_softplus(self): node_def = helper.make_node("Softplus", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.log(np.exp(x) + 1)) def test_softsign(self): node_def = helper.make_node("Softsign", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[3, 4, 5]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], x / (1 + np.abs(x))) def test_space_to_depth(self): node_def = helper.make_node("SpaceToDepth", ["X"], ["Y"], blocksize=2) x_shape = [1, 3, 2, 2] x = self._get_rnd_float32(shape=x_shape) output = run_node(node_def, [x]) x = np.transpose(x, (0, 2, 3, 1)) y = np.reshape( np.swapaxes(x.reshape(1, 1, 1, 1, 1, 12), 2, 3), (1, 1, 1, 12)) y = np.transpose(y, (0, 3, 1, 2)) np.testing.assert_allclose(output["Y"], y, rtol=1e-3) def test_split(self): split = [3, 3, 4] node_def = helper.make_node( "Split", ["X"], ["Z%i" % i for i in range(len(split))], axis=0, split=split) x = self._get_rnd_float32(shape=[100]).reshape([10, 10]) output = run_node(node_def, [x]) for a, b in zip(list(output), np.split(x, np.cumsum(split))[:-1]): np.testing.assert_almost_equal(a, b) def test_sqrt(self): node_def = helper.make_node("Sqrt", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) + 1.0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.sqrt(x), decimal=5) def test_squeeze(self): node_def = helper.make_node("Squeeze", ["X"], ["Y"], axes=[2]) x = np.array([[[0], [1], [2]]]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.squeeze(x, axis=2)) def test_sub(self): node_def = helper.make_node("Sub", ["X", "Y"], ["Z"]) x = self._get_rnd_float32(shape=[10, 10]) y = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x, y]) np.testing.assert_almost_equal(output["Z"], np.subtract(x, y)) def test_sum(self): node_def = helper.make_node("Sum", ["X1", "X2", "X3", "X4"], ["Z"]) x1 = self._get_rnd_float32(shape=[10, 10]) x2 = self._get_rnd_float32(shape=[10, 10]) x3 = self._get_rnd_float32(shape=[10, 10]) x4 = self._get_rnd_float32(shape=[10, 10]) output = run_node(node_def, [x1, x2, x3, x4]) test_output = x1 + x2 + x3 + x4 np.testing.assert_almost_equal(output["Z"], test_output) def test_tanh(self): node_def = helper.make_node("Tanh", ["X"], ["Y"]) x = self._get_rnd_float32(shape=[1000]) + 1.0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.tanh(x), decimal=5) def test_thresholded_relu(self): alpha = 2.0 node_def = helper.make_node( "ThresholdedRelu", ["X"], ["Y"], alpha=alpha) x = self._get_rnd_float32(-3.0, 3.0, [10]) y = np.clip(x, alpha, np.inf) y[y == alpha] = 0 output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], y) def test_tile(self): if legacy_onnx_pre_ver(1, 2): raise unittest.SkipTest( "The current version of ONNX does not record correctly the opset of Tile." ) node_def = helper.make_node("Tile", ["X1", "X2"], ["Z"]) x = self._get_rnd_float32(shape=[3, 5, 5, 3]) repeats = [1, 1, 2, 1] output = run_node(node_def, [x, repeats]) np.testing.assert_allclose(output["Z"], np.tile(x, repeats), rtol=1e-3) def test_transpose(self): node_def = helper.make_node("Transpose", ["X"], ["Y"], perm=[0, 2, 1]) x = self._get_rnd_float32(shape=[1000]).reshape([10, 10, 10]) output = run_node(node_def, [x]) np.testing.assert_almost_equal(output["Y"], np.transpose(x, (0, 2, 1))) def test_topk(self): x = np.arange(15, dtype=np.float32).reshape(3, 5) values = np.array([[4, 3], [9, 8], [14, 13]], dtype=np.float32) indices = np.array([[4, 3], [4, 3], [4, 3]], dtype=np.int64) if legacy_opset_pre_ver(10): node_def = helper.make_node("TopK", ["x"], ["values", "indices"], k=2) output = run_node(node_def, [x]) elif legacy_opset_pre_ver(11): k = np.array([2], dtype=np.int64) node_def = helper.make_node("TopK", ["x", "k"], ["values", "indices"]) output = run_node(node_def, [x, k]) else: x = np.array([[3, 2, 5, 10, 7], [12, 15, 10, 7, 20], [21, 16, 5, 3, 6]], dtype=np.float32) values = np.array([[3, 2], [10, 7], [5, 3]], dtype=np.float32) indices = np.array([[0, 1], [2, 3], [2, 3]], dtype=np.int64) k = np.array([2], dtype=np.int64) node_def = helper.make_node( "TopK", ["x", "k"], ["values", "indices"], largest=0, sorted=0) output = run_node(node_def, [x, k]) np.testing.assert_almost_equal(output["values"], values) np.testing.assert_almost_equal(output["indices"], indices) def test_where(self): if legacy_opset_pre_ver(9): raise unittest.SkipTest("ONNX version {} doesn't support Where.".format( defs.onnx_opset_version())) node_def = helper.make_node("Where", ["C", "X", "Y"], ["Z"]) c = np.array([[1, 0], [1, 1]], dtype=np.bool) x = np.array([[1, 2], [3, 4]], dtype=np.float32) y = np.array([[9, 8], [7, 6]], dtype=np.float32) output = run_node(node_def, [c, x, y]) np.testing.assert_almost_equal(output["Z"], np.where(c, x, y)) if __name__ == '__main__': unittest.main()

true

f738f76413d33197ccb79eae071324cc3b4852b8

85

py

Python

django/django_fundamentals/django_intro/SemiRestfulTvShows/shows/apps.py

fatimaalheeh/python_stack

9ba84e6dc030a65494f105152a97f0a38aa2e4f3

[ "MIT" ]

1

2021-07-21T23:50:14.000Z

django/app/shows/apps.py

danieltorrescode/themoviedb

b963b15c2812a33ff707a8077e99106204efe023

[ "CNRI-Python" ]

26

2021-02-08T07:57:42.000Z

2022-03-01T02:07:58.000Z

django/app/shows/apps.py

danieltorrescode/themoviedb

b963b15c2812a33ff707a8077e99106204efe023

[ "CNRI-Python" ]

null

from django.apps import AppConfig class ShowsConfig(AppConfig): name = 'shows'

14.166667

33

0.741176

from django.apps import AppConfig class ShowsConfig(AppConfig): name = 'shows'

true

f738f7bdd36618d581b5ca730bc93d8921e26533

9,321

py

Python

src/lib/Bcfg2/Server/Reports/reports/templatetags/bcfg2_tags.py

espro/bcfg2

8470a15940309428d9286f2ef6372749dd14bddf

[ "mpich2" ]

null

src/lib/Bcfg2/Server/Reports/reports/templatetags/bcfg2_tags.py

espro/bcfg2

8470a15940309428d9286f2ef6372749dd14bddf

[ "mpich2" ]

null

src/lib/Bcfg2/Server/Reports/reports/templatetags/bcfg2_tags.py

espro/bcfg2

8470a15940309428d9286f2ef6372749dd14bddf

[ "mpich2" ]

null

from django import template from django.core.urlresolvers import resolve, reverse, Resolver404, NoReverseMatch from django.utils.encoding import smart_unicode, smart_str from datetime import datetime, timedelta from Bcfg2.Server.Reports.utils import filter_list register = template.Library() __PAGE_NAV_LIMITS__ = (10, 25, 50, 100) @register.inclusion_tag('widgets/page_bar.html', takes_context=True) def page_navigator(context): """ Creates paginated links. Expects the context to be a RequestContext and views.prepare_paginated_list() to have populated page information. """ fragment = dict() try: path = context['request'].META['PATH_INFO'] total_pages = int(context['total_pages']) records_per_page = int(context['records_per_page']) except KeyError: return fragment except ValueError: return fragment if total_pages < 2: return {} try: view, args, kwargs = resolve(path) current_page = int(kwargs.get('page_number',1)) fragment['current_page'] = current_page fragment['page_number'] = current_page fragment['total_pages'] = total_pages fragment['records_per_page'] = records_per_page if current_page > 1: kwargs['page_number'] = current_page - 1 fragment['prev_page'] = reverse(view, args=args, kwargs=kwargs) if current_page < total_pages: kwargs['page_number'] = current_page + 1 fragment['next_page'] = reverse(view, args=args, kwargs=kwargs) view_range = 5 if total_pages > view_range: pager_start = current_page - 2 pager_end = current_page + 2 if pager_start < 1: pager_end += (1 - pager_start) pager_start = 1 if pager_end > total_pages: pager_start -= (pager_end - total_pages) pager_end = total_pages else: pager_start = 1 pager_end = total_pages if pager_start > 1: kwargs['page_number'] = 1 fragment['first_page'] = reverse(view, args=args, kwargs=kwargs) if pager_end < total_pages: kwargs['page_number'] = total_pages fragment['last_page'] = reverse(view, args=args, kwargs=kwargs) pager = [] for page in range(pager_start, int(pager_end) + 1): kwargs['page_number'] = page pager.append( (page, reverse(view, args=args, kwargs=kwargs)) ) kwargs['page_number'] = 1 page_limits = [] for limit in __PAGE_NAV_LIMITS__: kwargs['page_limit'] = limit page_limits.append( (limit, reverse(view, args=args, kwargs=kwargs)) ) # resolver doesn't like this del kwargs['page_number'] del kwargs['page_limit'] page_limits.append( ('all', reverse(view, args=args, kwargs=kwargs) + "|all") ) fragment['pager'] = pager fragment['page_limits'] = page_limits except Resolver404: path = "404" except NoReverseMatch: nr = sys.exc_info()[1] path = "NoReverseMatch: %s" % nr except ValueError: path = "ValueError" #FIXME - Handle these fragment['path'] = path return fragment @register.inclusion_tag('widgets/filter_bar.html', takes_context=True) def filter_navigator(context): try: path = context['request'].META['PATH_INFO'] view, args, kwargs = resolve(path) # Strip any page limits and numbers if 'page_number' in kwargs: del kwargs['page_number'] if 'page_limit' in kwargs: del kwargs['page_limit'] filters = [] for filter in filter_list: if filter in kwargs: myargs = kwargs.copy() del myargs[filter] filters.append( (filter, reverse(view, args=args, kwargs=myargs) ) ) filters.sort(lambda x,y: cmp(x[0], y[0])) return { 'filters': filters } except (Resolver404, NoReverseMatch, ValueError, KeyError): pass return dict() def _subtract_or_na(mdict, x, y): """ Shortcut for build_metric_list """ try: return round(mdict[x] - mdict[y], 4) except: return "n/a" @register.filter def build_metric_list(mdict): """ Create a list of metric table entries Moving this here it simplify the view. Should really handle the case where these are missing... """ td_list = [] # parse td_list.append( _subtract_or_na(mdict, 'config_parse', 'config_download')) #probe td_list.append( _subtract_or_na(mdict, 'probe_upload', 'start')) #inventory td_list.append( _subtract_or_na(mdict, 'inventory', 'initialization')) #install td_list.append( _subtract_or_na(mdict, 'install', 'inventory')) #cfg download & parse td_list.append( _subtract_or_na(mdict, 'config_parse', 'probe_upload')) #total td_list.append( _subtract_or_na(mdict, 'finished', 'start')) return td_list @register.filter def isstale(timestamp, entry_max=None): """ Check for a stale timestamp Compares two timestamps and returns True if the difference is greater then 24 hours. """ if not entry_max: entry_max = datetime.now() return entry_max - timestamp > timedelta(hours=24) @register.filter def sort_interactions_by_name(value): """ Sort an interaction list by client name """ inters = list(value) inters.sort(lambda a,b: cmp(a.client.name, b.client.name)) return inters class AddUrlFilter(template.Node): def __init__(self, filter_name, filter_value): self.filter_name = filter_name self.filter_value = filter_value self.fallback_view = 'Bcfg2.Server.Reports.reports.views.render_history_view' def render(self, context): link = '#' try: path = context['request'].META['PATH_INFO'] view, args, kwargs = resolve(path) filter_value = self.filter_value.resolve(context, True) if filter_value: filter_name = smart_str(self.filter_name) filter_value = smart_unicode(filter_value) kwargs[filter_name] = filter_value # These two don't make sense if filter_name == 'server' and 'hostname' in kwargs: del kwargs['hostname'] elif filter_name == 'hostname' and 'server' in kwargs: del kwargs['server'] try: link = reverse(view, args=args, kwargs=kwargs) except NoReverseMatch: link = reverse(self.fallback_view, args=None, kwargs={ filter_name: filter_value }) except NoReverseMatch: rm = sys.exc_info()[1] raise rm except (Resolver404, ValueError): pass return link @register.tag def add_url_filter(parser, token): """ Return a url with the filter added to the current view. Takes a new filter and resolves the current view with the new filter applied. Resolves to Bcfg2.Server.Reports.reports.views.client_history by default. {% add_url_filter server=interaction.server %} """ try: tag_name, filter_pair = token.split_contents() filter_name, filter_value = filter_pair.split('=', 1) filter_name = filter_name.strip() filter_value = parser.compile_filter(filter_value) except ValueError: raise template.TemplateSyntaxError("%r tag requires exactly one argument" % token.contents.split()[0]) if not filter_name or not filter_value: raise template.TemplateSyntaxError("argument should be a filter=value pair") return AddUrlFilter(filter_name, filter_value) @register.filter def sortwell(value): """ Sorts a list(or evaluates queryset to list) of bad, extra, or modified items in the best way for presentation """ configItems = list(value) configItems.sort(lambda x,y: cmp(x.entry.name, y.entry.name)) configItems.sort(lambda x,y: cmp(x.entry.kind, y.entry.kind)) return configItems class MediaTag(template.Node): def __init__(self, filter_value): self.filter_value = filter_value def render(self, context): base = context['MEDIA_URL'] try: request = context['request'] try: base = request.environ['bcfg2.media_url'] except: if request.path != request.META['PATH_INFO']: offset = request.path.find(request.META['PATH_INFO']) if offset > 0: base = "%s/%s" % (request.path[:offset], \ context['MEDIA_URL'].strip('/')) except: pass return "%s/%s" % (base, self.filter_value) @register.tag def to_media_url(parser, token): """ Return a url relative to the media_url. {% to_media_url /bcfg2.css %} """ try: tag_name, filter_value = token.split_contents() filter_value = parser.compile_filter(filter_value) except ValueError: raise template.TemplateSyntaxError("%r tag requires exactly one argument" % token.contents.split()[0]) return MediaTag(filter_value)

33.649819

110

0.623216

from django import template from django.core.urlresolvers import resolve, reverse, Resolver404, NoReverseMatch from django.utils.encoding import smart_unicode, smart_str from datetime import datetime, timedelta from Bcfg2.Server.Reports.utils import filter_list register = template.Library() __PAGE_NAV_LIMITS__ = (10, 25, 50, 100) @register.inclusion_tag('widgets/page_bar.html', takes_context=True) def page_navigator(context): fragment = dict() try: path = context['request'].META['PATH_INFO'] total_pages = int(context['total_pages']) records_per_page = int(context['records_per_page']) except KeyError: return fragment except ValueError: return fragment if total_pages < 2: return {} try: view, args, kwargs = resolve(path) current_page = int(kwargs.get('page_number',1)) fragment['current_page'] = current_page fragment['page_number'] = current_page fragment['total_pages'] = total_pages fragment['records_per_page'] = records_per_page if current_page > 1: kwargs['page_number'] = current_page - 1 fragment['prev_page'] = reverse(view, args=args, kwargs=kwargs) if current_page < total_pages: kwargs['page_number'] = current_page + 1 fragment['next_page'] = reverse(view, args=args, kwargs=kwargs) view_range = 5 if total_pages > view_range: pager_start = current_page - 2 pager_end = current_page + 2 if pager_start < 1: pager_end += (1 - pager_start) pager_start = 1 if pager_end > total_pages: pager_start -= (pager_end - total_pages) pager_end = total_pages else: pager_start = 1 pager_end = total_pages if pager_start > 1: kwargs['page_number'] = 1 fragment['first_page'] = reverse(view, args=args, kwargs=kwargs) if pager_end < total_pages: kwargs['page_number'] = total_pages fragment['last_page'] = reverse(view, args=args, kwargs=kwargs) pager = [] for page in range(pager_start, int(pager_end) + 1): kwargs['page_number'] = page pager.append( (page, reverse(view, args=args, kwargs=kwargs)) ) kwargs['page_number'] = 1 page_limits = [] for limit in __PAGE_NAV_LIMITS__: kwargs['page_limit'] = limit page_limits.append( (limit, reverse(view, args=args, kwargs=kwargs)) ) del kwargs['page_number'] del kwargs['page_limit'] page_limits.append( ('all', reverse(view, args=args, kwargs=kwargs) + "|all") ) fragment['pager'] = pager fragment['page_limits'] = page_limits except Resolver404: path = "404" except NoReverseMatch: nr = sys.exc_info()[1] path = "NoReverseMatch: %s" % nr except ValueError: path = "ValueError" #FIXME - Handle these fragment['path'] = path return fragment @register.inclusion_tag('widgets/filter_bar.html', takes_context=True) def filter_navigator(context): try: path = context['request'].META['PATH_INFO'] view, args, kwargs = resolve(path) # Strip any page limits and numbers if 'page_number' in kwargs: del kwargs['page_number'] if 'page_limit' in kwargs: del kwargs['page_limit'] filters = [] for filter in filter_list: if filter in kwargs: myargs = kwargs.copy() del myargs[filter] filters.append( (filter, reverse(view, args=args, kwargs=myargs) ) ) filters.sort(lambda x,y: cmp(x[0], y[0])) return { 'filters': filters } except (Resolver404, NoReverseMatch, ValueError, KeyError): pass return dict() def _subtract_or_na(mdict, x, y): try: return round(mdict[x] - mdict[y], 4) except: return "n/a" @register.filter def build_metric_list(mdict): td_list = [] # parse td_list.append( _subtract_or_na(mdict, 'config_parse', 'config_download')) #probe td_list.append( _subtract_or_na(mdict, 'probe_upload', 'start')) #inventory td_list.append( _subtract_or_na(mdict, 'inventory', 'initialization')) #install td_list.append( _subtract_or_na(mdict, 'install', 'inventory')) #cfg download & parse td_list.append( _subtract_or_na(mdict, 'config_parse', 'probe_upload')) #total td_list.append( _subtract_or_na(mdict, 'finished', 'start')) return td_list @register.filter def isstale(timestamp, entry_max=None): if not entry_max: entry_max = datetime.now() return entry_max - timestamp > timedelta(hours=24) @register.filter def sort_interactions_by_name(value): inters = list(value) inters.sort(lambda a,b: cmp(a.client.name, b.client.name)) return inters class AddUrlFilter(template.Node): def __init__(self, filter_name, filter_value): self.filter_name = filter_name self.filter_value = filter_value self.fallback_view = 'Bcfg2.Server.Reports.reports.views.render_history_view' def render(self, context): link = ' try: path = context['request'].META['PATH_INFO'] view, args, kwargs = resolve(path) filter_value = self.filter_value.resolve(context, True) if filter_value: filter_name = smart_str(self.filter_name) filter_value = smart_unicode(filter_value) kwargs[filter_name] = filter_value # These two don't make sense if filter_name == 'server' and 'hostname' in kwargs: del kwargs['hostname'] elif filter_name == 'hostname' and 'server' in kwargs: del kwargs['server'] try: link = reverse(view, args=args, kwargs=kwargs) except NoReverseMatch: link = reverse(self.fallback_view, args=None, kwargs={ filter_name: filter_value }) except NoReverseMatch: rm = sys.exc_info()[1] raise rm except (Resolver404, ValueError): pass return link @register.tag def add_url_filter(parser, token): try: tag_name, filter_pair = token.split_contents() filter_name, filter_value = filter_pair.split('=', 1) filter_name = filter_name.strip() filter_value = parser.compile_filter(filter_value) except ValueError: raise template.TemplateSyntaxError("%r tag requires exactly one argument" % token.contents.split()[0]) if not filter_name or not filter_value: raise template.TemplateSyntaxError("argument should be a filter=value pair") return AddUrlFilter(filter_name, filter_value) @register.filter def sortwell(value): configItems = list(value) configItems.sort(lambda x,y: cmp(x.entry.name, y.entry.name)) configItems.sort(lambda x,y: cmp(x.entry.kind, y.entry.kind)) return configItems class MediaTag(template.Node): def __init__(self, filter_value): self.filter_value = filter_value def render(self, context): base = context['MEDIA_URL'] try: request = context['request'] try: base = request.environ['bcfg2.media_url'] except: if request.path != request.META['PATH_INFO']: offset = request.path.find(request.META['PATH_INFO']) if offset > 0: base = "%s/%s" % (request.path[:offset], \ context['MEDIA_URL'].strip('/')) except: pass return "%s/%s" % (base, self.filter_value) @register.tag def to_media_url(parser, token): try: tag_name, filter_value = token.split_contents() filter_value = parser.compile_filter(filter_value) except ValueError: raise template.TemplateSyntaxError("%r tag requires exactly one argument" % token.contents.split()[0]) return MediaTag(filter_value)

true

f738f8af0f2cf36e0effa21aab9241a41cb0ed9c

381

py

Python

cracking_the_coding_interview_qs/17.15/get_longest_composite_test.py

angelusualle/algorithms

86286a49db2a755bc57330cb455bcbd8241ea6be

[ "Apache-2.0" ]

null

cracking_the_coding_interview_qs/17.15/get_longest_composite_test.py

angelusualle/algorithms

86286a49db2a755bc57330cb455bcbd8241ea6be

[ "Apache-2.0" ]

null

cracking_the_coding_interview_qs/17.15/get_longest_composite_test.py

angelusualle/algorithms

86286a49db2a755bc57330cb455bcbd8241ea6be

[ "Apache-2.0" ]

null

import unittest from get_longest_composite import get_longest_composite class Test_Case_Get_Longest_Composite(unittest.TestCase): def test_get_longest_composite(self): self.assertEqual(get_longest_composite(['bobby', 'brosef', 'john', 'apple', 'seed', 'pear', 'punch', 'bottom', 'appleseeds', 'applejohn']), 'applejohn') if __name__ == '__main__': unittest.main()

42.333333

160

0.745407

import unittest from get_longest_composite import get_longest_composite class Test_Case_Get_Longest_Composite(unittest.TestCase): def test_get_longest_composite(self): self.assertEqual(get_longest_composite(['bobby', 'brosef', 'john', 'apple', 'seed', 'pear', 'punch', 'bottom', 'appleseeds', 'applejohn']), 'applejohn') if __name__ == '__main__': unittest.main()

true

f738f96e3c7e444aa88fd83fb171e57d9f3c193d

1,698

py

Python

Picture/Exbar.py

hashtagSELFIE/That-s-a-Wrap-

31c8b824742fee01c384eefa49f9f82d85518651

[ "MIT" ]

2

2018-11-30T04:13:04.000Z

2018-11-30T13:01:12.000Z

Picture/Exbar.py

hashtagSELFIE/That-s-a-Wrap-

31c8b824742fee01c384eefa49f9f82d85518651

[ "MIT" ]

1

2022-02-12T05:05:55.000Z

Picture/Exbar.py

hashtagSELFIE/That-s-a-Wrap-

31c8b824742fee01c384eefa49f9f82d85518651

[ "MIT" ]

1

2018-12-03T07:33:39.000Z

import pygal def picture(): """picture Bar""" line_chart = pygal.Bar() line_chart.title = 'Director (in %)' line_chart.x_labels = map(str, range(2002, 2013)) line_chart.add('Action',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Adventure',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('War',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Drama',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Science',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Family',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Thriller',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Crime',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Documentaries',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Animation',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Comedy',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Erotic',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Fantasy',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Musicals',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Romance',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Western',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.render_to_file('bar-chart.svg') picture()

70.75

95

0.570671

import pygal def picture(): line_chart = pygal.Bar() line_chart.title = 'Director (in %)' line_chart.x_labels = map(str, range(2002, 2013)) line_chart.add('Action',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Adventure',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('War',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Drama',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Science',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Family',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Thriller',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Crime',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Documentaries',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Animation',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Comedy',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Erotic',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.add('Fantasy',[None, None, 0, 16.6, 25, 31, 36.4, 45.5, 46.3, 42.8, 37.1]) line_chart.add('Musicals',[None, None, None, None, None, None, 0, 3.9, 10.8, 23.8, 35.3]) line_chart.add('Romance',[85.8, 84.6, 84.7, 74.5, 66, 58.6, 54.7, 44.8, 36.2, 26.6, 20.1]) line_chart.add('Western',[14.2, 15.4, 15.3, 8.9, 9, 10.4, 8.9, 5.8, 6.7, 6.8, 7.5]) line_chart.render_to_file('bar-chart.svg') picture()

true

f738f99974c4e4b13c1fb2b29395384be695d5c0

924

py

Python

pyalmondplus/cli.py

penright/pyalmondplus

f6f223eb650352a17f3ce536b2258bed139cf317

[ "Apache-2.0" ]

1

2018-08-05T04:28:58.000Z

pyalmondplus/cli.py

penright/pyalmondplus

f6f223eb650352a17f3ce536b2258bed139cf317

[ "Apache-2.0" ]

311

2018-08-04T08:09:03.000Z

2022-03-28T05:17:18.000Z

pyalmondplus/cli.py

penright/pyalmondplus

f6f223eb650352a17f3ce536b2258bed139cf317

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """Console script for pyalmondplus.""" import sys import time import click import pyalmondplus.api import threading import asyncio def do_commands(url, my_api): click.echo("Connecting to " + url) while True: value = click.prompt("What next: ") print("command is: " + value) if value == "stop": break elif value == "dl": my_api.get_device_list() print("Do command is stopped") my_api.stop() time.sleep(3) def api_start(url, my_api): print("Do commands 1") my_api.start() print("Connected to Almond+") @click.command() @click.option('--url', default='') def main(url): my_api = pyalmondplus.api.PyAlmondPlus(url) do_command = threading.Thread(target=do_commands, args=(url, my_api)) do_command.start() start_api = threading.Thread(target=api_start, args=(url, my_api)) start_api.start()

23.1

73

0.640693

import sys import time import click import pyalmondplus.api import threading import asyncio def do_commands(url, my_api): click.echo("Connecting to " + url) while True: value = click.prompt("What next: ") print("command is: " + value) if value == "stop": break elif value == "dl": my_api.get_device_list() print("Do command is stopped") my_api.stop() time.sleep(3) def api_start(url, my_api): print("Do commands 1") my_api.start() print("Connected to Almond+") @click.command() @click.option('--url', default='') def main(url): my_api = pyalmondplus.api.PyAlmondPlus(url) do_command = threading.Thread(target=do_commands, args=(url, my_api)) do_command.start() start_api = threading.Thread(target=api_start, args=(url, my_api)) start_api.start()

true

f738f9d16d50cf5b6e563ba2caffbc8115609b53

5,354

py

Python

tapas/models/tapas_classifier_model_utils.py

Martin36/tapas

c2578e8dfaa862ae0eaa3ae3ade6808c81200ddf

[ "Apache-2.0" ]

816

2020-03-31T15:15:56.000Z

2022-03-31T19:28:02.000Z

tapas/models/tapas_classifier_model_utils.py

Fgerald/tapas

2987658c3b65c5ab6e698d6c57823dc30d3d0f96

[ "Apache-2.0" ]

155

2020-05-02T15:45:42.000Z

2022-03-31T08:35:23.000Z

tapas/models/tapas_classifier_model_utils.py

Fgerald/tapas

2987658c3b65c5ab6e698d6c57823dc30d3d0f96

[ "Apache-2.0" ]

173

2020-05-01T02:39:38.000Z

2022-03-30T06:43:29.000Z

# coding=utf-8 # Copyright 2019 The Google AI Language Team 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. # Lint as: python3 """TAPAS BERT model utils for classification.""" from typing import Dict, Text, Tuple, Optional from tapas.models import segmented_tensor import tensorflow.compat.v1 as tf EPSILON_ZERO_DIVISION = 1e-10 CLOSE_ENOUGH_TO_LOG_ZERO = -10000.0 def classification_initializer(): """Classification layer initializer.""" return tf.truncated_normal_initializer(stddev=0.02) def extract_answer_from_features( features, use_answer_as_supervision ): """Extracts the answer, numeric_values, numeric_values_scale.""" if use_answer_as_supervision: answer = tf.squeeze(features["answer"], axis=[1]) numeric_values = features["numeric_values"] numeric_values_scale = features["numeric_values_scale"] else: answer = None numeric_values = None numeric_values_scale = None return answer, numeric_values, numeric_values_scale def compute_token_logits(output_layer, temperature, init_cell_selection_weights_to_zero): """Computes logits per token. Args: output_layer: <float>[batch_size, seq_length, hidden_dim] Output of the encoder layer. temperature: float Temperature for the Bernoulli distribution. init_cell_selection_weights_to_zero: Whether the initial weights should be set to 0. This ensures that all tokens have the same prior probability. Returns: <float>[batch_size, seq_length] Logits per token. """ hidden_size = output_layer.shape.as_list()[-1] output_weights = tf.get_variable( "output_weights", [hidden_size], initializer=tf.zeros_initializer() if init_cell_selection_weights_to_zero else classification_initializer()) output_bias = tf.get_variable( "output_bias", shape=(), initializer=tf.zeros_initializer()) logits = (tf.einsum("bsj,j->bs", output_layer, output_weights) + output_bias) / temperature return logits # TODO(eisenjulian): Move more methods from tapas_classifier_model def compute_column_logits(output_layer, cell_index, cell_mask, init_cell_selection_weights_to_zero, allow_empty_column_selection): """Computes logits for each column. Args: output_layer: <float>[batch_size, seq_length, hidden_dim] Output of the encoder layer. cell_index: segmented_tensor.IndexMap [batch_size, seq_length] Index that groups tokens into cells. cell_mask: <float>[batch_size, max_num_rows * max_num_cols] Input mask per cell, 1 for cells that exists in the example and 0 for padding. init_cell_selection_weights_to_zero: Whether the initial weights should be set to 0. This is also applied to column logits, as they are used to select the cells. This ensures that all columns have the same prior probability. allow_empty_column_selection: Allow to select no column. Returns: <float>[batch_size, max_num_cols] Logits per column. Logits will be set to a very low value (such that the probability is 0) for the special id 0 (which means "outside the table") or columns that do not apear in the table. """ hidden_size = output_layer.shape.as_list()[-1] column_output_weights = tf.get_variable( "column_output_weights", [hidden_size], initializer=tf.zeros_initializer() if init_cell_selection_weights_to_zero else classification_initializer()) column_output_bias = tf.get_variable( "column_output_bias", shape=(), initializer=tf.zeros_initializer()) token_logits = ( tf.einsum("bsj,j->bs", output_layer, column_output_weights) + column_output_bias) # Average the logits per cell and then per column. # Note that by linearity it doesn't matter if we do the averaging on the # embeddings or on the logits. For performance we do the projection first. # [batch_size, max_num_cols * max_num_rows] cell_logits, cell_logits_index = segmented_tensor.reduce_mean( token_logits, cell_index) column_index = cell_index.project_inner(cell_logits_index) # [batch_size, max_num_cols] column_logits, out_index = segmented_tensor.reduce_sum( cell_logits * cell_mask, column_index) cell_count, _ = segmented_tensor.reduce_sum(cell_mask, column_index) column_logits /= cell_count + EPSILON_ZERO_DIVISION # Mask columns that do not appear in the example. is_padding = tf.logical_and(cell_count < 0.5, tf.not_equal(out_index.indices, 0)) column_logits += CLOSE_ENOUGH_TO_LOG_ZERO * tf.cast(is_padding, tf.float32) if not allow_empty_column_selection: column_logits += CLOSE_ENOUGH_TO_LOG_ZERO * tf.cast( tf.equal(out_index.indices, 0), tf.float32) return column_logits

39.955224

79

0.734591

from typing import Dict, Text, Tuple, Optional from tapas.models import segmented_tensor import tensorflow.compat.v1 as tf EPSILON_ZERO_DIVISION = 1e-10 CLOSE_ENOUGH_TO_LOG_ZERO = -10000.0 def classification_initializer(): return tf.truncated_normal_initializer(stddev=0.02) def extract_answer_from_features( features, use_answer_as_supervision ): if use_answer_as_supervision: answer = tf.squeeze(features["answer"], axis=[1]) numeric_values = features["numeric_values"] numeric_values_scale = features["numeric_values_scale"] else: answer = None numeric_values = None numeric_values_scale = None return answer, numeric_values, numeric_values_scale def compute_token_logits(output_layer, temperature, init_cell_selection_weights_to_zero): hidden_size = output_layer.shape.as_list()[-1] output_weights = tf.get_variable( "output_weights", [hidden_size], initializer=tf.zeros_initializer() if init_cell_selection_weights_to_zero else classification_initializer()) output_bias = tf.get_variable( "output_bias", shape=(), initializer=tf.zeros_initializer()) logits = (tf.einsum("bsj,j->bs", output_layer, output_weights) + output_bias) / temperature return logits def compute_column_logits(output_layer, cell_index, cell_mask, init_cell_selection_weights_to_zero, allow_empty_column_selection): hidden_size = output_layer.shape.as_list()[-1] column_output_weights = tf.get_variable( "column_output_weights", [hidden_size], initializer=tf.zeros_initializer() if init_cell_selection_weights_to_zero else classification_initializer()) column_output_bias = tf.get_variable( "column_output_bias", shape=(), initializer=tf.zeros_initializer()) token_logits = ( tf.einsum("bsj,j->bs", output_layer, column_output_weights) + column_output_bias) # embeddings or on the logits. For performance we do the projection first. # [batch_size, max_num_cols * max_num_rows] cell_logits, cell_logits_index = segmented_tensor.reduce_mean( token_logits, cell_index) column_index = cell_index.project_inner(cell_logits_index) # [batch_size, max_num_cols] column_logits, out_index = segmented_tensor.reduce_sum( cell_logits * cell_mask, column_index) cell_count, _ = segmented_tensor.reduce_sum(cell_mask, column_index) column_logits /= cell_count + EPSILON_ZERO_DIVISION # Mask columns that do not appear in the example. is_padding = tf.logical_and(cell_count < 0.5, tf.not_equal(out_index.indices, 0)) column_logits += CLOSE_ENOUGH_TO_LOG_ZERO * tf.cast(is_padding, tf.float32) if not allow_empty_column_selection: column_logits += CLOSE_ENOUGH_TO_LOG_ZERO * tf.cast( tf.equal(out_index.indices, 0), tf.float32) return column_logits

true

f738f9df61c3fda0d35caee0b14e0e5a092dc611

942

py

Python

Tests/generate_report.py

avpreserve/interstitial

4ac1fa470670289350fe32227400b325a1f2a328

[ "BSD-3-Clause" ]

5

2015-11-06T18:00:11.000Z

2017-12-14T16:22:33.000Z

Tests/generate_report.py

avpreserve/interstitial

4ac1fa470670289350fe32227400b325a1f2a328

[ "BSD-3-Clause" ]

1

2021-02-09T18:03:10.000Z

Tests/generate_report.py

WeAreAVP/interstitial

4ac1fa470670289350fe32227400b325a1f2a328

[ "BSD-3-Clause" ]

null

# -*- coding: UTF-8 -*- # Interstitial Error Detector # Version 0.2, 2013-08-28 # Copyright (c) 2013 AudioVisual Preservation Solutions # All rights reserved. # Released under the Apache license, v. 2.0 # Created on Aug 12, 2014 # @author: Furqan Wasi <furqan@avpreserve.com> import shlex, subprocess, os # Constructor if os.name == 'posix': OsType = 'linux' elif os.name == 'nt': OsType = 'Windows' elif os.name == 'os2': OsType = 'check' command_html_report = 'coverage html --omit=../GUI/*,../Tests/*,../Config/Validation.py,../Core/CustomException.py,../Core/Debugger.py' if OsType == 'Windows': startupinfo = subprocess.STARTUPINFO() startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW process_response = subprocess.call(command_html_report, startupinfo=startupinfo) else: args = shlex.split(command_html_report) p = subprocess.Popen(args, stdout=subprocess.PIPE)

29.4375

136

0.685775

import shlex, subprocess, os if os.name == 'posix': OsType = 'linux' elif os.name == 'nt': OsType = 'Windows' elif os.name == 'os2': OsType = 'check' command_html_report = 'coverage html --omit=../GUI/*,../Tests/*,../Config/Validation.py,../Core/CustomException.py,../Core/Debugger.py' if OsType == 'Windows': startupinfo = subprocess.STARTUPINFO() startupinfo.dwFlags |= subprocess.STARTF_USESHOWWINDOW process_response = subprocess.call(command_html_report, startupinfo=startupinfo) else: args = shlex.split(command_html_report) p = subprocess.Popen(args, stdout=subprocess.PIPE)

true

f738fae13d36290b3bda56030bc913e1edc0187f

713

py

Python

full-problems/gameWithStrings.py

vikas-t/DS-Algo

ea654d1cad5374c824c52da9d3815a9546eb43fa

[ "Apache-2.0" ]

null

full-problems/gameWithStrings.py

vikas-t/DS-Algo

ea654d1cad5374c824c52da9d3815a9546eb43fa

[ "Apache-2.0" ]

null

full-problems/gameWithStrings.py

vikas-t/DS-Algo

ea654d1cad5374c824c52da9d3815a9546eb43fa

[ "Apache-2.0" ]

null

#!/usr/bin/python3 # https://practice.geeksforgeeks.org/problems/game-with-string/0 import heapq def sol(s, k): """ Keep decreasing the max frequency by 1 uptill k. We store the frequencies in a max heap to get the max each time """ f = [0]*26 for x in s: f[ord(x)-97] -= 1 # We store the negative of the frequencies heapq.heapify(f) # Make it a max heap while k and f: d = heapq.heappop(f) heapq.heappush(f, d+1) # Reduce the max frequency by 1 and k by 1 till k exists k-=1 res = 0 for x in f: res += x**2 # Return the result, we dont care for the '-' since its gets squared return res

24.586207

72

0.57784

import heapq def sol(s, k): f = [0]*26 for x in s: f[ord(x)-97] -= 1 heapq.heapify(f) while k and f: d = heapq.heappop(f) heapq.heappush(f, d+1) k-=1 res = 0 for x in f: res += x**2 return res

true

f738fb591d3e4da7bac480926eae3a268abc1135

37,282

py

Python

PythonAPI/carissma_project/lib/python3.5/site-packages/matplotlib/dviread.py

AbdulHoffmann/carla_carissma

8d382769ffa02a6c61a22c57160285505f5ff0a4

[ "MIT" ]

445

2019-01-26T13:50:26.000Z

2022-03-18T05:17:38.000Z

venv/lib/python3.7/site-packages/matplotlib/dviread.py

John1001Song/Big-Data-Robo-Adviser

9444dce96954c546333d5aecc92a06c3bfd19aa5

[ "MIT" ]

242

2019-01-29T15:48:27.000Z

2022-03-31T22:09:21.000Z

venv/lib/python3.7/site-packages/matplotlib/dviread.py

John1001Song/Big-Data-Robo-Adviser

9444dce96954c546333d5aecc92a06c3bfd19aa5

[ "MIT" ]

64

2018-04-25T08:51:57.000Z

2022-01-29T14:13:57.000Z

""" A module for reading dvi files output by TeX. Several limitations make this not (currently) useful as a general-purpose dvi preprocessor, but it is currently used by the pdf backend for processing usetex text. Interface:: with Dvi(filename, 72) as dvi: # iterate over pages: for page in dvi: w, h, d = page.width, page.height, page.descent for x, y, font, glyph, width in page.text: fontname = font.texname pointsize = font.size ... for x, y, height, width in page.boxes: ... """ from collections import namedtuple import enum from functools import lru_cache, partial, wraps import logging import os import re import struct import subprocess import textwrap import numpy as np from matplotlib import cbook, rcParams _log = logging.getLogger(__name__) # Many dvi related files are looked for by external processes, require # additional parsing, and are used many times per rendering, which is why they # are cached using lru_cache(). # Dvi is a bytecode format documented in # http://mirrors.ctan.org/systems/knuth/dist/texware/dvitype.web # http://texdoc.net/texmf-dist/doc/generic/knuth/texware/dvitype.pdf # # The file consists of a preamble, some number of pages, a postamble, # and a finale. Different opcodes are allowed in different contexts, # so the Dvi object has a parser state: # # pre: expecting the preamble # outer: between pages (followed by a page or the postamble, # also e.g. font definitions are allowed) # page: processing a page # post_post: state after the postamble (our current implementation # just stops reading) # finale: the finale (unimplemented in our current implementation) _dvistate = enum.Enum('DviState', 'pre outer inpage post_post finale') # The marks on a page consist of text and boxes. A page also has dimensions. Page = namedtuple('Page', 'text boxes height width descent') Text = namedtuple('Text', 'x y font glyph width') Box = namedtuple('Box', 'x y height width') # Opcode argument parsing # # Each of the following functions takes a Dvi object and delta, # which is the difference between the opcode and the minimum opcode # with the same meaning. Dvi opcodes often encode the number of # argument bytes in this delta. def _arg_raw(dvi, delta): """Return *delta* without reading anything more from the dvi file""" return delta def _arg(bytes, signed, dvi, _): """Read *bytes* bytes, returning the bytes interpreted as a signed integer if *signed* is true, unsigned otherwise.""" return dvi._arg(bytes, signed) def _arg_slen(dvi, delta): """Signed, length *delta* Read *delta* bytes, returning None if *delta* is zero, and the bytes interpreted as a signed integer otherwise.""" if delta == 0: return None return dvi._arg(delta, True) def _arg_slen1(dvi, delta): """Signed, length *delta*+1 Read *delta*+1 bytes, returning the bytes interpreted as signed.""" return dvi._arg(delta+1, True) def _arg_ulen1(dvi, delta): """Unsigned length *delta*+1 Read *delta*+1 bytes, returning the bytes interpreted as unsigned.""" return dvi._arg(delta+1, False) def _arg_olen1(dvi, delta): """Optionally signed, length *delta*+1 Read *delta*+1 bytes, returning the bytes interpreted as unsigned integer for 0<=*delta*<3 and signed if *delta*==3.""" return dvi._arg(delta + 1, delta == 3) _arg_mapping = dict(raw=_arg_raw, u1=partial(_arg, 1, False), u4=partial(_arg, 4, False), s4=partial(_arg, 4, True), slen=_arg_slen, olen1=_arg_olen1, slen1=_arg_slen1, ulen1=_arg_ulen1) def _dispatch(table, min, max=None, state=None, args=('raw',)): """Decorator for dispatch by opcode. Sets the values in *table* from *min* to *max* to this method, adds a check that the Dvi state matches *state* if not None, reads arguments from the file according to *args*. *table* the dispatch table to be filled in *min* minimum opcode for calling this function *max* maximum opcode for calling this function, None if only *min* is allowed *state* state of the Dvi object in which these opcodes are allowed *args* sequence of argument specifications: ``'raw'``: opcode minus minimum ``'u1'``: read one unsigned byte ``'u4'``: read four bytes, treat as an unsigned number ``'s4'``: read four bytes, treat as a signed number ``'slen'``: read (opcode - minimum) bytes, treat as signed ``'slen1'``: read (opcode - minimum + 1) bytes, treat as signed ``'ulen1'``: read (opcode - minimum + 1) bytes, treat as unsigned ``'olen1'``: read (opcode - minimum + 1) bytes, treat as unsigned if under four bytes, signed if four bytes """ def decorate(method): get_args = [_arg_mapping[x] for x in args] @wraps(method) def wrapper(self, byte): if state is not None and self.state != state: raise ValueError("state precondition failed") return method(self, *[f(self, byte-min) for f in get_args]) if max is None: table[min] = wrapper else: for i in range(min, max+1): assert table[i] is None table[i] = wrapper return wrapper return decorate class Dvi(object): """ A reader for a dvi ("device-independent") file, as produced by TeX. The current implementation can only iterate through pages in order, and does not even attempt to verify the postamble. This class can be used as a context manager to close the underlying file upon exit. Pages can be read via iteration. Here is an overly simple way to extract text without trying to detect whitespace:: >>> with matplotlib.dviread.Dvi('input.dvi', 72) as dvi: ... for page in dvi: ... print(''.join(chr(t.glyph) for t in page.text)) """ # dispatch table _dtable = [None] * 256 _dispatch = partial(_dispatch, _dtable) def __init__(self, filename, dpi): """ Read the data from the file named *filename* and convert TeX's internal units to units of *dpi* per inch. *dpi* only sets the units and does not limit the resolution. Use None to return TeX's internal units. """ _log.debug('Dvi: %s', filename) self.file = open(filename, 'rb') self.dpi = dpi self.fonts = {} self.state = _dvistate.pre self.baseline = self._get_baseline(filename) def _get_baseline(self, filename): if rcParams['text.latex.preview']: base, ext = os.path.splitext(filename) baseline_filename = base + ".baseline" if os.path.exists(baseline_filename): with open(baseline_filename, 'rb') as fd: l = fd.read().split() height, depth, width = l return float(depth) return None def __enter__(self): """ Context manager enter method, does nothing. """ return self def __exit__(self, etype, evalue, etrace): """ Context manager exit method, closes the underlying file if it is open. """ self.close() def __iter__(self): """ Iterate through the pages of the file. Yields ------ Page Details of all the text and box objects on the page. The Page tuple contains lists of Text and Box tuples and the page dimensions, and the Text and Box tuples contain coordinates transformed into a standard Cartesian coordinate system at the dpi value given when initializing. The coordinates are floating point numbers, but otherwise precision is not lost and coordinate values are not clipped to integers. """ while self._read(): yield self._output() def close(self): """ Close the underlying file if it is open. """ if not self.file.closed: self.file.close() def _output(self): """ Output the text and boxes belonging to the most recent page. page = dvi._output() """ minx, miny, maxx, maxy = np.inf, np.inf, -np.inf, -np.inf maxy_pure = -np.inf for elt in self.text + self.boxes: if isinstance(elt, Box): x, y, h, w = elt e = 0 # zero depth else: # glyph x, y, font, g, w = elt h, e = font._height_depth_of(g) minx = min(minx, x) miny = min(miny, y - h) maxx = max(maxx, x + w) maxy = max(maxy, y + e) maxy_pure = max(maxy_pure, y) if self.dpi is None: # special case for ease of debugging: output raw dvi coordinates return Page(text=self.text, boxes=self.boxes, width=maxx-minx, height=maxy_pure-miny, descent=maxy-maxy_pure) # convert from TeX's "scaled points" to dpi units d = self.dpi / (72.27 * 2**16) if self.baseline is None: descent = (maxy - maxy_pure) * d else: descent = self.baseline text = [Text((x-minx)*d, (maxy-y)*d - descent, f, g, w*d) for (x, y, f, g, w) in self.text] boxes = [Box((x-minx)*d, (maxy-y)*d - descent, h*d, w*d) for (x, y, h, w) in self.boxes] return Page(text=text, boxes=boxes, width=(maxx-minx)*d, height=(maxy_pure-miny)*d, descent=descent) def _read(self): """ Read one page from the file. Return True if successful, False if there were no more pages. """ while True: byte = self.file.read(1)[0] self._dtable[byte](self, byte) if byte == 140: # end of page return True if self.state is _dvistate.post_post: # end of file self.close() return False def _arg(self, nbytes, signed=False): """ Read and return an integer argument *nbytes* long. Signedness is determined by the *signed* keyword. """ str = self.file.read(nbytes) value = str[0] if signed and value >= 0x80: value = value - 0x100 for i in range(1, nbytes): value = 0x100*value + str[i] return value @_dispatch(min=0, max=127, state=_dvistate.inpage) def _set_char_immediate(self, char): self._put_char_real(char) self.h += self.fonts[self.f]._width_of(char) @_dispatch(min=128, max=131, state=_dvistate.inpage, args=('olen1',)) def _set_char(self, char): self._put_char_real(char) self.h += self.fonts[self.f]._width_of(char) @_dispatch(132, state=_dvistate.inpage, args=('s4', 's4')) def _set_rule(self, a, b): self._put_rule_real(a, b) self.h += b @_dispatch(min=133, max=136, state=_dvistate.inpage, args=('olen1',)) def _put_char(self, char): self._put_char_real(char) def _put_char_real(self, char): font = self.fonts[self.f] if font._vf is None: self.text.append(Text(self.h, self.v, font, char, font._width_of(char))) else: scale = font._scale for x, y, f, g, w in font._vf[char].text: newf = DviFont(scale=_mul2012(scale, f._scale), tfm=f._tfm, texname=f.texname, vf=f._vf) self.text.append(Text(self.h + _mul2012(x, scale), self.v + _mul2012(y, scale), newf, g, newf._width_of(g))) self.boxes.extend([Box(self.h + _mul2012(x, scale), self.v + _mul2012(y, scale), _mul2012(a, scale), _mul2012(b, scale)) for x, y, a, b in font._vf[char].boxes]) @_dispatch(137, state=_dvistate.inpage, args=('s4', 's4')) def _put_rule(self, a, b): self._put_rule_real(a, b) def _put_rule_real(self, a, b): if a > 0 and b > 0: self.boxes.append(Box(self.h, self.v, a, b)) @_dispatch(138) def _nop(self, _): pass @_dispatch(139, state=_dvistate.outer, args=('s4',)*11) def _bop(self, c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, p): self.state = _dvistate.inpage self.h, self.v, self.w, self.x, self.y, self.z = 0, 0, 0, 0, 0, 0 self.stack = [] self.text = [] # list of Text objects self.boxes = [] # list of Box objects @_dispatch(140, state=_dvistate.inpage) def _eop(self, _): self.state = _dvistate.outer del self.h, self.v, self.w, self.x, self.y, self.z, self.stack @_dispatch(141, state=_dvistate.inpage) def _push(self, _): self.stack.append((self.h, self.v, self.w, self.x, self.y, self.z)) @_dispatch(142, state=_dvistate.inpage) def _pop(self, _): self.h, self.v, self.w, self.x, self.y, self.z = self.stack.pop() @_dispatch(min=143, max=146, state=_dvistate.inpage, args=('slen1',)) def _right(self, b): self.h += b @_dispatch(min=147, max=151, state=_dvistate.inpage, args=('slen',)) def _right_w(self, new_w): if new_w is not None: self.w = new_w self.h += self.w @_dispatch(min=152, max=156, state=_dvistate.inpage, args=('slen',)) def _right_x(self, new_x): if new_x is not None: self.x = new_x self.h += self.x @_dispatch(min=157, max=160, state=_dvistate.inpage, args=('slen1',)) def _down(self, a): self.v += a @_dispatch(min=161, max=165, state=_dvistate.inpage, args=('slen',)) def _down_y(self, new_y): if new_y is not None: self.y = new_y self.v += self.y @_dispatch(min=166, max=170, state=_dvistate.inpage, args=('slen',)) def _down_z(self, new_z): if new_z is not None: self.z = new_z self.v += self.z @_dispatch(min=171, max=234, state=_dvistate.inpage) def _fnt_num_immediate(self, k): self.f = k @_dispatch(min=235, max=238, state=_dvistate.inpage, args=('olen1',)) def _fnt_num(self, new_f): self.f = new_f @_dispatch(min=239, max=242, args=('ulen1',)) def _xxx(self, datalen): special = self.file.read(datalen) _log.debug( 'Dvi._xxx: encountered special: %s', ''.join([chr(ch) if 32 <= ch < 127 else '<%02x>' % ch for ch in special])) @_dispatch(min=243, max=246, args=('olen1', 'u4', 'u4', 'u4', 'u1', 'u1')) def _fnt_def(self, k, c, s, d, a, l): self._fnt_def_real(k, c, s, d, a, l) def _fnt_def_real(self, k, c, s, d, a, l): n = self.file.read(a + l) fontname = n[-l:].decode('ascii') tfm = _tfmfile(fontname) if tfm is None: raise FileNotFoundError("missing font metrics file: %s" % fontname) if c != 0 and tfm.checksum != 0 and c != tfm.checksum: raise ValueError('tfm checksum mismatch: %s' % n) vf = _vffile(fontname) self.fonts[k] = DviFont(scale=s, tfm=tfm, texname=n, vf=vf) @_dispatch(247, state=_dvistate.pre, args=('u1', 'u4', 'u4', 'u4', 'u1')) def _pre(self, i, num, den, mag, k): comment = self.file.read(k) if i != 2: raise ValueError("Unknown dvi format %d" % i) if num != 25400000 or den != 7227 * 2**16: raise ValueError("nonstandard units in dvi file") # meaning: TeX always uses those exact values, so it # should be enough for us to support those # (There are 72.27 pt to an inch so 7227 pt = # 7227 * 2**16 sp to 100 in. The numerator is multiplied # by 10^5 to get units of 10**-7 meters.) if mag != 1000: raise ValueError("nonstandard magnification in dvi file") # meaning: LaTeX seems to frown on setting \mag, so # I think we can assume this is constant self.state = _dvistate.outer @_dispatch(248, state=_dvistate.outer) def _post(self, _): self.state = _dvistate.post_post # TODO: actually read the postamble and finale? # currently post_post just triggers closing the file @_dispatch(249) def _post_post(self, _): raise NotImplementedError @_dispatch(min=250, max=255) def _malformed(self, offset): raise ValueError("unknown command: byte %d", 250 + offset) class DviFont(object): """ Encapsulation of a font that a DVI file can refer to. This class holds a font's texname and size, supports comparison, and knows the widths of glyphs in the same units as the AFM file. There are also internal attributes (for use by dviread.py) that are *not* used for comparison. The size is in Adobe points (converted from TeX points). Parameters ---------- scale : float Factor by which the font is scaled from its natural size. tfm : Tfm TeX font metrics for this font texname : bytes Name of the font as used internally by TeX and friends, as an ASCII bytestring. This is usually very different from any external font names, and :class:`dviread.PsfontsMap` can be used to find the external name of the font. vf : Vf A TeX "virtual font" file, or None if this font is not virtual. Attributes ---------- texname : bytes size : float Size of the font in Adobe points, converted from the slightly smaller TeX points. widths : list Widths of glyphs in glyph-space units, typically 1/1000ths of the point size. """ __slots__ = ('texname', 'size', 'widths', '_scale', '_vf', '_tfm') def __init__(self, scale, tfm, texname, vf): if not isinstance(texname, bytes): raise ValueError("texname must be a bytestring, got %s" % type(texname)) self._scale, self._tfm, self.texname, self._vf = \ scale, tfm, texname, vf self.size = scale * (72.0 / (72.27 * 2**16)) try: nchars = max(tfm.width) + 1 except ValueError: nchars = 0 self.widths = [(1000*tfm.width.get(char, 0)) >> 20 for char in range(nchars)] def __eq__(self, other): return self.__class__ == other.__class__ and \ self.texname == other.texname and self.size == other.size def __ne__(self, other): return not self.__eq__(other) def _width_of(self, char): """ Width of char in dvi units. For internal use by dviread.py. """ width = self._tfm.width.get(char, None) if width is not None: return _mul2012(width, self._scale) _log.debug('No width for char %d in font %s.', char, self.texname) return 0 def _height_depth_of(self, char): """ Height and depth of char in dvi units. For internal use by dviread.py. """ result = [] for metric, name in ((self._tfm.height, "height"), (self._tfm.depth, "depth")): value = metric.get(char, None) if value is None: _log.debug('No %s for char %d in font %s', name, char, self.texname) result.append(0) else: result.append(_mul2012(value, self._scale)) return result class Vf(Dvi): """ A virtual font (\\*.vf file) containing subroutines for dvi files. Usage:: vf = Vf(filename) glyph = vf[code] glyph.text, glyph.boxes, glyph.width Parameters ---------- filename : string or bytestring Notes ----- The virtual font format is a derivative of dvi: http://mirrors.ctan.org/info/knuth/virtual-fonts This class reuses some of the machinery of `Dvi` but replaces the `_read` loop and dispatch mechanism. """ def __init__(self, filename): Dvi.__init__(self, filename, 0) try: self._first_font = None self._chars = {} self._read() finally: self.close() def __getitem__(self, code): return self._chars[code] def _read(self): """ Read one page from the file. Return True if successful, False if there were no more pages. """ packet_char, packet_ends = None, None packet_len, packet_width = None, None while True: byte = self.file.read(1)[0] # If we are in a packet, execute the dvi instructions if self.state is _dvistate.inpage: byte_at = self.file.tell()-1 if byte_at == packet_ends: self._finalize_packet(packet_char, packet_width) packet_len, packet_char, packet_width = None, None, None # fall through to out-of-packet code elif byte_at > packet_ends: raise ValueError("Packet length mismatch in vf file") else: if byte in (139, 140) or byte >= 243: raise ValueError( "Inappropriate opcode %d in vf file" % byte) Dvi._dtable[byte](self, byte) continue # We are outside a packet if byte < 242: # a short packet (length given by byte) packet_len = byte packet_char, packet_width = self._arg(1), self._arg(3) packet_ends = self._init_packet(byte) self.state = _dvistate.inpage elif byte == 242: # a long packet packet_len, packet_char, packet_width = \ [self._arg(x) for x in (4, 4, 4)] self._init_packet(packet_len) elif 243 <= byte <= 246: k = self._arg(byte - 242, byte == 246) c, s, d, a, l = [self._arg(x) for x in (4, 4, 4, 1, 1)] self._fnt_def_real(k, c, s, d, a, l) if self._first_font is None: self._first_font = k elif byte == 247: # preamble i, k = self._arg(1), self._arg(1) x = self.file.read(k) cs, ds = self._arg(4), self._arg(4) self._pre(i, x, cs, ds) elif byte == 248: # postamble (just some number of 248s) break else: raise ValueError("unknown vf opcode %d" % byte) def _init_packet(self, pl): if self.state != _dvistate.outer: raise ValueError("Misplaced packet in vf file") self.h, self.v, self.w, self.x, self.y, self.z = 0, 0, 0, 0, 0, 0 self.stack, self.text, self.boxes = [], [], [] self.f = self._first_font return self.file.tell() + pl def _finalize_packet(self, packet_char, packet_width): self._chars[packet_char] = Page( text=self.text, boxes=self.boxes, width=packet_width, height=None, descent=None) self.state = _dvistate.outer def _pre(self, i, x, cs, ds): if self.state is not _dvistate.pre: raise ValueError("pre command in middle of vf file") if i != 202: raise ValueError("Unknown vf format %d" % i) if len(x): _log.debug('vf file comment: %s', x) self.state = _dvistate.outer # cs = checksum, ds = design size def _fix2comp(num): """ Convert from two's complement to negative. """ assert 0 <= num < 2**32 if num & 2**31: return num - 2**32 else: return num def _mul2012(num1, num2): """ Multiply two numbers in 20.12 fixed point format. """ # Separated into a function because >> has surprising precedence return (num1*num2) >> 20 class Tfm(object): """ A TeX Font Metric file. This implementation covers only the bare minimum needed by the Dvi class. Parameters ---------- filename : string or bytestring Attributes ---------- checksum : int Used for verifying against the dvi file. design_size : int Design size of the font (unknown units) width, height, depth : dict Dimensions of each character, need to be scaled by the factor specified in the dvi file. These are dicts because indexing may not start from 0. """ __slots__ = ('checksum', 'design_size', 'width', 'height', 'depth') def __init__(self, filename): _log.debug('opening tfm file %s', filename) with open(filename, 'rb') as file: header1 = file.read(24) lh, bc, ec, nw, nh, nd = \ struct.unpack('!6H', header1[2:14]) _log.debug('lh=%d, bc=%d, ec=%d, nw=%d, nh=%d, nd=%d', lh, bc, ec, nw, nh, nd) header2 = file.read(4*lh) self.checksum, self.design_size = \ struct.unpack('!2I', header2[:8]) # there is also encoding information etc. char_info = file.read(4*(ec-bc+1)) widths = file.read(4*nw) heights = file.read(4*nh) depths = file.read(4*nd) self.width, self.height, self.depth = {}, {}, {} widths, heights, depths = \ [struct.unpack('!%dI' % (len(x)/4), x) for x in (widths, heights, depths)] for idx, char in enumerate(range(bc, ec+1)): byte0 = char_info[4*idx] byte1 = char_info[4*idx+1] self.width[char] = _fix2comp(widths[byte0]) self.height[char] = _fix2comp(heights[byte1 >> 4]) self.depth[char] = _fix2comp(depths[byte1 & 0xf]) PsFont = namedtuple('Font', 'texname psname effects encoding filename') class PsfontsMap(object): """ A psfonts.map formatted file, mapping TeX fonts to PS fonts. Usage:: >>> map = PsfontsMap(find_tex_file('pdftex.map')) >>> entry = map[b'ptmbo8r'] >>> entry.texname b'ptmbo8r' >>> entry.psname b'Times-Bold' >>> entry.encoding '/usr/local/texlive/2008/texmf-dist/fonts/enc/dvips/base/8r.enc' >>> entry.effects {'slant': 0.16700000000000001} >>> entry.filename Parameters ---------- filename : string or bytestring Notes ----- For historical reasons, TeX knows many Type-1 fonts by different names than the outside world. (For one thing, the names have to fit in eight characters.) Also, TeX's native fonts are not Type-1 but Metafont, which is nontrivial to convert to PostScript except as a bitmap. While high-quality conversions to Type-1 format exist and are shipped with modern TeX distributions, we need to know which Type-1 fonts are the counterparts of which native fonts. For these reasons a mapping is needed from internal font names to font file names. A texmf tree typically includes mapping files called e.g. :file:`psfonts.map`, :file:`pdftex.map`, or :file:`dvipdfm.map`. The file :file:`psfonts.map` is used by :program:`dvips`, :file:`pdftex.map` by :program:`pdfTeX`, and :file:`dvipdfm.map` by :program:`dvipdfm`. :file:`psfonts.map` might avoid embedding the 35 PostScript fonts (i.e., have no filename for them, as in the Times-Bold example above), while the pdf-related files perhaps only avoid the "Base 14" pdf fonts. But the user may have configured these files differently. """ __slots__ = ('_font', '_filename') # Create a filename -> PsfontsMap cache, so that calling # `PsfontsMap(filename)` with the same filename a second time immediately # returns the same object. @lru_cache() def __new__(cls, filename): self = object.__new__(cls) self._font = {} self._filename = os.fsdecode(filename) with open(filename, 'rb') as file: self._parse(file) return self def __getitem__(self, texname): assert isinstance(texname, bytes) try: result = self._font[texname] except KeyError: fmt = ('A PostScript file for the font whose TeX name is "{0}" ' 'could not be found in the file "{1}". The dviread module ' 'can only handle fonts that have an associated PostScript ' 'font file. ' 'This problem can often be solved by installing ' 'a suitable PostScript font package in your (TeX) ' 'package manager.') msg = fmt.format(texname.decode('ascii'), self._filename) msg = textwrap.fill(msg, break_on_hyphens=False, break_long_words=False) _log.info(msg) raise fn, enc = result.filename, result.encoding if fn is not None and not fn.startswith(b'/'): fn = find_tex_file(fn) if enc is not None and not enc.startswith(b'/'): enc = find_tex_file(result.encoding) return result._replace(filename=fn, encoding=enc) def _parse(self, file): """ Parse the font mapping file. The format is, AFAIK: texname fontname [effects and filenames] Effects are PostScript snippets like ".177 SlantFont", filenames begin with one or two less-than signs. A filename ending in enc is an encoding file, other filenames are font files. This can be overridden with a left bracket: <[foobar indicates an encoding file named foobar. There is some difference between <foo.pfb and <<bar.pfb in subsetting, but I have no example of << in my TeX installation. """ # If the map file specifies multiple encodings for a font, we # follow pdfTeX in choosing the last one specified. Such # entries are probably mistakes but they have occurred. # http://tex.stackexchange.com/questions/10826/ # http://article.gmane.org/gmane.comp.tex.pdftex/4914 empty_re = re.compile(br'%|\s*$') word_re = re.compile( br'''(?x) (?: "<\[ (?P<enc1> [^"]+ )" | # quoted encoding marked by [ "< (?P<enc2> [^"]+.enc)" | # quoted encoding, ends in .enc "<<? (?P<file1> [^"]+ )" | # quoted font file name " (?P<eff1> [^"]+ )" | # quoted effects or font name <\[ (?P<enc3> \S+ ) | # encoding marked by [ < (?P<enc4> \S+ .enc) | # encoding, ends in .enc <<? (?P<file2> \S+ ) | # font file name (?P<eff2> \S+ ) # effects or font name )''') effects_re = re.compile( br'''(?x) (?P<slant> -?[0-9]*(?:\.[0-9]+)) \s* SlantFont | (?P<extend>-?[0-9]*(?:\.[0-9]+)) \s* ExtendFont''') lines = (line.strip() for line in file if not empty_re.match(line)) for line in lines: effects, encoding, filename = b'', None, None words = word_re.finditer(line) # The named groups are mutually exclusive and are # referenced below at an estimated order of probability of # occurrence based on looking at my copy of pdftex.map. # The font names are probably unquoted: w = next(words) texname = w.group('eff2') or w.group('eff1') w = next(words) psname = w.group('eff2') or w.group('eff1') for w in words: # Any effects are almost always quoted: eff = w.group('eff1') or w.group('eff2') if eff: effects = eff continue # Encoding files usually have the .enc suffix # and almost never need quoting: enc = (w.group('enc4') or w.group('enc3') or w.group('enc2') or w.group('enc1')) if enc: if encoding is not None: _log.debug('Multiple encodings for %s = %s', texname, psname) encoding = enc continue # File names are probably unquoted: filename = w.group('file2') or w.group('file1') effects_dict = {} for match in effects_re.finditer(effects): slant = match.group('slant') if slant: effects_dict['slant'] = float(slant) else: effects_dict['extend'] = float(match.group('extend')) self._font[texname] = PsFont( texname=texname, psname=psname, effects=effects_dict, encoding=encoding, filename=filename) class Encoding(object): """ Parses a \\*.enc file referenced from a psfonts.map style file. The format this class understands is a very limited subset of PostScript. Usage (subject to change):: for name in Encoding(filename): whatever(name) Parameters ---------- filename : string or bytestring Attributes ---------- encoding : list List of character names """ __slots__ = ('encoding',) def __init__(self, filename): with open(filename, 'rb') as file: _log.debug('Parsing TeX encoding %s', filename) self.encoding = self._parse(file) _log.debug('Result: %s', self.encoding) def __iter__(self): yield from self.encoding @staticmethod def _parse(file): result = [] lines = (line.split(b'%', 1)[0].strip() for line in file) data = b''.join(lines) beginning = data.find(b'[') if beginning < 0: raise ValueError("Cannot locate beginning of encoding in {}" .format(file)) data = data[beginning:] end = data.find(b']') if end < 0: raise ValueError("Cannot locate end of encoding in {}" .format(file)) data = data[:end] return re.findall(br'/([^][{}<>\s]+)', data) @lru_cache() def find_tex_file(filename, format=None): """ Find a file in the texmf tree. Calls :program:`kpsewhich` which is an interface to the kpathsea library [1]_. Most existing TeX distributions on Unix-like systems use kpathsea. It is also available as part of MikTeX, a popular distribution on Windows. Parameters ---------- filename : string or bytestring format : string or bytestring Used as the value of the `--format` option to :program:`kpsewhich`. Could be e.g. 'tfm' or 'vf' to limit the search to that type of files. References ---------- .. [1] `Kpathsea documentation <http://www.tug.org/kpathsea/>`_ The library that :program:`kpsewhich` is part of. """ # we expect these to always be ascii encoded, but use utf-8 # out of caution if isinstance(filename, bytes): filename = filename.decode('utf-8', errors='replace') if isinstance(format, bytes): format = format.decode('utf-8', errors='replace') cmd = ['kpsewhich'] if format is not None: cmd += ['--format=' + format] cmd += [filename] _log.debug('find_tex_file(%s): %s', filename, cmd) pipe = subprocess.Popen(cmd, stdout=subprocess.PIPE) result = pipe.communicate()[0].rstrip() _log.debug('find_tex_file result: %s', result) return result.decode('ascii') @lru_cache() def _fontfile(cls, suffix, texname): filename = find_tex_file(texname + suffix) return cls(filename) if filename else None _tfmfile = partial(_fontfile, Tfm, ".tfm") _vffile = partial(_fontfile, Vf, ".vf") if __name__ == '__main__': import sys fname = sys.argv[1] try: dpi = float(sys.argv[2]) except IndexError: dpi = None with Dvi(fname, dpi) as dvi: fontmap = PsfontsMap(find_tex_file('pdftex.map')) for page in dvi: print('=== new page ===') fPrev = None for x, y, f, c, w in page.text: if f != fPrev: print('font', f.texname, 'scaled', f._scale/pow(2.0, 20)) fPrev = f print(x, y, c, 32 <= c < 128 and chr(c) or '.', w) for x, y, w, h in page.boxes: print(x, y, 'BOX', w, h)

