xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

85e7812e3adb9a9392fe81b3aef0d8fe535aff0f

135

py

Python

pics/gallery/admin.py

i-k-i/pics

ceaab81aa3110de4686b632a531297c4d7cdb691

[ "MIT" ]

null

pics/gallery/admin.py

i-k-i/pics

ceaab81aa3110de4686b632a531297c4d7cdb691

[ "MIT" ]

10

2020-06-06T00:28:20.000Z

2022-02-10T09:01:40.000Z

pics/gallery/admin.py

i-k-i/pics

ceaab81aa3110de4686b632a531297c4d7cdb691

[ "MIT" ]

null

from django.contrib import admin from .models import Picture, Note admin.site.register((Picture, Note)) # Register your models here.

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c80f106209903bc0495b5f4c58f5abcbad6e1004

9,916

py

Python

ppipe/ee_ls.py

rfernand387/Planet-GEE-Pipeline-CLI

18da56148f94fee9b48cefe64b8ab91ae173cddd

[ "Apache-2.0" ]

42

2017-05-05T21:22:51.000Z

2022-03-08T09:54:17.000Z

ppipe/ee_ls.py

rfernand387/Planet-GEE-Pipeline-CLI

18da56148f94fee9b48cefe64b8ab91ae173cddd

[ "Apache-2.0" ]

18

2017-06-20T20:15:49.000Z

2021-04-25T15:13:44.000Z

ppipe/ee_ls.py

rfernand387/Planet-GEE-Pipeline-CLI

18da56148f94fee9b48cefe64b8ab91ae173cddd

[ "Apache-2.0" ]

12

2017-06-20T15:07:20.000Z

2021-07-07T16:57:21.000Z

from __future__ import print_function __copyright__ = """ Copyright 2019 Samapriya Roy 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. """ __license__ = "Apache 2.0" import ee import subprocess import csv import os ##initialize earth engine ee.Initialize() suffixes = ["B", "KB", "MB", "GB", "TB", "PB"] def humansize(nbytes): i = 0 while nbytes >= 1024 and i < len(suffixes) - 1: nbytes /= 1024.0 i += 1 f = ("%.2f" % nbytes).rstrip("0").rstrip(".") return "%s %s" % (f, suffixes[i]) def object_sz(object): sz = humansize(object.get("system:asset_size").getInfo()) return sz def collect_sz(object): sz = humansize( object.reduceColumns(ee.Reducer.sum(), ["system:asset_size"]) .get("sum") .getInfo() ) return sz def lst(location, typ, items=None, output=None): if items is None and typ == "print": assets_list = ee.data.getList(params={"id": location}) for things in assets_list: header = things["type"] tail = things["id"] try: if header == "ImageCollection": collc = ee.ImageCollection(tail) ast = collc.size().getInfo() sz = collect_sz(collc) print( "Image Collection: " + str(tail) + " has " + str(ast) + " images a total of " + str(sz) ) elif header == "Image": collc = ee.Image(tail) sz = object_sz(collc) print("Image: " + str(tail) + " is " + str(sz)) elif header == "Table": collc = ee.FeatureCollection(tail) sz = object_sz(collc) print("Table: " + str(tail) + " is " + str(sz)) elif ( header == "Folder" ): ##Folders are not added to the list but are print assets_list = ee.data.getList(params={"id": location}) print("Folder: " + str(tail) + " has " + str(len(assets_list))) except Exception as e: print(e) elif items > 0 and typ == "print": assets_list = ee.data.getList(params={"id": location}) if int(len(assets_list)) > int(items): subset = assets_list[: int(items)] for things in subset: header = things["type"] tail = things["id"] try: if header == "ImageCollection": collc = ee.ImageCollection(tail) ast = collc.size().getInfo() sz = collect_sz(collc) print( "Image Collection: " + str(tail) + " has " + str(ast) + " images a total of " + str(sz) ) elif header == "Image": collc = ee.Image(tail) sz = object_sz(collc) print("Image: " + str(tail) + " is " + str(sz)) elif header == "Table": collc = ee.FeatureCollection(tail) sz = object_sz(collc) print("Table: " + str(tail) + " is " + str(sz)) elif ( header == "Folder" ): ##Folders are not added to the list but are print assets_list = ee.data.getList(params={"id": location}) print("Folder: " + str(tail) + " has " + str(len(assets_list))) except Exception as e: print(e) elif items is None and typ == "report": with open(output, "wb") as csvfile: writer = csv.DictWriter( csvfile, fieldnames=["type", "path", "No of Assets", "size"], delimiter=",", ) writer.writeheader() assets_list = ee.data.getList(params={"id": location}) for things in assets_list: header = things["type"] tail = things["id"] try: if header == "ImageCollection": collc = ee.ImageCollection(tail) ast = collc.size().getInfo() sz = collect_sz(collc) print( "Image Collection: " + str(tail) + " has " + str(ast) + " images a total of " + str(sz) ) with open(output, "a") as csvfile: writer = csv.writer(csvfile, delimiter=",", lineterminator="\n") writer.writerow([header, tail, ast, str(sz)]) csvfile.close() elif header == "Image": collc = ee.Image(tail) sz = object_sz(collc) print("Image: " + str(tail) + " is " + str(sz)) with open(output, "a") as csvfile: writer = csv.writer(csvfile, delimiter=",", lineterminator="\n") writer.writerow([header, tail, ast, str(sz)]) csvfile.close() elif header == "Table": collc = ee.FeatureCollection(tail) sz = object_sz(collc) print("Table: " + str(tail) + " is " + str(sz)) with open(output, "a") as csvfile: writer = csv.writer(csvfile, delimiter=",", lineterminator="\n") writer.writerow([header, tail, ast, str(sz)]) csvfile.close() elif ( header == "Folder" ): ##Folders are not added to the list but are print assets_list = ee.data.getList(params={"id": location}) print("Folder: " + str(tail) + " has " + str(len(assets_list))) except Exception as e: print(e) elif items > 0 and typ == "report": with open(output, "wb") as csvfile: writer = csv.DictWriter( csvfile, fieldnames=["type", "path", "No of Assets", "size"], delimiter=",", ) writer.writeheader() assets_list = ee.data.getList(params={"id": location}) if int(len(assets_list)) > int(items): subset = assets_list[: int(items)] for things in subset: header = things["type"] tail = things["id"] try: if header == "ImageCollection": collc = ee.ImageCollection(tail) ast = collc.size().getInfo() sz = collect_sz(collc) print( "Image Collection: " + str(tail) + " has " + str(ast) + " images a total of " + str(sz) ) with open(output, "a") as csvfile: writer = csv.writer( csvfile, delimiter=",", lineterminator="\n" ) writer.writerow([header, tail, ast, str(sz)]) csvfile.close() elif header == "Image": collc = ee.Image(tail) sz = object_sz(collc) print("Image: " + str(tail) + " is " + str(sz)) with open(output, "a") as csvfile: writer = csv.writer( csvfile, delimiter=",", lineterminator="\n" ) writer.writerow([header, tail, 1, str(sz)]) csvfile.close() elif header == "Table": collc = ee.FeatureCollection(tail) sz = object_sz(collc) print("Table: " + str(tail) + " is " + str(sz)) with open(output, "a") as csvfile: writer = csv.writer( csvfile, delimiter=",", lineterminator="\n" ) writer.writerow([header, tail, 1, str(sz)]) csvfile.close() elif ( header == "Folder" ): ##Folders are not added to the list but are print assets_list = ee.data.getList(params={"id": location}) print("Folder: " + str(tail) + " has " + str(len(assets_list))) except Exception as e: print(e) # lst(location="users/samapriya/Belem", typ="report",items=0,output=r"C:\planet_demo\rep.csv")

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py

Python

Codewars/8kyu/will-there-be-enough-space/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

7

2017-09-20T16:40:39.000Z

2021-08-31T18:15:08.000Z

Codewars/8kyu/will-there-be-enough-space/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

Codewars/8kyu/will-there-be-enough-space/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

# Python - 3.6.0 test.describe('Example Tests') test.assert_equals(enough(10, 5, 5), 0) test.assert_equals(enough(100, 60, 50), 10)

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6

c849e2a9387f4e5ff4905e8018485c8c44780b6b

102

py

Python

stattools/ensemble/__init__.py

artemmavrin/SLTools

04525b5d6777be3ccdc6ad44e4cbfe24a8875933

[ "MIT" ]

2

2018-07-10T22:16:23.000Z

2019-10-08T00:12:44.000Z

stattools/ensemble/__init__.py

artemmavrin/SLTools

04525b5d6777be3ccdc6ad44e4cbfe24a8875933

[ "MIT" ]

null

stattools/ensemble/__init__.py

artemmavrin/SLTools

04525b5d6777be3ccdc6ad44e4cbfe24a8875933

[ "MIT" ]

4

2019-05-17T23:06:07.000Z

2021-03-22T14:04:24.000Z

"""Ensemble methods.""" from .bagging import BaggingClassifier from .bagging import BaggingRegressor

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c0933194ec466b9778437f767913ba2b23f51a4d

591

py

Python

ABC/079/c.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

ABC/079/c.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

ABC/079/c.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

def main(): # input A, B, C, D = list(map(int, input())) # compute # output if A+B+C+D == 7: print(f'{A}+{B}+{C}+{D}=7') elif A-B+C+D == 7: print(f'{A}-{B}+{C}+{D}=7') elif A+B-C+D == 7: print(f'{A}+{B}-{C}+{D}=7') elif A+B+C-D == 7: print(f'{A}+{B}+{C}-{D}=7') elif A-B-C+D == 7: print(f'{A}-{B}-{C}+{D}=7') elif A+B-C-D == 7: print(f'{A}+{B}-{C}-{D}=7') elif A-B+C-D == 7: print(f'{A}-{B}+{C}-{D}=7') else: print(f'{A}-{B}-{C}-{D}=7') if __name__ == '__main__': main()

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9b1181f1774b1ed6beb8d20cf4976642ba407b00

134

py

Python

faculty_distributed/__init__.py

facultyai/faculty-distributed

d5b770da603e3d5fe13c1b0c33e86dd9af2d6b8d

[ "Apache-2.0" ]

5

2019-05-15T12:45:25.000Z

2020-10-11T15:21:25.000Z

faculty_distributed/__init__.py

facultyai/faculty-distributed

d5b770da603e3d5fe13c1b0c33e86dd9af2d6b8d

[ "Apache-2.0" ]

7

2019-05-10T11:25:29.000Z

2020-02-12T18:29:24.000Z

faculty_distributed/__init__.py

facultyai/faculty-distributed

d5b770da603e3d5fe13c1b0c33e86dd9af2d6b8d

[ "Apache-2.0" ]

1

2021-04-04T14:29:06.000Z

from .manager import FacultyJobExecutor from .utils import job_name_to_job_id __all__ = ["FacultyJobExecutor", "job_name_to_job_id"]

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7b22a2b8cb328f6bd47c419f4b4b4c4a2dcbcccd

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py

Python

tests/plugins/mockserver/test_tracing_enabled.py

itrofimow/yandex-taxi-testsuite

bea758af35ae19db929f4b2b99d2a2917ff4c147

[ "MIT" ]

null

tests/plugins/mockserver/test_tracing_enabled.py

itrofimow/yandex-taxi-testsuite

bea758af35ae19db929f4b2b99d2a2917ff4c147

[ "MIT" ]

null

tests/plugins/mockserver/test_tracing_enabled.py

itrofimow/yandex-taxi-testsuite

bea758af35ae19db929f4b2b99d2a2917ff4c147

[ "MIT" ]

null

import aiohttp.web import pytest from testsuite.mockserver import server # pylint: disable=protected-access # pylint: disable=invalid-name async def test_mockserver_responds_with_handler_to_current_test( mockserver, create_service_client, ): @mockserver.handler('/arbitrary/path') def _handler(request): return aiohttp.web.Response(text='arbitrary text', status=200) client = create_service_client( mockserver.base_url, headers={mockserver.trace_id_header: mockserver.trace_id}, ) response = await client.post('arbitrary/path') assert response.status_code == 200 assert response.text == 'arbitrary text' async def test_mockserver_responds_with_json_handler_to_current_test( mockserver, create_service_client, ): @mockserver.json_handler('/arbitrary/path') def _json_handler(request): return {'arbitrary_key': True} client = create_service_client( mockserver.base_url, headers={mockserver.trace_id_header: mockserver.trace_id}, ) response = await client.post('arbitrary/path') assert response.status_code == 200 assert response.json() == {'arbitrary_key': True} async def test_mockserver_skips_handler_and_responds_500_to_other_test( mockserver, create_service_client, ): @mockserver.handler('/arbitrary/path') def _handler(request): return aiohttp.web.Response(text='arbitrary text', status=200) client = create_service_client( mockserver.base_url, headers={mockserver.trace_id_header: server.generate_trace_id()}, ) response = await client.post('arbitrary/path') assert response.status_code == 500 assert response.text == server.REQUEST_FROM_ANOTHER_TEST_ERROR async def test_mockserver_skips_json_handler_and_responds_500_to_other_test( mockserver, create_service_client, ): @mockserver.json_handler('/arbitrary/path') def _json_handler(request): return {'arbitrary_key': True} client = create_service_client( mockserver.base_url, headers={mockserver.trace_id_header: server.generate_trace_id()}, ) response = await client.post('arbitrary/path') assert response.status_code == 500 assert response.text == server.REQUEST_FROM_ANOTHER_TEST_ERROR @pytest.mark.parametrize( 'http_headers', [ {}, # no trace_id in http headers {server.DEFAULT_TRACE_ID_HEADER: ''}, {server.DEFAULT_TRACE_ID_HEADER: 'id_without_testsuite-_prefix'}, ], ) async def test_mockserver_responds_500_on_unhandled_request_from_other_sources( mockserver, http_headers, create_service_client, ): client = create_service_client(mockserver.base_url, headers=http_headers) response = await client.post('arbitrary/path') assert response.status_code == 500

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py

Python

examples/docs_snippets_crag/docs_snippets_crag/concepts/solids_pipelines/dynamic_pipeline/sample/program.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

4,606

2018-06-21T17:45:20.000Z

2022-03-31T23:39:42.000Z

examples/docs_snippets_crag/docs_snippets_crag/concepts/solids_pipelines/dynamic_pipeline/sample/program.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

6,221

2018-06-12T04:36:01.000Z

2022-03-31T21:43:05.000Z

examples/docs_snippets_crag/docs_snippets_crag/concepts/solids_pipelines/dynamic_pipeline/sample/program.py

dbatten5/dagster

d76e50295054ffe5a72f9b292ef57febae499528

[ "Apache-2.0" ]

619

2018-08-22T22:43:09.000Z

2022-03-31T22:48:06.000Z

def calculate(): return "yes"

11.333333

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2

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0

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6

9e5957c6a467306f2065db95b6865cbdda4a16d5

681

py

Python

app/controllers/index_controller.py

dhruvshah1996/Project3

d87ad37f6cf2de0d3402c71d21b25258946aad69

[ "MIT" ]

null

app/controllers/index_controller.py

dhruvshah1996/Project3

d87ad37f6cf2de0d3402c71d21b25258946aad69

[ "MIT" ]

null

app/controllers/index_controller.py

dhruvshah1996/Project3

d87ad37f6cf2de0d3402c71d21b25258946aad69

[ "MIT" ]

null

from app.controllers.controller import ControllerBase from flask import render_template class IndexController(ControllerBase): @staticmethod def get(): return render_template('index.html') class pylintController(ControllerBase): @staticmethod def get(): return render_template('pylint.html') class AAAtestingController(ControllerBase): @staticmethod def get(): return render_template('AAA.html') class OOPController(ControllerBase): @staticmethod def get(): return render_template('OOPs.html') class SOLIDController(ControllerBase): @staticmethod def get(): return render_template('SOLID.html')

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1

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6

9e6df1b085fd8146d6edae666e6954eff8adaaaf

729

py

Python

Fastir_Collector/hooks/hook-cachedns.py

Unam3dd/Train-2018-2020

afb6ae70fe338cbe55a21b74648d91996b818fa2

[ "MIT" ]

4

2021-04-23T15:39:17.000Z

2021-12-27T22:53:24.000Z

Fastir_Collector/hooks/hook-cachedns.py

Unam3dd/Train-2018-2020

afb6ae70fe338cbe55a21b74648d91996b818fa2

[ "MIT" ]

null

Fastir_Collector/hooks/hook-cachedns.py

Unam3dd/Train-2018-2020

afb6ae70fe338cbe55a21b74648d91996b818fa2

[ "MIT" ]

2

2021-04-19T08:28:54.000Z

2022-01-19T13:23:29.000Z

import sys if sys.maxsize > 2 ** 32: datas = [("./../_x64/boost_python-vc120-gd-1_55.dll", ''), ("./../_x64/boost_python-vc120-gd-1_55.lib", ''), ("./../_x64/boost_python-vc120-mt-gd-1_55.lib", ''), ("./../_x64/msvcp120d.dll", ''), ("./../_x64/msvcr120d.dll", ''), ("./../memory/dnscache_x64.pyd", ''), ] else: datas = [("./../_x86/boost_python-vc120-gd-1_55.dll", ''), ("./../_x86/boost_python-vc120-gd-1_55.lib", ''), ("./../_x86/boost_python-vc120-mt-gd-1_55.lib", ''), ("./../_x86/msvcp120d.dll", ''), ("./../_x86/msvcr120d.dll", ''), ("./../memory/dnscache_x64.pyd", ''), ]

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9eb99be89f8c3fc8b0f17ca4c26f85a61803c227

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py

Python

venv/lib/python3.8/site-packages/rope/refactor/topackage.py

GiulianaPola/select_repeats

17a0d053d4f874e42cf654dd142168c2ec8fbd11

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/rope/refactor/topackage.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/rope/refactor/topackage.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/d8/83/47/d86c3973cf9be39d7cc2a59a4cf385ca8e19160ff32f3839d0e0cb11a9

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1

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6

7b5e3e5f6e35636614d06c88e79635190dcbf6cd

62

py

Python

tensor2struct/datasets/__init__.py

DreamerDeo/tensor2struct-public

48e41b7faf041189c17dff8445d9e2b4d709e753

[ "MIT" ]

null

tensor2struct/datasets/__init__.py

DreamerDeo/tensor2struct-public

48e41b7faf041189c17dff8445d9e2b4d709e753

[ "MIT" ]

null

tensor2struct/datasets/__init__.py

DreamerDeo/tensor2struct-public

48e41b7faf041189c17dff8445d9e2b4d709e753

[ "MIT" ]

null

from . import overnight from . import spider from . import ssp

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7babb10f1c816ae63ebada6885d6192577b9fe17

25

py

Python

__init__.py

JeffHeard/terrapyn

8d883b6c8a729e972c12d6f0c3b2a34ea86dcd88

[ "Apache-2.0" ]

1

2016-10-27T14:58:04.000Z

__init__.py

JeffHeard/terrapyn

8d883b6c8a729e972c12d6f0c3b2a34ea86dcd88

[ "Apache-2.0" ]

null

__init__.py

JeffHeard/terrapyn

8d883b6c8a729e972c12d6f0c3b2a34ea86dcd88

[ "Apache-2.0" ]

null

import ows import geocms

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6

c889f8dd9250f3812967c26638d3f001e902c3ad

41

py

Python

taf/testlib/linux/maa/__init__.py

stepanandr/taf

75cb85861f8e9703bab7dc6195f3926b8394e3d0

[ "Apache-2.0" ]

10

2016-12-16T00:05:58.000Z

2018-10-30T17:48:25.000Z

taf/testlib/linux/maa/__init__.py

stepanandr/taf

75cb85861f8e9703bab7dc6195f3926b8394e3d0

[ "Apache-2.0" ]

40

2017-01-04T23:07:05.000Z

2018-04-16T19:52:02.000Z

taf/testlib/linux/maa/__init__.py

stepanandr/taf

75cb85861f8e9703bab7dc6195f3926b8394e3d0

[ "Apache-2.0" ]

23

2016-12-30T05:03:53.000Z

2020-04-01T08:40:24.000Z

from .maa import MatchActionAcceleration

20.5

40

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c88b5c5af758bae12b7c4e100640ba8f5a404572

132

py

Python

ChatbotCreator/__init__.py

SamambaMan/chatbot-creator

9a266d5b6f2100540aff64d72cd785b6069ad122

[ "MIT" ]

2

2021-04-20T23:12:35.000Z

2021-04-23T16:05:39.000Z

ChatbotCreator/__init__.py

SamambaMan/chatbot-creator

9a266d5b6f2100540aff64d72cd785b6069ad122

[ "MIT" ]

null

ChatbotCreator/__init__.py

SamambaMan/chatbot-creator

9a266d5b6f2100540aff64d72cd785b6069ad122

[ "MIT" ]

1

2021-04-21T00:25:15.000Z

from ChatbotCreator.dbot import CreateDiscordBot from ChatbotCreator.run import Run from ChatbotCreator.cc import ChatbotCreator

33

49

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132

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6

c8c4bda63f77889233fa80787aa027cc09f9897e

57

py

Python

python/ga4gh/wes/__init__.py

junjun-zhang/workflow-execution-service-schemas

120cd3b265e531855c4ae48046bf596a3e83329f

[ "Apache-2.0" ]

null

python/ga4gh/wes/__init__.py

junjun-zhang/workflow-execution-service-schemas

120cd3b265e531855c4ae48046bf596a3e83329f

[ "Apache-2.0" ]

null

python/ga4gh/wes/__init__.py

junjun-zhang/workflow-execution-service-schemas

120cd3b265e531855c4ae48046bf596a3e83329f

[ "Apache-2.0" ]

1

2018-05-30T20:53:36.000Z

import client import server assert server assert client

9.5

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6

c8f0a3a5f223c29f35ad538b05c7a54e802177c7

45

py

Python

sqljob/__init__.py

kota7/sqljob

32c88f637ae25ace23bdb6a9be09d90d878f8ccb

[ "MIT" ]

null

sqljob/__init__.py

kota7/sqljob

32c88f637ae25ace23bdb6a9be09d90d878f8ccb

[ "MIT" ]

null

sqljob/__init__.py

kota7/sqljob

32c88f637ae25ace23bdb6a9be09d90d878f8ccb

[ "MIT" ]

null

from .sqljob import sqljob, SqlJob, Connector

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1

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6

c8f76a05fe0a774394c6f6e98dca9fc237e5b68d

23

py

Python

HSVideo/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

HSVideo/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

HSVideo/__init__.py

jwbrooks0/johnspythonlibrary2

10ca519276d8c32da0fbd41a597f75c0c98a8736

[ "MIT" ]

null

from ._hsvideo import *

23

0.782609

3

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null

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1

0

6

c8fd3bf5ad7becd53168fbf06ca72ade6da3ec43

1,599

py

Python

students/k3342/laboratory_works/Demin_Danil/laboratory_work_2-3/django-vue-auth/django_project/django_app/migrations/0003_auto_20200814_2201.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

10

2020-03-20T09:06:12.000Z

2021-07-27T13:06:02.000Z

students/k3342/laboratory_works/Demin_Danil/laboratory_work_2-3/django-vue-auth/django_project/django_app/migrations/0003_auto_20200814_2201.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

134

2020-03-23T09:47:48.000Z

2022-03-12T01:05:19.000Z

students/k3342/laboratory_works/Demin_Danil/laboratory_work_2-3/django-vue-auth/django_project/django_app/migrations/0003_auto_20200814_2201.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

71

2020-03-20T12:45:56.000Z

2021-10-31T19:22:25.000Z

# Generated by Django 3.0.8 on 2020-08-14 22:01 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('django_app', '0002_auto_20200705_1507'), ] operations = [ migrations.AddField( model_name='breed', name='avg_productivity', field=models.IntegerField(default=0), ), migrations.AddField( model_name='breed', name='avg_weight', field=models.IntegerField(default=0), ), migrations.AddField( model_name='building', name='number', field=models.IntegerField(default=0), ), migrations.AddField( model_name='cage', name='number', field=models.IntegerField(default=0), ), migrations.AddField( model_name='cage', name='row', field=models.IntegerField(default=0), ), migrations.AddField( model_name='chicken', name='age', field=models.IntegerField(default=0), ), migrations.AddField( model_name='chicken', name='productivity', field=models.IntegerField(default=0), ), migrations.AddField( model_name='chicken', name='weight', field=models.IntegerField(default=0), ), migrations.AddField( model_name='worker', name='salary', field=models.IntegerField(default=0), ), ]

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1

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1

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null

0

6

cdaffca0ec8cc082ee712c4000dfdc3fb6bcdb05

19

py

Python

lltk/corpus/tcp/__init__.py

literarylab/lltk

0e516d7fa0978c1a3bd2cb7636f0089772e515ec

[ "MIT" ]

5

2021-03-15T21:05:06.000Z

2022-03-04T10:52:16.000Z

lltk/corpus/tcp/__init__.py

literarylab/lltk

0e516d7fa0978c1a3bd2cb7636f0089772e515ec

[ "MIT" ]

1

2021-05-04T17:01:47.000Z

2021-05-10T15:14:55.000Z

lltk/corpus/tcp/__init__.py

literarylab/lltk

0e516d7fa0978c1a3bd2cb7636f0089772e515ec

[ "MIT" ]

null

from .tcp import *

9.5

18

0.684211

3

19

4.333333

1

0

0.210526

19

1

19

0.866667

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null

0

1

0

1

0

1

0

6

b5319c21e7738c887dd6d54c2e970224bd9fdf04

98

py

Python

pydocxs3upload/exceptions.py

jhubert/pydocx-s3-images

e7c96b257c67db8043822292550c193db410a4e6

[ "Apache-2.0" ]

2

2016-04-17T02:45:33.000Z

2019-07-26T09:26:41.000Z

pydocxs3upload/exceptions.py

jhubert/pydocx-s3-images

e7c96b257c67db8043822292550c193db410a4e6

[ "Apache-2.0" ]

3

2015-07-17T20:04:53.000Z

2015-07-18T19:24:40.000Z

pydocxs3upload/exceptions.py

jhubert/pydocx-s3-images

e7c96b257c67db8043822292550c193db410a4e6

[ "Apache-2.0" ]

null

from __future__ import ( absolute_import, ) class ImageUploadException(Exception): pass

12.25

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9

98

7.555556

0.888889

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0.193878

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7

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true

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null

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1

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1

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6

b5a7eccebecfc2d7bd617f2ccc94c4e890ce2263

93

py

Python

config.py

mayukh18/covidexplore

7181c845e789c4d2eb2477dc4f6c6ea1f761761b

[ "MIT" ]

5

2020-03-31T19:30:11.000Z

2020-05-12T10:37:12.000Z

config.py

mayukh18/covidexplore

7181c845e789c4d2eb2477dc4f6c6ea1f761761b

[ "MIT" ]

1

2020-04-02T23:02:07.000Z

config.py

mayukh18/covidexplore

7181c845e789c4d2eb2477dc4f6c6ea1f761761b

[ "MIT" ]

3

2020-05-12T05:41:52.000Z

2020-07-26T03:54:49.000Z

# Dates CASES_DATA_UPDATE_DATE = 'April 23, 2020' CLIMATE_DATA_UPDATE_DATE = 'April 23, 2020'

31

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93

3

43

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false

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null

1

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1

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null

0

6

a982398c3388704ba31d1f9546c7f4643b40b852

6,932

py

Python

hubcheck/pageobjects/widgets/members_profile_form.py

codedsk/hubcheck

2ff506eb56ba00f035300862f8848e4168452a17

[ "MIT" ]

1

2016-02-13T13:42:23.000Z

hubcheck/pageobjects/widgets/members_profile_form.py

codedsk/hubcheck

2ff506eb56ba00f035300862f8848e4168452a17

[ "MIT" ]

null

hubcheck/pageobjects/widgets/members_profile_form.py

codedsk/hubcheck

2ff506eb56ba00f035300862f8848e4168452a17

[ "MIT" ]

null

from hubcheck.pageobjects.basepagewidget import BasePageWidget class MembersProfileForm1(BasePageWidget): def __init__(self, owner, locatordict={}): super(MembersProfileForm1,self).__init__(owner,locatordict) # load hub's classes MembersProfileForm_Locators = self.load_class('MembersProfileForm_Locators') MembersProfileBiography = self.load_class('MembersProfileBiography') MembersProfileCitizenship = self.load_class('MembersProfileCitizenship') MembersProfileEmail = self.load_class('MembersProfileEmail') MembersProfileEmployment = self.load_class('MembersProfileEmployment') MembersProfileGender = self.load_class('MembersProfileGender') MembersProfileInterests = self.load_class('MembersProfileInterests') MembersProfileMailPreference = self.load_class('MembersProfileMailPreference') MembersProfileName = self.load_class('MembersProfileName') MembersProfileOrganization = self.load_class('MembersProfileOrganization') MembersProfilePassword = self.load_class('MembersProfilePassword') MembersProfileResidence = self.load_class('MembersProfileResidence') MembersProfileWebsite = self.load_class('MembersProfileWebsite') MembersProfileTelephone = self.load_class('MembersProfileTelephone') # update this object's locator self.locators.update(MembersProfileForm_Locators.locators) # update the locators with those from the owner self.update_locators_from_owner() # setup page object's components self.biography = MembersProfileBiography(self,{'base':'biography'}) self.citizenship = MembersProfileCitizenship(self,{'base':'citizenship'}) self.email = MembersProfileEmail(self,{'base':'email'}) self.employment = MembersProfileEmployment(self,{'base':'employment'}) self.gender = MembersProfileGender(self,{'base':'gender'}) self.interests = MembersProfileInterests(self,{'base':'interests'}) self.mailpreference = MembersProfileMailPreference(self,{'base':'mailpreference'}) self.name = MembersProfileName(self,{'base':'name'}) self.organization = MembersProfileOrganization(self,{'base':'organization'}) self.password = MembersProfilePassword(self,{'base':'password'}) self.residence = MembersProfileResidence(self,{'base':'residence'}) self.website = MembersProfileWebsite(self,{'base':'website'}) self.telephone = MembersProfileTelephone(self,{'base':'telephone'}) # update the component's locators with this objects overrides self._updateLocators() class MembersProfileForm2(BasePageWidget): def __init__(self, owner, locatordict=None): super(MembersProfileForm2,self).__init__(owner,locatordict) # load hub's classes MembersProfileForm_Locators = self.load_class('MembersProfileForm_Locators') MembersProfileBiography = self.load_class('MembersProfileBiography') MembersProfileEmail = self.load_class('MembersProfileEmail') MembersProfileName = self.load_class('MembersProfileName') MembersProfilePassword = self.load_class('MembersProfilePassword') # update this object's locator self.locators.update(MembersProfileForm_Locators.locators) # update the locators with those from the owner self.update_locators_from_owner() # setup page object's components self.biography = MembersProfileBiography(self,{'base':'biography'}) self.email = MembersProfileEmail(self,{'base':'email'}) self.name = MembersProfileName(self,{'base':'name'}) self.password = MembersProfilePassword(self,{'base':'password'}) # update the component's locators with this objects overrides self._updateLocators() class MembersProfileForm3(BasePageWidget): def __init__(self, owner, locatordict={}): super(MembersProfileForm3,self).__init__(owner,locatordict) # load hub's classes MembersProfileForm_Locators = self.load_class('MembersProfileForm_Locators') MembersProfileBiography = self.load_class('MembersProfileBiography') MembersProfileEmail = self.load_class('MembersProfileEmail') MembersProfileEmployment = self.load_class('MembersProfileEmployment') MembersProfileInterests = self.load_class('MembersProfileInterests') MembersProfileMailPreference = self.load_class('MembersProfileMailPreference') MembersProfileName = self.load_class('MembersProfileName') MembersProfileOrganization = self.load_class('MembersProfileOrganization') MembersProfileWebsite = self.load_class('MembersProfileWebsite') MembersProfileTelephone = self.load_class('MembersProfileTelephone') # update this object's locator self.locators.update(MembersProfileForm_Locators.locators) # update the locators with those from the owner self.update_locators_from_owner() # setup page object's components self.biography = MembersProfileBiography(self,{'base':'biography'}) self.email = MembersProfileEmail(self,{'base':'email'}) self.employment = MembersProfileEmployment(self,{'base':'employment'}) self.interests = MembersProfileInterests(self,{'base':'interests'}) self.mailpreference = MembersProfileMailPreference(self,{'base':'mailpreference'}) self.name = MembersProfileName(self,{'base':'name'}) self.organization = MembersProfileOrganization(self,{'base':'organization'}) self.website = MembersProfileWebsite(self,{'base':'website'}) self.telephone = MembersProfileTelephone(self,{'base':'telephone'}) # update the component's locators with this objects overrides self._updateLocators() class MembersProfileForm_Locators_Base(object): """locators for MembersProfileForm object""" locators = { 'base' : "css=#profile", 'biography' : "css=.profile-bio", 'citizenship' : "css=.profile-countryorigin", 'email' : "css=.profile-email", 'employment' : "css=.profile-orgtype", 'gender' : "css=.profile-sex", 'interests' : "css=.profile-interests", 'mailpreference' : "css=.profile-optin", 'name' : "css=.profile-name", 'organization' : "css=.profile-org", 'password' : "css=.profile-password", 'residence' : "css=.profile-countryresident", 'website' : "css=.profile-web", 'telephone' : "css=.profile-phone", }

53.323077

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0.67513

553

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6,932

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0.054945

0.010989

0

0.098901

0

null

0

1

0

null

0

1

0

6

a9834508a52115f665f75846901ea4cb8df774e5

183

py

Python

A-Byte-of-Python/18_5_list_comprehension.py

anklav24/Python-Education

49ebcfabda1376390ee71e1fe321a51e33831f9e

[ "Apache-2.0" ]

null

A-Byte-of-Python/18_5_list_comprehension.py

anklav24/Python-Education

49ebcfabda1376390ee71e1fe321a51e33831f9e

[ "Apache-2.0" ]

null

A-Byte-of-Python/18_5_list_comprehension.py

anklav24/Python-Education

49ebcfabda1376390ee71e1fe321a51e33831f9e

[ "Apache-2.0" ]

null

list_one = [2, 3, 4] list_two = [2 * i for i in list_one if i > 2] print(list_two) print() list_one = [2, 3, 4] list_two = [2 * i for i in list_one if i > 1] print(list_two) print()

18.3

45

0.622951

42

183

2.52381

0.285714

0.264151

0.150943

0.169811

0.660377

0

0.070423

0.224044

183

9

46

20.333333

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1

0

1

0

null

0

1

0

6

a99e3827965cc9149cc3166a80d1d4563b0641dc

144

py

Python

helloWorld.py

jakekali/learning-python

6d390883fa32b43a39fbed7ea4345095ea35ff05

[ "MIT" ]

null

helloWorld.py

jakekali/learning-python

6d390883fa32b43a39fbed7ea4345095ea35ff05

[ "MIT" ]

null

helloWorld.py

jakekali/learning-python

6d390883fa32b43a39fbed7ea4345095ea35ff05

[ "MIT" ]

null

x = "Hello " + "World" print(x) if(x == "Hello World"): print("X is equal to hello World") else: print("X is not equal to Hello World")