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from collections import namedtuple import enum from functools import lru_cache, partial, wraps import logging import os import re import struct import subprocess import textwrap import numpy as np from matplotlib import cbook, rcParams _log = logging.getLogger(__name__) _dvistate = enum.Enum('DviState', 'pre outer inpage post_post finale') Page = namedtuple('Page', 'text boxes height width descent') Text = namedtuple('Text', 'x y font glyph width') Box = namedtuple('Box', 'x y height width') def _arg_raw(dvi, delta): return delta def _arg(bytes, signed, dvi, _): return dvi._arg(bytes, signed) def _arg_slen(dvi, delta): if delta == 0: return None return dvi._arg(delta, True) def _arg_slen1(dvi, delta): return dvi._arg(delta+1, True) def _arg_ulen1(dvi, delta): return dvi._arg(delta+1, False) def _arg_olen1(dvi, delta): return dvi._arg(delta + 1, delta == 3) _arg_mapping = dict(raw=_arg_raw, u1=partial(_arg, 1, False), u4=partial(_arg, 4, False), s4=partial(_arg, 4, True), slen=_arg_slen, olen1=_arg_olen1, slen1=_arg_slen1, ulen1=_arg_ulen1) def _dispatch(table, min, max=None, state=None, args=('raw',)): def decorate(method): get_args = [_arg_mapping[x] for x in args] @wraps(method) def wrapper(self, byte): if state is not None and self.state != state: raise ValueError("state precondition failed") return method(self, *[f(self, byte-min) for f in get_args]) if max is None: table[min] = wrapper else: for i in range(min, max+1): assert table[i] is None table[i] = wrapper return wrapper return decorate class Dvi(object): _dtable = [None] * 256 _dispatch = partial(_dispatch, _dtable) def __init__(self, filename, dpi): _log.debug('Dvi: %s', filename) self.file = open(filename, 'rb') self.dpi = dpi self.fonts = {} self.state = _dvistate.pre self.baseline = self._get_baseline(filename) def _get_baseline(self, filename): if rcParams['text.latex.preview']: base, ext = os.path.splitext(filename) baseline_filename = base + ".baseline" if os.path.exists(baseline_filename): with open(baseline_filename, 'rb') as fd: l = fd.read().split() height, depth, width = l return float(depth) return None def __enter__(self): return self def __exit__(self, etype, evalue, etrace): self.close() def __iter__(self): while self._read(): yield self._output() def close(self): if not self.file.closed: self.file.close() def _output(self): minx, miny, maxx, maxy = np.inf, np.inf, -np.inf, -np.inf maxy_pure = -np.inf for elt in self.text + self.boxes: if isinstance(elt, Box): x, y, h, w = elt e = 0 else: x, y, font, g, w = elt h, e = font._height_depth_of(g) minx = min(minx, x) miny = min(miny, y - h) maxx = max(maxx, x + w) maxy = max(maxy, y + e) maxy_pure = max(maxy_pure, y) if self.dpi is None: return Page(text=self.text, boxes=self.boxes, width=maxx-minx, height=maxy_pure-miny, descent=maxy-maxy_pure) d = self.dpi / (72.27 * 2**16) if self.baseline is None: descent = (maxy - maxy_pure) * d else: descent = self.baseline text = [Text((x-minx)*d, (maxy-y)*d - descent, f, g, w*d) for (x, y, f, g, w) in self.text] boxes = [Box((x-minx)*d, (maxy-y)*d - descent, h*d, w*d) for (x, y, h, w) in self.boxes] return Page(text=text, boxes=boxes, width=(maxx-minx)*d, height=(maxy_pure-miny)*d, descent=descent) def _read(self): while True: byte = self.file.read(1)[0] self._dtable[byte](self, byte) if byte == 140: # end of page return True if self.state is _dvistate.post_post: # end of file self.close() return False def _arg(self, nbytes, signed=False): str = self.file.read(nbytes) value = str[0] if signed and value >= 0x80: value = value - 0x100 for i in range(1, nbytes): value = 0x100*value + str[i] return value @_dispatch(min=0, max=127, state=_dvistate.inpage) def _set_char_immediate(self, char): self._put_char_real(char) self.h += self.fonts[self.f]._width_of(char) @_dispatch(min=128, max=131, state=_dvistate.inpage, args=('olen1',)) def _set_char(self, char): self._put_char_real(char) self.h += self.fonts[self.f]._width_of(char) @_dispatch(132, state=_dvistate.inpage, args=('s4', 's4')) def _set_rule(self, a, b): self._put_rule_real(a, b) self.h += b @_dispatch(min=133, max=136, state=_dvistate.inpage, args=('olen1',)) def _put_char(self, char): self._put_char_real(char) def _put_char_real(self, char): font = self.fonts[self.f] if font._vf is None: self.text.append(Text(self.h, self.v, font, char, font._width_of(char))) else: scale = font._scale for x, y, f, g, w in font._vf[char].text: newf = DviFont(scale=_mul2012(scale, f._scale), tfm=f._tfm, texname=f.texname, vf=f._vf) self.text.append(Text(self.h + _mul2012(x, scale), self.v + _mul2012(y, scale), newf, g, newf._width_of(g))) self.boxes.extend([Box(self.h + _mul2012(x, scale), self.v + _mul2012(y, scale), _mul2012(a, scale), _mul2012(b, scale)) for x, y, a, b in font._vf[char].boxes]) @_dispatch(137, state=_dvistate.inpage, args=('s4', 's4')) def _put_rule(self, a, b): self._put_rule_real(a, b) def _put_rule_real(self, a, b): if a > 0 and b > 0: self.boxes.append(Box(self.h, self.v, a, b)) @_dispatch(138) def _nop(self, _): pass @_dispatch(139, state=_dvistate.outer, args=('s4',)*11) def _bop(self, c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, p): self.state = _dvistate.inpage self.h, self.v, self.w, self.x, self.y, self.z = 0, 0, 0, 0, 0, 0 self.stack = [] self.text = [] # list of Text objects self.boxes = [] # list of Box objects @_dispatch(140, state=_dvistate.inpage) def _eop(self, _): self.state = _dvistate.outer del self.h, self.v, self.w, self.x, self.y, self.z, self.stack @_dispatch(141, state=_dvistate.inpage) def _push(self, _): self.stack.append((self.h, self.v, self.w, self.x, self.y, self.z)) @_dispatch(142, state=_dvistate.inpage) def _pop(self, _): self.h, self.v, self.w, self.x, self.y, self.z = self.stack.pop() @_dispatch(min=143, max=146, state=_dvistate.inpage, args=('slen1',)) def _right(self, b): self.h += b @_dispatch(min=147, max=151, state=_dvistate.inpage, args=('slen',)) def _right_w(self, new_w): if new_w is not None: self.w = new_w self.h += self.w @_dispatch(min=152, max=156, state=_dvistate.inpage, args=('slen',)) def _right_x(self, new_x): if new_x is not None: self.x = new_x self.h += self.x @_dispatch(min=157, max=160, state=_dvistate.inpage, args=('slen1',)) def _down(self, a): self.v += a @_dispatch(min=161, max=165, state=_dvistate.inpage, args=('slen',)) def _down_y(self, new_y): if new_y is not None: self.y = new_y self.v += self.y @_dispatch(min=166, max=170, state=_dvistate.inpage, args=('slen',)) def _down_z(self, new_z): if new_z is not None: self.z = new_z self.v += self.z @_dispatch(min=171, max=234, state=_dvistate.inpage) def _fnt_num_immediate(self, k): self.f = k @_dispatch(min=235, max=238, state=_dvistate.inpage, args=('olen1',)) def _fnt_num(self, new_f): self.f = new_f @_dispatch(min=239, max=242, args=('ulen1',)) def _xxx(self, datalen): special = self.file.read(datalen) _log.debug( 'Dvi._xxx: encountered special: %s', ''.join([chr(ch) if 32 <= ch < 127 else '<%02x>' % ch for ch in special])) @_dispatch(min=243, max=246, args=('olen1', 'u4', 'u4', 'u4', 'u1', 'u1')) def _fnt_def(self, k, c, s, d, a, l): self._fnt_def_real(k, c, s, d, a, l) def _fnt_def_real(self, k, c, s, d, a, l): n = self.file.read(a + l) fontname = n[-l:].decode('ascii') tfm = _tfmfile(fontname) if tfm is None: raise FileNotFoundError("missing font metrics file: %s" % fontname) if c != 0 and tfm.checksum != 0 and c != tfm.checksum: raise ValueError('tfm checksum mismatch: %s' % n) vf = _vffile(fontname) self.fonts[k] = DviFont(scale=s, tfm=tfm, texname=n, vf=vf) @_dispatch(247, state=_dvistate.pre, args=('u1', 'u4', 'u4', 'u4', 'u1')) def _pre(self, i, num, den, mag, k): comment = self.file.read(k) if i != 2: raise ValueError("Unknown dvi format %d" % i) if num != 25400000 or den != 7227 * 2**16: raise ValueError("nonstandard units in dvi file") # meaning: TeX always uses those exact values, so it # should be enough for us to support those # (There are 72.27 pt to an inch so 7227 pt = # 7227 * 2**16 sp to 100 in. The numerator is multiplied # by 10^5 to get units of 10**-7 meters.) if mag != 1000: raise ValueError("nonstandard magnification in dvi file") # meaning: LaTeX seems to frown on setting \mag, so # I think we can assume this is constant self.state = _dvistate.outer @_dispatch(248, state=_dvistate.outer) def _post(self, _): self.state = _dvistate.post_post # TODO: actually read the postamble and finale? # currently post_post just triggers closing the file @_dispatch(249) def _post_post(self, _): raise NotImplementedError @_dispatch(min=250, max=255) def _malformed(self, offset): raise ValueError("unknown command: byte %d", 250 + offset) class DviFont(object): __slots__ = ('texname', 'size', 'widths', '_scale', '_vf', '_tfm') def __init__(self, scale, tfm, texname, vf): if not isinstance(texname, bytes): raise ValueError("texname must be a bytestring, got %s" % type(texname)) self._scale, self._tfm, self.texname, self._vf = \ scale, tfm, texname, vf self.size = scale * (72.0 / (72.27 * 2**16)) try: nchars = max(tfm.width) + 1 except ValueError: nchars = 0 self.widths = [(1000*tfm.width.get(char, 0)) >> 20 for char in range(nchars)] def __eq__(self, other): return self.__class__ == other.__class__ and \ self.texname == other.texname and self.size == other.size def __ne__(self, other): return not self.__eq__(other) def _width_of(self, char): width = self._tfm.width.get(char, None) if width is not None: return _mul2012(width, self._scale) _log.debug('No width for char %d in font %s.', char, self.texname) return 0 def _height_depth_of(self, char): result = [] for metric, name in ((self._tfm.height, "height"), (self._tfm.depth, "depth")): value = metric.get(char, None) if value is None: _log.debug('No %s for char %d in font %s', name, char, self.texname) result.append(0) else: result.append(_mul2012(value, self._scale)) return result class Vf(Dvi): def __init__(self, filename): Dvi.__init__(self, filename, 0) try: self._first_font = None self._chars = {} self._read() finally: self.close() def __getitem__(self, code): return self._chars[code] def _read(self): packet_char, packet_ends = None, None packet_len, packet_width = None, None while True: byte = self.file.read(1)[0] # If we are in a packet, execute the dvi instructions if self.state is _dvistate.inpage: byte_at = self.file.tell()-1 if byte_at == packet_ends: self._finalize_packet(packet_char, packet_width) packet_len, packet_char, packet_width = None, None, None # fall through to out-of-packet code elif byte_at > packet_ends: raise ValueError("Packet length mismatch in vf file") else: if byte in (139, 140) or byte >= 243: raise ValueError( "Inappropriate opcode %d in vf file" % byte) Dvi._dtable[byte](self, byte) continue # We are outside a packet if byte < 242: # a short packet (length given by byte) packet_len = byte packet_char, packet_width = self._arg(1), self._arg(3) packet_ends = self._init_packet(byte) self.state = _dvistate.inpage elif byte == 242: # a long packet packet_len, packet_char, packet_width = \ [self._arg(x) for x in (4, 4, 4)] self._init_packet(packet_len) elif 243 <= byte <= 246: k = self._arg(byte - 242, byte == 246) c, s, d, a, l = [self._arg(x) for x in (4, 4, 4, 1, 1)] self._fnt_def_real(k, c, s, d, a, l) if self._first_font is None: self._first_font = k elif byte == 247: # preamble i, k = self._arg(1), self._arg(1) x = self.file.read(k) cs, ds = self._arg(4), self._arg(4) self._pre(i, x, cs, ds) elif byte == 248: # postamble (just some number of 248s) break else: raise ValueError("unknown vf opcode %d" % byte) def _init_packet(self, pl): if self.state != _dvistate.outer: raise ValueError("Misplaced packet in vf file") self.h, self.v, self.w, self.x, self.y, self.z = 0, 0, 0, 0, 0, 0 self.stack, self.text, self.boxes = [], [], [] self.f = self._first_font return self.file.tell() + pl def _finalize_packet(self, packet_char, packet_width): self._chars[packet_char] = Page( text=self.text, boxes=self.boxes, width=packet_width, height=None, descent=None) self.state = _dvistate.outer def _pre(self, i, x, cs, ds): if self.state is not _dvistate.pre: raise ValueError("pre command in middle of vf file") if i != 202: raise ValueError("Unknown vf format %d" % i) if len(x): _log.debug('vf file comment: %s', x) self.state = _dvistate.outer # cs = checksum, ds = design size def _fix2comp(num): assert 0 <= num < 2**32 if num & 2**31: return num - 2**32 else: return num def _mul2012(num1, num2): # Separated into a function because >> has surprising precedence return (num1*num2) >> 20 class Tfm(object): __slots__ = ('checksum', 'design_size', 'width', 'height', 'depth') def __init__(self, filename): _log.debug('opening tfm file %s', filename) with open(filename, 'rb') as file: header1 = file.read(24) lh, bc, ec, nw, nh, nd = \ struct.unpack('!6H', header1[2:14]) _log.debug('lh=%d, bc=%d, ec=%d, nw=%d, nh=%d, nd=%d', lh, bc, ec, nw, nh, nd) header2 = file.read(4*lh) self.checksum, self.design_size = \ struct.unpack('!2I', header2[:8]) # there is also encoding information etc. char_info = file.read(4*(ec-bc+1)) widths = file.read(4*nw) heights = file.read(4*nh) depths = file.read(4*nd) self.width, self.height, self.depth = {}, {}, {} widths, heights, depths = \ [struct.unpack('!%dI' % (len(x)/4), x) for x in (widths, heights, depths)] for idx, char in enumerate(range(bc, ec+1)): byte0 = char_info[4*idx] byte1 = char_info[4*idx+1] self.width[char] = _fix2comp(widths[byte0]) self.height[char] = _fix2comp(heights[byte1 >> 4]) self.depth[char] = _fix2comp(depths[byte1 & 0xf]) PsFont = namedtuple('Font', 'texname psname effects encoding filename') class PsfontsMap(object): __slots__ = ('_font', '_filename') # Create a filename -> PsfontsMap cache, so that calling # `PsfontsMap(filename)` with the same filename a second time immediately # returns the same object. @lru_cache() def __new__(cls, filename): self = object.__new__(cls) self._font = {} self._filename = os.fsdecode(filename) with open(filename, 'rb') as file: self._parse(file) return self def __getitem__(self, texname): assert isinstance(texname, bytes) try: result = self._font[texname] except KeyError: fmt = ('A PostScript file for the font whose TeX name is "{0}" ' 'could not be found in the file "{1}". The dviread module ' 'can only handle fonts that have an associated PostScript ' 'font file. ' 'This problem can often be solved by installing ' 'a suitable PostScript font package in your (TeX) ' 'package manager.') msg = fmt.format(texname.decode('ascii'), self._filename) msg = textwrap.fill(msg, break_on_hyphens=False, break_long_words=False) _log.info(msg) raise fn, enc = result.filename, result.encoding if fn is not None and not fn.startswith(b'/'): fn = find_tex_file(fn) if enc is not None and not enc.startswith(b'/'): enc = find_tex_file(result.encoding) return result._replace(filename=fn, encoding=enc) def _parse(self, file): # If the map file specifies multiple encodings for a font, we # follow pdfTeX in choosing the last one specified. Such # entries are probably mistakes but they have occurred. # http://tex.stackexchange.com/questions/10826/ # http://article.gmane.org/gmane.comp.tex.pdftex/4914 empty_re = re.compile(br'%|\s*$') word_re = re.compile( br'''(?x) (?: "<\[ (?P<enc1> [^"]+ )" | # quoted encoding marked by [ "< (?P<enc2> [^"]+.enc)" | # quoted encoding, ends in .enc "<<? (?P<file1> [^"]+ )" | # quoted font file name " (?P<eff1> [^"]+ )" | # quoted effects or font name <\[ (?P<enc3> \S+ ) | # encoding marked by [ < (?P<enc4> \S+ .enc) | # encoding, ends in .enc <<? (?P<file2> \S+ ) | # font file name (?P<eff2> \S+ ) # effects or font name )''') effects_re = re.compile( br'''(?x) (?P<slant> -?[0-9]*(?:\.[0-9]+)) \s* SlantFont | (?P<extend>-?[0-9]*(?:\.[0-9]+)) \s* ExtendFont''') lines = (line.strip() for line in file if not empty_re.match(line)) for line in lines: effects, encoding, filename = b'', None, None words = word_re.finditer(line) # The named groups are mutually exclusive and are # referenced below at an estimated order of probability of # occurrence based on looking at my copy of pdftex.map. # The font names are probably unquoted: w = next(words) texname = w.group('eff2') or w.group('eff1') w = next(words) psname = w.group('eff2') or w.group('eff1') for w in words: # Any effects are almost always quoted: eff = w.group('eff1') or w.group('eff2') if eff: effects = eff continue # Encoding files usually have the .enc suffix # and almost never need quoting: enc = (w.group('enc4') or w.group('enc3') or w.group('enc2') or w.group('enc1')) if enc: if encoding is not None: _log.debug('Multiple encodings for %s = %s', texname, psname) encoding = enc continue # File names are probably unquoted: filename = w.group('file2') or w.group('file1') effects_dict = {} for match in effects_re.finditer(effects): slant = match.group('slant') if slant: effects_dict['slant'] = float(slant) else: effects_dict['extend'] = float(match.group('extend')) self._font[texname] = PsFont( texname=texname, psname=psname, effects=effects_dict, encoding=encoding, filename=filename) class Encoding(object): __slots__ = ('encoding',) def __init__(self, filename): with open(filename, 'rb') as file: _log.debug('Parsing TeX encoding %s', filename) self.encoding = self._parse(file) _log.debug('Result: %s', self.encoding) def __iter__(self): yield from self.encoding @staticmethod def _parse(file): result = [] lines = (line.split(b'%', 1)[0].strip() for line in file) data = b''.join(lines) beginning = data.find(b'[') if beginning < 0: raise ValueError("Cannot locate beginning of encoding in {}" .format(file)) data = data[beginning:] end = data.find(b']') if end < 0: raise ValueError("Cannot locate end of encoding in {}" .format(file)) data = data[:end] return re.findall(br'/([^][{}<>\s]+)', data) @lru_cache() def find_tex_file(filename, format=None): # we expect these to always be ascii encoded, but use utf-8 # out of caution if isinstance(filename, bytes): filename = filename.decode('utf-8', errors='replace') if isinstance(format, bytes): format = format.decode('utf-8', errors='replace') cmd = ['kpsewhich'] if format is not None: cmd += ['--format=' + format] cmd += [filename] _log.debug('find_tex_file(%s): %s', filename, cmd) pipe = subprocess.Popen(cmd, stdout=subprocess.PIPE) result = pipe.communicate()[0].rstrip() _log.debug('find_tex_file result: %s', result) return result.decode('ascii') @lru_cache() def _fontfile(cls, suffix, texname): filename = find_tex_file(texname + suffix) return cls(filename) if filename else None _tfmfile = partial(_fontfile, Tfm, ".tfm") _vffile = partial(_fontfile, Vf, ".vf") if __name__ == '__main__': import sys fname = sys.argv[1] try: dpi = float(sys.argv[2]) except IndexError: dpi = None with Dvi(fname, dpi) as dvi: fontmap = PsfontsMap(find_tex_file('pdftex.map')) for page in dvi: print('=== new page ===') fPrev = None for x, y, f, c, w in page.text: if f != fPrev: print('font', f.texname, 'scaled', f._scale/pow(2.0, 20)) fPrev = f print(x, y, c, 32 <= c < 128 and chr(c) or '.', w) for x, y, w, h in page.boxes: print(x, y, 'BOX', w, h)

true

f738fb755883c2f74681fac8b121abf0c9cd6e56

5,175

py

Python

vehicle_detection.py

suhongkim/SSD-Vehicle-Detector

8337d237f4c7923e55d02747ec37a60681e5beff

[ "MIT" ]

null

vehicle_detection.py

suhongkim/SSD-Vehicle-Detector

8337d237f4c7923e55d02747ec37a60681e5beff

[ "MIT" ]

null

vehicle_detection.py

suhongkim/SSD-Vehicle-Detector

8337d237f4c7923e55d02747ec37a60681e5beff

[ "MIT" ]

null

import os import torch from torch.utils.data import DataLoader from cityscape_dataset import CityScapeDataset from ssd_util import load_dataset_list, load_dataset_list_original, show_loss, show_log from ssd_net import SSD from ssd_train import train_net from ssd_test import test_net if __name__ == '__main__': # Define Label Group dataset_label_group = { 'background': [], 'sm_veh': ['motorcycle', 'motorcyclegroup', 'bicycle', 'bicyclegroup'], 'med_veh': ['car', 'cargroup'], # 'ego_veh': ['ego vehicle'], 'big_veh': ['bus', 'trailer', 'truck'], # 'people': ['person', 'persongroup'], # 'riders': ['rider', 'ridergroup'] } # Define Configurations config = {'is_gpu': True, 'debug': False, 'n_aug': 1, 'n_batch': 64, 'n_worker': 4, 'lr': 0.001, 'max_epoch': 100, 'save_epochs': [10,20,30,40,50,60,70,80,90], 'is_lr_scheduled': False, # 'class_labels': ['background', 'cargroup'], # 'class_labels': ['background', 'persongroup', 'person', 'cargroup', 'car'], 'label_groups': dataset_label_group, 'class_labels': list(dataset_label_group.keys()), 'is_train': True, 'is_test': True, 'results_path': '/home/suhongk/sfuhome/CMPT742/Lab3/vehicle_detection_v2/results/SSD__28th_16:47_best_model.pth' } # crop original image # person + persongroup , car+Cargroup # Overfitted data for the unaug # check training set # Default Cuda Setting ------------------------------------------------- from torch.multiprocessing import Pool, Process, set_start_method try: set_start_method('spawn') except RuntimeError: pass if torch.cuda.is_available(): torch.set_default_tensor_type('torch.cuda.FloatTensor') torch.backends.cudnn.benchmark = True # load dataset_list ------------------------------------------------- if config['is_gpu']: sample_path = '/home/datasets/full_dataset/train_extra/' label_path = '/home/datasets/full_dataset_labels/train_extra' else: sample_path = '../cityscapes_samples/' label_path = '../cityscapes_samples_labels/' dataset_list = load_dataset_list(sample_path, label_path, config['label_groups']) # dataset_list = load_dataset_list_original(sample_path, label_path, config['class_labels']) # Define dataset/dataloader ------------------------------------------- num_train = int(0.3 * len(dataset_list)) num_valid = int(0.1 * len(dataset_list)) if config['is_train']: train_dataset = CityScapeDataset(dataset_list[:num_train], n_augmented=config['n_aug'], debug=config['debug']) train_loader = DataLoader(train_dataset, batch_size=config['n_batch'], shuffle=True, num_workers=config['n_worker']) print('Total training items: ', len(train_dataset)) print('Total training batches size in one epoch: ', len(train_loader)) valid_dataset = CityScapeDataset(dataset_list[num_train:(num_train + num_valid)], debug=config['debug']) valid_loader = DataLoader(valid_dataset, batch_size=config['n_batch'], shuffle=True, num_workers=config['n_worker']) print('Total validating items: ', len(valid_dataset)) print('Total validating batches size in one epoch: ', len(valid_loader)) if config['is_test']: test_dataset = CityScapeDataset(dataset_list[(num_train + num_valid):], debug=config['debug']) print('Total testing items: ', len(test_dataset)) # Train network ----------------------------------------------------- if config['is_train']: lab_results_dir = "./results/" # for the results results_path = train_net(train_loader, valid_loader, config['class_labels'], lab_results_dir, learning_rate=config['lr'], is_lr_scheduled=config['is_lr_scheduled'], max_epoch=config['max_epoch'], save_epochs=config['save_epochs']) print('\n\n-----------------------\n\tresult_path:', results_path) if not config['is_gpu']: show_loss(results_path + '.loss') # show_log(results_path + '__train.log') # show_log(results_path + '__valid.log') if config['is_test']: test_net(test_dataset, config['class_labels'], (results_path + '__model.pth')) # Train network ----------------------------------------------------- if config['is_test'] and not config['is_train']: test_net(test_dataset, config['class_labels'], config['results_path']) # pass # Test Code ---------------------------------------------------------- # idx, (imgs, bbox_label, bbox_indices, _) = next(enumerate(train_loader)) # print(bbox_indices) # test_dataset.__getitem__(9) # net = SSD(len(class_labels)) # net.cuda() # net.forward(torch.rand(1, 3, 300, 300))

45.394737

127

0.582802

import os import torch from torch.utils.data import DataLoader from cityscape_dataset import CityScapeDataset from ssd_util import load_dataset_list, load_dataset_list_original, show_loss, show_log from ssd_net import SSD from ssd_train import train_net from ssd_test import test_net if __name__ == '__main__': dataset_label_group = { 'background': [], 'sm_veh': ['motorcycle', 'motorcyclegroup', 'bicycle', 'bicyclegroup'], 'med_veh': ['car', 'cargroup'], 'big_veh': ['bus', 'trailer', 'truck'], } config = {'is_gpu': True, 'debug': False, 'n_aug': 1, 'n_batch': 64, 'n_worker': 4, 'lr': 0.001, 'max_epoch': 100, 'save_epochs': [10,20,30,40,50,60,70,80,90], 'is_lr_scheduled': False, 'label_groups': dataset_label_group, 'class_labels': list(dataset_label_group.keys()), 'is_train': True, 'is_test': True, 'results_path': '/home/suhongk/sfuhome/CMPT742/Lab3/vehicle_detection_v2/results/SSD__28th_16:47_best_model.pth' } from torch.multiprocessing import Pool, Process, set_start_method try: set_start_method('spawn') except RuntimeError: pass if torch.cuda.is_available(): torch.set_default_tensor_type('torch.cuda.FloatTensor') torch.backends.cudnn.benchmark = True if config['is_gpu']: sample_path = '/home/datasets/full_dataset/train_extra/' label_path = '/home/datasets/full_dataset_labels/train_extra' else: sample_path = '../cityscapes_samples/' label_path = '../cityscapes_samples_labels/' dataset_list = load_dataset_list(sample_path, label_path, config['label_groups']) num_train = int(0.3 * len(dataset_list)) num_valid = int(0.1 * len(dataset_list)) if config['is_train']: train_dataset = CityScapeDataset(dataset_list[:num_train], n_augmented=config['n_aug'], debug=config['debug']) train_loader = DataLoader(train_dataset, batch_size=config['n_batch'], shuffle=True, num_workers=config['n_worker']) print('Total training items: ', len(train_dataset)) print('Total training batches size in one epoch: ', len(train_loader)) valid_dataset = CityScapeDataset(dataset_list[num_train:(num_train + num_valid)], debug=config['debug']) valid_loader = DataLoader(valid_dataset, batch_size=config['n_batch'], shuffle=True, num_workers=config['n_worker']) print('Total validating items: ', len(valid_dataset)) print('Total validating batches size in one epoch: ', len(valid_loader)) if config['is_test']: test_dataset = CityScapeDataset(dataset_list[(num_train + num_valid):], debug=config['debug']) print('Total testing items: ', len(test_dataset)) if config['is_train']: lab_results_dir = "./results/" results_path = train_net(train_loader, valid_loader, config['class_labels'], lab_results_dir, learning_rate=config['lr'], is_lr_scheduled=config['is_lr_scheduled'], max_epoch=config['max_epoch'], save_epochs=config['save_epochs']) print('\n\n-----------------------\n\tresult_path:', results_path) if not config['is_gpu']: show_loss(results_path + '.loss') if config['is_test']: test_net(test_dataset, config['class_labels'], (results_path + '__model.pth')) if config['is_test'] and not config['is_train']: test_net(test_dataset, config['class_labels'], config['results_path'])

true

f738feb48528bc44a1c44d1a4c3cafea3b88882f

2,149

py

Python

CMSIS/DSP/Examples/ARM/arm_bayes_example/train.py

DavidLesnjak/CMSIS_5

e0848410d137758a3356a5ee94ca4501cea708a8

[ "Apache-2.0" ]

2,293

2016-02-25T06:47:33.000Z

2022-03-29T16:44:02.000Z

CMSIS/DSP/Examples/ARM/arm_bayes_example/train.py

DavidLesnjak/CMSIS_5

e0848410d137758a3356a5ee94ca4501cea708a8

[ "Apache-2.0" ]

1,125

2016-02-27T09:56:01.000Z

2022-03-31T13:57:05.000Z

CMSIS/DSP/Examples/ARM/arm_bayes_example/train.py

DavidLesnjak/CMSIS_5

e0848410d137758a3356a5ee94ca4501cea708a8

[ "Apache-2.0" ]

1,160

2016-02-27T09:06:10.000Z

2022-03-31T19:06:24.000Z

from sklearn.naive_bayes import GaussianNB import random import numpy as np import math from pylab import scatter,figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show,semilogx, semilogy import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties # Generation of data to train the classifier # 100 vectors are generated. Vector have dimension 2 so can be represented as points NBVECS = 100 VECDIM = 2 # 3 cluster of points are generated ballRadius = 1.0 x1 = [1.5, 1] + ballRadius * np.random.randn(NBVECS,VECDIM) x2 = [-1.5, 1] + ballRadius * np.random.randn(NBVECS,VECDIM) x3 = [0, -3] + ballRadius * np.random.randn(NBVECS,VECDIM) # All points are concatenated X_train=np.concatenate((x1,x2,x3)) # The classes are 0,1 and 2. Y_train=np.concatenate((np.zeros(NBVECS),np.ones(NBVECS),2*np.ones(NBVECS))) gnb = GaussianNB() gnb.fit(X_train, Y_train) print("Testing") y_pred = gnb.predict([[1.5,1.0]]) print(y_pred) y_pred = gnb.predict([[-1.5,1.0]]) print(y_pred) y_pred = gnb.predict([[0,-3.0]]) print(y_pred) # Dump of data for CMSIS-DSP print("Parameters") # Gaussian averages print("Theta = ",list(np.reshape(gnb.theta_,np.size(gnb.theta_)))) # Gaussian variances print("Sigma = ",list(np.reshape(gnb.sigma_,np.size(gnb.sigma_)))) # Class priors print("Prior = ",list(np.reshape(gnb.class_prior_,np.size(gnb.class_prior_)))) print("Epsilon = ",gnb.epsilon_) # Some bounds are computed for the graphical representation x_min = X_train[:, 0].min() x_max = X_train[:, 0].max() y_min = X_train[:, 1].min() y_max = X_train[:, 1].max() font = FontProperties() font.set_size(20) r=plt.figure() plt.axis('off') plt.text(1.5,1.0,"A", verticalalignment='center', horizontalalignment='center',fontproperties=font) plt.text(-1.5,1.0,"B",verticalalignment='center', horizontalalignment='center', fontproperties=font) plt.text(0,-3,"C", verticalalignment='center', horizontalalignment='center',fontproperties=font) scatter(x1[:,0],x1[:,1],s=1.0,color='#FF6B00') scatter(x2[:,0],x2[:,1],s=1.0,color='#95D600') scatter(x3[:,0],x3[:,1],s=1.0,color='#00C1DE') #r.savefig('fig.jpeg') #plt.close(r) show()

29.040541

115

0.717543

from sklearn.naive_bayes import GaussianNB import random import numpy as np import math from pylab import scatter,figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show,semilogx, semilogy import matplotlib.pyplot as plt from matplotlib.font_manager import FontProperties NBVECS = 100 VECDIM = 2 ballRadius = 1.0 x1 = [1.5, 1] + ballRadius * np.random.randn(NBVECS,VECDIM) x2 = [-1.5, 1] + ballRadius * np.random.randn(NBVECS,VECDIM) x3 = [0, -3] + ballRadius * np.random.randn(NBVECS,VECDIM) X_train=np.concatenate((x1,x2,x3)) Y_train=np.concatenate((np.zeros(NBVECS),np.ones(NBVECS),2*np.ones(NBVECS))) gnb = GaussianNB() gnb.fit(X_train, Y_train) print("Testing") y_pred = gnb.predict([[1.5,1.0]]) print(y_pred) y_pred = gnb.predict([[-1.5,1.0]]) print(y_pred) y_pred = gnb.predict([[0,-3.0]]) print(y_pred) print("Parameters") print("Theta = ",list(np.reshape(gnb.theta_,np.size(gnb.theta_)))) print("Sigma = ",list(np.reshape(gnb.sigma_,np.size(gnb.sigma_)))) print("Prior = ",list(np.reshape(gnb.class_prior_,np.size(gnb.class_prior_)))) print("Epsilon = ",gnb.epsilon_) x_min = X_train[:, 0].min() x_max = X_train[:, 0].max() y_min = X_train[:, 1].min() y_max = X_train[:, 1].max() font = FontProperties() font.set_size(20) r=plt.figure() plt.axis('off') plt.text(1.5,1.0,"A", verticalalignment='center', horizontalalignment='center',fontproperties=font) plt.text(-1.5,1.0,"B",verticalalignment='center', horizontalalignment='center', fontproperties=font) plt.text(0,-3,"C", verticalalignment='center', horizontalalignment='center',fontproperties=font) scatter(x1[:,0],x1[:,1],s=1.0,color='#FF6B00') scatter(x2[:,0],x2[:,1],s=1.0,color='#95D600') scatter(x3[:,0],x3[:,1],s=1.0,color='#00C1DE') show()

true

f738ff1b59bd6407c45587658b34887b5f3bc25d

1,511

py

Python

bilibili/bilibili/spiders/relationship.py

PyDee/Spiders

6fc0a414060032b5ba4332302285e3fcc9a6113e

[ "Apache-2.0" ]

6

2020-06-02T16:22:58.000Z

2021-09-18T03:20:16.000Z

bilibili/bilibili/spiders/relationship.py

PyDee/Spiders

6fc0a414060032b5ba4332302285e3fcc9a6113e

[ "Apache-2.0" ]

4

2021-03-31T19:54:37.000Z

2022-03-12T00:33:41.000Z

bilibili/bilibili/spiders/relationship.py

PyDee/Spiders

6fc0a414060032b5ba4332302285e3fcc9a6113e

[ "Apache-2.0" ]

5

2020-06-02T16:23:00.000Z

2021-09-03T02:16:15.000Z

# -*- coding: utf-8 -*- """ 获取用户关注 """ import json import redis from scrapy_redis.spiders import RedisSpider from ..items import Relationship from .bos_filter import RedisDB, BosFilter class RelationshipSpider(RedisSpider): rdb = RedisDB() r = redis.Redis(host="127.0.0.1") name = 'relationship' allowed_domains = ['api.bilibili.com'] redis_key = "bili_relation_list" redis_set = "bili_relation_set" def parse(self, response): ret_dict = json.loads(response.text) status_code = ret_dict.get('code') if not status_code: if 'data' in ret_dict.keys(): info_dict = ret_dict.get('data') total = info_dict.get('total') focus_list = info_dict.get('list') user_id = response.url.strip('https://api.bilibili.com/x/relation/followings?vmid=').split('&')[0] for focus_item in focus_list: focus_info = Relationship() focus_info['total'] = total focus_info['user_id'] = user_id focus_info['focus_id'] = focus_item.get('mid') focus_info['focus_name'] = focus_item.get('uname') focus_info['focus_face'] = focus_item.get('face') focus_info['introduction'] = focus_item.get('sign') # 将 follower id 写入到待抓取队列 self.r.sadd(self.redis_set, focus_info.get('focus_id')) yield focus_info

36.853659

114

0.577763

import json import redis from scrapy_redis.spiders import RedisSpider from ..items import Relationship from .bos_filter import RedisDB, BosFilter class RelationshipSpider(RedisSpider): rdb = RedisDB() r = redis.Redis(host="127.0.0.1") name = 'relationship' allowed_domains = ['api.bilibili.com'] redis_key = "bili_relation_list" redis_set = "bili_relation_set" def parse(self, response): ret_dict = json.loads(response.text) status_code = ret_dict.get('code') if not status_code: if 'data' in ret_dict.keys(): info_dict = ret_dict.get('data') total = info_dict.get('total') focus_list = info_dict.get('list') user_id = response.url.strip('https://api.bilibili.com/x/relation/followings?vmid=').split('&')[0] for focus_item in focus_list: focus_info = Relationship() focus_info['total'] = total focus_info['user_id'] = user_id focus_info['focus_id'] = focus_item.get('mid') focus_info['focus_name'] = focus_item.get('uname') focus_info['focus_face'] = focus_item.get('face') focus_info['introduction'] = focus_item.get('sign') self.r.sadd(self.redis_set, focus_info.get('focus_id')) yield focus_info

true

f738ff759b6f7cf53b2e7583c0b4df87d9a35a39

1,352

py

Python

kaggle_SIIM-ACR_Pneumothorax_Segmentation/utils/loss.py

allen050883/Project

22a9f1e466e595d8808e59fc58801881f3399df4

[ "MIT" ]

null

kaggle_SIIM-ACR_Pneumothorax_Segmentation/utils/loss.py

allen050883/Project

22a9f1e466e595d8808e59fc58801881f3399df4

[ "MIT" ]

null

kaggle_SIIM-ACR_Pneumothorax_Segmentation/utils/loss.py

allen050883/Project

22a9f1e466e595d8808e59fc58801881f3399df4

[ "MIT" ]

null

import torch import torch.nn.functional as F def dice_score(inputs, targets, smooth=1): # Flatten label and prediction tensors inputs = inputs.view(-1) targets = targets.view(-1) intersection = (inputs * targets).sum() dice_score = (2.*intersection + smooth)/(inputs.sum() + targets.sum() + smooth) return dice_score def get_dice_loss(inputs, targets, smooth=1): # Flatten label and prediction tensors inputs = inputs.view(-1) targets = targets.view(-1) intersection = (inputs * targets).sum() dice_loss = 1 - (2.*intersection + smooth)/(inputs.sum() + targets.sum() + smooth) return dice_loss def get_focal_loss(inputs, targets, alpha=0.8, gamma=2): # Flatten label and prediction tensors inputs = inputs.view(-1) targets = targets.view(-1) # First compute binary cross-entropy BCE = F.binary_cross_entropy(inputs, targets, reduction='mean') BCE_EXP = torch.exp(-BCE) focal_loss = alpha * (1-BCE_EXP)**gamma * BCE return focal_loss def combo_loss(inputs, targets): dice_loss = get_dice_loss(inputs, targets) BCE = F.binary_cross_entropy(inputs, targets, reduction='mean') focal_loss = get_focal_loss(inputs, targets) return focal_loss - torch.log(1-dice_loss)

32.190476

88

0.647189

import torch import torch.nn.functional as F def dice_score(inputs, targets, smooth=1): inputs = inputs.view(-1) targets = targets.view(-1) intersection = (inputs * targets).sum() dice_score = (2.*intersection + smooth)/(inputs.sum() + targets.sum() + smooth) return dice_score def get_dice_loss(inputs, targets, smooth=1): inputs = inputs.view(-1) targets = targets.view(-1) intersection = (inputs * targets).sum() dice_loss = 1 - (2.*intersection + smooth)/(inputs.sum() + targets.sum() + smooth) return dice_loss def get_focal_loss(inputs, targets, alpha=0.8, gamma=2): inputs = inputs.view(-1) targets = targets.view(-1) BCE = F.binary_cross_entropy(inputs, targets, reduction='mean') BCE_EXP = torch.exp(-BCE) focal_loss = alpha * (1-BCE_EXP)**gamma * BCE return focal_loss def combo_loss(inputs, targets): dice_loss = get_dice_loss(inputs, targets) BCE = F.binary_cross_entropy(inputs, targets, reduction='mean') focal_loss = get_focal_loss(inputs, targets) return focal_loss - torch.log(1-dice_loss)

true

f738ffc00adfe3ae0e5db9437b05b358c231180f

296

py

Python

daiquiri/stats/admin.py

agy-why/daiquiri

4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d

[ "Apache-2.0" ]

14

2018-12-23T18:35:02.000Z

2021-12-15T04:55:12.000Z

daiquiri/stats/admin.py

agy-why/daiquiri

4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d

[ "Apache-2.0" ]

40

2018-12-20T12:44:05.000Z

2022-03-21T11:35:20.000Z

daiquiri/stats/admin.py

agy-why/daiquiri

4d3e2ce51e202d5a8f1df404a0094a4e018dcb4d

[ "Apache-2.0" ]

5

2019-05-16T08:03:35.000Z

2021-08-23T20:03:11.000Z

from django.contrib import admin from .models import Record class RecordAdmin(admin.ModelAdmin): search_fields = ('resource', 'user__username') list_display = ('time', 'resource_type', 'client_ip', 'user') list_display_links = ('time', ) admin.site.register(Record, RecordAdmin)

22.769231

65

0.722973

from django.contrib import admin from .models import Record class RecordAdmin(admin.ModelAdmin): search_fields = ('resource', 'user__username') list_display = ('time', 'resource_type', 'client_ip', 'user') list_display_links = ('time', ) admin.site.register(Record, RecordAdmin)

true

f73900a0283ab4836b6eccbee5cb864bc5a14b42

3,725

py

Python

main.py

wcontreras785/Controlador-Termohigrometro-Micropayhon

a15c4b71eec8f0e8fb72f20e9de2e1032b97685c

[ "MIT" ]

null

main.py

wcontreras785/Controlador-Termohigrometro-Micropayhon

a15c4b71eec8f0e8fb72f20e9de2e1032b97685c

[ "MIT" ]

null

main.py

wcontreras785/Controlador-Termohigrometro-Micropayhon

a15c4b71eec8f0e8fb72f20e9de2e1032b97685c

[ "MIT" ]

null

from machine import SoftI2C, Pin, RTC import onewire, ds18x20, time import utime, dht, network, urequests import OLED, ntptime temp=30 url = "https://api.thingspeak.com/update?api_key=CTVG0E49RI7RSV78" #------------------------------------------WIFI------------------- def conectaWifi (red, password): global miRed miRed = network.WLAN(network.STA_IF) if not miRed.isconnected(): #Si no está conectado… miRed.active(True) #activa la interface miRed.connect(red, password) #Intenta conectar con la red print('Conectando a la red', red +"…") timeout = time.time () while not miRed.isconnected(): #Mientras no se conecte.. if (time.ticks_diff (time.time (), timeout) > 10): return False return True if conectaWifi (".", "V5MVH6F3SVDU"): print ("Conexión exitosa!") print('Datos de la red (IP/netmask/gw/DNS):', miRed.ifconfig()) #--------------------------SINCRONIZACIÓN DEL RELOJ INTERNO E IMPRESIÓN DE FECHA Y HORA---------------------- ntptime.settime() rtc= RTC() (year, month, mday, weekday, hour, minute, second, milisecond)=rtc.datetime() rtc.init((year, month, mday, weekday, hour-5, minute, second, milisecond)) # GMT corrección -Colombia-: GMT-5 def rfecha(): print ("Fecha: {:02d}/{:02d}/{}".format(rtc.datetime()[2], rtc.datetime()[1], rtc.datetime()[0])) def rhora(): print ("Hora: {:02d}:{:02d}:{:02d}".format(rtc.datetime()[4], rtc.datetime()[5], rtc.datetime()[6])) rtcdate=rfecha() #---------------------------------Oled------ i2c = SoftI2C(scl=Pin(4), sda=Pin(16)) # pines I2C oled = OLED.SSD1306_I2C(128,64,i2c) #-----------------------------------DHT------- pindht =Pin(15, Pin.IN) dht11 = dht.DHT11(pindht) #-----------------------------------DS18B20---------- ds_pin=Pin(5) ds = ds18x20.DS18X20(onewire.OneWire(ds_pin)) roms = ds.scan() #-----------------------------------mocs------------------ moc1=Pin(27, Pin.OUT) moc2=Pin(32, Pin.OUT) #-----------------------------------Botones-------------- btn1=Pin(23, Pin.IN, Pin.PULL_UP) # 1 AL OPRIMIR 0 btn2=Pin(22, Pin.IN, Pin.PULL_DOWN)# 0 AL OPRIMIR 1 def ftemp(): global temp print(round(temp,2)) utime.sleep_ms(200) if btn1.value()==0: temp=temp+0.1 if btn2.value()==1: temp=temp-0.1 def calor(): if t >= temp or t2 >= temp: moc1.value(0) else: utime.sleep_ms(500) moc1.value(1) print("Ajustando Temperatura") rfecha() rhora() def motor(): utime.sleep(2) moc2.value(1) utime.sleep(2) moc2.value(0) while True: ftemp() utime.sleep(1) dht11.measure() t=dht11.temperature() h=dht11.humidity() #----------------------------------DS18B20---------- ds.convert_temp() utime.sleep_ms(750) #The reading temperature needs at least 750ms for rom in roms: oled.fill(0) t2=ds.read_temp(rom) oled.text("T2: "+ str(round(t2,2)),5,30) oled.text("T1: "+ str(t) +" C",5,20) oled.text("Hum:"+ str(h) +" %",5,50) oled.text("tem:"+ str(round(temp,2)) +" C",5,0) oled.show() motor() calor() time.sleep(4) respuesta = urequests.get(url+"&field1="+str(temp)+"&field2="+str(t)+"&field3="+str(t2)+"&field4="+str(h)) print(respuesta.text) print (respuesta.status_code) respuesta.close () if __name__==("__main__"): main()

30.040323

112

0.506577

from machine import SoftI2C, Pin, RTC import onewire, ds18x20, time import utime, dht, network, urequests import OLED, ntptime temp=30 url = "https://api.thingspeak.com/update?api_key=CTVG0E49RI7RSV78" def conectaWifi (red, password): global miRed miRed = network.WLAN(network.STA_IF) if not miRed.isconnected(): miRed.active(True) miRed.connect(red, password) print('Conectando a la red', red +"…") timeout = time.time () while not miRed.isconnected(): if (time.ticks_diff (time.time (), timeout) > 10): return False return True if conectaWifi (".", "V5MVH6F3SVDU"): print ("Conexión exitosa!") print('Datos de la red (IP/netmask/gw/DNS):', miRed.ifconfig()) ntptime.settime() rtc= RTC() (year, month, mday, weekday, hour, minute, second, milisecond)=rtc.datetime() rtc.init((year, month, mday, weekday, hour-5, minute, second, milisecond)) def rfecha(): print ("Fecha: {:02d}/{:02d}/{}".format(rtc.datetime()[2], rtc.datetime()[1], rtc.datetime()[0])) def rhora(): print ("Hora: {:02d}:{:02d}:{:02d}".format(rtc.datetime()[4], rtc.datetime()[5], rtc.datetime()[6])) rtcdate=rfecha() i2c = SoftI2C(scl=Pin(4), sda=Pin(16)) oled = OLED.SSD1306_I2C(128,64,i2c) pindht =Pin(15, Pin.IN) dht11 = dht.DHT11(pindht) ds_pin=Pin(5) ds = ds18x20.DS18X20(onewire.OneWire(ds_pin)) roms = ds.scan() moc1=Pin(27, Pin.OUT) moc2=Pin(32, Pin.OUT) btn1=Pin(23, Pin.IN, Pin.PULL_UP) btn2=Pin(22, Pin.IN, Pin.PULL_DOWN) def ftemp(): global temp print(round(temp,2)) utime.sleep_ms(200) if btn1.value()==0: temp=temp+0.1 if btn2.value()==1: temp=temp-0.1 def calor(): if t >= temp or t2 >= temp: moc1.value(0) else: utime.sleep_ms(500) moc1.value(1) print("Ajustando Temperatura") rfecha() rhora() def motor(): utime.sleep(2) moc2.value(1) utime.sleep(2) moc2.value(0) while True: ftemp() utime.sleep(1) dht11.measure() t=dht11.temperature() h=dht11.humidity() ds.convert_temp() utime.sleep_ms(750) for rom in roms: oled.fill(0) t2=ds.read_temp(rom) oled.text("T2: "+ str(round(t2,2)),5,30) oled.text("T1: "+ str(t) +" C",5,20) oled.text("Hum:"+ str(h) +" %",5,50) oled.text("tem:"+ str(round(temp,2)) +" C",5,0) oled.show() motor() calor() time.sleep(4) respuesta = urequests.get(url+"&field1="+str(temp)+"&field2="+str(t)+"&field3="+str(t2)+"&field4="+str(h)) print(respuesta.text) print (respuesta.status_code) respuesta.close () if __name__==("__main__"): main()

true

f73900beec9d1bdce44f7fe9ddbae6a26c87436c

34,396

py

Python

scripts/interp_sea_level_ICESat2_ATL07.py

mrsiegfried/read-ICESat-2

1406b92691d284616ca6c9d72646eca4592d1f1d

[ "MIT" ]

null

scripts/interp_sea_level_ICESat2_ATL07.py

mrsiegfried/read-ICESat-2

1406b92691d284616ca6c9d72646eca4592d1f1d

[ "MIT" ]

null

scripts/interp_sea_level_ICESat2_ATL07.py

mrsiegfried/read-ICESat-2

1406b92691d284616ca6c9d72646eca4592d1f1d

[ "MIT" ]

null

#!/usr/bin/env python u""" interp_sea_level_ICESat2_ATL07.py Written by Tyler Sutterley (05/2021) Interpolates sea level anomalies (sla), absolute dynamic topography (adt) and mean dynamic topography (mdt) to times and locations of ICESat-2 ATL07 data https://www.aviso.altimetry.fr/en/data/products/sea-surface-height-products/ global/msla-h.html ftp://ftp.sltac.cls.fr/Core/SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047/ dataset-duacs-rep-global-merged-allsat-phy-l4-v3 Note that the AVISO sea level data are gzip compressed netCDF4 files COMMAND LINE OPTIONS: -D X, --directory X: Working data directory -V, --verbose: Output information about each created file -M X, --mode X: Permission mode of directories and files created PYTHON DEPENDENCIES: numpy: Scientific Computing Tools For Python https://numpy.org https://numpy.org/doc/stable/user/numpy-for-matlab-users.html pyproj: Python interface to PROJ library https://pypi.org/project/pyproj/ scikit-learn: Machine Learning in Python https://scikit-learn.org/stable/index.html https://github.com/scikit-learn/scikit-learn h5py: Python interface for Hierarchal Data Format 5 (HDF5) https://h5py.org netCDF4: Python interface to the netCDF C library https://unidata.github.io/netcdf4-python/netCDF4/index.html PROGRAM DEPENDENCIES: read_ICESat2_ATL07.py: reads ICESat-2 sea ice height data files time.py: utilities for calculating time operations utilities.py: download and management utilities for syncing files UPDATE HISTORY: Updated 05/2021: print full path of output filename Written 03/2021 """ from __future__ import print_function import os import re import gzip import h5py import pyproj import netCDF4 import argparse import datetime import numpy as np import sklearn.neighbors import icesat2_toolkit.time from icesat2_toolkit.read_ICESat2_ATL07 import read_HDF5_ATL07 #-- PURPOSE: set the hemisphere of interest based on the granule def set_hemisphere(GRANULE): if GRANULE in ('10','11','12'): projection_flag = 'S' elif GRANULE in ('03','04','05'): projection_flag = 'N' return projection_flag #-- PURPOSE: interpolates to coordinates with inverse distance weighting def inverse_distance(x, y, z, xi, yi, SEARCH='BallTree', N=10, POWER=2.0): #-- number of output points npts = len(xi) #-- create neighbors object for coordinates if (SEARCH == 'BallTree'): tree = sklearn.neighbors.BallTree(np.c_[x,y]) elif (SEARCH == 'KDTree'): tree = sklearn.neighbors.KDTree(np.c_[x,y]) #-- query the search tree to find the N closest points dist,indices = tree.query(np.c_[xi,yi], k=N, return_distance=True) #-- normalized weights if POWER > 0 (typically between 1 and 3) #-- in the inverse distance weighting power_inverse_distance = dist**(-POWER) s = np.sum(power_inverse_distance, axis=1) w = power_inverse_distance/np.broadcast_to(s[:,None],(npts,N)) #-- calculate interpolated fields by inverse distance weighting return np.sum(w*z[indices],axis=1) #-- PURPOSE interpolate sea level anomalies to lat/lon and then to time def interpolate_sea_level(base_dir, xi, yi, CJD, HEM): #-- EPSG projections for converting lat/lon to polar stereographic EPSG = dict(N=3413,S=3031) #-- pyproj transformer for converting to polar stereographic crs1 = pyproj.CRS.from_string('epsg:4326') crs2 = pyproj.CRS.from_string(EPSG[HEM]) transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True) #-- interpolate mean dynamic topography input_file = 'mdt_cnes_cls2013_global.nc.gz' #-- read bytes from compressed file fd = gzip.open(os.path.join(base_dir,input_file),'rb') #-- dictionary with input fields dinput = {} #-- read netCDF file for mean dynamic topography with netCDF4.Dataset('mdt', mode='r', memory=fd.read()) as fileID: dinput['lon'] = fileID['lon'][:].copy() dinput['lat'] = fileID['lat'][:].copy() dinput['mdt'] = np.ma.array(fileID['mdt'][0,:,:].copy(), fill_value=fileID['mdt']._FillValue) dinput['mdt'].mask = (dinput['mdt'].data == dinput['mdt'].fill_value) #-- close the compressed file objects fd.close() #-- create 2-D grid coordinates from longitude and latitude vectors gridlon,gridlat = np.meshgrid(dinput['lon'],dinput['lat']) #-- convert from latitude/longitude into polar stereographic xg,yg = transformer.transform(gridlon,gridlat) #-- reduce to local coordinates to improve computational time gridmask = np.logical_not(dinput['mdt'].mask) if (HEM.upper() == 'N'): gridmask &= (gridlat >= 50.0) elif (HEM.upper() == 'S'): gridmask &= (gridlat <= -50.0) indy,indx = np.nonzero(gridmask) #-- calculate mean dynamic topography by inverse distance weighting MDT = inverse_distance(xg[indy,indx], yg[indy,indx], dinput['mdt'].data[indy,indx], xi, yi) #-- CNES Julian Days before and after measurement CJD1 = np.floor(CJD) #-- scale for linearly interpolating to date dt = (CJD - CJD1[0]) #-- output sea level anomaly and absolute dynamic topography SLA = np.zeros_like(CJD) ADT = np.zeros_like(CJD) #-- for the range of dates for day in range(2): #-- convert from CNES Julians Days to calendar dates for time JD1 = CJD1 + day + 2433282.5 YY,MM,DD,HH,MN,SS = icesat2_toolkit.time.convert_julian(JD1[0], FORMAT='tuple', ASTYPE=int) #-- sea level directory ddir = os.path.join(base_dir, '{0:0.0f}'.format(YY)) #-- input file for day before the measurement regex = re.compile(('dt_global_allsat_phy_l4_{0:4d}{1:02d}{2:02d}_' '(\d{{4}})(\d{{2}})(\d{{2}}).nc.gz').format(YY,MM,DD)) input_file, = [fi for fi in os.listdir(ddir) if regex.match(fi)] #-- dictionary with input fields dinput = {} #-- read bytes from compressed file fd = gzip.open(os.path.join(ddir,input_file),'rb') #-- read netCDF file for time with netCDF4.Dataset('sla', mode='r', memory=fd.read()) as fileID: dinput['lon'] = fileID['lon'][:].copy() dinput['lat'] = fileID['lat'][:].copy() dinput['sla'] = np.ma.array(fileID['sla'][0,:,:].copy(), fill_value=fileID['sla']._FillValue) dinput['adt'] = np.ma.array(fileID['adt'][0,:,:].copy(), fill_value=fileID['adt']._FillValue) #-- close the compressed file objects fd.close() #-- for each variable to interpolate out = {} for var in ['sla','adt']: #-- reduce to local coordinates to improve computational time gridmask = np.logical_not(dinput[var].mask) if (HEM.upper() == 'N'): gridmask &= (gridlat >= 50.0) elif (HEM.upper() == 'S'): gridmask &= (gridlat <= -50.0) indy,indx = np.nonzero(gridmask) #-- calculate variable by inverse distance weighting out[var] = inverse_distance(xg[indy,indx], yg[indy,indx], dinput[var].data[indy,indx], xi, yi) #-- linearly interpolate to date for iteration SLA += out['sla']*(2.0*dt*day - dt - day + 1.0) ADT += out['adt']*(2.0*dt*day - dt - day + 1.0) #-- return interpolated values return dict(h_mdt=MDT,h_sla=SLA,h_adt=ADT) #-- PURPOSE: read ICESat-2 sea ice height (ATL07) from NSIDC #-- interpolate AVISO sea level at points and times def interp_sea_level_ICESat2(base_dir, FILE, VERBOSE=False, MODE=0o775): #-- read data from input_file print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None IS2_atl07_mds,IS2_atl07_attrs,IS2_atl07_beams = read_HDF5_ATL07(FILE, ATTRIBUTES=True) DIRECTORY = os.path.dirname(FILE) #-- extract parameters from ICESat-2 ATLAS HDF5 sea ice file name rx = re.compile(r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})' r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$') SUB,PRD,HMN,YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX=rx.findall(FILE).pop() #-- set the hemisphere flag based on ICESat-2 granule HEM = set_hemisphere(HMN) #-- HDF5 file attributes attrib = {} #-- mean dynamic topography attrib['h_mdt'] = {} attrib['h_mdt']['long_name'] = 'Mean Dynamic Topography' attrib['h_mdt']['description'] = 'Sea surface height above geoid' attrib['h_mdt']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') #-- sea level anomalies attrib['h_sla'] = {} attrib['h_sla']['long_name'] = 'Sea Level Anomaly' attrib['h_sla']['description'] = 'Sea surface anomalies' attrib['h_sla']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') #-- absolute dynamic topography attrib['h_adt'] = {} attrib['h_adt']['long_name'] = 'Absolute Dynamic Topography' attrib['h_adt']['description'] = ('Sea surface height above geoid calculated ' 'by adding the mean dynamic topography to the sea level anomalies') attrib['h_adt']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') #-- EPSG projections for converting lat/lon to polar stereographic EPSG = dict(N=3413,S=3031) #-- pyproj transformer for converting to polar stereographic crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(4326)) crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(EPSG[HEM])) transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True) #-- number of GPS seconds between the GPS epoch #-- and ATLAS Standard Data Product (SDP) epoch atlas_sdp_gps_epoch = IS2_atl07_mds['ancillary_data']['atlas_sdp_gps_epoch'] #-- copy variables for outputting to HDF5 file IS2_atl07_corr = {} IS2_atl07_fill = {} IS2_atl07_dims = {} IS2_atl07_corr_attrs = {} #-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC) #-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC) #-- Add this value to delta time parameters to compute full gps_seconds IS2_atl07_corr['ancillary_data'] = {} IS2_atl07_corr_attrs['ancillary_data'] = {} for key in ['atlas_sdp_gps_epoch']: #-- get each HDF5 variable IS2_atl07_corr['ancillary_data'][key] = IS2_atl07_mds['ancillary_data'][key] #-- Getting attributes of group and included variables IS2_atl07_corr_attrs['ancillary_data'][key] = {} for att_name,att_val in IS2_atl07_attrs['ancillary_data'][key].items(): IS2_atl07_corr_attrs['ancillary_data'][key][att_name] = att_val #-- for each input beam within the file for gtx in sorted(IS2_atl07_beams): #-- output data dictionaries for beam IS2_atl07_corr[gtx] = dict(sea_ice_segments={}) IS2_atl07_fill[gtx] = dict(sea_ice_segments={}) IS2_atl07_dims[gtx] = dict(sea_ice_segments={}) IS2_atl07_corr_attrs[gtx] = dict(sea_ice_segments={}) #-- number of segments val = IS2_atl07_mds[gtx]['sea_ice_segments'] n_seg = len(val['height_segment_id']) #-- convert time from ATLAS SDP to CNES JD #-- days relative to 1950-01-01T00:00:00 gps_seconds = atlas_sdp_gps_epoch + val['delta_time'] leap_seconds = icesat2_toolkit.time.count_leap_seconds(gps_seconds) cnes_time = icesat2_toolkit.time.convert_delta_time(gps_seconds-leap_seconds, epoch1=(1980,1,6,0,0,0), epoch2=(1950,1,1,0,0,0), scale=1.0/86400.0) #-- extract lat/lon and convert to polar stereographic X,Y = transformer.transform(val['longitude'],val['latitude']) #-- interpolate sea level anomalies and dynamic topographies interp = interpolate_sea_level(base_dir,X,Y,cnes_time,HEM) #-- group attributes for beam IS2_atl07_corr_attrs[gtx]['Description'] = IS2_atl07_attrs[gtx]['Description'] IS2_atl07_corr_attrs[gtx]['atlas_pce'] = IS2_atl07_attrs[gtx]['atlas_pce'] IS2_atl07_corr_attrs[gtx]['atlas_beam_type'] = IS2_atl07_attrs[gtx]['atlas_beam_type'] IS2_atl07_corr_attrs[gtx]['groundtrack_id'] = IS2_atl07_attrs[gtx]['groundtrack_id'] IS2_atl07_corr_attrs[gtx]['atmosphere_profile'] = IS2_atl07_attrs[gtx]['atmosphere_profile'] IS2_atl07_corr_attrs[gtx]['atlas_spot_number'] = IS2_atl07_attrs[gtx]['atlas_spot_number'] IS2_atl07_corr_attrs[gtx]['sc_orientation'] = IS2_atl07_attrs[gtx]['sc_orientation'] #-- group attributes for sea_ice_segments IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['Description'] = ("Top group for sea " "ice segments as computed by the ATBD algorithm.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['data_rate'] = ("Data within this " "group are stored at the variable segment rate.") #-- geolocation, time and segment ID #-- delta time IS2_atl07_corr[gtx]['sea_ice_segments']['delta_time'] = val['delta_time'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['delta_time'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['delta_time'] = None IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['units'] = "seconds since 2018-01-01" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['long_name'] = "Elapsed GPS seconds" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['standard_name'] = "time" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['source'] = "telemetry" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['calendar'] = "standard" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['description'] = ("Number of " "GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch " "offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS " "seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP " "epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time " "parameters, the time in gps_seconds relative to the GPS epoch can be computed.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['coordinates'] = \ "height_segment_id latitude longitude" #-- latitude IS2_atl07_corr[gtx]['sea_ice_segments']['latitude'] = val['latitude'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['latitude'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['latitude'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['units'] = "degrees_north" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['contentType'] = "physicalMeasurement" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['long_name'] = "Latitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['standard_name'] = "latitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['description'] = ("Latitude of " "segment center") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['valid_min'] = -90.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['valid_max'] = 90.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['coordinates'] = \ "height_segment_id delta_time longitude" #-- longitude IS2_atl07_corr[gtx]['sea_ice_segments']['longitude'] = val['longitude'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['longitude'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['longitude'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['units'] = "degrees_east" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['contentType'] = "physicalMeasurement" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['long_name'] = "Longitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['standard_name'] = "longitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['description'] = ("Longitude of " "segment center") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['valid_min'] = -180.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['valid_max'] = 180.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['coordinates'] = \ "height_segment_id delta_time latitude" #-- segment ID IS2_atl07_corr[gtx]['sea_ice_segments']['height_segment_id'] = val['height_segment_id'] IS2_atl07_fill[gtx]['sea_ice_segments']['height_segment_id'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['height_segment_id'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['long_name'] = \ "Identifier of each height segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['description'] = \ "Identifier of each height segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['coordinates'] = \ "delta_time latitude longitude" #-- geolocation segment beginning IS2_atl07_corr[gtx]['sea_ice_segments']['geoseg_beg'] = val['geoseg_beg'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_beg'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_beg'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['long_name'] = "Beginning GEOSEG" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['description'] = \ "Geolocation segment (geoseg) ID associated with the first photon used in this sea ice segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['coordinates'] = \ "height_segment_id delta_time latitude longitude" #-- geolocation segment ending IS2_atl07_corr[gtx]['sea_ice_segments']['geoseg_end'] = val['geoseg_end'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_end'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_end'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['long_name'] = "Ending GEOSEG" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['description'] = \ "Geolocation segment (geoseg) ID associated with the last photon used in this sea ice segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['coordinates'] = \ "height_segment_id delta_time latitude longitude" #-- along track distance IS2_atl07_corr[gtx]['sea_ice_segments']['seg_dist_x'] = val['seg_dist_x'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['seg_dist_x'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['seg_dist_x'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['units'] = "meters" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['long_name'] = "Along track distance" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['description'] = \ "Along-track distance from the equator crossing to the segment center." IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['coordinates'] = \ "height_segment_id delta_time latitude longitude" #-- geophysical variables IS2_atl07_corr[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical']['Description'] = ("Contains geophysical " "parameters and corrections used to correct photon heights for geophysical effects, such as tides.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical']['data_rate'] = ("Data within this group " "are stored at the sea_ice_height segment rate.") #-- interpolated sea level products for key,val in interp.items(): #-- copy output variables sea_level = np.ma.zeros((n_seg)) sea_level.data[:] = np.copy(val) #-- replace nan values with fill value sea_level.mask = np.isnan(sea_level.data) sea_level.data[sea_level.mask] = sea_level.fill_value #-- add to output IS2_atl07_corr[gtx]['sea_ice_segments']['geophysical'][key] = sea_level.copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'][key] = sea_level.fill_value IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'][key] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['units'] = "meters" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['long_name'] = attrib[key]['long_name'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['description'] = attrib[key]['description'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['source'] = 'AVISO/Copernicus' IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['reference'] = attrib[key]['reference'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['coordinates'] = \ "../height_segment_id ../delta_time ../latitude ../longitude" #-- output HDF5 files with interpolated sea level data fargs = (PRD,HEM,'AVISO_SEA_LEVEL',YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX) file_format = '{0}-{1}_{2}_{3}{4}{5}{6}{7}{8}_{9}{10}{11}_{12}_{13}{14}.h5' output_file = os.path.join(DIRECTORY,file_format.format(*fargs)) #-- print file information print('\t{0}'.format(output_file)) if VERBOSE else None HDF5_ATL07_corr_write(IS2_atl07_corr, IS2_atl07_corr_attrs, CLOBBER=True, INPUT=os.path.basename(FILE), FILL_VALUE=IS2_atl07_fill, DIMENSIONS=IS2_atl07_dims, FILENAME=output_file) #-- change the permissions mode os.chmod(output_file, MODE) #-- PURPOSE: outputting the correction values for ICESat-2 data to HDF5 def HDF5_ATL07_corr_write(IS2_atl07_corr, IS2_atl07_attrs, INPUT=None, FILENAME='', FILL_VALUE=None, DIMENSIONS=None, CLOBBER=False): #-- setting HDF5 clobber attribute if CLOBBER: clobber = 'w' else: clobber = 'w-' #-- open output HDF5 file fileID = h5py.File(os.path.expanduser(FILENAME), clobber) #-- create HDF5 records h5 = {} #-- number of GPS seconds between the GPS epoch (1980-01-06T00:00:00Z UTC) #-- and ATLAS Standard Data Product (SDP) epoch (2018-01-01T00:00:00Z UTC) h5['ancillary_data'] = {} for k,v in IS2_atl07_corr['ancillary_data'].items(): #-- Defining the HDF5 dataset variables val = 'ancillary_data/{0}'.format(k) h5['ancillary_data'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') #-- add HDF5 variable attributes for att_name,att_val in IS2_atl07_attrs['ancillary_data'][k].items(): h5['ancillary_data'][k].attrs[att_name] = att_val #-- write each output beam beams = [k for k in IS2_atl07_corr.keys() if bool(re.match(r'gt\d[lr]',k))] for gtx in beams: fileID.create_group(gtx) #-- add HDF5 group attributes for beam for att_name in ['Description','atlas_pce','atlas_beam_type', 'groundtrack_id','atmosphere_profile','atlas_spot_number', 'sc_orientation']: fileID[gtx].attrs[att_name] = IS2_atl07_attrs[gtx][att_name] #-- create sea_ice_segments group fileID[gtx].create_group('sea_ice_segments') h5[gtx] = dict(sea_ice_segments={}) for att_name in ['Description','data_rate']: att_val = IS2_atl07_attrs[gtx]['sea_ice_segments'][att_name] fileID[gtx]['sea_ice_segments'].attrs[att_name] = att_val #-- delta_time, geolocation and segment identification variables for k in ['delta_time','latitude','longitude','height_segment_id', 'geoseg_beg','geoseg_end','seg_dist_x']: #-- values and attributes v = IS2_atl07_corr[gtx]['sea_ice_segments'][k] attrs = IS2_atl07_attrs[gtx]['sea_ice_segments'][k] fillvalue = FILL_VALUE[gtx]['sea_ice_segments'][k] #-- Defining the HDF5 dataset variables val = '{0}/{1}/{2}'.format(gtx,'sea_ice_segments',k) if fillvalue: h5[gtx]['sea_ice_segments'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, fillvalue=fillvalue, compression='gzip') else: h5[gtx]['sea_ice_segments'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') #-- create or attach dimensions for HDF5 variable if DIMENSIONS[gtx]['sea_ice_segments'][k]: #-- attach dimensions for i,dim in enumerate(DIMENSIONS[gtx]['sea_ice_segments'][k]): h5[gtx]['sea_ice_segments'][k].dims[i].attach_scale( h5[gtx]['sea_ice_segments'][dim]) else: #-- make dimension h5[gtx]['sea_ice_segments'][k].make_scale(k) #-- add HDF5 variable attributes for att_name,att_val in attrs.items(): h5[gtx]['sea_ice_segments'][k].attrs[att_name] = att_val #-- add to geophysical corrections key = 'geophysical' fileID[gtx]['sea_ice_segments'].create_group(key) h5[gtx]['sea_ice_segments'][key] = {} for att_name in ['Description','data_rate']: att_val=IS2_atl07_attrs[gtx]['sea_ice_segments'][key][att_name] fileID[gtx]['sea_ice_segments'][key].attrs[att_name] = att_val for k,v in IS2_atl07_corr[gtx]['sea_ice_segments'][key].items(): #-- attributes attrs = IS2_atl07_attrs[gtx]['sea_ice_segments'][key][k] fillvalue = FILL_VALUE[gtx]['sea_ice_segments'][key][k] #-- Defining the HDF5 dataset variables val = '{0}/{1}/{2}/{3}'.format(gtx,'sea_ice_segments',key,k) if fillvalue: h5[gtx]['sea_ice_segments'][key][k] = \ fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, fillvalue=fillvalue, compression='gzip') else: h5[gtx]['sea_ice_segments'][key][k] = \ fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') #-- attach dimensions for i,dim in enumerate(DIMENSIONS[gtx]['sea_ice_segments'][key][k]): h5[gtx]['sea_ice_segments'][key][k].dims[i].attach_scale( h5[gtx]['sea_ice_segments'][dim]) #-- add HDF5 variable attributes for att_name,att_val in attrs.items(): h5[gtx]['sea_ice_segments'][key][k].attrs[att_name] = att_val #-- HDF5 file title fileID.attrs['featureType'] = 'trajectory' fileID.attrs['title'] = 'ATLAS/ICESat-2 L3A Sea Ice Height' fileID.attrs['summary'] = ('Estimates of the sea ice correction parameters ' 'needed to interpret and assess the quality of sea height estimates.') fileID.attrs['description'] = ('The data set (ATL07) contains along-track ' 'heights for sea ice and open water leads (at varying length scales) ' 'relative to the WGS84 ellipsoid (ITRF2014 reference frame) after ' 'adjustment for geoidal and tidal variations, and inverted barometer ' 'effects.') date_created = datetime.datetime.today() fileID.attrs['date_created'] = date_created.isoformat() project = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2' fileID.attrs['project'] = project platform = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2' fileID.attrs['project'] = platform #-- add attribute for elevation instrument and designated processing level instrument = 'ATLAS > Advanced Topographic Laser Altimeter System' fileID.attrs['instrument'] = instrument fileID.attrs['source'] = 'Spacecraft' fileID.attrs['references'] = 'https://nsidc.org/data/icesat-2' fileID.attrs['processing_level'] = '4' #-- add attributes for input ATL07 file fileID.attrs['input_files'] = os.path.basename(INPUT) #-- find geospatial and temporal ranges lnmn,lnmx,ltmn,ltmx,tmn,tmx = (np.inf,-np.inf,np.inf,-np.inf,np.inf,-np.inf) for gtx in beams: lon = IS2_atl07_corr[gtx]['sea_ice_segments']['longitude'] lat = IS2_atl07_corr[gtx]['sea_ice_segments']['latitude'] delta_time = IS2_atl07_corr[gtx]['sea_ice_segments']['delta_time'] #-- setting the geospatial and temporal ranges lnmn = lon.min() if (lon.min() < lnmn) else lnmn lnmx = lon.max() if (lon.max() > lnmx) else lnmx ltmn = lat.min() if (lat.min() < ltmn) else ltmn ltmx = lat.max() if (lat.max() > ltmx) else ltmx tmn = delta_time.min() if (delta_time.min() < tmn) else tmn tmx = delta_time.max() if (delta_time.max() > tmx) else tmx #-- add geospatial and temporal attributes fileID.attrs['geospatial_lat_min'] = ltmn fileID.attrs['geospatial_lat_max'] = ltmx fileID.attrs['geospatial_lon_min'] = lnmn fileID.attrs['geospatial_lon_max'] = lnmx fileID.attrs['geospatial_lat_units'] = "degrees_north" fileID.attrs['geospatial_lon_units'] = "degrees_east" fileID.attrs['geospatial_ellipsoid'] = "WGS84" fileID.attrs['date_type'] = 'UTC' fileID.attrs['time_type'] = 'CCSDS UTC-A' #-- convert start and end time from ATLAS SDP seconds into GPS seconds atlas_sdp_gps_epoch=IS2_atl07_corr['ancillary_data']['atlas_sdp_gps_epoch'] gps_seconds = atlas_sdp_gps_epoch + np.array([tmn,tmx]) #-- calculate leap seconds leaps = icesat2_toolkit.time.count_leap_seconds(gps_seconds) #-- convert from seconds since 1980-01-06T00:00:00 to Modified Julian days MJD = icesat2_toolkit.time.convert_delta_time(gps_seconds - leaps, epoch1=(1980,1,6,0,0,0), epoch2=(1858,11,17,0,0,0), scale=1.0/86400.0) #-- convert to calendar date YY,MM,DD,HH,MN,SS = icesat2_toolkit.time.convert_julian(MJD + 2400000.5, FORMAT='tuple') #-- add attributes with measurement date start, end and duration tcs = datetime.datetime(int(YY[0]), int(MM[0]), int(DD[0]), int(HH[0]), int(MN[0]), int(SS[0]), int(1e6*(SS[0] % 1))) fileID.attrs['time_coverage_start'] = tcs.isoformat() tce = datetime.datetime(int(YY[1]), int(MM[1]), int(DD[1]), int(HH[1]), int(MN[1]), int(SS[1]), int(1e6*(SS[1] % 1))) fileID.attrs['time_coverage_end'] = tce.isoformat() fileID.attrs['time_coverage_duration'] = '{0:0.0f}'.format(tmx-tmn) #-- Closing the HDF5 file fileID.close() #-- Main program that calls interp_sea_level_ICESat2() def main(): #-- Read the system arguments listed after the program parser = argparse.ArgumentParser( description="""Interpolates AVISO sea level anomalies, absolute dynamic topography and mean dynamic topography to ICESat-2 ATL07 sea ice height data """ ) #-- command line parameters parser.add_argument('infile', type=lambda p: os.path.abspath(os.path.expanduser(p)), nargs='+', help='ICESat-2 ATL07 file to run') #-- directory with sea level data parser.add_argument('--directory','-D', type=lambda p: os.path.abspath(os.path.expanduser(p)), default=os.getcwd(), help='Working data directory') #-- verbosity settings #-- verbose will output information about each output file parser.add_argument('--verbose','-V', default=False, action='store_true', help='Output information about each created file') #-- permissions mode of the local files (number in octal) parser.add_argument('--mode','-M', type=lambda x: int(x,base=8), default=0o775, help='Permission mode of directories and files created') args = parser.parse_args() #-- run for each input ATL07 file for FILE in args.infile: interp_sea_level_ICESat2(args.directory, FILE, VERBOSE=args.verbose, MODE=args.mode) #-- run main program if __name__ == '__main__': main()

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from __future__ import print_function import os import re import gzip import h5py import pyproj import netCDF4 import argparse import datetime import numpy as np import sklearn.neighbors import icesat2_toolkit.time from icesat2_toolkit.read_ICESat2_ATL07 import read_HDF5_ATL07 def set_hemisphere(GRANULE): if GRANULE in ('10','11','12'): projection_flag = 'S' elif GRANULE in ('03','04','05'): projection_flag = 'N' return projection_flag def inverse_distance(x, y, z, xi, yi, SEARCH='BallTree', N=10, POWER=2.0): npts = len(xi) if (SEARCH == 'BallTree'): tree = sklearn.neighbors.BallTree(np.c_[x,y]) elif (SEARCH == 'KDTree'): tree = sklearn.neighbors.KDTree(np.c_[x,y]) dist,indices = tree.query(np.c_[xi,yi], k=N, return_distance=True) power_inverse_distance = dist**(-POWER) s = np.sum(power_inverse_distance, axis=1) w = power_inverse_distance/np.broadcast_to(s[:,None],(npts,N)) return np.sum(w*z[indices],axis=1) def interpolate_sea_level(base_dir, xi, yi, CJD, HEM): EPSG = dict(N=3413,S=3031) crs1 = pyproj.CRS.from_string('epsg:4326') crs2 = pyproj.CRS.from_string(EPSG[HEM]) transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True) input_file = 'mdt_cnes_cls2013_global.nc.gz' fd = gzip.open(os.path.join(base_dir,input_file),'rb') dinput = {} with netCDF4.Dataset('mdt', mode='r', memory=fd.read()) as fileID: dinput['lon'] = fileID['lon'][:].copy() dinput['lat'] = fileID['lat'][:].copy() dinput['mdt'] = np.ma.array(fileID['mdt'][0,:,:].copy(), fill_value=fileID['mdt']._FillValue) dinput['mdt'].mask = (dinput['mdt'].data == dinput['mdt'].fill_value) fd.close() gridlon,gridlat = np.meshgrid(dinput['lon'],dinput['lat']) xg,yg = transformer.transform(gridlon,gridlat) gridmask = np.logical_not(dinput['mdt'].mask) if (HEM.upper() == 'N'): gridmask &= (gridlat >= 50.0) elif (HEM.upper() == 'S'): gridmask &= (gridlat <= -50.0) indy,indx = np.nonzero(gridmask) MDT = inverse_distance(xg[indy,indx], yg[indy,indx], dinput['mdt'].data[indy,indx], xi, yi) CJD1 = np.floor(CJD) dt = (CJD - CJD1[0]) SLA = np.zeros_like(CJD) ADT = np.zeros_like(CJD) for day in range(2): JD1 = CJD1 + day + 2433282.5 YY,MM,DD,HH,MN,SS = icesat2_toolkit.time.convert_julian(JD1[0], FORMAT='tuple', ASTYPE=int) ddir = os.path.join(base_dir, '{0:0.0f}'.format(YY)) regex = re.compile(('dt_global_allsat_phy_l4_{0:4d}{1:02d}{2:02d}_' '(\d{{4}})(\d{{2}})(\d{{2}}).nc.gz').format(YY,MM,DD)) input_file, = [fi for fi in os.listdir(ddir) if regex.match(fi)] dinput = {} fd = gzip.open(os.path.join(ddir,input_file),'rb') with netCDF4.Dataset('sla', mode='r', memory=fd.read()) as fileID: dinput['lon'] = fileID['lon'][:].copy() dinput['lat'] = fileID['lat'][:].copy() dinput['sla'] = np.ma.array(fileID['sla'][0,:,:].copy(), fill_value=fileID['sla']._FillValue) dinput['adt'] = np.ma.array(fileID['adt'][0,:,:].copy(), fill_value=fileID['adt']._FillValue) fd.close() out = {} for var in ['sla','adt']: gridmask = np.logical_not(dinput[var].mask) if (HEM.upper() == 'N'): gridmask &= (gridlat >= 50.0) elif (HEM.upper() == 'S'): gridmask &= (gridlat <= -50.0) indy,indx = np.nonzero(gridmask) out[var] = inverse_distance(xg[indy,indx], yg[indy,indx], dinput[var].data[indy,indx], xi, yi) SLA += out['sla']*(2.0*dt*day - dt - day + 1.0) ADT += out['adt']*(2.0*dt*day - dt - day + 1.0) return dict(h_mdt=MDT,h_sla=SLA,h_adt=ADT) def interp_sea_level_ICESat2(base_dir, FILE, VERBOSE=False, MODE=0o775): print('{0} -->'.format(os.path.basename(FILE))) if VERBOSE else None IS2_atl07_mds,IS2_atl07_attrs,IS2_atl07_beams = read_HDF5_ATL07(FILE, ATTRIBUTES=True) DIRECTORY = os.path.dirname(FILE) rx = re.compile(r'(processed_)?(ATL\d{2})-(\d{2})_(\d{4})(\d{2})(\d{2})' r'(\d{2})(\d{2})(\d{2})_(\d{4})(\d{2})(\d{2})_(\d{3})_(\d{2})(.*?).h5$') SUB,PRD,HMN,YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX=rx.findall(FILE).pop() HEM = set_hemisphere(HMN) attrib = {} attrib['h_mdt'] = {} attrib['h_mdt']['long_name'] = 'Mean Dynamic Topography' attrib['h_mdt']['description'] = 'Sea surface height above geoid' attrib['h_mdt']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') attrib['h_sla'] = {} attrib['h_sla']['long_name'] = 'Sea Level Anomaly' attrib['h_sla']['description'] = 'Sea surface anomalies' attrib['h_sla']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') attrib['h_adt'] = {} attrib['h_adt']['long_name'] = 'Absolute Dynamic Topography' attrib['h_adt']['description'] = ('Sea surface height above geoid calculated ' 'by adding the mean dynamic topography to the sea level anomalies') attrib['h_adt']['reference'] = ('https://www.aviso.altimetry.fr/en/data/' 'products/sea-surface-height-products/global/msla-h.html') EPSG = dict(N=3413,S=3031) crs1 = pyproj.CRS.from_string("epsg:{0:d}".format(4326)) crs2 = pyproj.CRS.from_string("epsg:{0:d}".format(EPSG[HEM])) transformer = pyproj.Transformer.from_crs(crs1, crs2, always_xy=True) atlas_sdp_gps_epoch = IS2_atl07_mds['ancillary_data']['atlas_sdp_gps_epoch'] IS2_atl07_corr = {} IS2_atl07_fill = {} IS2_atl07_dims = {} IS2_atl07_corr_attrs = {} IS2_atl07_corr['ancillary_data'] = {} IS2_atl07_corr_attrs['ancillary_data'] = {} for key in ['atlas_sdp_gps_epoch']: IS2_atl07_corr['ancillary_data'][key] = IS2_atl07_mds['ancillary_data'][key] IS2_atl07_corr_attrs['ancillary_data'][key] = {} for att_name,att_val in IS2_atl07_attrs['ancillary_data'][key].items(): IS2_atl07_corr_attrs['ancillary_data'][key][att_name] = att_val for gtx in sorted(IS2_atl07_beams): IS2_atl07_corr[gtx] = dict(sea_ice_segments={}) IS2_atl07_fill[gtx] = dict(sea_ice_segments={}) IS2_atl07_dims[gtx] = dict(sea_ice_segments={}) IS2_atl07_corr_attrs[gtx] = dict(sea_ice_segments={}) val = IS2_atl07_mds[gtx]['sea_ice_segments'] n_seg = len(val['height_segment_id']) gps_seconds = atlas_sdp_gps_epoch + val['delta_time'] leap_seconds = icesat2_toolkit.time.count_leap_seconds(gps_seconds) cnes_time = icesat2_toolkit.time.convert_delta_time(gps_seconds-leap_seconds, epoch1=(1980,1,6,0,0,0), epoch2=(1950,1,1,0,0,0), scale=1.0/86400.0) X,Y = transformer.transform(val['longitude'],val['latitude']) interp = interpolate_sea_level(base_dir,X,Y,cnes_time,HEM) IS2_atl07_corr_attrs[gtx]['Description'] = IS2_atl07_attrs[gtx]['Description'] IS2_atl07_corr_attrs[gtx]['atlas_pce'] = IS2_atl07_attrs[gtx]['atlas_pce'] IS2_atl07_corr_attrs[gtx]['atlas_beam_type'] = IS2_atl07_attrs[gtx]['atlas_beam_type'] IS2_atl07_corr_attrs[gtx]['groundtrack_id'] = IS2_atl07_attrs[gtx]['groundtrack_id'] IS2_atl07_corr_attrs[gtx]['atmosphere_profile'] = IS2_atl07_attrs[gtx]['atmosphere_profile'] IS2_atl07_corr_attrs[gtx]['atlas_spot_number'] = IS2_atl07_attrs[gtx]['atlas_spot_number'] IS2_atl07_corr_attrs[gtx]['sc_orientation'] = IS2_atl07_attrs[gtx]['sc_orientation'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['Description'] = ("Top group for sea " "ice segments as computed by the ATBD algorithm.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['data_rate'] = ("Data within this " "group are stored at the variable segment rate.") IS2_atl07_corr[gtx]['sea_ice_segments']['delta_time'] = val['delta_time'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['delta_time'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['delta_time'] = None IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['units'] = "seconds since 2018-01-01" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['long_name'] = "Elapsed GPS seconds" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['standard_name'] = "time" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['source'] = "telemetry" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['calendar'] = "standard" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['description'] = ("Number of " "GPS seconds since the ATLAS SDP epoch. The ATLAS Standard Data Products (SDP) epoch " "offset is defined within /ancillary_data/atlas_sdp_gps_epoch as the number of GPS " "seconds between the GPS epoch (1980-01-06T00:00:00.000000Z UTC) and the ATLAS SDP " "epoch. By adding the offset contained within atlas_sdp_gps_epoch to delta time " "parameters, the time in gps_seconds relative to the GPS epoch can be computed.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['delta_time']['coordinates'] = \ "height_segment_id latitude longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['latitude'] = val['latitude'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['latitude'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['latitude'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['units'] = "degrees_north" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['contentType'] = "physicalMeasurement" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['long_name'] = "Latitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['standard_name'] = "latitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['description'] = ("Latitude of " "segment center") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['valid_min'] = -90.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['valid_max'] = 90.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['latitude']['coordinates'] = \ "height_segment_id delta_time longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['longitude'] = val['longitude'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['longitude'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['longitude'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['units'] = "degrees_east" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['contentType'] = "physicalMeasurement" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['long_name'] = "Longitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['standard_name'] = "longitude" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['description'] = ("Longitude of " "segment center") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['valid_min'] = -180.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['valid_max'] = 180.0 IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['longitude']['coordinates'] = \ "height_segment_id delta_time latitude" IS2_atl07_corr[gtx]['sea_ice_segments']['height_segment_id'] = val['height_segment_id'] IS2_atl07_fill[gtx]['sea_ice_segments']['height_segment_id'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['height_segment_id'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['long_name'] = \ "Identifier of each height segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['description'] = \ "Identifier of each height segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['height_segment_id']['coordinates'] = \ "delta_time latitude longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['geoseg_beg'] = val['geoseg_beg'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_beg'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_beg'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['long_name'] = "Beginning GEOSEG" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['description'] = \ "Geolocation segment (geoseg) ID associated with the first photon used in this sea ice segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_beg']['coordinates'] = \ "height_segment_id delta_time latitude longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['geoseg_end'] = val['geoseg_end'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geoseg_end'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['geoseg_end'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['units'] = "1" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['long_name'] = "Ending GEOSEG" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['description'] = \ "Geolocation segment (geoseg) ID associated with the last photon used in this sea ice segment" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geoseg_end']['coordinates'] = \ "height_segment_id delta_time latitude longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['seg_dist_x'] = val['seg_dist_x'].copy() IS2_atl07_fill[gtx]['sea_ice_segments']['seg_dist_x'] = None IS2_atl07_dims[gtx]['sea_ice_segments']['seg_dist_x'] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['units'] = "meters" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['long_name'] = "Along track distance" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['description'] = \ "Along-track distance from the equator crossing to the segment center." IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['seg_dist_x']['coordinates'] = \ "height_segment_id delta_time latitude longitude" IS2_atl07_corr[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical']['Description'] = ("Contains geophysical " "parameters and corrections used to correct photon heights for geophysical effects, such as tides.") IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical']['data_rate'] = ("Data within this group " "are stored at the sea_ice_height segment rate.") for key,val in interp.items(): sea_level = np.ma.zeros((n_seg)) sea_level.data[:] = np.copy(val) sea_level.mask = np.isnan(sea_level.data) sea_level.data[sea_level.mask] = sea_level.fill_value IS2_atl07_corr[gtx]['sea_ice_segments']['geophysical'][key] = sea_level.copy() IS2_atl07_fill[gtx]['sea_ice_segments']['geophysical'][key] = sea_level.fill_value IS2_atl07_dims[gtx]['sea_ice_segments']['geophysical'][key] = ['delta_time'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key] = {} IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['units'] = "meters" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['contentType'] = "referenceInformation" IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['long_name'] = attrib[key]['long_name'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['description'] = attrib[key]['description'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['source'] = 'AVISO/Copernicus' IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['reference'] = attrib[key]['reference'] IS2_atl07_corr_attrs[gtx]['sea_ice_segments']['geophysical'][key]['coordinates'] = \ "../height_segment_id ../delta_time ../latitude ../longitude" fargs = (PRD,HEM,'AVISO_SEA_LEVEL',YY,MM,DD,HH,MN,SS,TRK,CYCL,SN,RL,VERS,AUX) file_format = '{0}-{1}_{2}_{3}{4}{5}{6}{7}{8}_{9}{10}{11}_{12}_{13}{14}.h5' output_file = os.path.join(DIRECTORY,file_format.format(*fargs)) print('\t{0}'.format(output_file)) if VERBOSE else None HDF5_ATL07_corr_write(IS2_atl07_corr, IS2_atl07_corr_attrs, CLOBBER=True, INPUT=os.path.basename(FILE), FILL_VALUE=IS2_atl07_fill, DIMENSIONS=IS2_atl07_dims, FILENAME=output_file) os.chmod(output_file, MODE) def HDF5_ATL07_corr_write(IS2_atl07_corr, IS2_atl07_attrs, INPUT=None, FILENAME='', FILL_VALUE=None, DIMENSIONS=None, CLOBBER=False): if CLOBBER: clobber = 'w' else: clobber = 'w-' fileID = h5py.File(os.path.expanduser(FILENAME), clobber) h5 = {} h5['ancillary_data'] = {} for k,v in IS2_atl07_corr['ancillary_data'].items(): val = 'ancillary_data/{0}'.format(k) h5['ancillary_data'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') for att_name,att_val in IS2_atl07_attrs['ancillary_data'][k].items(): h5['ancillary_data'][k].attrs[att_name] = att_val beams = [k for k in IS2_atl07_corr.keys() if bool(re.match(r'gt\d[lr]',k))] for gtx in beams: fileID.create_group(gtx) for att_name in ['Description','atlas_pce','atlas_beam_type', 'groundtrack_id','atmosphere_profile','atlas_spot_number', 'sc_orientation']: fileID[gtx].attrs[att_name] = IS2_atl07_attrs[gtx][att_name] fileID[gtx].create_group('sea_ice_segments') h5[gtx] = dict(sea_ice_segments={}) for att_name in ['Description','data_rate']: att_val = IS2_atl07_attrs[gtx]['sea_ice_segments'][att_name] fileID[gtx]['sea_ice_segments'].attrs[att_name] = att_val for k in ['delta_time','latitude','longitude','height_segment_id', 'geoseg_beg','geoseg_end','seg_dist_x']: v = IS2_atl07_corr[gtx]['sea_ice_segments'][k] attrs = IS2_atl07_attrs[gtx]['sea_ice_segments'][k] fillvalue = FILL_VALUE[gtx]['sea_ice_segments'][k] val = '{0}/{1}/{2}'.format(gtx,'sea_ice_segments',k) if fillvalue: h5[gtx]['sea_ice_segments'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, fillvalue=fillvalue, compression='gzip') else: h5[gtx]['sea_ice_segments'][k] = fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') if DIMENSIONS[gtx]['sea_ice_segments'][k]: for i,dim in enumerate(DIMENSIONS[gtx]['sea_ice_segments'][k]): h5[gtx]['sea_ice_segments'][k].dims[i].attach_scale( h5[gtx]['sea_ice_segments'][dim]) else: h5[gtx]['sea_ice_segments'][k].make_scale(k) for att_name,att_val in attrs.items(): h5[gtx]['sea_ice_segments'][k].attrs[att_name] = att_val key = 'geophysical' fileID[gtx]['sea_ice_segments'].create_group(key) h5[gtx]['sea_ice_segments'][key] = {} for att_name in ['Description','data_rate']: att_val=IS2_atl07_attrs[gtx]['sea_ice_segments'][key][att_name] fileID[gtx]['sea_ice_segments'][key].attrs[att_name] = att_val for k,v in IS2_atl07_corr[gtx]['sea_ice_segments'][key].items(): attrs = IS2_atl07_attrs[gtx]['sea_ice_segments'][key][k] fillvalue = FILL_VALUE[gtx]['sea_ice_segments'][key][k] val = '{0}/{1}/{2}/{3}'.format(gtx,'sea_ice_segments',key,k) if fillvalue: h5[gtx]['sea_ice_segments'][key][k] = \ fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, fillvalue=fillvalue, compression='gzip') else: h5[gtx]['sea_ice_segments'][key][k] = \ fileID.create_dataset(val, np.shape(v), data=v, dtype=v.dtype, compression='gzip') for i,dim in enumerate(DIMENSIONS[gtx]['sea_ice_segments'][key][k]): h5[gtx]['sea_ice_segments'][key][k].dims[i].attach_scale( h5[gtx]['sea_ice_segments'][dim]) for att_name,att_val in attrs.items(): h5[gtx]['sea_ice_segments'][key][k].attrs[att_name] = att_val fileID.attrs['featureType'] = 'trajectory' fileID.attrs['title'] = 'ATLAS/ICESat-2 L3A Sea Ice Height' fileID.attrs['summary'] = ('Estimates of the sea ice correction parameters ' 'needed to interpret and assess the quality of sea height estimates.') fileID.attrs['description'] = ('The data set (ATL07) contains along-track ' 'heights for sea ice and open water leads (at varying length scales) ' 'relative to the WGS84 ellipsoid (ITRF2014 reference frame) after ' 'adjustment for geoidal and tidal variations, and inverted barometer ' 'effects.') date_created = datetime.datetime.today() fileID.attrs['date_created'] = date_created.isoformat() project = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2' fileID.attrs['project'] = project platform = 'ICESat-2 > Ice, Cloud, and land Elevation Satellite-2' fileID.attrs['project'] = platform instrument = 'ATLAS > Advanced Topographic Laser Altimeter System' fileID.attrs['instrument'] = instrument fileID.attrs['source'] = 'Spacecraft' fileID.attrs['references'] = 'https://nsidc.org/data/icesat-2' fileID.attrs['processing_level'] = '4' fileID.attrs['input_files'] = os.path.basename(INPUT) lnmn,lnmx,ltmn,ltmx,tmn,tmx = (np.inf,-np.inf,np.inf,-np.inf,np.inf,-np.inf) for gtx in beams: lon = IS2_atl07_corr[gtx]['sea_ice_segments']['longitude'] lat = IS2_atl07_corr[gtx]['sea_ice_segments']['latitude'] delta_time = IS2_atl07_corr[gtx]['sea_ice_segments']['delta_time'] lnmn = lon.min() if (lon.min() < lnmn) else lnmn lnmx = lon.max() if (lon.max() > lnmx) else lnmx ltmn = lat.min() if (lat.min() < ltmn) else ltmn ltmx = lat.max() if (lat.max() > ltmx) else ltmx tmn = delta_time.min() if (delta_time.min() < tmn) else tmn tmx = delta_time.max() if (delta_time.max() > tmx) else tmx fileID.attrs['geospatial_lat_min'] = ltmn fileID.attrs['geospatial_lat_max'] = ltmx fileID.attrs['geospatial_lon_min'] = lnmn fileID.attrs['geospatial_lon_max'] = lnmx fileID.attrs['geospatial_lat_units'] = "degrees_north" fileID.attrs['geospatial_lon_units'] = "degrees_east" fileID.attrs['geospatial_ellipsoid'] = "WGS84" fileID.attrs['date_type'] = 'UTC' fileID.attrs['time_type'] = 'CCSDS UTC-A' atlas_sdp_gps_epoch=IS2_atl07_corr['ancillary_data']['atlas_sdp_gps_epoch'] gps_seconds = atlas_sdp_gps_epoch + np.array([tmn,tmx]) leaps = icesat2_toolkit.time.count_leap_seconds(gps_seconds) MJD = icesat2_toolkit.time.convert_delta_time(gps_seconds - leaps, epoch1=(1980,1,6,0,0,0), epoch2=(1858,11,17,0,0,0), scale=1.0/86400.0) YY,MM,DD,HH,MN,SS = icesat2_toolkit.time.convert_julian(MJD + 2400000.5, FORMAT='tuple') tcs = datetime.datetime(int(YY[0]), int(MM[0]), int(DD[0]), int(HH[0]), int(MN[0]), int(SS[0]), int(1e6*(SS[0] % 1))) fileID.attrs['time_coverage_start'] = tcs.isoformat() tce = datetime.datetime(int(YY[1]), int(MM[1]), int(DD[1]), int(HH[1]), int(MN[1]), int(SS[1]), int(1e6*(SS[1] % 1))) fileID.attrs['time_coverage_end'] = tce.isoformat() fileID.attrs['time_coverage_duration'] = '{0:0.0f}'.format(tmx-tmn) fileID.close() def main(): parser = argparse.ArgumentParser( description="""Interpolates AVISO sea level anomalies, absolute dynamic topography and mean dynamic topography to ICESat-2 ATL07 sea ice height data """ ) parser.add_argument('infile', type=lambda p: os.path.abspath(os.path.expanduser(p)), nargs='+', help='ICESat-2 ATL07 file to run') parser.add_argument('--directory','-D', type=lambda p: os.path.abspath(os.path.expanduser(p)), default=os.getcwd(), help='Working data directory') parser.add_argument('--verbose','-V', default=False, action='store_true', help='Output information about each created file') parser.add_argument('--mode','-M', type=lambda x: int(x,base=8), default=0o775, help='Permission mode of directories and files created') args = parser.parse_args() for FILE in args.infile: interp_sea_level_ICESat2(args.directory, FILE, VERBOSE=args.verbose, MODE=args.mode) if __name__ == '__main__': main()

true

f739014e51e38690018ed000125672340d61618f

8,914

py

Python

src/argteller/builder/access_object.py

mozjay0619/argteller-viz

963c6d43019efb2b0e9bcdb4b3053b57cd4ff373

[ "BSD-3-Clause" ]

null

src/argteller/builder/access_object.py

mozjay0619/argteller-viz

963c6d43019efb2b0e9bcdb4b3053b57cd4ff373

[ "BSD-3-Clause" ]

7

2021-08-04T15:54:07.000Z

2021-09-17T17:40:38.000Z

src/argteller/builder/access_object.py

mozjay0619/argteller-viz

963c6d43019efb2b0e9bcdb4b3053b57cd4ff373

[ "BSD-3-Clause" ]

null

from ..tree.tree_node import TreeNode from ..tree.tree_builder import display_tree from ..widgets.dynamic_widgets import DynamicWidget from ..utils.data_structure_utils import nested_defaultdict try: from IPython.display import display import ipywidgets as widgets from ipywidgets import HBox, Label, VBox from ipywidgets import Button, Layout, HTML module_found = True except ModuleNotFoundError: module_found = False from threading import Event class AccessObject(): """Creates the DynamicWidgets based on the input tree. """ def __init__(self, root, node_dicts): self.initial_event = Event() param_setter_event = Event() self.module_found = module_found if not self.module_found: return self.root, self.node_dicts = root, node_dicts self.widget_dicts = nested_defaultdict(dict) self.widget_nodes = nested_defaultdict(dict) # this should replace widget_dicts, so we don't have duplicates # we don't have duplicates they are the same objects. self.param_vboxes = {} for topic in self.root.children: param_widgets = [] for param in topic.children: param_widget = DynamicWidget(topic.name, param, self.widget_dicts, self.widget_nodes, self.initial_event, param_setter_event) param_widgets.append(param_widget) param_vbox = VBox(param_widgets) self.param_vboxes[topic.name] = param_vbox self.initial_event.set() def display_tree(self): display_tree(self.root) def get_topics(self): return self.root.get_children_names() def get_params(self, topic=None): if topic: return list(self.widget_dicts[topic].keys()) else: l = [] self._find_params(self.root, l) return l def get_effective_params(self, topic=None): effective_params = [] params = self.get_params(topic) for param in params: widget_type = self.widget_nodes[topic][param].type if widget_type=='text': if not self.get_value(param, topic) == '': effective_params.append(param) elif widget_type=='choice': if not self.get_value(param, topic) is None: effective_params.append(param) elif widget_type=='boolean': effective_params.append(param) return effective_params def _find_params(self, node, l): depth = node.depth node_type = node.primary_type node_name = node.name if node_type != 'root': if node_type == 'topic': depth += 1 if node_type in ['param', 'optional']: if node_name not in l: l.append(node_name) for child in node.children: self._find_params(child, l) def get_value(self, param, topic=None): """This will return the string casted user input values. We will not cast this value to the castable type since the access_object is meant for the internal uses only. All widget values are internally treated as strings, so we will keep it that way. The returned values will be casted into castable types in the class decorator just before the values are returned to the user. """ return self.get_widget(param, topic).value def set_value(self, value, param, topic=None): try: widget_type = self.get_widget_node(param, topic).type except: print("The parameter [ {} ] in topic [ {} ] does not exist anymore. Skipping it.".format(param, topic)) return if widget_type=='boolean': self.get_widget(param, topic).value = eval(value) else: self.get_widget(param, topic).value = str(value) def get_vbox(self, topic): return self.param_vboxes[topic] def get_widget_node(self, param, topic=None): if topic: try: return self.widget_nodes[topic][param] except: return None else: params = [] topics = [] for topic, param_dict in self.widget_nodes.items(): if param in param_dict: params.append(param_dict[param]) topics.append(topic) if len(params) > 1: raise TypeError('Specify the topic!', topics) return params[0] def get_widget(self, param, topic=None): if '/' in param: topic, param = param.split('/') if topic: return self.widget_dicts[topic][param].children[-1] else: params = [] topics = [] for topic, param_dict in self.widget_dicts.items(): if param in param_dict: params.append(param_dict[param]) topics.append(topic) if len(params) > 1: raise TypeError('Specify the topic!', topics) return params[0].children[-1] def get_node(self, node, topic=None): if topic: return self.node_dicts[topic][node] else: nodes = [] topics = [] for topic, node_dict in self.node_dicts.items(): if node in node_dict: nodes.append(node_dict[node]) topics.append(topic) if len(nodes) > 1: raise TypeError('Specify the topic!', topics) if len(nodes)==0: return None return nodes[0] def node_exists(self, node, topic=None): node = self.get_node(node, topic) if node is None: return False else: return True def get_active_param_values(self): dsl_gen = [""] added_params = [] for topic in self.root.children: if topic.name not in self.topic_choice_widget.value: continue dsl_gen[0] += "{}\n".format(topic.name) for param in topic.children: # genesis params self._follow_branch(param, topic, dsl_gen, added_params) if len(added_params)==0: dsl = dsl_gen[0][0:-1] dsl_gen[0] = '\n'.join(dsl.split('\n')[0:-1]) dsl_gen[0] += "\n" return dsl_gen[0][0:-2] def _follow_branch(self, param, topic, dsl_gen, added_params): """Notice the similarity to _add_widgets method in DynamicWidget class """ input_value = self.get_value(param.name, topic.name) # print(param.name, param.secondary_type, input_value, '+++', param.secondary_type=='boolean', type(input_value)) # if param.name=='simulate_treatment_effect': # print() # print(param.children) # print() if param.name in self.widget_nodes[topic.name]: # For the topic/param names widget_type = self.widget_nodes[topic.name][param.name].type else: widget_type = None if widget_type=='text': if not input_value == '': dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) elif widget_type=='choice': if not input_value is None: dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) elif widget_type=='boolean': dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) if input_value: for child_node in param.children: if child_node.primary_type=='param' or child_node.primary_type=='optional': self._follow_branch(child_node, topic, dsl_gen, added_params) for child_node in param.children: # Since this is choice param, child_nodes are all options if child_node.name==input_value: for _child_node in child_node.children: self._follow_branch(_child_node, topic, dsl_gen, added_params)

26.372781

141

0.538479

from ..tree.tree_node import TreeNode from ..tree.tree_builder import display_tree from ..widgets.dynamic_widgets import DynamicWidget from ..utils.data_structure_utils import nested_defaultdict try: from IPython.display import display import ipywidgets as widgets from ipywidgets import HBox, Label, VBox from ipywidgets import Button, Layout, HTML module_found = True except ModuleNotFoundError: module_found = False from threading import Event class AccessObject(): def __init__(self, root, node_dicts): self.initial_event = Event() param_setter_event = Event() self.module_found = module_found if not self.module_found: return self.root, self.node_dicts = root, node_dicts self.widget_dicts = nested_defaultdict(dict) self.widget_nodes = nested_defaultdict(dict) # we don't have duplicates they are the same objects. self.param_vboxes = {} for topic in self.root.children: param_widgets = [] for param in topic.children: param_widget = DynamicWidget(topic.name, param, self.widget_dicts, self.widget_nodes, self.initial_event, param_setter_event) param_widgets.append(param_widget) param_vbox = VBox(param_widgets) self.param_vboxes[topic.name] = param_vbox self.initial_event.set() def display_tree(self): display_tree(self.root) def get_topics(self): return self.root.get_children_names() def get_params(self, topic=None): if topic: return list(self.widget_dicts[topic].keys()) else: l = [] self._find_params(self.root, l) return l def get_effective_params(self, topic=None): effective_params = [] params = self.get_params(topic) for param in params: widget_type = self.widget_nodes[topic][param].type if widget_type=='text': if not self.get_value(param, topic) == '': effective_params.append(param) elif widget_type=='choice': if not self.get_value(param, topic) is None: effective_params.append(param) elif widget_type=='boolean': effective_params.append(param) return effective_params def _find_params(self, node, l): depth = node.depth node_type = node.primary_type node_name = node.name if node_type != 'root': if node_type == 'topic': depth += 1 if node_type in ['param', 'optional']: if node_name not in l: l.append(node_name) for child in node.children: self._find_params(child, l) def get_value(self, param, topic=None): return self.get_widget(param, topic).value def set_value(self, value, param, topic=None): try: widget_type = self.get_widget_node(param, topic).type except: print("The parameter [ {} ] in topic [ {} ] does not exist anymore. Skipping it.".format(param, topic)) return if widget_type=='boolean': self.get_widget(param, topic).value = eval(value) else: self.get_widget(param, topic).value = str(value) def get_vbox(self, topic): return self.param_vboxes[topic] def get_widget_node(self, param, topic=None): if topic: try: return self.widget_nodes[topic][param] except: return None else: params = [] topics = [] for topic, param_dict in self.widget_nodes.items(): if param in param_dict: params.append(param_dict[param]) topics.append(topic) if len(params) > 1: raise TypeError('Specify the topic!', topics) return params[0] def get_widget(self, param, topic=None): if '/' in param: topic, param = param.split('/') if topic: return self.widget_dicts[topic][param].children[-1] else: params = [] topics = [] for topic, param_dict in self.widget_dicts.items(): if param in param_dict: params.append(param_dict[param]) topics.append(topic) if len(params) > 1: raise TypeError('Specify the topic!', topics) return params[0].children[-1] def get_node(self, node, topic=None): if topic: return self.node_dicts[topic][node] else: nodes = [] topics = [] for topic, node_dict in self.node_dicts.items(): if node in node_dict: nodes.append(node_dict[node]) topics.append(topic) if len(nodes) > 1: raise TypeError('Specify the topic!', topics) if len(nodes)==0: return None return nodes[0] def node_exists(self, node, topic=None): node = self.get_node(node, topic) if node is None: return False else: return True def get_active_param_values(self): dsl_gen = [""] added_params = [] for topic in self.root.children: if topic.name not in self.topic_choice_widget.value: continue dsl_gen[0] += "{}\n".format(topic.name) for param in topic.children: self._follow_branch(param, topic, dsl_gen, added_params) if len(added_params)==0: dsl = dsl_gen[0][0:-1] dsl_gen[0] = '\n'.join(dsl.split('\n')[0:-1]) dsl_gen[0] += "\n" return dsl_gen[0][0:-2] def _follow_branch(self, param, topic, dsl_gen, added_params): input_value = self.get_value(param.name, topic.name) if param.name in self.widget_nodes[topic.name]: widget_type = self.widget_nodes[topic.name][param.name].type else: widget_type = None if widget_type=='text': if not input_value == '': dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) elif widget_type=='choice': if not input_value is None: dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) elif widget_type=='boolean': dsl_gen[0] += "-{}:{}\n".format(param.name, input_value) added_params.append(param.name) if input_value: for child_node in param.children: if child_node.primary_type=='param' or child_node.primary_type=='optional': self._follow_branch(child_node, topic, dsl_gen, added_params) for child_node in param.children: if child_node.name==input_value: for _child_node in child_node.children: self._follow_branch(_child_node, topic, dsl_gen, added_params)

true

f73901e1ff6cfefad9f65ca0f31da49a0cddd668

8,751

py

Python

models/reid.py

FDU-VTS/Person-Search

36a1eab8d8fdf149e32dece030edff02dbc8a915

[ "Apache-2.0" ]

null

models/reid.py

FDU-VTS/Person-Search

36a1eab8d8fdf149e32dece030edff02dbc8a915

[ "Apache-2.0" ]

null

models/reid.py

FDU-VTS/Person-Search

36a1eab8d8fdf149e32dece030edff02dbc8a915

[ "Apache-2.0" ]

null

# encoding: utf-8 """ @author: liaoxingyu @contact: sherlockliao01@gmail.com """ import math import torch from torch import nn from torch.utils import model_zoo from models.context_block import * model_urls = { 'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth', 'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth', 'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pth', 'resnet101': 'https://download.pytorch.org/models/resnet101-5d3b4d8f.pth', 'resnet152': 'https://download.pytorch.org/models/resnet152-b121ed2d.pth', 'resnext50_32x4d': 'https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth', 'resnext101_32x8d': 'https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth', 'wide_resnet50_2': 'https://download.pytorch.org/models/wide_resnet50_2-95faca4d.pth', 'wide_resnet101_2': 'https://download.pytorch.org/models/wide_resnet101_2-32ee1156.pth', } model_layers = { 'resnet50': [3, 4, 6, 3], 'resnet101': [3, 4, 23, 3] } __all__ = ['ResNet', 'Bottleneck'] class IBN(nn.Module): """ IBN with BN:IN = 7:1 """ def __init__(self, planes): super(IBN, self).__init__() half1 = int(planes / 8) self.half = half1 half2 = planes - half1 self.IN = nn.InstanceNorm2d(half1, affine=True) self.BN = nn.BatchNorm2d(half2) def forward(self, x): split = torch.split(x, self.half, dim=1) out1 = self.IN(split[0].contiguous()) out2 = self.BN(torch.cat(split[1:], dim=1).contiguous()) out = torch.cat((out1, out2), 1) return out class Bottleneck(nn.Module): expansion = 4 def __init__(self, inplanes, planes, with_ibn=False, gcb=None, stride=1, downsample=None): super(Bottleneck, self).__init__() self.with_gcb = gcb is not None self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False) if with_ibn: self.bn1 = IBN(planes) else: self.bn1 = nn.BatchNorm2d(planes) self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn2 = nn.BatchNorm2d(planes) self.conv3 = nn.Conv2d(planes, planes * 4, kernel_size=1, bias=False) self.bn3 = nn.BatchNorm2d(planes * 4) self.relu = nn.ReLU(inplace=True) self.downsample = downsample self.stride = stride # GCNet if self.with_gcb: gcb_inplanes = planes * self.expansion self.context_block = ContextBlock(inplanes=gcb_inplanes, **gcb) def forward(self, x): residual = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) out = self.relu(out) out = self.conv3(out) out = self.bn3(out) if self.with_gcb: out = self.context_block(out) if self.downsample is not None: residual = self.downsample(x) out += residual out = self.relu(out) return out class ResNet(nn.Module): def __init__(self, last_stride, with_ibn, gcb, stage_with_gcb, block, layers): scale = 64 self.inplanes = scale super().__init__() self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False) self.bn1 = nn.BatchNorm2d(64) self.relu = nn.ReLU(inplace=True) self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) self.layer1 = self._make_layer(block, scale, layers[0], with_ibn=with_ibn, gcb=gcb if stage_with_gcb[0] else None) self.layer2 = self._make_layer(block, scale * 2, layers[1], stride=2, with_ibn=with_ibn, gcb=gcb if stage_with_gcb[1] else None) self.layer3 = self._make_layer(block, scale * 4, layers[2], stride=2, with_ibn=with_ibn, gcb=gcb if stage_with_gcb[2] else None) self.layer4 = self._make_layer(block, scale * 8, layers[3], stride=last_stride, gcb=gcb if stage_with_gcb[3] else None) def _make_layer(self, block, planes, blocks, stride=1, with_ibn=False, gcb=None): downsample = None if stride != 1 or self.inplanes != planes * block.expansion: downsample = nn.Sequential( nn.Conv2d(self.inplanes, planes * block.expansion, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(planes * block.expansion), ) layers = [] if planes == 512: with_ibn = False layers.append(block(self.inplanes, planes, with_ibn, gcb, stride, downsample)) self.inplanes = planes * block.expansion for i in range(1, blocks): layers.append(block(self.inplanes, planes, with_ibn, gcb)) return nn.Sequential(*layers) def forward(self, x): x = self.conv1(x) x = self.bn1(x) x = self.relu(x) x = self.maxpool(x) x = self.layer1(x) x = self.layer2(x) x = self.layer3(x) x = self.layer4(x) return x def load_pretrain(self, model_path=''): with_model_path = (model_path is not '') if not with_model_path: # resnet pretrain state_dict = model_zoo.load_url(model_urls[self._model_name]) state_dict.pop('fc.weight') state_dict.pop('fc.bias') self.load_state_dict(state_dict) else: # ibn pretrain state_dict = torch.load(model_path)['state_dict'] state_dict.pop('module.fc.weight') state_dict.pop('module.fc.bias') new_state_dict = {} for k in state_dict: new_k = '.'.join(k.split('.')[1:]) # remove module in name if self.state_dict()[new_k].shape == state_dict[k].shape: new_state_dict[new_k] = state_dict[k] state_dict = new_state_dict self.load_state_dict(state_dict, strict=False) def random_init(self): for m in self.modules(): if isinstance(m, nn.Conv2d): n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels m.weight.data.normal_(0, math.sqrt(2. / n)) elif isinstance(m, nn.BatchNorm2d): m.weight.data.fill_(1) m.bias.data.zero_() @classmethod def from_name(cls, model_name, last_stride, with_ibn, gcb, stage_with_gcb): cls._model_name = model_name return ResNet(last_stride, with_ibn, gcb, stage_with_gcb, block=Bottleneck, layers=model_layers[model_name]) class Baseline(nn.Module): in_planes = 2048 def __init__(self, backbone, num_classes, last_stride, with_ibn, gcb, stage_with_gcb, pretrain=True, model_path=''): super().__init__() try: self.base = ResNet.from_name(backbone, last_stride, with_ibn, gcb, stage_with_gcb) except: print(f'not support {backbone} backbone') if pretrain: self.base.load_pretrain(model_path) self.gap = nn.AdaptiveAvgPool2d(1) self.num_classes = num_classes self.bottleneck = nn.BatchNorm1d(self.in_planes) self.bottleneck.bias.requires_grad_(False) # no shift self.classifier = nn.Linear(self.in_planes, self.num_classes, bias=False) def forward(self, x, label=None): base = self.base(x) global_feat = self.gap(base) # (b, 2048, 1, 1) global_feat = global_feat.view(-1, global_feat.size()[1]) feat = self.bottleneck(global_feat) # normalize for angular softmax return feat, torch.sum(base*feat.unsqueeze(-1).unsqueeze(-1), dim=1) def load_params_wo_fc(self, state_dict): # new_state_dict = {} # for k, v in state_dict.items(): # k = '.'.join(k.split('.')[1:]) # new_state_dict[k] = v # state_dict = new_state_dict state_dict.pop('classifier.weight') res = self.load_state_dict(state_dict, strict=False) assert str(res.missing_keys) == str(['classifier.weight',]), 'issue loading pretrained weights' if __name__ == "__main__": model = Baseline( 'resnet50', 1453, 1, True, "ratio", (False, False, False, False), pretrain = False, model_path = '') print(model)