20.571429

42

0.604167

25

144

3.48

0.4

0.45977

0.252874

0.367816

0.390805

0

0.229167

144

7

42

20.571429

0.783784

0

0.524138

0

0.166667

0

1

0

false

0

0.5

1

0

null

1

0

1

0

null

0

1

0

6

8d19910405d7a6c1c4c2a464035cf616bd61f887

26,030

py

Python

Model&Data/CADA-VAE/main.py

LiangjunFeng/Generative-Any-Shot-Learning

693c4ab92f2eb04cc453c870782710a982f98e80

[ "Apache-2.0" ]

null

Model&Data/CADA-VAE/main.py

LiangjunFeng/Generative-Any-Shot-Learning

693c4ab92f2eb04cc453c870782710a982f98e80

[ "Apache-2.0" ]

null

Model&Data/CADA-VAE/main.py

LiangjunFeng/Generative-Any-Shot-Learning

693c4ab92f2eb04cc453c870782710a982f98e80

[ "Apache-2.0" ]

null

# execute # generalized ZSL # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA1 --few_train False --num_shots 0 --generalized True > awa1.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset SUN --few_train False --num_shots 0 --generalized True > sun.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset CUB --few_train False --num_shots 0 --generalized True > cub.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 0 --generalized True > awa2.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized True > flo.log 2>&1 & # naive feature # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 0 --generalized True --image_embedding res101_naive > awa2.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset SUN --few_train False --num_shots 0 --generalized True --image_embedding res101_naive > sun.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset CUB --few_train False --num_shots 0 --generalized True --image_embedding res101_naive > cub.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized True --image_embedding res101_naive > flo.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset aPY --few_train False --num_shots 0 --generalized True --image_embedding res101_naive > apy.log 2>&1 & # finetue feature # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 0 --generalized True --image_embedding res101_finetune > awa2.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset SUN --few_train False --num_shots 0 --generalized True --image_embedding res101_finetune > sun.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset CUB --few_train False --num_shots 0 --generalized True --image_embedding res101_finetune > cub.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized True --image_embedding res101_finetune > flo.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset aPY --few_train False --num_shots 0 --generalized True --image_embedding res101_finetune > apy.log 2>&1 & # reg feature # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized True --image_embedding res101_reg > flo.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset CUB --few_train False --num_shots 0 --generalized True --image_embedding res101_reg > cub.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset SUN --few_train False --num_shots 0 --generalized True --image_embedding res101_reg > sun.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 0 --generalized True --image_embedding res101_reg > awa2.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset aPY --few_train False --num_shots 0 --generalized True --image_embedding res101_reg > apy.log 2>&1 & # few shot # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 1 --generalized True --image_embedding res101_reg > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train False --num_shots 5 --generalized True --image_embedding res101_reg > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train False --num_shots 10 --generalized True --image_embedding res101_reg > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train False --num_shots 20 --generalized True --image_embedding res101_reg > flo3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train True --num_shots 1 --generalized True --image_embedding res101_naive > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train True --num_shots 5 --generalized True --image_embedding res101_naive > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train True --num_shots 10 --generalized True --image_embedding res101_naive > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train True --num_shots 20 --generalized True --image_embedding res101_naive > flo3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset CUB --few_train False --num_shots 1 --generalized True --image_embedding res101_reg > cub0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset CUB --few_train False --num_shots 5 --generalized True --image_embedding res101_reg > cub1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset CUB --few_train False --num_shots 10 --generalized True --image_embedding res101_reg > cub2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset CUB --few_train False --num_shots 20 --generalized True --image_embedding res101_reg > cub3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset CUB --few_train True --num_shots 1 --generalized True --image_embedding res101_naive > cub0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset CUB --few_train True --num_shots 5 --generalized True --image_embedding res101_naive > cub1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset CUB --few_train True --num_shots 10 --generalized True --image_embedding res101_naive > cub2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset CUB --few_train True --num_shots 20 --generalized True --image_embedding res101_naive > cub3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset SUN --few_train False --num_shots 1 --generalized True --image_embedding res101_reg > sun0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset SUN --few_train False --num_shots 5 --generalized True --image_embedding res101_reg > sun1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset SUN --few_train False --num_shots 10 --generalized True --image_embedding res101_reg > sun2.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset SUN --few_train True --num_shots 1 --generalized True --image_embedding res101 > sun0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset SUN --few_train True --num_shots 5 --generalized True --image_embedding res101 > sun1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset SUN --few_train True --num_shots 10 --generalized True --image_embedding res101 > sun2.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 1 --generalized True --image_embedding res101_naive > awa20.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 5 --generalized True --image_embedding res101_naive > awa21.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 10 --generalized True --image_embedding res101_naive > awa22.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset AWA2 --few_train False --num_shots 20 --generalized True --image_embedding res101_naive > awa23.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA2 --few_train True --num_shots 1 --generalized True --image_embedding res101_naive > awa20.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset AWA2 --few_train True --num_shots 5 --generalized True --image_embedding res101_naive > awa21.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset AWA2 --few_train True --num_shots 10 --generalized True --image_embedding res101_naive > awa22.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset AWA2 --few_train True --num_shots 20 --generalized True --image_embedding res101_naive > awa23.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA1 --few_train False --num_shots 1 --generalized True --image_embedding res101 > awa10.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset AWA1 --few_train False --num_shots 5 --generalized True --image_embedding res101 > awa11.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset AWA1 --few_train False --num_shots 10 --generalized True --image_embedding res101 > awa12.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset AWA1 --few_train False --num_shots 20 --generalized True --image_embedding res101 > awa13.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset AWA1 --few_train True --num_shots 1 --generalized True --image_embedding res101 > awa10.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset AWA1 --few_train True --num_shots 5 --generalized True --image_embedding res101 > awa11.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset AWA1 --few_train True --num_shots 10 --generalized True --image_embedding res101 > awa12.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset AWA1 --few_train True --num_shots 20 --generalized True --image_embedding res101 > awa13.log 2>&1 & # reg feature + att # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized False --image_embedding res101_reg --class_embedding att > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized False --image_embedding res101_reg --class_embedding att_naive > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized False --image_embedding res101_reg --class_embedding att_GRU > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 0 --generalized False --image_embedding res101_reg --class_embedding att_GRU_biased > flo3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train True --num_shots 1 --generalized True --image_embedding res101_naive --class_embedding att_GRU_biased > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train True --num_shots 5 --generalized True --image_embedding res101_naive --class_embedding att_GRU_biased > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train True --num_shots 10 --generalized True --image_embedding res101_naive --class_embedding att_GRU_biased > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train True --num_shots 20 --generalized True --image_embedding res101_naive --class_embedding att_GRU_biased > flo3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train True --num_shots 1 --generalized True --image_embedding res101_naive --class_embedding att > flo4.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train True --num_shots 5 --generalized True --image_embedding res101_naive --class_embedding att > flo5.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train True --num_shots 10 --generalized True --image_embedding res101_naive --class_embedding att > flo6.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train True --num_shots 20 --generalized True --image_embedding res101_naive --class_embedding att > flo7.log 2>&1 & # few shot + class # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train False --num_shots 1 --generalized False --image_embedding res101_reg --class_embedding att_GRU_biased > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train False --num_shots 5 --generalized False --image_embedding res101_reg --class_embedding att_GRU_biased > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train False --num_shots 10 --generalized False --image_embedding res101_reg --class_embedding att_GRU_biased > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train False --num_shots 20 --generalized False --image_embedding res101_reg --class_embedding att_GRU_biased > flo3.log 2>&1 & # CUDA_VISIBLE_DEVICES=0 nohup python -u main.py --dataset FLO --few_train True --num_shots 1 --generalized False --image_embedding res101_naive --class_embedding att_GRU_biased > flo0.log 2>&1 & # CUDA_VISIBLE_DEVICES=1 nohup python -u main.py --dataset FLO --few_train True --num_shots 5 --generalized False --image_embedding res101_naive --class_embedding att_GRU_biased > flo1.log 2>&1 & # CUDA_VISIBLE_DEVICES=2 nohup python -u main.py --dataset FLO --few_train True --num_shots 10 --generalized False --image_embedding res101_naive --class_embedding att_GRU_biased > flo2.log 2>&1 & # CUDA_VISIBLE_DEVICES=3 nohup python -u main.py --dataset FLO --few_train True --num_shots 20 --generalized False --image_embedding res101_naive --class_embedding att_GRU_biased > flo3.log 2>&1 & from vaemodel import Model import torch import argparse import warnings import numpy as np warnings.filterwarnings("ignore") def str2bool(v): if v.lower() in ('yes', 'true', 't', 'y', '1'): return True elif v.lower() in ('no', 'false', 'f', 'n', '0'): return False else: raise argparse.ArgumentTypeError('Boolean value expected.') parser = argparse.ArgumentParser() parser.add_argument('--dataset', default='FLO', help='FLO') parser.add_argument('--few_train', default = False, type = str2bool, help='use few train samples') parser.add_argument('--num_shots', type=int, default=5, help='the number of shots, if few_train, then num_shots is for train classes, else for test classes') parser.add_argument('--generalized', default=False, type = str2bool, help='enable generalized zero-shot learning') parser.add_argument('--image_embedding', default='res101', help='res101') parser.add_argument('--class_embedding', default='att', help='att') args = parser.parse_args() ######################################## # the basic hyperparameters ######################################## hyperparameters = { 'num_shots': 0, 'device': 'cuda', 'model_specifics': {'cross_reconstruction': True, 'name': 'CADA', 'distance': 'wasserstein', 'warmup': {'beta': {'factor': 0.25, 'end_epoch': 93, 'start_epoch': 0}, 'cross_reconstruction': {'factor': 2.37, 'end_epoch': 75, 'start_epoch': 21}, 'distance': {'factor': 8.13, 'end_epoch': 22, 'start_epoch': 6}}}, 'lr_gen_model': 0.00015, 'generalized': True, 'batch_size': 50, 'xyu_samples_per_class': {'SUN': (200, 0, 400, 0), 'aPY': (200, 0, 400, 0), 'CUB': (200, 0, 400, 0), 'AWA2': (200, 0, 400, 0), 'FLO': (200, 0, 400, 0), 'AWA1': (200, 0, 400, 0)}, 'epochs': 100, 'loss': 'l1', 'auxiliary_data_source' : 'attributes', 'lr_cls': 0.001, 'dataset': 'CUB', 'hidden_size_rule': {'resnet_features': (1560, 1660), 'attributes': (1450, 665), 'sentences': (1450, 665) }, 'latent_size': 64 } # The training epochs for the final classifier, for early stopping, # as determined on the validation spit cls_train_steps = [ {'dataset': 'SUN', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 21}, {'dataset': 'SUN', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 30}, {'dataset': 'SUN', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 22}, {'dataset': 'SUN', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 96}, {'dataset': 'SUN', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 29}, {'dataset': 'SUN', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 78}, {'dataset': 'SUN', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 29}, {'dataset': 'SUN', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 61}, {'dataset': 'SUN', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 79}, {'dataset': 'SUN', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 94}, {'dataset': 'SUN', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 79}, {'dataset': 'SUN', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 94}, {'dataset': 'AWA1', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 33}, {'dataset': 'AWA1', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 100}, {'dataset': 'AWA1', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 40}, {'dataset': 'AWA1', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 81}, {'dataset': 'AWA1', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 89}, {'dataset': 'AWA1', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 62}, {'dataset': 'AWA1', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 56}, {'dataset': 'AWA1', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 59}, {'dataset': 'AWA1', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 100}, {'dataset': 'AWA1', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 50}, {'dataset': 'AWA1', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 100}, {'dataset': 'AWA1', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 50}, {'dataset': 'CUB', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 100}, {'dataset': 'CUB', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 100}, {'dataset': 'CUB', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 34}, {'dataset': 'CUB', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 46}, {'dataset': 'CUB', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 64}, {'dataset': 'CUB', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 73}, {'dataset': 'CUB', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 39}, {'dataset': 'CUB', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 31}, {'dataset': 'CUB', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'CUB', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 67}, {'dataset': 'CUB', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'CUB', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 67}, {'dataset': 'AWA2', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 29}, {'dataset': 'AWA2', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 39}, {'dataset': 'AWA2', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 44}, {'dataset': 'AWA2', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 96}, {'dataset': 'AWA2', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 99}, {'dataset': 'AWA2', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 100}, {'dataset': 'AWA2', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 69}, {'dataset': 'AWA2', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 79}, {'dataset': 'AWA2', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 86}, {'dataset': 'AWA2', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 78}, {'dataset': 'AWA2', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 86}, {'dataset': 'AWA2', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 78}, {'dataset': 'aPY', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 23}, {'dataset': 'aPY', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 22}, {'dataset': 'aPY', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 34}, {'dataset': 'aPY', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 46}, {'dataset': 'aPY', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 64}, {'dataset': 'aPY', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 73}, {'dataset': 'aPY', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 39}, {'dataset': 'aPY', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 31}, {'dataset': 'aPY', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'aPY', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 67}, {'dataset': 'aPY', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'aPY', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 67}, {'dataset': 'FLO', 'num_shots': 0, 'generalized': True, 'cls_train_steps': 23}, {'dataset': 'FLO', 'num_shots': 0, 'generalized': False, 'cls_train_steps': 100}, {'dataset': 'FLO', 'num_shots': 1, 'generalized': True, 'cls_train_steps': 34}, {'dataset': 'FLO', 'num_shots': 1, 'generalized': False, 'cls_train_steps': 46}, {'dataset': 'FLO', 'num_shots': 5, 'generalized': True, 'cls_train_steps': 64}, {'dataset': 'FLO', 'num_shots': 5, 'generalized': False, 'cls_train_steps': 73}, {'dataset': 'FLO', 'num_shots': 2, 'generalized': True, 'cls_train_steps': 39}, {'dataset': 'FLO', 'num_shots': 2, 'generalized': False, 'cls_train_steps': 31}, {'dataset': 'FLO', 'num_shots': 10, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'FLO', 'num_shots': 10, 'generalized': False, 'cls_train_steps': 67}, {'dataset': 'FLO', 'num_shots': 20, 'generalized': True, 'cls_train_steps': 85}, {'dataset': 'FLO', 'num_shots': 20, 'generalized': False, 'cls_train_steps': 67} ] ################################## # change some hyperparameters here ################################## hyperparameters['dataset'] = args.dataset hyperparameters['num_shots']= args.num_shots hyperparameters['generalized']= args.generalized hyperparameters['few_train']= args.few_train hyperparameters['image_embedding']= args.image_embedding hyperparameters['class_embedding']= args.class_embedding hyperparameters['cls_train_steps'] = [x['cls_train_steps'] for x in cls_train_steps if all([hyperparameters['dataset']==x['dataset'], hyperparameters['num_shots']==x['num_shots'], hyperparameters['generalized']==x['generalized'] ])][0] print('***') print(hyperparameters['cls_train_steps']) if hyperparameters['generalized']: if hyperparameters['few_train']==True or hyperparameters['num_shots']==0: hyperparameters['samples_per_class'] = {'CUB': (200, 0, 400, 0), 'SUN': (200, 0, 400, 0), 'aPY': (200, 0, 400, 0), 'AWA1': (200, 0, 400, 0), 'AWA2': (200, 0, 400, 0), 'FLO': (200, 0, 400, 0)} else: hyperparameters['samples_per_class'] = {'CUB': (200, 0, 200, 200), 'SUN': (200, 0, 200, 200), 'aPY': (200, 0, 200, 200), 'AWA1': (200, 0, 200, 200), 'AWA2': (200, 0, 200, 200), 'FLO': (200, 0, 200, 200)} else: if hyperparameters['few_train']==True or hyperparameters['num_shots']==0: hyperparameters['samples_per_class'] = {'CUB': (0, 0, 200, 0), 'SUN': (0, 0, 200, 0), 'aPY': (0, 0, 200, 0), 'AWA1': (0, 0, 200, 0), 'AWA2': (0, 0, 200, 0), 'FLO': (0, 0, 200, 0)} else: hyperparameters['samples_per_class'] = {'CUB': (0, 0, 200, 200), 'SUN': (0, 0, 200, 200), 'aPY': (0, 0, 200, 200), 'AWA1': (0, 0, 200, 200), 'AWA2': (0, 0, 200, 200), 'FLO': (0, 0, 200, 200)} model = Model(hyperparameters) model.to(hyperparameters['device']) """ ######################################## ### load model where u left ######################################## saved_state = torch.load('./saved_models/CADA_trained.pth.tar') model.load_state_dict(saved_state['state_dict']) for d in model.all_data_sources_without_duplicates: model.encoder[d].load_state_dict(saved_state['encoder'][d]) model.decoder[d].load_state_dict(saved_state['decoder'][d]) ######################################## """ losses = model.train_vae() u,s,h,history = model.train_classifier() if model.DATASET == "AWA2": syn_feature, syn_label = model.generate_syn_feature() np.save("./cadavae_feat.npy", syn_feature.data.cpu().numpy()) np.save("./cadavae_label.npy", syn_label.data.cpu().numpy()) print(syn_feature.data.cpu().numpy().shape, syn_label.data.cpu().numpy().shape) if hyperparameters['generalized']==True: acc = [hi[2] for hi in history] elif hyperparameters['generalized']==False: acc = [hi[1] for hi in history] print(acc[-1]) state = { 'state_dict': model.state_dict() , 'hyperparameters':hyperparameters, 'encoder':{}, 'decoder':{} } for d in model.all_data_sources: state['encoder'][d] = model.encoder[d].state_dict() state['decoder'][d] = model.decoder[d].state_dict() torch.save(state, 'CADA_trained.pth.tar') print('>> saved')

69.413333

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3,670

26,030

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0.085688

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0.027174

0

null

0

1

0

null

0

6

8d4d44172cb6cf8cc8abb5a7448ade57f61bff5d

30

py

Python

court_scraper/platforms/wiscourts/__init__.py

DiPierro/court-scraper

eb289e1559d317c04f1d92dacc96a49b9480e552

[ "ISC" ]

null

court_scraper/platforms/wiscourts/__init__.py

DiPierro/court-scraper

eb289e1559d317c04f1d92dacc96a49b9480e552

[ "ISC" ]

null

court_scraper/platforms/wiscourts/__init__.py

DiPierro/court-scraper

eb289e1559d317c04f1d92dacc96a49b9480e552

[ "ISC" ]

null

from .site import WiscourtSite

30

0.866667

4

30

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1

0

null

0

1

0

1

0

1

0

6

8d9ed684ac8ecf9feba491a315963d05508d9dab

215

py

Python

nose2_kflag/tests/scenario/doctests/pymodule.py

stefanholek/nose2-kflag

8236cc43d0f06afabdb401b111af45d5d8fd9a49

[ "BSD-2-Clause" ]

1

2020-06-14T13:54:15.000Z

nose2_kflag/tests/scenario/doctests/pymodule.py

stefanholek/nose2-kflag

8236cc43d0f06afabdb401b111af45d5d8fd9a49

[ "BSD-2-Clause" ]

1

2021-02-02T05:04:05.000Z

nose2_kflag/tests/scenario/doctests/pymodule.py

stefanholek/nose2-kflag

8236cc43d0f06afabdb401b111af45d5d8fd9a49

[ "BSD-2-Clause" ]

null

""" >>> print('foo') foo """ def func_foo(): """ >>> print('foo') foo """ def func_bar(): """ >>> print('bar') bar """ def func_baz(): """ >>> print('baz') baz """

9.347826

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0.297297

0.378378

0.486486

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0.35814

215

22

21

9.772727

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0

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0

1

0

null

1

0

null

0

1

0

6

8da95e612cbffa6047266e2f2f1d7089de586633

19

py

Python

bills_service/bills_service/routes/__init__.py

reubinoff/bills

36163ff643046cbdf78ed572dd110e045a4b6d08

[ "MIT" ]

1

2021-11-15T19:10:41.000Z

bot/handlers/__init__.py

famaxth/YouTube-Parser-Bot

420c8f0bdc6f3abd367b475b2034969057f6e3f2

[ "MIT" ]

7

2021-09-02T00:44:06.000Z

2022-02-26T17:23:44.000Z

backend/flask/app/apis/__init__.py

yf-dev/twitch-dccon-manager

97b0b5410621a10896679474f149bf1892e678b8

[ "MIT" ]

null

from . import users

19

0.789474

3

19

5

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true

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null

0

1

0

1

0

1

0

6

9392ab80e4bb630a8a2e1da2c6f9e5b211336f1e

13,467

py

Python

main/migrations/0001_initial.py

AminAliH47/PicoStyle

768daccc6f28f08aa848318d633af1a19544e499

[ "Apache-2.0" ]

19

2022-02-16T20:00:08.000Z

2022-03-08T17:38:59.000Z

main/migrations/0001_initial.py

AminAliH47/PicoStyle

768daccc6f28f08aa848318d633af1a19544e499

[ "Apache-2.0" ]

3

2022-02-16T20:59:11.000Z

2022-02-23T20:40:12.000Z

main/migrations/0001_initial.py

AminAliH47/PicoStyle

768daccc6f28f08aa848318d633af1a19544e499

[ "Apache-2.0" ]

null

# Generated by Django 3.2.9 on 2022-02-12 08:44 import ckeditor.fields import django.core.validators from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='BrandsSlider', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('page', models.CharField(choices=[('All', 'All'), ('Women', 'Women'), ('Men', 'Men'), ('Raw material', 'Raw material'), ('Life style', 'Life style')], help_text='Which home page to display?', max_length=15)), ('title_en', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('title_ru', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('title_it', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('link', models.CharField(max_length=120)), ('description_en', models.TextField(blank=True, max_length=100, null=True, verbose_name='Description')), ('description_ru', models.TextField(blank=True, max_length=100, null=True, verbose_name='Description')), ('description_it', models.TextField(blank=True, max_length=100, null=True, verbose_name='Description')), ('button_en', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_ru', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_it', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_link', models.CharField(blank=True, max_length=150, null=True)), ('cover', models.BooleanField(default=True, help_text='Have dark cover?')), ('image', models.ImageField(upload_to='')), ], options={ 'verbose_name': 'slide', 'verbose_name_plural': '03. Brands slider', }, ), migrations.CreateModel( name='MainCategories', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('page', models.CharField(choices=[('All', 'All'), ('Women', 'Women'), ('Men', 'Men'), ('Raw material', 'Raw material'), ('Life style', 'Life style')], help_text='Which home page to display?', max_length=15)), ('title_en', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_ru', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_it', models.CharField(max_length=50, null=True, verbose_name='Title')), ('image', models.ImageField(upload_to='main/categories')), ('link', models.CharField(max_length=100)), ], options={ 'verbose_name': 'category', 'verbose_name_plural': '07. Main categories', }, ), migrations.CreateModel( name='MainNavbar', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('page', models.CharField(choices=[('All', 'All'), ('Women', 'Women'), ('Men', 'Men'), ('Raw material', 'Raw material'), ('Life style', 'Life style')], help_text='Which home page to display?', max_length=15)), ('title_en', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_ru', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_it', models.CharField(max_length=50, null=True, verbose_name='Title')), ('slug', models.CharField(max_length=150)), ], options={ 'verbose_name': 'item', 'verbose_name_plural': '04. Main navbar', }, ), migrations.CreateModel( name='MainSlider', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('page', models.CharField(choices=[('All', 'All'), ('Women', 'Women'), ('Men', 'Men'), ('Raw material', 'Raw material'), ('Life style', 'Life style')], help_text='Which home page to display?', max_length=15)), ('title_en', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('title_ru', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('title_it', models.CharField(blank=True, max_length=15, verbose_name='Title')), ('link', models.CharField(max_length=120)), ('description_en', models.TextField(blank=True, max_length=120, null=True, verbose_name='Description')), ('description_ru', models.TextField(blank=True, max_length=120, null=True, verbose_name='Description')), ('description_it', models.TextField(blank=True, max_length=120, null=True, verbose_name='Description')), ('button_en', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_ru', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_it', models.CharField(blank=True, max_length=15, null=True, verbose_name='Button')), ('button_link', models.CharField(blank=True, max_length=150, null=True)), ('cover', models.BooleanField(default=True, help_text='Have dark cover?')), ('image', models.ImageField(upload_to='')), ], options={ 'verbose_name': 'slide', 'verbose_name_plural': '02. Main slider', }, ), migrations.CreateModel( name='Retailers', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('gender', models.CharField(choices=[('MS.', 'MS.'), ('MrS.', 'MrS.'), ('Mr.', 'Mr.')], max_length=4)), ('first_name', models.CharField(max_length=50)), ('last_name', models.CharField(max_length=50)), ('email', models.EmailField(max_length=254)), ('phone', models.CharField(max_length=11, validators=[django.core.validators.RegexValidator(message='Your entered phone number is not valid', regex='^[ 0-9]+$')])), ('address', models.TextField()), ('zip_code', models.CharField(max_length=20)), ('country', models.CharField(max_length=50)), ('city', models.CharField(max_length=50)), ('experience', models.CharField(choices=[('Yes', 'Yes'), ('No', 'No')], max_length=4)), ('experience_info', models.JSONField()), ('have_store', models.CharField(choices=[('Yes', 'Yes'), ('No', 'No')], max_length=4, null=True)), ('center_town', models.CharField(choices=[('Yes', 'Yes'), ('No', 'No')], max_length=4, null=True)), ], options={ 'verbose_name': 'retailer', 'verbose_name_plural': '08. Retailers', }, ), migrations.CreateModel( name='SiteSetting', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('site_title', models.CharField(max_length=100)), ('logo', models.ImageField(upload_to='main/logo')), ('favicon', models.ImageField(upload_to='main/favicon')), ], options={ 'verbose_name': 'setting', 'verbose_name_plural': '01. Site setting', }, ), migrations.CreateModel( name='SizeGuide', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title_en', models.CharField(max_length=100, verbose_name='title')), ('title_ru', models.CharField(max_length=100, verbose_name='title')), ('title_it', models.CharField(max_length=100, verbose_name='title')), ('link', models.CharField(max_length=120)), ('image', models.ImageField(upload_to='main/size-guide')), ], options={ 'verbose_name': 'item', 'verbose_name_plural': '12. Size guide', }, ), migrations.CreateModel( name='SocialMedia', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title_en', models.CharField(max_length=50, null=True, verbose_name='title')), ('title_ru', models.CharField(max_length=50, null=True, verbose_name='title')), ('title_it', models.CharField(max_length=50, null=True, verbose_name='title')), ('link', models.CharField(max_length=120)), ('icon_code', models.CharField(choices=[('linkedin', 'linkedin'), ('youtube', 'youtube'), ('facebook', 'facebook'), ('instagram', 'instagram'), ('telegram', 'telegram')], max_length=15)), ], options={ 'verbose_name': 'social media', 'verbose_name_plural': '06. Social media', }, ), migrations.CreateModel( name='SpecialProjects', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title_en', models.CharField(max_length=100, verbose_name='title')), ('title_ru', models.CharField(max_length=100, verbose_name='title')), ('title_it', models.CharField(max_length=100, verbose_name='title')), ('link', models.CharField(max_length=120)), ('image', models.ImageField(upload_to='main/special-project')), ], options={ 'verbose_name': 'item', 'verbose_name_plural': '10. Special projects', }, ), migrations.CreateModel( name='StoreAgent', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name_en', models.CharField(max_length=120, null=True, verbose_name='Name')), ('name_ru', models.CharField(max_length=120, null=True, verbose_name='Name')), ('name_it', models.CharField(max_length=120, null=True, verbose_name='Name')), ('country', models.CharField(max_length=120)), ('country_code', models.CharField(max_length=4)), ('description_en', ckeditor.fields.RichTextField(max_length=450, null=True, verbose_name='Description')), ('description_ru', ckeditor.fields.RichTextField(max_length=450, null=True, verbose_name='Description')), ('description_it', ckeditor.fields.RichTextField(max_length=450, null=True, verbose_name='Description')), ('image', models.ImageField(upload_to='main/store-and-agent')), ('active', models.BooleanField(default=True)), ], options={ 'verbose_name': 'store', 'verbose_name_plural': '09. Store and agent', }, ), migrations.CreateModel( name='SubNavbar', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('page', models.CharField(choices=[('All', 'All'), ('Women', 'Women'), ('Men', 'Men'), ('Raw material', 'Raw material'), ('Life style', 'Life style')], help_text='Which home page to display?', max_length=15)), ('title_en', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_ru', models.CharField(max_length=50, null=True, verbose_name='Title')), ('title_it', models.CharField(max_length=50, null=True, verbose_name='Title')), ('slug', models.CharField(max_length=150)), ], options={ 'verbose_name': 'item', 'verbose_name_plural': '05. Sub navbar', }, ), migrations.CreateModel( name='WorkWithUs', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title_en', models.CharField(max_length=100, verbose_name='title')), ('title_ru', models.CharField(max_length=100, verbose_name='title')), ('title_it', models.CharField(max_length=100, verbose_name='title')), ('link', models.CharField(max_length=120)), ('image', models.ImageField(upload_to='main/work-with-us')), ], options={ 'verbose_name': 'item', 'verbose_name_plural': '11. Work with us', }, ), ]

59.325991

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0.56709

1,396

13,467

5.280802

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0.120863

0.10255

0.136734

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0.752849

0.735757

0.719343

0.715138

0

0.022644

0.268731

13,467

226

59.588496

0.725934

0.003342

0

0.584475

1

0

0.19225

0

1

0

false

0

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0

0.031963

0

null

0

1

0

1

0

null

0

6

93c5bf4ecd6ae4b4a8cb9c24cb5594fc9a800fa7

187

py

Python

datek_jaipur/domain/errors/player_created.py

DAtek/datek-jaipur

e49e4b391f2e23ed5a333477cc479ccbc1c90dee

[ "MIT" ]

null

datek_jaipur/domain/errors/player_created.py

DAtek/datek-jaipur

e49e4b391f2e23ed5a333477cc479ccbc1c90dee

[ "MIT" ]

1

2022-03-26T11:05:28.000Z

datek_jaipur/domain/errors/player_created.py

DAtek/datek-jaipur

e49e4b391f2e23ed5a333477cc479ccbc1c90dee

[ "MIT" ]

null

from datek_jaipur.errors import EventValidationError class PlayerCreatedValidationError(EventValidationError): pass class InvalidNameError(PlayerCreatedValidationError): pass

18.7

57

0.84492

14

187

11.214286

0.714286

0

0.117647

187

9

58

20.777778

0.951515

0

0.4

0

1

0

true

0.4

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0.6

0

1

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1

null

0

1

0

null

0

1

0

1

0

6

93d84167912b639dbd9b9a34c228afc885455bb0

20,933

py

Python

test_numfile.py

bzaczynski/numfile

b00694f83954bc79e2be582a548e61c1fd900c18

[ "MIT" ]

null

test_numfile.py

bzaczynski/numfile

b00694f83954bc79e2be582a548e61c1fd900c18

[ "MIT" ]

null

test_numfile.py

bzaczynski/numfile

b00694f83954bc79e2be582a548e61c1fd900c18

[ "MIT" ]

null

import types from pathlib import Path from unittest.mock import call import pytest from pytest_mock import MockerFixture from numfile import NumberedFile, open_all, open_latest, open_next class TestNumberedFileOf: def test_should_accept_str_or_path(self): assert NumberedFile.of("file") == NumberedFile.of(Path("file")) def test_should_return_numbered_file(self): assert isinstance(NumberedFile.of("/path/to/file"), NumberedFile) def test_should_parse_no_path(self): file = NumberedFile.of("file") assert file.parent == Path(".") def test_should_parse_relative_path(self): file = NumberedFile.of("path/to/file") assert file.parent == Path("path/to/") def test_should_parse_absolute_path(self): file = NumberedFile.of("/path/to/file") assert file.parent == Path("/path/to") def test_should_parse_plain_name(self): file = NumberedFile.of("/path/to/file") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number is None assert file.suffix == "" def test_should_parse_simple_suffix(self): file = NumberedFile.of("/path/to/file.txt") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number is None assert file.suffix == ".txt" def test_should_parse_complex_suffix(self): file = NumberedFile.of("/path/to/file.txt.tar.gz") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number is None assert file.suffix == ".txt.tar.gz" def test_should_parse_number(self): file = NumberedFile.of("/path/to/file-42") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number == 42 assert file.suffix == "" def test_should_parse_number_and_simple_suffix(self): file = NumberedFile.of("/path/to/file-42.txt") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number == 42 assert file.suffix == ".txt" def test_should_parse_number_and_complex_suffix(self): file = NumberedFile.of("/path/to/file-42.txt.tar.gz") assert file.parent == Path("/path/to") assert file.name == "file" assert file.number == 42 assert file.suffix == ".txt.tar.gz" class TestCurrentPath: @pytest.mark.parametrize( "path", [ "/path/to/file", "/path/to/file.txt", "/path/to/file.txt.tar.gz", "/path/to/file-42", "/path/to/file-42.txt", "/path/to/file-42.txt.tar.gz", ], ) def test_should_return_path_instance(self, path: str): file = NumberedFile.of(path) assert isinstance(file.path, Path) @pytest.mark.parametrize( "path", [ "/path/to/file", "/path/to/file.txt", "/path/to/file.txt.tar.gz", ], ) def test_should_parse_path_without_number(self, path: str): file = NumberedFile.of(path) assert file.path == Path(path) @pytest.mark.parametrize( "path", [ "/path/to/file-42", "/path/to/file-42.txt", "/path/to/file-42.txt.tar.gz", ], ) def test_should_parse_path_with_number(self, path: str): file = NumberedFile.of(path) assert file.path == Path(path) class TestNext: def test_should_return_numbered_file(self, fake_files): file = NumberedFile.of("/path/to/file") assert isinstance(file.next, NumberedFile) def test_no_latest_and_no_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, False]) file = NumberedFile.of("/path/to/no-such-file") assert file.next == NumberedFile.of("/path/to/no-such-file-1") def test_no_latest_but_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, False]) file = NumberedFile.of("/path/to/no-such-file-42") assert file.next == NumberedFile.of("/path/to/no-such-file-42") def test_latest_without_number_and_no_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, True]) file = NumberedFile.of("/path/to/foobar") assert file.next == NumberedFile.of("/path/to/foobar-2") def test_latest_without_number_but_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, True]) file = NumberedFile.of("/path/to/foobar-42") assert file.next == NumberedFile.of("/path/to/foobar-2") def test_latest_with_number_but_no_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, True]) file = NumberedFile.of("/path/to/foo") assert file.next == NumberedFile.of("/path/to/foo-3") def test_latest_with_number_and_number_given( self, mocker: MockerFixture, fake_files ): mocker.patch.object(Path, "exists", side_effect=[True, True]) file = NumberedFile.of("/path/to/foo-42") assert file.next == NumberedFile.of("/path/to/foo-3") class TestLatest: def test_should_return_numbered_file(self, fake_files): file = NumberedFile.of("/path/to/file") assert isinstance(file.latest, NumberedFile) def test_should_return_self_if_no_such_file(self, fake_files): file = NumberedFile.of("/path/to/no-such-file") assert file.latest is file def test_should_return_file_with_highest_number(self, fake_files): file = NumberedFile.of("/path/to/ipsum") assert file.latest.path == Path("/path/to/ipsum-12") def test_should_ignore_given_number(self, fake_files): file = NumberedFile.of("/path/to/ipsum-42") assert file.latest.path == Path("/path/to/ipsum-12") @pytest.fixture def fake_files(mocker: MockerFixture) -> None: mocker.patch.object(Path, "exists", return_value=True) mocker.patch.object( Path, "iterdir", return_value=[ # Unrelated files Path("/path/to/__init__.py"), Path("/path/to/main.py"), Path("/path/to/utils.py"), # Same name but different suffixes Path("/path/to/foo"), Path("/path/to/foo.md"), Path("/path/to/foo.txt"), Path("/path/to/foo.txt.tar.gz"), # Name prefix shared with other files Path("/path/to/foobar"), Path("/path/to/foobar.md"), Path("/path/to/foobar.txt"), Path("/path/to/foobar.txt.tar.gz"), # Plain with numbers Path("/path/to/file-1"), Path("/path/to/file-2"), Path("/path/to/file-3"), Path("/path/to/file-4"), # Plain starting with no number Path("/path/to/lorem"), Path("/path/to/lorem-2"), Path("/path/to/lorem-3"), # Gaps Path("/path/to/ipsum-3"), Path("/path/to/ipsum-8"), Path("/path/to/ipsum-9"), Path("/path/to/ipsum-12"), # Numbers Path("/path/to/foo-1"), Path("/path/to/foo-2"), Path("/path/to/foo-1.md"), Path("/path/to/foo-2.md"), Path("/path/to/foo-3.md"), Path("/path/to/foo-1.txt"), Path("/path/to/foo-2.txt"), Path("/path/to/foo-3.txt"), Path("/path/to/foo-4.txt"), Path("/path/to/foo-1.txt.tar.gz"), Path("/path/to/foo-2.txt.tar.gz"), ], ) class TestSiblings: def test_should_return_generator_of_numbered_files(self, fake_files): file = NumberedFile.of("/path/to/file") siblings = file.siblings assert isinstance(siblings, types.GeneratorType) assert isinstance(next(siblings), NumberedFile) def test_should_be_empty_when_no_parent_dir(self, fake_files): file = NumberedFile.of("/no/such/path") assert list(file.siblings) == [] def test_should_be_empty_when_no_such_file(self, fake_files): file = NumberedFile.of("/path/to/no-such-file") assert list(file.siblings) == [] def test_should_retain_parent(self, fake_files): file = NumberedFile.of("/path/to/file") sibling = next(file.siblings) assert sibling.parent == Path("/path/to") @pytest.mark.parametrize( "path, expected_siblings", [ ( "/path/to/foo", { Path("/path/to/foo"), Path("/path/to/foo-1"), Path("/path/to/foo-2"), }, ), ( "/path/to/foo.txt", { Path("/path/to/foo.txt"), Path("/path/to/foo-1.txt"), Path("/path/to/foo-2.txt"), Path("/path/to/foo-3.txt"), Path("/path/to/foo-4.txt"), }, ), ( "/path/to/foo.txt.tar.gz", { Path("/path/to/foo.txt.tar.gz"), Path("/path/to/foo-1.txt.tar.gz"), Path("/path/to/foo-2.txt.tar.gz"), }, ), ( "/path/to/foo.md", { Path("/path/to/foo.md"), Path("/path/to/foo-1.md"), Path("/path/to/foo-2.md"), Path("/path/to/foo-3.md"), }, ), ( "/path/to/foobar", { Path("/path/to/foobar"), }, ), ( "/path/to/foobar.md", { Path("/path/to/foobar.md"), }, ), ( "/path/to/foobar.txt", { Path("/path/to/foobar.txt"), }, ), ( "/path/to/foobar.txt.tar.gz", { Path("/path/to/foobar.txt.tar.gz"), }, ), ( "/path/to/file", { Path("/path/to/file-1"), Path("/path/to/file-2"), Path("/path/to/file-3"), Path("/path/to/file-4"), }, ), ( "/path/to/lorem", { Path("/path/to/lorem"), Path("/path/to/lorem-2"), Path("/path/to/lorem-3"), }, ), ( "/path/to/ipsum", { Path("/path/to/ipsum-3"), Path("/path/to/ipsum-8"), Path("/path/to/ipsum-9"), Path("/path/to/ipsum-12"), }, ), ( "/path/to/main.py", { Path("/path/to/main.py"), }, ), ], ) def test_should_filter_files_by_name_and_suffix( self, path, expected_siblings, fake_files ): file = NumberedFile.of(path) siblings = set(sibling.path for sibling in file.siblings) assert siblings == expected_siblings @pytest.mark.parametrize( "path, expected_siblings", [ ( "/path/to/foo-42", { Path("/path/to/foo"), Path("/path/to/foo-1"), Path("/path/to/foo-2"), }, ), ( "/path/to/foo-42.txt", { Path("/path/to/foo.txt"), Path("/path/to/foo-1.txt"), Path("/path/to/foo-2.txt"), Path("/path/to/foo-3.txt"), Path("/path/to/foo-4.txt"), }, ), ( "/path/to/foo-42.txt.tar.gz", { Path("/path/to/foo.txt.tar.gz"), Path("/path/to/foo-1.txt.tar.gz"), Path("/path/to/foo-2.txt.tar.gz"), }, ), ], ) def test_should_ignore_given_number( self, path, expected_siblings, fake_files ): file = NumberedFile.of(path) siblings = set(sibling.path for sibling in file.siblings) assert siblings == expected_siblings class TestSiblingsAscending: def test_should_return_list_of_numbered_files(self, fake_files): file = NumberedFile.of("/path/to/file") siblings_ascending = file.siblings_ascending assert isinstance(siblings_ascending, list) assert isinstance(siblings_ascending[0], NumberedFile) def test_should_be_empty_when_no_parent_dir(self, fake_files): file = NumberedFile.of("/no/such/path") assert file.siblings_ascending == [] def test_should_be_empty_when_no_such_file(self, fake_files): file = NumberedFile.of("/path/to/no-such-file") assert file.siblings_ascending == [] @pytest.mark.parametrize( "path, expected_siblings", [ ( "/path/to/foo", [ Path("/path/to/foo"), Path("/path/to/foo-1"), Path("/path/to/foo-2"), ], ), ( "/path/to/ipsum", [ Path("/path/to/ipsum-3"), Path("/path/to/ipsum-8"), Path("/path/to/ipsum-9"), Path("/path/to/ipsum-12"), ], ), ], ) def test_should_have_increasing_number( self, path: str, expected_siblings: list, fake_files ): file = NumberedFile.of(path) siblings_ascending = [ sibling.path for sibling in file.siblings_ascending ] assert siblings_ascending == expected_siblings class TestSiblingsDescending: def test_should_return_list_of_numbered_files(self, fake_files): file = NumberedFile.of("/path/to/file") siblings_descending = file.siblings_descending assert isinstance(siblings_descending, list) assert isinstance(siblings_descending[0], NumberedFile) def test_should_be_empty_when_no_parent_dir(self, fake_files): file = NumberedFile.of("/no/such/path") assert file.siblings_descending == [] def test_should_be_empty_when_no_such_file(self, fake_files): file = NumberedFile.of("/path/to/no-such-file") assert file.siblings_descending == [] @pytest.mark.parametrize( "path, expected_siblings", [ ( "/path/to/foo", [ Path("/path/to/foo-2"), Path("/path/to/foo-1"), Path("/path/to/foo"), ], ), ( "/path/to/ipsum", [ Path("/path/to/ipsum-12"), Path("/path/to/ipsum-9"), Path("/path/to/ipsum-8"), Path("/path/to/ipsum-3"), ], ), ], ) def test_should_have_decreasing_number( self, path: str, expected_siblings: list, fake_files ): file = NumberedFile.of(path) siblings_descending = [ sibling.path for sibling in file.siblings_descending ] assert siblings_descending == expected_siblings class TestOpenAll: def test_should_open_ascending_siblings( self, mocker: MockerFixture, fake_files ): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) expected_calls = [ call(Path("/path/to/foo.txt"), mode="r", encoding="utf-8"), call(Path("/path/to/foo-1.txt"), mode="r", encoding="utf-8"), call(Path("/path/to/foo-2.txt"), mode="r", encoding="utf-8"), call(Path("/path/to/foo-3.txt"), mode="r", encoding="utf-8"), call(Path("/path/to/foo-4.txt"), mode="r", encoding="utf-8"), ] for i, file in enumerate(open_all("/path/to/foo.txt", mode="r")): assert expected_calls[i] == mock_open.call_args def test_should_close_all_files_automatically( self, mocker: MockerFixture, fake_files ): mocker.patch("builtins.open", mocker.mock_open(read_data="fake data")) files = [] for file in open_all("/path/to/foo.txt", mode="r"): assert file.read() == "fake data" files.append(file) for file in files: file.close.assert_called() def test_should_open_in_read_mode_by_default( self, mocker: MockerFixture, fake_files ): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) for _ in enumerate(open_all("/path/to/foo.txt")): assert mock_open.call_args.kwargs["mode"] == "r" class TestOpenLatest: def test_read_no_such_file(self, mocker: MockerFixture, fake_files): mocker.patch.object(Path, "exists", side_effect=[False]) with pytest.raises(FileNotFoundError): open_latest("/path/to/no-such-file", mode="r") def test_write_no_such_file(self, mocker: MockerFixture, fake_files): mocker.patch("builtins.open", mocker.mock_open()) mocker.patch.object(Path, "exists", side_effect=[False]) open_latest("/path/to/no-such-file", mode="w") def test_read_existing_file(self, mocker: MockerFixture, fake_files): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) mocker.patch.object(Path, "exists", side_effect=[True]) open_latest("/path/to/file", mode="r") mock_open.assert_called_once_with( Path("/path/to/file-4"), mode="r", encoding="utf-8" ) def test_write_existing_file(self, mocker: MockerFixture, fake_files): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) mocker.patch.object(Path, "exists", side_effect=[True]) open_latest("/path/to/file", mode="w") mock_open.assert_called_once_with( Path("/path/to/file-4"), mode="w", encoding="utf-8" ) def test_should_open_in_append_mode_by_default( self, mocker: MockerFixture, fake_files ): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) for _ in enumerate(open_latest("/path/to/foo.txt")): assert mock_open.call_args.kwargs["mode"] == "a" class TestOpenNext: def test_read_no_such_file(self, mocker: MockerFixture, fake_files): mocker.patch.object(Path, "exists", return_value=False) with pytest.raises(FileNotFoundError): open_next("/path/to/no-such-file", mode="r") def test_write_no_such_file(self, mocker: MockerFixture, fake_files): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) mocker.patch.object(Path, "exists", return_value=False) open_next("/path/to/no-such-file", mode="w") mock_open.assert_called_once_with( Path("/path/to/no-such-file-1"), mode="w", encoding="utf-8" ) def test_read_existing_file(self, mocker: MockerFixture, fake_files): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) mocker.patch.object(Path, "exists", return_value=True) open_next("/path/to/file", mode="r") mock_open.assert_called_once_with( Path("/path/to/file-5"), mode="r", encoding="utf-8" ) def test_write_existing_file(self, mocker: MockerFixture, fake_files): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) mocker.patch.object(Path, "exists", return_value=True) open_next("/path/to/file", mode="w") mock_open.assert_called_once_with( Path("/path/to/file-5"), mode="w", encoding="utf-8" ) def test_should_open_in_write_mode_by_default( self, mocker: MockerFixture, fake_files ): mock_open = mocker.mock_open() mocker.patch("builtins.open", mock_open) for _ in enumerate(open_next("/path/to/foo.txt")): assert mock_open.call_args.kwargs["mode"] == "w"