34.864542

116

0.587019

import math import torch from torch import nn from torch.utils import model_zoo from models.context_block import * model_urls = { 'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth', 'resnet34': 'https://download.pytorch.org/models/resnet34-333f7ec4.pth', 'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pth', 'resnet101': 'https://download.pytorch.org/models/resnet101-5d3b4d8f.pth', 'resnet152': 'https://download.pytorch.org/models/resnet152-b121ed2d.pth', 'resnext50_32x4d': 'https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth', 'resnext101_32x8d': 'https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth', 'wide_resnet50_2': 'https://download.pytorch.org/models/wide_resnet50_2-95faca4d.pth', 'wide_resnet101_2': 'https://download.pytorch.org/models/wide_resnet101_2-32ee1156.pth', } model_layers = { 'resnet50': [3, 4, 6, 3], 'resnet101': [3, 4, 23, 3] } __all__ = ['ResNet', 'Bottleneck'] class IBN(nn.Module): def __init__(self, planes): super(IBN, self).__init__() half1 = int(planes / 8) self.half = half1 half2 = planes - half1 self.IN = nn.InstanceNorm2d(half1, affine=True) self.BN = nn.BatchNorm2d(half2) def forward(self, x): split = torch.split(x, self.half, dim=1) out1 = self.IN(split[0].contiguous()) out2 = self.BN(torch.cat(split[1:], dim=1).contiguous()) out = torch.cat((out1, out2), 1) return out class Bottleneck(nn.Module): expansion = 4 def __init__(self, inplanes, planes, with_ibn=False, gcb=None, stride=1, downsample=None): super(Bottleneck, self).__init__() self.with_gcb = gcb is not None self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False) if with_ibn: self.bn1 = IBN(planes) else: self.bn1 = nn.BatchNorm2d(planes) self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn2 = nn.BatchNorm2d(planes) self.conv3 = nn.Conv2d(planes, planes * 4, kernel_size=1, bias=False) self.bn3 = nn.BatchNorm2d(planes * 4) self.relu = nn.ReLU(inplace=True) self.downsample = downsample self.stride = stride if self.with_gcb: gcb_inplanes = planes * self.expansion self.context_block = ContextBlock(inplanes=gcb_inplanes, **gcb) def forward(self, x): residual = x out = self.conv1(x) out = self.bn1(out) out = self.relu(out) out = self.conv2(out) out = self.bn2(out) out = self.relu(out) out = self.conv3(out) out = self.bn3(out) if self.with_gcb: out = self.context_block(out) if self.downsample is not None: residual = self.downsample(x) out += residual out = self.relu(out) return out class ResNet(nn.Module): def __init__(self, last_stride, with_ibn, gcb, stage_with_gcb, block, layers): scale = 64 self.inplanes = scale super().__init__() self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False) self.bn1 = nn.BatchNorm2d(64) self.relu = nn.ReLU(inplace=True) self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1) self.layer1 = self._make_layer(block, scale, layers[0], with_ibn=with_ibn, gcb=gcb if stage_with_gcb[0] else None) self.layer2 = self._make_layer(block, scale * 2, layers[1], stride=2, with_ibn=with_ibn, gcb=gcb if stage_with_gcb[1] else None) self.layer3 = self._make_layer(block, scale * 4, layers[2], stride=2, with_ibn=with_ibn, gcb=gcb if stage_with_gcb[2] else None) self.layer4 = self._make_layer(block, scale * 8, layers[3], stride=last_stride, gcb=gcb if stage_with_gcb[3] else None) def _make_layer(self, block, planes, blocks, stride=1, with_ibn=False, gcb=None): downsample = None if stride != 1 or self.inplanes != planes * block.expansion: downsample = nn.Sequential( nn.Conv2d(self.inplanes, planes * block.expansion, kernel_size=1, stride=stride, bias=False), nn.BatchNorm2d(planes * block.expansion), ) layers = [] if planes == 512: with_ibn = False layers.append(block(self.inplanes, planes, with_ibn, gcb, stride, downsample)) self.inplanes = planes * block.expansion for i in range(1, blocks): layers.append(block(self.inplanes, planes, with_ibn, gcb)) return nn.Sequential(*layers) def forward(self, x): x = self.conv1(x) x = self.bn1(x) x = self.relu(x) x = self.maxpool(x) x = self.layer1(x) x = self.layer2(x) x = self.layer3(x) x = self.layer4(x) return x def load_pretrain(self, model_path=''): with_model_path = (model_path is not '') if not with_model_path: state_dict = model_zoo.load_url(model_urls[self._model_name]) state_dict.pop('fc.weight') state_dict.pop('fc.bias') self.load_state_dict(state_dict) else: state_dict = torch.load(model_path)['state_dict'] state_dict.pop('module.fc.weight') state_dict.pop('module.fc.bias') new_state_dict = {} for k in state_dict: new_k = '.'.join(k.split('.')[1:]) if self.state_dict()[new_k].shape == state_dict[k].shape: new_state_dict[new_k] = state_dict[k] state_dict = new_state_dict self.load_state_dict(state_dict, strict=False) def random_init(self): for m in self.modules(): if isinstance(m, nn.Conv2d): n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels m.weight.data.normal_(0, math.sqrt(2. / n)) elif isinstance(m, nn.BatchNorm2d): m.weight.data.fill_(1) m.bias.data.zero_() @classmethod def from_name(cls, model_name, last_stride, with_ibn, gcb, stage_with_gcb): cls._model_name = model_name return ResNet(last_stride, with_ibn, gcb, stage_with_gcb, block=Bottleneck, layers=model_layers[model_name]) class Baseline(nn.Module): in_planes = 2048 def __init__(self, backbone, num_classes, last_stride, with_ibn, gcb, stage_with_gcb, pretrain=True, model_path=''): super().__init__() try: self.base = ResNet.from_name(backbone, last_stride, with_ibn, gcb, stage_with_gcb) except: print(f'not support {backbone} backbone') if pretrain: self.base.load_pretrain(model_path) self.gap = nn.AdaptiveAvgPool2d(1) self.num_classes = num_classes self.bottleneck = nn.BatchNorm1d(self.in_planes) self.bottleneck.bias.requires_grad_(False) self.classifier = nn.Linear(self.in_planes, self.num_classes, bias=False) def forward(self, x, label=None): base = self.base(x) global_feat = self.gap(base) global_feat = global_feat.view(-1, global_feat.size()[1]) feat = self.bottleneck(global_feat) return feat, torch.sum(base*feat.unsqueeze(-1).unsqueeze(-1), dim=1) def load_params_wo_fc(self, state_dict): state_dict.pop('classifier.weight') res = self.load_state_dict(state_dict, strict=False) assert str(res.missing_keys) == str(['classifier.weight',]), 'issue loading pretrained weights' if __name__ == "__main__": model = Baseline( 'resnet50', 1453, 1, True, "ratio", (False, False, False, False), pretrain = False, model_path = '') print(model)

true

f73901ef4984a451692d472712810fe344735601

965

py

Python

qiskit/providers/basicaer/__init__.py

lerongil/qiskit-terra

a25af2a2378bc3d4f5ec73b948d048d1b707454c

[ "Apache-2.0" ]

1

2021-10-13T14:37:54.000Z

qiskit/providers/basicaer/__init__.py

lerongil/qiskit-terra

a25af2a2378bc3d4f5ec73b948d048d1b707454c

[ "Apache-2.0" ]

null

qiskit/providers/basicaer/__init__.py

lerongil/qiskit-terra

a25af2a2378bc3d4f5ec73b948d048d1b707454c

[ "Apache-2.0" ]

2

2020-02-10T16:34:18.000Z

2020-05-22T08:37:07.000Z

# -*- coding: utf-8 -*- # This code is part of Qiskit. # # (C) Copyright IBM 2017, 2018. # # 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. """BasicAer Provider: Contains Python simulators.""" from .basicaerprovider import BasicAerProvider from .basicaerjob import BasicAerJob from .qasm_simulator import QasmSimulatorPy from .statevector_simulator import StatevectorSimulatorPy from .unitary_simulator import UnitarySimulatorPy from .exceptions import BasicAerError # Global instance to be used as the entry point for convenience. BasicAer = BasicAerProvider() # pylint: disable=invalid-name

37.115385

77

0.786528

from .basicaerprovider import BasicAerProvider from .basicaerjob import BasicAerJob from .qasm_simulator import QasmSimulatorPy from .statevector_simulator import StatevectorSimulatorPy from .unitary_simulator import UnitarySimulatorPy from .exceptions import BasicAerError BasicAer = BasicAerProvider()

true

f73904b8d9c1cb95aa33edbe0ce7ade57ca5ceab

1,757

py

Python

test/test_image_helpers.py

vincentriche/yoga

583217064e31e303cfe93eeaa5a0a25a7fb2c2b1

[ "BSD-3-Clause" ]

null

test/test_image_helpers.py

vincentriche/yoga

583217064e31e303cfe93eeaa5a0a25a7fb2c2b1

[ "BSD-3-Clause" ]

null

test/test_image_helpers.py

vincentriche/yoga

583217064e31e303cfe93eeaa5a0a25a7fb2c2b1

[ "BSD-3-Clause" ]

null

import pytest from PIL import Image from yoga.image import helpers class Test_image_have_alpha(object): @pytest.mark.parametrize( "image_path", [ "test/images/image1.jpg", "test/images/unused-alpha.png", "test/images/indexed.png", "test/images/grayscale.png", ], ) def test_image_without_alpha(self, image_path): image = Image.open(image_path) assert not helpers.image_have_alpha(image) def test_image_with_alpha(self): image = Image.open("test/images/alpha.png") assert helpers.image_have_alpha(image) @pytest.mark.parametrize( "image_path, threshold, is_alpha", [ ("test/images/threshold.png", 0xEF, True), ("test/images/threshold.png", 0xE0, False), ], ) def test_alpha_threshold(self, image_path, threshold, is_alpha): image = Image.open("test/images/threshold.png") if is_alpha: assert helpers.image_have_alpha(image, threshold) else: assert not helpers.image_have_alpha(image, threshold) class Test_gess_image_format(object): @pytest.mark.parametrize( "image_path, expected_format", [ ("test/images/image1.jpg", "jpeg"), ("test/images/alpha.png", "png"), ], ) def test_supported_image_format(self, image_path, expected_format): image_bytes = open(image_path, "rb").read() assert helpers.guess_image_format(image_bytes) == expected_format def test_unsuported_image_format(self): image_bytes = open("test/images/alpha.svg", "rb").read() with pytest.raises(ValueError): helpers.guess_image_format(image_bytes)

31.375

73

0.63062

import pytest from PIL import Image from yoga.image import helpers class Test_image_have_alpha(object): @pytest.mark.parametrize( "image_path", [ "test/images/image1.jpg", "test/images/unused-alpha.png", "test/images/indexed.png", "test/images/grayscale.png", ], ) def test_image_without_alpha(self, image_path): image = Image.open(image_path) assert not helpers.image_have_alpha(image) def test_image_with_alpha(self): image = Image.open("test/images/alpha.png") assert helpers.image_have_alpha(image) @pytest.mark.parametrize( "image_path, threshold, is_alpha", [ ("test/images/threshold.png", 0xEF, True), ("test/images/threshold.png", 0xE0, False), ], ) def test_alpha_threshold(self, image_path, threshold, is_alpha): image = Image.open("test/images/threshold.png") if is_alpha: assert helpers.image_have_alpha(image, threshold) else: assert not helpers.image_have_alpha(image, threshold) class Test_gess_image_format(object): @pytest.mark.parametrize( "image_path, expected_format", [ ("test/images/image1.jpg", "jpeg"), ("test/images/alpha.png", "png"), ], ) def test_supported_image_format(self, image_path, expected_format): image_bytes = open(image_path, "rb").read() assert helpers.guess_image_format(image_bytes) == expected_format def test_unsuported_image_format(self): image_bytes = open("test/images/alpha.svg", "rb").read() with pytest.raises(ValueError): helpers.guess_image_format(image_bytes)

true

f739068bdaf87f5feab35741d7c2f3304166461b

86

py

Python

src/final_exam/q_player/main_player.py

acc-cosc-1336/cosc-1336-spring-2018-Miguelh1997

ac4b0405c4070758d0fc07458d4dca8a8a0313de

[ "MIT" ]

null

src/final_exam/q_player/main_player.py

acc-cosc-1336/cosc-1336-spring-2018-Miguelh1997

ac4b0405c4070758d0fc07458d4dca8a8a0313de

[ "MIT" ]

null

src/final_exam/q_player/main_player.py

acc-cosc-1336/cosc-1336-spring-2018-Miguelh1997

ac4b0405c4070758d0fc07458d4dca8a8a0313de

[ "MIT" ]

1

2018-02-13T03:32:50.000Z

from player import Player p = Player(7,11) new = p.check_come_out_roll() print(new)

12.285714

29

0.732558

from player import Player p = Player(7,11) new = p.check_come_out_roll() print(new)

true

f7390997788e9f8d8c665a703e70cda0e5065dcd

226

py

Python

Products/admin.py

Annukumari99312/e-commerce

3e7c206fb545f41adfa09bdbc64c765eb8be8b0c

[ "MIT" ]

null

Products/admin.py

Annukumari99312/e-commerce

3e7c206fb545f41adfa09bdbc64c765eb8be8b0c

[ "MIT" ]

null

Products/admin.py

Annukumari99312/e-commerce

3e7c206fb545f41adfa09bdbc64c765eb8be8b0c

[ "MIT" ]

null

from django.contrib import admin from .models import Product class ProductAdmin(admin.ModelAdmin): list_display = ['__str__', 'slug'] class Meta: model = Product admin.site.register(Product, ProductAdmin)

17.384615

42

0.721239

from django.contrib import admin from .models import Product class ProductAdmin(admin.ModelAdmin): list_display = ['__str__', 'slug'] class Meta: model = Product admin.site.register(Product, ProductAdmin)

true

f7390b592a5ce8e43b6054ce5bf5ec8c333bb565

15,777

py

Python

devel/lib/python2.7/dist-packages/robotnik_msgs/msg/_SetElevatorActionResult.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

devel/lib/python2.7/dist-packages/robotnik_msgs/msg/_SetElevatorActionResult.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

devel/lib/python2.7/dist-packages/robotnik_msgs/msg/_SetElevatorActionResult.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

# This Python file uses the following encoding: utf-8 """autogenerated by genpy from robotnik_msgs/SetElevatorActionResult.msg. Do not edit.""" import codecs import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import actionlib_msgs.msg import genpy import robotnik_msgs.msg import std_msgs.msg class SetElevatorActionResult(genpy.Message): _md5sum = "d72997606702a7ef168a85ecdb795c78" _type = "robotnik_msgs/SetElevatorActionResult" _has_header = True # flag to mark the presence of a Header object _full_text = """# ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ====== Header header actionlib_msgs/GoalStatus status SetElevatorResult result ================================================================================ MSG: std_msgs/Header # Standard metadata for higher-level stamped data types. # This is generally used to communicate timestamped data # in a particular coordinate frame. # # sequence ID: consecutively increasing ID uint32 seq #Two-integer timestamp that is expressed as: # * stamp.sec: seconds (stamp_secs) since epoch (in Python the variable is called 'secs') # * stamp.nsec: nanoseconds since stamp_secs (in Python the variable is called 'nsecs') # time-handling sugar is provided by the client library time stamp #Frame this data is associated with string frame_id ================================================================================ MSG: actionlib_msgs/GoalStatus GoalID goal_id uint8 status uint8 PENDING = 0 # The goal has yet to be processed by the action server uint8 ACTIVE = 1 # The goal is currently being processed by the action server uint8 PREEMPTED = 2 # The goal received a cancel request after it started executing # and has since completed its execution (Terminal State) uint8 SUCCEEDED = 3 # The goal was achieved successfully by the action server (Terminal State) uint8 ABORTED = 4 # The goal was aborted during execution by the action server due # to some failure (Terminal State) uint8 REJECTED = 5 # The goal was rejected by the action server without being processed, # because the goal was unattainable or invalid (Terminal State) uint8 PREEMPTING = 6 # The goal received a cancel request after it started executing # and has not yet completed execution uint8 RECALLING = 7 # The goal received a cancel request before it started executing, # but the action server has not yet confirmed that the goal is canceled uint8 RECALLED = 8 # The goal received a cancel request before it started executing # and was successfully cancelled (Terminal State) uint8 LOST = 9 # An action client can determine that a goal is LOST. This should not be # sent over the wire by an action server #Allow for the user to associate a string with GoalStatus for debugging string text ================================================================================ MSG: actionlib_msgs/GoalID # The stamp should store the time at which this goal was requested. # It is used by an action server when it tries to preempt all # goals that were requested before a certain time time stamp # The id provides a way to associate feedback and # result message with specific goal requests. The id # specified must be unique. string id ================================================================================ MSG: robotnik_msgs/SetElevatorResult # ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ====== bool result robotnik_msgs/ElevatorStatus status ================================================================================ MSG: robotnik_msgs/ElevatorStatus # state string RAISING=raising string LOWERING=lowering string IDLE=idle string ERROR_G_IO=error_getting_io string ERROR_S_IO=error_setting_io string ERROR_TIMEOUT=error_timeout_in_action # position string UP=up string DOWN=down string UNKNOWN=unknown # IDLE, RAISING, LOWERING string state # UP, DOWN, UNKNOWN string position float32 height """ __slots__ = ['header','status','result'] _slot_types = ['std_msgs/Header','actionlib_msgs/GoalStatus','robotnik_msgs/SetElevatorResult'] def __init__(self, *args, **kwds): """ Constructor. Any message fields that are implicitly/explicitly set to None will be assigned a default value. The recommend use is keyword arguments as this is more robust to future message changes. You cannot mix in-order arguments and keyword arguments. The available fields are: header,status,result :param args: complete set of field values, in .msg order :param kwds: use keyword arguments corresponding to message field names to set specific fields. """ if args or kwds: super(SetElevatorActionResult, self).__init__(*args, **kwds) # message fields cannot be None, assign default values for those that are if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() else: self.header = std_msgs.msg.Header() self.status = actionlib_msgs.msg.GoalStatus() self.result = robotnik_msgs.msg.SetElevatorResult() def _get_types(self): """ internal API method """ return self._slot_types def serialize(self, buff): """ serialize message into buffer :param buff: buffer, ``StringIO`` """ try: _x = self buff.write(_get_struct_3I().pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs)) _x = self.header.frame_id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self buff.write(_get_struct_2I().pack(_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs)) _x = self.status.goal_id.id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.status.status buff.write(_get_struct_B().pack(_x)) _x = self.status.text length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.result buff.write(_get_struct_B().pack(_x)) _x = self.result.status.state length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.position length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.height buff.write(_get_struct_f().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): """ unpack serialized message in str into this message instance :param str: byte array of serialized message, ``str`` """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() end = 0 _x = self start = end end += 12 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.header.frame_id = str[start:end].decode('utf-8', 'rosmsg') else: self.header.frame_id = str[start:end] _x = self start = end end += 8 (_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs,) = _get_struct_2I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.goal_id.id = str[start:end].decode('utf-8', 'rosmsg') else: self.status.goal_id.id = str[start:end] start = end end += 1 (self.status.status,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.text = str[start:end].decode('utf-8', 'rosmsg') else: self.status.text = str[start:end] start = end end += 1 (self.result.result,) = _get_struct_B().unpack(str[start:end]) self.result.result = bool(self.result.result) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.state = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.state = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.position = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.position = str[start:end] start = end end += 4 (self.result.status.height,) = _get_struct_f().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill def serialize_numpy(self, buff, numpy): """ serialize message with numpy array types into buffer :param buff: buffer, ``StringIO`` :param numpy: numpy python module """ try: _x = self buff.write(_get_struct_3I().pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs)) _x = self.header.frame_id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self buff.write(_get_struct_2I().pack(_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs)) _x = self.status.goal_id.id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.status.status buff.write(_get_struct_B().pack(_x)) _x = self.status.text length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.result buff.write(_get_struct_B().pack(_x)) _x = self.result.status.state length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.position length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.height buff.write(_get_struct_f().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): """ unpack serialized message in str into this message instance using numpy for array types :param str: byte array of serialized message, ``str`` :param numpy: numpy python module """ if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() end = 0 _x = self start = end end += 12 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.header.frame_id = str[start:end].decode('utf-8', 'rosmsg') else: self.header.frame_id = str[start:end] _x = self start = end end += 8 (_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs,) = _get_struct_2I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.goal_id.id = str[start:end].decode('utf-8', 'rosmsg') else: self.status.goal_id.id = str[start:end] start = end end += 1 (self.status.status,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.text = str[start:end].decode('utf-8', 'rosmsg') else: self.status.text = str[start:end] start = end end += 1 (self.result.result,) = _get_struct_B().unpack(str[start:end]) self.result.result = bool(self.result.result) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.state = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.state = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.position = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.position = str[start:end] start = end end += 4 (self.result.status.height,) = _get_struct_f().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) # most likely buffer underfill _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_2I = None def _get_struct_2I(): global _struct_2I if _struct_2I is None: _struct_2I = struct.Struct("<2I") return _struct_2I _struct_3I = None def _get_struct_3I(): global _struct_3I if _struct_3I is None: _struct_3I = struct.Struct("<3I") return _struct_3I _struct_B = None def _get_struct_B(): global _struct_B if _struct_B is None: _struct_B = struct.Struct("<B") return _struct_B _struct_f = None def _get_struct_f(): global _struct_f if _struct_f is None: _struct_f = struct.Struct("<f") return _struct_f

36.352535

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0.623566

import codecs import sys python3 = True if sys.hexversion > 0x03000000 else False import genpy import struct import actionlib_msgs.msg import genpy import robotnik_msgs.msg import std_msgs.msg class SetElevatorActionResult(genpy.Message): _md5sum = "d72997606702a7ef168a85ecdb795c78" _type = "robotnik_msgs/SetElevatorActionResult" _has_header = True _full_text = """# ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ====== Header header actionlib_msgs/GoalStatus status SetElevatorResult result ================================================================================ MSG: std_msgs/Header # Standard metadata for higher-level stamped data types. # This is generally used to communicate timestamped data # in a particular coordinate frame. # # sequence ID: consecutively increasing ID uint32 seq #Two-integer timestamp that is expressed as: # * stamp.sec: seconds (stamp_secs) since epoch (in Python the variable is called 'secs') # * stamp.nsec: nanoseconds since stamp_secs (in Python the variable is called 'nsecs') # time-handling sugar is provided by the client library time stamp #Frame this data is associated with string frame_id ================================================================================ MSG: actionlib_msgs/GoalStatus GoalID goal_id uint8 status uint8 PENDING = 0 # The goal has yet to be processed by the action server uint8 ACTIVE = 1 # The goal is currently being processed by the action server uint8 PREEMPTED = 2 # The goal received a cancel request after it started executing # and has since completed its execution (Terminal State) uint8 SUCCEEDED = 3 # The goal was achieved successfully by the action server (Terminal State) uint8 ABORTED = 4 # The goal was aborted during execution by the action server due # to some failure (Terminal State) uint8 REJECTED = 5 # The goal was rejected by the action server without being processed, # because the goal was unattainable or invalid (Terminal State) uint8 PREEMPTING = 6 # The goal received a cancel request after it started executing # and has not yet completed execution uint8 RECALLING = 7 # The goal received a cancel request before it started executing, # but the action server has not yet confirmed that the goal is canceled uint8 RECALLED = 8 # The goal received a cancel request before it started executing # and was successfully cancelled (Terminal State) uint8 LOST = 9 # An action client can determine that a goal is LOST. This should not be # sent over the wire by an action server #Allow for the user to associate a string with GoalStatus for debugging string text ================================================================================ MSG: actionlib_msgs/GoalID # The stamp should store the time at which this goal was requested. # It is used by an action server when it tries to preempt all # goals that were requested before a certain time time stamp # The id provides a way to associate feedback and # result message with specific goal requests. The id # specified must be unique. string id ================================================================================ MSG: robotnik_msgs/SetElevatorResult # ====== DO NOT MODIFY! AUTOGENERATED FROM AN ACTION DEFINITION ====== bool result robotnik_msgs/ElevatorStatus status ================================================================================ MSG: robotnik_msgs/ElevatorStatus # state string RAISING=raising string LOWERING=lowering string IDLE=idle string ERROR_G_IO=error_getting_io string ERROR_S_IO=error_setting_io string ERROR_TIMEOUT=error_timeout_in_action # position string UP=up string DOWN=down string UNKNOWN=unknown # IDLE, RAISING, LOWERING string state # UP, DOWN, UNKNOWN string position float32 height """ __slots__ = ['header','status','result'] _slot_types = ['std_msgs/Header','actionlib_msgs/GoalStatus','robotnik_msgs/SetElevatorResult'] def __init__(self, *args, **kwds): if args or kwds: super(SetElevatorActionResult, self).__init__(*args, **kwds) if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() else: self.header = std_msgs.msg.Header() self.status = actionlib_msgs.msg.GoalStatus() self.result = robotnik_msgs.msg.SetElevatorResult() def _get_types(self): return self._slot_types def serialize(self, buff): try: _x = self buff.write(_get_struct_3I().pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs)) _x = self.header.frame_id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self buff.write(_get_struct_2I().pack(_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs)) _x = self.status.goal_id.id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.status.status buff.write(_get_struct_B().pack(_x)) _x = self.status.text length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.result buff.write(_get_struct_B().pack(_x)) _x = self.result.status.state length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.position length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.height buff.write(_get_struct_f().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize(self, str): if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() end = 0 _x = self start = end end += 12 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.header.frame_id = str[start:end].decode('utf-8', 'rosmsg') else: self.header.frame_id = str[start:end] _x = self start = end end += 8 (_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs,) = _get_struct_2I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.goal_id.id = str[start:end].decode('utf-8', 'rosmsg') else: self.status.goal_id.id = str[start:end] start = end end += 1 (self.status.status,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.text = str[start:end].decode('utf-8', 'rosmsg') else: self.status.text = str[start:end] start = end end += 1 (self.result.result,) = _get_struct_B().unpack(str[start:end]) self.result.result = bool(self.result.result) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.state = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.state = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.position = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.position = str[start:end] start = end end += 4 (self.result.status.height,) = _get_struct_f().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) def serialize_numpy(self, buff, numpy): try: _x = self buff.write(_get_struct_3I().pack(_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs)) _x = self.header.frame_id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self buff.write(_get_struct_2I().pack(_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs)) _x = self.status.goal_id.id length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.status.status buff.write(_get_struct_B().pack(_x)) _x = self.status.text length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.result buff.write(_get_struct_B().pack(_x)) _x = self.result.status.state length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.position length = len(_x) if python3 or type(_x) == unicode: _x = _x.encode('utf-8') length = len(_x) buff.write(struct.Struct('<I%ss'%length).pack(length, _x)) _x = self.result.status.height buff.write(_get_struct_f().pack(_x)) except struct.error as se: self._check_types(struct.error("%s: '%s' when writing '%s'" % (type(se), str(se), str(locals().get('_x', self))))) except TypeError as te: self._check_types(ValueError("%s: '%s' when writing '%s'" % (type(te), str(te), str(locals().get('_x', self))))) def deserialize_numpy(self, str, numpy): if python3: codecs.lookup_error("rosmsg").msg_type = self._type try: if self.header is None: self.header = std_msgs.msg.Header() if self.status is None: self.status = actionlib_msgs.msg.GoalStatus() if self.result is None: self.result = robotnik_msgs.msg.SetElevatorResult() end = 0 _x = self start = end end += 12 (_x.header.seq, _x.header.stamp.secs, _x.header.stamp.nsecs,) = _get_struct_3I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.header.frame_id = str[start:end].decode('utf-8', 'rosmsg') else: self.header.frame_id = str[start:end] _x = self start = end end += 8 (_x.status.goal_id.stamp.secs, _x.status.goal_id.stamp.nsecs,) = _get_struct_2I().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.goal_id.id = str[start:end].decode('utf-8', 'rosmsg') else: self.status.goal_id.id = str[start:end] start = end end += 1 (self.status.status,) = _get_struct_B().unpack(str[start:end]) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.status.text = str[start:end].decode('utf-8', 'rosmsg') else: self.status.text = str[start:end] start = end end += 1 (self.result.result,) = _get_struct_B().unpack(str[start:end]) self.result.result = bool(self.result.result) start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.state = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.state = str[start:end] start = end end += 4 (length,) = _struct_I.unpack(str[start:end]) start = end end += length if python3: self.result.status.position = str[start:end].decode('utf-8', 'rosmsg') else: self.result.status.position = str[start:end] start = end end += 4 (self.result.status.height,) = _get_struct_f().unpack(str[start:end]) return self except struct.error as e: raise genpy.DeserializationError(e) _struct_I = genpy.struct_I def _get_struct_I(): global _struct_I return _struct_I _struct_2I = None def _get_struct_2I(): global _struct_2I if _struct_2I is None: _struct_2I = struct.Struct("<2I") return _struct_2I _struct_3I = None def _get_struct_3I(): global _struct_3I if _struct_3I is None: _struct_3I = struct.Struct("<3I") return _struct_3I _struct_B = None def _get_struct_B(): global _struct_B if _struct_B is None: _struct_B = struct.Struct("<B") return _struct_B _struct_f = None def _get_struct_f(): global _struct_f if _struct_f is None: _struct_f = struct.Struct("<f") return _struct_f

true

f7390c2e11c7451649e3783cb5ad8d2db9e0dc57

17,027

py

Python

setup.py

RobertHalwass/habitat-sim

a329a90a70767c92789bdbeb2a983161d1207e98

[ "MIT" ]

null

setup.py

RobertHalwass/habitat-sim

a329a90a70767c92789bdbeb2a983161d1207e98

[ "MIT" ]

null

setup.py

RobertHalwass/habitat-sim

a329a90a70767c92789bdbeb2a983161d1207e98

[ "MIT" ]

null

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. """ Adapted from: http://www.benjack.io/2017/06/12/python-cpp-tests.html """ import argparse import builtins import glob import json import os import os.path as osp import re import shlex import shutil import subprocess import sys from distutils.util import strtobool from distutils.version import StrictVersion from setuptools import Extension, find_packages, setup from setuptools.command.build_ext import build_ext try: import cmake # If the cmake python package is installed, use that exe CMAKE_BIN_DIR = cmake.CMAKE_BIN_DIR except ImportError: CMAKE_BIN_DIR = "" sys.path.insert(0, osp.dirname(__file__)) ARG_CACHE_BLACKLIST = {"force_cmake", "cache_args", "inplace"} def str2bool(input_str: str) -> bool: return bool(strtobool(input_str.lower())) def is_pip(): # This will end with python if driven with python setup.py ... return osp.basename(os.environ.get("_", "/pip/no")).startswith("pip") # TODO refactor to the proper way to pass options to setup.py so pip can do so. def build_parser(): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter ) parser.add_argument( "--headless", dest="headless", default=str2bool(os.environ.get("HEADLESS", str(is_pip()))), action="store_true", help="""Build in headless mode. Use "HEADLESS=True pip install ." to build in headless mode with pip""", ) parser.add_argument( "--with-cuda", action="store_true", default=str2bool(os.environ.get("WITH_CUDA", "False")), dest="with_cuda", help="Build CUDA enabled features. Requires CUDA to be installed", ) parser.add_argument( "--bullet", "--with-bullet", dest="with_bullet", default=str2bool(os.environ.get("WITH_BULLET", str(is_pip()))), action="store_true", help="""Build with Bullet simulation engine. Default to True when pip installing. Default value is otherwise false or provided WITH_BULLET=ON or WITH_BULLET_OFF when doing pip install.""", ) parser.add_argument("--no-bullet", dest="with_bullet", action="store_false") parser.add_argument( "--vhacd", dest="with_vhacd", action="store_true", help="""Build with VHACD convex hull decomposition and voxelization engine.""", ) parser.add_argument( "--cmake", "--force-cmake", dest="force_cmake", action="store_true", help="Forces cmake to be rerun. This argument is not cached", ) parser.add_argument( "--build-tests", dest="build_tests", action="store_true", help="Build tests" ) parser.add_argument( "--build-datatool", dest="build_datatool", action="store_true", help="Build data tool", ) parser.add_argument( "--cmake-args", type=str, default=os.environ.get("CMAKE_ARGS", ""), help="""Additional arguements to be passed to cmake. Note that you will need to do `--cmake-args="..."` as `--cmake-args "..."` will generally not be parsed correctly You may need to use --force-cmake to ensure cmake is rerun with new args. Use "CMAKE_ARGS="..." pip install ." to set cmake args with pip""", ) parser.add_argument( "--no-update-submodules", dest="no_update_submodules", action="store_true", help="Don't update git submodules", ) parser.add_argument( "--build-type", dest="build_type", default=None, help="CMake configuration to build with (Release, Debug, etc...)", ) parser.add_argument( "--no-lto", dest="lto", default=None, action="store_false", help="Disables Link Time Optimization: faster compile times but worse performance.", ) parser.add_argument( "--lto", dest="lto", action="store_true", help="Enables Link Time Optimization: better performance but longer compile time", ) parser.add_argument( "--cache-args", dest="cache_args", action="store_true", help="""Caches the arguements sent to setup.py and reloads them on the next invocation. This argument is not cached""", ) parser.add_argument( "--skip-install-magnum", dest="skip_install_magnum", action="store_true", help="Don't install magnum. " "This is nice for incrementally building for development but " "can cause install magnum bindings to fall out-of-sync", ) parser.add_argument( "--build-basis-compressor", "--basis-compressor", dest="build_basis_compressor", action="store_true", help="Wether or not to build the basis compressor." " Loading basis compressed meshes does NOT require this.", ) return parser parseable_args = [] unparseable_args = [] for i, arg in enumerate(sys.argv): if arg == "--": unparseable_args = sys.argv[i:] break parseable_args.append(arg) parser = build_parser() args, filtered_args = parser.parse_known_args(args=parseable_args) sys.argv = filtered_args + unparseable_args def in_git(): try: subprocess.check_output(["git", "rev-parse", "--is-inside-work-tree"]) return True except (OSError, subprocess.SubprocessError): return False def has_ninja(): try: subprocess.check_output(["ninja", "--version"]) return True except (OSError, subprocess.SubprocessError): return False class CMakeExtension(Extension): def __init__(self, name, sourcedir=""): Extension.__init__(self, name, sources=[]) self.sourcedir = os.path.abspath(sourcedir) # populated in CMakeBuild.build_extension() _cmake_build_dir = None class CMakeBuild(build_ext): def finalize_options(self): super().finalize_options() cacheable_params = [ opt[0].replace("=", "").replace("-", "_") for opt in self.user_options ] args_cache_file = ".setuppy_args_cache.json" if not args.cache_args and osp.exists(args_cache_file): with open(args_cache_file, "r") as f: cached_args = json.load(f) for k, v in cached_args["args"].items(): setattr(args, k, v) for k, v in cached_args["build_ext"].items(): setattr(self, k, v) elif args.cache_args: cache = dict( args={ k: v for k, v in vars(args).items() if k not in ARG_CACHE_BLACKLIST }, build_ext={ k: getattr(self, k) for k in cacheable_params if k not in ARG_CACHE_BLACKLIST }, ) with open(args_cache_file, "w") as f: json.dump(cache, f, indent=4, sort_keys=True) if not os.path.exists(self.build_temp): os.makedirs(self.build_temp) # Save the CMake build directory -- that's where the generated setup.py # for magnum-bindings will appear which we need to run later global _cmake_build_dir _cmake_build_dir = self.build_temp def run(self): try: subprocess.check_output([osp.join(CMAKE_BIN_DIR, "cmake"), "--version"]) except (OSError, subprocess.SubprocessError): raise RuntimeError( "CMake must be installed to build the following extensions: " + ", ".join(e.name for e in self.extensions) ) for ext in self.extensions: self.build_extension(ext) def build_extension(self, ext): extdir = os.path.abspath(os.path.dirname(self.get_ext_fullpath(ext.name))) # Init & update all submodules if not already (the user might be pinned # on some particular commit or have working tree changes, don't destroy # those) if in_git() and not args.no_update_submodules: subprocess.check_call( ["git", "submodule", "update", "--init", "--recursive"] ) cmake_args = [ "-DBUILD_PYTHON_BINDINGS=ON", "-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=" + extdir, "-DPYTHON_EXECUTABLE=" + sys.executable, "-DCMAKE_EXPORT_COMPILE_COMMANDS={}".format("OFF" if is_pip() else "ON"), "-DREL_BUILD_RPATH={}".format("OFF" if self.inplace else "ON"), ] if args.lto is not None: cmake_args += [ "-DCMAKE_INTERPROCEDURAL_OPTIMIZATION={}".format( "ON" if args.lto else "OFF" ) ] cmake_args += shlex.split(args.cmake_args) build_type = args.build_type assert not ( build_type is not None and self.debug ), f"Debug and Build-Type flags conflict: {self.debug}, {build_type}" if build_type is None: build_type = "Debug" if self.debug else "RelWithDebInfo" build_args = ["--config", build_type] cmake_args += ["-DCMAKE_BUILD_TYPE=" + build_type] build_args += ["--"] if has_ninja(): cmake_args += ["-GNinja"] # Make it possible to *reduce* the number of jobs. Ninja requires a # number passed to -j (and builds on all cores by default), while make # doesn't require a number (but builds sequentially by default), so we # add the argument only when it's not ninja or the number of jobs is # specified. if not has_ninja() or self.parallel: build_args += ["-j{}".format(self.parallel) if self.parallel else "-j"] cmake_args += [ "-DBUILD_GUI_VIEWERS={}".format("ON" if not args.headless else "OFF") ] if sys.platform not in ["darwin", "win32", "win64"]: cmake_args += [ # So Magnum itself prefers EGL over GLX for windowless apps. # Makes sense only on platforms with EGL (Linux, BSD, ...). "-DTARGET_HEADLESS={}".format("ON" if args.headless else "OFF") ] # NOTE: BUILD_TEST is intentional as opposed to BUILD_TESTS which collides # with definition used by some of our dependencies cmake_args += ["-DBUILD_TEST={}".format("ON" if args.build_tests else "OFF")] cmake_args += [ "-DBUILD_WITH_BULLET={}".format("ON" if args.with_bullet else "OFF") ] cmake_args += [ "-DBUILD_WITH_VHACD={}".format("ON" if args.with_vhacd else "OFF") ] cmake_args += [ "-DBUILD_DATATOOL={}".format("ON" if args.build_datatool else "OFF") ] cmake_args += ["-DBUILD_WITH_CUDA={}".format("ON" if args.with_cuda else "OFF")] cmake_args += [ "-DBUILD_BASIS_COMPRESSOR={}".format( "ON" if args.build_basis_compressor else "OFF" ) ] env = os.environ.copy() env["CXXFLAGS"] = '{} -DVERSION_INFO=\\"{}\\"'.format( env.get("CXXFLAGS", ""), self.distribution.get_version() ) if is_pip() or self.run_cmake(cmake_args): os.makedirs(self.build_temp, exist_ok=True) # Remove invalid cmakefiles if is is_pip() for cmake_cache_f in [ "CMakeFiles", "CMakeCache.txt", "cmake_install.cmake", ]: cmake_cache_f = osp.join(self.build_temp, cmake_cache_f) if is_pip() and osp.exists(cmake_cache_f): if osp.isdir(cmake_cache_f): shutil.rmtree(cmake_cache_f) else: os.remove(cmake_cache_f) subprocess.check_call( [osp.join(CMAKE_BIN_DIR, "cmake")] + cmake_args + [osp.realpath(ext.sourcedir)], env=env, cwd=self.build_temp, ) if not is_pip(): self.create_compile_commands() subprocess.check_call( [osp.join(CMAKE_BIN_DIR, "cmake"), "--build", self.build_temp] + build_args ) print() # Add an empty line for cleaner output # The things following this don't work with pip if is_pip(): return if not args.headless: link_dst = osp.join(self.build_temp, "viewer") if not osp.islink(link_dst): os.symlink( osp.abspath(osp.join(self.build_temp, "utils/viewer/viewer")), link_dst, ) def run_cmake(self, cmake_args): if args.force_cmake: return True cache_parser = re.compile(r"(?P<K>\w+?)(:\w+?|)=(?P<V>.*?)$") cmake_cache = osp.join(self.build_temp, "CMakeCache.txt") if osp.exists(cmake_cache): with open(cmake_cache, "r") as f: cache_contents = f.readlines() for arg in cmake_args: if arg[0:2] == "-G": continue k, v = arg.split("=", 1) # Strip +D k = k[2:] for l in cache_contents: match = cache_parser.match(l) if match is None: continue if match.group("K") == k and match.group("V") != v: return True return False return True def create_compile_commands(self): def load(filename): with open(filename) as f: return json.load(f) command_files = [osp.join(self.build_temp, "compile_commands.json")] command_files += glob.glob("{}/*/compile_commands.json".format(self.build_temp)) all_commands = [entry for f in command_files for entry in load(f)] # cquery does not like c++ compiles that start with gcc. # It forgets to include the c++ header directories. # We can work around this by replacing the gcc calls that python # setup.py generates with g++ calls instead for command in all_commands: if command["command"].startswith("gcc "): command["command"] = "g++ " + command["command"][4:] new_contents = json.dumps(all_commands, indent=2) contents = "" if os.path.exists("compile_commands.json"): with open("compile_commands.json", "r") as f: contents = f.read() if contents != new_contents: with open("compile_commands.json", "w") as f: f.write(new_contents) if __name__ == "__main__": assert StrictVersion( "{}.{}".format(sys.version_info[0], sys.version_info[1]) ) >= StrictVersion("3.6"), "Must use python3.6 or newer" with open("./requirements.txt", "r") as f: requirements = [l.strip() for l in f.readlines() if len(l.strip()) > 0] # Only install pytest if we are running tests if {"pytest", "test", "ptr"}.intersection(sys.argv): setup_requires = ["pytest-runner"] else: setup_requires = [] builtins.__HSIM_SETUP__ = True import habitat_sim setup( name="habitat_sim", version=habitat_sim.__version__, author="FAIR A-STAR", description="A high performance simulator for training embodied agents", long_description="", packages=find_packages(), install_requires=requirements, setup_requires=setup_requires, tests_require=["hypothesis", "pytest-benchmark", "pytest"], python_requires=">=3.6", # add extension module ext_modules=[CMakeExtension("habitat_sim._ext.habitat_sim_bindings", "src")], # add custom build_ext command cmdclass=dict(build_ext=CMakeBuild), zip_safe=False, include_package_data=True, ) pymagnum_build_dir = osp.join( _cmake_build_dir, "deps", "magnum-bindings", "src", "python" ) if ( not args.skip_install_magnum and "sdist" not in sys.argv and os.path.exists(pymagnum_build_dir) ): subprocess.check_call( [sys.executable, "-m", "pip", "install", pymagnum_build_dir] ) else: if not os.path.exists(pymagnum_build_dir) and "sdist" not in sys.argv: print( f"{pymagnum_build_dir} does not exist and therefore we cannot install magnum-bindings directly." ) print( "Assuming magnum bindings are already installed (or we're inside pip and *\\_('-')_/*)" ) print( f"Run '{sys.executable} -m pip install {pymagnum_build_dir}' if this assumption is incorrect" )

34.054

112

0.58789

import argparse import builtins import glob import json import os import os.path as osp import re import shlex import shutil import subprocess import sys from distutils.util import strtobool from distutils.version import StrictVersion from setuptools import Extension, find_packages, setup from setuptools.command.build_ext import build_ext try: import cmake CMAKE_BIN_DIR = cmake.CMAKE_BIN_DIR except ImportError: CMAKE_BIN_DIR = "" sys.path.insert(0, osp.dirname(__file__)) ARG_CACHE_BLACKLIST = {"force_cmake", "cache_args", "inplace"} def str2bool(input_str: str) -> bool: return bool(strtobool(input_str.lower())) def is_pip(): return osp.basename(os.environ.get("_", "/pip/no")).startswith("pip") def build_parser(): parser = argparse.ArgumentParser( formatter_class=argparse.ArgumentDefaultsHelpFormatter ) parser.add_argument( "--headless", dest="headless", default=str2bool(os.environ.get("HEADLESS", str(is_pip()))), action="store_true", help="""Build in headless mode. Use "HEADLESS=True pip install ." to build in headless mode with pip""", ) parser.add_argument( "--with-cuda", action="store_true", default=str2bool(os.environ.get("WITH_CUDA", "False")), dest="with_cuda", help="Build CUDA enabled features. Requires CUDA to be installed", ) parser.add_argument( "--bullet", "--with-bullet", dest="with_bullet", default=str2bool(os.environ.get("WITH_BULLET", str(is_pip()))), action="store_true", help="""Build with Bullet simulation engine. Default to True when pip installing. Default value is otherwise false or provided WITH_BULLET=ON or WITH_BULLET_OFF when doing pip install.""", ) parser.add_argument("--no-bullet", dest="with_bullet", action="store_false") parser.add_argument( "--vhacd", dest="with_vhacd", action="store_true", help="""Build with VHACD convex hull decomposition and voxelization engine.""", ) parser.add_argument( "--cmake", "--force-cmake", dest="force_cmake", action="store_true", help="Forces cmake to be rerun. This argument is not cached", ) parser.add_argument( "--build-tests", dest="build_tests", action="store_true", help="Build tests" ) parser.add_argument( "--build-datatool", dest="build_datatool", action="store_true", help="Build data tool", ) parser.add_argument( "--cmake-args", type=str, default=os.environ.get("CMAKE_ARGS", ""), help="""Additional arguements to be passed to cmake. Note that you will need to do `--cmake-args="..."` as `--cmake-args "..."` will generally not be parsed correctly You may need to use --force-cmake to ensure cmake is rerun with new args. Use "CMAKE_ARGS="..." pip install ." to set cmake args with pip""", ) parser.add_argument( "--no-update-submodules", dest="no_update_submodules", action="store_true", help="Don't update git submodules", ) parser.add_argument( "--build-type", dest="build_type", default=None, help="CMake configuration to build with (Release, Debug, etc...)", ) parser.add_argument( "--no-lto", dest="lto", default=None, action="store_false", help="Disables Link Time Optimization: faster compile times but worse performance.", ) parser.add_argument( "--lto", dest="lto", action="store_true", help="Enables Link Time Optimization: better performance but longer compile time", ) parser.add_argument( "--cache-args", dest="cache_args", action="store_true", help="""Caches the arguements sent to setup.py and reloads them on the next invocation. This argument is not cached""", ) parser.add_argument( "--skip-install-magnum", dest="skip_install_magnum", action="store_true", help="Don't install magnum. " "This is nice for incrementally building for development but " "can cause install magnum bindings to fall out-of-sync", ) parser.add_argument( "--build-basis-compressor", "--basis-compressor", dest="build_basis_compressor", action="store_true", help="Wether or not to build the basis compressor." " Loading basis compressed meshes does NOT require this.", ) return parser parseable_args = [] unparseable_args = [] for i, arg in enumerate(sys.argv): if arg == "--": unparseable_args = sys.argv[i:] break parseable_args.append(arg) parser = build_parser() args, filtered_args = parser.parse_known_args(args=parseable_args) sys.argv = filtered_args + unparseable_args def in_git(): try: subprocess.check_output(["git", "rev-parse", "--is-inside-work-tree"]) return True except (OSError, subprocess.SubprocessError): return False def has_ninja(): try: subprocess.check_output(["ninja", "--version"]) return True except (OSError, subprocess.SubprocessError): return False class CMakeExtension(Extension): def __init__(self, name, sourcedir=""): Extension.__init__(self, name, sources=[]) self.sourcedir = os.path.abspath(sourcedir) _cmake_build_dir = None class CMakeBuild(build_ext): def finalize_options(self): super().finalize_options() cacheable_params = [ opt[0].replace("=", "").replace("-", "_") for opt in self.user_options ] args_cache_file = ".setuppy_args_cache.json" if not args.cache_args and osp.exists(args_cache_file): with open(args_cache_file, "r") as f: cached_args = json.load(f) for k, v in cached_args["args"].items(): setattr(args, k, v) for k, v in cached_args["build_ext"].items(): setattr(self, k, v) elif args.cache_args: cache = dict( args={ k: v for k, v in vars(args).items() if k not in ARG_CACHE_BLACKLIST }, build_ext={ k: getattr(self, k) for k in cacheable_params if k not in ARG_CACHE_BLACKLIST }, ) with open(args_cache_file, "w") as f: json.dump(cache, f, indent=4, sort_keys=True) if not os.path.exists(self.build_temp): os.makedirs(self.build_temp) # for magnum-bindings will appear which we need to run later global _cmake_build_dir _cmake_build_dir = self.build_temp def run(self): try: subprocess.check_output([osp.join(CMAKE_BIN_DIR, "cmake"), "--version"]) except (OSError, subprocess.SubprocessError): raise RuntimeError( "CMake must be installed to build the following extensions: " + ", ".join(e.name for e in self.extensions) ) for ext in self.extensions: self.build_extension(ext) def build_extension(self, ext): extdir = os.path.abspath(os.path.dirname(self.get_ext_fullpath(ext.name))) # Init & update all submodules if not already (the user might be pinned # on some particular commit or have working tree changes, don't destroy if in_git() and not args.no_update_submodules: subprocess.check_call( ["git", "submodule", "update", "--init", "--recursive"] ) cmake_args = [ "-DBUILD_PYTHON_BINDINGS=ON", "-DCMAKE_LIBRARY_OUTPUT_DIRECTORY=" + extdir, "-DPYTHON_EXECUTABLE=" + sys.executable, "-DCMAKE_EXPORT_COMPILE_COMMANDS={}".format("OFF" if is_pip() else "ON"), "-DREL_BUILD_RPATH={}".format("OFF" if self.inplace else "ON"), ] if args.lto is not None: cmake_args += [ "-DCMAKE_INTERPROCEDURAL_OPTIMIZATION={}".format( "ON" if args.lto else "OFF" ) ] cmake_args += shlex.split(args.cmake_args) build_type = args.build_type assert not ( build_type is not None and self.debug ), f"Debug and Build-Type flags conflict: {self.debug}, {build_type}" if build_type is None: build_type = "Debug" if self.debug else "RelWithDebInfo" build_args = ["--config", build_type] cmake_args += ["-DCMAKE_BUILD_TYPE=" + build_type] build_args += ["--"] if has_ninja(): cmake_args += ["-GNinja"] # add the argument only when it's not ninja or the number of jobs is if not has_ninja() or self.parallel: build_args += ["-j{}".format(self.parallel) if self.parallel else "-j"] cmake_args += [ "-DBUILD_GUI_VIEWERS={}".format("ON" if not args.headless else "OFF") ] if sys.platform not in ["darwin", "win32", "win64"]: cmake_args += [ "-DTARGET_HEADLESS={}".format("ON" if args.headless else "OFF") ] cmake_args += ["-DBUILD_TEST={}".format("ON" if args.build_tests else "OFF")] cmake_args += [ "-DBUILD_WITH_BULLET={}".format("ON" if args.with_bullet else "OFF") ] cmake_args += [ "-DBUILD_WITH_VHACD={}".format("ON" if args.with_vhacd else "OFF") ] cmake_args += [ "-DBUILD_DATATOOL={}".format("ON" if args.build_datatool else "OFF") ] cmake_args += ["-DBUILD_WITH_CUDA={}".format("ON" if args.with_cuda else "OFF")] cmake_args += [ "-DBUILD_BASIS_COMPRESSOR={}".format( "ON" if args.build_basis_compressor else "OFF" ) ] env = os.environ.copy() env["CXXFLAGS"] = '{} -DVERSION_INFO=\\"{}\\"'.format( env.get("CXXFLAGS", ""), self.distribution.get_version() ) if is_pip() or self.run_cmake(cmake_args): os.makedirs(self.build_temp, exist_ok=True) for cmake_cache_f in [ "CMakeFiles", "CMakeCache.txt", "cmake_install.cmake", ]: cmake_cache_f = osp.join(self.build_temp, cmake_cache_f) if is_pip() and osp.exists(cmake_cache_f): if osp.isdir(cmake_cache_f): shutil.rmtree(cmake_cache_f) else: os.remove(cmake_cache_f) subprocess.check_call( [osp.join(CMAKE_BIN_DIR, "cmake")] + cmake_args + [osp.realpath(ext.sourcedir)], env=env, cwd=self.build_temp, ) if not is_pip(): self.create_compile_commands() subprocess.check_call( [osp.join(CMAKE_BIN_DIR, "cmake"), "--build", self.build_temp] + build_args ) print() if is_pip(): return if not args.headless: link_dst = osp.join(self.build_temp, "viewer") if not osp.islink(link_dst): os.symlink( osp.abspath(osp.join(self.build_temp, "utils/viewer/viewer")), link_dst, ) def run_cmake(self, cmake_args): if args.force_cmake: return True cache_parser = re.compile(r"(?P<K>\w+?)(:\w+?|)=(?P<V>.*?)$") cmake_cache = osp.join(self.build_temp, "CMakeCache.txt") if osp.exists(cmake_cache): with open(cmake_cache, "r") as f: cache_contents = f.readlines() for arg in cmake_args: if arg[0:2] == "-G": continue k, v = arg.split("=", 1) # Strip +D k = k[2:] for l in cache_contents: match = cache_parser.match(l) if match is None: continue if match.group("K") == k and match.group("V") != v: return True return False return True def create_compile_commands(self): def load(filename): with open(filename) as f: return json.load(f) command_files = [osp.join(self.build_temp, "compile_commands.json")] command_files += glob.glob("{}/*/compile_commands.json".format(self.build_temp)) all_commands = [entry for f in command_files for entry in load(f)] # cquery does not like c++ compiles that start with gcc. # It forgets to include the c++ header directories. # We can work around this by replacing the gcc calls that python # setup.py generates with g++ calls instead for command in all_commands: if command["command"].startswith("gcc "): command["command"] = "g++ " + command["command"][4:] new_contents = json.dumps(all_commands, indent=2) contents = "" if os.path.exists("compile_commands.json"): with open("compile_commands.json", "r") as f: contents = f.read() if contents != new_contents: with open("compile_commands.json", "w") as f: f.write(new_contents) if __name__ == "__main__": assert StrictVersion( "{}.{}".format(sys.version_info[0], sys.version_info[1]) ) >= StrictVersion("3.6"), "Must use python3.6 or newer" with open("./requirements.txt", "r") as f: requirements = [l.strip() for l in f.readlines() if len(l.strip()) > 0] # Only install pytest if we are running tests if {"pytest", "test", "ptr"}.intersection(sys.argv): setup_requires = ["pytest-runner"] else: setup_requires = [] builtins.__HSIM_SETUP__ = True import habitat_sim setup( name="habitat_sim", version=habitat_sim.__version__, author="FAIR A-STAR", description="A high performance simulator for training embodied agents", long_description="", packages=find_packages(), install_requires=requirements, setup_requires=setup_requires, tests_require=["hypothesis", "pytest-benchmark", "pytest"], python_requires=">=3.6", # add extension module ext_modules=[CMakeExtension("habitat_sim._ext.habitat_sim_bindings", "src")], # add custom build_ext command cmdclass=dict(build_ext=CMakeBuild), zip_safe=False, include_package_data=True, ) pymagnum_build_dir = osp.join( _cmake_build_dir, "deps", "magnum-bindings", "src", "python" ) if ( not args.skip_install_magnum and "sdist" not in sys.argv and os.path.exists(pymagnum_build_dir) ): subprocess.check_call( [sys.executable, "-m", "pip", "install", pymagnum_build_dir] ) else: if not os.path.exists(pymagnum_build_dir) and "sdist" not in sys.argv: print( f"{pymagnum_build_dir} does not exist and therefore we cannot install magnum-bindings directly." ) print( "Assuming magnum bindings are already installed (or we're inside pip and *\\_('-')_/*)" ) print( f"Run '{sys.executable} -m pip install {pymagnum_build_dir}' if this assumption is incorrect" )

true

f7390cd227338410fabb9b4cd5b45f0af8f77191

11,974

py

Python

ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/dcenodetopologyrange_34374b8565456318538178dbf3a92ccb.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