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null

0

6

93da43f63fccb6f1298cf2f4dd5b80db2bce17f9

60

py

Python

dlmb/utils/__init__.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

5

2019-11-23T13:32:21.000Z

2022-01-01T16:32:48.000Z

dlmb/utils/__init__.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

null

dlmb/utils/__init__.py

Jonathan-Andrews/dlmb

552148bcac2ffb4308c8db24599c458652684ed2

[ "MIT" ]

null

from .function_helpers import * from .data_helpers import *

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6

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4,565

py

Python

mysite/polls/tests.py

z-gora/django-tutorial

8af9de5e4ce233767b2b6303de69bfea9d7c4df6

[ "MIT" ]

null

mysite/polls/tests.py

z-gora/django-tutorial

8af9de5e4ce233767b2b6303de69bfea9d7c4df6

[ "MIT" ]

null

mysite/polls/tests.py

z-gora/django-tutorial

8af9de5e4ce233767b2b6303de69bfea9d7c4df6

[ "MIT" ]

null

import datetime from django.test import TestCase from django.utils import timezone from django.urls import reverse from .models import Question # Create your tests here. class QuestionModelTests(TestCase): def test_was_published_recently_with_future_question(self): time = timezone.now() + datetime.timedelta(days=30) future_question = Question(pub_date=time) self.assertIs(future_question.was_published_recently(), False) def test_was_published_recently_with_recent_question(self): time = timezone.now() + datetime.timedelta(minutes=-10) future_question = Question(pub_date=time) self.assertIs(future_question.was_published_recently(), True) def test_was_published_recently_with_old_question(self): time = timezone.now() + datetime.timedelta(days=-30) future_question = Question(pub_date=time) self.assertIs(future_question.was_published_recently(), False) def create_question(question_text, days): time = timezone.now() + datetime.timedelta(days=days) return Question.objects.create(question_text=question_text, pub_date=time) class QuestionIndexViewTest(TestCase): def test_no_questions(self): # No questions in the database response = self.client.get(reverse("polls:index")) self.assertEqual(response.status_code, 200) self.assertContains(response, "No polls are available") self.assertQuerysetEqual(response.context['latest_question_list'], []) def test_past_question(self): # Questions with pub_date in the past should be displayed create_question(question_text="Past question", days=-30) response = self.client.get(reverse("polls:index")) self.assertContains(response, "Past question") self.assertQuerysetEqual( response.context['latest_question_list'], ['<Question: Past question>'] ) def test_future_question(self): # Questions with pub_date in the future should not be displayed create_question(question_text="Future question", days=30) response = self.client.get(reverse("polls:index")) self.assertContains(response, "No polls are available") self.assertQuerysetEqual(response.context['latest_question_list'], []) def test_future_and_past_question(self): # ONLY past questions are displayed create_question(question_text="Past question", days=-30) create_question(question_text="Future question", days=30) response = self.client.get(reverse("polls:index")) self.assertContains(response, "Past question") self.assertQuerysetEqual( response.context['latest_question_list'], ['<Question: Past question>'] ) def test_future_and_past_question(self): # ONLY past questions are displayed create_question(question_text="Past question 1", days=-20) create_question(question_text="Past question 2", days=-30) response = self.client.get(reverse("polls:index")) self.assertContains(response, "Past question 1") self.assertContains(response, "Past question 2") self.assertQuerysetEqual( response.context['latest_question_list'], ['<Question: Past question 1>', '<Question: Past question 2>'] ) class QuestionDetailViewTest(TestCase): def test_future_question(self): future_question = create_question(question_text="Past question", days=30) url = reverse('polls:detail', args=(future_question.id,)) response = self.client.get(url) self.assertEqual(response.status_code,404) def test_past_question(self): future_question = create_question(question_text="Future question", days=-30) url = reverse('polls:detail', args=(future_question.id,)) response = self.client.get(url) self.assertContains(response, future_question.question_text) class QuestionResultsViewTest(TestCase): def test_future_question(self): future_question = create_question(question_text="Past question", days=30) url = reverse('polls:results', args=(future_question.id,)) response = self.client.get(url) self.assertEqual(response.status_code,404) def test_past_question(self): future_question = create_question(question_text="Future question", days=-30) url = reverse('polls:results', args=(future_question.id,)) response = self.client.get(url) self.assertContains(response, future_question.question_text)

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0

null

0

1

0

null

0

6

93fb51a815e78253510f821d1020e6d0059996b6

774

py

Python

octicons16px/telescope.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

1

2021-01-28T06:47:39.000Z

octicons16px/telescope.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

null

octicons16px/telescope.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

null

OCTICON_TELESCOPE = """ <svg class="octicon octicon-telescope" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" width="16" height="16"><path fill-rule="evenodd" d="M14.184 1.143a1.75 1.75 0 00-2.502-.57L.912 7.916a1.75 1.75 0 00-.53 2.32l.447.775a1.75 1.75 0 002.275.702l11.745-5.656a1.75 1.75 0 00.757-2.451l-1.422-2.464zm-1.657.669a.25.25 0 01.358.081l1.422 2.464a.25.25 0 01-.108.35l-2.016.97-1.505-2.605 1.85-1.26zM9.436 3.92l1.391 2.41-5.42 2.61-.942-1.63 4.97-3.39zM3.222 8.157l-1.466 1a.25.25 0 00-.075.33l.447.775a.25.25 0 00.325.1l1.598-.769-.83-1.436zm6.253 2.306a.75.75 0 00-.944-.252l-1.809.87a.75.75 0 00-.293.253L4.38 14.326a.75.75 0 101.238.848l1.881-2.75v2.826a.75.75 0 001.5 0v-2.826l1.881 2.75a.75.75 0 001.238-.848l-2.644-3.863z"></path></svg> """

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6

9e19e9d4e4f219dbdbcd2bdc903af06f06bde4a6

19,029

py

Python

cloud_userInfo.py

Christopherfwz/YourGuide

425654d285b656980a395e20f0f8323baea2dc16

[ "MIT" ]

null

cloud_userInfo.py

Christopherfwz/YourGuide

425654d285b656980a395e20f0f8323baea2dc16

[ "MIT" ]

null

cloud_userInfo.py

Christopherfwz/YourGuide

425654d285b656980a395e20f0f8323baea2dc16

[ "MIT" ]

null

# coding: utf-8 # import datetime import leancloud import re from django.core.wsgi import get_wsgi_application from leancloud import Engine from leancloud import LeanEngineError import datetime import requests import json cloud_userInfo = Engine(get_wsgi_application()) @cloud_userInfo.define def getUserInfo(**params): try: id = params.get('id') except: raise LeanEngineError(501, 'Invalid argument.') # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(id) user.fetch() avatar = user.get("avatar") nickname = user.get("nickname") city = user.get("city") level = user.get("level") intro = user.get("introduction") is_guide = user.get("is_guide") if avatar: avatar_url = avatar.url else: avatar_url = None # 查询该用户的游记 TravelNote = leancloud.Object.extend("TravelNote") query = TravelNote.query query.equal_to("author", user) query_list = query.find() moments = [] for j in query_list: pics = [] content = j.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(j.get("author").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None # 查询comment数量 Comment = leancloud.Object.extend("Comment") query = Comment.query query.equal_to("travelNote", j) query_list = query.find() commentNum = len(query_list) moments.append({ "id": str(j.id), "image": pics[0], "title": j.get("title"), "nickname": user.get("nickname"), "avatar": avatar_url, "favNum": j.get("like"), "replyNum": commentNum, "price": j.get("spend"), "date": j.get("createdAt").strftime("%Y-%m-%d %H:%M:%S"), }) favorites = [] TravelNoteFav = leancloud.Object.extend("TravelNoteFav") query = TravelNoteFav.query query.equal_to("favUser", user) query_list = query.find() for j in query_list: pics = [] travelNote = TravelNote.create_without_data(j.get("TravelNote").id) travelNote.fetch() content = travelNote.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(travelNote.get("author").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None # 查询comment数量 Comment = leancloud.Object.extend("Comment") query = Comment.query query.equal_to("travelNote", travelNote) query_list = query.find() commentNum = len(query_list) favorites.append({ "id": str(travelNote.id), "image": pics[0], "title": travelNote.get("title"), "nickname": user.get("nickname"), "avatar": avatar_url, "favNum": travelNote.get("like"), "replyNum": commentNum, "price": travelNote.get("spend"), "date": travelNote.get("createdAt").strftime("%Y-%m-%d %H:%M:%S"), }) result = { "avatar": avatar_url, "nickname": nickname, "city": city, "level": level, "intro": intro, "is_guide": is_guide, "moments": moments, "favorites": favorites, } return result @cloud_userInfo.define def getReceivedLike(**params): current_user = cloud_userInfo.current.user if not current_user: raise LeanEngineError("401", "Unauthorized") try: page = params.get('page') except: raise LeanEngineError(501, 'Invalid argument.') array = [] # 查询我的游记 TravelNote = leancloud.Object.extend("TravelNote") query = TravelNote.query query.equal_to("author", current_user) query_list = query.find() # j是游记 for j in query_list: # 这篇游记的图片、标题、发布时间 title = j.get("title") publishTime = j.get("createdAt") pics = [] content = j.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询谁赞了这篇游记 TravelNoteLike = leancloud.Object.extend("TravelNoteLike") query = TravelNoteLike.query query.equal_to("TravelNote", j) query_list1 = query.find() # k是赞了游记的记录 for k in query_list1: # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(k.get("likeUser").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None array.append({ "id": str(k.id), # 赞的id "image": pics[0], # 你游记的图片，或者你评论的那个游记的图片， "title": title, # 同上的那个游记的标题 "nickname": user.get("nickname"), # 赞的人的名字， "avatar": avatar_url, # 赞的人的头像 "time": k.get("createdAt").strftime("%Y-%m-%d %H:%M:%S"), # 赞的时间 "publishTime": publishTime.strftime("%Y-%m-%d %H:%M:%S"), # 同上的那个游记的发布时间 "type": 0, # 0为赞了游记，1为赞了评论 "comment": None }) # 查询我的评论 Comment = leancloud.Object.extend("Comment") query = Comment.query query.equal_to("comment_user", current_user) query_list = query.find() # j是评论 for j in query_list: # 我的评论的内容 content = j.get("content") # 我评论的游记 travelNote = TravelNote.create_without_data(j.get("TravelNote").id) travelNote.fetch() # 这篇游记的图片、标题、发布时间 title = travelNote.get("title") publishTime = travelNote.get("createdAt") pics = [] content = travelNote.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询谁赞了这个评论 CommentLike = leancloud.Object.extend("CommentLike") query = CommentLike.query query.equal_to("comment", j) query_list1 = query.find() # k是赞了评论的记录 for k in query_list1: # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(k.get("likeUser").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None array.append({ "id": str(k.id), # 赞的id "image": pics[0], # 你游记的图片，或者你评论的那个游记的图片， "title": title, # 同上的那个游记的标题 "nickname": user.get("nickname"), # 赞的人的名字， "avatar": avatar_url, # 赞的人的头像 "time": k.get("createdAt").strftime("%Y-%m-%d %H:%M:%S"), # 赞的时间 "publishTime": publishTime.strftime("%Y-%m-%d %H:%M:%S"), # 同上的那个游记的发布时间 "type": 1, # 0为赞了游记，1为赞了评论 "comment": content }) result = { "next": -1, "array": array, } return result @cloud_userInfo.define def getReceivedComment(**params): current_user = cloud_userInfo.current.user if not current_user: raise LeanEngineError("401", "Unauthorized") try: page = params.get('page') except: raise LeanEngineError(501, 'Invalid argument.') array = [] # 查询我的游记 TravelNote = leancloud.Object.extend("TravelNote") query = TravelNote.query query.equal_to("author", current_user) query_list = query.find() # j是游记 for j in query_list: # 这篇游记的图片、标题、发布时间 title = j.get("title") publishTime = j.get("createdAt") pics = [] content = j.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询谁评论了这篇游记 Comment = leancloud.Object.extend("Comment") query = Comment.query query.equal_to("TravelNote", j) query_list1 = query.find() # k是评论了游记的记录 for k in query_list1: # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(k.get("comment_user").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None array.append({ "id": str(k.id), # 评论的id "image": pics[0], # 你游记的图片，或者你评论的那个游记的图片， "title": title, # 同上的那个游记的标题 "nickname": user.get("nickname"), # 评论的人的名字， "avatar": avatar_url, # 评论的人的头像 "time": k.get("createdAt").strftime("%Y-%m-%d %H:%M:%S"), # 评论的时间 "publishTime": publishTime.strftime("%Y-%m-%d %H:%M:%S"), # 同上的那个游记的发布时间 "comment": k.get("content") }) result = { "next": -1, "array": array, } return result @cloud_userInfo.define def getGuideInfo(**params): try: id = params.get('id') # 用户id，是user的objectId，不是导游表的id except: raise LeanEngineError(501, 'Invalid argument.') # 根据用户id查询用户 User = leancloud.Object.extend("_User") user = User.create_without_data(id) user.fetch() # 根据用户查询导游信息 Guide = leancloud.Object.extend("Guide") query = Guide.query query.equal_to("user", user) query_list = query.find() # i是导游 for i in query_list: guide_id = i.id # 导游id labels = [] features = i.get("features") sightseeings = [] about = i.get("about") # 根据导游id查询导游标签 GuideNeedTagMap = leancloud.Object.extend("GuideNeedTagMap") query = GuideNeedTagMap.query query.equal_to("guide", i) query_list = query.find() # j是导游标签map的条目 for j in query_list: GuideNeedTag = leancloud.Object.extend("GuideNeedTag") guideNeedTag = GuideNeedTag.create_without_data(j.get("guideNeedTag").id) guideNeedTag.fetch() labels.append(guideNeedTag.get("name")) # 根据导游id查询导游熟悉景点 GuideAttractionMap = leancloud.Object.extend("GuideAttractionMap") query = GuideAttractionMap.query query.equal_to("guide", i) query_list = query.find() # j是导游熟悉景点map的条目 for j in query_list: Attraction = leancloud.Object.extend("Attraction") attraction = Attraction.create_without_data(j.get("attraction").id) attraction.fetch() sightseeings.append(attraction.get("title")) # 查询该导游的相关游记 TravelNote = leancloud.Object.extend("TravelNote") query = TravelNote.query query.equal_to("guide", i) query_list = query.find() travel_notes = [] for j in query_list: pics = [] content = j.get("content") if content != None: # picUrls_pre = re.findall('!\[.*?\]$.*?$', str(i.get("content"))) #MD的正则表达式 picUrls_pre = re.findall('<img.*?>', content) # html的提取img标签的正则表达式 else: picUrls_pre = [] # for url in picUrls_pre: # print url # c = re.compile('\]$.*?$', re.S) # v = c.findall(url)[0] # pics.append(v[2:-1]) # 读取src中的url，放在pics里 for group in picUrls_pre: match_obj = re.search('src="(.*?)"', group) picUrls = match_obj.groups() pics = list(picUrls) if len(pics) == 0: pics.append("http://lc-vqwqjioq.cn-n1.lcfile.com/72a3304b67086be0c5bd.jpg") # 查询author信息 User = leancloud.Object.extend("_User") user = User.create_without_data(j.get("author").id) user.fetch() avatar = user.get("avatar") if avatar: avatar_url = avatar.url else: avatar_url = None # 查询comment数量 Comment = leancloud.Object.extend("Comment") query = Comment.query query.equal_to("travelNote", j) query_list = query.find() commentNum = len(query_list) travel_notes.append({ "id": str(j.id), "image": pics[0], "title": j.get("title"), "nickname": user.get("username"), "avatar": avatar_url, "favNum": j.get("like"), "replyNum": commentNum, "price": j.get("spend"), "date": [j.get("startDate").strftime("%Y-%m-%d %H:%M:%S"), j.get("endDate").strftime("%Y-%m-%d %H:%M:%S")] }) result = { "labels": labels, "features": features, "sightseeings": sightseeings, "about": about, "travel_notes": travel_notes } return result @cloud_userInfo.define def editUserInfo(**params): current_user = cloud_userInfo.current.user if not current_user: raise LeanEngineError("401", "Unauthorized") try: filed = params.get('filed') data = params.get('data') except: raise LeanEngineError(501, 'Invalid argument.') try: current_user.set(filed, data) current_user.save() except: return { "status": -1, "message": '字段不存在或无权限修改', } return { "status": 0, } @cloud_userInfo.define def getFullInfo(**params): current_user = cloud_userInfo.current.user if not current_user: raise LeanEngineError("401", "Unauthorized") phone = current_user.get("mobilePhoneNumber") nickname = current_user.get("nickname") introduction = current_user.get("introduction") user = { "phone": phone, "nickname": nickname, "introduction": introduction, } is_guide = current_user.get("is_guide") guide = {} # 根据用户查询导游信息 Guide = leancloud.Object.extend("Guide") query = Guide.query query.equal_to("user", current_user) query_list = query.find() # i是导游 for i in query_list: guide_id = i.id # 导游id introduction = i.get("about") max_num = i.get("max_num") price = i.get("price") city = i.get("area") sightseeings = [] sightseeing_names = [] features = i.get("features") # 根据导游id查询导游熟悉景点 GuideAttractionMap = leancloud.Object.extend("GuideAttractionMap") query = GuideAttractionMap.query query.equal_to("guide", i) query_list = query.find() # j是导游熟悉景点map的条目 for j in query_list: Attraction = leancloud.Object.extend("Attraction") attraction = Attraction.create_without_data(j.get("attraction").id) attraction.fetch() sightseeings.append(attraction.id) sightseeing_names.append(attraction.get("title")) guide = { "is_open": is_guide, "introduction": introduction, "max_num": max_num, "price": price, "city": city, "sightseeings": sightseeings, "sightseeing_names": sightseeing_names, "features": features } break result = { "user": user, "guide": guide } return result

31.767947

122

0.533607

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19,029

5.109913

0.108372

0.030154

0.059101

0.029048

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0.715951

0.709318

0.704392

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0.326344

19,029

598

123

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null

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1

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null

0

6

f5587844b5ba1dcfdbc30a62bd524ab8b0478223

1,104

py

Python

part3/ex05-exercise/answer01a.py

abasu1007/intro-to-python

f6978816c3020860b74219a1bfe191aea8e4e75f

[ "CC-BY-4.0" ]

13

2015-05-11T06:20:24.000Z

2017-04-13T19:47:54.000Z

part3/ex05-exercise/answer01a.py

PythonWorkshop/intro-to-python

9f8ad86e42e40d059877fd234fb160602e8907ac

[ "CC-BY-4.0" ]

null

part3/ex05-exercise/answer01a.py

PythonWorkshop/intro-to-python

9f8ad86e42e40d059877fd234fb160602e8907ac

[ "CC-BY-4.0" ]

10

2016-04-16T19:28:22.000Z

2018-06-15T14:56:57.000Z

# Script that wishes happy birthday to Wolfe+585, Senior # http://en.wikipedia.org/wiki/Wolfe+585,_Senior def happy_birthday(name): print("Happy Birthday, dear " + name + "!") # This guy is a real-life test case for name fields happy_birthday("Adolph Blaine Charles David Earl Frederick Gerald Hubert Irvin John Kenneth Lloyd Martin Nero Oliver Paul Quincy Randolph Sherman Thomas Uncas Victor William Xerxes Yancy Zeus Wolfeschlegelsteinhausenbergerdorffvoralternwarengewissenhaftschaferswessenschafewarenwohlgepflegeundsorgfaltigkeitbeschutzenvonangreifendurchihrraubgierigfeindewelchevoralternzwolftausendjahresvorandieerscheinenwanderersteerdemenschderraumschiffgebrauchlichtalsseinursprungvonkraftgestartseinlangefahrthinzwischensternartigraumaufdersuchenachdiesternwelchegehabtbewohnbarplanetenkreisedrehensichundwohinderneurassevonverstandigmenschlichkeitkonntefortplanzenundsicherfreuenanlebenslanglichfreudeundruhemitnichteinfurchtvorangreifenvonandererintelligentgeschopfsvonhinzwischensternartigraum, Senior")

110.4

868

0.84058

219

1,104

4.570776

0.538813

0.01998

0.024975

0.053946

0

0.005786

0.060688

1,104

9

869

122.666667

0.88621

0.136775

0

0.333333

0.918862

0.702845

0

1

0.333333

false

0

0.333333

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null

0

1

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1

0

1

null

0

1

0

6

f577921775e8fab37d96397ea2b596f1ccc9b103

121

py

Python

wingline/pingpong.py

HappyEinara/wingline

08d67ad9f58c869c385f954def6af5fa92e968ff

[ "MIT" ]

null

wingline/pingpong.py

HappyEinara/wingline

08d67ad9f58c869c385f954def6af5fa92e968ff

[ "MIT" ]

null

wingline/pingpong.py

HappyEinara/wingline

08d67ad9f58c869c385f954def6af5fa92e968ff

[ "MIT" ]

null

"""A basic placeholder to stand in for initial tests.""" def ping() -> str: """Return "pong".""" return "pong"

17.285714

56

0.586777

16

121

4.4375

0.875

0.28169

0

0.223141

121

6

57

20.166667

0.755319

0.53719

0

0.088889

0

1

0.5

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

f58bb1e8b1d66ce85d31cc31bed1c82466bca700

42

py

Python

mlxgtools/ml/__init__.py

gdtydm/mlxgtools

542eada8837f69a35b5694a926e90dabcc1d4323

[ "Apache-2.0" ]

null

mlxgtools/ml/__init__.py

gdtydm/mlxgtools

542eada8837f69a35b5694a926e90dabcc1d4323

[ "Apache-2.0" ]

null

mlxgtools/ml/__init__.py

gdtydm/mlxgtools

542eada8837f69a35b5694a926e90dabcc1d4323

[ "Apache-2.0" ]

null

from .cv import PurgedGroupTimeSeriesSplit

42

0.904762

4

42

9.5

1

0

0.071429

42

1

42

0.974359

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f59ac154c5980ef8f4572e7767e9ae22addf9fa3

33

py

Python

public/testpython.py

mekimeki/MiddleBack

e371c67bf99f503621eb4091b4d6123ae87b9bbe

[ "MIT" ]

null

public/testpython.py

mekimeki/MiddleBack

e371c67bf99f503621eb4091b4d6123ae87b9bbe

[ "MIT" ]

null

public/testpython.py

mekimeki/MiddleBack

e371c67bf99f503621eb4091b4d6123ae87b9bbe

[ "MIT" ]

null

import sys print("hello world")

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py

Python

pytorch/utils/vcl.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

pytorch/utils/vcl.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

pytorch/utils/vcl.py

goldfarbDave/vcl

24fb33a1dcadfa6c6cf5e9e9838b64f4fd23143a

[ "Apache-2.0" ]

null

import numpy as np from utils.mobile_net_v2_vanilla import mobilenetv2_vanilla from utils.mobile_net_v2_bayesian import mobilenetv2_bayesian import utils.test as test from utils.multihead_models import Vanilla_NN, Vanilla_CNN, MFVI_NN, MFVI_CNN from . import flags import utils.GAN as GAN import torch device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") try: from torchviz import make_dot, make_dot_from_trace except ImportError: print("Torchviz was not found.") def run_vcl(hidden_size, no_epochs, data_gen, coreset_method, coreset_size=0, batch_size=None, single_head=True, gan_bol = False, is_toy=False, use_lrt=False): in_dim, out_dim = data_gen.get_dims() x_coresets, y_coresets = [], [] x_testsets, y_testsets = [], [] x_trainsets, y_trainsets = [], [] gans = [] all_acc = np.array([]) for task_id in range(data_gen.max_iter): print('Current task: '+str(task_id)) x_train, y_train, x_test, y_test = data_gen.next_task() x_testsets.append(x_test) y_testsets.append(y_test) x_trainsets.append(x_train) y_trainsets.append(y_train) # Set the readout head to train head = 0 if single_head else task_id bsize = x_train.shape[0] if (batch_size is None) else batch_size # Train network with maximum likelihood to initialize first model if task_id == 0: print_graph_bol = False #set to True if you want to see the graph if(is_toy): ml_model = Vanilla_NN(in_dim, hidden_size, out_dim, x_train.shape[0], learning_rate=0.005) else: ml_model = Vanilla_NN(in_dim, hidden_size, out_dim, x_train.shape[0]) # train for first task ml_model.train(x_train, y_train, task_id, no_epochs, bsize) # updated weights of network after SGD on task 1 -- these are means of posterior distribution of weights after task 1 ==> new prior for task 2 mf_weights = ml_model.get_weights() # use these weights to initialise weights of new task model mf_model = MFVI_NN(in_dim, hidden_size, out_dim, x_train.shape[0], single_head = single_head, prev_means=mf_weights, LRT=use_lrt) if not gan_bol: if coreset_size > 0: x_coresets, y_coresets, x_train, y_train = coreset_method(x_coresets, y_coresets, x_train, y_train, coreset_size) gans = None if print_graph_bol: #Just if you want to see the computational graph output_tensor = mf_model._KL_term() #mf_model.get_loss(torch.Tensor(x_train).to(device), torch.Tensor(y_train).to(device), task_id), params=params) print_graph(mf_model, output_tensor) print_graph_bol = False if gan_bol: gan_i = GAN.VGR(task_id) gan_i.train(x_train, y_train) gans.append(gan_i) mf_model.train(x_train, y_train, head, no_epochs, bsize) mf_model.update_prior() # Save weights before test (and last-minute training on coreset mf_model.save_weights() acc = test.get_scores(mf_model, x_trainsets, y_trainsets, x_testsets, y_testsets, no_epochs, single_head, x_coresets, y_coresets, batch_size, False,gans, is_toy=is_toy) all_acc = test.concatenate_results(acc, all_acc) mf_model.load_weights() mf_model.clean_copy_weights() if not single_head: mf_model.create_head() return all_acc def run_vcl_cnn(input_dims, hidden_size, output_dims, no_epochs, data_gen, coreset_method, coreset_size=0, batch_size=None, single_head=True, gan_bol = False, is_toy=False, use_lrt=False, is_cifar=False): in_dim, out_dim = data_gen.get_dims() x_coresets, y_coresets = [], [] x_testsets, y_testsets = [], [] x_trainsets, y_trainsets = [], [] gans = [] all_acc = np.array([]) for task_id in range(data_gen.max_iter): print('Current task: '+str(task_id)) x_train, y_train, x_test, y_test = data_gen.next_task() x_testsets.append(x_test) y_testsets.append(y_test) x_trainsets.append(x_train) y_trainsets.append(y_train) # Set the readout head to train head = 0 if single_head else task_id bsize = x_train.shape[0] if (batch_size is None) else batch_size # Train network with maximum likelihood to initialize first model if task_id == 0: print_graph_bol = False #set to True if you want to see the graph if(is_toy): ml_model = Vanilla_CNN(input_dims, hidden_size, output_dims, x_train.shape[0], learning_rate=0.005, is_cifar=is_cifar) else: ml_model = Vanilla_CNN(input_dims, hidden_size, output_dims, x_train.shape[0],is_cifar=is_cifar) # train for first task ml_model.train(x_train, y_train, task_id, no_epochs, bsize) # updated weights of network after SGD on task 1 -- these are means of posterior distribution of weights after task 1 ==> new prior for task 2 mf_weights = ml_model.get_weights() # use these weights to initialise weights of new task model if(is_cifar): mf_model = MFVI_CNN(input_dims, hidden_size, output_dims, x_train.shape[0], single_head = single_head, prev_means=mf_weights, LRT=use_lrt, is_cifar=is_cifar, learning_rate=0.01) else: mf_model = MFVI_CNN(input_dims, hidden_size, output_dims, x_train.shape[0], single_head = single_head, prev_means=mf_weights, LRT=use_lrt, is_cifar=is_cifar) if not gan_bol: if coreset_size > 0: x_coresets, y_coresets, x_train, y_train = coreset_method(x_coresets, y_coresets, x_train, y_train, coreset_size) gans = None if print_graph_bol: #Just if you want to see the computational graph output_tensor = mf_model._KL_term() #mf_model.get_loss(torch.Tensor(x_train).to(device), torch.Tensor(y_train).to(device), task_id), params=params) print_graph(mf_model, output_tensor) print_graph_bol = False if gan_bol: gan_i = GAN.VGR(task_id) gan_i.train(x_train, y_train) gans.append(gan_i) mf_model.train(x_train, y_train, head, no_epochs, bsize) mf_model.update_prior() # Save weights before test (and last-minute training on coreset mf_model.save_weights() acc = test.get_scores(mf_model, x_trainsets, y_trainsets, x_testsets, y_testsets, no_epochs, single_head, x_coresets, y_coresets, batch_size, False,gans, is_toy=is_toy) all_acc = test.concatenate_results(acc, all_acc) mf_model.load_weights() mf_model.clean_copy_weights() if not single_head: mf_model.create_head() return all_acc def run_coreset_only(hidden_size, no_epochs, data_gen, coreset_method, coreset_size=0, batch_size=None, single_head=True): in_dim, out_dim = data_gen.get_dims() x_coresets, y_coresets = [], [] x_testsets, y_testsets = [], [] x_trainsets, y_trainsets = [], [] all_acc = np.array([]) for task_id in range(data_gen.max_iter): x_train, y_train, x_test, y_test = data_gen.next_task() x_testsets.append(x_test) y_testsets.append(y_test) x_trainsets.append(x_train) y_trainsets.append(y_train) head = 0 if single_head else task_id bsize = x_train.shape[0] if (batch_size is None) else batch_size if task_id == 0: mf_model = MFVI_NN(in_dim, hidden_size, out_dim, x_train.shape[0], single_head = single_head, prev_means=None) if coreset_size > 0: x_coresets, y_coresets, x_train, y_train = coreset_method(x_coresets, y_coresets, x_train, y_train, coreset_size) mf_model.save_weights() acc = test.get_scores(mf_model, x_trainsets, y_trainsets, x_testsets, y_testsets, no_epochs, single_head, x_coresets, y_coresets, batch_size, just_vanilla =False) all_acc = test.concatenate_results(acc, all_acc) mf_model.load_weights() mf_model.clean_copy_weights() if not single_head: mf_model.create_head() return all_acc def run_vcl_cifar(no_epochs, data_gen, coreset_method, coreset_size=0, batch_size=None, single_head=True, gan_bol = False, use_lrt=False, device="cpu"): x_coresets, y_coresets = [], [] x_testsets, y_testsets = [], [] x_trainsets, y_trainsets = [], [] gans = [] all_acc = np.array([]) in_dim, out_dim = data_gen.get_dims() for task_id in range(data_gen.max_iter): print('Current task: '+str(task_id)) x_train, y_train, x_test, y_test = data_gen.next_task() x_testsets.append(x_test) y_testsets.append(y_test) x_trainsets.append(x_train) y_trainsets.append(y_train) # Set the readout head to train head = 0 if single_head else task_id bsize = x_train.shape[0] if (batch_size is None) else batch_size cur_acc = 0 # Train network with maximum likelihood to initialize first model if task_id == 0: print_graph_bol = False #set to True if you want to see the graph ml_model = mobilenetv2_vanilla(device=device, num_classes=out_dim) ml_model.to(device=device) # train for first task ml_model.train(x_train, y_train, task_id, no_epochs, bsize) pred_means = [] pred=torch.argmax(ml_model.prediction_prob(torch.Tensor(x_test).to(device=device), None), dim=1) y_labs = torch.Tensor(y_test).type(torch.LongTensor).to(device=device) print(pred.shape, y_labs.shape) # # # Loop over all batches # for i in range(len(x_test)//bsize): # start_ind = i*bsize # end_ind = np.min([(i+1)*bsize, len(x_test)]) # batch_x_test = torch.Tensor(x_test[start_ind:end_ind, :]).to(device = device) # batch_y_test = torch.Tensor(y_test[start_ind:end_ind]).type(torch.LongTensor).to(device = device) # pred = ml_model.prediction_prob(batch_x_test, head) # # pred_mean = pred.mean(0) # pred_means.extend(list(pred.detach().cpu().numpy())) # # pred_y = torch.argmax(pred_mean, dim=0) # # cur_acc += end_ind - start_ind-(pred_y - batch_y_test).nonzero().shape[0] print(sum(pred==y_labs)/len(y_labs)) # cur_acc = float(cur_acc) # cur_acc /= len(x_test) # print(cur_acc) # acc.append(cur_acc) # print("Accuracy is {}".format(cur_acc)) # updated weights of network after SGD on task 1 -- these are means of posterior distribution of weights after task 1 ==> new prior for task 2 mf_weights = ml_model.get_weights_for_bayesian() # use these weights to initialise weights of new task model mf_model = mobilenetv2_bayesian(device=device, num_classes=out_dim, prev_means=mf_weights) mf_model.to(device=device) if not gan_bol: if coreset_size > 0: x_coresets, y_coresets, x_train, y_train = coreset_method(x_coresets, y_coresets, x_train, y_train, coreset_size) gans = None if print_graph_bol: #Just if you want to see the computational graph output_tensor = mf_model._KL_term() #mf_model.get_loss(torch.Tensor(x_train).to(device), torch.Tensor(y_train).to(device), task_id), params=params) print_graph(mf_model, output_tensor) print_graph_bol = False if gan_bol: gan_i = GAN.VGR(task_id) gan_i.train(x_train, y_train) gans.append(gan_i) mf_model.train(x_train, y_train, head, no_epochs, bsize) for ind_test, x_test_ in enumerate(x_testsets): print('Task:'+str(ind_test)) pred=torch.argmax(mf_model.prediction_prob(torch.Tensor(x_test_).to(device=device), head).squeeze(0), dim=1) y_labs = torch.Tensor(y_testsets[ind_test]).type(torch.LongTensor).to(device=device) print(pred.shape, y_labs.shape) # # # Loop over all batches # for i in range(len(x_test)//bsize): # start_ind = i*bsize # end_ind = np.min([(i+1)*bsize, len(x_test)]) # batch_x_test = torch.Tensor(x_test[start_ind:end_ind, :]).to(device = device) # batch_y_test = torch.Tensor(y_test[start_ind:end_ind]).type(torch.LongTensor).to(device = device) # pred = ml_model.prediction_prob(batch_x_test, head) # # pred_mean = pred.mean(0) # pred_means.extend(list(pred.detach().cpu().numpy())) # # pred_y = torch.argmax(pred_mean, dim=0) # # cur_acc += end_ind - start_ind-(pred_y - batch_y_test).nonzero().shape[0] print(sum(pred==y_labs)/len(y_labs)) print(len(x_testsets), len(y_testsets)) mf_model.update_prior() # Save weights before test (and last-minute training on coreset) mf_model.save_weights() # acc = test.get_scores(mf_model, x_trainsets, y_trainsets, x_testsets, y_testsets, no_epochs, single_head, x_coresets, y_coresets, batch_size, False,gans) # all_acc = test.concatenate_results(acc, all_acc) mf_model.load_weights() if not single_head: mf_model.create_head() return None # return all_acc def print_graph(model, output): params = dict() for i in range(len(model.W_m)): params["W_m{}".format(i)] = model.W_m[i] params["W_v{}".format(i)] = model.W_v[i] params["b_m{}".format(i)] = model.b_m[i] params["b_v{}".format(i)] = model.b_v[i] params["prior_W_m".format(i)] = model.prior_W_m[i] params["prior_W_v".format(i)] = model.prior_W_v[i] params["prior_b_m".format(i)] = model.prior_b_m[i] params["prior_b_v".format(i)] = model.prior_b_v[i] for i in range(len(model.W_last_m)): params["W_last_m".format(i)] = model.W_last_m[i] params["W_last_v".format(i)] = model.W_last_v[i] params["b_last_m".format(i)] = model.b_last_m[i] params["b_last_v".format(i)] = model.b_last_v[i] params["prior_W_last_m".format(i)] = model.prior_W_last_m[i] params["prior_W_last_v".format(i)] = model.prior_W_last_v[i] params["prior_b_last_m".format(i)] = model.prior_b_last_m[i] params["prior_b_last_v".format(i)] = model.prior_b_last_v[i] dot = make_dot(output, params=params) dot.view() return