20

2019-05-07T01:59:14.000Z

2022-02-11T05:24:47.000Z

ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/dcenodetopologyrange_34374b8565456318538178dbf3a92ccb.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

60

2019-04-03T18:59:35.000Z

2022-02-22T12:05:05.000Z

ixnetwork_restpy/testplatform/sessions/ixnetwork/vport/protocols/dcenodetopologyrange_34374b8565456318538178dbf3a92ccb.py

OpenIxia/ixnetwork_restpy

f628db450573a104f327cf3c737ca25586e067ae

[ "MIT" ]

13

2019-05-20T10:48:31.000Z

2021-10-06T07:45:44.000Z

# MIT LICENSE # # Copyright 1997 - 2020 by IXIA Keysight # # 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 ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files from typing import List, Any, Union class DceNodeTopologyRange(Base): """Sets the DCE Node Topology of a particular DCE ISIS Topology Range. The DceNodeTopologyRange class encapsulates a list of dceNodeTopologyRange resources that are managed by the user. A list of resources can be retrieved from the server using the DceNodeTopologyRange.find() method. The list can be managed by using the DceNodeTopologyRange.add() and DceNodeTopologyRange.remove() methods. """ __slots__ = () _SDM_NAME = 'dceNodeTopologyRange' _SDM_ATT_MAP = { 'BroadcastPriority': 'broadcastPriority', 'IncludeL2Topology': 'includeL2Topology', 'InternodeNicknameIncrement': 'internodeNicknameIncrement', 'NicknameCount': 'nicknameCount', 'NoOfTreesToCompute': 'noOfTreesToCompute', 'StartNickname': 'startNickname', 'TopologyCount': 'topologyCount', 'TopologyId': 'topologyId', } _SDM_ENUM_MAP = { } def __init__(self, parent, list_op=False): super(DceNodeTopologyRange, self).__init__(parent, list_op) @property def DceNodeInterestedVlanRange(self): """ Returns ------- - obj(ixnetwork_restpy.testplatform.sessions.ixnetwork.vport.protocols.dcenodeinterestedvlanrange_b15c6822c508a957290b5d3ed2b3ea4e.DceNodeInterestedVlanRange): An instance of the DceNodeInterestedVlanRange class Raises ------ - ServerError: The server has encountered an uncategorized error condition """ from ixnetwork_restpy.testplatform.sessions.ixnetwork.vport.protocols.dcenodeinterestedvlanrange_b15c6822c508a957290b5d3ed2b3ea4e import DceNodeInterestedVlanRange if self._properties.get('DceNodeInterestedVlanRange', None) is not None: return self._properties.get('DceNodeInterestedVlanRange') else: return DceNodeInterestedVlanRange(self) @property def BroadcastPriority(self): # type: () -> int """ Returns ------- - number: Sets the priority in which the topology is broadcast. """ return self._get_attribute(self._SDM_ATT_MAP['BroadcastPriority']) @BroadcastPriority.setter def BroadcastPriority(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['BroadcastPriority'], value) @property def IncludeL2Topology(self): # type: () -> bool """ Returns ------- - bool: If true, includes the L2 topology. """ return self._get_attribute(self._SDM_ATT_MAP['IncludeL2Topology']) @IncludeL2Topology.setter def IncludeL2Topology(self, value): # type: (bool) -> None self._set_attribute(self._SDM_ATT_MAP['IncludeL2Topology'], value) @property def InternodeNicknameIncrement(self): # type: () -> int """ Returns ------- - number: The increment step to be used for creating the internode increment. """ return self._get_attribute(self._SDM_ATT_MAP['InternodeNicknameIncrement']) @InternodeNicknameIncrement.setter def InternodeNicknameIncrement(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['InternodeNicknameIncrement'], value) @property def NicknameCount(self): # type: () -> int """ Returns ------- - number: The count of the nickname. """ return self._get_attribute(self._SDM_ATT_MAP['NicknameCount']) @NicknameCount.setter def NicknameCount(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['NicknameCount'], value) @property def NoOfTreesToCompute(self): # type: () -> int """ Returns ------- - number: The number of trees to compute. """ return self._get_attribute(self._SDM_ATT_MAP['NoOfTreesToCompute']) @NoOfTreesToCompute.setter def NoOfTreesToCompute(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['NoOfTreesToCompute'], value) @property def StartNickname(self): # type: () -> int """ Returns ------- - number: If true, uses the nickname. """ return self._get_attribute(self._SDM_ATT_MAP['StartNickname']) @StartNickname.setter def StartNickname(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['StartNickname'], value) @property def TopologyCount(self): # type: () -> int """ Returns ------- - number: The count of the topology. """ return self._get_attribute(self._SDM_ATT_MAP['TopologyCount']) @TopologyCount.setter def TopologyCount(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['TopologyCount'], value) @property def TopologyId(self): # type: () -> int """ Returns ------- - number: The unique identification number of the topology range. """ return self._get_attribute(self._SDM_ATT_MAP['TopologyId']) @TopologyId.setter def TopologyId(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['TopologyId'], value) def update(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): # type: (int, bool, int, int, int, int, int, int) -> DceNodeTopologyRange """Updates dceNodeTopologyRange resource on the server. Args ---- - BroadcastPriority (number): Sets the priority in which the topology is broadcast. - IncludeL2Topology (bool): If true, includes the L2 topology. - InternodeNicknameIncrement (number): The increment step to be used for creating the internode increment. - NicknameCount (number): The count of the nickname. - NoOfTreesToCompute (number): The number of trees to compute. - StartNickname (number): If true, uses the nickname. - TopologyCount (number): The count of the topology. - TopologyId (number): The unique identification number of the topology range. Raises ------ - ServerError: The server has encountered an uncategorized error condition """ return self._update(self._map_locals(self._SDM_ATT_MAP, locals())) def add(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): # type: (int, bool, int, int, int, int, int, int) -> DceNodeTopologyRange """Adds a new dceNodeTopologyRange resource on the server and adds it to the container. Args ---- - BroadcastPriority (number): Sets the priority in which the topology is broadcast. - IncludeL2Topology (bool): If true, includes the L2 topology. - InternodeNicknameIncrement (number): The increment step to be used for creating the internode increment. - NicknameCount (number): The count of the nickname. - NoOfTreesToCompute (number): The number of trees to compute. - StartNickname (number): If true, uses the nickname. - TopologyCount (number): The count of the topology. - TopologyId (number): The unique identification number of the topology range. Returns ------- - self: This instance with all currently retrieved dceNodeTopologyRange resources using find and the newly added dceNodeTopologyRange resources available through an iterator or index Raises ------ - ServerError: The server has encountered an uncategorized error condition """ return self._create(self._map_locals(self._SDM_ATT_MAP, locals())) def remove(self): """Deletes all the contained dceNodeTopologyRange resources in this instance from the server. Raises ------ - NotFoundError: The requested resource does not exist on the server - ServerError: The server has encountered an uncategorized error condition """ self._delete() def find(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): # type: (int, bool, int, int, int, int, int, int) -> DceNodeTopologyRange """Finds and retrieves dceNodeTopologyRange resources from the server. All named parameters are evaluated on the server using regex. The named parameters can be used to selectively retrieve dceNodeTopologyRange resources from the server. To retrieve an exact match ensure the parameter value starts with ^ and ends with $ By default the find method takes no parameters and will retrieve all dceNodeTopologyRange resources from the server. Args ---- - BroadcastPriority (number): Sets the priority in which the topology is broadcast. - IncludeL2Topology (bool): If true, includes the L2 topology. - InternodeNicknameIncrement (number): The increment step to be used for creating the internode increment. - NicknameCount (number): The count of the nickname. - NoOfTreesToCompute (number): The number of trees to compute. - StartNickname (number): If true, uses the nickname. - TopologyCount (number): The count of the topology. - TopologyId (number): The unique identification number of the topology range. Returns ------- - self: This instance with matching dceNodeTopologyRange resources retrieved from the server available through an iterator or index Raises ------ - ServerError: The server has encountered an uncategorized error condition """ return self._select(self._map_locals(self._SDM_ATT_MAP, locals())) def read(self, href): """Retrieves a single instance of dceNodeTopologyRange data from the server. Args ---- - href (str): An href to the instance to be retrieved Returns ------- - self: This instance with the dceNodeTopologyRange resources from the server available through an iterator or index Raises ------ - NotFoundError: The requested resource does not exist on the server - ServerError: The server has encountered an uncategorized error condition """ return self._read(href)

42.310954

219

0.674461

from ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files from typing import List, Any, Union class DceNodeTopologyRange(Base): __slots__ = () _SDM_NAME = 'dceNodeTopologyRange' _SDM_ATT_MAP = { 'BroadcastPriority': 'broadcastPriority', 'IncludeL2Topology': 'includeL2Topology', 'InternodeNicknameIncrement': 'internodeNicknameIncrement', 'NicknameCount': 'nicknameCount', 'NoOfTreesToCompute': 'noOfTreesToCompute', 'StartNickname': 'startNickname', 'TopologyCount': 'topologyCount', 'TopologyId': 'topologyId', } _SDM_ENUM_MAP = { } def __init__(self, parent, list_op=False): super(DceNodeTopologyRange, self).__init__(parent, list_op) @property def DceNodeInterestedVlanRange(self): from ixnetwork_restpy.testplatform.sessions.ixnetwork.vport.protocols.dcenodeinterestedvlanrange_b15c6822c508a957290b5d3ed2b3ea4e import DceNodeInterestedVlanRange if self._properties.get('DceNodeInterestedVlanRange', None) is not None: return self._properties.get('DceNodeInterestedVlanRange') else: return DceNodeInterestedVlanRange(self) @property def BroadcastPriority(self): return self._get_attribute(self._SDM_ATT_MAP['BroadcastPriority']) @BroadcastPriority.setter def BroadcastPriority(self, value): self._set_attribute(self._SDM_ATT_MAP['BroadcastPriority'], value) @property def IncludeL2Topology(self): return self._get_attribute(self._SDM_ATT_MAP['IncludeL2Topology']) @IncludeL2Topology.setter def IncludeL2Topology(self, value): self._set_attribute(self._SDM_ATT_MAP['IncludeL2Topology'], value) @property def InternodeNicknameIncrement(self): return self._get_attribute(self._SDM_ATT_MAP['InternodeNicknameIncrement']) @InternodeNicknameIncrement.setter def InternodeNicknameIncrement(self, value): self._set_attribute(self._SDM_ATT_MAP['InternodeNicknameIncrement'], value) @property def NicknameCount(self): return self._get_attribute(self._SDM_ATT_MAP['NicknameCount']) @NicknameCount.setter def NicknameCount(self, value): self._set_attribute(self._SDM_ATT_MAP['NicknameCount'], value) @property def NoOfTreesToCompute(self): return self._get_attribute(self._SDM_ATT_MAP['NoOfTreesToCompute']) @NoOfTreesToCompute.setter def NoOfTreesToCompute(self, value): self._set_attribute(self._SDM_ATT_MAP['NoOfTreesToCompute'], value) @property def StartNickname(self): return self._get_attribute(self._SDM_ATT_MAP['StartNickname']) @StartNickname.setter def StartNickname(self, value): self._set_attribute(self._SDM_ATT_MAP['StartNickname'], value) @property def TopologyCount(self): return self._get_attribute(self._SDM_ATT_MAP['TopologyCount']) @TopologyCount.setter def TopologyCount(self, value): self._set_attribute(self._SDM_ATT_MAP['TopologyCount'], value) @property def TopologyId(self): return self._get_attribute(self._SDM_ATT_MAP['TopologyId']) @TopologyId.setter def TopologyId(self, value): self._set_attribute(self._SDM_ATT_MAP['TopologyId'], value) def update(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): return self._update(self._map_locals(self._SDM_ATT_MAP, locals())) def add(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): return self._create(self._map_locals(self._SDM_ATT_MAP, locals())) def remove(self): self._delete() def find(self, BroadcastPriority=None, IncludeL2Topology=None, InternodeNicknameIncrement=None, NicknameCount=None, NoOfTreesToCompute=None, StartNickname=None, TopologyCount=None, TopologyId=None): return self._select(self._map_locals(self._SDM_ATT_MAP, locals())) def read(self, href): return self._read(href)

true

f7390cf292e209f021713892d3fb85ddd364f972

3,048

py

Python

packages/w3af/w3af/plugins/evasion/full_width_encode.py

ZooAtmosphereGroup/HelloPackages

0ccffd33bf927b13d28c8f715ed35004c33465d9

[ "Apache-2.0" ]

null

packages/w3af/w3af/plugins/evasion/full_width_encode.py

ZooAtmosphereGroup/HelloPackages

0ccffd33bf927b13d28c8f715ed35004c33465d9

[ "Apache-2.0" ]

null

packages/w3af/w3af/plugins/evasion/full_width_encode.py

ZooAtmosphereGroup/HelloPackages

0ccffd33bf927b13d28c8f715ed35004c33465d9

[ "Apache-2.0" ]

null

""" full_width_encode.py Copyright 2006 Andres Riancho This file is part of w3af, http://w3af.org/ . w3af is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation version 2 of the License. w3af is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with w3af; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA """ import urllib from w3af.core.controllers.plugins.evasion_plugin import EvasionPlugin from w3af.core.data.parsers.doc.url import parse_qs class full_width_encode(EvasionPlugin): """ Evade detection using full width encoding. :author: Andres Riancho (andres.riancho@gmail.com) """ def modify_request(self, request): """ Mangles the request :param request: HTTPRequest instance that is going to be modified by the evasion plugin :return: The modified request """ # First we mangle the URL path = request.url_object.get_path() path = self._mutate(path) # Now we mangle the postdata data = request.get_data() if data: try: # Only mangle the postdata if it is a url encoded string parse_qs(data) except: pass else: # We get here only if the parsing was successful data = self._mutate(data) # Finally, we set all the mutants to the request in order to return it new_url = request.url_object.copy() new_url.set_path(path) new_req = request.copy() new_req.set_data(data) new_req.set_uri(new_url) return new_req def _mutate(self, to_mutate): to_mutate = urllib.unquote(to_mutate) mutant = '' for char in to_mutate: if char not in ['?', '/', '&', '\\', '=', '%', '+']: # The "- 0x20" was taken from UFF00.pdf char = "%%uFF%02x" % (ord(char) - 0x20) mutant += char return mutant def get_priority(self): """ This function is called when sorting evasion plugins. Each evasion plugin should implement this. :return: An integer specifying the priority. 0 is run first, 100 last. """ return 50 def get_long_desc(self): """ :return: A DETAILED description of the plugin functions and features. """ return """ This evasion plugin does full width encoding as described here: - http://www.kb.cert.org/vuls/id/739224 Example: Input: '/bar/foo.asp' Output: '/b%uFF61r/%uFF66oo.asp' """

29.882353

78

0.614829

import urllib from w3af.core.controllers.plugins.evasion_plugin import EvasionPlugin from w3af.core.data.parsers.doc.url import parse_qs class full_width_encode(EvasionPlugin): def modify_request(self, request): path = request.url_object.get_path() path = self._mutate(path) data = request.get_data() if data: try: parse_qs(data) except: pass else: data = self._mutate(data) new_url = request.url_object.copy() new_url.set_path(path) new_req = request.copy() new_req.set_data(data) new_req.set_uri(new_url) return new_req def _mutate(self, to_mutate): to_mutate = urllib.unquote(to_mutate) mutant = '' for char in to_mutate: if char not in ['?', '/', '&', '\\', '=', '%', '+']: char = "%%uFF%02x" % (ord(char) - 0x20) mutant += char return mutant def get_priority(self): return 50 def get_long_desc(self): return """ This evasion plugin does full width encoding as described here: - http://www.kb.cert.org/vuls/id/739224 Example: Input: '/bar/foo.asp' Output: '/b%uFF61r/%uFF66oo.asp' """

true

f7390dc9891b3c2959a43d730cd03c3815a2319d

9,135

py

Python

tests/utilities/test_storage.py

nicolasiltis/prefect

4298105651c2fe02b21013ae8a0468e9e101154d

[ "Apache-2.0" ]

3

2021-11-09T10:46:58.000Z

2022-03-11T04:22:35.000Z

tests/utilities/test_storage.py

nicolasiltis/prefect

4298105651c2fe02b21013ae8a0468e9e101154d

[ "Apache-2.0" ]

8

2021-10-11T16:42:59.000Z

2022-03-31T08:42:24.000Z

tests/utilities/test_storage.py

nicolasiltis/prefect

4298105651c2fe02b21013ae8a0468e9e101154d

[ "Apache-2.0" ]

1

2022-03-11T04:22:40.000Z

import os import sys import types import textwrap import pytest import cloudpickle import prefect from prefect import Flow, Task from prefect.storage import Docker, Local from prefect.exceptions import FlowStorageError from prefect.run_configs import DockerRun, UniversalRun from prefect.utilities.storage import ( get_flow_image, extract_flow_from_file, extract_flow_from_module, flow_to_bytes_pickle, flow_from_bytes_pickle, ) def test_get_flow_image_docker_storage(): flow = Flow( "test", run_config=UniversalRun(), storage=Docker(registry_url="test", image_name="name", image_tag="tag"), ) image = get_flow_image(flow=flow) assert image == "test/name:tag" def test_get_flow_image_run_config(): flow = Flow( "test", run_config=DockerRun(image="repo/name:tag"), storage=Local(), ) image = get_flow_image(flow=flow) assert image == "repo/name:tag" def test_get_flow_image_raises_on_missing_info(): flow = Flow( "test", run_config=UniversalRun(), storage=Local(), ) with pytest.raises(ValueError): get_flow_image(flow=flow) class TestExtractFlowFromFile: @pytest.fixture def flow_path(self, tmpdir): contents = """from prefect import Flow\nf=Flow('flow-1')\nf2=Flow('flow-2')""" full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(contents) return full_path @pytest.fixture def flow_path_with_additional_file(self, tmpdir): contents = """\ from prefect import Flow from pathlib import Path with open(str(Path(__file__).resolve().parent)+"/test.txt", "r") as f: name = f.read() f2 = Flow(name) """ full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(textwrap.dedent(contents)) with open(os.path.join(tmpdir, "test.txt"), "w") as f: f.write("test-flow") return full_path def test_extract_flow_from_file_path(self, flow_path): flow = extract_flow_from_file(file_path=flow_path) assert flow.name == "flow-1" assert flow.run().is_successful() flow = extract_flow_from_file(file_path=flow_path, flow_name="flow-1") assert flow.name == "flow-1" flow = extract_flow_from_file(file_path=flow_path, flow_name="flow-2") assert flow.name == "flow-2" def test_extract_flow_from_file_path_can_load_files_from_same_directory( self, flow_path_with_additional_file ): flow = extract_flow_from_file(file_path=flow_path_with_additional_file) assert flow.name == "test-flow" assert flow.run().is_successful() def test_extract_flow_from_file_contents(self, flow_path): with open(flow_path, "r") as f: contents = f.read() flow = extract_flow_from_file(file_contents=contents) assert flow.name == "flow-1" assert flow.run().is_successful() flow = extract_flow_from_file(file_contents=contents, flow_name="flow-1") assert flow.name == "flow-1" flow = extract_flow_from_file(file_contents=contents, flow_name="flow-2") assert flow.name == "flow-2" def test_extract_flow_from_file_errors(self, flow_path): with pytest.raises(ValueError, match="but not both"): extract_flow_from_file(file_path="", file_contents="") with pytest.raises(ValueError, match="Provide either"): extract_flow_from_file() expected = ( "Flow 'not-real' not found in file. Found flows:\n- 'flow-1'\n- 'flow-2'" ) with pytest.raises(ValueError, match=expected): extract_flow_from_file(file_path=flow_path, flow_name="not-real") with pytest.raises(ValueError, match="No flows found in file."): extract_flow_from_file(file_contents="") @pytest.mark.parametrize("method", ["run", "register"]) def test_extract_flow_from_file_raises_on_run_register(self, tmpdir, method): contents = f"from prefect import Flow\nf=Flow('test-flow')\nf.{method}()" full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(contents) with prefect.context({"loading_flow": True}): with pytest.warns(Warning): extract_flow_from_file(file_path=full_path) @pytest.fixture def mymodule(monkeypatch): mod_name = "mymodule" module = types.ModuleType(mod_name) monkeypatch.setitem(sys.modules, mod_name, module) return module def test_extract_flow_from_module(mymodule): class Obj: flow = Flow("multi-level flow") mymodule.flow = Flow("top level flow") mymodule.multi_level = Obj() mymodule.bad_type = 1 # module with single top-level flow has flow auto-inferred assert extract_flow_from_module("mymodule") is mymodule.flow # Specifying name/attribute still works assert extract_flow_from_module("mymodule", "top level flow") is mymodule.flow assert extract_flow_from_module("mymodule:flow", "top level flow") is mymodule.flow # Multi-level attrs work assert extract_flow_from_module("mymodule:multi_level.flow") is Obj.flow # Multiple top-level flows mymodule.flow2 = Flow("a second flow") assert extract_flow_from_module("mymodule", "top level flow") is mymodule.flow assert extract_flow_from_module("mymodule", "a second flow") is mymodule.flow2 # Multiple flows not auto-inferred with pytest.raises(ValueError, match="Multiple flows found"): extract_flow_from_module("mymodule") # Name not found with pytest.raises(ValueError, match="Failed to find flow"): extract_flow_from_module("mymodule", "unknown name") # Name doesn't match specified object with pytest.raises(ValueError, match="Flow at 'mymodule:flow' is named"): extract_flow_from_module("mymodule:flow", "incorrect name") # Not a flow object with pytest.raises(TypeError, match="Object at 'mymodule:bad_type'"): extract_flow_from_module("mymodule:bad_type") def test_extract_flow_from_module_callable_objects(mymodule): flow1 = Flow("flow 1") flow2 = Flow("flow 2") class Obj: def build_flow(self): return flow2 mymodule.build_flow = lambda: flow1 mymodule.multi_level = Obj() mymodule.bad_type = lambda: 1 assert extract_flow_from_module("mymodule:build_flow") is flow1 assert extract_flow_from_module("mymodule:build_flow", "flow 1") is flow1 assert extract_flow_from_module("mymodule:multi_level.build_flow") is flow2 with pytest.raises(TypeError, match="Object at 'mymodule:bad_type'"): extract_flow_from_module("mymodule:bad_type") class RaiseOnLoad(Task): def __init__(self, exc): super().__init__() self.exc = exc @staticmethod def _raise(exc): raise exc def __reduce__(self): return (self._raise, (self.exc,)) class TestFlowToFromBytesPickle: def test_serialize_deserialize(self): s = flow_to_bytes_pickle(Flow("test")) assert isinstance(s, bytes) flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" def test_flow_from_bytes_loads_raw_pickle(self): """Older versions of prefect serialized flows as straight pickle bytes. This checks that we can still deserialize these payloads""" s = cloudpickle.dumps(Flow("test")) flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" def test_flow_from_bytes_warns_prefect_version_mismatch(self, monkeypatch): s = flow_to_bytes_pickle(Flow("test")) monkeypatch.setattr(prefect, "__version__", "0.1.0") with pytest.warns(UserWarning, match="This flow was built using Prefect"): flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" @pytest.mark.parametrize("version_mismatch", [False, True]) @pytest.mark.parametrize("import_error", [False, True]) def test_flow_from_bytes_error(self, monkeypatch, version_mismatch, import_error): exc = ImportError("mymodule") if import_error else ValueError("Oh no!") flow = Flow("test", tasks=[RaiseOnLoad(exc)]) s = flow_to_bytes_pickle(flow) if version_mismatch: monkeypatch.setattr(prefect, "__version__", "0.0.1") monkeypatch.setattr(cloudpickle, "__version__", "0.0.2") with pytest.raises( FlowStorageError, match="An error occurred while unpickling" ) as exc: flow_from_bytes_pickle(s) msg = "mymodule" if import_error else "Oh no!" assert msg in str(exc.value) # Extra components only present if relevant assert ("missing Python module" in str(exc.value)) == import_error assert ("version mismatches" in str(exc.value)) == version_mismatch

33.218182

87

0.67214

import os import sys import types import textwrap import pytest import cloudpickle import prefect from prefect import Flow, Task from prefect.storage import Docker, Local from prefect.exceptions import FlowStorageError from prefect.run_configs import DockerRun, UniversalRun from prefect.utilities.storage import ( get_flow_image, extract_flow_from_file, extract_flow_from_module, flow_to_bytes_pickle, flow_from_bytes_pickle, ) def test_get_flow_image_docker_storage(): flow = Flow( "test", run_config=UniversalRun(), storage=Docker(registry_url="test", image_name="name", image_tag="tag"), ) image = get_flow_image(flow=flow) assert image == "test/name:tag" def test_get_flow_image_run_config(): flow = Flow( "test", run_config=DockerRun(image="repo/name:tag"), storage=Local(), ) image = get_flow_image(flow=flow) assert image == "repo/name:tag" def test_get_flow_image_raises_on_missing_info(): flow = Flow( "test", run_config=UniversalRun(), storage=Local(), ) with pytest.raises(ValueError): get_flow_image(flow=flow) class TestExtractFlowFromFile: @pytest.fixture def flow_path(self, tmpdir): contents = """from prefect import Flow\nf=Flow('flow-1')\nf2=Flow('flow-2')""" full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(contents) return full_path @pytest.fixture def flow_path_with_additional_file(self, tmpdir): contents = """\ from prefect import Flow from pathlib import Path with open(str(Path(__file__).resolve().parent)+"/test.txt", "r") as f: name = f.read() f2 = Flow(name) """ full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(textwrap.dedent(contents)) with open(os.path.join(tmpdir, "test.txt"), "w") as f: f.write("test-flow") return full_path def test_extract_flow_from_file_path(self, flow_path): flow = extract_flow_from_file(file_path=flow_path) assert flow.name == "flow-1" assert flow.run().is_successful() flow = extract_flow_from_file(file_path=flow_path, flow_name="flow-1") assert flow.name == "flow-1" flow = extract_flow_from_file(file_path=flow_path, flow_name="flow-2") assert flow.name == "flow-2" def test_extract_flow_from_file_path_can_load_files_from_same_directory( self, flow_path_with_additional_file ): flow = extract_flow_from_file(file_path=flow_path_with_additional_file) assert flow.name == "test-flow" assert flow.run().is_successful() def test_extract_flow_from_file_contents(self, flow_path): with open(flow_path, "r") as f: contents = f.read() flow = extract_flow_from_file(file_contents=contents) assert flow.name == "flow-1" assert flow.run().is_successful() flow = extract_flow_from_file(file_contents=contents, flow_name="flow-1") assert flow.name == "flow-1" flow = extract_flow_from_file(file_contents=contents, flow_name="flow-2") assert flow.name == "flow-2" def test_extract_flow_from_file_errors(self, flow_path): with pytest.raises(ValueError, match="but not both"): extract_flow_from_file(file_path="", file_contents="") with pytest.raises(ValueError, match="Provide either"): extract_flow_from_file() expected = ( "Flow 'not-real' not found in file. Found flows:\n- 'flow-1'\n- 'flow-2'" ) with pytest.raises(ValueError, match=expected): extract_flow_from_file(file_path=flow_path, flow_name="not-real") with pytest.raises(ValueError, match="No flows found in file."): extract_flow_from_file(file_contents="") @pytest.mark.parametrize("method", ["run", "register"]) def test_extract_flow_from_file_raises_on_run_register(self, tmpdir, method): contents = f"from prefect import Flow\nf=Flow('test-flow')\nf.{method}()" full_path = os.path.join(tmpdir, "flow.py") with open(full_path, "w") as f: f.write(contents) with prefect.context({"loading_flow": True}): with pytest.warns(Warning): extract_flow_from_file(file_path=full_path) @pytest.fixture def mymodule(monkeypatch): mod_name = "mymodule" module = types.ModuleType(mod_name) monkeypatch.setitem(sys.modules, mod_name, module) return module def test_extract_flow_from_module(mymodule): class Obj: flow = Flow("multi-level flow") mymodule.flow = Flow("top level flow") mymodule.multi_level = Obj() mymodule.bad_type = 1 assert extract_flow_from_module("mymodule") is mymodule.flow assert extract_flow_from_module("mymodule", "top level flow") is mymodule.flow assert extract_flow_from_module("mymodule:flow", "top level flow") is mymodule.flow assert extract_flow_from_module("mymodule:multi_level.flow") is Obj.flow mymodule.flow2 = Flow("a second flow") assert extract_flow_from_module("mymodule", "top level flow") is mymodule.flow assert extract_flow_from_module("mymodule", "a second flow") is mymodule.flow2 with pytest.raises(ValueError, match="Multiple flows found"): extract_flow_from_module("mymodule") with pytest.raises(ValueError, match="Failed to find flow"): extract_flow_from_module("mymodule", "unknown name") with pytest.raises(ValueError, match="Flow at 'mymodule:flow' is named"): extract_flow_from_module("mymodule:flow", "incorrect name") # Not a flow object with pytest.raises(TypeError, match="Object at 'mymodule:bad_type'"): extract_flow_from_module("mymodule:bad_type") def test_extract_flow_from_module_callable_objects(mymodule): flow1 = Flow("flow 1") flow2 = Flow("flow 2") class Obj: def build_flow(self): return flow2 mymodule.build_flow = lambda: flow1 mymodule.multi_level = Obj() mymodule.bad_type = lambda: 1 assert extract_flow_from_module("mymodule:build_flow") is flow1 assert extract_flow_from_module("mymodule:build_flow", "flow 1") is flow1 assert extract_flow_from_module("mymodule:multi_level.build_flow") is flow2 with pytest.raises(TypeError, match="Object at 'mymodule:bad_type'"): extract_flow_from_module("mymodule:bad_type") class RaiseOnLoad(Task): def __init__(self, exc): super().__init__() self.exc = exc @staticmethod def _raise(exc): raise exc def __reduce__(self): return (self._raise, (self.exc,)) class TestFlowToFromBytesPickle: def test_serialize_deserialize(self): s = flow_to_bytes_pickle(Flow("test")) assert isinstance(s, bytes) flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" def test_flow_from_bytes_loads_raw_pickle(self): s = cloudpickle.dumps(Flow("test")) flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" def test_flow_from_bytes_warns_prefect_version_mismatch(self, monkeypatch): s = flow_to_bytes_pickle(Flow("test")) monkeypatch.setattr(prefect, "__version__", "0.1.0") with pytest.warns(UserWarning, match="This flow was built using Prefect"): flow = flow_from_bytes_pickle(s) assert isinstance(flow, Flow) assert flow.name == "test" @pytest.mark.parametrize("version_mismatch", [False, True]) @pytest.mark.parametrize("import_error", [False, True]) def test_flow_from_bytes_error(self, monkeypatch, version_mismatch, import_error): exc = ImportError("mymodule") if import_error else ValueError("Oh no!") flow = Flow("test", tasks=[RaiseOnLoad(exc)]) s = flow_to_bytes_pickle(flow) if version_mismatch: monkeypatch.setattr(prefect, "__version__", "0.0.1") monkeypatch.setattr(cloudpickle, "__version__", "0.0.2") with pytest.raises( FlowStorageError, match="An error occurred while unpickling" ) as exc: flow_from_bytes_pickle(s) msg = "mymodule" if import_error else "Oh no!" assert msg in str(exc.value) # Extra components only present if relevant assert ("missing Python module" in str(exc.value)) == import_error assert ("version mismatches" in str(exc.value)) == version_mismatch

true

f7390dce5ed924db4eacae76988830e0d21eb18c

7,605

py

Python

iot/api-client/http_example/cloudiot_http_example.py

bxue16/bx_byte1

e8c2face224f16ab2d2fa927a0c944176e4dd557

[ "Apache-2.0" ]

null

iot/api-client/http_example/cloudiot_http_example.py

bxue16/bx_byte1

e8c2face224f16ab2d2fa927a0c944176e4dd557

[ "Apache-2.0" ]

null

iot/api-client/http_example/cloudiot_http_example.py

bxue16/bx_byte1

e8c2face224f16ab2d2fa927a0c944176e4dd557

[ "Apache-2.0" ]

1

2018-09-19T05:55:27.000Z

#!/usr/bin/env python # Copyright 2017 Google Inc. # # 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. """Python sample for connecting to Google Cloud IoT Core via HTTP, using JWT. This example connects to Google Cloud IoT Core via HTTP, using a JWT for device authentication. After connecting, by default the device publishes 100 messages to the server at a rate of one per second, and then exits. Before you run the sample, you must register your device as described in the README in the parent folder. """ import argparse import base64 import datetime import json import time from google.api_core import retry import jwt import requests _BASE_URL = 'https://cloudiot-device.googleapis.com/v1beta1' _BACKOFF_DURATION = 60 def create_jwt(project_id, private_key_file, algorithm): token = { # The time the token was issued. 'iat': datetime.datetime.utcnow(), # Token expiration time. 'exp': datetime.datetime.utcnow() + datetime.timedelta(minutes=60), # The audience field should always be set to the GCP project id. 'aud': project_id } # Read the private key file. with open(private_key_file, 'r') as f: private_key = f.read() print('Creating JWT using {} from private key file {}'.format( algorithm, private_key_file)) return jwt.encode(token, private_key, algorithm=algorithm).decode('ascii') @retry.Retry( predicate=retry.if_exception_type(AssertionError), deadline=_BACKOFF_DURATION) def publish_message( message, message_type, base_url, project_id, cloud_region, registry_id, device_id, jwt_token): headers = { 'authorization': 'Bearer {}'.format(jwt_token), 'content-type': 'application/json', 'cache-control': 'no-cache' } # Publish to the events or state topic based on the flag. url_suffix = 'publishEvent' if message_type == 'event' else 'setState' publish_url = ( '{}/projects/{}/locations/{}/registries/{}/devices/{}:{}').format( base_url, project_id, cloud_region, registry_id, device_id, url_suffix) body = None msg_bytes = base64.urlsafe_b64encode(message.encode('utf-8')) if message_type == 'event': body = {'binary_data': msg_bytes.decode('ascii')} else: body = { 'state': {'binary_data': msg_bytes.decode('ascii')} } resp = requests.post( publish_url, data=json.dumps(body), headers=headers) if (resp.status_code != 200): print('Response came back {}, retrying'.format(resp.status_code)) raise AssertionError('Not OK response: {}'.format(resp.status_code)) return resp @retry.Retry( predicate=retry.if_exception_type(AssertionError), deadline=_BACKOFF_DURATION) # [START iot_http_getconfig] def get_config( version, message_type, base_url, project_id, cloud_region, registry_id, device_id, jwt_token): headers = { 'authorization': 'Bearer {}'.format(jwt_token), 'content-type': 'application/json', 'cache-control': 'no-cache' } basepath = '{}/projects/{}/locations/{}/registries/{}/devices/{}/' template = basepath + 'config?local_version={}' config_url = template.format( base_url, project_id, cloud_region, registry_id, device_id, version) resp = requests.get(config_url, headers=headers) if (resp.status_code != 200): print('Error getting config: {}, retrying'.format(resp.status_code)) raise AssertionError('Not OK response: {}'.format(resp.status_code)) return resp # [END iot_http_getconfig] def parse_command_line_args(): """Parse command line arguments.""" parser = argparse.ArgumentParser(description=( 'Example Google Cloud IoT Core HTTP device connection code.')) parser.add_argument( '--project_id', required=True, help='GCP cloud project name') parser.add_argument( '--registry_id', required=True, help='Cloud IoT Core registry id') parser.add_argument( '--device_id', required=True, help='Cloud IoT Core device id') parser.add_argument( '--private_key_file', required=True, help='Path to private key file.') parser.add_argument( '--algorithm', choices=('RS256', 'ES256'), required=True, help='The encryption algorithm to use to generate the JWT.') parser.add_argument( '--cloud_region', default='us-central1', help='GCP cloud region') parser.add_argument( '--ca_certs', default='roots.pem', help=('CA root from https://pki.google.com/roots.pem')) parser.add_argument( '--num_messages', type=int, default=100, help='Number of messages to publish.') parser.add_argument( '--message_type', choices=('event', 'state'), default='event', required=True, help=('Indicates whether the message to be published is a ' 'telemetry event or a device state message.')) parser.add_argument( '--base_url', default=_BASE_URL, help=('Base URL for the Cloud IoT Core Device Service API')) parser.add_argument( '--jwt_expires_minutes', default=20, type=int, help=('Expiration time, in minutes, for JWT tokens.')) return parser.parse_args() def main(): args = parse_command_line_args() jwt_token = create_jwt( args.project_id, args.private_key_file, args.algorithm) jwt_iat = datetime.datetime.utcnow() jwt_exp_mins = args.jwt_expires_minutes print('Latest configuration: {}'.format(get_config( '0', args.message_type, args.base_url, args.project_id, args.cloud_region, args.registry_id, args.device_id, jwt_token).text)) # Publish num_messages mesages to the HTTP bridge once per second. for i in range(1, args.num_messages + 1): seconds_since_issue = (datetime.datetime.utcnow() - jwt_iat).seconds if seconds_since_issue > 60 * jwt_exp_mins: print('Refreshing token after {}s').format(seconds_since_issue) jwt_token = create_jwt( args.project_id, args.private_key_file, args.algorithm) jwt_iat = datetime.datetime.utcnow() payload = '{}/{}-payload-{}'.format( args.registry_id, args.device_id, i) print('Publishing message {}/{}: \'{}\''.format( i, args.num_messages, payload)) resp = publish_message( payload, args.message_type, args.base_url, args.project_id, args.cloud_region, args.registry_id, args.device_id, jwt_token) print('HTTP response: ', resp) # Send events every second. State should not be updated as often time.sleep(1 if args.message_type == 'event' else 5) print('Finished.') if __name__ == '__main__': main()

35.372093

79

0.644313

import argparse import base64 import datetime import json import time from google.api_core import retry import jwt import requests _BASE_URL = 'https://cloudiot-device.googleapis.com/v1beta1' _BACKOFF_DURATION = 60 def create_jwt(project_id, private_key_file, algorithm): token = { 'iat': datetime.datetime.utcnow(), 'exp': datetime.datetime.utcnow() + datetime.timedelta(minutes=60), 'aud': project_id } with open(private_key_file, 'r') as f: private_key = f.read() print('Creating JWT using {} from private key file {}'.format( algorithm, private_key_file)) return jwt.encode(token, private_key, algorithm=algorithm).decode('ascii') @retry.Retry( predicate=retry.if_exception_type(AssertionError), deadline=_BACKOFF_DURATION) def publish_message( message, message_type, base_url, project_id, cloud_region, registry_id, device_id, jwt_token): headers = { 'authorization': 'Bearer {}'.format(jwt_token), 'content-type': 'application/json', 'cache-control': 'no-cache' } url_suffix = 'publishEvent' if message_type == 'event' else 'setState' publish_url = ( '{}/projects/{}/locations/{}/registries/{}/devices/{}:{}').format( base_url, project_id, cloud_region, registry_id, device_id, url_suffix) body = None msg_bytes = base64.urlsafe_b64encode(message.encode('utf-8')) if message_type == 'event': body = {'binary_data': msg_bytes.decode('ascii')} else: body = { 'state': {'binary_data': msg_bytes.decode('ascii')} } resp = requests.post( publish_url, data=json.dumps(body), headers=headers) if (resp.status_code != 200): print('Response came back {}, retrying'.format(resp.status_code)) raise AssertionError('Not OK response: {}'.format(resp.status_code)) return resp @retry.Retry( predicate=retry.if_exception_type(AssertionError), deadline=_BACKOFF_DURATION) def get_config( version, message_type, base_url, project_id, cloud_region, registry_id, device_id, jwt_token): headers = { 'authorization': 'Bearer {}'.format(jwt_token), 'content-type': 'application/json', 'cache-control': 'no-cache' } basepath = '{}/projects/{}/locations/{}/registries/{}/devices/{}/' template = basepath + 'config?local_version={}' config_url = template.format( base_url, project_id, cloud_region, registry_id, device_id, version) resp = requests.get(config_url, headers=headers) if (resp.status_code != 200): print('Error getting config: {}, retrying'.format(resp.status_code)) raise AssertionError('Not OK response: {}'.format(resp.status_code)) return resp def parse_command_line_args(): parser = argparse.ArgumentParser(description=( 'Example Google Cloud IoT Core HTTP device connection code.')) parser.add_argument( '--project_id', required=True, help='GCP cloud project name') parser.add_argument( '--registry_id', required=True, help='Cloud IoT Core registry id') parser.add_argument( '--device_id', required=True, help='Cloud IoT Core device id') parser.add_argument( '--private_key_file', required=True, help='Path to private key file.') parser.add_argument( '--algorithm', choices=('RS256', 'ES256'), required=True, help='The encryption algorithm to use to generate the JWT.') parser.add_argument( '--cloud_region', default='us-central1', help='GCP cloud region') parser.add_argument( '--ca_certs', default='roots.pem', help=('CA root from https://pki.google.com/roots.pem')) parser.add_argument( '--num_messages', type=int, default=100, help='Number of messages to publish.') parser.add_argument( '--message_type', choices=('event', 'state'), default='event', required=True, help=('Indicates whether the message to be published is a ' 'telemetry event or a device state message.')) parser.add_argument( '--base_url', default=_BASE_URL, help=('Base URL for the Cloud IoT Core Device Service API')) parser.add_argument( '--jwt_expires_minutes', default=20, type=int, help=('Expiration time, in minutes, for JWT tokens.')) return parser.parse_args() def main(): args = parse_command_line_args() jwt_token = create_jwt( args.project_id, args.private_key_file, args.algorithm) jwt_iat = datetime.datetime.utcnow() jwt_exp_mins = args.jwt_expires_minutes print('Latest configuration: {}'.format(get_config( '0', args.message_type, args.base_url, args.project_id, args.cloud_region, args.registry_id, args.device_id, jwt_token).text)) for i in range(1, args.num_messages + 1): seconds_since_issue = (datetime.datetime.utcnow() - jwt_iat).seconds if seconds_since_issue > 60 * jwt_exp_mins: print('Refreshing token after {}s').format(seconds_since_issue) jwt_token = create_jwt( args.project_id, args.private_key_file, args.algorithm) jwt_iat = datetime.datetime.utcnow() payload = '{}/{}-payload-{}'.format( args.registry_id, args.device_id, i) print('Publishing message {}/{}: \'{}\''.format( i, args.num_messages, payload)) resp = publish_message( payload, args.message_type, args.base_url, args.project_id, args.cloud_region, args.registry_id, args.device_id, jwt_token) print('HTTP response: ', resp) time.sleep(1 if args.message_type == 'event' else 5) print('Finished.') if __name__ == '__main__': main()

true

f7390e4926bf78ad6d372fb87866cacff08ee9fb

7,677

py

Python

tests/e2e/test_clickhouse.py

a-dot/clickhouse-operator

cecb54ad1ade33a9d748a0108e765abad9b2412e

[ "Apache-2.0" ]

null

tests/e2e/test_clickhouse.py

a-dot/clickhouse-operator

cecb54ad1ade33a9d748a0108e765abad9b2412e

[ "Apache-2.0" ]

null

tests/e2e/test_clickhouse.py

a-dot/clickhouse-operator

cecb54ad1ade33a9d748a0108e765abad9b2412e

[ "Apache-2.0" ]

null

import time import e2e.clickhouse as clickhouse import e2e.kubectl as kubectl import e2e.yaml_manifest as yaml_manifest import e2e.settings as settings import e2e.util as util from testflows.core import * from testflows.asserts import error @TestScenario @Name("test_ch_001. Insert quorum") def test_ch_001(self): util.require_keeper(keeper_type=self.context.keeper_type) quorum_template = "manifests/chit/tpl-clickhouse-21.8.yaml" chit_data = yaml_manifest.get_manifest_data(util.get_full_path(quorum_template)) kubectl.launch(f"delete chit {chit_data['metadata']['name']}", ns=settings.test_namespace, ok_to_fail=True) kubectl.create_and_check( "manifests/chi/test-ch-001-insert-quorum.yaml", { "apply_templates": {quorum_template}, "pod_count": 2, "do_not_delete": 1, }) chi = yaml_manifest.get_chi_name(util.get_full_path("manifests/chi/test-ch-001-insert-quorum.yaml")) chi_data = kubectl.get("chi", ns=settings.test_namespace, name=chi) util.wait_clickhouse_cluster_ready(chi_data) host0 = "chi-test-ch-001-insert-quorum-default-0-0" host1 = "chi-test-ch-001-insert-quorum-default-0-1" create_table = """ create table t1 on cluster default (a Int8, d Date default today()) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by d order by a TTL d + interval 5 second SETTINGS merge_with_ttl_timeout=5""".replace('\r', '').replace('\n', '') create_mv_table2 = """ create table t2 on cluster default (a Int8) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by tuple() order by a""".replace('\r', '').replace('\n', '') create_mv_table3 = """ create table t3 on cluster default (a Int8) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by tuple() order by a""".replace('\r', '').replace('\n', '') create_mv2 = "create materialized view t_mv2 on cluster default to t2 as select a from t1" create_mv3 = "create materialized view t_mv3 on cluster default to t3 as select a from t1" with Given("Tables t1, t2, t3 and MVs t1->t2, t1-t3 are created"): clickhouse.query(chi, create_table) clickhouse.query(chi, create_mv_table2) clickhouse.query(chi, create_mv_table3) clickhouse.query(chi, create_mv2) clickhouse.query(chi, create_mv3) with When("Add a row to an old partition"): clickhouse.query(chi, "insert into t1(a,d) values(6, today()-1)", host=host0) with When("Stop fetches for t1 at replica1"): clickhouse.query(chi, "system stop fetches default.t1", host=host1) with Then("Wait 10 seconds and the data should be dropped by TTL"): time.sleep(10) out = clickhouse.query(chi, "select count() from t1 where a=6", host=host0) assert out == "0", error() with When("Resume fetches for t1 at replica1"): clickhouse.query(chi, "system start fetches default.t1", host=host1) time.sleep(5) with Then("Inserts should resume"): clickhouse.query(chi, "insert into t1(a) values(7)", host=host0) clickhouse.query(chi, "insert into t1(a) values(1)") with When("Stop fetches for t2 at replica1"): clickhouse.query(chi, "system stop fetches default.t2", host=host1) with Then("Insert should fail since it can not reach the quorum"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(2)", host=host0) assert "Timeout while waiting for quorum" in out, error() # kubectl(f"exec {host0}-0 -n test -- cp /var/lib//clickhouse/data/default/t2/all_1_1_0/a.mrk2 /var/lib//clickhouse/data/default/t2/all_1_1_0/a.bin") # with Then("Corrupt data part in t2"): # kubectl(f"exec {host0}-0 -n test -- sed -i \"s/b/c/\" /var/lib/clickhouse/data/default/t2/all_1_1_0/a.bin") with When("Resume fetches for t2 at replica1"): clickhouse.query(chi, "system start fetches default.t2", host=host1) i = 0 while "2" != clickhouse.query(chi, "select active_replicas from system.replicas where database='default' and table='t1'", pod=host0) and i < 10: with Then("Not ready, wait 5 seconds"): time.sleep(5) i += 1 with Then("Inserts should fail with an error regarding not satisfied quorum"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(3)", host=host0) assert "Quorum for previous write has not been satisfied yet" in out, error() with And("Second insert of the same block should pass"): clickhouse.query(chi, "insert into t1(a) values(3)", host=host0) with And("Insert of the new block should fail"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(4)", host=host0) assert "Quorum for previous write has not been satisfied yet" in out, error() with And("Second insert of the same block with 'deduplicate_blocks_in_dependent_materialized_views' setting should fail"): out = clickhouse.query_with_error( chi, "set deduplicate_blocks_in_dependent_materialized_views=1; insert into t1(a) values(5)", host=host0 ) assert "Quorum for previous write has not been satisfied yet" in out, error() out = clickhouse.query_with_error( chi, "select t1.a t1_a, t2.a t2_a from t1 left outer join t2 using (a) order by t1_a settings join_use_nulls=1" ) note(out) # cat /var/log/clickhouse-server/clickhouse-server.log | grep t2 | grep -E "all_1_1_0|START|STOP" @TestScenario @Name("test_ch_002. Row-level security") def test_ch_002(self): kubectl.create_and_check( "manifests/chi/test-ch-002-row-level.yaml", { "apply_templates": {"manifests/chit/tpl-clickhouse-21.8.yaml"}, "do_not_delete": 1, }) chi = "test-ch-002-row-level" create_table = """create table test (d Date default today(), team LowCardinality(String), user String) Engine = MergeTree() PARTITION BY d ORDER BY d;""" with When("Create test table"): clickhouse.query(chi, create_table) with And("Insert some data"): clickhouse.query( chi, "INSERT INTO test(team, user) values('team1', 'user1'),('team2', 'user2'),('team3', 'user3'),('team4', 'user4')" ) with Then("Make another query for different users. It should be restricted to corresponding team by row-level security"): for user in ['user1', 'user2', 'user3', 'user4']: out = clickhouse.query(chi, "select user from test", user=user, pwd=user) assert out == user, error() with Then("Make a count() query for different users. It should be restricted to corresponding team by row-level security"): for user in ['user1', 'user2', 'user3', 'user4']: out = clickhouse.query(chi, "select count() from test", user=user, pwd=user) assert out == "1", error() kubectl.delete_chi(chi) @TestFeature @Name("e2e.test_clickhouse") def test(self): util.clean_namespace(delete_chi=False) all_tests = [ test_ch_001, test_ch_002, ] run_test = all_tests # placeholder for selective test running # run_test = [test_ch_002] for t in run_test: Scenario(test=t)()

42.65

157

0.639703

import time import e2e.clickhouse as clickhouse import e2e.kubectl as kubectl import e2e.yaml_manifest as yaml_manifest import e2e.settings as settings import e2e.util as util from testflows.core import * from testflows.asserts import error @TestScenario @Name("test_ch_001. Insert quorum") def test_ch_001(self): util.require_keeper(keeper_type=self.context.keeper_type) quorum_template = "manifests/chit/tpl-clickhouse-21.8.yaml" chit_data = yaml_manifest.get_manifest_data(util.get_full_path(quorum_template)) kubectl.launch(f"delete chit {chit_data['metadata']['name']}", ns=settings.test_namespace, ok_to_fail=True) kubectl.create_and_check( "manifests/chi/test-ch-001-insert-quorum.yaml", { "apply_templates": {quorum_template}, "pod_count": 2, "do_not_delete": 1, }) chi = yaml_manifest.get_chi_name(util.get_full_path("manifests/chi/test-ch-001-insert-quorum.yaml")) chi_data = kubectl.get("chi", ns=settings.test_namespace, name=chi) util.wait_clickhouse_cluster_ready(chi_data) host0 = "chi-test-ch-001-insert-quorum-default-0-0" host1 = "chi-test-ch-001-insert-quorum-default-0-1" create_table = """ create table t1 on cluster default (a Int8, d Date default today()) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by d order by a TTL d + interval 5 second SETTINGS merge_with_ttl_timeout=5""".replace('\r', '').replace('\n', '') create_mv_table2 = """ create table t2 on cluster default (a Int8) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by tuple() order by a""".replace('\r', '').replace('\n', '') create_mv_table3 = """ create table t3 on cluster default (a Int8) Engine = ReplicatedMergeTree('/clickhouse/tables/{table}', '{replica}') partition by tuple() order by a""".replace('\r', '').replace('\n', '') create_mv2 = "create materialized view t_mv2 on cluster default to t2 as select a from t1" create_mv3 = "create materialized view t_mv3 on cluster default to t3 as select a from t1" with Given("Tables t1, t2, t3 and MVs t1->t2, t1-t3 are created"): clickhouse.query(chi, create_table) clickhouse.query(chi, create_mv_table2) clickhouse.query(chi, create_mv_table3) clickhouse.query(chi, create_mv2) clickhouse.query(chi, create_mv3) with When("Add a row to an old partition"): clickhouse.query(chi, "insert into t1(a,d) values(6, today()-1)", host=host0) with When("Stop fetches for t1 at replica1"): clickhouse.query(chi, "system stop fetches default.t1", host=host1) with Then("Wait 10 seconds and the data should be dropped by TTL"): time.sleep(10) out = clickhouse.query(chi, "select count() from t1 where a=6", host=host0) assert out == "0", error() with When("Resume fetches for t1 at replica1"): clickhouse.query(chi, "system start fetches default.t1", host=host1) time.sleep(5) with Then("Inserts should resume"): clickhouse.query(chi, "insert into t1(a) values(7)", host=host0) clickhouse.query(chi, "insert into t1(a) values(1)") with When("Stop fetches for t2 at replica1"): clickhouse.query(chi, "system stop fetches default.t2", host=host1) with Then("Insert should fail since it can not reach the quorum"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(2)", host=host0) assert "Timeout while waiting for quorum" in out, error() with When("Resume fetches for t2 at replica1"): clickhouse.query(chi, "system start fetches default.t2", host=host1) i = 0 while "2" != clickhouse.query(chi, "select active_replicas from system.replicas where database='default' and table='t1'", pod=host0) and i < 10: with Then("Not ready, wait 5 seconds"): time.sleep(5) i += 1 with Then("Inserts should fail with an error regarding not satisfied quorum"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(3)", host=host0) assert "Quorum for previous write has not been satisfied yet" in out, error() with And("Second insert of the same block should pass"): clickhouse.query(chi, "insert into t1(a) values(3)", host=host0) with And("Insert of the new block should fail"): out = clickhouse.query_with_error(chi, "insert into t1(a) values(4)", host=host0) assert "Quorum for previous write has not been satisfied yet" in out, error() with And("Second insert of the same block with 'deduplicate_blocks_in_dependent_materialized_views' setting should fail"): out = clickhouse.query_with_error( chi, "set deduplicate_blocks_in_dependent_materialized_views=1; insert into t1(a) values(5)", host=host0 ) assert "Quorum for previous write has not been satisfied yet" in out, error() out = clickhouse.query_with_error( chi, "select t1.a t1_a, t2.a t2_a from t1 left outer join t2 using (a) order by t1_a settings join_use_nulls=1" ) note(out) @TestScenario @Name("test_ch_002. Row-level security") def test_ch_002(self): kubectl.create_and_check( "manifests/chi/test-ch-002-row-level.yaml", { "apply_templates": {"manifests/chit/tpl-clickhouse-21.8.yaml"}, "do_not_delete": 1, }) chi = "test-ch-002-row-level" create_table = """create table test (d Date default today(), team LowCardinality(String), user String) Engine = MergeTree() PARTITION BY d ORDER BY d;""" with When("Create test table"): clickhouse.query(chi, create_table) with And("Insert some data"): clickhouse.query( chi, "INSERT INTO test(team, user) values('team1', 'user1'),('team2', 'user2'),('team3', 'user3'),('team4', 'user4')" ) with Then("Make another query for different users. It should be restricted to corresponding team by row-level security"): for user in ['user1', 'user2', 'user3', 'user4']: out = clickhouse.query(chi, "select user from test", user=user, pwd=user) assert out == user, error() with Then("Make a count() query for different users. It should be restricted to corresponding team by row-level security"): for user in ['user1', 'user2', 'user3', 'user4']: out = clickhouse.query(chi, "select count() from test", user=user, pwd=user) assert out == "1", error() kubectl.delete_chi(chi) @TestFeature @Name("e2e.test_clickhouse") def test(self): util.clean_namespace(delete_chi=False) all_tests = [ test_ch_001, test_ch_002, ] run_test = all_tests for t in run_test: Scenario(test=t)()

true

f7390f2181b2fb75bb45374f2417c1618860d2fb

387

py

Python

djnic/djnic/wsgi.py

avdata99/nic

70399bd78fd2b4b496d338e7959867ad12cdf477

[ "MIT" ]

8

2021-05-01T13:03:22.000Z

2021-12-17T21:50:04.000Z

djnic/djnic/wsgi.py

avdata99/nic

70399bd78fd2b4b496d338e7959867ad12cdf477

[ "MIT" ]

16

2020-11-20T23:18:22.000Z

2021-04-08T20:09:35.000Z

djnic/djnic/wsgi.py

OpenDataCordoba/nic

f9528856e13d106bdfb476cab1236bc5b8a92183

[ "MIT" ]

null

""" WSGI config for djnic project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'djnic.settings') application = get_wsgi_application()

22.764706

78

0.782946

import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'djnic.settings') application = get_wsgi_application()

true

f7390f52affc6ece0f1ab2fdfedbef5e4b8f2be3

7,721

py

Python

doc/conf.py

dbolshak/secure-xgboost

fd4f240fc35b07329b39795fc17a5ad5540656ec

[ "Apache-2.0" ]

77

2019-10-28T04:41:29.000Z

2022-03-04T03:56:47.000Z

doc/conf.py

dbolshak/secure-xgboost

fd4f240fc35b07329b39795fc17a5ad5540656ec

[ "Apache-2.0" ]

61

2020-02-25T21:18:39.000Z

2020-06-20T10:13:39.000Z

doc/conf.py

chester-leung/mc2-xgboost

71c00b7c597a7145aae179980052bff79ec61846

[ "Apache-2.0" ]