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195389e20c88d6e537f3a8199a8cfd489bb3b221

65

py

Python

tests/test_modules/test_modules.py

aaron-parsons/pymalcolm

4e7ebd6b09382ab7e013278a81097d17873fa5c4

[ "Apache-2.0" ]

11

2016-10-04T23:11:39.000Z

2022-01-25T15:44:43.000Z

tests/test_modules/test_modules.py

aaron-parsons/pymalcolm

4e7ebd6b09382ab7e013278a81097d17873fa5c4

[ "Apache-2.0" ]

153

2016-06-01T13:31:02.000Z

2022-03-31T11:17:18.000Z

tests/test_modules/test_modules.py

aaron-parsons/pymalcolm

4e7ebd6b09382ab7e013278a81097d17873fa5c4

[ "Apache-2.0" ]

16

2016-06-10T13:45:27.000Z

2020-10-24T13:45:04.000Z

import unittest class TestModules(unittest.TestCase): pass

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1992a2d6ffa2d5b2e779e0d40b406d5b32cecc61

138

py

Python

python/pySimE/space/exp/pykep/example2.py

ProkopHapala/SimpleSimulationEngine

240f9b7e85b3a6eda7a27dc15fe3f7b8c08774c5

[ "MIT" ]

26

2016-12-04T04:45:12.000Z

2022-03-24T09:39:28.000Z

python/pySimE/space/exp/pykep/example2.py

Aki78/FlightAI

9c5480f2392c9c89b9fee4902db0c4cde5323a6c

[ "MIT" ]

null

python/pySimE/space/exp/pykep/example2.py

Aki78/FlightAI

9c5480f2392c9c89b9fee4902db0c4cde5323a6c

[ "MIT" ]

2

2019-02-09T12:31:06.000Z

2019-04-28T02:24:50.000Z

# -*- coding: utf-8 -*- from PyKEP import * #kep_examples.run_example1() #kep_examples.run_example2() #kep_examples.run_example3()

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153

py

Python

core/__init__.py

macrat/macracoin

a5267c4b3b9f812378af059562676dc5e7cb320e

[ "MIT" ]

null

core/__init__.py

macrat/macracoin

a5267c4b3b9f812378af059562676dc5e7cb320e

[ "MIT" ]

null

core/__init__.py

macrat/macracoin

a5267c4b3b9f812378af059562676dc5e7cb320e

[ "MIT" ]

null

from core.block import Block, mining from core.chain import Chain from core.message import Message from core.user import User from core.errors import *

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13,437

py

Python

test/test_application_properties.py

jackdewinter/application_properties

087696f6e155b98503036d929e0a7fcc17a10996

[ "MIT" ]

null

test/test_application_properties.py

jackdewinter/application_properties

087696f6e155b98503036d929e0a7fcc17a10996

[ "MIT" ]

null

test/test_application_properties.py

jackdewinter/application_properties

087696f6e155b98503036d929e0a7fcc17a10996

[ "MIT" ]

null

""" Tests for the ApplicationProperties class """ from application_properties import ApplicationProperties # pylint: disable=too-many-lines def test_property_name_separator(): """ Test to make sure that the property name separator is as expected. """ # Arrange application_properties = ApplicationProperties() expected_separator = "." # Act actual_separator = application_properties.separator # Assert assert actual_separator == expected_separator def test_properties_with_object(): """ Test to make sure that a default application properties object has no properties. """ # Arrange application_properties = ApplicationProperties() expected_property_count = 0 # Act actual_property_count = application_properties.number_of_properties # Assert assert actual_property_count == expected_property_count def test_properties_with_single_property(): """ Test a configuration map with a single property, and how that property looks. """ # Arrange application_properties = ApplicationProperties() config_map = {"enabled": True} expected_property_count = 1 # Act application_properties.load_from_dict(config_map) actual_property_count = application_properties.number_of_properties found_names = application_properties.property_names # Assert assert actual_property_count == expected_property_count assert len(found_names) == expected_property_count assert "enabled" in found_names def test_properties_with_single_nested_property(): """ Test a configuration map with a single nested property, and how that property looks. """ # Arrange application_properties = ApplicationProperties() config_map = {"feature": {"enabled": True}} expected_property_count = 1 # Act application_properties.load_from_dict(config_map) actual_property_count = application_properties.number_of_properties found_names = application_properties.property_names # Assert assert actual_property_count == expected_property_count assert len(found_names) == expected_property_count assert "feature.enabled" in found_names def test_properties_with_mixed_properties(): """ Test a configuration map with properties at different levels, and how those properties look. """ # Arrange application_properties = ApplicationProperties() config_map = { "feature": {"enabled": True}, "other_feature": {"enabled": False, "other": 1}, } expected_property_count = 3 # Act application_properties.load_from_dict(config_map) actual_property_count = application_properties.number_of_properties found_names = application_properties.property_names # Assert assert actual_property_count == expected_property_count assert len(found_names) == expected_property_count assert "feature.enabled" in found_names assert "other_feature.enabled" in found_names assert "other_feature.other" in found_names def test_get_properties_under_at_top_level_partial(): """ Test calling the `property_names_under` function specifying only part of the top level. """ # Arrange config_map = { "feature": {"enabled": True}, "other_feature": {"enabled": False, "other": 1}, } application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act found_names = application_properties.property_names_under("other_feature") # Assert assert len(found_names) == len(config_map["other_feature"]) assert "other_feature.enabled" in found_names assert "other_feature.other" in found_names def test_get_properties_under_at_top_level_none(): """ Test calling the `property_names_under` function specifying none of the top level. """ # Arrange config_map = { "feature": {"enabled": True}, "other_feature": {"enabled": False, "other": 1}, } application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act found_names = application_properties.property_names_under("missing_feature") # Assert assert not found_names assert "missing_feature" not in config_map def test_get_properties_under_at_sub_level(): """ Test calling the `property_names_under` function specifying none of the top level. """ # Arrange config_map = { "new_top_level": { "feature": {"enabled": True}, "other_feature": {"enabled": False, "other": 1}, } } application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act found_names = application_properties.property_names_under("new_top_level.feature") # Assert assert len(found_names) == len(config_map["new_top_level"]["feature"]) assert "new_top_level.feature.enabled" in found_names def test_properties_load_from_non_dictionary(): """ Test a loading a configuration map that is not a dictionary. """ # Arrange application_properties = ApplicationProperties() config_map = [{"feature": True}] # Act raised_exception = None try: application_properties.load_from_dict(config_map) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "Specified parameter was not a dictionary." ), "Expected message was not present in exception." def test_properties_load_with_non_string_key(): """ Test a loading a configuration map that contains a key that is not a string. """ # Arrange application_properties = ApplicationProperties() config_map = {1: True} # Act raised_exception = None try: application_properties.load_from_dict(config_map) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "All keys in the main dictionary and nested dictionaries must be strings." ), "Expected message was not present in exception." def test_properties_load_with_key_containing_dot(): """ Test a loading a configuration map that contains a key with a '.' character. """ # Arrange application_properties = ApplicationProperties() config_map = {"my.property": True} # Act raised_exception = None try: application_properties.load_from_dict(config_map) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "Keys strings cannot contain the separator character '.'." ), "Expected message was not present in exception." def test_properties_get_generic_with_bad_type(): """ Test a fetching a configuration value where the generic function is used and the type and the default are confused. """ # Arrange config_map = {"property": True} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act raised_exception = None try: application_properties.get_property("property", False) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "The property_type argument for 'property' must be a type." ), "Expected message was not present in exception." def test_properties_get_generic_with_required_and_found(): """ Test a fetching a configuration value where the value is required and present. """ # Arrange config_map = {"property": True} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) expected_value = True # Act actual_value = application_properties.get_property( "property", bool, is_required=True ) # Assert assert actual_value == expected_value def test_properties_get_generic_with_required_and_not_found(): """ Test a fetching a configuration value where the value is required and not present. """ # Arrange config_map = {"property": True} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act raised_exception = None try: application_properties.get_property("other_property", bool, is_required=True) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "A value for property 'other_property' must be provided." ), "Expected message was not present in exception." def test_properties_get_generic_with_strict_mode_and_bad_type(): """ Test a fetching a configuration value where strict mode is on and the type is not correct. """ # Arrange config_map = {"property": 1} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act raised_exception = None try: application_properties.get_property("property", str, strict_mode=True) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "The value for property 'property' must be of type 'str'." ), "Expected message was not present in exception." def test_properties_get_generic_with_global_strict_mode_and_bad_type(): """ Test a fetching a configuration value where strict mode is on and the type is not correct. """ # Arrange config_map = {"property": 1} application_properties = ApplicationProperties(strict_mode=True) application_properties.load_from_dict(config_map) # Act raised_exception = None try: application_properties.get_property("property", str) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert application_properties.strict_mode assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "The value for property 'property' must be of type 'str'." ), "Expected message was not present in exception." def test_properties_get_generic_with_delayed_global_strict_mode_and_bad_type(): """ Test a fetching a configuration value where strict mode is on through the delayed mechanism and the type is not correct. """ # Arrange config_map = {"property": 1} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) application_properties.enable_strict_mode() # Act raised_exception = None try: application_properties.get_property("property", str) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert application_properties.strict_mode assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "The value for property 'property' must be of type 'str'." ), "Expected message was not present in exception." def __sample_string_validation_function(property_value): """ Simple string validation that throws an error if not "1" or "2". """ if property_value not in ["1", "2"]: raise ValueError("Value '" + str(property_value) + "' is not '1' or '2'") def test_properties_get_generic_with_strict_mode_and_bad_validity(): """ Test a fetching a configuration value where strict mode is on and the value is not valid. """ # Arrange config_map = {"property": "3"} application_properties = ApplicationProperties() application_properties.load_from_dict(config_map) # Act raised_exception = None try: application_properties.get_property( "property", str, strict_mode=True, valid_value_fn=__sample_string_validation_function, ) assert False, "Should have raised an exception by now." except ValueError as this_exception: raised_exception = this_exception # Assert assert raised_exception, "Expected exception was not raised." assert ( str(raised_exception) == "The value for property 'property' is not valid: Value '3' is not '1' or '2'" ), "Expected message was not present in exception."

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null

0

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null

0

6

271c6c4835fb0ccb630f053573294b6472232b09

8,495

py

Python

tests/functional/factories/test_minion_factory.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

tests/functional/factories/test_minion_factory.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

tests/functional/factories/test_minion_factory.py

cmcmarrow/pytest-salt-factories

12515411ea0fa11d7058a9deb61584a56c5f5108

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ tests.functional.factories.test_minion_factory ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Functional tests for the salt minion factory """ import pytest def test_hook_basic_config_defaults(testdir): testdir.makeconftest( """ def pytest_saltfactories_minion_configuration_defaults(): return {'zzzz': True} """ ) p = testdir.makepyfile( """ def test_basic_config_override(request, salt_factories): minion_config = salt_factories.configure_minion(request, 'minion-1') assert 'zzzz' in minion_config """ ) res = testdir.runpytest("-v") res.assert_outcomes(passed=1) def test_keyword_basic_config_defaults(request, salt_factories): minion_config = salt_factories.configure_minion( request, "minion-1", config_defaults={"zzzz": True} ) assert "zzzz" in minion_config def test_interface_config_defaults(request, salt_factories): interface = "172.17.0.1" master_config = salt_factories.configure_master( request, "master-1", config_defaults={"interface": interface} ) assert master_config["interface"] != interface assert master_config["interface"] == "127.0.0.1" def test_master_config_defaults(request, salt_factories): master = "172.17.0.1" minion_config = salt_factories.configure_minion( request, "minion-1", config_defaults={"master": master} ) assert minion_config["master"] != master assert minion_config["master"] == "127.0.0.1" def test_hook_basic_config_overrides(testdir): testdir.makeconftest( """ def pytest_saltfactories_minion_configuration_overrides(): return {'zzzz': True} """ ) p = testdir.makepyfile( """ def test_basic_config_override(request, salt_factories): minion_config = salt_factories.configure_minion(request, 'minion-1') assert 'zzzz' in minion_config """ ) res = testdir.runpytest("-v") res.assert_outcomes(passed=1) def test_keyword_basic_config_overrides(request, salt_factories): minion_config = salt_factories.configure_minion( request, "minion-1", config_overrides={"zzzz": True} ) assert "zzzz" in minion_config def test_interface_config_overrides(request, salt_factories): interface = "172.17.0.1" master_config = salt_factories.configure_master( request, "master-1", config_overrides={"interface": interface} ) assert master_config["interface"] == interface assert master_config["interface"] != "127.0.0.1" def test_master_config_overrides(request, salt_factories): master = "172.17.0.1" minion_config = salt_factories.configure_minion( request, "minion-1", config_overrides={"master": master} ) assert minion_config["master"] == master assert minion_config["master"] != "127.0.0.1" def test_hook_simple_overrides_override_defaults(testdir): testdir.makeconftest( """ def pytest_saltfactories_minion_configuration_defaults(): return {'zzzz': False} def pytest_saltfactories_minion_configuration_overrides(): return {'zzzz': True} """ ) p = testdir.makepyfile( """ def test_basic_config_override(request, salt_factories): minion_config = salt_factories.configure_minion(request, 'minion-1') assert 'zzzz' in minion_config assert minion_config['zzzz'] is True """ ) res = testdir.runpytest("-v") res.assert_outcomes(passed=1) def test_keyword_simple_overrides_override_defaults(request, salt_factories): minion_config = salt_factories.configure_minion( request, "minion-1", config_defaults={"zzzz": False}, config_overrides={"zzzz": True} ) assert "zzzz" in minion_config assert minion_config["zzzz"] is True def test_hook_nested_overrides_override_defaults(testdir): testdir.makeconftest( """ def pytest_saltfactories_minion_configuration_defaults(): return { 'zzzz': False, 'user': 'foobar', 'colors': { 'black': True, 'white': False } } def pytest_saltfactories_minion_configuration_overrides(): return { 'colors': { 'white': True, 'grey': False } } """ ) p = testdir.makepyfile( """ def test_basic_config_override(request, salt_factories): minion_config = salt_factories.configure_minion(request, 'minion-1') assert 'zzzz' in minion_config assert minion_config['zzzz'] is False assert minion_config['colors'] == { 'black': True, 'white': True, 'grey': False } """ ) res = testdir.runpytest("-v") res.assert_outcomes(passed=1) def test_keyword_nested_overrides_override_defaults(request, salt_factories): minion_config = salt_factories.configure_minion( request, "minion-1", config_defaults={ "zzzz": False, "user": "foobar", "colors": {"black": True, "white": False}, }, config_overrides={"colors": {"white": True, "grey": False}}, ) assert "zzzz" in minion_config assert minion_config["zzzz"] is False assert minion_config["colors"] == {"black": True, "white": True, "grey": False} def test_nested_overrides_override_defaults(testdir): testdir.makeconftest( """ def pytest_saltfactories_minion_configuration_defaults(): return { 'zzzz': True, 'user': 'foobar', 'colors': { 'black': False, 'white': True, 'blue': False, } } def pytest_saltfactories_minion_configuration_overrides(): return { 'colors': { 'white': False, 'grey': True, 'blue': True, } } """ ) p = testdir.makepyfile( """ def test_basic_config_override(request, salt_factories): minion_config = salt_factories.configure_minion( request, 'minion-1', config_defaults={ 'zzzz': False, 'user': 'foobar', 'colors': { 'black': True, 'white': False } }, config_overrides={ 'colors': { 'white': True, 'grey': False } } ) assert 'zzzz' in minion_config assert minion_config['zzzz'] is False assert minion_config['colors'] == { 'black': True, 'white': True, 'grey': False, 'blue': True } """ ) res = testdir.runpytest("-v") res.assert_outcomes(passed=1) def test_provide_root_dir(testdir, request, salt_factories): root_dir = testdir.mkdir("custom-root") config_defaults = {"root_dir": root_dir} minion_config = salt_factories.configure_minion( request, "minion-1", config_defaults=config_defaults ) assert minion_config["root_dir"] == root_dir def configure_kwargs_ids(value): return "configure_kwargs={!r}".format(value) @pytest.mark.parametrize( "configure_kwargs", [{"config_defaults": {"user": "blah"}}, {"config_overrides": {"user": "blah"}}, {}], ids=configure_kwargs_ids, ) def test_provide_user(request, salt_factories, configure_kwargs): minion_config = salt_factories.configure_minion(request, "minion-1", **configure_kwargs) if not configure_kwargs: # salt-factories injects the current username assert minion_config["user"] is not None assert minion_config["user"] == salt_factories.get_running_username() else: # salt-factories does not override the passed user value assert minion_config["user"] != salt_factories.get_running_username() assert minion_config["user"] == "blah"

31.579926

93

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0.098943

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0

null

0

1

0

null

0

6

272b9b67fc4e5bec8501ee64e785e2b17a624aaf

21,987

py

Python

deuce/tests/test_blockstorage.py

BenjamenMeyer/deuce

fbca31cb5248a808a85bfc24af10119453359276

[ "Apache-2.0" ]

null

deuce/tests/test_blockstorage.py

BenjamenMeyer/deuce

fbca31cb5248a808a85bfc24af10119453359276

[ "Apache-2.0" ]

null

deuce/tests/test_blockstorage.py

BenjamenMeyer/deuce

fbca31cb5248a808a85bfc24af10119453359276

[ "Apache-2.0" ]

null

import ddt import hashlib import falcon from deuce.util.misc import relative_uri import json import uuid import os from mock import patch from deuce.model import Block from deuce.tests import ControllerTest @ddt.ddt class TestBlockStorageController(ControllerTest): def setUp(self): super(TestBlockStorageController, self).setUp() # Create a vault for us to work with self.vault_name = self.create_vault_id() self._vault_path = '/v1.0/vaults/{0}'.format(self.vault_name) self._blocks_path = '{0:}/blocks'.format(self._vault_path) self._storage_path = '{0:}/storage'.format(self._vault_path) self._block_storage_path = '{0:}/blocks'.format(self._storage_path) self._hdrs = {"x-project-id": self.create_project_id()} self.helper_create_vault(self.vault_name, self._hdrs) def tearDown(self): self.helper_delete_vault(self.vault_name, self._hdrs) super(TestBlockStorageController, self).tearDown() def test_post_blocks(self): data = 'abcdef' block_path = 'http://localhost' + \ self.get_blocks_path(self.vault_name) storage_path = self.get_storage_blocks_path(self.vault_name) response = self.simulate_post(storage_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_405) self.assertIn('x-blocks-location', self.srmock.headers_dict) self.assertEqual(block_path, self.srmock.headers_dict['x-blocks-location']) def test_put_block_nonexistant_block(self): # No block already in metadata/storage block_id = self.create_storage_block_id() block_path = self.get_storage_block_path(self.vault_name, block_id) response = self.simulate_put(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_405) self.assertTrue(self.srmock.headers_dict['x-block-location']) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(block_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(str(None), self.srmock.headers_dict['x-block-id']) def test_put_block_existing_block(self): # block already in metadata/storage # Generate a block upload_data = os.urandom(100) upload_block_id = self.calc_sha1(upload_data) # Upload it to Deuce in the correct method (via blocks/{sha1}) upload_block_path = self.get_block_path(self.vault_name, upload_block_id) upload_headers = self._hdrs upload_headers.update({ "Content-Type": "application/octet-stream", "Content-Length": "100" }) response = self.simulate_put(upload_block_path, headers=self._hdrs, body=upload_data) self.assertEqual(self.srmock.status, falcon.HTTP_201) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(upload_block_id, self.srmock.headers_dict['x-block-id']) # Now try to upload it via the Storage Blocks method storage_block_id = self.srmock.headers_dict['x-storage-id'] block_path = self.get_storage_block_path( self.vault_name, storage_block_id) response = self.simulate_put(block_path, headers=upload_headers, body=upload_data) self.assertEqual(self.srmock.status, falcon.HTTP_405) self.assertTrue(self.srmock.headers_dict['x-block-location']) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(storage_block_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(upload_block_id, self.srmock.headers_dict['x-block-id']) def test_put_block_vault_name_is_storage(self): # Rebuild the vault data self.vault_name = 'storage' self._vault_path = '/v1.0/vaults/{0}'.format(self.vault_name) self._blocks_path = '{0}/blocks'.format(self._vault_path) self._storage_path = '{0:}/storage'.format(self._vault_path) self._block_storage_path = '{0:}/blocks'.format(self._storage_path) self.helper_create_vault(self.vault_name, self._hdrs) block_id = self.create_storage_block_id() block_path = 'http://localhost{0}/{1}'.format(self._blocks_path, block_id) storage_block_path = self.get_storage_block_path( self.vault_name, block_id) response = self.simulate_put(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_405) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(block_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(str(None), self.srmock.headers_dict['x-block-id']) block_location = self.srmock.headers_dict['x-block-location'] self.assertTrue(block_location) self.assertIn('storage', block_location) self.assertEqual(block_path, block_location) def test_list_blocks_bad_vault(self): block_storage_path = self.get_storage_blocks_path( self.create_vault_id()) response = self.simulate_get(block_storage_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_list_blocks(self): response = self.simulate_get(self._block_storage_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_200) def test_list_blocks_with_limit_marker(self): # Test with bad marker block_storage_path = self.get_storage_blocks_path(self.vault_name) block_marker = self.create_storage_block_id() marker = 'marker={0:}'.format(block_marker) response = self.simulate_get(self._block_storage_path, query_string=marker, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_200) self.assertEqual(response[0].decode(), '[]') block_list, block_data = self.helper_create_blocks(num_blocks=40) storage_list = self.helper_store_blocks(self.vault_name, block_data) # Test with no marker response = self.simulate_get(self._block_storage_path, headers=self._hdrs) storage_ids = json.loads(response[0].decode()) self.assertEqual(self.srmock.status, falcon.HTTP_200) # Test valid marker # Lets list from the second storage_id query_marker = storage_ids[0] marker = 'marker={0:}'.format(query_marker) response = self.simulate_get(self._block_storage_path, query_string=marker, headers=self._hdrs) responses = json.loads(response[0].decode()) for resp in responses: resp_sha1, resp_uuid = resp.split('_') self.assertTrue(uuid.UUID(resp_uuid)) self.assertIn(resp, storage_ids) # Test valid limit response = self.simulate_get(self._block_storage_path, query_string='limit=3', headers=self._hdrs) self.assertEqual(len(json.loads(response[0].decode())), 3) # Test valid marker with limit query_string = 'marker={0:}&limit={1:}'.format(query_marker, '2') response = self.simulate_get(self._block_storage_path, query_string=query_string, headers=self._hdrs) self.assertEqual(len(json.loads(response[0].decode())), 2) next_url, querystring = relative_uri( self.srmock.headers_dict['x-next-batch']) response = self.simulate_get(next_url, query_string=querystring, headers=self._hdrs) self.assertEqual(len(json.loads(response[0].decode())), 2) def test_head_block_in_nonexistent_vault(self): block_id = self.create_storage_block_id() block_path = self.get_storage_block_path(self.create_vault_id(), block_id) response = self.simulate_head(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_head_block_nonexistent_block(self): block_id = self.create_storage_block_id() block_path = self.get_storage_block_path(self.vault_name, block_id) response = self.simulate_head(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_head_orphaned_block(self): block_list, block_data = self.helper_create_blocks(num_blocks=1) self.assertEqual(len(block_list), 1) size, data, sha1 = zip(*block_data) block_path = self.get_block_path(self.vault_name, sha1[0]) upload_headers = {} upload_headers.update(self._hdrs) upload_headers.update({ "Content-Type": "application/octet-stream", "Content-Length": str(size[0]), }) # Upload the block twice, orphaning the second block upload_first = self.simulate_put(block_path, headers=upload_headers, body=data[0]) self.assertEqual(self.srmock.status, falcon.HTTP_201) first_storage_id = self.srmock.headers_dict['x-storage-id'] first_block_id = self.srmock.headers_dict['x-block-id'] upload_second = self.simulate_put(block_path, headers=upload_headers, body=data[0]) self.assertEqual(self.srmock.status, falcon.HTTP_201) second_storage_id = self.srmock.headers_dict['x-storage-id'] second_block_id = self.srmock.headers_dict['x-block-id'] # Verify we got the same block id but different storage ids self.assertEqual(first_block_id, second_block_id) self.assertNotEqual(first_storage_id, second_storage_id) # Get the storage id from the orphaned second block storage_id = second_storage_id storage_block_path = self.get_storage_block_path(self.vault_name, storage_id) # Now try to head the orphaned block response = self.simulate_head(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_204) self.assertIn('x-block-size', self.srmock.headers_dict) self.assertEqual(str(size[0]), self.srmock.headers_dict['x-block-size']) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(storage_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual('None', self.srmock.headers_dict['x-block-id']) self.assertIn('x-ref-modified', self.srmock.headers_dict) self.assertEqual('None', self.srmock.headers_dict['x-ref-modified']) self.assertIn('x-block-reference-count', self.srmock.headers_dict) self.assertEqual('0', self.srmock.headers_dict['x-block-reference-count']) self.assertIn('x-block-orphaned', self.srmock.headers_dict) self.assertEqual(str(True), self.srmock.headers_dict['x-block-orphaned']) def test_head_happy_path(self): block_list, block_data = self.helper_create_blocks(num_blocks=1) self.assertEqual(len(block_list), 1) size, data, sha1 = zip(*block_data) block_path = self.get_block_path(self.vault_name, sha1[0]) upload_headers = {} upload_headers.update(self._hdrs) upload_headers.update({ "Content-Type": "application/octet-stream", "Content-Length": str(size[0]), }) upload = self.simulate_put(block_path, headers=upload_headers, body=data[0]) self.assertEqual(self.srmock.status, falcon.HTTP_201) # Get the storage id from the orphaned second block storage_id = self.srmock.headers_dict['x-storage-id'] storage_block_path = self.get_storage_block_path(self.vault_name, storage_id) # Now try to head the block response = self.simulate_head(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_204) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(storage_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(sha1[0], self.srmock.headers_dict['x-block-id']) self.assertIn('x-ref-modified', self.srmock.headers_dict) self.assertNotEqual('None', self.srmock.headers_dict['x-ref-modified']) self.assertIn('x-block-reference-count', self.srmock.headers_dict) self.assertEqual('0', self.srmock.headers_dict['x-block-reference-count']) self.assertIn('x-block-size', self.srmock.headers_dict) self.assertEqual(str(size[0]), self.srmock.headers_dict['x-block-size']) self.assertIn('x-block-orphaned', self.srmock.headers_dict) self.assertEqual(str(False), self.srmock.headers_dict['x-block-orphaned']) def test_get_block_invalid_block(self): block_id = self.create_storage_block_id() block_path = self.get_storage_block_path(self.vault_name, block_id) response = self.simulate_get(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_get_block_bad_vault(self): storage_block_id = self.create_storage_block_id() block_path = self.get_storage_block_path(self.create_vault_id(), storage_block_id) response = self.simulate_get(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_get_block(self): block_list, block_data = self.helper_create_blocks(num_blocks=1) self.assertEqual(len(block_list), 1) storage_list = self.helper_store_blocks(self.vault_name, block_data) self.assertEqual(len(storage_list), 1) block_path = self.get_storage_block_path( self.vault_name, storage_list[0][1]) response = self.simulate_get(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_200) self.assertIn('x-ref-modified', self.srmock.headers_dict) self.assertIn('x-block-reference-count', self.srmock.headers_dict) self.assertEqual( int(self.srmock.headers_dict['x-block-reference-count']), 0) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(storage_list[0][1], self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(block_list[0], self.srmock.headers_dict['x-block-id']) z = hashlib.sha1() z.update(response.read()) self.assertEqual(z.hexdigest(), block_list[0]) def test_get_block_orphaned_block(self): block_list, block_data = self.helper_create_blocks(num_blocks=1) self.assertEqual(len(block_list), 1) size, data, sha1 = zip(*block_data) upload_block_path = self.get_block_path(self.vault_name, sha1[0]) upload_headers = {} upload_headers.update(self._hdrs) upload_headers.update({ "Content-Type": "application/octet-stream", "Content-Length": str(size[0]), }) # Upload the block twice, orphaning the second block upload_first = self.simulate_put(upload_block_path, headers=upload_headers, body=data[0]) self.assertEqual(self.srmock.status, falcon.HTTP_201) first_storage_id = self.srmock.headers_dict['x-storage-id'] first_block_id = self.srmock.headers_dict['x-block-id'] upload_second = self.simulate_put(upload_block_path, headers=upload_headers, body=data[0]) self.assertEqual(self.srmock.status, falcon.HTTP_201) second_storage_id = self.srmock.headers_dict['x-storage-id'] second_block_id = self.srmock.headers_dict['x-block-id'] # Verify we got the same block id but different storage ids self.assertEqual(first_block_id, second_block_id) self.assertNotEqual(first_storage_id, second_storage_id) # Get the storage id from the orphaned second block storage_id = second_storage_id block_path = self.get_storage_block_path(self.vault_name, storage_id) response = self.simulate_get(block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_200) self.assertIn('x-ref-modified', self.srmock.headers_dict) self.assertIn('x-block-reference-count', self.srmock.headers_dict) self.assertEqual( int(self.srmock.headers_dict['x-block-reference-count']), 0) self.assertIn('x-storage-id', self.srmock.headers_dict) self.assertEqual(second_storage_id, self.srmock.headers_dict['x-storage-id']) self.assertIn('x-block-id', self.srmock.headers_dict) self.assertEqual(str(None), self.srmock.headers_dict['x-block-id']) bindata = response.read() z = hashlib.sha1() z.update(bindata) self.assertEqual(z.hexdigest(), sha1[0]) self.assertIn('content-length', self.srmock.headers_dict) self.assertEqual(str(size[0]), self.srmock.headers_dict['content-length']) self.assertEqual(size[0], len(bindata)) self.assertEqual(data[0], bindata) def test_delete_storage_non_existent(self): storage_block_id = self.create_storage_block_id() storage_block_path = self.get_storage_block_path(self.vault_name, storage_block_id) response = self.simulate_delete(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_404) def test_delete_storage_block_with_references(self): # NOTE(TheSriram): Let's just spoof ref-count to get 42 References. with patch.object(Block, 'get_ref_count', return_value=42): block_id = self.create_block_id(b'mock') response = self.simulate_put(self.get_block_path(self.vault_name, block_id), headers=self._hdrs, body=b'mock') storage_block_id = self.srmock.headers_dict['x-storage-id'] storage_block_path = self.get_storage_block_path(self.vault_name, storage_block_id) response = self.simulate_delete(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_409) def test_delete_storage_orphaned_block(self): block_id = self.create_block_id(b'mock') # NOTE(TheSriram): We put the same block twice, to orphan the second # block as it will not have a reference in the metadata. But, it will # nevertheless be present in block storage response = self.simulate_put(self.get_block_path(self.vault_name, block_id), headers=self._hdrs, body=b'mock') real_storage_id = self.srmock.headers_dict['x-storage-id'] response = self.simulate_put(self.get_block_path(self.vault_name, block_id), headers=self._hdrs, body=b'mock') orphaned_storage_id = self.srmock.headers_dict['x-storage-id'] self.assertNotEqual(real_storage_id, orphaned_storage_id) storage_block_path = self.get_storage_block_path(self.vault_name, orphaned_storage_id) response = self.simulate_delete(storage_block_path, headers=self._hdrs) self.assertEqual(self.srmock.status, falcon.HTTP_204)