27

2019-10-02T00:04:18.000Z

2022-03-02T07:57:46.000Z

# -*- coding: utf-8 -*- # # documentation build configuration file, created by # sphinx-quickstart on Thu Jul 23 19:40:08 2015. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. from subprocess import call # from sh.contrib import git # import urllib.request # from urllib.error import HTTPError from recommonmark.parser import CommonMarkParser import sys import re import os, subprocess import shlex # import guzzle_sphinx_theme # git_branch = os.getenv('SPHINX_GIT_BRANCH', default=None) # if git_branch is None: # # If SPHINX_GIT_BRANCH environment variable is not given, run git to determine branch name # git_branch = [re.sub(r'origin/', '', x.lstrip(' ')) for x in str(git.branch('-r', '--contains', 'HEAD')).rstrip('\n').split('\n')] # git_branch = [x for x in git_branch if 'HEAD' not in x] # print('git_branch = {}'.format(git_branch[0])) # try: # filename, _ = urllib.request.urlretrieve('https://s3-us-west-2.amazonaws.com/xgboost-docs/{}.tar.bz2'.format(git_branch[0])) # call('if [ -d tmp ]; then rm -rf tmp; fi; mkdir -p tmp/jvm; cd tmp/jvm; tar xvf {}'.format(filename), shell=True) # except HTTPError: # print('JVM doc not found. Skipping...') # try: # filename, _ = urllib.request.urlretrieve('https://s3-us-west-2.amazonaws.com/xgboost-docs/doxygen/{}.tar.bz2'.format(git_branch[0])) # call('mkdir -p tmp/dev; cd tmp/dev; tar xvf {}; mv doc_doxygen/html/* .; rm -rf doc_doxygen'.format(filename), shell=True) # except HTTPError: # print('C API doc not found. Skipping...') # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__))) libpath = os.path.join(curr_path, '../python-package/') sys.path.insert(0, libpath) sys.path.insert(0, curr_path) # -- mock out modules import mock MOCK_MODULES = ['scipy', 'scipy.sparse', 'sklearn', 'pandas'] for mod_name in MOCK_MODULES: sys.modules[mod_name] = mock.Mock() # -- General configuration ------------------------------------------------ # General information about the project. project = u'Secure XGBoost' author = u'%s developers' % project copyright = u'2020, %s' % author github_doc_root = 'https://github.com/mc2-project/secure-xgboost/tree/master/doc' os.environ['XGBOOST_BUILD_DOC'] = '1' # Version information. import securexgboost # version = securexgboost.__version__ # release = securexgboost.__version__ # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones extensions = [ 'matplotlib.sphinxext.plot_directive', 'sphinx.ext.autodoc', 'sphinx.ext.napoleon', 'sphinx.ext.mathjax', 'sphinx.ext.intersphinx', 'breathe', 'sphinx.ext.autosectionlabel' ] graphviz_output_format = 'png' plot_formats = [('svg', 300), ('png', 100), ('hires.png', 300)] plot_html_show_source_link = False plot_html_show_formats = False # Breathe extension variables breathe_projects = {"xgboost": "doxyxml/"} breathe_default_project = "xgboost" # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] source_parsers = { '.md': CommonMarkParser, } # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: source_suffix = ['.rst', '.md'] # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None autoclass_content = 'both' # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] html_extra_path = ['./tmp'] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. #keep_warnings = False # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = False # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = "furo" # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # html_theme_options = { "light_css_variables": { "color-brand-primary": "#00B0FF", "color-brand-content": "#00B0FF", "color-admonition-background": "#F0F0F0", }, } # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Output file base name for HTML help builder. htmlhelp_basename = project + 'doc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, '%s.tex' % project, project, author, 'manual'), ] intersphinx_mapping = {'python': ('https://docs.python.org/3.6', None), 'numpy': ('http://docs.scipy.org/doc/numpy/', None), 'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None), 'pandas': ('http://pandas-docs.github.io/pandas-docs-travis/', None), 'sklearn': ('http://scikit-learn.org/stable', None)} # hook for doxygen def run_doxygen(folder): """Run the doxygen make command in the designated folder.""" try: retcode = subprocess.call("cd %s; make doxygen" % folder, shell=True) if retcode < 0: sys.stderr.write("doxygen terminated by signal %s" % (-retcode)) except OSError as e: sys.stderr.write("doxygen execution failed: %s" % e) def generate_doxygen_xml(app): """Run the doxygen make commands if we're on the ReadTheDocs server""" read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True' if read_the_docs_build: run_doxygen('..') def setup(app): app.add_stylesheet('custom.css')

35.417431

137

0.696671

from subprocess import call from recommonmark.parser import CommonMarkParser import sys import re import os, subprocess import shlex )) libpath = os.path.join(curr_path, '../python-package/') sys.path.insert(0, libpath) sys.path.insert(0, curr_path) import mock MOCK_MODULES = ['scipy', 'scipy.sparse', 'sklearn', 'pandas'] for mod_name in MOCK_MODULES: sys.modules[mod_name] = mock.Mock() project = u'Secure XGBoost' author = u'%s developers' % project copyright = u'2020, %s' % author github_doc_root = 'https://github.com/mc2-project/secure-xgboost/tree/master/doc' os.environ['XGBOOST_BUILD_DOC'] = '1' import securexgboost extensions = [ 'matplotlib.sphinxext.plot_directive', 'sphinx.ext.autodoc', 'sphinx.ext.napoleon', 'sphinx.ext.mathjax', 'sphinx.ext.intersphinx', 'breathe', 'sphinx.ext.autosectionlabel' ] graphviz_output_format = 'png' plot_formats = [('svg', 300), ('png', 100), ('hires.png', 300)] plot_html_show_source_link = False plot_html_show_formats = False breathe_projects = {"xgboost": "doxyxml/"} breathe_default_project = "xgboost" templates_path = ['_templates'] source_parsers = { '.md': CommonMarkParser, } source_suffix = ['.rst', '.md'] master_doc = 'index' language = None autoclass_content = 'both' exclude_patterns = ['_build'] html_extra_path = ['./tmp'] pygments_style = 'sphinx' todo_include_todos = False html_theme = "furo" html_theme_options = { "light_css_variables": { "color-brand-primary": "#00B0FF", "color-brand-content": "#00B0FF", "color-admonition-background": "#F0F0F0", }, } html_static_path = ['_static'] htmlhelp_basename = project + 'doc' latex_elements = { } latex_documents = [ (master_doc, '%s.tex' % project, project, author, 'manual'), ] intersphinx_mapping = {'python': ('https://docs.python.org/3.6', None), 'numpy': ('http://docs.scipy.org/doc/numpy/', None), 'scipy': ('http://docs.scipy.org/doc/scipy/reference/', None), 'pandas': ('http://pandas-docs.github.io/pandas-docs-travis/', None), 'sklearn': ('http://scikit-learn.org/stable', None)} def run_doxygen(folder): try: retcode = subprocess.call("cd %s; make doxygen" % folder, shell=True) if retcode < 0: sys.stderr.write("doxygen terminated by signal %s" % (-retcode)) except OSError as e: sys.stderr.write("doxygen execution failed: %s" % e) def generate_doxygen_xml(app): read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True' if read_the_docs_build: run_doxygen('..') def setup(app): app.add_stylesheet('custom.css')

true

f7390f5e6066b32bfb5e0deb3646be9a163e3667

25,060

py

Python

SimG4Core/Application/python/g4SimHits_cfi.py

AFJohan92/cmssw

c5b36f05986c35998ddd4c873dc6812646579744

[ "Apache-2.0" ]

2

2020-01-21T11:23:39.000Z

2020-01-21T11:23:42.000Z

SimG4Core/Application/python/g4SimHits_cfi.py

AFJohan92/cmssw

c5b36f05986c35998ddd4c873dc6812646579744

[ "Apache-2.0" ]

null

SimG4Core/Application/python/g4SimHits_cfi.py

AFJohan92/cmssw

c5b36f05986c35998ddd4c873dc6812646579744

[ "Apache-2.0" ]

3

2019-03-09T13:06:43.000Z

2020-07-03T00:47:30.000Z

import FWCore.ParameterSet.Config as cms from SimG4Core.Application.hectorParameter_cfi import * ## HF Raddam Dose Class in /SimG4CMS/Calo from SimG4CMS.Calo.HFDarkeningParams_cff import * ## This object is used to customise g4SimHits for different running scenarios common_heavy_suppression = cms.PSet( NeutronThreshold = cms.double(30.0), ProtonThreshold = cms.double(30.0), IonThreshold = cms.double(30.0) ) common_maximum_time = cms.PSet( MaxTrackTime = cms.double(500.0), MaxTimeNames = cms.vstring('ZDCRegion'), MaxTrackTimes = cms.vdouble(2000.0), #DeadRegions = cms.vstring('QuadRegion','CastorRegion','InterimRegion'), DeadRegions = cms.vstring('QuadRegion','InterimRegion'), CriticalEnergyForVacuum = cms.double(2.0), CriticalDensity = cms.double(1e-15) ) common_UsePMT = cms.PSet( UseR7600UPMT = cms.bool(False) ) common_UseHF = cms.PSet( Lambda1 = cms.double(280.0), Lambda2 = cms.double(700.0), Gain = cms.double(0.33), CheckSurvive = cms.bool(False), FibreR = cms.untracked.double(0.3) ) common_UseLuminosity = cms.PSet( InstLuminosity = cms.double(0.), DelivLuminosity = cms.double(5000.) ) g4SimHits = cms.EDProducer("OscarMTProducer", g4GeometryDD4hepSource = cms.bool(False), NonBeamEvent = cms.bool(False), G4EventManagerVerbosity = cms.untracked.int32(0), UseMagneticField = cms.bool(True), StoreRndmSeeds = cms.bool(False), RestoreRndmSeeds = cms.bool(False), PhysicsTablesDirectory = cms.untracked.string('PhysicsTables'), StorePhysicsTables = cms.untracked.bool(False), RestorePhysicsTables = cms.untracked.bool(False), UseParametrisedEMPhysics = cms.untracked.bool(True), CheckGeometry = cms.untracked.bool(False), G4CheckOverlap = cms.untracked.PSet( OutputBaseName = cms.string('2017'), MaterialFlag = cms.bool(True), GeomFlag = cms.bool(True), OverlapFlag = cms.bool(False), RegionFlag = cms.bool(True), # if true - selection by G4Region name gdmlFlag = cms.bool(False), # if true - dump gdml file Verbose = cms.bool(True), Tolerance = cms.double(0.0), Resolution = cms.int32(10000), ErrorThreshold = cms.int32(1), Level = cms.int32(1), Depth = cms.int32(3), # -1 means check whatever depth PVname = cms.string(''), LVname = cms.string(''), NodeNames = cms.vstring('World') ), G4Commands = cms.vstring(), SteppingVerbosity = cms.untracked.int32(0), StepVerboseThreshold = cms.untracked.double(0.1), # in GeV VerboseEvents = cms.untracked.vint32(), VertexNumber = cms.untracked.vint32(), VerboseTracks = cms.untracked.vint32(), FileNameField = cms.untracked.string(''), FileNameGDML = cms.untracked.string(''), FileNameRegions = cms.untracked.string(''), Watchers = cms.VPSet(), HepMCProductLabel = cms.InputTag("generatorSmeared"), theLHCTlinkTag = cms.InputTag("LHCTransport"), CustomUIsession = cms.untracked.PSet( Type = cms.untracked.string("MessageLogger"), # alternatives: MessageLoggerThreadPrefix, FilePerThread ThreadPrefix = cms.untracked.string("W"), # for MessageLoggerThreadPrefix ThreadFile = cms.untracked.string("sim_output_thread"), # for FilePerThread ), MagneticField = cms.PSet( UseLocalMagFieldManager = cms.bool(False), Verbosity = cms.bool(False), ConfGlobalMFM = cms.PSet( Volume = cms.string('OCMS'), OCMS = cms.PSet( Stepper = cms.string('G4DormandPrince745'), Type = cms.string('CMSIMField'), StepperParam = cms.PSet( VacRegions = cms.vstring(), # VacRegions = cms.vstring('DefaultRegionForTheWorld','BeamPipeVacuum','BeamPipeOutside'), MaximumEpsilonStep = cms.untracked.double(0.01), ## in mm DeltaOneStep = cms.double(0.001), ## in mm MaximumLoopCounts = cms.untracked.double(1000.0), DeltaChord = cms.double(0.001), ## in mm MinStep = cms.double(0.1), ## in mm DeltaIntersectionAndOneStep = cms.untracked.double(-1.0), DeltaIntersection = cms.double(0.0001),## in mm MaxStep = cms.double(150.), ## in cm MinimumEpsilonStep = cms.untracked.double(1e-05), ## in mm EnergyThSimple = cms.double(0.015), ## in GeV DeltaChordSimple = cms.double(0.1), ## in mm DeltaOneStepSimple = cms.double(0.1), ## in mm DeltaIntersectionSimple = cms.double(0.01), ## in mm MaxStepSimple = cms.double(50.), ## in cm ) ) ), delta = cms.double(1.0) ), Physics = cms.PSet( common_maximum_time, # NOTE : if you want EM Physics only, # please select "SimG4Core/Physics/DummyPhysics" for type # and turn ON DummyEMPhysics # type = cms.string('SimG4Core/Physics/FTFP_BERT_EMM'), DummyEMPhysics = cms.bool(False), CutsPerRegion = cms.bool(True), CutsOnProton = cms.bool(True), DefaultCutValue = cms.double(1.0), ## cuts in cm G4BremsstrahlungThreshold = cms.double(0.5), ## cut in GeV Verbosity = cms.untracked.int32(0), # 1 will print cuts as they get set from DD # 2 will do as 1 + will dump Geant4 table of cuts MonopoleCharge = cms.untracked.int32(1), MonopoleDeltaRay = cms.untracked.bool(True), MonopoleMultiScatter = cms.untracked.bool(False), MonopoleTransport = cms.untracked.bool(True), MonopoleMass = cms.untracked.double(0), ExoticaTransport = cms.untracked.bool(False), ExoticaPhysicsSS = cms.untracked.bool(False), RhadronPhysics = cms.bool(False), DarkMPFactor = cms.double(1.0), Region = cms.string(''), TrackingCut = cms.bool(False), SRType = cms.bool(True), FlagMuNucl = cms.bool(False), FlagFluo = cms.bool(False), EMPhysics = cms.untracked.bool(True), HadPhysics = cms.untracked.bool(True), FlagBERT = cms.untracked.bool(False), EminFTFP = cms.double(3.), # in GeV EmaxBERT = cms.double(6.), # in GeV EminQGSP = cms.double(12.), # in GeV EmaxFTFP = cms.double(30.), # in GeV EmaxBERTpi = cms.double(12.), # in GeV LowEnergyGflashEcal = cms.bool(False), LowEnergyGflashEcalEmax = cms.double(100), GflashEcal = cms.bool(False), GflashHcal = cms.bool(False), GflashEcalHad = cms.bool(False), GflashHcalHad = cms.bool(False), bField = cms.double(3.8), energyScaleEB = cms.double(1.032), energyScaleEE = cms.double(1.024), ThermalNeutrons = cms.untracked.bool(False), RusRoElectronEnergyLimit = cms.double(0.0), RusRoEcalElectron = cms.double(1.0), RusRoHcalElectron = cms.double(1.0), RusRoMuonIronElectron = cms.double(1.0), RusRoPreShowerElectron = cms.double(1.0), RusRoCastorElectron = cms.double(1.0), RusRoWorldElectron = cms.double(1.0), ElectronStepLimit = cms.bool(False), ElectronRangeTest = cms.bool(False), PositronStepLimit = cms.bool(False), ProtonRegionLimit = cms.bool(False), PionRegionLimit = cms.bool(False), LimitsPerRegion = cms.vstring('EcalRegion','HcalRegion'), EnergyLimitsE = cms.vdouble(0.,0.0), EnergyLimitsH = cms.vdouble(0.,0.0), EnergyFactorsE = cms.vdouble(1.,0.0), EnergyRMSE = cms.vdouble(0.0,0.0), MinStepLimit = cms.double(1.0), ModifyTransportation = cms.bool(False), ThresholdWarningEnergy = cms.untracked.double(100.0), ThresholdImportantEnergy = cms.untracked.double(250.0), ThresholdTrials = cms.untracked.int32(10) ), Generator = cms.PSet( HectorEtaCut, HepMCProductLabel = cms.InputTag('generatorSmeared'), ApplyPCuts = cms.bool(True), ApplyPtransCut = cms.bool(False), MinPCut = cms.double(0.04), ## the cut is in GeV MaxPCut = cms.double(99999.0), ## the pmax=99.TeV ApplyEtaCuts = cms.bool(True), MinEtaCut = cms.double(-5.5), MaxEtaCut = cms.double(5.5), RDecLenCut = cms.double(2.9), ## (cm) the cut on vertex radius LDecLenCut = cms.double(30.0), ## (cm) decay volume length ApplyPhiCuts = cms.bool(False), MinPhiCut = cms.double(-3.14159265359), ## (radians) MaxPhiCut = cms.double(3.14159265359), ## according to CMS conventions ApplyLumiMonitorCuts = cms.bool(False), ## primary for lumi monitors Verbosity = cms.untracked.int32(0), PDGselection = cms.PSet( PDGfilterSel = cms.bool(False), ## filter out unwanted particles PDGfilter = cms.vint32(21,1,2,3,4,5,6) ## list of unwanted particles (gluons and quarks) ) ), RunAction = cms.PSet( StopFile = cms.string('') ), EventAction = cms.PSet( debug = cms.untracked.bool(False), StopFile = cms.string(''), PrintRandomSeed = cms.bool(False), CollapsePrimaryVertices = cms.bool(False) ), StackingAction = cms.PSet( common_heavy_suppression, common_maximum_time, KillDeltaRay = cms.bool(False), TrackNeutrino = cms.bool(False), KillHeavy = cms.bool(False), KillGamma = cms.bool(True), GammaThreshold = cms.double(0.0001), ## (MeV) SaveFirstLevelSecondary = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInTracker = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInCalo = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInMuon = cms.untracked.bool(False), SaveAllPrimaryDecayProductsAndConversions = cms.untracked.bool(True), RusRoGammaEnergyLimit = cms.double(5.0), ## (MeV) RusRoEcalGamma = cms.double(0.3), RusRoHcalGamma = cms.double(0.3), RusRoMuonIronGamma = cms.double(0.3), RusRoPreShowerGamma = cms.double(0.3), RusRoCastorGamma = cms.double(0.3), RusRoWorldGamma = cms.double(0.3), RusRoNeutronEnergyLimit = cms.double(10.0), ## (MeV) RusRoEcalNeutron = cms.double(0.1), RusRoHcalNeutron = cms.double(0.1), RusRoMuonIronNeutron = cms.double(0.1), RusRoPreShowerNeutron = cms.double(0.1), RusRoCastorNeutron = cms.double(0.1), RusRoWorldNeutron = cms.double(0.1), RusRoProtonEnergyLimit = cms.double(0.0), RusRoEcalProton = cms.double(1.0), RusRoHcalProton = cms.double(1.0), RusRoMuonIronProton = cms.double(1.0), RusRoPreShowerProton = cms.double(1.0), RusRoCastorProton = cms.double(1.0), RusRoWorldProton = cms.double(1.0) ), TrackingAction = cms.PSet( DetailedTiming = cms.untracked.bool(False), CheckTrack = cms.untracked.bool(False) ), SteppingAction = cms.PSet( common_maximum_time, EkinNames = cms.vstring(), EkinThresholds = cms.vdouble(), EkinParticles = cms.vstring() ), TrackerSD = cms.PSet( ZeroEnergyLoss = cms.bool(False), PrintHits = cms.bool(False), ElectronicSigmaInNanoSeconds = cms.double(12.06), NeverAccumulate = cms.bool(False), EnergyThresholdForPersistencyInGeV = cms.double(0.2), EnergyThresholdForHistoryInGeV = cms.double(0.05) ), MuonSD = cms.PSet( EnergyThresholdForPersistency = cms.double(1.0), PrintHits = cms.bool(False), AllMuonsPersistent = cms.bool(True) ), CaloSD = cms.PSet( common_heavy_suppression, SuppressHeavy = cms.bool(False), EminTrack = cms.double(1.0), TmaxHit = cms.double(1000.0), HCNames = cms.vstring('EcalHitsEB','EcalHitsEE','EcalHitsES','HcalHits','ZDCHITS'), EminHits = cms.vdouble(0.015,0.010,0.0,0.0,0.0), EminHitsDepth = cms.vdouble(0.0,0.0,0.0,0.0,0.0), TmaxHits = cms.vdouble(500.0,500.0,500.0,500.0,2000.0), UseResponseTables = cms.vint32(0,0,0,0,0), BeamPosition = cms.double(0.0), CorrectTOFBeam = cms.bool(False), UseFineCaloID = cms.bool(False), DetailedTiming = cms.untracked.bool(False), UseMap = cms.untracked.bool(False), Verbosity = cms.untracked.int32(0), CheckHits = cms.untracked.int32(25) ), CaloResponse = cms.PSet( UseResponseTable = cms.bool(True), ResponseScale = cms.double(1.0), ResponseFile = cms.FileInPath('SimG4CMS/Calo/data/responsTBpim50.dat') ), ECalSD = cms.PSet( common_UseLuminosity, UseBirkLaw = cms.bool(True), BirkL3Parametrization = cms.bool(True), BirkSlope = cms.double(0.253694), BirkCut = cms.double(0.1), BirkC1 = cms.double(0.03333), BirkC3 = cms.double(1.0), BirkC2 = cms.double(0.0), SlopeLightYield = cms.double(0.02), StoreSecondary = cms.bool(False), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), XtalMat = cms.untracked.string('E_PbWO4'), TestBeam = cms.untracked.bool(False), NullNumbering = cms.untracked.bool(False), StoreRadLength = cms.untracked.bool(False), ScaleRadLength = cms.untracked.double(1.0), StoreLayerTimeSim = cms.untracked.bool(False), AgeingWithSlopeLY = cms.untracked.bool(False) ), HCalSD = cms.PSet( common_UseLuminosity, UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0060), UseShowerLibrary = cms.bool(True), UseParametrize = cms.bool(False), UsePMTHits = cms.bool(False), UseFibreBundleHits = cms.bool(False), TestNumberingScheme = cms.bool(False), doNeutralDensityFilter = cms.bool(False), EminHitHB = cms.double(0.0), EminHitHE = cms.double(0.0), EminHitHO = cms.double(0.0), EminHitHF = cms.double(0.0), BetaThreshold = cms.double(0.7), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), HBDarkening = cms.bool(False), HEDarkening = cms.bool(False), HFDarkening = cms.bool(False), UseHF = cms.untracked.bool(True), ForTBH2 = cms.untracked.bool(False), ForTBHCAL = cms.untracked.bool(False), UseLayerWt = cms.untracked.bool(False), WtFile = cms.untracked.string('None'), TestNS = cms.untracked.bool(False), HFDarkeningParameterBlock = HFDarkeningParameterBlock ), CaloTrkProcessing = cms.PSet( TestBeam = cms.bool(False), EminTrack = cms.double(0.01), PutHistory = cms.bool(False), DoFineCalo = cms.bool(False), EminFineTrack = cms.double(10000.0), EminFinePhoton = cms.double(5000.0) ), HFShower = cms.PSet( common_UsePMT, common_UseHF, ProbMax = cms.double(1.0), CFibre = cms.double(0.5), PEPerGeV = cms.double(0.31), TrackEM = cms.bool(False), UseShowerLibrary = cms.bool(True), UseHFGflash = cms.bool(False), EminLibrary = cms.double(0.0), OnlyLong = cms.bool(True), LambdaMean = cms.double(350.0), ApplyFiducialCut = cms.bool(True), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5), ParametrizeLast = cms.untracked.bool(False) ), HFShowerLibrary = cms.PSet( FileName = cms.FileInPath('SimG4CMS/Calo/data/HFShowerLibrary_oldpmt_noatt_eta4_16en_v3.root'), BackProbability = cms.double(0.2), TreeEMID = cms.string('emParticles'), TreeHadID = cms.string('hadParticles'), Verbosity = cms.untracked.bool(False), ApplyFiducialCut= cms.bool(True), BranchPost = cms.untracked.string(''), BranchEvt = cms.untracked.string(''), BranchPre = cms.untracked.string('') ), HFShowerPMT = cms.PSet( common_UsePMT, common_UseHF, PEPerGeVPMT = cms.double(1.0), RefIndex = cms.double(1.52), Aperture = cms.double(0.99), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFShowerStraightBundle = cms.PSet( common_UsePMT, common_UseHF, FactorBundle = cms.double(1.0), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFShowerConicalBundle = cms.PSet( common_UsePMT, common_UseHF, FactorBundle = cms.double(1.0), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFGflash = cms.PSet( BField = cms.untracked.double(3.8), WatcherOn = cms.untracked.bool(True), FillHisto = cms.untracked.bool(True) ), CastorSD = cms.PSet( useShowerLibrary = cms.bool(True), minEnergyInGeVforUsingSLibrary = cms.double(1.0), nonCompensationFactor = cms.double(0.817), Verbosity = cms.untracked.int32(0) ), CastorShowerLibrary = cms.PSet( FileName = cms.FileInPath('SimG4CMS/Forward/data/CastorShowerLibrary_CMSSW500_Standard.root'), BranchEvt = cms.untracked.string('hadShowerLibInfo.'), BranchEM = cms.untracked.string('emParticles.'), BranchHAD = cms.untracked.string('hadParticles.'), Verbosity = cms.untracked.bool(False) ), BHMSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), MtdSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.01), #stepping = 10 ps (for timing) IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), CheckID = cms.untracked.bool(True), ), HGCSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.001), #stepping = 1 ps (for timing) IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), RejectMouseBite = cms.bool(False), RotatedWafer = cms.bool(False), CornerMinMask = cms.int32(0), WaferAngles = cms.untracked.vdouble(90.0,30.0), WaferSize = cms.untracked.double(123.7), MouseBite = cms.untracked.double(2.5), CheckID = cms.untracked.bool(True), ), HGCScintSD = cms.PSet( Verbosity = cms.untracked.int32(0), EminHit = cms.double(0.0), UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0052), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), ), HFNoseSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.001), #stepping = 1 ps (for timing) IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), RejectMouseBite = cms.bool(False), RotatedWafer = cms.bool(False), CornerMinMask = cms.int32(0), WaferAngles = cms.untracked.vdouble(90.0,30.0), CheckID = cms.untracked.bool(True), ), TotemRPSD = cms.PSet( Verbosity = cms.int32(0) ), TotemSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), TotemT2ScintSD = cms.PSet( UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.006), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), ), PPSDiamondSD = cms.PSet( Verbosity = cms.int32(0) ), PPSPixelSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), ZdcSD = cms.PSet( Verbosity = cms.int32(0), UseShowerLibrary = cms.bool(True), UseShowerHits = cms.bool(False), FiberDirection = cms.double(45.0), ZdcHitEnergyCut = cms.double(10.0) ), ZdcShowerLibrary = cms.PSet( Verbosity = cms.untracked.int32(0) ), FP420SD = cms.PSet( Verbosity = cms.untracked.int32(2) ), BscSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), PltSD = cms.PSet( EnergyThresholdForPersistencyInGeV = cms.double(0.2), EnergyThresholdForHistoryInGeV = cms.double(0.05) ), Bcm1fSD = cms.PSet( EnergyThresholdForPersistencyInGeV = cms.double(0.010), EnergyThresholdForHistoryInGeV = cms.double(0.005) ), HcalTB02SD = cms.PSet( UseBirkLaw = cms.untracked.bool(False), BirkC1 = cms.untracked.double(0.013), BirkC3 = cms.untracked.double(1.75), BirkC2 = cms.untracked.double(0.0568) ), EcalTBH4BeamSD = cms.PSet( UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568) ), HGCalTestBeamSD = cms.PSet( Material = cms.string('Scintillator'), UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568), ), HcalTB06BeamSD = cms.PSet( UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568) ), AHCalSD = cms.PSet( UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0052), EminHit = cms.double(0.0), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), ), ) ## ## Change the HFShowerLibrary file used for Run 2 ## from Configuration.Eras.Modifier_run2_common_cff import run2_common run2_common.toModify( g4SimHits.HFShowerLibrary, FileName = 'SimG4CMS/Calo/data/HFShowerLibrary_npmt_noatt_eta4_16en_v4.root' ) run2_common.toModify( g4SimHits.HFShower, ProbMax = 0.5) from Configuration.Eras.Modifier_run2_HCAL_2017_cff import run2_HCAL_2017 run2_HCAL_2017.toModify( g4SimHits, HCalSD = dict( TestNumberingScheme = True ) ) from Configuration.Eras.Modifier_phase2_timing_cff import phase2_timing phase2_timing.toModify( g4SimHits.ECalSD, StoreLayerTimeSim = cms.untracked.bool(True), TimeSliceUnit = cms.double(0.001) ) from Configuration.ProcessModifiers.dd4hep_cff import dd4hep dd4hep.toModify( g4SimHits, g4GeometryDD4hepSource = True )

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import FWCore.ParameterSet.Config as cms from SimG4Core.Application.hectorParameter_cfi import * f import * 0), ProtonThreshold = cms.double(30.0), IonThreshold = cms.double(30.0) ) common_maximum_time = cms.PSet( MaxTrackTime = cms.double(500.0), MaxTimeNames = cms.vstring('ZDCRegion'), MaxTrackTimes = cms.vdouble(2000.0), DeadRegions = cms.vstring('QuadRegion','InterimRegion'), CriticalEnergyForVacuum = cms.double(2.0), CriticalDensity = cms.double(1e-15) ) common_UsePMT = cms.PSet( UseR7600UPMT = cms.bool(False) ) common_UseHF = cms.PSet( Lambda1 = cms.double(280.0), Lambda2 = cms.double(700.0), Gain = cms.double(0.33), CheckSurvive = cms.bool(False), FibreR = cms.untracked.double(0.3) ) common_UseLuminosity = cms.PSet( InstLuminosity = cms.double(0.), DelivLuminosity = cms.double(5000.) ) g4SimHits = cms.EDProducer("OscarMTProducer", g4GeometryDD4hepSource = cms.bool(False), NonBeamEvent = cms.bool(False), G4EventManagerVerbosity = cms.untracked.int32(0), UseMagneticField = cms.bool(True), StoreRndmSeeds = cms.bool(False), RestoreRndmSeeds = cms.bool(False), PhysicsTablesDirectory = cms.untracked.string('PhysicsTables'), StorePhysicsTables = cms.untracked.bool(False), RestorePhysicsTables = cms.untracked.bool(False), UseParametrisedEMPhysics = cms.untracked.bool(True), CheckGeometry = cms.untracked.bool(False), G4CheckOverlap = cms.untracked.PSet( OutputBaseName = cms.string('2017'), MaterialFlag = cms.bool(True), GeomFlag = cms.bool(True), OverlapFlag = cms.bool(False), RegionFlag = cms.bool(True), gdmlFlag = cms.bool(False), Verbose = cms.bool(True), Tolerance = cms.double(0.0), Resolution = cms.int32(10000), ErrorThreshold = cms.int32(1), Level = cms.int32(1), Depth = cms.int32(3), PVname = cms.string(''), LVname = cms.string(''), NodeNames = cms.vstring('World') ), G4Commands = cms.vstring(), SteppingVerbosity = cms.untracked.int32(0), StepVerboseThreshold = cms.untracked.double(0.1), VerboseEvents = cms.untracked.vint32(), VertexNumber = cms.untracked.vint32(), VerboseTracks = cms.untracked.vint32(), FileNameField = cms.untracked.string(''), FileNameGDML = cms.untracked.string(''), FileNameRegions = cms.untracked.string(''), Watchers = cms.VPSet(), HepMCProductLabel = cms.InputTag("generatorSmeared"), theLHCTlinkTag = cms.InputTag("LHCTransport"), CustomUIsession = cms.untracked.PSet( Type = cms.untracked.string("MessageLogger"), ThreadPrefix = cms.untracked.string("W"), ThreadFile = cms.untracked.string("sim_output_thread"), ), MagneticField = cms.PSet( UseLocalMagFieldManager = cms.bool(False), Verbosity = cms.bool(False), ConfGlobalMFM = cms.PSet( Volume = cms.string('OCMS'), OCMS = cms.PSet( Stepper = cms.string('G4DormandPrince745'), Type = cms.string('CMSIMField'), StepperParam = cms.PSet( VacRegions = cms.vstring(), MaximumEpsilonStep = cms.untracked.double(0.01), DeltaOneStep = cms.double(0.001), MaximumLoopCounts = cms.untracked.double(1000.0), DeltaChord = cms.double(0.001), MinStep = cms.double(0.1), DeltaIntersectionAndOneStep = cms.untracked.double(-1.0), DeltaIntersection = cms.double(0.0001), MaxStep = cms.double(150.), MinimumEpsilonStep = cms.untracked.double(1e-05), EnergyThSimple = cms.double(0.015), DeltaChordSimple = cms.double(0.1), DeltaOneStepSimple = cms.double(0.1), DeltaIntersectionSimple = cms.double(0.01), MaxStepSimple = cms.double(50.), ) ) ), delta = cms.double(1.0) ), Physics = cms.PSet( common_maximum_time, type = cms.string('SimG4Core/Physics/FTFP_BERT_EMM'), DummyEMPhysics = cms.bool(False), CutsPerRegion = cms.bool(True), CutsOnProton = cms.bool(True), DefaultCutValue = cms.double(1.0), remsstrahlungThreshold = cms.double(0.5), bosity = cms.untracked.int32(0), MonopoleCharge = cms.untracked.int32(1), MonopoleDeltaRay = cms.untracked.bool(True), MonopoleMultiScatter = cms.untracked.bool(False), MonopoleTransport = cms.untracked.bool(True), MonopoleMass = cms.untracked.double(0), ExoticaTransport = cms.untracked.bool(False), ExoticaPhysicsSS = cms.untracked.bool(False), RhadronPhysics = cms.bool(False), DarkMPFactor = cms.double(1.0), Region = cms.string(''), TrackingCut = cms.bool(False), SRType = cms.bool(True), FlagMuNucl = cms.bool(False), FlagFluo = cms.bool(False), EMPhysics = cms.untracked.bool(True), HadPhysics = cms.untracked.bool(True), FlagBERT = cms.untracked.bool(False), EminFTFP = cms.double(3.), EmaxBERT = cms.double(6.), EminQGSP = cms.double(12.), EmaxFTFP = cms.double(30.), EmaxBERTpi = cms.double(12.), LowEnergyGflashEcal = cms.bool(False), LowEnergyGflashEcalEmax = cms.double(100), GflashEcal = cms.bool(False), GflashHcal = cms.bool(False), GflashEcalHad = cms.bool(False), GflashHcalHad = cms.bool(False), bField = cms.double(3.8), energyScaleEB = cms.double(1.032), energyScaleEE = cms.double(1.024), ThermalNeutrons = cms.untracked.bool(False), RusRoElectronEnergyLimit = cms.double(0.0), RusRoEcalElectron = cms.double(1.0), RusRoHcalElectron = cms.double(1.0), RusRoMuonIronElectron = cms.double(1.0), RusRoPreShowerElectron = cms.double(1.0), RusRoCastorElectron = cms.double(1.0), RusRoWorldElectron = cms.double(1.0), ElectronStepLimit = cms.bool(False), ElectronRangeTest = cms.bool(False), PositronStepLimit = cms.bool(False), ProtonRegionLimit = cms.bool(False), PionRegionLimit = cms.bool(False), LimitsPerRegion = cms.vstring('EcalRegion','HcalRegion'), EnergyLimitsE = cms.vdouble(0.,0.0), EnergyLimitsH = cms.vdouble(0.,0.0), EnergyFactorsE = cms.vdouble(1.,0.0), EnergyRMSE = cms.vdouble(0.0,0.0), MinStepLimit = cms.double(1.0), ModifyTransportation = cms.bool(False), ThresholdWarningEnergy = cms.untracked.double(100.0), ThresholdImportantEnergy = cms.untracked.double(250.0), ThresholdTrials = cms.untracked.int32(10) ), Generator = cms.PSet( HectorEtaCut, HepMCProductLabel = cms.InputTag('generatorSmeared'), ApplyPCuts = cms.bool(True), ApplyPtransCut = cms.bool(False), MinPCut = cms.double(0.04), ms.double(99999.0), uts = cms.bool(True), MinEtaCut = cms.double(-5.5), MaxEtaCut = cms.double(5.5), RDecLenCut = cms.double(2.9), e(30.0), s.bool(False), MinPhiCut = cms.double(-3.14159265359), xPhiCut = cms.double(3.14159265359), = cms.bool(False), tracked.int32(0), PDGselection = cms.PSet( PDGfilterSel = cms.bool(False), nt32(21,1,2,3,4,5,6) StopFile = cms.string('') ), EventAction = cms.PSet( debug = cms.untracked.bool(False), StopFile = cms.string(''), PrintRandomSeed = cms.bool(False), CollapsePrimaryVertices = cms.bool(False) ), StackingAction = cms.PSet( common_heavy_suppression, common_maximum_time, KillDeltaRay = cms.bool(False), TrackNeutrino = cms.bool(False), KillHeavy = cms.bool(False), KillGamma = cms.bool(True), GammaThreshold = cms.double(0.0001), SaveFirstLevelSecondary = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInTracker = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInCalo = cms.untracked.bool(False), SavePrimaryDecayProductsAndConversionsInMuon = cms.untracked.bool(False), SaveAllPrimaryDecayProductsAndConversions = cms.untracked.bool(True), RusRoGammaEnergyLimit = cms.double(5.0), RusRoEcalGamma = cms.double(0.3), RusRoHcalGamma = cms.double(0.3), RusRoMuonIronGamma = cms.double(0.3), RusRoPreShowerGamma = cms.double(0.3), RusRoCastorGamma = cms.double(0.3), RusRoWorldGamma = cms.double(0.3), RusRoNeutronEnergyLimit = cms.double(10.0), RusRoEcalNeutron = cms.double(0.1), RusRoHcalNeutron = cms.double(0.1), RusRoMuonIronNeutron = cms.double(0.1), RusRoPreShowerNeutron = cms.double(0.1), RusRoCastorNeutron = cms.double(0.1), RusRoWorldNeutron = cms.double(0.1), RusRoProtonEnergyLimit = cms.double(0.0), RusRoEcalProton = cms.double(1.0), RusRoHcalProton = cms.double(1.0), RusRoMuonIronProton = cms.double(1.0), RusRoPreShowerProton = cms.double(1.0), RusRoCastorProton = cms.double(1.0), RusRoWorldProton = cms.double(1.0) ), TrackingAction = cms.PSet( DetailedTiming = cms.untracked.bool(False), CheckTrack = cms.untracked.bool(False) ), SteppingAction = cms.PSet( common_maximum_time, EkinNames = cms.vstring(), EkinThresholds = cms.vdouble(), EkinParticles = cms.vstring() ), TrackerSD = cms.PSet( ZeroEnergyLoss = cms.bool(False), PrintHits = cms.bool(False), ElectronicSigmaInNanoSeconds = cms.double(12.06), NeverAccumulate = cms.bool(False), EnergyThresholdForPersistencyInGeV = cms.double(0.2), EnergyThresholdForHistoryInGeV = cms.double(0.05) ), MuonSD = cms.PSet( EnergyThresholdForPersistency = cms.double(1.0), PrintHits = cms.bool(False), AllMuonsPersistent = cms.bool(True) ), CaloSD = cms.PSet( common_heavy_suppression, SuppressHeavy = cms.bool(False), EminTrack = cms.double(1.0), TmaxHit = cms.double(1000.0), HCNames = cms.vstring('EcalHitsEB','EcalHitsEE','EcalHitsES','HcalHits','ZDCHITS'), EminHits = cms.vdouble(0.015,0.010,0.0,0.0,0.0), EminHitsDepth = cms.vdouble(0.0,0.0,0.0,0.0,0.0), TmaxHits = cms.vdouble(500.0,500.0,500.0,500.0,2000.0), UseResponseTables = cms.vint32(0,0,0,0,0), BeamPosition = cms.double(0.0), CorrectTOFBeam = cms.bool(False), UseFineCaloID = cms.bool(False), DetailedTiming = cms.untracked.bool(False), UseMap = cms.untracked.bool(False), Verbosity = cms.untracked.int32(0), CheckHits = cms.untracked.int32(25) ), CaloResponse = cms.PSet( UseResponseTable = cms.bool(True), ResponseScale = cms.double(1.0), ResponseFile = cms.FileInPath('SimG4CMS/Calo/data/responsTBpim50.dat') ), ECalSD = cms.PSet( common_UseLuminosity, UseBirkLaw = cms.bool(True), BirkL3Parametrization = cms.bool(True), BirkSlope = cms.double(0.253694), BirkCut = cms.double(0.1), BirkC1 = cms.double(0.03333), BirkC3 = cms.double(1.0), BirkC2 = cms.double(0.0), SlopeLightYield = cms.double(0.02), StoreSecondary = cms.bool(False), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), XtalMat = cms.untracked.string('E_PbWO4'), TestBeam = cms.untracked.bool(False), NullNumbering = cms.untracked.bool(False), StoreRadLength = cms.untracked.bool(False), ScaleRadLength = cms.untracked.double(1.0), StoreLayerTimeSim = cms.untracked.bool(False), AgeingWithSlopeLY = cms.untracked.bool(False) ), HCalSD = cms.PSet( common_UseLuminosity, UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0060), UseShowerLibrary = cms.bool(True), UseParametrize = cms.bool(False), UsePMTHits = cms.bool(False), UseFibreBundleHits = cms.bool(False), TestNumberingScheme = cms.bool(False), doNeutralDensityFilter = cms.bool(False), EminHitHB = cms.double(0.0), EminHitHE = cms.double(0.0), EminHitHO = cms.double(0.0), EminHitHF = cms.double(0.0), BetaThreshold = cms.double(0.7), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), HBDarkening = cms.bool(False), HEDarkening = cms.bool(False), HFDarkening = cms.bool(False), UseHF = cms.untracked.bool(True), ForTBH2 = cms.untracked.bool(False), ForTBHCAL = cms.untracked.bool(False), UseLayerWt = cms.untracked.bool(False), WtFile = cms.untracked.string('None'), TestNS = cms.untracked.bool(False), HFDarkeningParameterBlock = HFDarkeningParameterBlock ), CaloTrkProcessing = cms.PSet( TestBeam = cms.bool(False), EminTrack = cms.double(0.01), PutHistory = cms.bool(False), DoFineCalo = cms.bool(False), EminFineTrack = cms.double(10000.0), EminFinePhoton = cms.double(5000.0) ), HFShower = cms.PSet( common_UsePMT, common_UseHF, ProbMax = cms.double(1.0), CFibre = cms.double(0.5), PEPerGeV = cms.double(0.31), TrackEM = cms.bool(False), UseShowerLibrary = cms.bool(True), UseHFGflash = cms.bool(False), EminLibrary = cms.double(0.0), OnlyLong = cms.bool(True), LambdaMean = cms.double(350.0), ApplyFiducialCut = cms.bool(True), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5), ParametrizeLast = cms.untracked.bool(False) ), HFShowerLibrary = cms.PSet( FileName = cms.FileInPath('SimG4CMS/Calo/data/HFShowerLibrary_oldpmt_noatt_eta4_16en_v3.root'), BackProbability = cms.double(0.2), TreeEMID = cms.string('emParticles'), TreeHadID = cms.string('hadParticles'), Verbosity = cms.untracked.bool(False), ApplyFiducialCut= cms.bool(True), BranchPost = cms.untracked.string(''), BranchEvt = cms.untracked.string(''), BranchPre = cms.untracked.string('') ), HFShowerPMT = cms.PSet( common_UsePMT, common_UseHF, PEPerGeVPMT = cms.double(1.0), RefIndex = cms.double(1.52), Aperture = cms.double(0.99), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFShowerStraightBundle = cms.PSet( common_UsePMT, common_UseHF, FactorBundle = cms.double(1.0), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFShowerConicalBundle = cms.PSet( common_UsePMT, common_UseHF, FactorBundle = cms.double(1.0), RefIndex = cms.double(1.459), Aperture = cms.double(0.33), ApertureTrapped = cms.double(0.22), CosApertureTrapped= cms.double(0.5), SinPsiMax = cms.untracked.double(0.5) ), HFGflash = cms.PSet( BField = cms.untracked.double(3.8), WatcherOn = cms.untracked.bool(True), FillHisto = cms.untracked.bool(True) ), CastorSD = cms.PSet( useShowerLibrary = cms.bool(True), minEnergyInGeVforUsingSLibrary = cms.double(1.0), nonCompensationFactor = cms.double(0.817), Verbosity = cms.untracked.int32(0) ), CastorShowerLibrary = cms.PSet( FileName = cms.FileInPath('SimG4CMS/Forward/data/CastorShowerLibrary_CMSSW500_Standard.root'), BranchEvt = cms.untracked.string('hadShowerLibInfo.'), BranchEM = cms.untracked.string('emParticles.'), BranchHAD = cms.untracked.string('hadParticles.'), Verbosity = cms.untracked.bool(False) ), BHMSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), MtdSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.01), IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), CheckID = cms.untracked.bool(True), ), HGCSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.001), IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), RejectMouseBite = cms.bool(False), RotatedWafer = cms.bool(False), CornerMinMask = cms.int32(0), WaferAngles = cms.untracked.vdouble(90.0,30.0), WaferSize = cms.untracked.double(123.7), MouseBite = cms.untracked.double(2.5), CheckID = cms.untracked.bool(True), ), HGCScintSD = cms.PSet( Verbosity = cms.untracked.int32(0), EminHit = cms.double(0.0), UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0052), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), ), HFNoseSD = cms.PSet( Verbosity = cms.untracked.int32(0), TimeSliceUnit = cms.double(0.001), IgnoreTrackID = cms.bool(False), EminHit = cms.double(0.0), FiducialCut = cms.bool(False), DistanceFromEdge = cms.double(1.0), StoreAllG4Hits = cms.bool(False), RejectMouseBite = cms.bool(False), RotatedWafer = cms.bool(False), CornerMinMask = cms.int32(0), WaferAngles = cms.untracked.vdouble(90.0,30.0), CheckID = cms.untracked.bool(True), ), TotemRPSD = cms.PSet( Verbosity = cms.int32(0) ), TotemSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), TotemT2ScintSD = cms.PSet( UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.006), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), ), PPSDiamondSD = cms.PSet( Verbosity = cms.int32(0) ), PPSPixelSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), ZdcSD = cms.PSet( Verbosity = cms.int32(0), UseShowerLibrary = cms.bool(True), UseShowerHits = cms.bool(False), FiberDirection = cms.double(45.0), ZdcHitEnergyCut = cms.double(10.0) ), ZdcShowerLibrary = cms.PSet( Verbosity = cms.untracked.int32(0) ), FP420SD = cms.PSet( Verbosity = cms.untracked.int32(2) ), BscSD = cms.PSet( Verbosity = cms.untracked.int32(0) ), PltSD = cms.PSet( EnergyThresholdForPersistencyInGeV = cms.double(0.2), EnergyThresholdForHistoryInGeV = cms.double(0.05) ), Bcm1fSD = cms.PSet( EnergyThresholdForPersistencyInGeV = cms.double(0.010), EnergyThresholdForHistoryInGeV = cms.double(0.005) ), HcalTB02SD = cms.PSet( UseBirkLaw = cms.untracked.bool(False), BirkC1 = cms.untracked.double(0.013), BirkC3 = cms.untracked.double(1.75), BirkC2 = cms.untracked.double(0.0568) ), EcalTBH4BeamSD = cms.PSet( UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568) ), HGCalTestBeamSD = cms.PSet( Material = cms.string('Scintillator'), UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568), ), HcalTB06BeamSD = cms.PSet( UseBirkLaw = cms.bool(False), BirkC1 = cms.double(0.013), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.0568) ), AHCalSD = cms.PSet( UseBirkLaw = cms.bool(True), BirkC3 = cms.double(1.75), BirkC2 = cms.double(0.142), BirkC1 = cms.double(0.0052), EminHit = cms.double(0.0), TimeSliceUnit = cms.double(1), IgnoreTrackID = cms.bool(False), ), ) f import run2_common run2_common.toModify( g4SimHits.HFShowerLibrary, FileName = 'SimG4CMS/Calo/data/HFShowerLibrary_npmt_noatt_eta4_16en_v4.root' ) run2_common.toModify( g4SimHits.HFShower, ProbMax = 0.5) from Configuration.Eras.Modifier_run2_HCAL_2017_cff import run2_HCAL_2017 run2_HCAL_2017.toModify( g4SimHits, HCalSD = dict( TestNumberingScheme = True ) ) from Configuration.Eras.Modifier_phase2_timing_cff import phase2_timing phase2_timing.toModify( g4SimHits.ECalSD, StoreLayerTimeSim = cms.untracked.bool(True), TimeSliceUnit = cms.double(0.001) ) from Configuration.ProcessModifiers.dd4hep_cff import dd4hep dd4hep.toModify( g4SimHits, g4GeometryDD4hepSource = True )

true

f7390fff6ac1b29779d480d4cd31cc41351d32f0

4,304

py

Python

webcam_animal_classifier.py

MaximeSorgenfrei/cat_dog_cnn

bc1301fb683de2111db2c25b9da22608ede8e070

[ "MIT" ]

null

webcam_animal_classifier.py

MaximeSorgenfrei/cat_dog_cnn

bc1301fb683de2111db2c25b9da22608ede8e070

[ "MIT" ]

null

webcam_animal_classifier.py

MaximeSorgenfrei/cat_dog_cnn

bc1301fb683de2111db2c25b9da22608ede8e070

[ "MIT" ]

null

import cv2 import keras from keras.models import Sequential, Model from keras.callbacks import EarlyStopping from keras.optimizers import Adam import json import matplotlib.pyplot as plt import numpy as np import os import pandas as pd from random import shuffle # import tensorflow as tf import time file_list = os.listdir("./") keras_model_files = [] for file in file_list: if file.split(".")[-1] in ["h5","npy"]: print(file) keras_model_files.append(file) # load model from file keras_model_file_i_want_to_use = keras_model_files[0] model = keras.models.load_model(keras_model_file_i_want_to_use) model.summary() # classes = ["ape", "bear", "bee", "beetle", "bird", "bos", "canine", "deer", "elephants", "feline", "frogs", "gekko", "golden moles", "hare", "human", "lemur", "loris", "none", "rodent", "salamander", "scorpions", "shark", "sheep", "snake", "spider", "squirrel", "turtle", "whale"] # read directories, resize and label data # Write some Text # dict with open(keras_model_files[1],"r") as f: class_list = json.load(f) class_stats = pd.DataFrame(data={"classes":class_list}) classes = class_stats["classes"].to_dict() f.close() print("Classes: {}".format(classes)) print("Using following model file for predictions:\n{}".format(keras_model_file_i_want_to_use)) font = cv2.FONT_HERSHEY_COMPLEX bottomLeftCornerOfText = (50,50) bottomLeftCornerOfText2 = (50,75) fontScale = 0.5 fontColor = (255,255,255) lineType = 2 width, height = 50, 50 cap_width = 1280 cap_height = 720 roi_width = 400 roi_height = 300 WebCam_cap = cv2.VideoCapture(0) WebCam_cap.set(cv2.CAP_PROP_FRAME_WIDTH, cap_width) WebCam_cap.set(cv2.CAP_PROP_FRAME_HEIGHT, cap_height) SETTING_PHOTOFRAME = True while True: # get frame ret, frame = WebCam_cap.read() # print(type(frame), frame.shape) try: # reduce frame to 50x50 pixles # image = cv2.imread(frame, cv2.IMREAD_GRAYSCALE) if SETTING_PHOTOFRAME: roi = np.ones_like(frame) roi[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] = frame[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] image = frame[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] # print("image shape: ",image.shape) else: image = frame # resize, turn to gray and reshape for CNN image = cv2.resize(image, (height, width), interpolation=cv2.INTER_AREA) image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) image_to_predict = np.reshape(image, (1, height, width, 1)) # predict with NN pred = model.predict_classes(image_to_predict, verbose=0) pred_ = model.predict(image_to_predict, verbose=0) prediction = "{}: {} | {}: {}".format(classes[0], pred_[0][0], classes[1], pred_[0][1]) if pred_[0][pred[0]] > 0.30: prediction_class = "Predicted class: {} [{:.2f}]".format(classes[pred[0]], pred_[0][pred[0]]) else: prediction_class = "No significant prediction possible!" # print prediction and class to frame # cv2.putText(frame, prediction, bottomLeftCornerOfText, font, fontScale, fontColor, lineType) if SETTING_PHOTOFRAME: cv2.putText(roi, prediction_class, bottomLeftCornerOfText2, font, fontScale, fontColor, lineType) else: cv2.putText(frame, prediction_class, bottomLeftCornerOfText2, font, fontScale, fontColor, lineType) # ax[i].set_title("{}: {}-{} ({})".format(i, pred, classes[pred[0]], np.round(pred_, decimals=4))) # display resut # cv2.namedWindow("Result", cv2.WINDOW_AUTOSIZE) # cv2.imshow("Result", image) except Exception as e: print(e) else: cv2.namedWindow("WebCam", cv2.WINDOW_AUTOSIZE) if SETTING_PHOTOFRAME: cv2.imshow("WebCam", roi) else: cv2.imshow("WebCam", frame) if cv2.waitKey(1) & 0xFF==ord("q"): break WebCam_cap.release() cv2.destroyAllWindows()

39.486239

282

0.655901

import cv2 import keras from keras.models import Sequential, Model from keras.callbacks import EarlyStopping from keras.optimizers import Adam import json import matplotlib.pyplot as plt import numpy as np import os import pandas as pd from random import shuffle import time file_list = os.listdir("./") keras_model_files = [] for file in file_list: if file.split(".")[-1] in ["h5","npy"]: print(file) keras_model_files.append(file) keras_model_file_i_want_to_use = keras_model_files[0] model = keras.models.load_model(keras_model_file_i_want_to_use) model.summary() with open(keras_model_files[1],"r") as f: class_list = json.load(f) class_stats = pd.DataFrame(data={"classes":class_list}) classes = class_stats["classes"].to_dict() f.close() print("Classes: {}".format(classes)) print("Using following model file for predictions:\n{}".format(keras_model_file_i_want_to_use)) font = cv2.FONT_HERSHEY_COMPLEX bottomLeftCornerOfText = (50,50) bottomLeftCornerOfText2 = (50,75) fontScale = 0.5 fontColor = (255,255,255) lineType = 2 width, height = 50, 50 cap_width = 1280 cap_height = 720 roi_width = 400 roi_height = 300 WebCam_cap = cv2.VideoCapture(0) WebCam_cap.set(cv2.CAP_PROP_FRAME_WIDTH, cap_width) WebCam_cap.set(cv2.CAP_PROP_FRAME_HEIGHT, cap_height) SETTING_PHOTOFRAME = True while True: ret, frame = WebCam_cap.read() try: if SETTING_PHOTOFRAME: roi = np.ones_like(frame) roi[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] = frame[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] image = frame[int((cap_height-roi_height)/2):-int((cap_height-roi_height)/2), int((cap_width-roi_width)/2):-int((cap_width-roi_width)/2), :] else: image = frame image = cv2.resize(image, (height, width), interpolation=cv2.INTER_AREA) image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) image_to_predict = np.reshape(image, (1, height, width, 1)) pred = model.predict_classes(image_to_predict, verbose=0) pred_ = model.predict(image_to_predict, verbose=0) prediction = "{}: {} | {}: {}".format(classes[0], pred_[0][0], classes[1], pred_[0][1]) if pred_[0][pred[0]] > 0.30: prediction_class = "Predicted class: {} [{:.2f}]".format(classes[pred[0]], pred_[0][pred[0]]) else: prediction_class = "No significant prediction possible!" if SETTING_PHOTOFRAME: cv2.putText(roi, prediction_class, bottomLeftCornerOfText2, font, fontScale, fontColor, lineType) else: cv2.putText(frame, prediction_class, bottomLeftCornerOfText2, font, fontScale, fontColor, lineType) except Exception as e: print(e) else: cv2.namedWindow("WebCam", cv2.WINDOW_AUTOSIZE) if SETTING_PHOTOFRAME: cv2.imshow("WebCam", roi) else: cv2.imshow("WebCam", frame) if cv2.waitKey(1) & 0xFF==ord("q"): break WebCam_cap.release() cv2.destroyAllWindows()

true

f73910657fede1ff95dd3e376594d155dc4a8249

1,324

py

Python

computer_vision/learning-opencv-practical/image-process-100ask/Question_41_50/answers/answer_48.py

magic428/subjects_notes

6930adbb3f445c11ca9d024abb12a53d6aca19e7

[ "MIT" ]

2

2020-03-18T17:13:00.000Z

2020-03-25T02:34:03.000Z

computer_vision/learning-opencv-practical/image-process-100ask/Question_41_50/answers/answer_48.py

magic428/subjects_notes

6930adbb3f445c11ca9d024abb12a53d6aca19e7

[ "MIT" ]

null

computer_vision/learning-opencv-practical/image-process-100ask/Question_41_50/answers/answer_48.py

magic428/subjects_notes

6930adbb3f445c11ca9d024abb12a53d6aca19e7

[ "MIT" ]

null

import cv2 import numpy as np import matplotlib.pyplot as plt # Read image img = cv2.imread("imori.jpg").astype(np.float32) H, W, C = img.shape # Otsu binary ## Grayscale out = 0.2126 * img[..., 2] + 0.7152 * img[..., 1] + 0.0722 * img[..., 0] out = out.astype(np.uint8) ## Determine threshold of Otsu's binarization max_sigma = 0 max_t = 0 for _t in range(1, 255): v0 = out[np.where(out < _t)] m0 = np.mean(v0) if len(v0) > 0 else 0. w0 = len(v0) / (H * W) v1 = out[np.where(out >= _t)] m1 = np.mean(v1) if len(v1) > 0 else 0. w1 = len(v1) / (H * W) sigma = w0 * w1 * ((m0 - m1) ** 2) if sigma > max_sigma: max_sigma = sigma max_t = _t ## Binarization #print("threshold >>", max_t) th = max_t out[out < th] = 0 out[out >= th] = 255 # Morphology filter MF = np.array(((0, 1, 0), (1, 0, 1), (0, 1, 0)), dtype=np.int) # Morphology - erode Erode_time = 2 for i in range(Erode_time): tmp = np.pad(out, (1, 1), 'edge') for y in range(1, H+1): for x in range(1, W+1): if np.sum(MF * tmp[y-1:y+2, x-1:x+2]) < 255*4: out[y-1, x-1] = 0 # Save result cv2.imwrite("out.jpg", out) cv2.imshow("result", out) cv2.waitKey(0) cv2.destroyAllWindows()

22.827586

73

0.52568

import cv2 import numpy as np import matplotlib.pyplot as plt img = cv2.imread("imori.jpg").astype(np.float32) H, W, C = img.shape 6 * img[..., 2] + 0.7152 * img[..., 1] + 0.0722 * img[..., 0] out = out.astype(np.uint8) 1, 255): v0 = out[np.where(out < _t)] m0 = np.mean(v0) if len(v0) > 0 else 0. w0 = len(v0) / (H * W) v1 = out[np.where(out >= _t)] m1 = np.mean(v1) if len(v1) > 0 else 0. w1 = len(v1) / (H * W) sigma = w0 * w1 * ((m0 - m1) ** 2) if sigma > max_sigma: max_sigma = sigma max_t = _t ## Binarization #print("threshold >>", max_t) th = max_t out[out < th] = 0 out[out >= th] = 255 # Morphology filter MF = np.array(((0, 1, 0), (1, 0, 1), (0, 1, 0)), dtype=np.int) # Morphology - erode Erode_time = 2 for i in range(Erode_time): tmp = np.pad(out, (1, 1), 'edge') for y in range(1, H+1): for x in range(1, W+1): if np.sum(MF * tmp[y-1:y+2, x-1:x+2]) < 255*4: out[y-1, x-1] = 0 # Save result cv2.imwrite("out.jpg", out) cv2.imshow("result", out) cv2.waitKey(0) cv2.destroyAllWindows()

true

f73910f59d21f2145a1c358627a1f69dca0b5486

86,942

py

Python

google/ads/google_ads/v4/proto/resources/campaign_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

1

2021-04-09T04:28:47.000Z

google/ads/google_ads/v4/proto/resources/campaign_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

null

google/ads/google_ads/v4/proto/resources/campaign_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: google/ads/googleads_v4/proto/resources/campaign.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from google.ads.google_ads.v4.proto.common import bidding_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2 from google.ads.google_ads.v4.proto.common import custom_parameter_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2 from google.ads.google_ads.v4.proto.common import frequency_cap_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2 from google.ads.google_ads.v4.proto.common import real_time_bidding_setting_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2 from google.ads.google_ads.v4.proto.common import targeting_setting_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2 from google.ads.google_ads.v4.proto.enums import ad_serving_optimization_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2 from google.ads.google_ads.v4.proto.enums import advertising_channel_sub_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2 from google.ads.google_ads.v4.proto.enums import advertising_channel_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2 from google.ads.google_ads.v4.proto.enums import app_campaign_app_store_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2 from google.ads.google_ads.v4.proto.enums import app_campaign_bidding_strategy_goal_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2 from google.ads.google_ads.v4.proto.enums import bidding_strategy_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2 from google.ads.google_ads.v4.proto.enums import brand_safety_suitability_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2 from google.ads.google_ads.v4.proto.enums import campaign_experiment_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2 from google.ads.google_ads.v4.proto.enums import campaign_serving_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2 from google.ads.google_ads.v4.proto.enums import campaign_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2 from google.ads.google_ads.v4.proto.enums import location_source_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2 from google.ads.google_ads.v4.proto.enums import negative_geo_target_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2 from google.ads.google_ads.v4.proto.enums import optimization_goal_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2 from google.ads.google_ads.v4.proto.enums import payment_mode_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2 from google.ads.google_ads.v4.proto.enums import positive_geo_target_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2 from google.ads.google_ads.v4.proto.enums import vanity_pharma_display_url_mode_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2 from google.ads.google_ads.v4.proto.enums import vanity_pharma_text_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2 from google.api import field_behavior_pb2 as google_dot_api_dot_field__behavior__pb2 from google.api import resource_pb2 as google_dot_api_dot_resource__pb2 from google.protobuf import wrappers_pb2 as google_dot_protobuf_dot_wrappers__pb2 from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='google/ads/googleads_v4/proto/resources/campaign.proto', package='google.ads.googleads.v4.resources', syntax='proto3', serialized_options=_b('\n%com.google.ads.googleads.v4.resourcesB\rCampaignProtoP\001ZJgoogle.golang.org/genproto/googleapis/ads/googleads/v4/resources;resources\242\002\003GAA\252\002!Google.Ads.GoogleAds.V4.Resources\312\002!Google\\Ads\\GoogleAds\\V4\\Resources\352\002%Google::Ads::GoogleAds::V4::Resources'), serialized_pb=_b('\n6google/ads/googleads_v4/proto/resources/campaign.proto\x12!google.ads.googleads.v4.resources\x1a\x32google/ads/googleads_v4/proto/common/bidding.proto\x1a;google/ads/googleads_v4/proto/common/custom_parameter.proto\x1a\x38google/ads/googleads_v4/proto/common/frequency_cap.proto\x1a\x44google/ads/googleads_v4/proto/common/real_time_bidding_setting.proto\x1a<google/ads/googleads_v4/proto/common/targeting_setting.proto\x1aHgoogle/ads/googleads_v4/proto/enums/ad_serving_optimization_status.proto\x1a\x46google/ads/googleads_v4/proto/enums/advertising_channel_sub_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/advertising_channel_type.proto\x1a@google/ads/googleads_v4/proto/enums/app_campaign_app_store.proto\x1aQgoogle/ads/googleads_v4/proto/enums/app_campaign_bidding_strategy_goal_type.proto\x1a?google/ads/googleads_v4/proto/enums/bidding_strategy_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/brand_safety_suitability.proto\x1a\x42google/ads/googleads_v4/proto/enums/campaign_experiment_type.proto\x1a\x41google/ads/googleads_v4/proto/enums/campaign_serving_status.proto\x1a\x39google/ads/googleads_v4/proto/enums/campaign_status.proto\x1a>google/ads/googleads_v4/proto/enums/location_source_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/negative_geo_target_type.proto\x1a@google/ads/googleads_v4/proto/enums/optimization_goal_type.proto\x1a\x36google/ads/googleads_v4/proto/enums/payment_mode.proto\x1a\x42google/ads/googleads_v4/proto/enums/positive_geo_target_type.proto\x1aHgoogle/ads/googleads_v4/proto/enums/vanity_pharma_display_url_mode.proto\x1a<google/ads/googleads_v4/proto/enums/vanity_pharma_text.proto\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/resource.proto\x1a\x1egoogle/protobuf/wrappers.proto\x1a\x1cgoogle/api/annotations.proto\"\xc2\x31\n\x08\x43\x61mpaign\x12@\n\rresource_name\x18\x01 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dependencies=[google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2.DESCRIPTOR,google_dot_api_dot_field__behavior__pb2.DESCRIPTOR,google_dot_api_dot_resource__pb2.DESCRIPTOR,google_dot_protobuf_dot_wrappers__pb2.DESCRIPTOR,google_dot_api_dot_annotations__pb2.DESCRIPTOR,]) _CAMPAIGN_NETWORKSETTINGS = _descriptor.Descriptor( name='NetworkSettings', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='target_google_search', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_google_search', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_search_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_search_network', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_content_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_content_network', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_partner_search_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_partner_search_network', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=5747, serialized_end=6008, ) _CAMPAIGN_HOTELSETTINGINFO = _descriptor.Descriptor( name='HotelSettingInfo', full_name='google.ads.googleads.v4.resources.Campaign.HotelSettingInfo', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='hotel_center_id', full_name='google.ads.googleads.v4.resources.Campaign.HotelSettingInfo.hotel_center_id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6010, serialized_end=6087, ) _CAMPAIGN_LOCALCAMPAIGNSETTING = _descriptor.Descriptor( name='LocalCampaignSetting', full_name='google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='location_source_type', full_name='google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting.location_source_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6089, serialized_end=6215, ) _CAMPAIGN_APPCAMPAIGNSETTING = _descriptor.Descriptor( name='AppCampaignSetting', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='bidding_strategy_goal_type', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.bidding_strategy_goal_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_id', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.app_id', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_store', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.app_store', index=2, number=3, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6218, serialized_end=6532, ) _CAMPAIGN_DYNAMICSEARCHADSSETTING = _descriptor.Descriptor( name='DynamicSearchAdsSetting', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='domain_name', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.domain_name', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language_code', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.language_code', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='use_supplied_urls_only', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.use_supplied_urls_only', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='feeds', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.feeds', index=3, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A\037\n\035googleads.googleapis.com/Feed'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6535, serialized_end=6808, ) _CAMPAIGN_SELECTIVEOPTIMIZATION = _descriptor.Descriptor( name='SelectiveOptimization', full_name='google.ads.googleads.v4.resources.Campaign.SelectiveOptimization', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='conversion_actions', full_name='google.ads.googleads.v4.resources.Campaign.SelectiveOptimization.conversion_actions', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A+\n)googleads.googleapis.com/ConversionAction'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6811, serialized_end=6940, ) _CAMPAIGN_SHOPPINGSETTING = _descriptor.Descriptor( name='ShoppingSetting', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='merchant_id', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.merchant_id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='sales_country', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.sales_country', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='campaign_priority', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.campaign_priority', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='enable_local', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.enable_local', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6943, serialized_end=7179, ) _CAMPAIGN_TRACKINGSETTING = _descriptor.Descriptor( name='TrackingSetting', full_name='google.ads.googleads.v4.resources.Campaign.TrackingSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='tracking_url', full_name='google.ads.googleads.v4.resources.Campaign.TrackingSetting.tracking_url', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7181, serialized_end=7255, ) _CAMPAIGN_GEOTARGETTYPESETTING = _descriptor.Descriptor( name='GeoTargetTypeSetting', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='positive_geo_target_type', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting.positive_geo_target_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='negative_geo_target_type', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting.negative_geo_target_type', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7258, serialized_end=7508, ) _CAMPAIGN_OPTIMIZATIONGOALSETTING = _descriptor.Descriptor( name='OptimizationGoalSetting', full_name='google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='optimization_goal_types', full_name='google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting.optimization_goal_types', index=0, number=1, type=14, cpp_type=8, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7511, serialized_end=7647, ) _CAMPAIGN_VANITYPHARMA = _descriptor.Descriptor( name='VanityPharma', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='vanity_pharma_display_url_mode', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma.vanity_pharma_display_url_mode', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vanity_pharma_text', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma.vanity_pharma_text', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7650, serialized_end=7893, ) _CAMPAIGN = _descriptor.Descriptor( name='Campaign', full_name='google.ads.googleads.v4.resources.Campaign', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='resource_name', full_name='google.ads.googleads.v4.resources.Campaign.resource_name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005\372A#\n!googleads.googleapis.com/Campaign'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='id', full_name='google.ads.googleads.v4.resources.Campaign.id', index=1, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.ads.googleads.v4.resources.Campaign.name', index=2, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.ads.googleads.v4.resources.Campaign.status', index=3, number=5, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='serving_status', full_name='google.ads.googleads.v4.resources.Campaign.serving_status', index=4, number=21, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ad_serving_optimization_status', full_name='google.ads.googleads.v4.resources.Campaign.ad_serving_optimization_status', index=5, number=8, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='advertising_channel_type', full_name='google.ads.googleads.v4.resources.Campaign.advertising_channel_type', index=6, number=9, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='advertising_channel_sub_type', full_name='google.ads.googleads.v4.resources.Campaign.advertising_channel_sub_type', index=7, number=10, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='tracking_url_template', full_name='google.ads.googleads.v4.resources.Campaign.tracking_url_template', index=8, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='url_custom_parameters', full_name='google.ads.googleads.v4.resources.Campaign.url_custom_parameters', index=9, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='real_time_bidding_setting', full_name='google.ads.googleads.v4.resources.Campaign.real_time_bidding_setting', index=10, number=39, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='network_settings', full_name='google.ads.googleads.v4.resources.Campaign.network_settings', index=11, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='hotel_setting', full_name='google.ads.googleads.v4.resources.Campaign.hotel_setting', index=12, number=32, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dynamic_search_ads_setting', full_name='google.ads.googleads.v4.resources.Campaign.dynamic_search_ads_setting', index=13, number=33, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='shopping_setting', full_name='google.ads.googleads.v4.resources.Campaign.shopping_setting', index=14, number=36, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='targeting_setting', full_name='google.ads.googleads.v4.resources.Campaign.targeting_setting', index=15, number=43, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='geo_target_type_setting', full_name='google.ads.googleads.v4.resources.Campaign.geo_target_type_setting', index=16, number=47, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='local_campaign_setting', full_name='google.ads.googleads.v4.resources.Campaign.local_campaign_setting', index=17, number=50, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_campaign_setting', full_name='google.ads.googleads.v4.resources.Campaign.app_campaign_setting', index=18, number=51, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='labels', full_name='google.ads.googleads.v4.resources.Campaign.labels', index=19, number=53, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A(\n&googleads.googleapis.com/CampaignLabel'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='experiment_type', full_name='google.ads.googleads.v4.resources.Campaign.experiment_type', index=20, number=17, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='base_campaign', full_name='google.ads.googleads.v4.resources.Campaign.base_campaign', index=21, number=28, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A#\n!googleads.googleapis.com/Campaign'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='campaign_budget', full_name='google.ads.googleads.v4.resources.Campaign.campaign_budget', index=22, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A)\n\'googleads.googleapis.com/CampaignBudget'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='bidding_strategy_type', full_name='google.ads.googleads.v4.resources.Campaign.bidding_strategy_type', index=23, number=22, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='start_date', full_name='google.ads.googleads.v4.resources.Campaign.start_date', index=24, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='end_date', full_name='google.ads.googleads.v4.resources.Campaign.end_date', index=25, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='final_url_suffix', full_name='google.ads.googleads.v4.resources.Campaign.final_url_suffix', index=26, number=38, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='frequency_caps', full_name='google.ads.googleads.v4.resources.Campaign.frequency_caps', index=27, number=40, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='video_brand_safety_suitability', full_name='google.ads.googleads.v4.resources.Campaign.video_brand_safety_suitability', index=28, number=42, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vanity_pharma', full_name='google.ads.googleads.v4.resources.Campaign.vanity_pharma', index=29, number=44, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='selective_optimization', full_name='google.ads.googleads.v4.resources.Campaign.selective_optimization', index=30, number=45, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='optimization_goal_setting', full_name='google.ads.googleads.v4.resources.Campaign.optimization_goal_setting', index=31, number=54, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='tracking_setting', full_name='google.ads.googleads.v4.resources.Campaign.tracking_setting', index=32, number=46, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='payment_mode', full_name='google.ads.googleads.v4.resources.Campaign.payment_mode', index=33, number=52, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='optimization_score', full_name='google.ads.googleads.v4.resources.Campaign.optimization_score', index=34, number=55, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='bidding_strategy', full_name='google.ads.googleads.v4.resources.Campaign.bidding_strategy', index=35, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A*\n(googleads.googleapis.com/BiddingStrategy'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='commission', full_name='google.ads.googleads.v4.resources.Campaign.commission', index=36, number=49, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpc', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpc', index=37, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpm', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpm', index=38, number=25, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpv', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpv', index=39, number=37, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='maximize_conversions', full_name='google.ads.googleads.v4.resources.Campaign.maximize_conversions', index=40, number=30, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='maximize_conversion_value', full_name='google.ads.googleads.v4.resources.Campaign.maximize_conversion_value', index=41, number=31, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_cpa', full_name='google.ads.googleads.v4.resources.Campaign.target_cpa', index=42, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_impression_share', full_name='google.ads.googleads.v4.resources.Campaign.target_impression_share', index=43, number=48, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_roas', full_name='google.ads.googleads.v4.resources.Campaign.target_roas', index=44, number=29, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_spend', full_name='google.ads.googleads.v4.resources.Campaign.target_spend', index=45, number=27, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='percent_cpc', full_name='google.ads.googleads.v4.resources.Campaign.percent_cpc', index=46, number=34, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_cpm', full_name='google.ads.googleads.v4.resources.Campaign.target_cpm', index=47, number=41, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_CAMPAIGN_NETWORKSETTINGS, _CAMPAIGN_HOTELSETTINGINFO, _CAMPAIGN_LOCALCAMPAIGNSETTING, _CAMPAIGN_APPCAMPAIGNSETTING, _CAMPAIGN_DYNAMICSEARCHADSSETTING, _CAMPAIGN_SELECTIVEOPTIMIZATION, _CAMPAIGN_SHOPPINGSETTING, _CAMPAIGN_TRACKINGSETTING, _CAMPAIGN_GEOTARGETTYPESETTING, _CAMPAIGN_OPTIMIZATIONGOALSETTING, _CAMPAIGN_VANITYPHARMA, ], enum_types=[ ], serialized_options=_b('\352AN\n!googleads.googleapis.com/Campaign\022)customers/{customer}/campaigns/{campaign}'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='campaign_bidding_strategy', full_name='google.ads.googleads.v4.resources.Campaign.campaign_bidding_strategy', index=0, containing_type=None, fields=[]), ], serialized_start=1667, serialized_end=8005, ) _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_google_search'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_search_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_content_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_partner_search_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.containing_type = _CAMPAIGN _CAMPAIGN_HOTELSETTINGINFO.fields_by_name['hotel_center_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN_HOTELSETTINGINFO.containing_type = _CAMPAIGN _CAMPAIGN_LOCALCAMPAIGNSETTING.fields_by_name['location_source_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2._LOCATIONSOURCETYPEENUM_LOCATIONSOURCETYPE _CAMPAIGN_LOCALCAMPAIGNSETTING.containing_type = _CAMPAIGN _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['bidding_strategy_goal_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2._APPCAMPAIGNBIDDINGSTRATEGYGOALTYPEENUM_APPCAMPAIGNBIDDINGSTRATEGYGOALTYPE _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_store'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2._APPCAMPAIGNAPPSTOREENUM_APPCAMPAIGNAPPSTORE _CAMPAIGN_APPCAMPAIGNSETTING.containing_type = _CAMPAIGN _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['domain_name'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['language_code'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['use_supplied_urls_only'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['feeds'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.containing_type = _CAMPAIGN _CAMPAIGN_SELECTIVEOPTIMIZATION.fields_by_name['conversion_actions'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_SELECTIVEOPTIMIZATION.containing_type = _CAMPAIGN _CAMPAIGN_SHOPPINGSETTING.fields_by_name['merchant_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['sales_country'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['campaign_priority'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT32VALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['enable_local'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_SHOPPINGSETTING.containing_type = _CAMPAIGN _CAMPAIGN_TRACKINGSETTING.fields_by_name['tracking_url'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_TRACKINGSETTING.containing_type = _CAMPAIGN _CAMPAIGN_GEOTARGETTYPESETTING.fields_by_name['positive_geo_target_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2._POSITIVEGEOTARGETTYPEENUM_POSITIVEGEOTARGETTYPE _CAMPAIGN_GEOTARGETTYPESETTING.fields_by_name['negative_geo_target_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2._NEGATIVEGEOTARGETTYPEENUM_NEGATIVEGEOTARGETTYPE _CAMPAIGN_GEOTARGETTYPESETTING.containing_type = _CAMPAIGN _CAMPAIGN_OPTIMIZATIONGOALSETTING.fields_by_name['optimization_goal_types'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2._OPTIMIZATIONGOALTYPEENUM_OPTIMIZATIONGOALTYPE _CAMPAIGN_OPTIMIZATIONGOALSETTING.containing_type = _CAMPAIGN _CAMPAIGN_VANITYPHARMA.fields_by_name['vanity_pharma_display_url_mode'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2._VANITYPHARMADISPLAYURLMODEENUM_VANITYPHARMADISPLAYURLMODE _CAMPAIGN_VANITYPHARMA.fields_by_name['vanity_pharma_text'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2._VANITYPHARMATEXTENUM_VANITYPHARMATEXT _CAMPAIGN_VANITYPHARMA.containing_type = _CAMPAIGN _CAMPAIGN.fields_by_name['id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN.fields_by_name['name'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2._CAMPAIGNSTATUSENUM_CAMPAIGNSTATUS _CAMPAIGN.fields_by_name['serving_status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2._CAMPAIGNSERVINGSTATUSENUM_CAMPAIGNSERVINGSTATUS _CAMPAIGN.fields_by_name['ad_serving_optimization_status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2._ADSERVINGOPTIMIZATIONSTATUSENUM_ADSERVINGOPTIMIZATIONSTATUS _CAMPAIGN.fields_by_name['advertising_channel_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2._ADVERTISINGCHANNELTYPEENUM_ADVERTISINGCHANNELTYPE _CAMPAIGN.fields_by_name['advertising_channel_sub_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2._ADVERTISINGCHANNELSUBTYPEENUM_ADVERTISINGCHANNELSUBTYPE _CAMPAIGN.fields_by_name['tracking_url_template'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['url_custom_parameters'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2._CUSTOMPARAMETER _CAMPAIGN.fields_by_name['real_time_bidding_setting'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2._REALTIMEBIDDINGSETTING _CAMPAIGN.fields_by_name['network_settings'].message_type = _CAMPAIGN_NETWORKSETTINGS _CAMPAIGN.fields_by_name['hotel_setting'].message_type = _CAMPAIGN_HOTELSETTINGINFO _CAMPAIGN.fields_by_name['dynamic_search_ads_setting'].message_type = _CAMPAIGN_DYNAMICSEARCHADSSETTING _CAMPAIGN.fields_by_name['shopping_setting'].message_type = _CAMPAIGN_SHOPPINGSETTING _CAMPAIGN.fields_by_name['targeting_setting'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2._TARGETINGSETTING _CAMPAIGN.fields_by_name['geo_target_type_setting'].message_type = _CAMPAIGN_GEOTARGETTYPESETTING _CAMPAIGN.fields_by_name['local_campaign_setting'].message_type = _CAMPAIGN_LOCALCAMPAIGNSETTING _CAMPAIGN.fields_by_name['app_campaign_setting'].message_type = _CAMPAIGN_APPCAMPAIGNSETTING _CAMPAIGN.fields_by_name['labels'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['experiment_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2._CAMPAIGNEXPERIMENTTYPEENUM_CAMPAIGNEXPERIMENTTYPE _CAMPAIGN.fields_by_name['base_campaign'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['campaign_budget'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['bidding_strategy_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2._BIDDINGSTRATEGYTYPEENUM_BIDDINGSTRATEGYTYPE _CAMPAIGN.fields_by_name['start_date'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['end_date'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['final_url_suffix'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['frequency_caps'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2._FREQUENCYCAPENTRY _CAMPAIGN.fields_by_name['video_brand_safety_suitability'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2._BRANDSAFETYSUITABILITYENUM_BRANDSAFETYSUITABILITY _CAMPAIGN.fields_by_name['vanity_pharma'].message_type = _CAMPAIGN_VANITYPHARMA _CAMPAIGN.fields_by_name['selective_optimization'].message_type = _CAMPAIGN_SELECTIVEOPTIMIZATION _CAMPAIGN.fields_by_name['optimization_goal_setting'].message_type = _CAMPAIGN_OPTIMIZATIONGOALSETTING _CAMPAIGN.fields_by_name['tracking_setting'].message_type = _CAMPAIGN_TRACKINGSETTING _CAMPAIGN.fields_by_name['payment_mode'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2._PAYMENTMODEENUM_PAYMENTMODE _CAMPAIGN.fields_by_name['optimization_score'].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE _CAMPAIGN.fields_by_name['bidding_strategy'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['commission'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._COMMISSION _CAMPAIGN.fields_by_name['manual_cpc'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPC _CAMPAIGN.fields_by_name['manual_cpm'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPM _CAMPAIGN.fields_by_name['manual_cpv'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPV _CAMPAIGN.fields_by_name['maximize_conversions'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MAXIMIZECONVERSIONS _CAMPAIGN.fields_by_name['maximize_conversion_value'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MAXIMIZECONVERSIONVALUE _CAMPAIGN.fields_by_name['target_cpa'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETCPA _CAMPAIGN.fields_by_name['target_impression_share'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETIMPRESSIONSHARE _CAMPAIGN.fields_by_name['target_roas'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETROAS _CAMPAIGN.fields_by_name['target_spend'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETSPEND _CAMPAIGN.fields_by_name['percent_cpc'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._PERCENTCPC _CAMPAIGN.fields_by_name['target_cpm'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETCPM _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['bidding_strategy']) _CAMPAIGN.fields_by_name['bidding_strategy'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['commission']) _CAMPAIGN.fields_by_name['commission'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpc']) _CAMPAIGN.fields_by_name['manual_cpc'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpm']) _CAMPAIGN.fields_by_name['manual_cpm'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpv']) _CAMPAIGN.fields_by_name['manual_cpv'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['maximize_conversions']) _CAMPAIGN.fields_by_name['maximize_conversions'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['maximize_conversion_value']) _CAMPAIGN.fields_by_name['maximize_conversion_value'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_cpa']) _CAMPAIGN.fields_by_name['target_cpa'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_impression_share']) _CAMPAIGN.fields_by_name['target_impression_share'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_roas']) _CAMPAIGN.fields_by_name['target_roas'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_spend']) _CAMPAIGN.fields_by_name['target_spend'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['percent_cpc']) _CAMPAIGN.fields_by_name['percent_cpc'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_cpm']) _CAMPAIGN.fields_by_name['target_cpm'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] DESCRIPTOR.message_types_by_name['Campaign'] = _CAMPAIGN _sym_db.RegisterFileDescriptor(DESCRIPTOR) Campaign = _reflection.GeneratedProtocolMessageType('Campaign', (_message.Message,), dict( NetworkSettings = _reflection.GeneratedProtocolMessageType('NetworkSettings', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_NETWORKSETTINGS, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The network settings for the campaign. Attributes: target_google_search: Whether ads will be served with google.com search results. target_search_network: Whether ads will be served on partner sites in the Google Search Network (requires ``target_google_search`` to also be ``true``). target_content_network: Whether ads will be served on specified placements in the Google Display Network. Placements are specified using the Placement criterion. target_partner_search_network: Whether ads will be served on the Google Partner Network. This is available only to some select Google partner accounts. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.NetworkSettings) )) , HotelSettingInfo = _reflection.GeneratedProtocolMessageType('HotelSettingInfo', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_HOTELSETTINGINFO, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for hotel ads. Attributes: hotel_center_id: Immutable. The linked Hotel Center account. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.HotelSettingInfo) )) , LocalCampaignSetting = _reflection.GeneratedProtocolMessageType('LocalCampaignSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_LOCALCAMPAIGNSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign setting for local campaigns. Attributes: location_source_type: The location source type for this local campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting) )) , AppCampaignSetting = _reflection.GeneratedProtocolMessageType('AppCampaignSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_APPCAMPAIGNSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for App Campaigns. Attributes: bidding_strategy_goal_type: Represents the goal which the bidding strategy of this app campaign should optimize towards. app_id: Immutable. A string that uniquely identifies a mobile application. app_store: Immutable. The application store that distributes this specific app. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.AppCampaignSetting) )) , DynamicSearchAdsSetting = _reflection.GeneratedProtocolMessageType('DynamicSearchAdsSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_DYNAMICSEARCHADSSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The setting for controlling Dynamic Search Ads (DSA). Attributes: domain_name: The Internet domain name that this setting represents, e.g., "google.com" or "www.google.com". language_code: The language code specifying the language of the domain, e.g., "en". use_supplied_urls_only: Whether the campaign uses advertiser supplied URLs exclusively. feeds: Output only. The list of page feeds associated with the campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting) )) , SelectiveOptimization = _reflection.GeneratedProtocolMessageType('SelectiveOptimization', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_SELECTIVEOPTIMIZATION, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Selective optimization setting for this campaign, which includes a set of conversion actions to optimize this campaign towards. Attributes: conversion_actions: The selected set of conversion actions for optimizing this campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.SelectiveOptimization) )) , ShoppingSetting = _reflection.GeneratedProtocolMessageType('ShoppingSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_SHOPPINGSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The setting for Shopping campaigns. Defines the universe of products that can be advertised by the campaign, and how this campaign interacts with other Shopping campaigns. Attributes: merchant_id: Immutable. ID of the Merchant Center account. This field is required for create operations. This field is immutable for Shopping campaigns. sales_country: Immutable. Sales country of products to include in the campaign. This field is required for Shopping campaigns. This field is immutable. This field is optional for non-Shopping campaigns, but it must be equal to 'ZZ' if set. campaign_priority: Priority of the campaign. Campaigns with numerically higher priorities take precedence over those with lower priorities. This field is required for Shopping campaigns, with values between 0 and 2, inclusive. This field is optional for Smart Shopping campaigns, but must be equal to 3 if set. enable_local: Whether to include local products. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.ShoppingSetting) )) , TrackingSetting = _reflection.GeneratedProtocolMessageType('TrackingSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_TRACKINGSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for tracking information. Attributes: tracking_url: Output only. The url used for dynamic tracking. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.TrackingSetting) )) , GeoTargetTypeSetting = _reflection.GeneratedProtocolMessageType('GeoTargetTypeSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_GEOTARGETTYPESETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Represents a collection of settings related to ads geotargeting. Attributes: positive_geo_target_type: The setting used for positive geotargeting in this particular campaign. negative_geo_target_type: The setting used for negative geotargeting in this particular campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting) )) , OptimizationGoalSetting = _reflection.GeneratedProtocolMessageType('OptimizationGoalSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_OPTIMIZATIONGOALSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Optimization goal setting for this campaign, which includes a set of optimization goal types. Attributes: optimization_goal_types: The list of optimization goal types. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting) )) , VanityPharma = _reflection.GeneratedProtocolMessageType('VanityPharma', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_VANITYPHARMA, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Describes how unbranded pharma ads will be displayed. Attributes: vanity_pharma_display_url_mode: The display mode for vanity pharma URLs. vanity_pharma_text: The text that will be displayed in display URL of the text ad when website description is the selected display mode for vanity pharma URLs. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.VanityPharma) )) , DESCRIPTOR = _CAMPAIGN, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """A campaign. Attributes: resource_name: Immutable. The resource name of the campaign. Campaign resource names have the form: ``customers/{customer_id}/campaigns/{campaign_id}`` id: Output only. The ID of the campaign. name: The name of the campaign. This field is required and should not be empty when creating new campaigns. It must not contain any null (code point 0x0), NL line feed (code point 0xA) or carriage return (code point 0xD) characters. status: The status of the campaign. When a new campaign is added, the status defaults to ENABLED. serving_status: Output only. The ad serving status of the campaign. ad_serving_optimization_status: The ad serving optimization status of the campaign. advertising_channel_type: Immutable. The primary serving target for ads within the campaign. The targeting options can be refined in ``network_settings``. This field is required and should not be empty when creating new campaigns. Can be set only when creating campaigns. After the campaign is created, the field can not be changed. advertising_channel_sub_type: Immutable. Optional refinement to ``advertising_channel_type``. Must be a valid sub-type of the parent channel type. Can be set only when creating campaigns. After campaign is created, the field can not be changed. tracking_url_template: The URL template for constructing a tracking URL. url_custom_parameters: The list of mappings used to substitute custom parameter tags in a ``tracking_url_template``, ``final_urls``, or ``mobile_final_urls``. real_time_bidding_setting: Settings for Real-Time Bidding, a feature only available for campaigns targeting the Ad Exchange network. network_settings: The network settings for the campaign. hotel_setting: Immutable. The hotel setting for the campaign. dynamic_search_ads_setting: The setting for controlling Dynamic Search Ads (DSA). shopping_setting: The setting for controlling Shopping campaigns. targeting_setting: Setting for targeting related features. geo_target_type_setting: The setting for ads geotargeting. local_campaign_setting: The setting for local campaign. app_campaign_setting: The setting related to App Campaign. labels: Output only. The resource names of labels attached to this campaign. experiment_type: Output only. The type of campaign: normal, draft, or experiment. base_campaign: Output only. The resource name of the base campaign of a draft or experiment campaign. For base campaigns, this is equal to ``resource_name``. This field is read-only. campaign_budget: The budget of the campaign. bidding_strategy_type: Output only. The type of bidding strategy. A bidding strategy can be created by setting either the bidding scheme to create a standard bidding strategy or the ``bidding_strategy`` field to create a portfolio bidding strategy. This field is read- only. start_date: The date when campaign started. This field must not be used in WHERE clauses. end_date: The date when campaign ended. This field must not be used in WHERE clauses. final_url_suffix: Suffix used to append query parameters to landing pages that are served with parallel tracking. frequency_caps: A list that limits how often each user will see this campaign's ads. video_brand_safety_suitability: Output only. 3-Tier Brand Safety setting for the campaign. vanity_pharma: Describes how unbranded pharma ads will be displayed. selective_optimization: Selective optimization setting for this campaign, which includes a set of conversion actions to optimize this campaign towards. optimization_goal_setting: Optimization goal setting for this campaign, which includes a set of optimization goal types. tracking_setting: Output only. Campaign-level settings for tracking information. payment_mode: Payment mode for the campaign. optimization_score: Output only. Optimization score of the campaign. Optimization score is an estimate of how well a campaign is set to perform. It ranges from 0% (0.0) to 100% (1.0), with 100% indicating that the campaign is performing at full potential. See "About optimization score" at https://support.google.com/google- ads/answer/9061546. This field is read-only. campaign_bidding_strategy: The bidding strategy for the campaign. Must be either portfolio (created via BiddingStrategy service) or standard, that is embedded into the campaign. bidding_strategy: Portfolio bidding strategy used by campaign. commission: Commission is an automatic bidding strategy in which the advertiser pays a certain portion of the conversion value. manual_cpc: Standard Manual CPC bidding strategy. Manual click-based bidding where user pays per click. manual_cpm: Standard Manual CPM bidding strategy. Manual impression-based bidding where user pays per thousand impressions. manual_cpv: Output only. A bidding strategy that pays a configurable amount per video view. maximize_conversions: Standard Maximize Conversions bidding strategy that automatically maximizes number of conversions given a daily budget. maximize_conversion_value: Standard Maximize Conversion Value bidding strategy that automatically sets bids to maximize revenue while spending your budget. target_cpa: Standard Target CPA bidding strategy that automatically sets bids to help get as many conversions as possible at the target cost-per-acquisition (CPA) you set. target_impression_share: Target Impression Share bidding strategy. An automated bidding strategy that sets bids to achieve a desired percentage of impressions. target_roas: Standard Target ROAS bidding strategy that automatically maximizes revenue while averaging a specific target return on ad spend (ROAS). target_spend: Standard Target Spend bidding strategy that automatically sets your bids to help get as many clicks as possible within your budget. percent_cpc: Standard Percent Cpc bidding strategy where bids are a fraction of the advertised price for some good or service. target_cpm: A bidding strategy that automatically optimizes cost per thousand impressions. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign) )) _sym_db.RegisterMessage(Campaign) _sym_db.RegisterMessage(Campaign.NetworkSettings) _sym_db.RegisterMessage(Campaign.HotelSettingInfo) _sym_db.RegisterMessage(Campaign.LocalCampaignSetting) _sym_db.RegisterMessage(Campaign.AppCampaignSetting) _sym_db.RegisterMessage(Campaign.DynamicSearchAdsSetting) _sym_db.RegisterMessage(Campaign.SelectiveOptimization) _sym_db.RegisterMessage(Campaign.ShoppingSetting) _sym_db.RegisterMessage(Campaign.TrackingSetting) _sym_db.RegisterMessage(Campaign.GeoTargetTypeSetting) _sym_db.RegisterMessage(Campaign.OptimizationGoalSetting) _sym_db.RegisterMessage(Campaign.VanityPharma) DESCRIPTOR._options = None _CAMPAIGN_HOTELSETTINGINFO.fields_by_name['hotel_center_id']._options = None _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_id']._options = None _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_store']._options = None _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['feeds']._options = None _CAMPAIGN_SELECTIVEOPTIMIZATION.fields_by_name['conversion_actions']._options = None _CAMPAIGN_SHOPPINGSETTING.fields_by_name['merchant_id']._options = None _CAMPAIGN_SHOPPINGSETTING.fields_by_name['sales_country']._options = None _CAMPAIGN_TRACKINGSETTING.fields_by_name['tracking_url']._options = None _CAMPAIGN.fields_by_name['resource_name']._options = None _CAMPAIGN.fields_by_name['id']._options = None _CAMPAIGN.fields_by_name['serving_status']._options = None _CAMPAIGN.fields_by_name['advertising_channel_type']._options = None _CAMPAIGN.fields_by_name['advertising_channel_sub_type']._options = None _CAMPAIGN.fields_by_name['hotel_setting']._options = None _CAMPAIGN.fields_by_name['labels']._options = None _CAMPAIGN.fields_by_name['experiment_type']._options = None _CAMPAIGN.fields_by_name['base_campaign']._options = None _CAMPAIGN.fields_by_name['campaign_budget']._options = None _CAMPAIGN.fields_by_name['bidding_strategy_type']._options = None _CAMPAIGN.fields_by_name['video_brand_safety_suitability']._options = None _CAMPAIGN.fields_by_name['tracking_setting']._options = None _CAMPAIGN.fields_by_name['optimization_score']._options = None _CAMPAIGN.fields_by_name['bidding_strategy']._options = None _CAMPAIGN.fields_by_name['manual_cpv']._options = None _CAMPAIGN._options = None # @@protoc_insertion_point(module_scope)

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import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database _sym_db = _symbol_database.Default() from google.ads.google_ads.v4.proto.common import bidding_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2 from google.ads.google_ads.v4.proto.common import custom_parameter_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2 from google.ads.google_ads.v4.proto.common import frequency_cap_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2 from google.ads.google_ads.v4.proto.common import real_time_bidding_setting_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2 from google.ads.google_ads.v4.proto.common import targeting_setting_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2 from google.ads.google_ads.v4.proto.enums import ad_serving_optimization_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2 from google.ads.google_ads.v4.proto.enums import advertising_channel_sub_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2 from google.ads.google_ads.v4.proto.enums import advertising_channel_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2 from google.ads.google_ads.v4.proto.enums import app_campaign_app_store_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2 from google.ads.google_ads.v4.proto.enums import app_campaign_bidding_strategy_goal_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2 from google.ads.google_ads.v4.proto.enums import bidding_strategy_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2 from google.ads.google_ads.v4.proto.enums import brand_safety_suitability_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2 from google.ads.google_ads.v4.proto.enums import campaign_experiment_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2 from google.ads.google_ads.v4.proto.enums import campaign_serving_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2 from google.ads.google_ads.v4.proto.enums import campaign_status_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2 from google.ads.google_ads.v4.proto.enums import location_source_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2 from google.ads.google_ads.v4.proto.enums import negative_geo_target_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2 from google.ads.google_ads.v4.proto.enums import optimization_goal_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2 from google.ads.google_ads.v4.proto.enums import payment_mode_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2 from google.ads.google_ads.v4.proto.enums import positive_geo_target_type_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2 from google.ads.google_ads.v4.proto.enums import vanity_pharma_display_url_mode_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2 from google.ads.google_ads.v4.proto.enums import vanity_pharma_text_pb2 as google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2 from google.api import field_behavior_pb2 as google_dot_api_dot_field__behavior__pb2 from google.api import resource_pb2 as google_dot_api_dot_resource__pb2 from google.protobuf import wrappers_pb2 as google_dot_protobuf_dot_wrappers__pb2 from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='google/ads/googleads_v4/proto/resources/campaign.proto', package='google.ads.googleads.v4.resources', syntax='proto3', serialized_options=_b('\n%com.google.ads.googleads.v4.resourcesB\rCampaignProtoP\001ZJgoogle.golang.org/genproto/googleapis/ads/googleads/v4/resources;resources\242\002\003GAA\252\002!Google.Ads.GoogleAds.V4.Resources\312\002!Google\\Ads\\GoogleAds\\V4\\Resources\352\002%Google::Ads::GoogleAds::V4::Resources'), serialized_pb=_b('\n6google/ads/googleads_v4/proto/resources/campaign.proto\x12!google.ads.googleads.v4.resources\x1a\x32google/ads/googleads_v4/proto/common/bidding.proto\x1a;google/ads/googleads_v4/proto/common/custom_parameter.proto\x1a\x38google/ads/googleads_v4/proto/common/frequency_cap.proto\x1a\x44google/ads/googleads_v4/proto/common/real_time_bidding_setting.proto\x1a<google/ads/googleads_v4/proto/common/targeting_setting.proto\x1aHgoogle/ads/googleads_v4/proto/enums/ad_serving_optimization_status.proto\x1a\x46google/ads/googleads_v4/proto/enums/advertising_channel_sub_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/advertising_channel_type.proto\x1a@google/ads/googleads_v4/proto/enums/app_campaign_app_store.proto\x1aQgoogle/ads/googleads_v4/proto/enums/app_campaign_bidding_strategy_goal_type.proto\x1a?google/ads/googleads_v4/proto/enums/bidding_strategy_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/brand_safety_suitability.proto\x1a\x42google/ads/googleads_v4/proto/enums/campaign_experiment_type.proto\x1a\x41google/ads/googleads_v4/proto/enums/campaign_serving_status.proto\x1a\x39google/ads/googleads_v4/proto/enums/campaign_status.proto\x1a>google/ads/googleads_v4/proto/enums/location_source_type.proto\x1a\x42google/ads/googleads_v4/proto/enums/negative_geo_target_type.proto\x1a@google/ads/googleads_v4/proto/enums/optimization_goal_type.proto\x1a\x36google/ads/googleads_v4/proto/enums/payment_mode.proto\x1a\x42google/ads/googleads_v4/proto/enums/positive_geo_target_type.proto\x1aHgoogle/ads/googleads_v4/proto/enums/vanity_pharma_display_url_mode.proto\x1a<google/ads/googleads_v4/proto/enums/vanity_pharma_text.proto\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/resource.proto\x1a\x1egoogle/protobuf/wrappers.proto\x1a\x1cgoogle/api/annotations.proto\"\xc2\x31\n\x08\x43\x61mpaign\x12@\n\rresource_name\x18\x01 \x01(\tB)\xe0\x41\x05\xfa\x41#\n!googleads.googleapis.com/Campaign\x12,\n\x02id\x18\x03 \x01(\x0b\x32\x1b.google.protobuf.Int64ValueB\x03\xe0\x41\x03\x12*\n\x04name\x18\x04 \x01(\x0b\x32\x1c.google.protobuf.StringValue\x12P\n\x06status\x18\x05 \x01(\x0e\x32@.google.ads.googleads.v4.enums.CampaignStatusEnum.CampaignStatus\x12k\n\x0eserving_status\x18\x15 \x01(\x0e\x32N.google.ads.googleads.v4.enums.CampaignServingStatusEnum.CampaignServingStatusB\x03\xe0\x41\x03\x12\x82\x01\n\x1e\x61\x64_serving_optimization_status\x18\x08 \x01(\x0e\x32Z.google.ads.googleads.v4.enums.AdServingOptimizationStatusEnum.AdServingOptimizationStatus\x12w\n\x18\x61\x64vertising_channel_type\x18\t \x01(\x0e\x32P.google.ads.googleads.v4.enums.AdvertisingChannelTypeEnum.AdvertisingChannelTypeB\x03\xe0\x41\x05\x12\x81\x01\n\x1c\x61\x64vertising_channel_sub_type\x18\n 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dependencies=[google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2.DESCRIPTOR,google_dot_api_dot_field__behavior__pb2.DESCRIPTOR,google_dot_api_dot_resource__pb2.DESCRIPTOR,google_dot_protobuf_dot_wrappers__pb2.DESCRIPTOR,google_dot_api_dot_annotations__pb2.DESCRIPTOR,]) _CAMPAIGN_NETWORKSETTINGS = _descriptor.Descriptor( name='NetworkSettings', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='target_google_search', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_google_search', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_search_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_search_network', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_content_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_content_network', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_partner_search_network', full_name='google.ads.googleads.v4.resources.Campaign.NetworkSettings.target_partner_search_network', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=5747, serialized_end=6008, ) _CAMPAIGN_HOTELSETTINGINFO = _descriptor.Descriptor( name='HotelSettingInfo', full_name='google.ads.googleads.v4.resources.Campaign.HotelSettingInfo', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='hotel_center_id', full_name='google.ads.googleads.v4.resources.Campaign.HotelSettingInfo.hotel_center_id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6010, serialized_end=6087, ) _CAMPAIGN_LOCALCAMPAIGNSETTING = _descriptor.Descriptor( name='LocalCampaignSetting', full_name='google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='location_source_type', full_name='google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting.location_source_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6089, serialized_end=6215, ) _CAMPAIGN_APPCAMPAIGNSETTING = _descriptor.Descriptor( name='AppCampaignSetting', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='bidding_strategy_goal_type', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.bidding_strategy_goal_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_id', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.app_id', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_store', full_name='google.ads.googleads.v4.resources.Campaign.AppCampaignSetting.app_store', index=2, number=3, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6218, serialized_end=6532, ) _CAMPAIGN_DYNAMICSEARCHADSSETTING = _descriptor.Descriptor( name='DynamicSearchAdsSetting', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='domain_name', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.domain_name', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='language_code', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.language_code', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='use_supplied_urls_only', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.use_supplied_urls_only', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='feeds', full_name='google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting.feeds', index=3, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A\037\n\035googleads.googleapis.com/Feed'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6535, serialized_end=6808, ) _CAMPAIGN_SELECTIVEOPTIMIZATION = _descriptor.Descriptor( name='SelectiveOptimization', full_name='google.ads.googleads.v4.resources.Campaign.SelectiveOptimization', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='conversion_actions', full_name='google.ads.googleads.v4.resources.Campaign.SelectiveOptimization.conversion_actions', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A+\n)googleads.googleapis.com/ConversionAction'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6811, serialized_end=6940, ) _CAMPAIGN_SHOPPINGSETTING = _descriptor.Descriptor( name='ShoppingSetting', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='merchant_id', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.merchant_id', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='sales_country', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.sales_country', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='campaign_priority', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.campaign_priority', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='enable_local', full_name='google.ads.googleads.v4.resources.Campaign.ShoppingSetting.enable_local', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=6943, serialized_end=7179, ) _CAMPAIGN_TRACKINGSETTING = _descriptor.Descriptor( name='TrackingSetting', full_name='google.ads.googleads.v4.resources.Campaign.TrackingSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='tracking_url', full_name='google.ads.googleads.v4.resources.Campaign.TrackingSetting.tracking_url', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7181, serialized_end=7255, ) _CAMPAIGN_GEOTARGETTYPESETTING = _descriptor.Descriptor( name='GeoTargetTypeSetting', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='positive_geo_target_type', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting.positive_geo_target_type', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='negative_geo_target_type', full_name='google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting.negative_geo_target_type', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7258, serialized_end=7508, ) _CAMPAIGN_OPTIMIZATIONGOALSETTING = _descriptor.Descriptor( name='OptimizationGoalSetting', full_name='google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='optimization_goal_types', full_name='google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting.optimization_goal_types', index=0, number=1, type=14, cpp_type=8, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7511, serialized_end=7647, ) _CAMPAIGN_VANITYPHARMA = _descriptor.Descriptor( name='VanityPharma', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='vanity_pharma_display_url_mode', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma.vanity_pharma_display_url_mode', index=0, number=1, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vanity_pharma_text', full_name='google.ads.googleads.v4.resources.Campaign.VanityPharma.vanity_pharma_text', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=7650, serialized_end=7893, ) _CAMPAIGN = _descriptor.Descriptor( name='Campaign', full_name='google.ads.googleads.v4.resources.Campaign', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='resource_name', full_name='google.ads.googleads.v4.resources.Campaign.resource_name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005\372A#\n!googleads.googleapis.com/Campaign'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='id', full_name='google.ads.googleads.v4.resources.Campaign.id', index=1, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='name', full_name='google.ads.googleads.v4.resources.Campaign.name', index=2, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='status', full_name='google.ads.googleads.v4.resources.Campaign.status', index=3, number=5, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='serving_status', full_name='google.ads.googleads.v4.resources.Campaign.serving_status', index=4, number=21, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='ad_serving_optimization_status', full_name='google.ads.googleads.v4.resources.Campaign.ad_serving_optimization_status', index=5, number=8, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='advertising_channel_type', full_name='google.ads.googleads.v4.resources.Campaign.advertising_channel_type', index=6, number=9, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='advertising_channel_sub_type', full_name='google.ads.googleads.v4.resources.Campaign.advertising_channel_sub_type', index=7, number=10, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='tracking_url_template', full_name='google.ads.googleads.v4.resources.Campaign.tracking_url_template', index=8, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='url_custom_parameters', full_name='google.ads.googleads.v4.resources.Campaign.url_custom_parameters', index=9, number=12, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='real_time_bidding_setting', full_name='google.ads.googleads.v4.resources.Campaign.real_time_bidding_setting', index=10, number=39, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='network_settings', full_name='google.ads.googleads.v4.resources.Campaign.network_settings', index=11, number=14, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='hotel_setting', full_name='google.ads.googleads.v4.resources.Campaign.hotel_setting', index=12, number=32, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\005'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='dynamic_search_ads_setting', full_name='google.ads.googleads.v4.resources.Campaign.dynamic_search_ads_setting', index=13, number=33, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='shopping_setting', full_name='google.ads.googleads.v4.resources.Campaign.shopping_setting', index=14, number=36, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='targeting_setting', full_name='google.ads.googleads.v4.resources.Campaign.targeting_setting', index=15, number=43, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='geo_target_type_setting', full_name='google.ads.googleads.v4.resources.Campaign.geo_target_type_setting', index=16, number=47, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='local_campaign_setting', full_name='google.ads.googleads.v4.resources.Campaign.local_campaign_setting', index=17, number=50, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='app_campaign_setting', full_name='google.ads.googleads.v4.resources.Campaign.app_campaign_setting', index=18, number=51, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='labels', full_name='google.ads.googleads.v4.resources.Campaign.labels', index=19, number=53, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A(\n&googleads.googleapis.com/CampaignLabel'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='experiment_type', full_name='google.ads.googleads.v4.resources.Campaign.experiment_type', index=20, number=17, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='base_campaign', full_name='google.ads.googleads.v4.resources.Campaign.base_campaign', index=21, number=28, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003\372A#\n!googleads.googleapis.com/Campaign'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='campaign_budget', full_name='google.ads.googleads.v4.resources.Campaign.campaign_budget', index=22, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A)\n\'googleads.googleapis.com/CampaignBudget'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='bidding_strategy_type', full_name='google.ads.googleads.v4.resources.Campaign.bidding_strategy_type', index=23, number=22, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='start_date', full_name='google.ads.googleads.v4.resources.Campaign.start_date', index=24, number=19, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='end_date', full_name='google.ads.googleads.v4.resources.Campaign.end_date', index=25, number=20, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='final_url_suffix', full_name='google.ads.googleads.v4.resources.Campaign.final_url_suffix', index=26, number=38, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='frequency_caps', full_name='google.ads.googleads.v4.resources.Campaign.frequency_caps', index=27, number=40, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='video_brand_safety_suitability', full_name='google.ads.googleads.v4.resources.Campaign.video_brand_safety_suitability', index=28, number=42, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='vanity_pharma', full_name='google.ads.googleads.v4.resources.Campaign.vanity_pharma', index=29, number=44, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='selective_optimization', full_name='google.ads.googleads.v4.resources.Campaign.selective_optimization', index=30, number=45, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='optimization_goal_setting', full_name='google.ads.googleads.v4.resources.Campaign.optimization_goal_setting', index=31, number=54, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='tracking_setting', full_name='google.ads.googleads.v4.resources.Campaign.tracking_setting', index=32, number=46, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='payment_mode', full_name='google.ads.googleads.v4.resources.Campaign.payment_mode', index=33, number=52, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='optimization_score', full_name='google.ads.googleads.v4.resources.Campaign.optimization_score', index=34, number=55, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='bidding_strategy', full_name='google.ads.googleads.v4.resources.Campaign.bidding_strategy', index=35, number=23, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\372A*\n(googleads.googleapis.com/BiddingStrategy'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='commission', full_name='google.ads.googleads.v4.resources.Campaign.commission', index=36, number=49, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpc', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpc', index=37, number=24, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpm', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpm', index=38, number=25, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='manual_cpv', full_name='google.ads.googleads.v4.resources.Campaign.manual_cpv', index=39, number=37, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=_b('\340A\003'), file=DESCRIPTOR), _descriptor.FieldDescriptor( name='maximize_conversions', full_name='google.ads.googleads.v4.resources.Campaign.maximize_conversions', index=40, number=30, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='maximize_conversion_value', full_name='google.ads.googleads.v4.resources.Campaign.maximize_conversion_value', index=41, number=31, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_cpa', full_name='google.ads.googleads.v4.resources.Campaign.target_cpa', index=42, number=26, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_impression_share', full_name='google.ads.googleads.v4.resources.Campaign.target_impression_share', index=43, number=48, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_roas', full_name='google.ads.googleads.v4.resources.Campaign.target_roas', index=44, number=29, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_spend', full_name='google.ads.googleads.v4.resources.Campaign.target_spend', index=45, number=27, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='percent_cpc', full_name='google.ads.googleads.v4.resources.Campaign.percent_cpc', index=46, number=34, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='target_cpm', full_name='google.ads.googleads.v4.resources.Campaign.target_cpm', index=47, number=41, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_CAMPAIGN_NETWORKSETTINGS, _CAMPAIGN_HOTELSETTINGINFO, _CAMPAIGN_LOCALCAMPAIGNSETTING, _CAMPAIGN_APPCAMPAIGNSETTING, _CAMPAIGN_DYNAMICSEARCHADSSETTING, _CAMPAIGN_SELECTIVEOPTIMIZATION, _CAMPAIGN_SHOPPINGSETTING, _CAMPAIGN_TRACKINGSETTING, _CAMPAIGN_GEOTARGETTYPESETTING, _CAMPAIGN_OPTIMIZATIONGOALSETTING, _CAMPAIGN_VANITYPHARMA, ], enum_types=[ ], serialized_options=_b('\352AN\n!googleads.googleapis.com/Campaign\022)customers/{customer}/campaigns/{campaign}'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='campaign_bidding_strategy', full_name='google.ads.googleads.v4.resources.Campaign.campaign_bidding_strategy', index=0, containing_type=None, fields=[]), ], serialized_start=1667, serialized_end=8005, ) _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_google_search'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_search_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_content_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.fields_by_name['target_partner_search_network'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_NETWORKSETTINGS.containing_type = _CAMPAIGN _CAMPAIGN_HOTELSETTINGINFO.fields_by_name['hotel_center_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN_HOTELSETTINGINFO.containing_type = _CAMPAIGN _CAMPAIGN_LOCALCAMPAIGNSETTING.fields_by_name['location_source_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_location__source__type__pb2._LOCATIONSOURCETYPEENUM_LOCATIONSOURCETYPE _CAMPAIGN_LOCALCAMPAIGNSETTING.containing_type = _CAMPAIGN _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['bidding_strategy_goal_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__bidding__strategy__goal__type__pb2._APPCAMPAIGNBIDDINGSTRATEGYGOALTYPEENUM_APPCAMPAIGNBIDDINGSTRATEGYGOALTYPE _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_store'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_app__campaign__app__store__pb2._APPCAMPAIGNAPPSTOREENUM_APPCAMPAIGNAPPSTORE _CAMPAIGN_APPCAMPAIGNSETTING.containing_type = _CAMPAIGN _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['domain_name'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['language_code'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['use_supplied_urls_only'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['feeds'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_DYNAMICSEARCHADSSETTING.containing_type = _CAMPAIGN _CAMPAIGN_SELECTIVEOPTIMIZATION.fields_by_name['conversion_actions'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_SELECTIVEOPTIMIZATION.containing_type = _CAMPAIGN _CAMPAIGN_SHOPPINGSETTING.fields_by_name['merchant_id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['sales_country'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['campaign_priority'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT32VALUE _CAMPAIGN_SHOPPINGSETTING.fields_by_name['enable_local'].message_type = google_dot_protobuf_dot_wrappers__pb2._BOOLVALUE _CAMPAIGN_SHOPPINGSETTING.containing_type = _CAMPAIGN _CAMPAIGN_TRACKINGSETTING.fields_by_name['tracking_url'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN_TRACKINGSETTING.containing_type = _CAMPAIGN _CAMPAIGN_GEOTARGETTYPESETTING.fields_by_name['positive_geo_target_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_positive__geo__target__type__pb2._POSITIVEGEOTARGETTYPEENUM_POSITIVEGEOTARGETTYPE _CAMPAIGN_GEOTARGETTYPESETTING.fields_by_name['negative_geo_target_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_negative__geo__target__type__pb2._NEGATIVEGEOTARGETTYPEENUM_NEGATIVEGEOTARGETTYPE _CAMPAIGN_GEOTARGETTYPESETTING.containing_type = _CAMPAIGN _CAMPAIGN_OPTIMIZATIONGOALSETTING.fields_by_name['optimization_goal_types'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_optimization__goal__type__pb2._OPTIMIZATIONGOALTYPEENUM_OPTIMIZATIONGOALTYPE _CAMPAIGN_OPTIMIZATIONGOALSETTING.containing_type = _CAMPAIGN _CAMPAIGN_VANITYPHARMA.fields_by_name['vanity_pharma_display_url_mode'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__display__url__mode__pb2._VANITYPHARMADISPLAYURLMODEENUM_VANITYPHARMADISPLAYURLMODE _CAMPAIGN_VANITYPHARMA.fields_by_name['vanity_pharma_text'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_vanity__pharma__text__pb2._VANITYPHARMATEXTENUM_VANITYPHARMATEXT _CAMPAIGN_VANITYPHARMA.containing_type = _CAMPAIGN _CAMPAIGN.fields_by_name['id'].message_type = google_dot_protobuf_dot_wrappers__pb2._INT64VALUE _CAMPAIGN.fields_by_name['name'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__status__pb2._CAMPAIGNSTATUSENUM_CAMPAIGNSTATUS _CAMPAIGN.fields_by_name['serving_status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__serving__status__pb2._CAMPAIGNSERVINGSTATUSENUM_CAMPAIGNSERVINGSTATUS _CAMPAIGN.fields_by_name['ad_serving_optimization_status'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_ad__serving__optimization__status__pb2._ADSERVINGOPTIMIZATIONSTATUSENUM_ADSERVINGOPTIMIZATIONSTATUS _CAMPAIGN.fields_by_name['advertising_channel_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__type__pb2._ADVERTISINGCHANNELTYPEENUM_ADVERTISINGCHANNELTYPE _CAMPAIGN.fields_by_name['advertising_channel_sub_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_advertising__channel__sub__type__pb2._ADVERTISINGCHANNELSUBTYPEENUM_ADVERTISINGCHANNELSUBTYPE _CAMPAIGN.fields_by_name['tracking_url_template'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['url_custom_parameters'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_custom__parameter__pb2._CUSTOMPARAMETER _CAMPAIGN.fields_by_name['real_time_bidding_setting'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_real__time__bidding__setting__pb2._REALTIMEBIDDINGSETTING _CAMPAIGN.fields_by_name['network_settings'].message_type = _CAMPAIGN_NETWORKSETTINGS _CAMPAIGN.fields_by_name['hotel_setting'].message_type = _CAMPAIGN_HOTELSETTINGINFO _CAMPAIGN.fields_by_name['dynamic_search_ads_setting'].message_type = _CAMPAIGN_DYNAMICSEARCHADSSETTING _CAMPAIGN.fields_by_name['shopping_setting'].message_type = _CAMPAIGN_SHOPPINGSETTING _CAMPAIGN.fields_by_name['targeting_setting'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_targeting__setting__pb2._TARGETINGSETTING _CAMPAIGN.fields_by_name['geo_target_type_setting'].message_type = _CAMPAIGN_GEOTARGETTYPESETTING _CAMPAIGN.fields_by_name['local_campaign_setting'].message_type = _CAMPAIGN_LOCALCAMPAIGNSETTING _CAMPAIGN.fields_by_name['app_campaign_setting'].message_type = _CAMPAIGN_APPCAMPAIGNSETTING _CAMPAIGN.fields_by_name['labels'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['experiment_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_campaign__experiment__type__pb2._CAMPAIGNEXPERIMENTTYPEENUM_CAMPAIGNEXPERIMENTTYPE _CAMPAIGN.fields_by_name['base_campaign'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['campaign_budget'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['bidding_strategy_type'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_bidding__strategy__type__pb2._BIDDINGSTRATEGYTYPEENUM_BIDDINGSTRATEGYTYPE _CAMPAIGN.fields_by_name['start_date'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['end_date'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['final_url_suffix'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['frequency_caps'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_frequency__cap__pb2._FREQUENCYCAPENTRY _CAMPAIGN.fields_by_name['video_brand_safety_suitability'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_brand__safety__suitability__pb2._BRANDSAFETYSUITABILITYENUM_BRANDSAFETYSUITABILITY _CAMPAIGN.fields_by_name['vanity_pharma'].message_type = _CAMPAIGN_VANITYPHARMA _CAMPAIGN.fields_by_name['selective_optimization'].message_type = _CAMPAIGN_SELECTIVEOPTIMIZATION _CAMPAIGN.fields_by_name['optimization_goal_setting'].message_type = _CAMPAIGN_OPTIMIZATIONGOALSETTING _CAMPAIGN.fields_by_name['tracking_setting'].message_type = _CAMPAIGN_TRACKINGSETTING _CAMPAIGN.fields_by_name['payment_mode'].enum_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_enums_dot_payment__mode__pb2._PAYMENTMODEENUM_PAYMENTMODE _CAMPAIGN.fields_by_name['optimization_score'].message_type = google_dot_protobuf_dot_wrappers__pb2._DOUBLEVALUE _CAMPAIGN.fields_by_name['bidding_strategy'].message_type = google_dot_protobuf_dot_wrappers__pb2._STRINGVALUE _CAMPAIGN.fields_by_name['commission'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._COMMISSION _CAMPAIGN.fields_by_name['manual_cpc'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPC _CAMPAIGN.fields_by_name['manual_cpm'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPM _CAMPAIGN.fields_by_name['manual_cpv'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MANUALCPV _CAMPAIGN.fields_by_name['maximize_conversions'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MAXIMIZECONVERSIONS _CAMPAIGN.fields_by_name['maximize_conversion_value'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._MAXIMIZECONVERSIONVALUE _CAMPAIGN.fields_by_name['target_cpa'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETCPA _CAMPAIGN.fields_by_name['target_impression_share'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETIMPRESSIONSHARE _CAMPAIGN.fields_by_name['target_roas'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETROAS _CAMPAIGN.fields_by_name['target_spend'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETSPEND _CAMPAIGN.fields_by_name['percent_cpc'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._PERCENTCPC _CAMPAIGN.fields_by_name['target_cpm'].message_type = google_dot_ads_dot_googleads__v4_dot_proto_dot_common_dot_bidding__pb2._TARGETCPM _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['bidding_strategy']) _CAMPAIGN.fields_by_name['bidding_strategy'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['commission']) _CAMPAIGN.fields_by_name['commission'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpc']) _CAMPAIGN.fields_by_name['manual_cpc'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpm']) _CAMPAIGN.fields_by_name['manual_cpm'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['manual_cpv']) _CAMPAIGN.fields_by_name['manual_cpv'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['maximize_conversions']) _CAMPAIGN.fields_by_name['maximize_conversions'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['maximize_conversion_value']) _CAMPAIGN.fields_by_name['maximize_conversion_value'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_cpa']) _CAMPAIGN.fields_by_name['target_cpa'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_impression_share']) _CAMPAIGN.fields_by_name['target_impression_share'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_roas']) _CAMPAIGN.fields_by_name['target_roas'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_spend']) _CAMPAIGN.fields_by_name['target_spend'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['percent_cpc']) _CAMPAIGN.fields_by_name['percent_cpc'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'].fields.append( _CAMPAIGN.fields_by_name['target_cpm']) _CAMPAIGN.fields_by_name['target_cpm'].containing_oneof = _CAMPAIGN.oneofs_by_name['campaign_bidding_strategy'] DESCRIPTOR.message_types_by_name['Campaign'] = _CAMPAIGN _sym_db.RegisterFileDescriptor(DESCRIPTOR) Campaign = _reflection.GeneratedProtocolMessageType('Campaign', (_message.Message,), dict( NetworkSettings = _reflection.GeneratedProtocolMessageType('NetworkSettings', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_NETWORKSETTINGS, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The network settings for the campaign. Attributes: target_google_search: Whether ads will be served with google.com search results. target_search_network: Whether ads will be served on partner sites in the Google Search Network (requires ``target_google_search`` to also be ``true``). target_content_network: Whether ads will be served on specified placements in the Google Display Network. Placements are specified using the Placement criterion. target_partner_search_network: Whether ads will be served on the Google Partner Network. This is available only to some select Google partner accounts. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.NetworkSettings) )) , HotelSettingInfo = _reflection.GeneratedProtocolMessageType('HotelSettingInfo', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_HOTELSETTINGINFO, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for hotel ads. Attributes: hotel_center_id: Immutable. The linked Hotel Center account. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.HotelSettingInfo) )) , LocalCampaignSetting = _reflection.GeneratedProtocolMessageType('LocalCampaignSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_LOCALCAMPAIGNSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign setting for local campaigns. Attributes: location_source_type: The location source type for this local campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.LocalCampaignSetting) )) , AppCampaignSetting = _reflection.GeneratedProtocolMessageType('AppCampaignSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_APPCAMPAIGNSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for App Campaigns. Attributes: bidding_strategy_goal_type: Represents the goal which the bidding strategy of this app campaign should optimize towards. app_id: Immutable. A string that uniquely identifies a mobile application. app_store: Immutable. The application store that distributes this specific app. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.AppCampaignSetting) )) , DynamicSearchAdsSetting = _reflection.GeneratedProtocolMessageType('DynamicSearchAdsSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_DYNAMICSEARCHADSSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The setting for controlling Dynamic Search Ads (DSA). Attributes: domain_name: The Internet domain name that this setting represents, e.g., "google.com" or "www.google.com". language_code: The language code specifying the language of the domain, e.g., "en". use_supplied_urls_only: Whether the campaign uses advertiser supplied URLs exclusively. feeds: Output only. The list of page feeds associated with the campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.DynamicSearchAdsSetting) )) , SelectiveOptimization = _reflection.GeneratedProtocolMessageType('SelectiveOptimization', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_SELECTIVEOPTIMIZATION, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Selective optimization setting for this campaign, which includes a set of conversion actions to optimize this campaign towards. Attributes: conversion_actions: The selected set of conversion actions for optimizing this campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.SelectiveOptimization) )) , ShoppingSetting = _reflection.GeneratedProtocolMessageType('ShoppingSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_SHOPPINGSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """The setting for Shopping campaigns. Defines the universe of products that can be advertised by the campaign, and how this campaign interacts with other Shopping campaigns. Attributes: merchant_id: Immutable. ID of the Merchant Center account. This field is required for create operations. This field is immutable for Shopping campaigns. sales_country: Immutable. Sales country of products to include in the campaign. This field is required for Shopping campaigns. This field is immutable. This field is optional for non-Shopping campaigns, but it must be equal to 'ZZ' if set. campaign_priority: Priority of the campaign. Campaigns with numerically higher priorities take precedence over those with lower priorities. This field is required for Shopping campaigns, with values between 0 and 2, inclusive. This field is optional for Smart Shopping campaigns, but must be equal to 3 if set. enable_local: Whether to include local products. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.ShoppingSetting) )) , TrackingSetting = _reflection.GeneratedProtocolMessageType('TrackingSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_TRACKINGSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Campaign-level settings for tracking information. Attributes: tracking_url: Output only. The url used for dynamic tracking. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.TrackingSetting) )) , GeoTargetTypeSetting = _reflection.GeneratedProtocolMessageType('GeoTargetTypeSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_GEOTARGETTYPESETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Represents a collection of settings related to ads geotargeting. Attributes: positive_geo_target_type: The setting used for positive geotargeting in this particular campaign. negative_geo_target_type: The setting used for negative geotargeting in this particular campaign. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.GeoTargetTypeSetting) )) , OptimizationGoalSetting = _reflection.GeneratedProtocolMessageType('OptimizationGoalSetting', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_OPTIMIZATIONGOALSETTING, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Optimization goal setting for this campaign, which includes a set of optimization goal types. Attributes: optimization_goal_types: The list of optimization goal types. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.OptimizationGoalSetting) )) , VanityPharma = _reflection.GeneratedProtocolMessageType('VanityPharma', (_message.Message,), dict( DESCRIPTOR = _CAMPAIGN_VANITYPHARMA, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """Describes how unbranded pharma ads will be displayed. Attributes: vanity_pharma_display_url_mode: The display mode for vanity pharma URLs. vanity_pharma_text: The text that will be displayed in display URL of the text ad when website description is the selected display mode for vanity pharma URLs. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v4.resources.Campaign.VanityPharma) )) , DESCRIPTOR = _CAMPAIGN, __module__ = 'google.ads.googleads_v4.proto.resources.campaign_pb2' , __doc__ = """A campaign. Attributes: resource_name: Immutable. The resource name of the campaign. Campaign resource names have the form: ``customers/{customer_id}/campaigns/{campaign_id}`` id: Output only. The ID of the campaign. name: The name of the campaign. This field is required and should not be empty when creating new campaigns. It must not contain any null (code point 0x0), NL line feed (code point 0xA) or carriage return (code point 0xD) characters. status: The status of the campaign. When a new campaign is added, the status defaults to ENABLED. serving_status: Output only. The ad serving status of the campaign. ad_serving_optimization_status: The ad serving optimization status of the campaign. advertising_channel_type: Immutable. The primary serving target for ads within the campaign. The targeting options can be refined in ``network_settings``. This field is required and should not be empty when creating new campaigns. Can be set only when creating campaigns. After the campaign is created, the field can not be changed. advertising_channel_sub_type: Immutable. Optional refinement to ``advertising_channel_type``. Must be a valid sub-type of the parent channel type. Can be set only when creating campaigns. After campaign is created, the field can not be changed. tracking_url_template: The URL template for constructing a tracking URL. url_custom_parameters: The list of mappings used to substitute custom parameter tags in a ``tracking_url_template``, ``final_urls``, or ``mobile_final_urls``. real_time_bidding_setting: Settings for Real-Time Bidding, a feature only available for campaigns targeting the Ad Exchange network. network_settings: The network settings for the campaign. hotel_setting: Immutable. The hotel setting for the campaign. dynamic_search_ads_setting: The setting for controlling Dynamic Search Ads (DSA). shopping_setting: The setting for controlling Shopping campaigns. targeting_setting: Setting for targeting related features. geo_target_type_setting: The setting for ads geotargeting. local_campaign_setting: The setting for local campaign. app_campaign_setting: The setting related to App Campaign. labels: Output only. The resource names of labels attached to this campaign. experiment_type: Output only. The type of campaign: normal, draft, or experiment. base_campaign: Output only. The resource name of the base campaign of a draft or experiment campaign. For base campaigns, this is equal to ``resource_name``. This field is read-only. campaign_budget: The budget of the campaign. bidding_strategy_type: Output only. The type of bidding strategy. A bidding strategy can be created by setting either the bidding scheme to create a standard bidding strategy or the ``bidding_strategy`` field to create a portfolio bidding strategy. This field is read- only. start_date: The date when campaign started. This field must not be used in WHERE clauses. end_date: The date when campaign ended. This field must not be used in WHERE clauses. final_url_suffix: Suffix used to append query parameters to landing pages that are served with parallel tracking. frequency_caps: A list that limits how often each user will see this campaign's ads. video_brand_safety_suitability: Output only. 3-Tier Brand Safety setting for the campaign. vanity_pharma: Describes how unbranded pharma ads will be displayed. selective_optimization: Selective optimization setting for this campaign, which includes a set of conversion actions to optimize this campaign towards. optimization_goal_setting: Optimization goal setting for this campaign, which includes a set of optimization goal types. tracking_setting: Output only. Campaign-level settings for tracking information. payment_mode: Payment mode for the campaign. optimization_score: Output only. Optimization score of the campaign. Optimization score is an estimate of how well a campaign is set to perform. It ranges from 0% (0.0) to 100% (1.0), with 100% indicating that the campaign is performing at full potential. See "About optimization score" at https://support.google.com/google- ads/answer/9061546. This field is read-only. campaign_bidding_strategy: The bidding strategy for the campaign. Must be either portfolio (created via BiddingStrategy service) or standard, that is embedded into the campaign. bidding_strategy: Portfolio bidding strategy used by campaign. commission: Commission is an automatic bidding strategy in which the advertiser pays a certain portion of the conversion value. manual_cpc: Standard Manual CPC bidding strategy. Manual click-based bidding where user pays per click. manual_cpm: Standard Manual CPM bidding strategy. Manual impression-based bidding where user pays per thousand impressions. manual_cpv: Output only. A bidding strategy that pays a configurable amount per video view. maximize_conversions: Standard Maximize Conversions bidding strategy that automatically maximizes number of conversions given a daily budget. maximize_conversion_value: Standard Maximize Conversion Value bidding strategy that automatically sets bids to maximize revenue while spending your budget. target_cpa: Standard Target CPA bidding strategy that automatically sets bids to help get as many conversions as possible at the target cost-per-acquisition (CPA) you set. target_impression_share: Target Impression Share bidding strategy. An automated bidding strategy that sets bids to achieve a desired percentage of impressions. target_roas: Standard Target ROAS bidding strategy that automatically maximizes revenue while averaging a specific target return on ad spend (ROAS). target_spend: Standard Target Spend bidding strategy that automatically sets your bids to help get as many clicks as possible within your budget. percent_cpc: Standard Percent Cpc bidding strategy where bids are a fraction of the advertised price for some good or service. target_cpm: A bidding strategy that automatically optimizes cost per thousand impressions. """, )) _sym_db.RegisterMessage(Campaign) _sym_db.RegisterMessage(Campaign.NetworkSettings) _sym_db.RegisterMessage(Campaign.HotelSettingInfo) _sym_db.RegisterMessage(Campaign.LocalCampaignSetting) _sym_db.RegisterMessage(Campaign.AppCampaignSetting) _sym_db.RegisterMessage(Campaign.DynamicSearchAdsSetting) _sym_db.RegisterMessage(Campaign.SelectiveOptimization) _sym_db.RegisterMessage(Campaign.ShoppingSetting) _sym_db.RegisterMessage(Campaign.TrackingSetting) _sym_db.RegisterMessage(Campaign.GeoTargetTypeSetting) _sym_db.RegisterMessage(Campaign.OptimizationGoalSetting) _sym_db.RegisterMessage(Campaign.VanityPharma) DESCRIPTOR._options = None _CAMPAIGN_HOTELSETTINGINFO.fields_by_name['hotel_center_id']._options = None _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_id']._options = None _CAMPAIGN_APPCAMPAIGNSETTING.fields_by_name['app_store']._options = None _CAMPAIGN_DYNAMICSEARCHADSSETTING.fields_by_name['feeds']._options = None _CAMPAIGN_SELECTIVEOPTIMIZATION.fields_by_name['conversion_actions']._options = None _CAMPAIGN_SHOPPINGSETTING.fields_by_name['merchant_id']._options = None _CAMPAIGN_SHOPPINGSETTING.fields_by_name['sales_country']._options = None _CAMPAIGN_TRACKINGSETTING.fields_by_name['tracking_url']._options = None _CAMPAIGN.fields_by_name['resource_name']._options = None _CAMPAIGN.fields_by_name['id']._options = None _CAMPAIGN.fields_by_name['serving_status']._options = None _CAMPAIGN.fields_by_name['advertising_channel_type']._options = None _CAMPAIGN.fields_by_name['advertising_channel_sub_type']._options = None _CAMPAIGN.fields_by_name['hotel_setting']._options = None _CAMPAIGN.fields_by_name['labels']._options = None _CAMPAIGN.fields_by_name['experiment_type']._options = None _CAMPAIGN.fields_by_name['base_campaign']._options = None _CAMPAIGN.fields_by_name['campaign_budget']._options = None _CAMPAIGN.fields_by_name['bidding_strategy_type']._options = None _CAMPAIGN.fields_by_name['video_brand_safety_suitability']._options = None _CAMPAIGN.fields_by_name['tracking_setting']._options = None _CAMPAIGN.fields_by_name['optimization_score']._options = None _CAMPAIGN.fields_by_name['bidding_strategy']._options = None _CAMPAIGN.fields_by_name['manual_cpv']._options = None _CAMPAIGN._options = None