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null

0

1

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null

0

6

272ee9938c8a1b9a446b2804c4ef5e759f1cb664

31

py

Python

SO_sim_runner.py

EngTurtle/VISSIM_Routing_Thesis

4ee77146675631175866137e4bec6a424cfb8c3b

[ "Apache-2.0" ]

null

SO_sim_runner.py

EngTurtle/VISSIM_Routing_Thesis

4ee77146675631175866137e4bec6a424cfb8c3b

[ "Apache-2.0" ]

null

SO_sim_runner.py

EngTurtle/VISSIM_Routing_Thesis

4ee77146675631175866137e4bec6a424cfb8c3b

[ "Apache-2.0" ]

null

import win32com.client as com

10.333333

29

0.806452

5

31

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null

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1

0

1

0

1

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6

27949205b594356143b2ec4249cc29950d520642

4,795

py

Python

recipes/Python/577284_Maclaurinsseriesbinomialseries/recipe-577284.py

tdiprima/code

61a74f5f93da087d27c70b2efe779ac6bd2a3b4f

[ "MIT" ]

2,023

2017-07-29T09:34:46.000Z

2022-03-24T08:00:45.000Z

recipes/Python/577284_Maclaurinsseriesbinomialseries/recipe-577284.py

unhacker/code

73b09edc1b9850c557a79296655f140ce5e853db

[ "MIT" ]

32

2017-09-02T17:20:08.000Z

2022-02-11T17:49:37.000Z

recipes/Python/577284_Maclaurinsseriesbinomialseries/recipe-577284.py

unhacker/code

73b09edc1b9850c557a79296655f140ce5e853db

[ "MIT" ]

780

2017-07-28T19:23:28.000Z

2022-03-25T20:39:41.000Z

#On the name of ALLAH and may the blessing and peace of Allah #be upon the Messenger of Allah Mohamed Salla Allahu Aliahi Wassalam. #Author : Fouad Teniou #Date : 06/07/10 #version :2.6 """ maclaurin_binomial is a function to compute(1+x)^m using maclaurin binomial series and the interval of convergence is -1 < x < 1 (1+x)^m = 1 + mx + m(m-1)x^2/2! + m(m-1)(m-2)x^3/3!........... note: if m is a nonegative integer the binomial is a polynomial of degree m and it is valid on -inf < x < +inf,thus, the error function will not be valid. """ from math import * def error(number): """ Raises interval of convergence error.""" if number >= 1 or number <= -1 : raise TypeError,\ "\n<The interval of convergence should be -1 < value < 1 \n" def maclaurin_binomial(value,m,k): """ Compute maclaurin's binomial series approximation for (1+x)^m. """ global first_value first_value = 0.0 error(value) #attempt to Approximate (1+x)^m for given values try: for item in xrange(1,k): next_value =m*(value**item)/factorial(item) for i in range(2,item+1): next_second_value =(m-i+1) next_value *= next_second_value first_value += next_value return first_value + 1 #Raise TypeError if input is not within #the interval of convergence except TypeError,exception: print exception #Raise OverflowError if an over flow occur except OverflowError: print '\n<Please enter a lower k value to avoid the Over flow\n ' if __name__ == "__main__": maclaurin_binomial_1 = maclaurin_binomial(0.777,-0.5,171) print maclaurin_binomial_1 maclaurin_binomial_2 = maclaurin_binomial(0.37,0.5,171) print maclaurin_binomial_2 maclaurin_binomial_3 = maclaurin_binomial(0.3,0.717,171) print maclaurin_binomial_3 ######################################################################## #c:python # #0.750164116353 #1.17046999107 #1.20697252357 ####################################################################### #Version : Python 3.2 #import math #def maclaurin_binomial(value,m,k): # """ # Compute maclaurin's binomial series approximation for (1+x)^m. # """ # global first_value # first_value = 0.0 # # #attempt to Approximate (1+x)^m for given values # try: # # for item in range(1,k): # next_value =m*(value**item)/math.factorial(item) # # for i in range(2,item+1): # next_second_value =(m-i+1) # next_value *= next_second_value # first_value += next_value # return first_value + 1 # # #Raise TypeError if input is not within # #the interval of convergence # except TypeError as exception: # print (exception) # # #Raise OverflowError if an over flow occur # except OverflowError: # print ('\n<Please enter a lower k value to avoid the Over flow\n ') # # #if __name__ == "__main__": # maclaurin_binomial_1 = maclaurin_binomial(0.777,-0.5,171) # print (maclaurin_binomial_1 ) # maclaurin_binomial_2 = maclaurin_binomial(0.37,0.5,171) # print (maclaurin_binomial_2) # maclaurin_binomial_3 = maclaurin_binomial(0.3,0.717,171) # print (maclaurin_binomial_3) ###################################################################################### #decimal Version Python 3.2 #from math import * #from decimal import Decimal as D,Context, localcontext #def error(number): # """ Raises interval of convergence error.""" # if number >= 1 or number <= -1 : # raise TypeError("\n<The interval of convergence should be -1 < value < 1 \n") #def maclaurin_binomial(value,m,k): # """ # Compute maclaurin's binomial series approximation for (1+x)^m. # """ # global first_value # first_value = 0 # # #attempt to Approximate (1+x)^m for given values # try: # # for item in range(1,k): # next_value = (m*(value**item))/factorial(item) # for i in range(2,item+1): # next_second_value =(m-i+1) # next_value *= next_second_value # first_value += next_value # # return (first_value) + (1) # # #Raise TypeError if input is not within # #the interval of convergence # except TypeError as exception: # print(exception) # # #Raise OverflowError if an over flow occur # except OverflowError: # print('\n<Please enter a lower k value to avoid the Over flow\n ') # # #if __name__ == "__main__": # # with localcontext(Context(prec= 1777)): # for arg in range(2,-8,-2): # print(maclaurin_binomial(D("0.777"),arg,171))

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null

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null

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1

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null

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6

279d065ffbd0a89a506adad41d988db86b27aa1f

61

py

Python

book-code/numpy-ml/numpy_ml/neural_nets/models/__init__.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

3

2021-07-07T13:28:01.000Z

2021-11-12T06:32:49.000Z

book-code/numpy-ml/numpy_ml/neural_nets/models/__init__.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

null

book-code/numpy-ml/numpy_ml/neural_nets/models/__init__.py

yangninghua/code_library

b769abecb4e0cbdbbb5762949c91847a0f0b3c5a

[ "MIT" ]

3

2021-11-17T08:46:37.000Z

2022-03-04T16:35:36.000Z

from .vae import * from .wgan_gp import * from .w2v import *

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6

27d2dacdbf1d1c931dd312f390681580ff305450

1,908

py

Python

tests/get_str_dict_property_tests.py

agorinenko/power_dict

01e8bcdfd6a77915e5c971882d5b94646f04cfdb

[ "MIT" ]

3

2019-11-28T11:56:02.000Z

2020-10-21T10:39:46.000Z

tests/get_str_dict_property_tests.py

agorinenko/power_dict

01e8bcdfd6a77915e5c971882d5b94646f04cfdb

[ "MIT" ]

6

2020-02-19T08:09:37.000Z

2020-09-02T15:17:01.000Z

tests/get_str_dict_property_tests.py

agorinenko/power-dict

01e8bcdfd6a77915e5c971882d5b94646f04cfdb

[ "MIT" ]

null

import unittest from power_dict.errors import NoneParameterError from power_dict.utils import DictUtils class GetStrDictPropertyTests(unittest.TestCase): properties = { "property_1": "Hello!", "property_1_none": None, "property_1_empty": '' } def test_get_property(self): target = DictUtils.get_str_dict_property(self.properties, 'property_1') self.assertIsInstance(target, str) self.assertEqual(target, "Hello!") target = DictUtils.get_str_dict_property(self.properties, 'property_1_none', default_value="Default string") self.assertIsInstance(target, str) self.assertEqual(target, "Default string") target = DictUtils.get_str_dict_property(self.properties, 'property_1_empty', default_value="Default string") self.assertIsInstance(target, str) self.assertEqual(target, "Default string") target = DictUtils.get_str_dict_property(self.properties, 'key_not_found') self.assertIsInstance(target, str) self.assertEqual(target, '') def test_get_required_property(self): target = DictUtils.get_required_str_dict_property(self.properties, 'property_1') self.assertIsInstance(target, str) self.assertEqual(target, "Hello!") with self.assertRaises(NoneParameterError): DictUtils.get_required_str_dict_property(self.properties, 'property_1_none', required_error="Key property_1_none is None") with self.assertRaises(NoneParameterError): DictUtils.get_required_str_dict_property(self.properties, 'property_1_empty', required_error="Key property_1_none is None") with self.assertRaises(NoneParameterError): DictUtils.get_required_str_dict_property(self.properties, 'key_not_found')

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6.102941

0.181373

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0.096386

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0.825703

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0.761446

0.729317

0

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0.224843

1,908

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118

42.4

0.834348

0

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0

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1

0.058824

false

0

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0

0.205882

0

null

0

1

0

null

0

6

27e35604505557e781c035de45bdd7a16548e089

36,449

py

Python

LibCns_Gas.py

stefdeli/Gas-Swing-Contracts

d32d6545f0a898b440a5e81f455cc28cb095bf6c

[ "MIT" ]

1

2021-08-07T06:00:51.000Z

LibCns_Gas.py

stefdeli/Gas-Swing-Contracts

d32d6545f0a898b440a5e81f455cc28cb095bf6c

[ "MIT" ]

1

2018-10-08T08:14:11.000Z

2018-10-08T08:17:50.000Z

LibCns_Gas.py

stefdeli/Gas-Swing-Contracts

d32d6545f0a898b440a5e81f455cc28cb095bf6c

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Thu Dec 7 17:13:27 2017 @author: delikars """ from collections import defaultdict import numpy as np import itertools import gurobipy as gb import defaults class expando(object): pass def OuterApprox_Discretization(self): # Pressure discretization at every gas node gnodes = self.gdata.gnodes gndata = self.gdata.gnodedf prd = defaultdict(list) for gn in gnodes: prd[gn] = np.linspace(gndata['PresMin'][gn], gndata['PresMax'][gn], self.gdata.Nfxpp).tolist() self.gdata.prd = prd # Create Parameter for Positive and negative part of outer approximation equation Kpos = defaultdict(lambda: defaultdict(list) ) for pl in self.gdata.pplinepassive: ns, nr = pl # Pipeline between nodes ns and nr for vs, vr in list(itertools.product(range(self.gdata.Nfxpp), repeat = 2)): if prd[ns][vs] > prd[nr][vr]: pres_s = prd[ns][vs] pres_r = prd[nr][vr] K = self.gdata.pplineK[pl] Kpos[pl][vs, vr] = K/np.sqrt(np.square(pres_s) - np.square(pres_r)) # elif prd[ns][vs] == prd[nr][vr]: # pres_s = prd[ns][vs]+1e-3 # pres_r = prd[nr][vr] # K = self.gdata.pplineK[pl] # Kpos[pl][vs, vr] =1#3 K/np.sqrt(np.square(pres_s) - np.square(pres_r)) self.gdata.Kpos = Kpos # if bi-directional flow model flow limits from Receiving to Sending end if self.gdata.flow2dir == True: Kneg = defaultdict(lambda: defaultdict(list) ) for pl in self.gdata.pplinepassive: ns, nr = pl for vs, vr in list(itertools.product(range(self.gdata.Nfxpp), repeat = 2)): if prd[ns][vs] < prd[nr][vr]: Kneg[pl][vs, vr] = self.gdata.pplineK[pl]/np.sqrt(np.square(prd[nr][vr]) - np.square(prd[ns][vs])) self.gdata.Kneg = Kneg def add_constraint(self,lhs,sign_str,rhs,name): ALL_ON_LHS=False ALL_ON_RHS=False # Only one will be executed if sign_str=='>=': self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=lhs cc.rhs=rhs if ALL_ON_LHS: cc.expr=self.model.addConstr( -cc.lhs+cc.rhs<=0.0,name=name) elif ALL_ON_RHS: cc.expr=self.model.addConstr(0.0<=cc.lhs-cc.rhs,name=name) else: cc.expr=self.model.addConstr(cc.lhs>=cc.rhs,name=name) elif sign_str=='<=': self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=lhs cc.rhs=rhs if ALL_ON_LHS: cc.expr=self.model.addConstr(-cc.rhs+cc.lhs<=0.0,name=name) elif ALL_ON_RHS: cc.expr=self.model.addConstr(0.0<=cc.rhs-cc.lhs,name=name) else: cc.expr=self.model.addConstr(cc.lhs<=cc.rhs,name=name) elif sign_str=='==': if defaults.REMOVE_EQUALITY: # gEQ self.constraints[name+'_geq']= expando() cc=self.constraints[name+'_geq'] cc.lhs=lhs cc.rhs=rhs if ALL_ON_LHS: cc.expr=self.model.addConstr(-cc.lhs+cc.rhs<=0.0,name=name+'_geq') elif ALL_ON_RHS: cc.expr=self.model.addConstr(0.0<=cc.lhs-cc.rhs,name=name+'_geq') else: cc.expr=self.model.addConstr(cc.lhs>=cc.rhs,name=name+'_geq') self.constraints[name+'_leq']= expando() cc=self.constraints[name+'_leq'] cc.lhs=lhs cc.rhs=rhs if ALL_ON_LHS: cc.expr=self.model.addConstr(-cc.rhs+cc.lhs<=0.0,name=name+'_leq') elif ALL_ON_RHS: cc.expr=self.model.addConstr(0.0<=cc.rhs-cc.lhs,name=name+'_leq') else: cc.expr=self.model.addConstr(cc.lhs<=cc.rhs,name=name+'_leq') else: self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=lhs cc.rhs=rhs if ALL_ON_LHS: cc.expr=self.model.addConstr(cc.lhs-cc.rhs==0.0,name=name) elif ALL_ON_RHS: cc.expr=self.model.addConstr(0.0==cc.lhs-cc.rhs,name=name) else: cc.expr=self.model.addConstr(cc.lhs==cc.rhs,name=name) #============================================================================== # Gas system constraints # NB! Gas storage constraints included as limits in variable definitions #============================================================================== #============================================================================== # Day-ahead market #============================================================================== def _build_constraints_gasDA(self): #--- Get Parameters m = self.model var = self.variables gnodes = self.gdata.gnodes pplines = self.gdata.pplineorder time = self.gdata.time gndata = self.gdata.gnodedf gstorage = self.gdata.gstorage gwells = self.gdata.wellsinfo.index.tolist() bigM = self.gdata.bigM sclim = self.gdata.sclim # Swing contract limits if self.gdata.GasSlack=='FixInput': gn=self.gdata.gnodeorder[0] for t in time: for k in sclim: name="PresSlackMax({0},{1},{2})".format(gn,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[gn,k,t] cc.rhs=self.gdata.gnodedf['PresMax'][gn] cc.expr = m.addConstr(cc.lhs==cc.rhs,name=name) elif self.gdata.GasSlack=='FixOutput': gn=self.gdata.gnodeorder[-1] # Do it for last node for t in time: for k in sclim: name="PresSlackMin({0},{1},{2})".format(gn,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[gn,k,t] cc.rhs=self.gdata.gnodedf['PresMax'][gn] cc.expr = m.addConstr(cc.lhs==cc.rhs,name=name) elif self.gdata.GasSlack == 'ConstantOutput': gn=self.gdata.gnodeorder[0] for tpr, t in zip(time, time[1:]): name="Constant_Slack({},{},{})".format(gn,t,tpr) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs= var.pr[gn,'k0',t]-var.pr[gn,'k0',tpr] cc.rhs=np.float64(0.0) cc.expr=m.addConstr(cc.lhs==cc.rhs,name=name) #--- Define Pressure Limits # Gas pressure limits for gn in gnodes: for t in time: for k in sclim: name="PresMax({0},{1},{2})".format(gn,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[gn,k,t] cc.rhs=self.gdata.gnodedf['PresMax'][gn] cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) name="PresMin({0},{1},{2})".format(gn,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[gn,k,t] cc.rhs=self.gdata.gnodedf['PresMin'][gn] cc.expr=m.addConstr(cc.lhs>=cc.rhs,name=name) # --- Outer Approximation of Weymouth # Create Points for Outer Approximation OuterApprox_Discretization(self) # Gas flow outer approximation if self.gdata.flow2dir == True: u = var.u # if bi-directional flow u={0,1} elif self.gdata.flow2dir == False: u = dict.fromkeys(self.variables.gflow_sr, 1.0) # if bi-directional flow u={1} i.e. from send to receive Kpos=self.gdata.Kpos prd=self.gdata.prd for pl in self.gdata.pplineorder: ns, nr = pl for t in time: for k in sclim: name = "gflow_sr_log({0},{1},{2})".format(pl,k,t).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gflow_sr[pl,k,t]-u[pl,k,t]*bigM cc.rhs=np.float64(0.0) cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) for vs, vr in Kpos[pl].keys(): name = "gflow_sr_lim({0},{1},{2},{3},{4})".format(pl,k,t,vs,vr).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gflow_sr[pl,k,t] cc.rhs=Kpos[pl][vs,vr] * prd[ns][vs] * var.pr[ns,k,t] - \ Kpos[pl][vs,vr] * prd[nr][vr] * var.pr[nr,k,t] \ + bigM * (1.0 - u[pl,k,t]) cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) # if bi-directional flow model flow limits from Receiving to Sending end # if bi-directional flow add constraints from Receiving to Sending end if self.gdata.flow2dir == True: Kneg=self.gdata.Kneg prd=self.gdata.prd for pl in self.gdata.pplineorder: ns, nr = pl for t in time: for k in sclim: name = "gflow_rs_log({0},{1},{2})".format(pl,k,t).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gflow_rs[pl,k,t] cc.rhs=(1.0-u[pl,k,t])*bigM cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) for vs, vr in self.gdata.Kneg[pl].keys(): name = "gflow_rs_lim({0},{1},{2},{3},{4})".format(pl,k,t,vs,vr).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gflow_rs[pl,k,t] cc.rhs= Kneg[pl][vs,vr] * prd[nr][vr] * var.pr[nr,k,t] - \ Kneg[pl][vs,vr] * prd[ns][vs] * var.pr[ns,k,t] +\ bigM * u[pl,k,t] cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) #--- Gas well maximum production for gw in gwells: for k in sclim: for t in time: name="gprod_max({0},{1},{2})".format(gw,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gprod[gw,k,t] cc.rhs=self.gdata.wellsinfo['MaxProd'][gw] cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) #--- Compressors # Compressors - Limit the outlet pressure of compressor to be less than # full compression (max) and above the inlet pressure (min) # Compressors #new comment for pl in self.gdata.pplineactive: ns, nr = pl for t in time: for k in sclim: name = 'compr_max({0},{1},{2})'.format(pl,k,t).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[nr,k,t] cc.rhs=self.gdata.pplinecr[pl] * var.pr[ns,k,t] cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) name = 'compr_min({0},{1},{2})'.format(pl,k,t).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.pr[ns,k,t] cc.rhs=var.pr[nr,k,t] cc.expr=m.addConstr(cc.lhs<=cc.rhs,name=name) #--- Line Pack Def # Line-pack constraints for pl in pplines: ns, nr = pl for t in time: for k in sclim: name='gflow_sr_io({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.gflow_sr[pl,k,t] rhs=(var.qin_sr[pl,k,t] + var.qout_sr[pl,k,t]) * 0.5 add_constraint(self,-lhs,'==',-rhs,name=name) # Separate for debugging purposes for pl in pplines: ns, nr = pl for k in sclim: for t in time: name= 'lpack_def({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.lpack[pl,k,t] rhs= self.gdata.pplinels[pl]*0.5*(var.pr[ns,k,t]+var.pr[nr,k,t]) add_constraint(self,-lhs,'==',-rhs,name=name) ''' NB! gflow_rs_io = {} # Gas flow (R to S) only if bi-directional flow. This needs to be included in the line-pack definition constraint ''' if self.gdata.flow2dir == True: # Gas flow (R to S) 'decomposition' to IN/OUT for pl in pplines: ns, nr = pl for t in time: for k in sclim: name='gflow_rs_io({0},{1},{2})'.format(pl,k,t).replace(" ","") self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gflow_rs[pl,k,t] cc.rhs=(var.qin_rs[pl,k,t] + var.qout_rs[pl,k,t]) * 0.5 cc.expr=m.addConstr(cc.lhs==cc.rhs,name=name) for tpr, t in zip(time, time[1:]): k = 'k0' # Line-pack storage defined for 'central case' k0 name='line_store({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.lpack[pl,k,t] rhs=var.lpack[pl,k,tpr] + var.qin_sr[pl,k,t] - var.qout_sr[pl,k,t] \ + var.qin_rs[pl,k,t] - var.qout_rs[pl,k,t] add_constraint(self,-lhs,'==',-rhs,name=name) t = time[0] k= 'k0' # Line-pack storage defined for 'central case' k0 name='line_store({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.lpack[pl,k,t] rhs= self.gdata.pplinelsini[pl] + var.qin_sr[pl,k,t] - var.qout_sr[pl,k,t] \ + var.qin_rs[pl,k,t] - var.qout_rs[pl,k,t] add_constraint(self,-lhs,'==',-rhs,name=name) elif self.gdata.flow2dir == False: kappa = 'k0' # Line-pack storage defined for 'central case' k0 for pl in pplines: ns, nr = pl for k in sclim: # For every Scenario # For all time steps (except for t=0) for tpr, t in zip(time, time[1:]): name='line_store({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs=var.lpack[pl,k,t] rhs=var.lpack[pl,kappa,tpr] + var.qin_sr[pl,k,t] - var.qout_sr[pl,k,t] add_constraint(self,-lhs,'==',-rhs,name=name) # Time =0 Either Steady State or Transient t = time[0] # If pipelines have linepack storage then add initial value if self.gdata.pplinels[pl] >0 : name='line_store({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.lpack[pl,k,t] rhs= self.gdata.pplinelsini[pl] + var.qin_sr[pl,k,t] - var.qout_sr[pl,k,t] add_constraint(self,-lhs,'==',-rhs,name=name) # Otherwise system is in steady state and there is no initial linepack else: name='line_store({0},{1},{2})'.format(pl,k,t).replace(" ","") lhs= var.lpack[pl,k,t] rhs= var.qin_sr[pl,k,t] - var.qout_sr[pl,k,t] add_constraint(self,-lhs,'==',-rhs,name=name) #--- Linepack End of Day # At end of optimization the total linepack should be within Line-pack end of optimization (only for case k0) # Only need this constraint if linepack parameters are defined if sum(self.gdata.pplinels.values()) >0: k = 'k0' name='lpack_end' self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=gb.quicksum(var.lpack[pl, k, time[-1]] for pl in pplines) cc.rhs=gb.quicksum(self.gdata.pplinelsini[pl] for pl in pplines) cc.expr=m.addConstr(cc.lhs>=cc.rhs,name=name) #--- Gas Storage for gs in self.gdata.gstorage: for t in time: for k in sclim: name='gsinMax({0},{1},{2})'.format(gs,t,k) lhs=var.gsin[gs,k,t] rhs=self.gdata.gstorageinfo['MaxInFlow'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gsoutMax({0},{1},{2})'.format(gs,t,k) lhs=var.gsout[gs,k,t] rhs=self.gdata.gstorageinfo['MaxOutFlow'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gstore_max({0},{1},{2})'.format(gs,t,k) lhs=var.gstore[gs,k,t] rhs=self.gdata.gstorageinfo['MaxStore'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gstore_min({0},{1},{2})'.format(gs,t,k) lhs=var.gstore[gs,k,t] rhs=self.gdata.gstorageinfo['MinStore'][gs] add_constraint(self,lhs,'>=',rhs,name) for gs in gstorage: for k in sclim: for tpr, t in zip(time, time[1:]): name='gstor_def({0},{1},{2})'.format(gs,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gstore[gs,k,t] cc.rhs=var.gstore[gs,k,tpr]+var.gsin[gs,k,t]-var.gsout[gs,k,t] cc.expr=m.addConstr(cc.lhs==cc.rhs,name=name) t = time[0] name='gstor_def({0},{1},{2})'.format(gs,k,t) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gstore[gs,k,t] cc.rhs=self.gdata.gstorageinfo['IniStore'][gs]+var.gsin[gs,k,t]-var.gsout[gs,k,t] cc.expr=m.addConstr(cc.lhs==cc.rhs,name=name) k = 'k0' # Gas storage content defined for 'central case' k0 name='gs_end({0},{1})'.format(gs,k) self.constraints[name]= expando() cc=self.constraints[name] cc.lhs=var.gstore[gs, k, time[-1]] cc.rhs=self.gdata.gstorageinfo['IniStore'][gs] cc.expr=m.addConstr(cc.lhs>=cc.rhs,name=name) #--- Nodal Gas Balance ########################################################################### # Swing constracts can be defined per Gas Node - Here defined per GFPP # ... we need the GFPP node mapping and efficiencies ########################################################################### Pgen = self.gdata.Pgen PgenSC = self.gdata.PgenSC RSC = self.gdata.RSC HR = self.gdata.generatorinfo.HR # if bi-directional flow add in gas balance flow from Receiving to Sending end if self.gdata.flow2dir == True: for k in sclim: for gn in gnodes: for t in time: name='gas_balance({0},{1},{2})'.format(gn,k,t) lhs=gb.quicksum(var.gprod[gw,k,t] for gw in self.gdata.Map_Gn2Gp[gn]) +\ gb.quicksum(var.qout_sr[pl,k,t] - var.qin_rs[pl,k,t] for pl in self.gdata.nodetoinpplines[gn]) +\ gb.quicksum(var.qout_rs[pl,k,t] - var.qin_sr[pl,k,t] for pl in self.gdata.nodetooutpplines[gn])+\ gb.quicksum(var.gsout[gs,k,t] - var.gsin[gs,k,t] for gs in self.gdata.Map_Gn2Gs[gn]) rhs=self.gdata.gasload[gn][t]+ gb.quicksum((Pgen[gen][t]+ \ PgenSC[gen][t]+RSC[gen,k,t])*self.gdata.generatorinfo.HR[gen] for gen in self.gdata.gfpp if gen in self.gdata.Map_Gn2Eg[gn] ) add_constraint(self,-lhs,'==',-rhs,name=name) elif self.gdata.flow2dir == False: for t in time: for gn in gnodes: for k in sclim: name='gas_balance({0},{1},{2})'.format(gn,k,t) lhs= gb.quicksum(var.gprod[gw,k,t] for gw in self.gdata.Map_Gn2Gp[gn]) \ + gb.quicksum(var.qout_sr[pl,k,t] for pl in self.gdata.nodetoinpplines[gn])\ - gb.quicksum(var.qin_sr[pl,k,t] for pl in self.gdata.nodetooutpplines[gn]) \ + gb.quicksum(var.gsout[gs,k,t] - var.gsin[gs,k,t] for gs in self.gdata.Map_Gn2Gs[gn]) rhs= self.gdata.gasload[gn][t] + gb.quicksum((Pgen[gen][t]+ \ PgenSC[gen][t]+RSC[gen,k,t])*HR[gen] for gen in self.gdata.gfpp if gen in self.gdata.Map_Gn2Eg[gn] ) add_constraint(self,-lhs,'==',-rhs,name=name) m.update() #============================================================================== # Real-time market #============================================================================== def _build_constraints_gasRT(self,dispatchGasDA,dispatchElecRT): m = self.model var = self.variables gnodes = self.gdata.gnodes pplines = self.gdata.pplineorder time = self.gdata.time gndata = self.gdata.gnodedf gstorage = self.gdata.gstorage gwells = self.gdata.wellsinfo.index.tolist() bigM = self.gdata.bigM scenarios = self.gdata.scenarios gprod = dispatchGasDA.gprod qin_sr = dispatchGasDA.qin_sr qout_sr = dispatchGasDA.qout_sr if self.gdata.GasSlack=='FixInput': gn=self.gdata.gnodeorder[0] for t in time: for s in scenarios: name="PresSlackMax({0},{1},{2})".format(gn,s,t) lhs=var.pr_rt[gn,s,t] rhs=self.gdata.gnodedf['PresMax'][gn] add_constraint(self,lhs,'==',rhs,name) elif self.gdata.GasSlack=='FixOutput': gn=self.gdata.gnodeorder[-1] # Do it for last node for t in time: for s in scenarios: name="PresSlackMin({0},{1},{2})".format(gn,s,t) lhs=var.pr_rt[gn,s,t] rhs=self.gdata.gnodedf['PresMax'][gn] add_constraint(self,lhs,'==',rhs,name) elif self.gdata.GasSlack == 'ConstantOutput': gn=self.gdata.gnodeorder[0] for tpr, t in zip(time, time[1:]): for s in scenarios: name="Constant_Slack({},{},{})".format(gn,t,tpr) lhs= var.pr_rt[gn,s,t]-var.pr_rt[gn,s,tpr] rhs=np.float64(0.0) add_constraint(self,lhs,'==',rhs,name) #--- Gas pressure limits for gn in gnodes: for t in time: for s in scenarios: name="PresMax({0},{1},{2})".format(gn,s,t) lhs=var.pr_rt[gn,s,t] rhs=self.gdata.gnodedf['PresMax'][gn] add_constraint(self,lhs,'<=',rhs,name) name="PresMin({0},{1},{2})".format(gn,s,t) lhs=var.pr_rt[gn,s,t] rhs=self.gdata.gnodedf['PresMin'][gn] add_constraint(self,lhs,'>=',rhs,name) # for t in time: # for s in scenarios: # name='Send_geq_Receive_rt{0}{1}'.format(t,s) # lhs=var.pr_rt['ng101',s,t] # rhs=var.pr_rt['ng102',s,t] # add_constraint(self,lhs,'>=',rhs,name) # #--- Outer Approximation # Gas flow outer approximation OuterApprox_Discretization(self) if self.gdata.flow2dir == True: u = var.u # if bi-directional flow u={0,1} elif self.gdata.flow2dir == False: u = dict.fromkeys(self.variables.gflow_sr_rt, 1.0) # if bi-directional flow u={1} i.e. from send to receive Kpos=self.gdata.Kpos prd=self.gdata.prd for pl in self.gdata.pplineorder: ns, nr = pl for t in time: for s in scenarios: # name = "gflow_sr_rt_logical_BIG_M({0},{1},{2})".format(pl,s,t).replace(" ","") # lhs=var.gflow_sr_rt[pl,s,t]-u[pl,s,t]*bigM # rhs=np.float64(0.0) # add_constraint(self,lhs,'<=',rhs,name) for vs, vr in Kpos[pl].keys(): name = "gflow_sr_rt_lim_approx_weymouth({0},{1},{2},{3},{4})".format(pl,s,t,vs,vr).replace(" ","") lhs=var.gflow_sr_rt[pl,s,t] rhs=Kpos[pl][vs,vr] * prd[ns][vs] * var.pr_rt[ns,s,t] - \ Kpos[pl][vs,vr] * prd[nr][vr] * var.pr_rt[nr,s,t] #+ bigM * (1.0 - u[pl,s,t]) add_constraint(self,lhs,'<=',rhs,name) # if bi-directional flow model flow limits from Receiving to Sending end # if bi-directional flow add constraints from Receiving to Sending end if self.gdata.flow2dir == True: Kneg=self.gdata.Kneg prd=self.gdata.prd for pl in self.gdata.pplineorder: ns, nr = pl for t in time: for s in scenarios: name = "gflow_rs_rt_logical_BIG_M({0},{1},{2})".format(pl,s,t).replace(" ","") lhs=var.gflow_rs[pl,s,t] rhs=(1.0-u[pl,s,t])*bigM add_constraint(self,lhs,'<=',rhs,name) for vs, vr in self.gdata.Kneg[pl].keys(): name = "gflow_rs_rt_lim_approx_weymouth({0},{1},{2},{3},{4})".format(pl,s,t,vs,vr).replace(" ","") lhs=var.gflow_rs_rt[pl,s,t] rhs= Kneg[pl][vs,vr] * prd[nr][vr] * var.pr_rt[nr,s,t] - \ Kneg[pl][vs,vr] * prd[ns][vs] * var.pr_rt[ns,s,t] +\ bigM * u[pl,s,t] add_constraint(self,lhs,'<=',rhs,name) # Gas well maximum production for gw in gwells: for s in scenarios: for t in time: name="gprodUp_max({0},{1},{2})".format(gw,s,t) lhs= var.gprodUp[gw,s,t] rhs=self.gdata.wellsinfo['MaxProd'][gw]-gprod[gw][t]['k0'] add_constraint(self,lhs,'<=',rhs,name) name="gprodDn_max({0},{1},{2})".format(gw,s,t) lhs= var.gprodDn[gw,s,t] rhs=gprod[gw][t]['k0'] add_constraint(self,lhs,'<=',rhs,name) # Compressors - Limit the outlet pressure of compressor to be less than # full compression (max) and above the inlet pressure (min) # Compression rate definition - Active pipelines for pl in self.gdata.pplineactive: ns, nr = pl for t in time: for s in scenarios: name = 'compr_rt_max({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs= var.pr_rt[nr,s,t] -self.gdata.pplinecr[pl] * var.pr_rt[ns,s,t] rhs= np.float64(0.0) add_constraint(self,lhs,'<=',rhs,name) name = 'compr_rt_min({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs=var.pr_rt[ns,s,t] -var.pr_rt[nr,s,t] rhs= np.float64(0.0) add_constraint(self,lhs,'<=',rhs,name) # Line-pack constraints for pl in pplines: ns, nr = pl for t in time: for s in scenarios: name='gflow_sr_io_rt({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs=var.gflow_sr_rt[pl,s,t]-(var.qin_sr_rt[pl,s,t] + var.qout_sr_rt[pl,s,t]) * 0.5 rhs=np.float64(0.0) add_constraint(self,-lhs,'==',-rhs,name) name = 'lpack_def_rt({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs=var.lpack_rt[pl,s,t]-self.gdata.pplinels[pl]*0.5*(var.pr_rt[ns,s,t]+var.pr_rt[nr,s,t]) rhs= np.float64(0.0) add_constraint(self,-lhs,'==',-rhs,name) ''' NB! gflow_rs_io = {} # Gas flow (R to S) only if bi-directional flow. This needs to be included in the line-pack definition constraint ''' for pl in pplines: ns, nr = pl for s in scenarios: for tpr, t in zip(time, time[1:]): name='line_store_rt({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs=var.lpack_rt[pl,s,t] -var.lpack_rt[pl,s,tpr] - var.qin_sr_rt[pl,s,t] + var.qout_sr_rt[pl,s,t] rhs= np.float64(0.0) add_constraint(self,-lhs,'==',-rhs,name) t = time[0] name='line_store_rt({0},{1},{2})'.format(pl,s,t).replace(" ","") lhs=var.lpack_rt[pl,s,t] - var.qin_sr_rt[pl,s,t] + var.qout_sr_rt[pl,s,t] rhs= self.gdata.pplinelsini[pl] add_constraint(self,-lhs,'==',-rhs,name) # for t in time: # name='ss{0},{1},{2}'.format(pl,s,t) # lhs=- var.qin_sr_rt[pl,s,t] + var.qout_sr_rt[pl,s,t] # rhs=np.float64(0.0) # add_constraint(self,lhs,'==',rhs,name) for s in scenarios: name='lpack_end_max({0})'.format(s) lhs=gb.quicksum(var.lpack_rt[pl, s, time[-1]] for pl in pplines) rhs= (1.0+defaults.FINAL_LP_DEV)*gb.quicksum(self.gdata.pplinelsini[pl] for pl in pplines) add_constraint(self,lhs,'<=',rhs,name) name='lpack_end_min({0})'.format(s) lhs=gb.quicksum(var.lpack_rt[pl, s, time[-1]] for pl in pplines) rhs= (1.0-defaults.FINAL_LP_DEV)*gb.quicksum(self.gdata.pplinelsini[pl] for pl in pplines) add_constraint(self,rhs,'<=',lhs,name) # # Gas Storage for gs in self.gdata.gstorage: for t in time: for s in scenarios: name='gsinMax_rt({0},{1},{2})'.format(gs,t,s) lhs=var.gsin_rt[gs,s,t] rhs=self.gdata.gstorageinfo['MaxInFlow'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gsoutMax_rt({0},{1},{2})'.format(gs,t,s) lhs=var.gsout_rt[gs,s,t] rhs=self.gdata.gstorageinfo['MaxOutFlow'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gstore_max_rt({0},{1},{2})'.format(gs,t,s) lhs=var.gstore_rt[gs,s,t] rhs=self.gdata.gstorageinfo['MaxStore'][gs] add_constraint(self,lhs,'<=',rhs,name) name='gstore_min_rt({0},{1},{2})'.format(gs,t,s) lhs=var.gstore_rt[gs,s,t] rhs=self.gdata.gstorageinfo['MinStore'][gs] add_constraint(self,lhs,'>=',rhs,name) for gs in gstorage: for s in scenarios: for tpr, t in zip(time, time[1:]): name='gstor_def_rt({0},{1},{2})'.format(gs,s,t) lhs=var.gstore_rt[gs,s,t] rhs= var.gstore_rt[gs,s,tpr]+var.gsin_rt[gs,s,t]-var.gsout_rt[gs,s,t] add_constraint(self,-lhs,'==',-rhs,name) t = time[0] name='gstor_def_rt({0},{1},{2})'.format(gs,s,t) lhs=var.gstore_rt[gs,s,t] rhs= self.gdata.gstorageinfo['IniStore'][gs]+var.gsin_rt[gs,s,t]-var.gsout_rt[gs,s,t] add_constraint(self,-lhs,'==',-rhs,name) # At end of time the linepack should be +/- 10% percent of the initial value # Actual deviations stored in defaults.FINAL_LP_DEV name='gstor_end({0},{1})'.format(gs,s) lhs=var.gstore_rt[gs, s, time[-1]] rhs= self.gdata.gstorageinfo['IniStore'][gs] add_constraint(self,lhs,'>=',rhs,name) # Gas shedding for s in scenarios: for gn in gnodes: for t in time: name = 'gas_shed_rt({0},{1},{2})'.format(gn,s,t) lhs= var.gshed_rt[gn,s,t] rhs= self.gdata.gasload[gn][t] add_constraint(self,lhs,'<=',rhs,name) # Nodal Gas Balance : Real-time # Here modeled only for 'uni-directional' gas flow (from S to R) ########################################################################### # Swing constracts can be defined per Gas Node - Here defined per GFPP # ... we need the GFPP node mapping and efficiencies ########################################################################### # Up/down reserve deployment by GFPP RUp_gfpp = dispatchElecRT.RUpSC.add(dispatchElecRT.RUp.loc[:, self.gdata.gfpp]) RDn_gfpp = dispatchElecRT.RDnSC.add(dispatchElecRT.RDn.loc[:, self.gdata.gfpp]) Rgfpp = RUp_gfpp - RDn_gfpp # Day-ahead gas flows qin_sr = dispatchGasDA.qin_sr qout_sr = dispatchGasDA.qout_sr HR=self.gdata.generatorinfo.HR # Day-ahead gas storage schedule gsin = dispatchGasDA.gsin gsout = dispatchGasDA.gsout for s in scenarios: for gn in gnodes: for t in time: name='gas_balance({0},{1},{2})'.format(gn,s,t) lhs= gb.quicksum(( var.gprodUp[gw,s,t] - var.gprodDn[gw,s,t]) for gw in self.gdata.Map_Gn2Gp[gn]) \ - gb.quicksum(( qout_sr[pl][t]['k0'] - var.qout_sr_rt[pl,s,t]) for pl in self.gdata.nodetoinpplines[gn]) \ + gb.quicksum(( qin_sr[pl][t]['k0'] - var.qin_sr_rt[pl,s,t] ) for pl in self.gdata.nodetooutpplines[gn]) \ + gb.quicksum(( var.gsout_rt[gs,s,t] - gsout[gs][t]['k0'] + gsin[gs][t]['k0'] - var.gsin_rt[gs,s,t]) for gs in self.gdata.Map_Gn2Gs[gn]) \ - gb.quicksum(Rgfpp[gen][t,s]*(HR[gen]) for gen in self.gdata.gfpp if gen in self.gdata.Map_Gn2Eg[gn]) \ + var.gshed_rt[gn,s,t] # Load SHedding rhs = np.float64(0.0) add_constraint(self,-lhs,'==',-rhs,name) m.update()

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null

0

6

7e10b64fdea6ed79f0a6e5b48c6b890f0791f12d

71

py

Python

paleocirc/__init__.py

xFranciB/PaleoCirc

bb95abf973342c004c4f84516092a686072bc12e

[ "MIT" ]

7

2021-02-16T15:41:59.000Z

2021-12-22T19:56:23.000Z

paleocirc/__init__.py

xFranciB/PaleoCirc

bb95abf973342c004c4f84516092a686072bc12e

[ "MIT" ]

5

2021-04-16T13:36:31.000Z

2021-12-12T17:43:13.000Z

paleocirc/__init__.py

xFranciB/paleocirc

bb95abf973342c004c4f84516092a686072bc12e

[ "MIT" ]

null

from .circolari import Circolari from .circolariasync import Circolari

35.5

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6

fd68b737ef778b3db9969f5d85a34c2aceac54f0

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py

Python

src/apis/__init__.py

wangyingbo/sspanel-mining

1b1d7caf195388e1d9144979b740c52b7163f477

[ "Apache-2.0" ]

1

2021-11-03T12:09:27.000Z

src/apis/__init__.py

starkiller43/sspanel-mining

27a7dd1fafcf551808245a69f2f449d5d52a0df7

[ "Apache-2.0" ]

null

src/apis/__init__.py

starkiller43/sspanel-mining

27a7dd1fafcf551808245a69f2f449d5d52a0df7

[ "Apache-2.0" ]

null

from .v2rss_api import v2rss_api

16.5

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0.121212

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6

fd6aa81e5fa5469d3c5161c0f5454a706b080667

42

py

Python

gym_npm/envs/__init__.py

a-nooj/gym-npm

650f49c25affef7cbe9d577106a860bebcb3ce5e

[ "MIT" ]

null

gym_npm/envs/__init__.py

a-nooj/gym-npm

650f49c25affef7cbe9d577106a860bebcb3ce5e

[ "MIT" ]

null

gym_npm/envs/__init__.py

a-nooj/gym-npm

650f49c25affef7cbe9d577106a860bebcb3ce5e

[ "MIT" ]

null

from gym_npm.envs.poke_env import PokeEnv

21

41

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6

fd944b87d6451d4118df7269e6fae293180e4976

157

py

Python

cqrs_template/authentication/__init__.py

wcomartin/cqrs-feature-template

bc9e5c2598f0290c110c5e199f8de056d6641d9a

[ "MIT" ]

null

cqrs_template/authentication/__init__.py

wcomartin/cqrs-feature-template

bc9e5c2598f0290c110c5e199f8de056d6641d9a

[ "MIT" ]

null

cqrs_template/authentication/__init__.py

wcomartin/cqrs-feature-template

bc9e5c2598f0290c110c5e199f8de056d6641d9a

[ "MIT" ]

null

from flask import Blueprint authentication = Blueprint('authentication', __name__) from .features.auth_login import * from .features.register_user import *

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6

fdc279afff0c8589fbc2f06edb9671098bb6fb6f

1,079

py

Python

autolens/aggregator/__init__.py

rakaar/PyAutoLens

bc140c5d196c426092c1178b8abfa492c6fab859

[ "MIT" ]

null

autolens/aggregator/__init__.py

rakaar/PyAutoLens

bc140c5d196c426092c1178b8abfa492c6fab859

[ "MIT" ]

null

autolens/aggregator/__init__.py

rakaar/PyAutoLens

bc140c5d196c426092c1178b8abfa492c6fab859

[ "MIT" ]

null

from autolens.aggregator.aggregator import grid_search_result_as_array from autolens.aggregator.aggregator import ( grid_search_log_evidences_as_array_from_grid_search_result, grid_search_subhalo_masses_as_array_from_grid_search_result, grid_search_subhalo_centres_as_array_from_grid_search_result, ) from autolens.aggregator.aggregator import fit_imaging_from_agg_obj from autolens.aggregator.aggregator import ( fit_imaging_generator_from_aggregator as FitImaging, ) from autolens.aggregator.aggregator import ( fit_interferometer_generator_from_aggregator as FitInterferometer, ) from autolens.aggregator.aggregator import masked_imaging_from_agg_obj from autolens.aggregator.aggregator import ( masked_imaging_generator_from_aggregator as MaskedImaging, ) from autolens.aggregator.aggregator import ( masked_interferometer_generator_from_aggregator as MaskedInterferometer, ) from autolens.aggregator.aggregator import tracer_from_agg_obj from autolens.aggregator.aggregator import tracer_generator_from_aggregator as Tracer

46.913043

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null

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1

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1

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6

fdda6b7d629d60335eedd79d09665c38fe15cdcc

115

py

Python

molecool/molecool_io/__init__.py

hgandhi2411/Molecool

aa2471241abcbe74443b6d764c7f7874645673aa

[ "BSD-3-Clause" ]

null

molecool/molecool_io/__init__.py

hgandhi2411/Molecool

aa2471241abcbe74443b6d764c7f7874645673aa

[ "BSD-3-Clause" ]

1

2020-02-05T19:19:57.000Z

molecool/molecool_io/__init__.py

hgandhi2411/Molecool

aa2471241abcbe74443b6d764c7f7874645673aa

[ "BSD-3-Clause" ]

null

""" Import functions for molecool_io subpackage """ from .xyz import open_xyz, write_xyz from .pdb import open_pdb

19.166667

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null

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1

0

1

0

6

e3053c014a29507ee6e8930f738925e516a97b42

31,054

py

Python

goutdotcom/ultaid/views.py

Spiewart/goutdotcom

0916155732a72fcb8c8a2fb0f4dd81efef618af8

[ "MIT" ]

null

goutdotcom/ultaid/views.py

Spiewart/goutdotcom

0916155732a72fcb8c8a2fb0f4dd81efef618af8

[ "MIT" ]

null

goutdotcom/ultaid/views.py

Spiewart/goutdotcom

0916155732a72fcb8c8a2fb0f4dd81efef618af8

[ "MIT" ]

null

from django.contrib.auth.mixins import LoginRequiredMixin from django.shortcuts import redirect from django.views.generic import CreateView, DetailView, UpdateView from ..history.forms import ( AllopurinolHypersensitivitySimpleForm, CKDForm, ErosionsForm, FebuxostatHypersensitivitySimpleForm, HeartAttackSimpleForm, OrganTransplantForm, StrokeSimpleForm, TophiForm, XOIInteractionsSimpleForm, ) from ..history.models import ( CKD, AllopurinolHypersensitivity, Erosions, FebuxostatHypersensitivity, HeartAttack, OrganTransplant, Stroke, Tophi, XOIInteractions, ) from ..ppxaid.models import PPxAid from ..ult.models import ULT from .forms import ULTAidForm from .models import ULTAid class ULTAidCreate(CreateView): model = ULTAid form_class = ULTAidForm CKD_form_class = CKDForm erosions_form_class = ErosionsForm XOI_interactions_form_class = XOIInteractionsSimpleForm organ_transplant_form_class = OrganTransplantForm allopurinol_hypersensitivity_form_class = AllopurinolHypersensitivitySimpleForm febuxostat_hypersensitivity_form_class = FebuxostatHypersensitivitySimpleForm heartattack_form_class = HeartAttackSimpleForm stroke_form_class = StrokeSimpleForm tophi_form_class = TophiForm def form_valid(self, form): # Check if POST has 'ult' kwarg and assign ULTAid ult OnetoOne related object based on pk='ult' if self.kwargs.get("ult"): form.instance.ult = ULT.objects.get(pk=self.kwargs.get("ult")) form.instance.erosions = form.instance.ult.erosions form.instance.tophi = form.instance.ult.tophi # Check if ULT calculator() result was indicated or conditional and set ULTAid need field true if so, False if not if form.instance.ult.calculator() == "Indicated" or form.instance.ult.calculator() == "Conditional": form.instance.need = True else: form.instance.need = False # If user is not authenticated and created a ULTAid from a ULT, use ULT CKD instance instead of making new one, removed forms in form via Kwargs and layout objects if self.request.user.is_authenticated == False: if form.instance.ult.ckd.value == False: form.instance.ckd = form.instance.ult.ckd if self.request.user.is_authenticated: form.instance.user = self.request.user return super().form_valid(form) else: return super().form_valid(form) def get(self, request, *args, **kwargs): # Checks if user is logged in, if they have already created a ULTAid, and redirects to UpdateView if so if self.request.user.is_authenticated: try: user_ULTAid = self.model.objects.get(user=self.request.user) except self.model.DoesNotExist: user_ULTAid = None if user_ULTAid: return redirect("ultaid:update", pk=self.model.objects.get(user=self.request.user).pk) else: return super().get(request, *args, **kwargs) else: return super().get(request, *args, **kwargs) def get_context_data(self, **kwargs): context = super(ULTAidCreate, self).get_context_data(**kwargs) ## IS IF NOT IN CONTEXT STATEMENT NECESSARY? TEST IT BY DELETING ## WHAT IF USER IS NOT LOGGED IN? CHECK CONTEXT # Add ULTAid OnetoOne related model objects from the MedicalProfile for the logged in User if self.request.user.is_anonymous == False: if "CKD_form" not in context: context["CKD_form"] = self.CKD_form_class(instance=self.request.user.medicalprofile.CKD) if "erosions_form" not in context: context["erosions_form"] = self.erosions_form_class(instance=self.request.user.medicalprofile.erosions) if "XOI_interactions_form" not in context: context["XOI_interactions_form"] = self.XOI_interactions_form_class( instance=self.request.user.medicalprofile.XOI_interactions ) if "organ_transplant_form" not in context: context["organ_transplant_form"] = self.organ_transplant_form_class( instance=self.request.user.medicalprofile.organ_transplant ) if "allopurinol_hypersensitivity_form" not in context: context["allopurinol_hypersensitivity_form"] = self.allopurinol_hypersensitivity_form_class( instance=self.request.user.medicalprofile.allopurinol_hypersensitivity ) if "febuxostat_hypersensitivity_form" not in context: context["febuxostat_hypersensitivity_form"] = self.febuxostat_hypersensitivity_form_class( instance=self.request.user.medicalprofile.febuxostat_hypersensitivity ) if "heartattack_form" not in context: context["heartattack_form"] = self.heartattack_form_class( instance=self.request.user.medicalprofile.heartattack ) if "stroke_form" not in context: context["stroke_form"] = self.stroke_form_class(instance=self.request.user.medicalprofile.stroke) if "tophi_form" not in context: context["tophi_form"] = self.tophi_form_class(instance=self.request.user.medicalprofile.tophi) # Check if user is logged in, pass ULT results to ULTAid view/context for JQuery evaluation to update form fields #### IS THIS NEEDED FOR POST? if self.request.user.is_authenticated: if self.request.user.ult: context["user_ult"] = ULT.objects.get(user=self.request.user).calculator() return context else: if "CKD_form" not in context: context["CKD_form"] = self.CKD_form_class(self.request.GET) if "erosions_form" not in context: context["erosions_form"] = self.erosions_form_class(self.request.GET) if "XOI_interactions_form" not in context: context["XOI_interactions_form"] = self.XOI_interactions_form_class(self.request.GET) if "organ_transplant_form" not in context: context["organ_transplant_form"] = self.organ_transplant_form_class(self.request.GET) if "allopurinol_hypersensitivity_form" not in context: context["allopurinol_hypersensitivity_form"] = self.allopurinol_hypersensitivity_form_class( self.request.GET ) if "febuxostat_hypersensitivity_form" not in context: context["febuxostat_hypersensitivity_form"] = self.febuxostat_hypersensitivity_form_class( self.request.GET ) if "heartattack_form" not in context: context["heartattack_form"] = self.heartattack_form_class(self.request.GET) if "stroke_form" not in context: context["stroke_form"] = self.stroke_form_class(self.request.GET) if "tophi_form" not in context: context["tophi_form"] = self.tophi_form_class(self.request.GET) return context def get_form_kwargs(self): """Ovewrites get_form_kwargs() to look for 'ult' kwarg in GET request, uses 'ult' to query database for associated ULT for use in ULTAidForm returns: [dict: dict containing 'ult' kwarg for form]""" # Assign self.flare from GET request kwargs before calling super() which will overwrite kwargs self.ult = self.kwargs.get("ult", None) self.no_user = False if self.request.user.is_authenticated == False: self.no_user = True kwargs = super(ULTAidCreate, self).get_form_kwargs() # Checks if flare kwarg came from Flare Detail and queries database for flare_pk that matches self.flare from initial kwargs if self.ult: ult_pk = self.ult ult = ULT.objects.get(pk=ult_pk) kwargs["ult"] = ult kwargs["no_user"] = self.no_user # If User is anonymous / not logged in and FlareAid has a Flare, pass ckd from ULT to ULTAid to avoid duplication of user input if self.request.user.is_authenticated == False: kwargs["ckd"] = ult.ckd return kwargs # This unfortunately needs to get rewritten and the object assigned at the start of POST once you mess with enough CBV code. Not sure what exactly triggers it. def get_object(self): object = self.model return object def post(self, request, **kwargs): form = self.form_class(request.POST, instance=ULTAid()) self.object = self.get_object() if form.is_valid(): ULTAid_data = form.save(commit=False) ## WOULD LIKE TO CONSOLIDATE REQUEST.USER ADD TO RIGHT BEFORE SAVE(), THEN CAN COMBINE THE REST # Check if user is authenticated and pull OnetoOne related model data from MedicalProfile if so if request.user.is_authenticated: ULTAid_data.user = request.user CKD_form = self.CKD_form_class(request.POST, instance=request.user.medicalprofile.CKD) CKD_data = CKD_form.save(commit=False) CKD_data.last_modified = "ULTAid" CKD_data.save() erosions_form = self.erosions_form_class(request.POST, instance=request.user.medicalprofile.erosions) erosions_data = erosions_form.save(commit=False) erosions_data.last_modified = "ULTAid" erosions_data.save() XOI_interactions_form = self.XOI_interactions_form_class( request.POST, instance=request.user.medicalprofile.XOI_interactions ) XOI_interactions_data = XOI_interactions_form.save(commit=False) XOI_interactions_data.last_modified = "ULTAid" XOI_interactions_data.save() organ_transplant_form = self.organ_transplant_form_class( request.POST, instance=request.user.medicalprofile.organ_transplant ) organ_transplant_data = organ_transplant_form.save(commit=False) organ_transplant_data.last_modified = "ULTAid" organ_transplant_data.save() allopurinol_hypersensitivity_form = self.allopurinol_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.allopurinol_hypersensitivity ) allopurinol_hypersensitivity_data = allopurinol_hypersensitivity_form.save(commit=False) allopurinol_hypersensitivity_data.last_modified = "ULTAid" allopurinol_hypersensitivity_data.save() febuxostat_hypersensitivity_form = self.febuxostat_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.febuxostat_hypersensitivity ) febuxostat_hypersensitivity_data = febuxostat_hypersensitivity_form.save(commit=False) febuxostat_hypersensitivity_data.last_modified = "ULTAid" febuxostat_hypersensitivity_data.save() heartattack_form = self.heartattack_form_class( request.POST, instance=request.user.medicalprofile.heartattack ) heartattack_data = heartattack_form.save(commit=False) heartattack_data.last_modified = "ULTAid" heartattack_data.save() stroke_form = self.stroke_form_class(request.POST, instance=request.user.medicalprofile.stroke) stroke_data = stroke_form.save(commit=False) stroke_data.last_modified = "ULTAid" stroke_data.save() tophi_form = self.tophi_form_class(request.POST, instance=request.user.medicalprofile.tophi) tophi_data = tophi_form.save(commit=False) tophi_data.last_modified = "ULTAid" tophi_data.save() ULTAid_data.ckd = CKD_data ULTAid_data.erosions = erosions_data ULTAid_data.XOI_interactions = XOI_interactions_data ULTAid_data.organ_transplant = organ_transplant_data ULTAid_data.allopurinol_hypersensitivity = allopurinol_hypersensitivity_data ULTAid_data.febuxostat_hypersensitivity = febuxostat_hypersensitivity_data ULTAid_data.heartattack = heartattack_data ULTAid_data.stroke = stroke_data ULTAid_data.tophi = tophi_data ULTAid_data.save() # Check if User has already created a PPxAid for some reason and, if so, assign it to the newly created/saved ULTAid to that attribute on the PPxAid try: self.ppxaid = request.user.ppxaid except PPxAid.DoesNotExist: self.ppxaid = None if self.ppxaid: self.ppxaid.ultaid = ULTAid_data self.ppxaid.save() else: CKD_form = self.CKD_form_class(request.POST, instance=CKD()) CKD_data = CKD_form.save(commit=False) CKD_data.last_modified = "ULTAid" CKD_data.save() erosions_form = self.erosions_form_class(request.POST, instance=Erosions()) erosions_data = erosions_form.save(commit=False) erosions_data.last_modified = "ULTAid" erosions_data.save() XOI_interactions_form = self.XOI_interactions_form_class(request.POST, instance=XOIInteractions()) XOI_interactions_data = XOI_interactions_form.save(commit=False) XOI_interactions_data.last_modified = "ULTAid" XOI_interactions_data.save() organ_transplant_form = self.organ_transplant_form_class(request.POST, instance=OrganTransplant()) organ_transplant_data = organ_transplant_form.save(commit=False) organ_transplant_data.last_modified = "ULTAid" organ_transplant_data.save() allopurinol_hypersensitivity_form = self.allopurinol_hypersensitivity_form_class( request.POST, instance=AllopurinolHypersensitivity() ) allopurinol_hypersensitivity_data = allopurinol_hypersensitivity_form.save(commit=False) allopurinol_hypersensitivity_data.last_modified = "ULTAid" allopurinol_hypersensitivity_data.save() febuxostat_hypersensitivity_form = self.febuxostat_hypersensitivity_form_class( request.POST, instance=FebuxostatHypersensitivity() ) febuxostat_hypersensitivity_data = febuxostat_hypersensitivity_form.save(commit=False) febuxostat_hypersensitivity_data.last_modified = "ULTAid" febuxostat_hypersensitivity_data.save() heartattack_form = self.heartattack_form_class(request.POST, instance=HeartAttack()) heartattack_data = heartattack_form.save(commit=False) heartattack_data.last_modified = "ULTAid" heartattack_data.save() stroke_form = self.stroke_form_class(request.POST, instance=Stroke()) stroke_data = stroke_form.save(commit=False) stroke_data.last_modified = "ULTAid" stroke_data.save() tophi_form = self.tophi_form_class(request.POST, instance=Tophi()) tophi_data = tophi_form.save(commit=False) tophi_data.last_modified = "ULTAid" tophi_data.save() ULTAid_data.ckd = CKD_data ULTAid_data.erosions = erosions_data ULTAid_data.XOI_interactions = XOI_interactions_data ULTAid_data.organ_transplant = organ_transplant_data ULTAid_data.allopurinol_hypersensitivity = allopurinol_hypersensitivity_data ULTAid_data.febuxostat_hypersensitivity = febuxostat_hypersensitivity_data ULTAid_data.heartattack = heartattack_data ULTAid_data.stroke = stroke_data ULTAid_data.tophi = tophi_data ULTAid_data.save() # Need to call form_valid(), not redirect. form_valid() super function returns to object DetailView return self.form_valid(form) else: if request.user.is_authenticated: return self.render_to_response( self.get_context_data( form=form, CKD_form=self.CKD_form_class(request.POST, instance=request.user.medicalprofile.CKD), erosions_form=self.erosions_form_class( request.POST, instance=request.user.medicalprofile.erosions ), XOI_interactions_form=self.XOI_interactions_form_class( request.POST, instance=request.user.medicalprofile.XOI_interactions ), organ_transplant_form=self.organ_transplant_form_class( request.POST, instance=request.user.medicalprofile.organ_transplant ), allopurinol_hypersensitivity_form=self.allopurinol_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.allopurinol_hypersensitivity ), febuxostat_hypersensitivity_form=self.febuxostat_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.febuxostat_hypersensitivity ), heartattack_form=self.heartattack_form_class( request.POST, instance=request.user.medicalprofile.heartattack ), stroke_form=self.stroke_form_class(request.POST, instance=request.user.medicalprofile.stroke), tophi_form=self.tophi_form_class(request.POST, instance=request.user.medicalprofile.tophi), ) ) else: return self.render_to_response( self.get_context_data( form=form, CKD_form=self.CKD_form_class(request.POST, instance=CKD()), erosions_form=self.erosions_form_class(request.POST, instance=Erosions()), XOI_interactions_form=self.XOI_interactions_form_class( request.POST, instance=XOIInteractions() ), organ_transplant_form=self.organ_transplant_form_class( request.POST, instance=OrganTransplant() ), allopurinol_hypersensitivity_form=self.allopurinol_hypersensitivity_form_class( request.POST, instance=AllopurinolHypersensitivity() ), febuxostat_hypersensitivity_form=self.febuxostat_hypersensitivity_form_class( request.POST, instance=FebuxostatHypersensitivity() ), heartattack_form=self.heartattack_form_class(request.POST, instance=HeartAttack()), stroke_form=self.stroke_form_class(request.POST, instance=Stroke()), tophi_form=self.tophi_form_class(request.POST, instance=Tophi()), ) ) class ULTAidDetail(DetailView): model = ULTAid class ULTAidUpdate(LoginRequiredMixin, UpdateView): model = ULTAid form_class = ULTAidForm CKD_form_class = CKDForm erosions_form_class = ErosionsForm XOI_interactions_form_class = XOIInteractionsSimpleForm organ_transplant_form_class = OrganTransplantForm allopurinol_hypersensitivity_form_class = AllopurinolHypersensitivitySimpleForm febuxostat_hypersensitivity_form_class = FebuxostatHypersensitivitySimpleForm heartattack_form_class = HeartAttackSimpleForm stroke_form_class = StrokeSimpleForm tophi_form_class = TophiForm def get_context_data(self, **kwargs): context = super(ULTAidUpdate, self).get_context_data(**kwargs) # Adds appropriate OnetoOne related History/MedicalProfile model forms to context if self.request.POST: if "CKD_form" not in context: context["CKD_form"] = self.CKD_form_class( self.request.POST, instance=self.request.user.medicalprofile.CKD ) if "erosions_form" not in context: context["erosions_form"] = self.erosions_form_class( self.request.POST, instance=self.request.user.medicalprofile.erosions ) if "XOI_interactions_form" not in context: context["XOI_interactions_form"] = self.XOI_interactions_form_class( self.request.POST, instance=self.request.user.medicalprofile.XOI_interactions ) if "organ_transplant_form" not in context: context["organ_transplant_form"] = self.organ_transplant_form_class( self.request.POST, instance=self.request.user.medicalprofile.organ_transplant ) if "allopurinol_hypersensitivity_form" not in context: context["allopurinol_hypersensitivity_form"] = self.allopurinol_hypersensitivity_form_class( self.request.POST, instance=self.request.user.medicalprofile.allopurinol_hypersensitivity ) if "febuxostat_hypersensitivity_form" not in context: context["febuxostat_hypersensitivity_form"] = self.febuxostat_hypersensitivity_form_class( self.request.POST, instance=self.request.user.medicalprofile.febuxostat_hypersensitivity ) if "heartattack_form" not in context: context["heartattack_form"] = self.heartattack_form_class( self.request.POST, instance=self.request.user.medicalprofile.heartattack ) if "stroke_form" not in context: context["stroke_form"] = self.stroke_form_class( self.request.POST, instance=self.request.user.medicalprofile.stroke ) if "tophi_form" not in context: context["tophi_form"] = self.tophi_form_class( self.request.POST, instance=self.request.user.medicalprofile.tophi ) # Check if user is logged in, pass ULT results to ULTAid view/context for JQuery evaluation to update form fields #### IS THIS NEEDED FOR POST? if self.request.user.is_authenticated: if self.request.user.ult: context["user_ult"] = ULT.objects.get(user=self.request.user).calculator() return context else: if "CKD_form" not in context: context["CKD_form"] = self.CKD_form_class(instance=self.request.user.medicalprofile.CKD) if "erosions_form" not in context: context["erosions_form"] = self.erosions_form_class(instance=self.request.user.medicalprofile.erosions) if "XOI_interactions_form" not in context: context["XOI_interactions_form"] = self.XOI_interactions_form_class( instance=self.request.user.medicalprofile.XOI_interactions ) if "organ_transplant_form" not in context: context["organ_transplant_form"] = self.organ_transplant_form_class( instance=self.request.user.medicalprofile.organ_transplant ) if "allopurinol_hypersensitivity_form" not in context: context["allopurinol_hypersensitivity_form"] = self.allopurinol_hypersensitivity_form_class( instance=self.request.user.medicalprofile.allopurinol_hypersensitivity ) if "febuxostat_hypersensitivity_form" not in context: context["febuxostat_hypersensitivity_form"] = self.febuxostat_hypersensitivity_form_class( instance=self.request.user.medicalprofile.febuxostat_hypersensitivity ) if "heartattack_form" not in context: context["heartattack_form"] = self.heartattack_form_class( instance=self.request.user.medicalprofile.heartattack ) if "stroke_form" not in context: context["stroke_form"] = self.stroke_form_class(instance=self.request.user.medicalprofile.stroke) if "tophi_form" not in context: context["tophi_form"] = self.tophi_form_class(instance=self.request.user.medicalprofile.tophi) # Check if user is logged in, pass ULT results to ULTAid view/context for JQuery evaluation to update form fields if self.request.user.is_authenticated: if self.request.user.ult: context["user_ult"] = ULT.objects.get(user=self.request.user).calculator() return context def post(self, request, **kwargs): # Uses UpdateView to get the ULTAid instance requested and put it in a form form = self.form_class(request.POST, instance=self.get_object()) CKD_form = self.CKD_form_class(request.POST, instance=request.user.medicalprofile.CKD) erosions_form = self.erosions_form_class(request.POST, instance=request.user.medicalprofile.erosions) XOI_interactions_form = self.XOI_interactions_form_class( request.POST, instance=request.user.medicalprofile.XOI_interactions ) organ_transplant_form = self.organ_transplant_form_class( request.POST, instance=request.user.medicalprofile.organ_transplant ) allopurinol_hypersensitivity_form = self.allopurinol_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.allopurinol_hypersensitivity ) febuxostat_hypersensitivity_form = self.febuxostat_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.febuxostat_hypersensitivity ) heartattack_form = self.heartattack_form_class(request.POST, instance=request.user.medicalprofile.heartattack) stroke_form = self.stroke_form_class(request.POST, instance=request.user.medicalprofile.stroke) tophi_form = self.tophi_form_class(request.POST, instance=request.user.medicalprofile.tophi) if form.is_valid(): # Uses related OnetoOne field forms to populate ULTAid fields, changes last_modified to ULTAid, and saves all data ULTAid_data = form.save(commit=False) CKD_data = CKD_form.save(commit=False) CKD_data.last_modified = "ULTAid" CKD_data.save() erosions_data = erosions_form.save(commit=False) erosions_data.last_modified = "ULTAid" erosions_data.save() XOI_interactions_data = XOI_interactions_form.save(commit=False) XOI_interactions_data.last_modified = "ULTAid" XOI_interactions_data.save() organ_transplant_data = organ_transplant_form.save(commit=False) organ_transplant_data.last_modified = "ULTAid" organ_transplant_data.save() allopurinol_hypersensitivity_data = allopurinol_hypersensitivity_form.save(commit=False) allopurinol_hypersensitivity_data.last_modified = "ULTAid" allopurinol_hypersensitivity_data.save() febuxostat_hypersensitivity_data = febuxostat_hypersensitivity_form.save(commit=False) febuxostat_hypersensitivity_data.last_modified = "ULTAid" febuxostat_hypersensitivity_data.save() heartattack_data = heartattack_form.save(commit=False) heartattack_data.last_modified = "ULTAid" heartattack_data.save() stroke_data = stroke_form.save(commit=False) stroke_data.last_modified = "ULTAid" stroke_data.save() tophi_data = tophi_form.save(commit=False) tophi_data.last_modified = "ULTAid" tophi_data.save() ULTAid_data.ckd = CKD_data ULTAid_data.erosions = erosions_data ULTAid_data.XOI_interactions = XOI_interactions_data ULTAid_data.organ_transplant = organ_transplant_data ULTAid_data.allopurinol_hypersensitivity = allopurinol_hypersensitivity_data ULTAid_data.febuxostat_hypersensitivity = febuxostat_hypersensitivity_data ULTAid_data.heartattack = heartattack_data ULTAid_data.stroke = stroke_data ULTAid_data.tophi = tophi_data ULTAid_data.save() return self.form_valid(form) else: return self.render_to_response( self.get_context_data( form=form, CKD_form=self.CKD_form_class(request.POST, instance=request.user.medicalprofile.CKD), erosions_form=self.erosions_form_class(request.POST, instance=request.user.medicalprofile.erosions), XOI_interactions_form=self.XOI_interactions_form_class( request.POST, instance=request.user.medicalprofile.XOI_interactions ), organ_transplant_form=self.organ_transplant_form_class( request.POST, instance=request.user.medicalprofile.organ_transplant ), allopurinol_hypersensitivity_form=self.allopurinol_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.allopurinol_hypersensitivity ), febuxostat_hypersensitivity_form=self.febuxostat_hypersensitivity_form_class( request.POST, instance=request.user.medicalprofile.febuxostat_hypersensitivity ), heartattack_form=self.heartattack_form_class( request.POST, instance=request.user.medicalprofile.heartattack ), stroke_form=self.stroke_form_class(request.POST, instance=request.user.medicalprofile.stroke), tophi_form=self.tophi_form_class(request.POST, instance=request.user.medicalprofile.tophi), ) )

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0.067067

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0.780693

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31,054

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0.078702

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null

0

6

e30b9acd39b58ec2c73f9efed75cd84cbb35a0d8

163

py

Python

wbb/core/types/__init__.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

wbb/core/types/__init__.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

wbb/core/types/__init__.py

sppidy/WilliamButcherBot

8cbd1593dd44a5384f7b1c4d630aa65271282e3e

[ "MIT" ]

null

# flake8: noqa from .InlineKeyboardButtons import InlineKeyboardButtonDict from .InlineQueryResult import InlineQueryResultCachedDocument, InlineQueryResultAudio

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163

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1

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6

e30bc1ca07fc199415b9ef04c536cd1d962a8595

106

py

Python

core/tests/test_inputs.py

rodolfolotte/tec

b97c39db7c90b87b5fe61888cf63111b2a32df5a

[ "MIT" ]

4

2019-08-15T17:27:02.000Z

2022-03-15T13:36:26.000Z

core/tests/test_inputs.py

rodolfolotte/tec

b97c39db7c90b87b5fe61888cf63111b2a32df5a

[ "MIT" ]

null

core/tests/test_inputs.py

rodolfolotte/tec

b97c39db7c90b87b5fe61888cf63111b2a32df5a

[ "MIT" ]

2

2022-01-05T10:56:27.000Z

2022-03-03T14:20:11.000Z

import unittest # import core.inputs as i class PrepareInputsInputsTest(unittest.TestCase): pass

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true

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1

0

null

0

1

0

1

0

6

e38852c8a192ceb40e65f2bc5b6cdf529e81c51a

113

py

Python

nutrition_calculator/__init__.py

marekvymazal/nutrition_calculator

d59dcb8941b77cd760033072e8aca0ae749db7eb

[ "MIT" ]

null

nutrition_calculator/__init__.py

marekvymazal/nutrition_calculator

d59dcb8941b77cd760033072e8aca0ae749db7eb

[ "MIT" ]

null

nutrition_calculator/__init__.py

marekvymazal/nutrition_calculator

d59dcb8941b77cd760033072e8aca0ae749db7eb

[ "MIT" ]

null

# import NutritionCalculator class for package convenience from .nutrition_calculator import NutritionCalculator

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0

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2

59

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1

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1

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null

0

1

0

1

0

1

0

6

8b98459a8e8548d1aefe8e8ac6e74535b2b17f7f

1,661

gyp

Python

clients/android/jni/Android.gyp

sleepingAnt/viewfinder

9caf4e75faa8070d85f605c91d4cfb52c4674588

[ "Apache-2.0" ]

645

2015-01-03T02:03:59.000Z

2021-12-03T08:43:16.000Z

clients/android/jni/Android.gyp

hoowang/viewfinder

9caf4e75faa8070d85f605c91d4cfb52c4674588

[ "Apache-2.0" ]

null

clients/android/jni/Android.gyp

hoowang/viewfinder

9caf4e75faa8070d85f605c91d4cfb52c4674588

[ "Apache-2.0" ]