true

f73910ff97bc6e0563c1408384190999e737fcfd

12,628

py

Python

build.py

charlie45000/corunners-example

0de8463074fa9a02d0a361fc3dd50bf620991ea2

[ "Apache-2.0" ]

null

build.py

charlie45000/corunners-example

0de8463074fa9a02d0a361fc3dd50bf620991ea2

[ "Apache-2.0" ]

1

2021-06-02T09:10:15.000Z

build.py

charlie45000/corunners-example

0de8463074fa9a02d0a361fc3dd50bf620991ea2

[ "Apache-2.0" ]

1

2021-03-08T13:18:03.000Z

#! /usr/bin/env python3 import argparse from pathlib import Path import subprocess import sys import scripts.templates from scripts.templates import P2020, MPC5777M, CORES, TOP_DIR, PSY_DIR, STUBS_DIR, SRC_DIR, CFG_DIR, Help, AGENT_CONFIG_HJSON_TEMPLATE, CORUNNER_CONFIG_HJSON_TEMPLATE, CORUNNER_KMEMORY_JSON_TEMPLATE, COMPILE_CONFIG_HJSON_TEMPLATE, PSYMODULE_CONFIG_HJSON_TEMPLATE, FLASHLIKE from scripts.scriptutil import load_db, load_json, dump_json, write_template, psyko from operator import itemgetter def corunner_to_list(s): """ This function takes the corunner string (a comma separated list: <core>,<start address of read>) and returns a python list of the same form (with none as second element if there is only a core). This allows to set a start address for each corunner in case there is at least two. Should not be used except as an argument parser type. """ pars = s.split(',') pars[0] = int(pars[0]) assert pars[0] in CORES, \ f"The corunner id must be one of {CORES.join(', ')}" l = len(pars) if l > 2: raise argparse.ArgumentTypeError("Corunners parameters must be of type <core>[,<start address of read>]") elif l == 2 and pars[1] != '': return pars else: return [pars[0], None] def cor_cores(cors): """ Takes a list returned by corunner_to_list and returns a list containing only the cores in the same order (to know which cores are used). """ return [i[0] for i in cors] def getopts(argv): parser = argparse.ArgumentParser(description='Corunners builder') parser.add_argument("--psyko", "-P", type=Path, help=Help.PSYKO, required=True) parser.add_argument("--kdbv", type=Path, required=True) parser.add_argument("--rtk-dir", "-K", type=Path, help=Help.RTK_DIR, required=True) parser.add_argument("--product", "-p", type=str, help=Help.PRODUCT, required=True, choices=[P2020,MPC5777M]) parser.add_argument("--corunner", "-C", type=corunner_to_list, action="append", help=Help.CORUNNER, default=[]) parser.add_argument("--task", "-T", type=str, choices=["H", "G"]+FLASHLIKE, help=Help.TASK, required=True) parser.add_argument("--core", "-c", type=int, choices=CORES, help=Help.CORE, required=True) parser.add_argument("--local-corunners", action='store_true', help=Help.LOCAL_CORUNNERS) parser.add_argument("--build-dir", type=Path, default=TOP_DIR / "build", help=Help.BUILD_DIR) parser.add_argument("--mem-conf", type=Path, help=Help.MEM_CONF) parser.add_argument("--output", "-o", type=Path, help=Help.OUTPUT) args = parser.parse_args(argv[1:]) assert args.core not in cor_cores(args.corunner) if args.output is None: args.output = args.build_dir / "program.elf" return args def gen_agent_config(output_filename, name, core): write_template(output_filename, AGENT_CONFIG_HJSON_TEMPLATE, { "agent_name": name, "agent_core": core, }) def gen_corunner_config(conf_filename, identifier, symbol, object_file, kmem_filename): write_template(conf_filename, CORUNNER_CONFIG_HJSON_TEMPLATE, { "corunner_id": identifier, "corunner_symbol": symbol, "corunner_object": str(object_file) }) write_template(kmem_filename, CORUNNER_KMEMORY_JSON_TEMPLATE, { 'symbol': symbol, }) def gen_corunner_source(output_filename, symbol, read=dict()): cmd = [sys.executable, TOP_DIR / "scripts" / "gen-corunner.py", symbol] if read: cmd += ["--read"] if 'nop' in read: cmd += ["--nop", str(read['nop'])] if 'start' in read: cmd += ["--startaddr", str(read['start'])] if 'size' in read: cmd += ["--tablesize", str(read['size'])] if 'stride' in read: cmd += ["--stride", str(read['stride'])] else: cmd += ["--jump", "2048"] with subprocess.Popen(cmd, stdout=subprocess.PIPE, universal_newlines=True) as proc: with open(output_filename, "w") as fileh: fileh.write(proc.stdout.read()) def gen_kmem_final(default, config, memreport, kdbv, tasks, corunners=list()): config_json = load_json(config) cmd = [sys.executable, TOP_DIR / 'scripts' / 'gen-kmem.py', '--config', config] del_list = [] config_json['memreport'] = str(memreport) config_json['default_kmemory'] = str(default) for el in config_json['elements']: if el['type'] == 'corunner': if corunners: el['names'] = corunners else: del_list.append(el) elif el['type'] == 'task': el['names'] = tasks else: del_list.append(el) for el in del_list: config_json['elements'].remove(el) dump_json(config_json, config) ret = subprocess.check_call(cmd) def get_sources(task_name): c_sources = [ SRC_DIR / "crc.c", SRC_DIR / "filter.c", SRC_DIR / "filter2.c", ] psy_sources = [PSY_DIR / f"task_{task_name}.psy"] if task_name not in FLASHLIKE: c_sources += [ STUBS_DIR / f"suite_task_{task_name}.c", ] psy_sources += [STUBS_DIR / f"for_task_{task_name}.psy"] return { "c": c_sources, "asm": [], "psy": psy_sources, } def main(argv): args = getopts(argv) used_cores = cor_cores(args.corunner) + [args.core] args.corunner.sort(key=itemgetter(0)) def object_of(source_filename, extension = ".o"): return args.build_dir / (source_filename.name + extension) sources = get_sources(args.task) ag_config = args.build_dir / "task.hjson" app_configs = [ args.build_dir / "app.hjson", CFG_DIR / f"task_{args.task}.hjson", ag_config, ] tasks = [f'task_{args.task}'] part_configs = [] compile_config = args.build_dir / "compile.hjson" partition_config = args.build_dir / "partition.hjson" psymodule_config = args.build_dir / "psymodule.hjson" gen_agent_config(ag_config, f"task_{args.task}", args.core) mem_configs = [] corunners = [] for corunner, cor_start in args.corunner: # The read corunner is created only if a start address si provided for this corunner. use_read = bool(cor_start) read_args = dict() co_config = args.build_dir / f"corunner_{corunner}.hjson" co_kmem = args.build_dir / f"corunner_{corunner}_kmem.json" co_file = args.build_dir / f"corunner_{corunner}" if use_read: read_args['start'] = cor_start read_args['size'] = int(env.get(f"CORUNNER_READ_SIZE_{corunner}", "0x2000"), 16) symbol = f"co_runner_read{corunner}" if read_args else f"co_runner_flash{corunner}" co_file = co_file.with_suffix('.asm') sources["asm"].append(co_file) gen_corunner_source(co_file, symbol, read_args) app_configs.append(co_config) mem_configs.append(co_kmem) corunners.append(symbol) gen_corunner_config(co_config, corunner, symbol, object_of(co_file), co_kmem) if args.task not in FLASHLIKE: stub_config = args.build_dir / "stub.hjson" gen_agent_config(stub_config, f"sends_to_task_{args.task}", args.core) app_configs.append(stub_config) tasks.append(f'sends_to_task_{args.task}') write_template(compile_config, COMPILE_CONFIG_HJSON_TEMPLATE, {}) write_template(psymodule_config, PSYMODULE_CONFIG_HJSON_TEMPLATE, {}) #========================================================================== # The functions below are just helpers to call the PsyC compiler psyko, # with a convenient access to global variables such as the path to the # compiler and the path to the RTK. psykonf = {'product': args.product, 'rtk_dir': args.rtk_dir, 'psyko': args.psyko, 'cwd': TOP_DIR} def psyko_cc(c_source): generated_object = object_of(c_source) psyko(psykonf, "cc", c_source, compile_config, "-o", generated_object) return generated_object def psyko_as(asm_source): generated_object = object_of(asm_source) psyko(psykonf, "as", asm_source, compile_config, "-o", generated_object) return generated_object def psyko_module(psy_source): generated_object = object_of(psy_source, ".psyo") psyko(psykonf, "module", psy_source, psymodule_config, "-o", generated_object) return generated_object def psyko_partition(name, objects, configs): generated_object = args.build_dir / (name + ".parto") psyko(psykonf, "partition", "-o", generated_object, '--gendir', args.build_dir / 'gen' / 'part', *objects, *configs) return generated_object def psyko_app(partos, configs): elf = args.build_dir / "program.elf" gendir = args.build_dir / "gen" / "app" psyko(psykonf, "app", "-a", args.build_dir / "program.app", "-b", args.output, '--gendir', gendir, *partos, *configs) return gendir def psyko_memconf(t, files, configs=[], cor_kmems=[]): """ This function generates a valid default memconf used to perform the first compilation. It creates a default kmemory for the task and adds the configs for all the corunners. """ kmemconf = args.build_dir / ('kmemconf_'+t+'.json') psyko(psykonf, 'gen-mem-conf', '-t', t, '--gendir', args.build_dir / 'gen' / 'memconf', '-o', kmemconf, *files, *configs) if cor_kmems: def_memconf = load_json(kmemconf) cor_memconf = [] for kmem in cor_kmems: cor_memconf.append(load_json(kmem)) max_reg = def_memconf['kmemory']['regions'][0] if len(def_memconf['kmemory']['regions']) > 1: for reg in def_memconf['kmemory']['regions'][1:]: if reg['size'] > max_reg['size']: max_reg = reg if 'domains' not in max_reg: max_reg['domains'] = [] out = cor_memconf[0]['domains'][0]['output_sections'][0] out['physical_address'] = mar_reg['physical_address'] stacks = {obj['id']: obj for obj in def_memconf['kmemory']['objects'] if obj['id'] in [f"core_{core}_co_runner_stack.c" for core in used_cores]} for core in cor_cores(args.corunner): stack = f"core_{core}_co_runner_stack.c" for corunner in corunners: symbol = corunner if corunner[-1] == str(core) else '' stacks[stack]['groups'] = [f'.stack_{symbol}'] for cor in cor_memconf: max_reg['domains'] += cor['domains'] def_memconf['kmemory']['groups'] += cor['groups'] def_memconf['kmemory']['objects'] += cor['objects'] dump_json(def_memconf, f=kmemconf) return kmemconf #========================================================================== # Compile all the C, ASM and PsyC sources. # ASM sources are only present when co-runners are enabled. parto_objects = [] for c_source in sources["c"]: parto_objects.append(psyko_cc(c_source)) for asm_source in sources.get("asm", []): parto_objects.append(psyko_as(asm_source)) for psy_source in sources["psy"]: parto_objects.append(psyko_module(psy_source)) #========================================================================== # Generate a single partition, and then executable to be able to get the size of the sections parto = psyko_partition("main", parto_objects, part_configs) mem_configs = [psyko_memconf('app', [parto], app_configs, mem_configs)] mem_configs.append("--overwrite-memory-configuration") gendir = psyko_app([parto], app_configs+mem_configs) assert args.output.is_file(), "first app compilation not successfull" # Finally generate the final memory configs and the executable if args.mem_conf: args.output.unlink() gen_kmem_final(mem_configs[0], args.mem_conf, gendir / 'applink' / 'memreport_out.ks', args.kdbv, tasks, corunners) psyko_app([parto], app_configs+mem_configs) assert args.output.is_file(), "final app compilation not successfull" if __name__ == "__main__": main(sys.argv)

42.375839

282

0.617041

import argparse from pathlib import Path import subprocess import sys import scripts.templates from scripts.templates import P2020, MPC5777M, CORES, TOP_DIR, PSY_DIR, STUBS_DIR, SRC_DIR, CFG_DIR, Help, AGENT_CONFIG_HJSON_TEMPLATE, CORUNNER_CONFIG_HJSON_TEMPLATE, CORUNNER_KMEMORY_JSON_TEMPLATE, COMPILE_CONFIG_HJSON_TEMPLATE, PSYMODULE_CONFIG_HJSON_TEMPLATE, FLASHLIKE from scripts.scriptutil import load_db, load_json, dump_json, write_template, psyko from operator import itemgetter def corunner_to_list(s): pars = s.split(',') pars[0] = int(pars[0]) assert pars[0] in CORES, \ f"The corunner id must be one of {CORES.join(', ')}" l = len(pars) if l > 2: raise argparse.ArgumentTypeError("Corunners parameters must be of type <core>[,<start address of read>]") elif l == 2 and pars[1] != '': return pars else: return [pars[0], None] def cor_cores(cors): return [i[0] for i in cors] def getopts(argv): parser = argparse.ArgumentParser(description='Corunners builder') parser.add_argument("--psyko", "-P", type=Path, help=Help.PSYKO, required=True) parser.add_argument("--kdbv", type=Path, required=True) parser.add_argument("--rtk-dir", "-K", type=Path, help=Help.RTK_DIR, required=True) parser.add_argument("--product", "-p", type=str, help=Help.PRODUCT, required=True, choices=[P2020,MPC5777M]) parser.add_argument("--corunner", "-C", type=corunner_to_list, action="append", help=Help.CORUNNER, default=[]) parser.add_argument("--task", "-T", type=str, choices=["H", "G"]+FLASHLIKE, help=Help.TASK, required=True) parser.add_argument("--core", "-c", type=int, choices=CORES, help=Help.CORE, required=True) parser.add_argument("--local-corunners", action='store_true', help=Help.LOCAL_CORUNNERS) parser.add_argument("--build-dir", type=Path, default=TOP_DIR / "build", help=Help.BUILD_DIR) parser.add_argument("--mem-conf", type=Path, help=Help.MEM_CONF) parser.add_argument("--output", "-o", type=Path, help=Help.OUTPUT) args = parser.parse_args(argv[1:]) assert args.core not in cor_cores(args.corunner) if args.output is None: args.output = args.build_dir / "program.elf" return args def gen_agent_config(output_filename, name, core): write_template(output_filename, AGENT_CONFIG_HJSON_TEMPLATE, { "agent_name": name, "agent_core": core, }) def gen_corunner_config(conf_filename, identifier, symbol, object_file, kmem_filename): write_template(conf_filename, CORUNNER_CONFIG_HJSON_TEMPLATE, { "corunner_id": identifier, "corunner_symbol": symbol, "corunner_object": str(object_file) }) write_template(kmem_filename, CORUNNER_KMEMORY_JSON_TEMPLATE, { 'symbol': symbol, }) def gen_corunner_source(output_filename, symbol, read=dict()): cmd = [sys.executable, TOP_DIR / "scripts" / "gen-corunner.py", symbol] if read: cmd += ["--read"] if 'nop' in read: cmd += ["--nop", str(read['nop'])] if 'start' in read: cmd += ["--startaddr", str(read['start'])] if 'size' in read: cmd += ["--tablesize", str(read['size'])] if 'stride' in read: cmd += ["--stride", str(read['stride'])] else: cmd += ["--jump", "2048"] with subprocess.Popen(cmd, stdout=subprocess.PIPE, universal_newlines=True) as proc: with open(output_filename, "w") as fileh: fileh.write(proc.stdout.read()) def gen_kmem_final(default, config, memreport, kdbv, tasks, corunners=list()): config_json = load_json(config) cmd = [sys.executable, TOP_DIR / 'scripts' / 'gen-kmem.py', '--config', config] del_list = [] config_json['memreport'] = str(memreport) config_json['default_kmemory'] = str(default) for el in config_json['elements']: if el['type'] == 'corunner': if corunners: el['names'] = corunners else: del_list.append(el) elif el['type'] == 'task': el['names'] = tasks else: del_list.append(el) for el in del_list: config_json['elements'].remove(el) dump_json(config_json, config) ret = subprocess.check_call(cmd) def get_sources(task_name): c_sources = [ SRC_DIR / "crc.c", SRC_DIR / "filter.c", SRC_DIR / "filter2.c", ] psy_sources = [PSY_DIR / f"task_{task_name}.psy"] if task_name not in FLASHLIKE: c_sources += [ STUBS_DIR / f"suite_task_{task_name}.c", ] psy_sources += [STUBS_DIR / f"for_task_{task_name}.psy"] return { "c": c_sources, "asm": [], "psy": psy_sources, } def main(argv): args = getopts(argv) used_cores = cor_cores(args.corunner) + [args.core] args.corunner.sort(key=itemgetter(0)) def object_of(source_filename, extension = ".o"): return args.build_dir / (source_filename.name + extension) sources = get_sources(args.task) ag_config = args.build_dir / "task.hjson" app_configs = [ args.build_dir / "app.hjson", CFG_DIR / f"task_{args.task}.hjson", ag_config, ] tasks = [f'task_{args.task}'] part_configs = [] compile_config = args.build_dir / "compile.hjson" partition_config = args.build_dir / "partition.hjson" psymodule_config = args.build_dir / "psymodule.hjson" gen_agent_config(ag_config, f"task_{args.task}", args.core) mem_configs = [] corunners = [] for corunner, cor_start in args.corunner: use_read = bool(cor_start) read_args = dict() co_config = args.build_dir / f"corunner_{corunner}.hjson" co_kmem = args.build_dir / f"corunner_{corunner}_kmem.json" co_file = args.build_dir / f"corunner_{corunner}" if use_read: read_args['start'] = cor_start read_args['size'] = int(env.get(f"CORUNNER_READ_SIZE_{corunner}", "0x2000"), 16) symbol = f"co_runner_read{corunner}" if read_args else f"co_runner_flash{corunner}" co_file = co_file.with_suffix('.asm') sources["asm"].append(co_file) gen_corunner_source(co_file, symbol, read_args) app_configs.append(co_config) mem_configs.append(co_kmem) corunners.append(symbol) gen_corunner_config(co_config, corunner, symbol, object_of(co_file), co_kmem) if args.task not in FLASHLIKE: stub_config = args.build_dir / "stub.hjson" gen_agent_config(stub_config, f"sends_to_task_{args.task}", args.core) app_configs.append(stub_config) tasks.append(f'sends_to_task_{args.task}') write_template(compile_config, COMPILE_CONFIG_HJSON_TEMPLATE, {}) write_template(psymodule_config, PSYMODULE_CONFIG_HJSON_TEMPLATE, {}) psykonf = {'product': args.product, 'rtk_dir': args.rtk_dir, 'psyko': args.psyko, 'cwd': TOP_DIR} def psyko_cc(c_source): generated_object = object_of(c_source) psyko(psykonf, "cc", c_source, compile_config, "-o", generated_object) return generated_object def psyko_as(asm_source): generated_object = object_of(asm_source) psyko(psykonf, "as", asm_source, compile_config, "-o", generated_object) return generated_object def psyko_module(psy_source): generated_object = object_of(psy_source, ".psyo") psyko(psykonf, "module", psy_source, psymodule_config, "-o", generated_object) return generated_object def psyko_partition(name, objects, configs): generated_object = args.build_dir / (name + ".parto") psyko(psykonf, "partition", "-o", generated_object, '--gendir', args.build_dir / 'gen' / 'part', *objects, *configs) return generated_object def psyko_app(partos, configs): elf = args.build_dir / "program.elf" gendir = args.build_dir / "gen" / "app" psyko(psykonf, "app", "-a", args.build_dir / "program.app", "-b", args.output, '--gendir', gendir, *partos, *configs) return gendir def psyko_memconf(t, files, configs=[], cor_kmems=[]): kmemconf = args.build_dir / ('kmemconf_'+t+'.json') psyko(psykonf, 'gen-mem-conf', '-t', t, '--gendir', args.build_dir / 'gen' / 'memconf', '-o', kmemconf, *files, *configs) if cor_kmems: def_memconf = load_json(kmemconf) cor_memconf = [] for kmem in cor_kmems: cor_memconf.append(load_json(kmem)) max_reg = def_memconf['kmemory']['regions'][0] if len(def_memconf['kmemory']['regions']) > 1: for reg in def_memconf['kmemory']['regions'][1:]: if reg['size'] > max_reg['size']: max_reg = reg if 'domains' not in max_reg: max_reg['domains'] = [] out = cor_memconf[0]['domains'][0]['output_sections'][0] out['physical_address'] = mar_reg['physical_address'] stacks = {obj['id']: obj for obj in def_memconf['kmemory']['objects'] if obj['id'] in [f"core_{core}_co_runner_stack.c" for core in used_cores]} for core in cor_cores(args.corunner): stack = f"core_{core}_co_runner_stack.c" for corunner in corunners: symbol = corunner if corunner[-1] == str(core) else '' stacks[stack]['groups'] = [f'.stack_{symbol}'] for cor in cor_memconf: max_reg['domains'] += cor['domains'] def_memconf['kmemory']['groups'] += cor['groups'] def_memconf['kmemory']['objects'] += cor['objects'] dump_json(def_memconf, f=kmemconf) return kmemconf parto_objects = [] for c_source in sources["c"]: parto_objects.append(psyko_cc(c_source)) for asm_source in sources.get("asm", []): parto_objects.append(psyko_as(asm_source)) for psy_source in sources["psy"]: parto_objects.append(psyko_module(psy_source)) parto = psyko_partition("main", parto_objects, part_configs) mem_configs = [psyko_memconf('app', [parto], app_configs, mem_configs)] mem_configs.append("--overwrite-memory-configuration") gendir = psyko_app([parto], app_configs+mem_configs) assert args.output.is_file(), "first app compilation not successfull" if args.mem_conf: args.output.unlink() gen_kmem_final(mem_configs[0], args.mem_conf, gendir / 'applink' / 'memreport_out.ks', args.kdbv, tasks, corunners) psyko_app([parto], app_configs+mem_configs) assert args.output.is_file(), "final app compilation not successfull" if __name__ == "__main__": main(sys.argv)

true

f7391168b99f6f2fdae5a55cffae7b304ded5b5e

1,429

py

Python

ctsutils/test.py

534ttl3/ctsutils

b070bf349d4a112df576404a3948e0de60f24927

[ "MIT" ]

null

ctsutils/test.py

534ttl3/ctsutils

b070bf349d4a112df576404a3948e0de60f24927

[ "MIT" ]

null

ctsutils/test.py

534ttl3/ctsutils

b070bf349d4a112df576404a3948e0de60f24927

[ "MIT" ]

null

import numpy as np import matplotlib.pyplot as plt from ctsutils.cparameterspace import CParam, CParameterSpace def foo(X, Y, Y2): """ """ return (1 - X / 2 + X ** 5 + (Y + Y2 ) ** 3) * np.exp(-X ** 2 - (Y + Y2 ) ** 2) # calcul du tableau des valeurs de Z def foo(X, Y, Y2, Y3): """ """ return (1 - X / 2 + X ** 5 + (Y + Y2 + Y3) ** 3) * np.exp(-X ** 2 - (Y + Y2 + Y3) ** 2) # calcul du tableau des valeurs de Z ps = CParameterSpace([CParam("x", np.linspace(-3, 3, 51), unit="m"), CParam("y", np.linspace(-2, 2, 41)), CParam("y2", np.linspace(-1, 1, 31)), CParam("y3", np.linspace(-1, 1, 10))]) # import pdb; pdb.set_trace() # noqa BREAKPOINT # x = ps.get_arr("x") Z = ps.calc_function(foo, args_param_names=("x", "y", "y2", "y3")) integrals = ps.calc_integral(Z, "x") # import pdb; pdb.set_trace() # noqa BREAKPOINT # fig, ax = plt.subplots(1, 1) # ps.plot(Z, ordering_of_params_names=("y2", "y"), ax=ax) # plt.show() # import pdb; pdb.set_trace() # noqa BREAKPOINT fig, ax = plt.subplots(1, 1) #ps.plot(Z, z_label="Z", ordering_of_params_name_and_value=(("y3", None), ("y2", None)), ax=ax) ps.plot(integrals, z_label="integrals", ordering_of_params_name_and_value=(("y3", None), ("y2", None)), ax=ax) # ps.plot(integrals, z_label="integrals", ordering_of_params_name_and_value=(("y2", None), ("y", None)), ax=ax) plt.show()

32.477273

129

0.582225

import numpy as np import matplotlib.pyplot as plt from ctsutils.cparameterspace import CParam, CParameterSpace def foo(X, Y, Y2): return (1 - X / 2 + X ** 5 + (Y + Y2 ) ** 3) * np.exp(-X ** 2 - (Y + Y2 ) ** 2) def foo(X, Y, Y2, Y3): return (1 - X / 2 + X ** 5 + (Y + Y2 + Y3) ** 3) * np.exp(-X ** 2 - (Y + Y2 + Y3) ** 2) ps = CParameterSpace([CParam("x", np.linspace(-3, 3, 51), unit="m"), CParam("y", np.linspace(-2, 2, 41)), CParam("y2", np.linspace(-1, 1, 31)), CParam("y3", np.linspace(-1, 1, 10))]) nction(foo, args_param_names=("x", "y", "y2", "y3")) integrals = ps.calc_integral(Z, "x") 1) ps.plot(integrals, z_label="integrals", ordering_of_params_name_and_value=(("y3", None), ("y2", None)), ax=ax) plt.show()

true

f73911a7c4582d4ab6d999c25103c7c89a6d2334

243

py

Python

globalvalues/constants/settingsconstants.py

adriangrepo/qreservoir

20fba1b1fd1a42add223d9e8af2d267665bec493

[ "MIT" ]

2

2019-10-04T13:54:51.000Z

2021-05-21T19:36:15.000Z

globalvalues/constants/settingsconstants.py

adriangrepo/qreservoir

20fba1b1fd1a42add223d9e8af2d267665bec493

[ "MIT" ]

3

2019-11-19T17:06:09.000Z

2020-01-18T20:39:54.000Z

globalvalues/constants/settingsconstants.py

adriangrepo/qreservoir

20fba1b1fd1a42add223d9e8af2d267665bec493

[ "MIT" ]

2

2020-07-02T13:20:48.000Z

2020-11-11T00:18:51.000Z

''' Created on 28 Jun 2015 @author: a ''' class SettingsConstants(object): ''' Constants related to settings dialogs ''' SETTINGS_ITEM_HISTORY_HEADERS = ["Item", "Date", "Action", "Details", "User", "Version", "Build date"]

18.692308

106

0.641975

class SettingsConstants(object): SETTINGS_ITEM_HISTORY_HEADERS = ["Item", "Date", "Action", "Details", "User", "Version", "Build date"]

true

f739129a416d3f39cfab817aa6633728cddb057c

6,298

py

Python

tests/examples/test_examples.py

brucebcampbell/mlflow

9aca8e27198f16ce4fa1e7a0a502554f2f81068b

[ "Apache-2.0" ]

null

tests/examples/test_examples.py

brucebcampbell/mlflow

9aca8e27198f16ce4fa1e7a0a502554f2f81068b

[ "Apache-2.0" ]

null

tests/examples/test_examples.py

brucebcampbell/mlflow

9aca8e27198f16ce4fa1e7a0a502554f2f81068b

[ "Apache-2.0" ]

null

import os import os.path import re import shutil import mlflow from mlflow import cli from mlflow.utils import process from tests.integration.utils import invoke_cli_runner import pytest import json import hashlib EXAMPLES_DIR = "examples" def hash_conda_env(conda_env_path): # use the same hashing logic as `_get_conda_env_name` in mlflow/utils/conda.py return hashlib.sha1(open(conda_env_path).read().encode("utf-8")).hexdigest() def get_conda_envs(): stdout = process.exec_cmd(["conda", "env", "list", "--json"])[1] return [os.path.basename(env) for env in json.loads(stdout)["envs"]] def is_mlflow_conda_env(env_name): return re.search(r"^mlflow-\w{40}$", env_name) is not None def remove_conda_env(env_name): process.exec_cmd(["conda", "remove", "--name", env_name, "--yes", "--all"]) def get_free_disk_space(): # https://stackoverflow.com/a/48929832/6943581 return shutil.disk_usage("/")[-1] / (2 ** 30) def is_conda_yaml(path): return bool(re.search("conda.ya?ml$", path)) def find_conda_yaml(directory): conda_yaml = list(filter(is_conda_yaml, os.listdir(directory)))[0] return os.path.join(directory, conda_yaml) def replace_mlflow_with_dev_version(yml_path): with open(yml_path, "r") as f: old_src = f.read() mlflow_dir = os.path.dirname(mlflow.__path__[0]) new_src = re.sub(r"- mlflow.*\n", "- {}\n".format(mlflow_dir), old_src) with open(yml_path, "w") as f: f.write(new_src) @pytest.fixture(scope="function", autouse=True) def clean_envs_and_cache(): yield if get_free_disk_space() < 7.0: # unit: GiB process.exec_cmd(["./dev/remove-conda-envs.sh"]) @pytest.fixture(scope="function", autouse=True) def report_free_disk_space(capsys): yield with capsys.disabled(): print(" | Free disk space: {:.1f} GiB".format(get_free_disk_space()), end="") @pytest.mark.large @pytest.mark.parametrize( "directory, params", [ ("h2o", []), ("hyperparam", ["-e", "train", "-P", "epochs=1"]), ("hyperparam", ["-e", "random", "-P", "epochs=1"]), ("hyperparam", ["-e", "gpyopt", "-P", "epochs=1"]), ("hyperparam", ["-e", "hyperopt", "-P", "epochs=1"]), ( "lightgbm", ["-P", "learning_rate=0.1", "-P", "colsample_bytree=0.8", "-P", "subsample=0.9"], ), ("statsmodels", ["-P", "inverse_method=qr"]), ("pytorch", ["-P", "epochs=2"]), ("sklearn_logistic_regression", []), ("sklearn_elasticnet_wine", ["-P", "alpha=0.5"]), (os.path.join("sklearn_elasticnet_diabetes", "linux"), []), ("spacy", []), (os.path.join("tensorflow", "tf1"), ["-P", "steps=10"]), ( "xgboost", ["-P", "learning_rate=0.3", "-P", "colsample_bytree=0.8", "-P", "subsample=0.9"], ), ("fastai", ["-P", "lr=0.02", "-P", "epochs=3"]), (os.path.join("pytorch", "MNIST"), ["-P", "max_epochs=1"]), ( os.path.join("pytorch", "BertNewsClassification"), ["-P", "max_epochs=1", "-P", "num_samples=100", "-P", "dataset=20newsgroups"], ), ( os.path.join("pytorch", "AxHyperOptimizationPTL"), ["-P", "max_epochs=10", "-P", "total_trials=1"], ), ( os.path.join("pytorch", "IterativePruning"), ["-P", "max_epochs=1", "-P", "total_trials=1"], ), (os.path.join("pytorch", "CaptumExample"), ["-P", "max_epochs=50"]), ], ) def test_mlflow_run_example(directory, params, tmpdir): example_dir = os.path.join(EXAMPLES_DIR, directory) tmp_example_dir = os.path.join(tmpdir.strpath, directory) shutil.copytree(example_dir, tmp_example_dir) conda_yml_path = find_conda_yaml(tmp_example_dir) replace_mlflow_with_dev_version(conda_yml_path) # remove old conda environments to free disk space envs = list(filter(is_mlflow_conda_env, get_conda_envs())) current_env_name = "mlflow-" + hash_conda_env(conda_yml_path) envs_to_remove = list(filter(lambda e: e != current_env_name, envs)) for env in envs_to_remove: remove_conda_env(env) cli_run_list = [tmp_example_dir] + params invoke_cli_runner(cli.run, cli_run_list) @pytest.mark.large @pytest.mark.parametrize( "directory, command", [ ("docker", ["docker", "build", "-t", "mlflow-docker-example", "-f", "Dockerfile", "."]), ("gluon", ["python", "train.py"]), ("keras", ["python", "train.py"]), ( "lightgbm", [ "python", "train.py", "--learning-rate", "0.2", "--colsample-bytree", "0.8", "--subsample", "0.9", ], ), ("statsmodels", ["python", "train.py", "--inverse-method", "qr"]), ("quickstart", ["python", "mlflow_tracking.py"]), ("remote_store", ["python", "remote_server.py"]), ( "xgboost", [ "python", "train.py", "--learning-rate", "0.2", "--colsample-bytree", "0.8", "--subsample", "0.9", ], ), ("catboost", ["python", "train.py"]), ("prophet", ["python", "train.py"]), ("sklearn_autolog", ["python", "linear_regression.py"]), ("sklearn_autolog", ["python", "pipeline.py"]), ("sklearn_autolog", ["python", "grid_search_cv.py"]), ("pyspark_ml_autologging", ["python", "logistic_regression.py"]), ("pyspark_ml_autologging", ["python", "one_vs_rest.py"]), ("pyspark_ml_autologging", ["python", "pipeline.py"]), ("shap", ["python", "regression.py"]), ("shap", ["python", "binary_classification.py"]), ("shap", ["python", "multiclass_classification.py"]), ("shap", ["python", "explainer_logging.py"]), ("ray_serve", ["python", "train_model.py"]), ("pip_requirements", ["python", "pip_requirements.py"]), ], ) def test_command_example(directory, command): cwd_dir = os.path.join(EXAMPLES_DIR, directory) process.exec_cmd(command, cwd=cwd_dir)

33.322751

96

0.566529

import os import os.path import re import shutil import mlflow from mlflow import cli from mlflow.utils import process from tests.integration.utils import invoke_cli_runner import pytest import json import hashlib EXAMPLES_DIR = "examples" def hash_conda_env(conda_env_path): return hashlib.sha1(open(conda_env_path).read().encode("utf-8")).hexdigest() def get_conda_envs(): stdout = process.exec_cmd(["conda", "env", "list", "--json"])[1] return [os.path.basename(env) for env in json.loads(stdout)["envs"]] def is_mlflow_conda_env(env_name): return re.search(r"^mlflow-\w{40}$", env_name) is not None def remove_conda_env(env_name): process.exec_cmd(["conda", "remove", "--name", env_name, "--yes", "--all"]) def get_free_disk_space(): return shutil.disk_usage("/")[-1] / (2 ** 30) def is_conda_yaml(path): return bool(re.search("conda.ya?ml$", path)) def find_conda_yaml(directory): conda_yaml = list(filter(is_conda_yaml, os.listdir(directory)))[0] return os.path.join(directory, conda_yaml) def replace_mlflow_with_dev_version(yml_path): with open(yml_path, "r") as f: old_src = f.read() mlflow_dir = os.path.dirname(mlflow.__path__[0]) new_src = re.sub(r"- mlflow.*\n", "- {}\n".format(mlflow_dir), old_src) with open(yml_path, "w") as f: f.write(new_src) @pytest.fixture(scope="function", autouse=True) def clean_envs_and_cache(): yield if get_free_disk_space() < 7.0: process.exec_cmd(["./dev/remove-conda-envs.sh"]) @pytest.fixture(scope="function", autouse=True) def report_free_disk_space(capsys): yield with capsys.disabled(): print(" | Free disk space: {:.1f} GiB".format(get_free_disk_space()), end="") @pytest.mark.large @pytest.mark.parametrize( "directory, params", [ ("h2o", []), ("hyperparam", ["-e", "train", "-P", "epochs=1"]), ("hyperparam", ["-e", "random", "-P", "epochs=1"]), ("hyperparam", ["-e", "gpyopt", "-P", "epochs=1"]), ("hyperparam", ["-e", "hyperopt", "-P", "epochs=1"]), ( "lightgbm", ["-P", "learning_rate=0.1", "-P", "colsample_bytree=0.8", "-P", "subsample=0.9"], ), ("statsmodels", ["-P", "inverse_method=qr"]), ("pytorch", ["-P", "epochs=2"]), ("sklearn_logistic_regression", []), ("sklearn_elasticnet_wine", ["-P", "alpha=0.5"]), (os.path.join("sklearn_elasticnet_diabetes", "linux"), []), ("spacy", []), (os.path.join("tensorflow", "tf1"), ["-P", "steps=10"]), ( "xgboost", ["-P", "learning_rate=0.3", "-P", "colsample_bytree=0.8", "-P", "subsample=0.9"], ), ("fastai", ["-P", "lr=0.02", "-P", "epochs=3"]), (os.path.join("pytorch", "MNIST"), ["-P", "max_epochs=1"]), ( os.path.join("pytorch", "BertNewsClassification"), ["-P", "max_epochs=1", "-P", "num_samples=100", "-P", "dataset=20newsgroups"], ), ( os.path.join("pytorch", "AxHyperOptimizationPTL"), ["-P", "max_epochs=10", "-P", "total_trials=1"], ), ( os.path.join("pytorch", "IterativePruning"), ["-P", "max_epochs=1", "-P", "total_trials=1"], ), (os.path.join("pytorch", "CaptumExample"), ["-P", "max_epochs=50"]), ], ) def test_mlflow_run_example(directory, params, tmpdir): example_dir = os.path.join(EXAMPLES_DIR, directory) tmp_example_dir = os.path.join(tmpdir.strpath, directory) shutil.copytree(example_dir, tmp_example_dir) conda_yml_path = find_conda_yaml(tmp_example_dir) replace_mlflow_with_dev_version(conda_yml_path) envs = list(filter(is_mlflow_conda_env, get_conda_envs())) current_env_name = "mlflow-" + hash_conda_env(conda_yml_path) envs_to_remove = list(filter(lambda e: e != current_env_name, envs)) for env in envs_to_remove: remove_conda_env(env) cli_run_list = [tmp_example_dir] + params invoke_cli_runner(cli.run, cli_run_list) @pytest.mark.large @pytest.mark.parametrize( "directory, command", [ ("docker", ["docker", "build", "-t", "mlflow-docker-example", "-f", "Dockerfile", "."]), ("gluon", ["python", "train.py"]), ("keras", ["python", "train.py"]), ( "lightgbm", [ "python", "train.py", "--learning-rate", "0.2", "--colsample-bytree", "0.8", "--subsample", "0.9", ], ), ("statsmodels", ["python", "train.py", "--inverse-method", "qr"]), ("quickstart", ["python", "mlflow_tracking.py"]), ("remote_store", ["python", "remote_server.py"]), ( "xgboost", [ "python", "train.py", "--learning-rate", "0.2", "--colsample-bytree", "0.8", "--subsample", "0.9", ], ), ("catboost", ["python", "train.py"]), ("prophet", ["python", "train.py"]), ("sklearn_autolog", ["python", "linear_regression.py"]), ("sklearn_autolog", ["python", "pipeline.py"]), ("sklearn_autolog", ["python", "grid_search_cv.py"]), ("pyspark_ml_autologging", ["python", "logistic_regression.py"]), ("pyspark_ml_autologging", ["python", "one_vs_rest.py"]), ("pyspark_ml_autologging", ["python", "pipeline.py"]), ("shap", ["python", "regression.py"]), ("shap", ["python", "binary_classification.py"]), ("shap", ["python", "multiclass_classification.py"]), ("shap", ["python", "explainer_logging.py"]), ("ray_serve", ["python", "train_model.py"]), ("pip_requirements", ["python", "pip_requirements.py"]), ], ) def test_command_example(directory, command): cwd_dir = os.path.join(EXAMPLES_DIR, directory) process.exec_cmd(command, cwd=cwd_dir)

true

f739129edf4dad67c2248bd06ec3d471d9ba24b7

1,126

py

Python

almost-triangles/almost-triangles.py

cdstanford/curiosities

511e55b9dbf2b49db4593be92a0e4fce07888eaf

[ "MIT" ]

1

2022-01-18T06:02:01.000Z

almost-triangles/almost-triangles.py

cdstanford/curiosities

511e55b9dbf2b49db4593be92a0e4fce07888eaf

[ "MIT" ]

null

almost-triangles/almost-triangles.py

cdstanford/curiosities

511e55b9dbf2b49db4593be92a0e4fce07888eaf

[ "MIT" ]

null

""" A triangle is an "almost right triangle" if one of its angles differs from 90 degrees by at most 15 degrees. A triangle is an "almost isosceles triangle" if two of its angles differ from each other by at most 15 degrees. Prove that all acute triangles are either almost right or almost isosceles. Note: if "at most 15" is replaced by "less than 15" in the problem statement (change "<= 15" to "< 15" everywhere below), the formula becomes satisfiable and we get the following counterexample: a triangle with angles 45, 60, and 75. """ import z3 def triangle(x, y, z): return z3.And(x > 0, y > 0, z > 0, x + y + z == 180) def acute(x, y, z): return z3.And(x < 90, y < 90, z < 90) def abs(x): return z3.If(x > 0, x, -x) def almost_right(x, y, z): return z3.Or(abs(x - 90) <= 15, abs(y - 90) <= 15, abs(z - 90) <= 15) def almost_isosceles(x, y, z): return z3.Or(abs(x - y) <= 15, abs(x - z) <= 15, abs(y - z) <= 15) x = z3.Real("x") y = z3.Real("y") z = z3.Real("z") z3.solve( triangle(x, y, z), acute(x, y, z), z3.Not(almost_right(x, y, z)), z3.Not(almost_isosceles(x, y, z)), )

28.15

79

0.626998

import z3 def triangle(x, y, z): return z3.And(x > 0, y > 0, z > 0, x + y + z == 180) def acute(x, y, z): return z3.And(x < 90, y < 90, z < 90) def abs(x): return z3.If(x > 0, x, -x) def almost_right(x, y, z): return z3.Or(abs(x - 90) <= 15, abs(y - 90) <= 15, abs(z - 90) <= 15) def almost_isosceles(x, y, z): return z3.Or(abs(x - y) <= 15, abs(x - z) <= 15, abs(y - z) <= 15) x = z3.Real("x") y = z3.Real("y") z = z3.Real("z") z3.solve( triangle(x, y, z), acute(x, y, z), z3.Not(almost_right(x, y, z)), z3.Not(almost_isosceles(x, y, z)), )

true

f739132662219264ff68cf9039a96b10b8ef6495

4,179

py

Python

lib/streamlit/util.py

sdrees/streamlit

d02c3fca9114c6b550785cca2fbe05ec37295f2b

[ "Apache-2.0" ]

1

2019-11-01T08:37:00.000Z

lib/streamlit/util.py

sdrees/streamlit

d02c3fca9114c6b550785cca2fbe05ec37295f2b

[ "Apache-2.0" ]

null

lib/streamlit/util.py

sdrees/streamlit

d02c3fca9114c6b550785cca2fbe05ec37295f2b

[ "Apache-2.0" ]

null

# Copyright 2018-2022 Streamlit Inc. # # 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. """A bunch of useful utilities.""" import functools import os import subprocess from typing import Any, Dict, List, TypeVar from typing_extensions import Final from streamlit import env_util # URL of Streamlit's help page. HELP_DOC: Final = "https://docs.streamlit.io/" def memoize(func): """Decorator to memoize the result of a no-args func.""" result = [] # type: List[Any] @functools.wraps(func) def wrapped_func(): if not result: result.append(func()) return result[0] return wrapped_func def open_browser(url): """Open a web browser pointing to a given URL. We use this function instead of Python's `webbrowser` module because this way we can capture stdout/stderr to avoid polluting the terminal with the browser's messages. For example, Chrome always prints things like "Created new window in existing browser session", and those get on the user's way. url : str The URL. Must include the protocol. """ # Treat Windows separately because: # 1. /dev/null doesn't exist. # 2. subprocess.Popen(['start', url]) doesn't actually pop up the # browser even though 'start url' works from the command prompt. # Fun! # Also, use webbrowser if we are on Linux and xdg-open is not installed. # # We don't use the webbrowser module on Linux and Mac because some browsers # (ahem... Chrome) always print "Opening in existing browser session" to # the terminal, which is spammy and annoying. So instead we start the # browser ourselves and send all its output to /dev/null. if env_util.IS_WINDOWS: _open_browser_with_webbrowser(url) return if env_util.IS_LINUX_OR_BSD: if env_util.is_executable_in_path("xdg-open"): _open_browser_with_command("xdg-open", url) return _open_browser_with_webbrowser(url) return if env_util.IS_DARWIN: _open_browser_with_command("open", url) return import platform raise Error('Cannot open browser in platform "%s"' % platform.system()) def _open_browser_with_webbrowser(url): import webbrowser webbrowser.open(url) def _open_browser_with_command(command, url): cmd_line = [command, url] with open(os.devnull, "w") as devnull: subprocess.Popen(cmd_line, stdout=devnull, stderr=subprocess.STDOUT) def _maybe_tuple_to_list(item: Any) -> Any: """Convert a tuple to a list. Leave as is if it's not a tuple.""" if isinstance(item, tuple): return list(item) return item def repr_(cls) -> str: classname = cls.__class__.__name__ args = ", ".join([f"{k}={repr(v)}" for (k, v) in cls.__dict__.items()]) return f"{classname}({args})" def index_(iterable, x) -> int: """Return zero-based index of the first item whose value is equal to x. Raises a ValueError if there is no such item. We need a custom implementation instead of the built-in list .index() to be compatible with NumPy array and Pandas Series. Parameters ---------- iterable : list, tuple, numpy.ndarray, pandas.Series Returns ------- int """ for i, value in enumerate(iterable): if x == value: return i raise ValueError("{} is not in iterable".format(str(x))) _Value = TypeVar("_Value") def lower_clean_dict_keys(dict: Dict[str, _Value]) -> Dict[str, _Value]: return {k.lower().strip(): v for k, v in dict.items()} # TODO: Move this into errors.py? Replace with StreamlitAPIException? class Error(Exception): pass

29.223776

79

0.682699

import functools import os import subprocess from typing import Any, Dict, List, TypeVar from typing_extensions import Final from streamlit import env_util HELP_DOC: Final = "https://docs.streamlit.io/" def memoize(func): result = [] # type: List[Any] @functools.wraps(func) def wrapped_func(): if not result: result.append(func()) return result[0] return wrapped_func def open_browser(url): # Treat Windows separately because: # 1. /dev/null doesn't exist. # browser even though 'start url' works from the command prompt. # Fun! # Also, use webbrowser if we are on Linux and xdg-open is not installed. # # We don't use the webbrowser module on Linux and Mac because some browsers if env_util.IS_WINDOWS: _open_browser_with_webbrowser(url) return if env_util.IS_LINUX_OR_BSD: if env_util.is_executable_in_path("xdg-open"): _open_browser_with_command("xdg-open", url) return _open_browser_with_webbrowser(url) return if env_util.IS_DARWIN: _open_browser_with_command("open", url) return import platform raise Error('Cannot open browser in platform "%s"' % platform.system()) def _open_browser_with_webbrowser(url): import webbrowser webbrowser.open(url) def _open_browser_with_command(command, url): cmd_line = [command, url] with open(os.devnull, "w") as devnull: subprocess.Popen(cmd_line, stdout=devnull, stderr=subprocess.STDOUT) def _maybe_tuple_to_list(item: Any) -> Any: if isinstance(item, tuple): return list(item) return item def repr_(cls) -> str: classname = cls.__class__.__name__ args = ", ".join([f"{k}={repr(v)}" for (k, v) in cls.__dict__.items()]) return f"{classname}({args})" def index_(iterable, x) -> int: for i, value in enumerate(iterable): if x == value: return i raise ValueError("{} is not in iterable".format(str(x))) _Value = TypeVar("_Value") def lower_clean_dict_keys(dict: Dict[str, _Value]) -> Dict[str, _Value]: return {k.lower().strip(): v for k, v in dict.items()} class Error(Exception): pass

true

f7391359e8c5b762abefb4eac0e7c17892575845

250

py

Python

src/atcoder/abc212/b/sol_0.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

1

2021-07-11T03:20:10.000Z

src/atcoder/abc212/b/sol_0.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

39

2021-07-10T05:21:09.000Z

2021-12-15T06:10:12.000Z

src/atcoder/abc212/b/sol_0.py

kagemeka/competitive-programming

c70fe481bcd518f507b885fc9234691d8ce63171

[ "MIT" ]

null

def main(): s = input() if len(set(s)) == 1: print('Weak') return *s, = map(int, list(s)) for i in range(3): if ( s[i + 1] != (s[i] + 1) % 10 ): print('Strong') return print('Weak') main()

12.5

25

0.408

def main(): s = input() if len(set(s)) == 1: print('Weak') return *s, = map(int, list(s)) for i in range(3): if ( s[i + 1] != (s[i] + 1) % 10 ): print('Strong') return print('Weak') main()

true