222

2015-01-07T05:00:52.000Z

2021-12-06T09:54:26.000Z

{ 'targets': [ { 'target_name': 'viewfinder', 'type': 'shared_library', 'include_dirs': [ '../../../third_party/shared/leveldb/include/', '../../../third_party/shared/leveldb/', '../../../third_party/shared/protobuf/src/', '../../../third_party/shared/protobuf/', '../../../third_party/shared/re2/', '../../../third_party/shared/icu', '../../../third_party/shared/icu/source/common', '../../../third_party/shared/icu/source/i18n', '../../../third_party/shared/icu/source/tools/tzcode', '../../../third_party/shared/phonenumbers/cpp/src', '../gen/', ], 'dependencies': [ '../../../third_party/shared/leveldb.gyp:libleveldb', '../../../third_party/shared/protobuf.gyp:libprotobuf', '../../../third_party/shared/snappy.gyp:libsnappy', '../../../third_party/shared/re2.gyp:libre2', '../../../third_party/shared/icu.gyp:icui18n', '../../../third_party/shared/icu.gyp:icuuc', '../../../third_party/shared/icu.gyp:icudata', '../../../third_party/shared/phonenumbers.gyp:libphonenumbers', '../../shared/shared.android.gyp:libshared', '../../shared/shared.android.gyp:sharedprotos', ], 'defines': [ 'LEVELDB_PLATFORM_ANDROID', 'LEVELDB_PLATFORM_POSIX', ], 'sources': [ 'DayTableEnv.cc', 'DBMigrationAndroid.cc', 'NativeAppState.cc', 'NetworkManagerAndroid.cc', ], 'cppflags': [ '-pthread', ], 'ldflags': [ '-lz', '-llog', ], }, ], }

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null

0

1

0

6

8be98282878886714c6f07c9f6d25db3fdea75b7

37

py

Python

core/models/__init__.py

swipswaps/retinal_oct

a99f93d88833fc328b9b7f6aaabe1310632c644b

[ "MIT" ]

15

2021-01-29T17:05:38.000Z

2022-03-16T17:47:42.000Z

core/models/__init__.py

solomonkimunyu/retinal_oct

a99f93d88833fc328b9b7f6aaabe1310632c644b

[ "MIT" ]

null

core/models/__init__.py

solomonkimunyu/retinal_oct

a99f93d88833fc328b9b7f6aaabe1310632c644b

[ "MIT" ]

14

2021-03-03T03:16:31.000Z

2022-03-23T19:23:42.000Z

from .retina_model import RetinaModel

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6.4

1

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1

37

0.941176

0

1

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1

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null

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null

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0

1

0

1

0

6

47784123f286f062d9069c60aa3210fdc987fae7

2,128

py

Python

policy/net/net_v0.py

yangmuzhi/wuziqi

7bdee51ef2a37373b0823b00c4536138560ec3bb

[ "MIT" ]

null

policy/net/net_v0.py

yangmuzhi/wuziqi

7bdee51ef2a37373b0823b00c4536138560ec3bb

[ "MIT" ]

null

policy/net/net_v0.py

yangmuzhi/wuziqi

7bdee51ef2a37373b0823b00c4536138560ec3bb

[ "MIT" ]

null

""" cnn """ import tensorflow as tf def policy_net(obs): x = tf.layers.Conv2D(filters=256, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(obs) x = tf.layers.Conv2D(filters=256, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(4,4), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(4,4), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=64, kernel_size=(3,3), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=64, kernel_size=(3,3), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.flatten(x) x = tf.layers.Dense(256, activation=tf.nn.relu)(x) pi = tf.layers.Dense(15*15, activation=tf.nn.sigmoid)(x) log_p = tf.log(pi) return pi, log_p def value_net(obs): x = tf.layers.Conv2D(filters=256, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(obs) x = tf.layers.Conv2D(filters=256, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(5,5), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(4,4), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=128, kernel_size=(4,4), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=64, kernel_size=(3,3), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.Conv2D(filters=64, kernel_size=(3,3), padding="same", use_bias=True, data_format="channels_first")(x) x = tf.layers.flatten(x) x = tf.layers.Dense(256, activation=tf.nn.relu)(x) out = tf.layers.Dense(1, activation=tf.nn.sigmoid)(x) return out

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null

0

1

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null

0

6

477a47e991128b5c1dfdcc58164ad430ca1cdf8b

231

py

Python

daskms/apps/tests/test_chunk_transformer.py

ratt-ru/dask-ms

becd3572f86a0ad78b55540f25fce6e129976a29

[ "BSD-3-Clause" ]

7

2019-08-23T03:44:53.000Z

2021-05-06T00:51:18.000Z

daskms/apps/tests/test_chunk_transformer.py

ska-sa/dask-ms

ce33e7aad36eeb7c2c79093622b9776186856304

[ "BSD-3-Clause" ]

76

2019-08-20T14:34:05.000Z

2022-02-10T13:21:29.000Z

daskms/apps/tests/test_chunk_transformer.py

ratt-ru/dask-ms

becd3572f86a0ad78b55540f25fce6e129976a29

[ "BSD-3-Clause" ]

4

2019-10-15T13:35:19.000Z

2021-03-23T14:52:23.000Z

from daskms.apps.convert import parse_chunks def test_chunk_parsing(): assert parse_chunks("{row: 1000, chan: 16}") == {"row": 1000, "chan": 16} assert parse_chunks("{row: (1000, 1000, 10)}") == {"row": (1000, 1000, 10)}

33

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0.195804

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0.27972

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0

0.164103

0.155844

231

6

80

38.5

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true

0

0.25

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null

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1

0

1

0

null

0

1

0

1

0

6

47c87188f1b48889dc0863270b6ce528269c3f88

77

py

Python

symmys/layers/__init__.py

klarh/symmys

13b232a817975a15fa471879fdd8d21de783ecd6

[ "MIT" ]

null

symmys/layers/__init__.py

klarh/symmys

13b232a817975a15fa471879fdd8d21de783ecd6

[ "MIT" ]

null

symmys/layers/__init__.py

klarh/symmys

13b232a817975a15fa471879fdd8d21de783ecd6

[ "MIT" ]

null

from .QuaternionRotation import QuaternionRotation, QuaternionRotoinversion

25.666667

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77

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0

0.077922

77

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1

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null

0

1

0

1

0

1

0

6

47f2406a4f2f3dbbd6b17b0682b5f096a773ee04

28

py

Python

sentinella/test/test/__init__.py

GloriaPG/test-plugin

2a0e3f9824bae5ba48ae262d9ba6c756453a82e5

[ "Apache-2.0" ]

null

sentinella/test/test/__init__.py

GloriaPG/test-plugin

2a0e3f9824bae5ba48ae262d9ba6c756453a82e5

[ "Apache-2.0" ]

null

sentinella/test/test/__init__.py

GloriaPG/test-plugin

2a0e3f9824bae5ba48ae262d9ba6c756453a82e5

[ "Apache-2.0" ]

null

from .test import get_stats

14

27

0.821429

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4.4

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1

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0.916667

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null

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1

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1

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1

0

6

9a5677978b7dd0975e6a7460230825726c7b801d

9,957

py

Python

tests/unit/altimeter/aws/access/test_accessor.py

jparten/altimeter

956cf7f7c2fe443751b8da393a764f8a7bb82348

[ "MIT" ]

null

tests/unit/altimeter/aws/access/test_accessor.py

jparten/altimeter

956cf7f7c2fe443751b8da393a764f8a7bb82348

[ "MIT" ]

null

tests/unit/altimeter/aws/access/test_accessor.py

jparten/altimeter

956cf7f7c2fe443751b8da393a764f8a7bb82348

[ "MIT" ]

null

import datetime import os from unittest import TestCase from altimeter.aws.access.accessor import ( AccessStep, MultiHopAccessor, SessionCache, SessionCacheValue, ) import boto3 from moto import mock_sts class TestSessionCacheValue(TestCase): def test_is_expired_when_expired(self): cache_value = SessionCacheValue( None, datetime.datetime.utcnow() - datetime.timedelta(minutes=5) ) self.assertTrue(cache_value.is_expired()) def test_is_expired_when_not_expired(self): cache_value = SessionCacheValue( None, datetime.datetime.utcnow() + datetime.timedelta(minutes=5) ) self.assertFalse(cache_value.is_expired()) class TestSessionCache(TestCase): def test_build_key(self): key = SessionCache._build_key( account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) self.assertEqual(key, "1234:test_role:test_role_session:test_region") def test_get_miss(self): cache = SessionCache() cached_session = cache.get( account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) self.assertIsNone(cached_session) def test_put_get_not_expired(self): cache = SessionCache() session = boto3.Session() cache.put( session=session, expiration=datetime.datetime.utcnow() + datetime.timedelta(minutes=5), account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) cached_session = cache.get( account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) self.assertIsNotNone(cached_session) def test_put_get_expired(self): cache = SessionCache() session = boto3.Session() cache.put( session=session, expiration=datetime.datetime.utcnow() - datetime.timedelta(minutes=5), account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) cached_session = cache.get( account_id="1234", role_name="test_role", role_session_name="test_role_session", region="test_region", ) self.assertIsNone(cached_session) class TestAccessStep(TestCase): def test_str_with_account(self): access_step = AccessStep(role_name="test_role_name", account_id="1234") self.assertEqual(str(access_step), "test_role_name@1234") def test_str_without_account(self): access_step = AccessStep(role_name="test_role_name") self.assertEqual(str(access_step), "test_role_name@target") def test_to_dict(self): access_step = AccessStep(role_name="test_role_name", account_id="1234", external_id="abcd") expected_dict = {"role_name": "test_role_name", "account_id": "1234", "external_id": "abcd"} self.assertEqual(expected_dict, access_step.to_dict()) def test_from_dict(self): d = {"role_name": "test_role_name", "account_id": "1234", "external_id": "abcd"} access_step = AccessStep.from_dict(d) self.assertEqual(access_step.to_dict(), d) def test_from_dict_without_role_name(self): d = {"account_id": "1234", "external_id": "abcd"} with self.assertRaises(ValueError): AccessStep.from_dict(d) def test_from_dict_with_external_id_env_var(self): d = {"role_name": "test_role_name", "account_id": "1234", "external_id_env_var": "EXT_ID"} os.environ["EXT_ID"] = "abcd" try: access_step = AccessStep.from_dict(d) expected_dict = { "role_name": "test_role_name", "account_id": "1234", "external_id": "abcd", } self.assertEqual(access_step.to_dict(), expected_dict) finally: del os.environ["EXT_ID"] def test_from_dict_with_external_id_env_var_missing_var(self): d = {"role_name": "test_role_name", "account_id": "1234", "external_id_env_var": "EXT_ID"} with self.assertRaises(ValueError): AccessStep.from_dict(d) @mock_sts class TestMultiHopAccessor(TestCase): def test_get_session(self): access_steps = [ AccessStep(role_name="test_role_name1", account_id="1234", external_id="abcd"), AccessStep(role_name="test_role_name2", account_id="5678"), AccessStep(role_name="test_role_name3"), ] mha = MultiHopAccessor( role_session_name="test_role_session_name", access_steps=access_steps ) session = mha.get_session("4566") self.assertIsInstance(session, boto3.Session) expected_cache_sorted_keys = [ "1234:test_role_name1:test_role_session_name:None", "4566:test_role_name3:test_role_session_name:None", "5678:test_role_name2:test_role_session_name:None", ] self.assertEqual(sorted(mha.session_cache._cache.keys()), expected_cache_sorted_keys) def test_without_access_steps(self): with self.assertRaises(ValueError): MultiHopAccessor(role_session_name="test_role_session_name", access_steps=[]) def test_with_access_steps_non_final_missing_account_id(self): access_steps = [ AccessStep(role_name="test_role_name1"), AccessStep(role_name="test_role_name2"), ] with self.assertRaises(ValueError): MultiHopAccessor(role_session_name="test_role_session_name", access_steps=access_steps) def test_with_access_steps_final_with_account_id(self): access_steps = [ AccessStep(role_name="test_role_name1", account_id="1234"), AccessStep(role_name="test_role_name2", account_id="5678"), ] with self.assertRaises(ValueError): MultiHopAccessor(role_session_name="test_role_session_name", access_steps=access_steps) def test_cache_usage(self): access_steps = [ AccessStep(role_name="test_role_name1", account_id="1234", external_id="abcd"), AccessStep(role_name="test_role_name2", account_id="5678"), AccessStep(role_name="test_role_name3"), ] mha = MultiHopAccessor( role_session_name="test_role_session_name", access_steps=access_steps ) mha.get_session("4567") mha.get_session("4567") mha.get_session("8901") mha.get_session("8901") expected_cache_sorted_keys = [ "1234:test_role_name1:test_role_session_name:None", "4567:test_role_name3:test_role_session_name:None", "5678:test_role_name2:test_role_session_name:None", "8901:test_role_name3:test_role_session_name:None", ] self.assertEqual(sorted(mha.session_cache._cache.keys()), expected_cache_sorted_keys) def test_str(self): access_steps = [ AccessStep(role_name="test_role_name1", account_id="1234", external_id="abcd"), AccessStep(role_name="test_role_name2", account_id="5678"), AccessStep(role_name="test_role_name3"), ] mha = MultiHopAccessor( role_session_name="test_role_session_name", access_steps=access_steps ) expected_str = "accessor:test_role_session_name:test_role_name1@1234,test_role_name2@5678,test_role_name3@target" self.assertEqual(str(mha), expected_str) def test_to_dict(self): access_steps = [ AccessStep(role_name="test_role_name1", account_id="1234", external_id="abcd"), AccessStep(role_name="test_role_name2", account_id="5678"), AccessStep(role_name="test_role_name3"), ] mha = MultiHopAccessor( role_session_name="test_role_session_name", access_steps=access_steps ) expected_dict = { "role_session_name": "test_role_session_name", "access_steps": [ {"role_name": "test_role_name1", "external_id": "abcd", "account_id": "1234"}, {"role_name": "test_role_name2", "external_id": None, "account_id": "5678"}, {"role_name": "test_role_name3", "external_id": None, "account_id": None}, ], } self.assertEqual(mha.to_dict(), expected_dict) def test_from_dict(self): mha_dict = { "role_session_name": "test_role_session_name", "access_steps": [ {"role_name": "test_role_name1", "external_id": "abcd", "account_id": "1234"}, {"role_name": "test_role_name2", "external_id": None, "account_id": "5678"}, {"role_name": "test_role_name3", "external_id": None, "account_id": None}, ], } mha = MultiHopAccessor.from_dict(mha_dict) self.assertEqual(mha_dict, mha.to_dict()) def test_from_dict_missing_access_steps(self): mha_dict = {"role_session_name": "test_role_session_name"} with self.assertRaises(ValueError): MultiHopAccessor.from_dict(mha_dict) def test_from_dict_missing_role_session_name(self): mha_dict = { "access_steps": [ {"role_name": "test_role_name1", "external_id": "abcd", "account_id": "1234"}, {"role_name": "test_role_name2", "external_id": None, "account_id": "5678"}, {"role_name": "test_role_name3", "external_id": None, "account_id": None}, ] } with self.assertRaises(ValueError): MultiHopAccessor.from_dict(mha_dict)

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0

null

0

1

0

null

0

6

9a6b5b6ee75f782ac9f503cb1d38a019589a0748

50

py

Python

hello.py

owainkenwayucl/DH-Hackathon

59ed4973ac648c1a50df5cfe2d986bfb0923f66d

[ "MIT" ]

null

hello.py

owainkenwayucl/DH-Hackathon

59ed4973ac648c1a50df5cfe2d986bfb0923f66d

[ "MIT" ]

1

2018-11-07T14:36:49.000Z

hello.py

owainkenwayucl/DH-Hackathon

59ed4973ac648c1a50df5cfe2d986bfb0923f66d

[ "MIT" ]

null

print("Hello, world") print("Hello, world again")

16.666667

27

0.7

7

50

5

0.571429

0.857143

0

0.1

50

2

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25

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0

0.6

0

1

0

true

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

d0a89af8880ef40302c3ba6f0d24ea600bed3bec

192

py

Python

malcolm/core/ntscalararray.py

MattTaylorDLS/pymalcolm

995a8e4729bd745f8f617969111cc5a34ce1ac14

[ "Apache-2.0" ]

null

malcolm/core/ntscalararray.py

MattTaylorDLS/pymalcolm

995a8e4729bd745f8f617969111cc5a34ce1ac14

[ "Apache-2.0" ]

null

malcolm/core/ntscalararray.py

MattTaylorDLS/pymalcolm

995a8e4729bd745f8f617969111cc5a34ce1ac14

[ "Apache-2.0" ]

null

from .attributemodel import AttributeModel from .serializable import Serializable @Serializable.register_subclass("epics:nt/NTScalarArray:1.0") class NTScalarArray(AttributeModel): pass

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null

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1

0

6

d0afad06191fc29424b90422f22143f974a2b5cc

426

py

Python

miwell-flask-app/tests/unit_tests/test_forms.py

joshuahigginson1/DevOps-Assessment-1

d617522ada565b8b587e2ff7525e1138d1559a75

[ "MIT" ]

1

2020-08-09T20:52:42.000Z

miwell-flask-app/tests/unit_tests/test_forms.py

joshuahigginson1/DevOps-Assessment-1

d617522ada565b8b587e2ff7525e1138d1559a75

[ "MIT" ]

null

miwell-flask-app/tests/unit_tests/test_forms.py

joshuahigginson1/DevOps-Assessment-1

d617522ada565b8b587e2ff7525e1138d1559a75

[ "MIT" ]

1

2020-08-08T11:47:27.000Z

# This script is for unit testing our forms. # Imports -------------------------------------------------------------------------------- # Login Form Tests ----------------------------------------------------------------------- # Patient Register Form Tests ------------------------------------------------------------ # Psychiatrist Register Form Tests -------------------------------------------------------

18.521739

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0.25

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91

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0.284211

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1

0

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null

0

1

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6

d0e10b97148b763ef388d204c9d5c842ab6d04ba

1,764

py

Python

epytope/Data/pssms/epidemix/mat/B_5101_8.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

7

2021-02-01T18:11:28.000Z

2022-01-31T19:14:07.000Z

epytope/Data/pssms/epidemix/mat/B_5101_8.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

22

2021-01-02T15:25:23.000Z

2022-03-14T11:32:53.000Z

epytope/Data/pssms/epidemix/mat/B_5101_8.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

4

2021-05-28T08:50:38.000Z

2022-03-14T11:45:32.000Z

B_5101_8 = {0: {'A': -2.8, 'C': -1.5, 'E': -2.1, 'D': 1.9, 'G': -3.0, 'F': -1.8, 'I': 0.8, 'H': -1.5, 'K': -2.5, 'M': -1.1, 'L': -0.3, 'N': -1.8, 'Q': -2.0, 'P': -2.5, 'S': -2.5, 'R': -2.6, 'T': 0.5, 'W': -1.0, 'V': 0.1, 'Y': 1.7}, 1: {'A': 1.5, 'C': -1.2, 'E': -2.5, 'D': -2.5, 'G': -2.5, 'F': -2.7, 'I': -2.8, 'H': -1.9, 'K': -2.5, 'M': -1.7, 'L': -3.3, 'N': -2.3, 'Q': -2.1, 'P': 2.4, 'S': -2.2, 'R': -2.7, 'T': -2.2, 'W': -1.9, 'V': -2.6, 'Y': -2.2}, 2: {'A': -2.9, 'C': -1.5, 'E': -3.0, 'D': -0.1, 'G': -3.5, 'F': 1.7, 'I': -1.8, 'H': -1.6, 'K': -3.0, 'M': 1.1, 'L': -0.2, 'N': -2.7, 'Q': -2.4, 'P': 1.1, 'S': -3.0, 'R': -3.0, 'T': -2.5, 'W': -0.7, 'V': 0.8, 'Y': 1.8}, 3: {'A': 0.2, 'C': -1.3, 'E': 0.1, 'D': -2.3, 'G': -2.8, 'F': 0.6, 'I': 0.2, 'H': 1.0, 'K': 1.0, 'M': -1.0, 'L': -0.2, 'N': -2.0, 'Q': -1.5, 'P': -2.4, 'S': 0.0, 'R': 1.0, 'T': 0.0, 'W': -1.1, 'V': 0.0, 'Y': -1.6}, 4: {'A': -2.5, 'C': -1.2, 'E': -2.7, 'D': -2.7, 'G': -3.2, 'F': -1.9, 'I': 1.5, 'H': 1.4, 'K': 0.0, 'M': -0.8, 'L': -0.4, 'N': -2.3, 'Q': -2.1, 'P': 1.4, 'S': 0.0, 'R': -2.4, 'T': -2.1, 'W': -1.3, 'V': 0.8, 'Y': -1.8}, 5: {'A': -2.8, 'C': -1.6, 'E': -2.8, 'D': -2.9, 'G': -3.4, 'F': -2.2, 'I': -2.0, 'H': 2.3, 'K': -2.7, 'M': -1.3, 'L': -0.3, 'N': -2.4, 'Q': -2.3, 'P': 1.7, 'S': 0.0, 'R': -2.8, 'T': -2.4, 'W': 1.3, 'V': 0.9, 'Y': 0.4}, 6: {'A': -2.4, 'C': -1.3, 'E': 0.1, 'D': -2.4, 'G': -2.9, 'F': -2.1, 'I': -1.7, 'H': 0.8, 'K': 0.7, 'M': -1.0, 'L': 0.0, 'N': -2.1, 'Q': 0.6, 'P': 0.4, 'S': 0.3, 'R': 0.8, 'T': -2.0, 'W': -1.2, 'V': 1.1, 'Y': -1.9}, 7: {'A': -2.4, 'C': -0.9, 'E': -2.9, 'D': -2.9, 'G': -3.4, 'F': 0.9, 'I': 2.0, 'H': -1.8, 'K': -2.7, 'M': -0.3, 'L': 0.8, 'N': -2.6, 'Q': -2.3, 'P': -2.6, 'S': -2.8, 'R': -2.6, 'T': -1.9, 'W': -0.7, 'V': 0.9, 'Y': -1.3}}

1,764

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1,764

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0.018219

0.024292

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0.032389

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0.232056

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1

null

0

1

0

1

0

null

0

6

d0ec44545456bbc2732a41f0aa731cbcc4944ae0

364

py

Python

lib/python/pulumi_crds/_utilities.py

eljoth/pulumi-kubernetes-operator

904f08d29510a824a77f17ea44bfd8fc3d21901b

[ "Apache-2.0" ]

null

lib/python/pulumi_crds/_utilities.py

eljoth/pulumi-kubernetes-operator

904f08d29510a824a77f17ea44bfd8fc3d21901b

[ "Apache-2.0" ]

2

2020-09-18T17:12:23.000Z

2020-12-30T19:40:56.000Z

lib/python/pulumi_crds/_utilities.py

eljoth/pulumi-kubernetes-operator

904f08d29510a824a77f17ea44bfd8fc3d21901b

[ "Apache-2.0" ]

null

from pulumi_kubernetes import _utilities def get_env(*args): return _utilities.get_env(*args) def get_env_bool(*args): return _utilities.get_env_bool(*args) def get_env_int(*args): return _utilities.get_env_int(*args) def get_env_float(*args): return _utilities.get_env_float(*args) def get_version(): return _utilities.get_version()

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364

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0.361446

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21

43

17.333333

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1

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0

null

0

1

0

null

0

1

0

1

0

6

ef7c8ff7940e9a89996998c242aff11415260522

32

py

Python

vae-pytorch/src/encoder/__init__.py

BeeGass/Readable-VAEs

50dcb03ad9b688c5249c52120cbbb5fed0a0a085

[ "MIT" ]

2

2022-01-02T16:41:14.000Z

2022-01-07T05:18:04.000Z

vae-pytorch/src/encoder/__init__.py

BeeGass/Readable-VAEs

50dcb03ad9b688c5249c52120cbbb5fed0a0a085

[ "MIT" ]

null

vae-pytorch/src/encoder/__init__.py

BeeGass/Readable-VAEs

50dcb03ad9b688c5249c52120cbbb5fed0a0a085

[ "MIT" ]

null

from .vae_encoder import Encoder

32

0.875

5

32

5.4

0.8

0

0.09375

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1

32

0.931034

0

1

0

true

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null

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0

null

0

1

0

1

0

1

0

6

efdfc707200667aabc8a6b59192cf5b8330dbba9

38

py

Python

vplotter/engines/__init__.py

AlexanderDKazakov/Plotter

38874946c0013c30b7749d60368f2e28b6d498fb

[ "MIT" ]

null

vplotter/engines/__init__.py

AlexanderDKazakov/Plotter

38874946c0013c30b7749d60368f2e28b6d498fb

[ "MIT" ]

1

2021-04-09T11:26:08.000Z

vplotter/engines/__init__.py

AlexanderDKazakov/Plotter

38874946c0013c30b7749d60368f2e28b6d498fb

[ "MIT" ]

null

from .veusz_engine import VeuszEngine

19

37

0.868421

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38

6.4

1

0

0.105263

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1

38

0.941176

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1

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true

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1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

6

324711e720b673587f3748c12567c140b115ca65

79

py

Python

2016/common/__init__.py

SimplyDanny/advent-of-code-2015

66ef2accccec479989fe47145a5fff3159c418bf

[ "BSD-2-Clause" ]

null

2016/common/__init__.py

SimplyDanny/advent-of-code-2015

66ef2accccec479989fe47145a5fff3159c418bf

[ "BSD-2-Clause" ]

2

2020-02-19T21:06:29.000Z

2020-03-15T15:14:58.000Z

2016/common/__init__.py

SimplyDanny/advent-of-code-2015

66ef2accccec479989fe47145a5fff3159c418bf

[ "BSD-2-Clause" ]

null

from .input import read, readline, readlines from .output import print_results

26.333333

44

0.822785

11

79

5.818182

0.818182

0

0.126582

79

2

45

39.5

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true

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null

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0

null

0

1

0

1

0

1

0

6

32b60cff6240a00af0d99d52cb1378bdb4f769b4

24

py

Python

__init__.py

jin0g/soundset

6167638323eac5c475102c72c836f51b8442f54e

[ "MIT" ]

null

__init__.py

jin0g/soundset

6167638323eac5c475102c72c836f51b8442f54e

[ "MIT" ]

null

__init__.py

jin0g/soundset

6167638323eac5c475102c72c836f51b8442f54e

[ "MIT" ]

null

from .soundset import *

12

23

0.75

3

24

6

1

0

0.166667

24

1

24

0.9

0

1

0

true

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1

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1

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1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

08752f079f4c0367d985988ab32a0569754ea95c

38

py

Python

Graphers/__init__.py

tuxtobin/ProfilerReport

9fd94241ff31511b51b9832448639078e6313fad

[ "MIT" ]

null

Graphers/__init__.py

tuxtobin/ProfilerReport

9fd94241ff31511b51b9832448639078e6313fad

[ "MIT" ]

null

Graphers/__init__.py

tuxtobin/ProfilerReport

9fd94241ff31511b51b9832448639078e6313fad

[ "MIT" ]

null

from .grapher import MatplotlibGraphs

19

37

0.868421

4

38

8.25

1

0

0.105263

38

1

38

0.970588

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

08b491aa2e3a967de122fa857eb794c91fdc744e

80

py

Python

module/__init__.py

hirusha-adi/GifGang

7b49767d9c0321844d7fc70a55a288d72c48acb5

[ "MIT" ]

null

module/__init__.py

hirusha-adi/GifGang

7b49767d9c0321844d7fc70a55a288d72c48acb5

[ "MIT" ]

null

module/__init__.py

hirusha-adi/GifGang

7b49767d9c0321844d7fc70a55a288d72c48acb5

[ "MIT" ]

null

""" The official Python API of GifGang """ from . import sfw from . import nsfw

13.333333

34

0.7

12

80

4.666667

0.833333

0.357143

0

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80

5

35

16

0.875

0.425

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

3e9419848d256db2b236a032adc6f372dbddee62

69

py

Python

curves/__init__.py

hamolicious/Curves

d4b4cb926f570865dbfc5974d033a85d9f1528fb

[ "WTFPL" ]

null

curves/__init__.py

hamolicious/Curves

d4b4cb926f570865dbfc5974d033a85d9f1528fb

[ "WTFPL" ]

null

curves/__init__.py

hamolicious/Curves

d4b4cb926f570865dbfc5974d033a85d9f1528fb

[ "WTFPL" ]

null

from curves.points import Point from curves.bezier import CubicBezier

34.5

37

0.869565

10

69

6

0.7

0.333333

0

0.101449

69

2

37

34.5

0.967742

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

3e9683b7b8401511aeb724d2c67d0127dd9b7e89

57

py

Python

python/testData/override/qualified.py

Sajaki/intellij-community

6748af2c40567839d11fd652ec77ba263c074aad

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/override/qualified.py

Sajaki/intellij-community

6748af2c40567839d11fd652ec77ba263c074aad

[ "Apache-2.0" ]

1

2020-07-30T19:04:47.000Z

python/testData/override/qualified.py

bradleesand/intellij-community

750ff9c10333c9c1278c00dbe8d88c877b1b9749

[ "Apache-2.0" ]

1

2020-10-15T05:56:42.000Z

import turtle class C(turtle.TurtleScreenBase): pass

14.25

33

0.77193

7

57

6.285714

0.857143

0

0.157895

57

4

34

14.25

0.916667

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

3eca6130ae5e411f621b26aa4647f2283b0a803a

68

py

Python

heimerdinger/__init__.py

jayfry1077/runeterra_audio_discord_bot

0327273e702003f094e39ed995a41d21840926c8

[ "MIT" ]

1

2020-04-19T06:00:15.000Z

heimerdinger/__init__.py

jayfry1077/runeterra_audio_discord_bot

0327273e702003f094e39ed995a41d21840926c8

[ "MIT" ]

null

heimerdinger/__init__.py

jayfry1077/runeterra_audio_discord_bot

0327273e702003f094e39ed995a41d21840926c8

[ "MIT" ]

null

from heimerdinger.invent import deck_code_to_audio, regions_to_audio

68

0.911765

11

68

5.181818

0.818182

0.245614

0

0.058824

68

1

68

0.890625

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

41215dfea66426994fa0af506e9af0757a912ede

189

py

Python

src/fastshelf/__init__.py

ligonliu/fastshelf

1d4250cbaaa062207090c0bd5e8237b271f96496

[ "MIT" ]

null

src/fastshelf/__init__.py

ligonliu/fastshelf

1d4250cbaaa062207090c0bd5e8237b271f96496

[ "MIT" ]

null

src/fastshelf/__init__.py

ligonliu/fastshelf

1d4250cbaaa062207090c0bd5e8237b271f96496

[ "MIT" ]

null

from .fastshelf import Shelf try: from PlyvelDB import PlyvelDB except ModuleNotFoundError as e: pass try: from RocksDB import RocksDB except ModuleNotFoundError as e: pass

18.9

33

0.761905

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189

6

0.5

0.097222

0.375

0.388889

0.444444

0

0.21164

189

10

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18.9

0.966443

0

0.666667

0

1

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true

0.222222

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

6

de24943e20de544e53a5c6d058defc9353cf07a3

136

py

Python

mythx_models/response/group_status.py

ConsenSys/mythx-models

e912c2fc6e7d18041310d3b9f0f95085db47ed9b

[ "MIT" ]

2

2019-08-26T13:42:28.000Z

2019-11-13T15:44:16.000Z

mythx_models/response/group_status.py

ConsenSys/mythx-models

e912c2fc6e7d18041310d3b9f0f95085db47ed9b

[ "MIT" ]

22

2019-08-26T13:14:55.000Z

2021-04-18T14:22:52.000Z

mythx_models/response/group_status.py

ConsenSys/mythx-models

e912c2fc6e7d18041310d3b9f0f95085db47ed9b

[ "MIT" ]

6

2019-08-29T15:51:38.000Z

2021-04-05T11:41:34.000Z

"""This module contains the GroupStatusResponse domain model.""" from .group import Group class GroupStatusResponse(Group): pass

17

64

0.764706

15

136

6.933333

0.8

0

0.154412

136

7

65

19.428571

0.904348

0.426471

0

1

0

true

0.333333

0

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0

1

0

null

0

1

0

null

0

1

0

1

0

6

de3654785fcc6df9a178b09af7cfa05ff0197461

29,991

py

Python

gewittergefahr/gg_utils/nwp_model_utils_test.py

dopplerchase/GewitterGefahr

4415b08dd64f37eba5b1b9e8cc5aa9af24f96593

[ "MIT" ]

26

2018-10-04T01:07:35.000Z

2022-01-29T08:49:32.000Z

gewittergefahr/gg_utils/nwp_model_utils_test.py

liuximarcus/GewitterGefahr

d819874d616f98a25187bfd3091073a2e6d5279e

[ "MIT" ]

4

2017-12-25T02:01:08.000Z

2018-12-19T01:54:21.000Z

gewittergefahr/gg_utils/nwp_model_utils_test.py

liuximarcus/GewitterGefahr

d819874d616f98a25187bfd3091073a2e6d5279e

[ "MIT" ]

11

2017-12-10T23:05:29.000Z

2022-01-29T08:49:33.000Z

"""Unit tests for nwp_model_utils.py.""" import os.path import unittest import numpy import pandas from gewittergefahr.gg_utils import nwp_model_utils from gewittergefahr.gg_utils import interp TOLERANCE = 1e-6 MAX_MEAN_DISTANCE_ERROR_RAP_METRES = 100. MAX_MAX_DISTANCE_ERROR_RAP_METRES = 500. MAX_MEAN_DISTANCE_ERROR_NARR_METRES = 250. MAX_MAX_DISTANCE_ERROR_NARR_METRES = 1000. GRID130_LATLNG_FILE_NAME = '{0:s}/grid_point_latlng_grid130.data'.format( os.path.dirname(__file__) ) GRID252_LATLNG_FILE_NAME = '{0:s}/grid_point_latlng_grid252.data'.format( os.path.dirname(__file__) ) NARR_LATLNG_FILE_NAME = '{0:s}/grid_point_latlng_grid221.data'.format( os.path.dirname(__file__) ) MAX_MEAN_SIN_OR_COS_ERROR = 1e-5 MAX_MAX_SIN_OR_COS_ERROR = 1e-4 GRID130_WIND_ROTATION_FILE_NAME = ( '{0:s}/wind_rotation_angles_grid130.data' ).format(os.path.dirname(__file__)) GRID252_WIND_ROTATION_FILE_NAME = ( '{0:s}/wind_rotation_angles_grid252.data' ).format(os.path.dirname(__file__)) # The following constants are used to test get_times_needed_for_interp. MODEL_TIME_STEP_HOURS = 3 QUERY_TIMES_UNIX_SEC = numpy.array( [14400, 18000, 21600, 25200, 28800, 32400, 36000], dtype=int ) MIN_QUERY_TIMES_UNIX_SEC = numpy.array([10800, 21600, 32400], dtype=int) MAX_QUERY_TIMES_UNIX_SEC = numpy.array([21600, 32400, 43200], dtype=int) MODEL_TIMES_PREV_INTERP_UNIX_SEC = numpy.array( [10800, 21600, 32400], dtype=int ) MODEL_TIMES_NEXT_INTERP_UNIX_SEC = numpy.array( [21600, 32400, 43200], dtype=int ) MODEL_TIMES_SUB_AND_LINEAR_INTERP_UNIX_SEC = numpy.array( [10800, 21600, 32400, 43200], dtype=int ) MODEL_TIMES_SUPERLINEAR_INTERP_UNIX_SEC = numpy.array( [0, 10800, 21600, 32400, 43200, 54000], dtype=int ) THIS_DICT = { nwp_model_utils.MIN_QUERY_TIME_COLUMN: MIN_QUERY_TIMES_UNIX_SEC, nwp_model_utils.MAX_QUERY_TIME_COLUMN: MAX_QUERY_TIMES_UNIX_SEC } INTERP_TIME_TABLE_PREV_INTERP = pandas.DataFrame.from_dict(THIS_DICT) INTERP_TIME_TABLE_NEXT_INTERP = pandas.DataFrame.from_dict(THIS_DICT) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP = pandas.DataFrame.from_dict(THIS_DICT) INTERP_TIME_TABLE_SUPERLINEAR_INTERP = pandas.DataFrame.from_dict(THIS_DICT) THIS_NESTED_ARRAY = INTERP_TIME_TABLE_PREV_INTERP[[ nwp_model_utils.MIN_QUERY_TIME_COLUMN, nwp_model_utils.MIN_QUERY_TIME_COLUMN ]].values.tolist() THIS_ARGUMENT_DICT = { nwp_model_utils.MODEL_TIMES_COLUMN: THIS_NESTED_ARRAY, nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN: THIS_NESTED_ARRAY } INTERP_TIME_TABLE_PREV_INTERP = INTERP_TIME_TABLE_PREV_INTERP.assign( **THIS_ARGUMENT_DICT) INTERP_TIME_TABLE_NEXT_INTERP = INTERP_TIME_TABLE_NEXT_INTERP.assign( **THIS_ARGUMENT_DICT) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP = ( INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP.assign(**THIS_ARGUMENT_DICT) ) INTERP_TIME_TABLE_SUPERLINEAR_INTERP = ( INTERP_TIME_TABLE_SUPERLINEAR_INTERP.assign(**THIS_ARGUMENT_DICT) ) INTERP_TIME_TABLE_PREV_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[0] = ( numpy.array([10800], dtype=int) ) INTERP_TIME_TABLE_PREV_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[1] = ( numpy.array([21600], dtype=int) ) INTERP_TIME_TABLE_PREV_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[2] = ( numpy.array([32400], dtype=int) ) INTERP_TIME_TABLE_PREV_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[0] = numpy.array([1, 0, 0], dtype=bool) INTERP_TIME_TABLE_PREV_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[1] = numpy.array([0, 1, 0], dtype=bool) INTERP_TIME_TABLE_PREV_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[2] = numpy.array([0, 0, 1], dtype=bool) INTERP_TIME_TABLE_NEXT_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[0] = ( numpy.array([21600], dtype=int) ) INTERP_TIME_TABLE_NEXT_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[1] = ( numpy.array([32400], dtype=int) ) INTERP_TIME_TABLE_NEXT_INTERP[nwp_model_utils.MODEL_TIMES_COLUMN].values[2] = ( numpy.array([43200], dtype=int) ) INTERP_TIME_TABLE_NEXT_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[0] = numpy.array([1, 0, 0], dtype=bool) INTERP_TIME_TABLE_NEXT_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[1] = numpy.array([0, 1, 0], dtype=bool) INTERP_TIME_TABLE_NEXT_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[2] = numpy.array([0, 0, 1], dtype=bool) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[0] = numpy.array([10800, 21600], dtype=int) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[1] = numpy.array([21600, 32400], dtype=int) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[2] = numpy.array([32400, 43200], dtype=int) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[0] = numpy.array([1, 1, 0, 0], dtype=bool) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[1] = numpy.array([0, 1, 1, 0], dtype=bool) INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[2] = numpy.array([0, 0, 1, 1], dtype=bool) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[0] = numpy.array([0, 10800, 21600, 32400], dtype=int) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[1] = numpy.array([10800, 21600, 32400, 43200], dtype=int) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_COLUMN ].values[2] = numpy.array([21600, 32400, 43200, 54000], dtype=int) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[0] = numpy.array([1, 1, 1, 1, 0, 0], dtype=bool) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[1] = numpy.array([0, 1, 1, 1, 1, 0], dtype=bool) INTERP_TIME_TABLE_SUPERLINEAR_INTERP[ nwp_model_utils.MODEL_TIMES_NEEDED_COLUMN ].values[2] = numpy.array([0, 0, 1, 1, 1, 1], dtype=bool) # The following constants are used to test rotate_winds_to_earth_relative and # rotate_winds_to_grid_relative. HALF_ROOT3 = numpy.sqrt(3) / 2 U_WINDS_GRID_RELATIVE_M_S01 = numpy.array([ [0, 5, 10], [0, -5, -10] ], dtype=float) V_WINDS_GRID_RELATIVE_M_S01 = numpy.array([ [10, 15, 20], [-10, -15, -20] ], dtype=float) ROTATION_ANGLE_COSINES = numpy.array([ [1, 0.5, -0.5], [-1, -0.5, 0.5] ]) ROTATION_ANGLE_SINES = numpy.array([ [0, HALF_ROOT3, HALF_ROOT3], [0, -HALF_ROOT3, -HALF_ROOT3] ]) U_WINDS_EARTH_RELATIVE_M_S01 = numpy.array([ [0, 2.5 + 15 * HALF_ROOT3, -5 + 20 * HALF_ROOT3], [0, 2.5 + 15 * HALF_ROOT3, -5 + 20 * HALF_ROOT3] ]) V_WINDS_EARTH_RELATIVE_M_S01 = numpy.array([ [10, 7.5 - 5 * HALF_ROOT3, -10 - 10 * HALF_ROOT3], [10, 7.5 - 5 * HALF_ROOT3, -10 - 10 * HALF_ROOT3] ]) def _compare_interp_time_tables(first_interp_time_table, second_interp_time_table): """Compares two tables with interpolation times. :param first_interp_time_table: pandas DataFrame created by `nwp_model_utils.get_times_needed_for_interp`. :param second_interp_time_table: Same. :return: are_tables_equal: Boolean flag. """ first_column_names = list(first_interp_time_table) second_column_names = list(second_interp_time_table) if set(first_column_names) != set(second_column_names): return False first_num_rows = len(first_interp_time_table.index) second_num_rows = len(second_interp_time_table.index) if first_num_rows != second_num_rows: return False for i in range(first_num_rows): for this_column in first_column_names: if not numpy.array_equal( first_interp_time_table[this_column].values[i], second_interp_time_table[this_column].values[i] ): return False return True class NwpModelUtilsTests(unittest.TestCase): """Each method is a unit test for nwp_model_utils.py.""" def test_check_grid_name_narr221(self): """Ensures correct output from check_grid_name. In this case, model is NARR and grid is NCEP 221. """ nwp_model_utils.check_grid_name( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) def test_check_grid_name_narr_extended221(self): """Ensures correct output from check_grid_name. In this case, model is NARR and grid is extended NCEP 221. """ nwp_model_utils.check_grid_name( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_EXTENDED_221GRID) def test_check_grid_name_narr130(self): """Ensures correct output from check_grid_name. In this case, model is NARR and grid is NCEP 130. """ with self.assertRaises(ValueError): nwp_model_utils.check_grid_name( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) def test_check_grid_name_rap221(self): """Ensures correct output from check_grid_name. In this case, model is RAP and grid is NCEP 221. """ with self.assertRaises(ValueError): nwp_model_utils.check_grid_name( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) def test_check_grid_name_rap_extended221(self): """Ensures correct output from check_grid_name. In this case, model is RAP and grid is extended NCEP 221. """ with self.assertRaises(ValueError): nwp_model_utils.check_grid_name( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_EXTENDED_221GRID) def test_check_grid_name_rap130(self): """Ensures correct output from check_grid_name. In this case, model is RAP and grid is NCEP 130. """ nwp_model_utils.check_grid_name( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) def test_dimensions_to_grid_221(self): """Ensures correct output from dimensions_to_grid for NCEP 221 grid.""" this_num_rows, this_num_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) this_grid_name = nwp_model_utils.dimensions_to_grid( num_rows=this_num_rows, num_columns=this_num_columns) self.assertTrue(this_grid_name == nwp_model_utils.NAME_OF_221GRID) def test_dimensions_to_grid_extended221(self): """Ensures correctness of dimensions_to_grid for extended 221 grid.""" this_num_rows, this_num_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_EXTENDED_221GRID) this_grid_name = nwp_model_utils.dimensions_to_grid( num_rows=this_num_rows, num_columns=this_num_columns) self.assertTrue( this_grid_name == nwp_model_utils.NAME_OF_EXTENDED_221GRID ) def test_dimensions_to_grid_130(self): """Ensures correct output from dimensions_to_grid for NCEP 130 grid.""" this_num_rows, this_num_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) this_grid_name = nwp_model_utils.dimensions_to_grid( num_rows=this_num_rows, num_columns=this_num_columns) self.assertTrue(this_grid_name == nwp_model_utils.NAME_OF_130GRID) def test_dimensions_to_grid_252(self): """Ensures correct output from dimensions_to_grid for NCEP 252 grid.""" this_num_rows, this_num_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) this_grid_name = nwp_model_utils.dimensions_to_grid( num_rows=this_num_rows, num_columns=this_num_columns) self.assertTrue(this_grid_name == nwp_model_utils.NAME_OF_252GRID) def test_dimensions_to_grid_fake(self): """Ensures correct output from dimensions_to_grid for fake grid.""" with self.assertRaises(ValueError): nwp_model_utils.dimensions_to_grid(num_rows=1, num_columns=2) def test_rotate_winds_to_earth_relative(self): """Ensures correct output from rotate_winds_to_earth_relative.""" these_u_winds_m_s01, these_v_winds_m_s01 = ( nwp_model_utils.rotate_winds_to_earth_relative( u_winds_grid_relative_m_s01=U_WINDS_GRID_RELATIVE_M_S01, v_winds_grid_relative_m_s01=V_WINDS_GRID_RELATIVE_M_S01, rotation_angle_cosines=ROTATION_ANGLE_COSINES, rotation_angle_sines=ROTATION_ANGLE_SINES) ) self.assertTrue(numpy.allclose( these_u_winds_m_s01, U_WINDS_EARTH_RELATIVE_M_S01, atol=TOLERANCE )) self.assertTrue(numpy.allclose( these_v_winds_m_s01, V_WINDS_EARTH_RELATIVE_M_S01, atol=TOLERANCE )) def test_rotate_winds_to_grid_relative(self): """Ensures correct output from rotate_winds_to_grid_relative.""" these_u_winds_m_s01, these_v_winds_m_s01 = ( nwp_model_utils.rotate_winds_to_grid_relative( u_winds_earth_relative_m_s01=U_WINDS_EARTH_RELATIVE_M_S01, v_winds_earth_relative_m_s01=V_WINDS_EARTH_RELATIVE_M_S01, rotation_angle_cosines=ROTATION_ANGLE_COSINES, rotation_angle_sines=ROTATION_ANGLE_SINES) ) self.assertTrue(numpy.allclose( these_u_winds_m_s01, U_WINDS_GRID_RELATIVE_M_S01, atol=TOLERANCE )) self.assertTrue(numpy.allclose( these_v_winds_m_s01, V_WINDS_GRID_RELATIVE_M_S01, atol=TOLERANCE )) def test_get_times_needed_for_interp_previous(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is previous-neighbour. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.PREV_NEIGHBOUR_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_PREV_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_PREV_INTERP )) def test_get_times_needed_for_interp_next(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is next-neighbour. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.NEXT_NEIGHBOUR_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_NEXT_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_NEXT_INTERP )) def test_get_times_needed_for_interp_nearest(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is nearest-neighbour. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.NEAREST_NEIGHBOUR_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_SUB_AND_LINEAR_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP )) def test_get_times_needed_for_interp_linear(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is linear. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.LINEAR_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_SUB_AND_LINEAR_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_SUB_AND_LINEAR_INTERP )) def test_get_times_needed_for_interp_quadratic(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is quadratic. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.SPLINE2_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_SUPERLINEAR_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_SUPERLINEAR_INTERP )) def test_get_times_needed_for_interp_cubic(self): """Ensures correct output from get_times_needed_for_interp. In this case, interpolation method is cubic. """ these_model_times_unix_sec, this_interp_time_table = ( nwp_model_utils.get_times_needed_for_interp( query_times_unix_sec=QUERY_TIMES_UNIX_SEC, model_time_step_hours=MODEL_TIME_STEP_HOURS, method_string=interp.SPLINE3_METHOD_STRING) ) self.assertTrue(numpy.array_equal( these_model_times_unix_sec, MODEL_TIMES_SUPERLINEAR_INTERP_UNIX_SEC )) self.assertTrue(_compare_interp_time_tables( this_interp_time_table, INTERP_TIME_TABLE_SUPERLINEAR_INTERP )) def test_projection_grid130(self): """Ensures approx correctness of Lambert proj for NCEP 130 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) unique_longitudes_deg, unique_latitudes_deg = numpy.loadtxt( GRID130_LATLNG_FILE_NAME, unpack=True) latitude_matrix_deg = numpy.reshape( unique_latitudes_deg, (num_grid_rows, num_grid_columns) ) longitude_matrix_deg = numpy.reshape( unique_longitudes_deg, (num_grid_rows, num_grid_columns) ) x_matrix_metres, y_matrix_metres = nwp_model_utils.project_latlng_to_xy( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) expected_x_matrix_metres, expected_y_matrix_metres = ( nwp_model_utils.get_xy_grid_point_matrices( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) ) x_error_matrix_metres = x_matrix_metres - expected_x_matrix_metres y_error_matrix_metres = y_matrix_metres - expected_y_matrix_metres distance_error_matrix_metres = numpy.sqrt( x_error_matrix_metres ** 2 + y_error_matrix_metres ** 2 ) self.assertTrue( numpy.mean(distance_error_matrix_metres) <= MAX_MEAN_DISTANCE_ERROR_RAP_METRES ) self.assertTrue( numpy.max(distance_error_matrix_metres) <= MAX_MAX_DISTANCE_ERROR_RAP_METRES ) def test_projection_grid252(self): """Ensures approx correctness of Lambert proj for NCEP 252 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) unique_longitudes_deg, unique_latitudes_deg = numpy.loadtxt( GRID252_LATLNG_FILE_NAME, unpack=True) latitude_matrix_deg = numpy.reshape( unique_latitudes_deg, (num_grid_rows, num_grid_columns) ) longitude_matrix_deg = numpy.reshape( unique_longitudes_deg, (num_grid_rows, num_grid_columns) ) x_matrix_metres, y_matrix_metres = nwp_model_utils.project_latlng_to_xy( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) expected_x_matrix_metres, expected_y_matrix_metres = ( nwp_model_utils.get_xy_grid_point_matrices( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) ) x_error_matrix_metres = x_matrix_metres - expected_x_matrix_metres y_error_matrix_metres = y_matrix_metres - expected_y_matrix_metres distance_error_matrix_metres = numpy.sqrt( x_error_matrix_metres ** 2 + y_error_matrix_metres ** 2 ) self.assertTrue( numpy.mean(distance_error_matrix_metres) <= MAX_MEAN_DISTANCE_ERROR_RAP_METRES ) self.assertTrue( numpy.max(distance_error_matrix_metres) <= MAX_MAX_DISTANCE_ERROR_RAP_METRES ) def test_projection_grid221(self): """Ensures approx correctness of Lambert proj for NCEP 221 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) unique_longitudes_deg, unique_latitudes_deg = numpy.loadtxt( NARR_LATLNG_FILE_NAME, unpack=True) latitude_matrix_deg = numpy.reshape( unique_latitudes_deg, (num_grid_rows, num_grid_columns) ) longitude_matrix_deg = numpy.reshape( unique_longitudes_deg, (num_grid_rows, num_grid_columns) ) x_matrix_metres, y_matrix_metres = nwp_model_utils.project_latlng_to_xy( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) expected_x_matrix_metres, expected_y_matrix_metres = ( nwp_model_utils.get_xy_grid_point_matrices( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) ) x_error_matrix_metres = x_matrix_metres - expected_x_matrix_metres y_error_matrix_metres = y_matrix_metres - expected_y_matrix_metres distance_error_matrix_metres = numpy.sqrt( x_error_matrix_metres ** 2 + y_error_matrix_metres ** 2 ) self.assertTrue( numpy.mean(distance_error_matrix_metres) <= MAX_MEAN_DISTANCE_ERROR_NARR_METRES ) self.assertTrue( numpy.max(distance_error_matrix_metres) <= MAX_MAX_DISTANCE_ERROR_NARR_METRES ) def test_projection_extended221(self): """Ensures approx correctness of Lambert proj for extended 221 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) unique_longitudes_deg, unique_latitudes_deg = numpy.loadtxt( NARR_LATLNG_FILE_NAME, unpack=True) latitude_matrix_deg = numpy.reshape( unique_latitudes_deg, (num_grid_rows, num_grid_columns) ) longitude_matrix_deg = numpy.reshape( unique_longitudes_deg, (num_grid_rows, num_grid_columns) ) x_matrix_metres, y_matrix_metres = nwp_model_utils.project_latlng_to_xy( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_221GRID) expected_x_matrix_metres, expected_y_matrix_metres = ( nwp_model_utils.get_xy_grid_point_matrices( model_name=nwp_model_utils.NARR_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_EXTENDED_221GRID) ) expected_x_matrix_metres = expected_x_matrix_metres[100:-100, 100:-100] expected_y_matrix_metres = expected_y_matrix_metres[100:-100, 100:-100] expected_x_matrix_metres -= expected_x_matrix_metres[0, 0] expected_y_matrix_metres -= expected_y_matrix_metres[0, 0] x_error_matrix_metres = x_matrix_metres - expected_x_matrix_metres y_error_matrix_metres = y_matrix_metres - expected_y_matrix_metres distance_error_matrix_metres = numpy.sqrt( x_error_matrix_metres ** 2 + y_error_matrix_metres ** 2 ) self.assertTrue( numpy.mean(distance_error_matrix_metres) <= MAX_MEAN_DISTANCE_ERROR_NARR_METRES ) self.assertTrue( numpy.max(distance_error_matrix_metres) <= MAX_MAX_DISTANCE_ERROR_NARR_METRES ) def test_wind_rotation_angles_grid130(self): """Ensures approx correctness of rotation angles for NCEP 130 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) expected_cos_vector, expected_sin_vector = numpy.loadtxt( GRID130_WIND_ROTATION_FILE_NAME, unpack=True) expected_cos_matrix = numpy.reshape( expected_cos_vector, (num_grid_rows, num_grid_columns) ) expected_sin_matrix = numpy.reshape( expected_sin_vector, (num_grid_rows, num_grid_columns) ) latitude_matrix_deg, longitude_matrix_deg = ( nwp_model_utils.get_latlng_grid_point_matrices( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_130GRID) ) rotation_angle_cos_matrix, rotation_angle_sin_matrix = ( nwp_model_utils.get_wind_rotation_angles( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.RAP_MODEL_NAME) ) cos_error_matrix = numpy.absolute( rotation_angle_cos_matrix - expected_cos_matrix ) sin_error_matrix = numpy.absolute( rotation_angle_sin_matrix - expected_sin_matrix ) self.assertTrue( numpy.mean(cos_error_matrix) <= MAX_MEAN_SIN_OR_COS_ERROR ) self.assertTrue(numpy.max(cos_error_matrix) <= MAX_MAX_SIN_OR_COS_ERROR) self.assertTrue( numpy.mean(sin_error_matrix) <= MAX_MEAN_SIN_OR_COS_ERROR ) self.assertTrue(numpy.max(sin_error_matrix) <= MAX_MAX_SIN_OR_COS_ERROR) def test_wind_rotation_angles_grid252(self): """Ensures approx correctness of rotation angles for NCEP 252 grid.""" num_grid_rows, num_grid_columns = nwp_model_utils.get_grid_dimensions( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) expected_cos_vector, expected_sin_vector = numpy.loadtxt( GRID252_WIND_ROTATION_FILE_NAME, unpack=True) expected_cos_matrix = numpy.reshape( expected_cos_vector, (num_grid_rows, num_grid_columns) ) expected_sin_matrix = numpy.reshape( expected_sin_vector, (num_grid_rows, num_grid_columns) ) latitude_matrix_deg, longitude_matrix_deg = ( nwp_model_utils.get_latlng_grid_point_matrices( model_name=nwp_model_utils.RAP_MODEL_NAME, grid_name=nwp_model_utils.NAME_OF_252GRID) ) rotation_angle_cos_matrix, rotation_angle_sin_matrix = ( nwp_model_utils.get_wind_rotation_angles( latitudes_deg=latitude_matrix_deg, longitudes_deg=longitude_matrix_deg, model_name=nwp_model_utils.RAP_MODEL_NAME) ) cos_error_matrix = numpy.absolute( rotation_angle_cos_matrix - expected_cos_matrix ) sin_error_matrix = numpy.absolute( rotation_angle_sin_matrix - expected_sin_matrix ) self.assertTrue( numpy.mean(cos_error_matrix) <= MAX_MEAN_SIN_OR_COS_ERROR ) self.assertTrue(numpy.max(cos_error_matrix) <= MAX_MAX_SIN_OR_COS_ERROR) self.assertTrue( numpy.mean(sin_error_matrix) <= MAX_MEAN_SIN_OR_COS_ERROR ) self.assertTrue(numpy.max(sin_error_matrix) <= MAX_MAX_SIN_OR_COS_ERROR) if __name__ == '__main__': unittest.main()

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6

de5fa67c9c5c4c6934271d80a8ec3b28d1b14862

62

py

Python

tests/test_hello.py

jfigura/playground

7f31b8dd962590ab8b700bf949ffc93a88c88f2c

[ "MIT" ]

null

tests/test_hello.py

jfigura/playground

7f31b8dd962590ab8b700bf949ffc93a88c88f2c

[ "MIT" ]

null

tests/test_hello.py

jfigura/playground

7f31b8dd962590ab8b700bf949ffc93a88c88f2c

[ "MIT" ]

null

from pytoo.hello import hello def test_hello(): hello()

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de83d420499af1bed39c727d28b0f250e2e56ce0

3,569

py

Python

tests/unit/command/test_prune_folder.py

mhadam/clutchless

be3791881749abe3d56c427e0bd61add54fcb615

[ "MIT" ]

1

2020-05-21T02:31:01.000Z

tests/unit/command/test_prune_folder.py

mhadam/clutchless

be3791881749abe3d56c427e0bd61add54fcb615

[ "MIT" ]

13

2020-06-14T15:03:11.000Z

2021-07-01T12:05:28.000Z

tests/unit/command/test_prune_folder.py

mhadam/clutchless

be3791881749abe3d56c427e0bd61add54fcb615

[ "MIT" ]

null

from pathlib import Path from pytest_mock import MockerFixture from clutchless.command.prune.folder import PruneFolderCommand from clutchless.domain.torrent import MetainfoFile from clutchless.service.torrent import PruneService from tests.mock_fs import MockFilesystem def test_prune_folder_run(mocker: MockerFixture): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "aaa", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) command.run() assert not fs.exists(Path("/some_path")) def test_prune_folder_dry_run(mocker: MockerFixture): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "aaa", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) command.dry_run() assert fs.exists(Path("/some_path")) def test_prune_folder_run_output(mocker: MockerFixture, capsys): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "aaa", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) output = command.run() output.display() result = capsys.readouterr().out assert ( result == "\n".join( ["The following metainfo files were removed:", "some_name at /some_path"] ) + "\n" ) def test_prune_folder_run_empty_output(mocker: MockerFixture, capsys): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "ccc", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) output = command.run() output.display() result = capsys.readouterr().out assert result == "No metainfo files were removed.\n" def test_prune_folder_dry_run_output(mocker: MockerFixture, capsys): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "aaa", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) output = command.dry_run() output.dry_run_display() result = capsys.readouterr().out assert ( result == "\n".join( [ "The following metainfo files would be removed:", "some_name at /some_path", ] ) + "\n" ) def test_prune_folder_dry_run_empty_output(mocker: MockerFixture, capsys): fs = MockFilesystem({"some_path"}) files = { MetainfoFile({"info_hash": "ccc", "name": "some_name"}, Path("/some_path")) } service: PruneService = mocker.Mock(spec=PruneService) service.get_torrent_hashes.return_value = {"aaa", "bbb"} command = PruneFolderCommand(service, fs, files) output = command.dry_run() output.dry_run_display() result = capsys.readouterr().out assert result == "No metainfo files would be removed.\n"

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null

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6

de8a979a5416ef7cbf92286af0376ef33fa8d3d4

181

py

Python

giscube_search/utils/apps.py

aroiginfraplan/giscube-admin

b7f3131b0186f847f3902df97f982cb288b16a49

[ "BSD-3-Clause" ]

5

2018-06-07T12:54:35.000Z

2022-01-14T10:38:38.000Z

giscube_search/utils/apps.py

aroiginfraplan/giscube-admin

b7f3131b0186f847f3902df97f982cb288b16a49

[ "BSD-3-Clause" ]

140

2018-06-18T10:27:28.000Z

2022-03-23T09:53:15.000Z

giscube_search/utils/apps.py

aroiginfraplan/giscube-admin

b7f3131b0186f847f3902df97f982cb288b16a49

[ "BSD-3-Clause" ]

1

2021-04-13T11:20:54.000Z

from django.apps import apps def giscube_search_get_app_modules(): """Return the Python module for each installed app""" return [i.module for i in apps.get_app_configs()]

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6

721bd2fda2a7619972bc9fe0ff0565cb6c4c75eb

207

py

Python

python/smqtk/representation/data_set/_plugins.py

joshanderson-kw/SMQTK

594e7c733fe7f4e514a1a08a7343293a883a41fc

[ "BSD-3-Clause" ]

82

2015-01-07T15:33:29.000Z

2021-08-11T18:34:05.000Z

python/smqtk/representation/data_set/_plugins.py

joshanderson-kw/SMQTK

594e7c733fe7f4e514a1a08a7343293a883a41fc

[ "BSD-3-Clause" ]

230

2015-04-08T14:36:51.000Z

2022-03-14T17:55:30.000Z

python/smqtk/representation/data_set/_plugins.py

joshanderson-kw/SMQTK

594e7c733fe7f4e514a1a08a7343293a883a41fc

[ "BSD-3-Clause" ]

65

2015-01-04T15:00:16.000Z

2021-11-19T18:09:11.000Z

from .file_set import DataFileSet # noqa: F401 from .kvstore_backed import KVSDataSet # noqa: F401 from .memory_set import DataMemorySet # noqa: F401 from .psql import PostgresNativeDataSet # noqa: F401

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6

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39,999

py

Python

tests/src/gretel_client/unit/transformers/conftest.py

franccesco/gretel-python-client

fd20dee07eba9657262edc902779142bf32c5b7c

[ "Apache-2.0" ]

null

tests/src/gretel_client/unit/transformers/conftest.py

franccesco/gretel-python-client

fd20dee07eba9657262edc902779142bf32c5b7c

[ "Apache-2.0" ]

null

tests/src/gretel_client/unit/transformers/conftest.py

franccesco/gretel-python-client

fd20dee07eba9657262edc902779142bf32c5b7c

[ "Apache-2.0" ]

null

import pytest @pytest.fixture(scope='session') def records_conditional(): return [ {'record': { 'first_name': 'Alex', 'last_name': 'Watson', 'user_id': '0003', 'dni': 'He loves 8.8.8.8 for DNS', 'city': 'San Diego', 'state': 'California', 'lat': 112.22134, 'lon': 135.76433, 'user_consent': '1' }, 'metadata': { 'gretel_id': '2732c7ed44a8402f899a01e52a931985', 'fields': { 'lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '12.22134'}]}}, 'lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '135.76433'}]}}}} }, {'record': { 'first_name': 'Alex', 'last_name': 'Ehrath', 'user_id': '0013', 'dni': 'He loves 192.168.8.254 for DNS', 'city': 'San Marcos', 'state': 'California', 'lat': 35.659491, 'lon': 139.72785, 'user_consent': '0' }, 'metadata': { 'gretel_id': '2732c7ed44a8402f899a01e52a931985', 'fields': { 'lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}} } ] @pytest.fixture(scope='session') def record_dirty_fpe_check(): return {'Address': '317 Massa. Av.', 'City': 'Didim', 'Country': 'Eritrea', 'Credit Card': '601128 2195205 818', 'Customer ID': '169/61*009 38-34', 'Date': '2019-10-08', 'Name': 'Grimes, Bo H.', 'Zipcode': '745558' } @pytest.fixture(scope='session') def record_meta_data_check(): return {'record': {'Address': '317 Massa. Av.', 'City': 'Didim', 'Country': 'Eritrea', 'Credit Card': '6011282195205818', 'Customer ID': '16961009 3834', 'Date': '2019-10-08', 'Name': 'Grimes, Bo H.', 'Zipcode': '745558'}, 'metadata': { 'gretel_id': '2732c7ed44a8402f899a01e52a931985', 'fields': { 'Country': { 'ner': { 'labels': [{ 'start': 0, 'end': 7, 'label': 'location', 'score': None, 'source': 'spacy', 'text': 'Eritrea' }] } }, 'Name': {'ner': { 'labels': [ {'start': 0, 'end': 6, 'label': 'person_name', 'score': None, 'source': 'spacy', 'text': 'Grimes'}]}}, 'Credit Card': {'ner': { 'labels': [ {'start': 0, 'end': 16, 'label': 'credit_card_number', 'score': 1, 'source': 'regex.credit_card', 'text': '6011282195205818'}]}}, 'Date': {'ner': { 'labels': [ {'start': 0, 'end': 10, 'label': 'date', 'score': 1.0, 'source': 'datetime', 'text': '2019-10-08'}]}}}}} @pytest.fixture(scope='session') def records_date_tweak(): return [ { 'first_name': 'Alex', 'last_name': 'Watson', 'user_id': '0003', 'dni': 'He loves 8.8.8.8 for DNS', 'city': 'San Diego', 'state': 'California', 'created': '2016-06-17T18:58:41Z' }, { 'first_name': 'Alex', 'last_name': 'Ehrath', 'user_id': '0013', 'dni': 'He loves 192.168.8.254 for DNS', 'city': 'San Marcos', 'state': 'California', 'created': '2016-06-17' } ] @pytest.fixture(scope='session') def record_and_meta_2(): record = { 'summary': 'Alex Watson <alex@gretel.ai> works at Gretel. Alexander Ehrath used to work at Qualcomm.', 'dni': 'He loves 8.8.8.8 for DNS', 'city': 'San Diego', 'state': 'California', 'stuff': 'nothing labeled here', 'latitude': 112.221 } meta = { 'gretel_id': '2732c7ed44a8402f899a01e52a931985', 'fields': { 'summary': { 'ner': { 'labels': [ { 'start': 0, 'end': 11, 'score': 0.8, 'text': 'Alex Watson', 'label': 'person_name', }, { 'start': 46, 'end': 62, 'score': 0.8, 'text': 'Alexander Ehrath', 'label': 'person_name', }, { 'start': 13, 'end': 27, 'score': 0.9, 'text': 'alex@gretel.ai', 'label': 'email_address', }, { 'start': 38, 'end': 44, 'score': 0.7, 'text': 'Gretel', 'label': 'company_name', }, { 'start': 79, 'end': 87, 'score': 0.8, 'text': 'Qualcomm', 'label': 'company_name', } ] } }, 'dni': { 'ner': { 'labels': [ { 'start': 9, 'end': 16, 'score': 1.0, 'text': '8.8.8.8', 'label': 'ip_address' } ] } }, 'city': { 'ner': { 'labels': [ { 'start': 0, 'end': 9, 'score': 1.0, 'text': 'San Diego', 'label': 'location_city' } ] } }, 'state': { 'ner': { 'labels': [ { 'start': 0, 'end': 10, 'score': 1.0, 'text': 'California', 'label': 'location_state' } ] } }, 'latitude': { 'ner': { 'labels': [ { 'start': 0, 'end': 7, 'score': 1, 'text': '112.221', 'label': 'latitude' } ] } } } } return {'record': record, 'metadata': meta} @pytest.fixture(scope='session') def safecast_test_bucket(): records = { 'records': [{'id': 'rrvewdk3dwb3', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:55Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.env_temp': 21.1, 'payload.bat_voltage': 7.64, 'payload.dev_comms_failures': 534, 'payload.dev_restarts': 648, 'payload.dev_free_memory': 53636, 'payload.dev_ntp_count': 1, 'payload.dev_last_failure': 'FAILsdcard', 'payload.service_uploaded': '2020-03-10T23:58:55Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': 'abf7a122a5a0c20588d239199c8c6d7f', 'payload.service_handler': 'i-051cab8ec0fe30bcd', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}}, {'id': '6gwrzlk665hv', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:54Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.lnd_7128ec': 25, 'payload.service_uploaded': '2020-03-10T23:58:54Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': 'cb93606463ba99994f832177e39dc6a5', 'payload.service_handler': 'i-051a2a353509414f0', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [{'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}}, {'id': 'p6vn0zp1yja1', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:54Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.lnd_7318u': 12, 'payload.service_uploaded': '2020-03-10T23:58:54Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': '72f2b7cf2132bcc50ea68a2b6bdb6e2d', 'payload.service_handler': 'i-0c65ac97805549e0d', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}} ] } return {'data': records} @pytest.fixture(scope='session') def safecast_test_bucket2(): records = { 'records': [{'id': 'rrvewdk3dwb3', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:55Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.env_temp': 21.1, 'payload.bat_voltage': 7.64, 'payload.dev_comms_failures': 534, 'payload.dev_restarts': 648, 'payload.dev_free_memory': 53636, 'payload.dev_ntp_count': 1, 'payload.dev_last_failure': 'FAILsdcard', 'payload.service_uploaded': '2020-03-10T23:58:55Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': 'abf7a122a5a0c20588d239199c8c6d7f', 'payload.service_handler': 'i-051cab8ec0fe30bcd', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}}, {'id': '6gwrzlk665hv', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:54Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.lnd_7128ec': 25, 'payload.service_uploaded': '2020-03-10T23:58:54Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': 'cb93606463ba99994f832177e39dc6a5', 'payload.service_handler': 'i-051a2a353509414f0', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [{'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}}, {'id': 'p6vn0zp1yja1', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10002', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10002', 'payload.device': 10002, 'payload.when_captured': '2020-03-10T23:58:54Z', 'payload.loc_lat': 35.659491, 'payload.loc_lon': 139.72785, 'payload.loc_alt': 92, 'payload.loc_olc': '8Q7XMP5H+Q4X', 'payload.lnd_7318u': 12, 'payload.service_uploaded': '2020-03-10T23:58:54Z', 'payload.service_transport': 'pointcast:122.212.234.10', 'payload.service_md5': '72f2b7cf2132bcc50ea68a2b6bdb6e2d', 'payload.service_handler': 'i-0c65ac97805549e0d', 'payload.ip_address': '122.212.234.10', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Shibuya', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Tokyo', 'payload.location': '35.659491,139.72785', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 14, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '122.212.234.10'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '35.659491'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '139.72785'}]}}}}}, {'id': 'lnj9o0xo6euz', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'geigiecast:62007', 'payload.device_class': 'geigiecast', 'payload.device_sn': 'bGeigiecast #62007', 'payload.device': 62007, 'payload.when_captured': '2020-03-10T23:58:50Z', 'payload.loc_lat': 34.48273, 'payload.loc_lon': 136.16316, 'payload.loc_olc': '8Q6RF5M7+37V', 'payload.lnd_7318u': 44, 'payload.dev_test': True, 'payload.service_uploaded': '2020-03-10T23:58:51Z', 'payload.service_transport': 'geigiecast:61.205.85.144', 'payload.service_md5': 'b5b622d94f501074111ff6051a833e79', 'payload.service_handler': 'i-051cab8ec0fe30bcd', 'payload.ip_address': '61.205.85.144', 'payload.ip_country_code': 'JP', 'payload.ip_city': 'Kashihara-shi', 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': 'Nara', 'payload.location': '34.48273,136.16316', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [ {'start': 11, 'end': 24, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '61.205.85.144'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 13, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '61.205.85.144'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 8, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '34.48273'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '136.16316'}]}}}}}, {'id': 'o6vnl2lrypt1', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10042', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10042', 'payload.device': 10042, 'payload.when_captured': '2020-03-10T23:58:45Z', 'payload.loc_lat': 37.7233303, 'payload.loc_lon': 140.4767968, 'payload.loc_alt': 145, 'payload.loc_olc': '8R92PFFG+8PM', 'payload.env_temp': 23.8, 'payload.bat_voltage': 5.03, 'payload.dev_comms_failures': 5990, 'payload.dev_restarts': 1542, 'payload.dev_free_memory': 50588, 'payload.dev_last_failure': 'no EPOCH', 'payload.service_uploaded': '2020-03-10T23:58:44Z', 'payload.service_transport': 'pointcast:103.67.223.44', 'payload.service_md5': '044cb5d5e2cd9a873d35c7bce29ddd8d', 'payload.service_handler': 'i-051a2a353509414f0', 'payload.ip_address': '103.67.223.44', 'payload.ip_country_code': 'JP', 'payload.ip_city': None, 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': None, 'payload.location': '37.7233303,140.4767968', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 23, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 13, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '37.7233303'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '140.4767968'}]}}}}}, {'id': '6gwrzlzpkjhv', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10042', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10042', 'payload.device': 10042, 'payload.when_captured': '2020-03-10T23:58:39Z', 'payload.loc_lat': 37.7233303, 'payload.loc_lon': 140.4767968, 'payload.loc_alt': 145, 'payload.loc_olc': '8R92PFFG+8PM', 'payload.lnd_7128ec': 15, 'payload.service_uploaded': '2020-03-10T23:58:39Z', 'payload.service_transport': 'pointcast:103.67.223.44', 'payload.service_md5': 'e7aa396b744d524f184830155a77ca97', 'payload.service_handler': 'i-051cab8ec0fe30bcd', 'payload.ip_address': '103.67.223.44', 'payload.ip_country_code': 'JP', 'payload.ip_city': None, 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': None, 'payload.location': '37.7233303,140.4767968', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [ {'start': 10, 'end': 23, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 13, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '37.7233303'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '140.4767968'}]}}}}}, {'id': 'kjzno9o6j9hz', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:20105', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #20105', 'payload.device': 20105, 'payload.when_captured': '2020-03-10T23:58:43Z', 'payload.loc_lat': 38.3151, 'payload.loc_lon': -123.0752, 'payload.loc_olc': '84CR8W8F+2WV', 'payload.lnd_78017w': 95, 'payload.service_uploaded': '2020-03-10T23:58:43Z', 'payload.service_transport': 'pointcast:12.235.42.3', 'payload.service_md5': 'afa4110616de9bb1b9cd3930eef9b50e', 'payload.service_handler': 'i-0c65ac97805549e0d', 'payload.ip_address': '12.235.42.3', 'payload.ip_country_code': 'US', 'payload.ip_city': 'Bodega Bay', 'payload.ip_country_name': 'United States', 'payload.ip_subdivision': 'California', 'payload.location': '38.3151,-123.0752', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 21, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '12.235.42.3'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '12.235.42.3'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 7, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '38.3151'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '-123.0752'}]}}}}}, {'id': 'y6yp272rglb7', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10024', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10024', 'payload.device': 10024, 'payload.when_captured': '2020-03-10T23:58:33Z', 'payload.loc_lat': 37.54562, 'payload.loc_lon': 140.398995, 'payload.loc_alt': 238, 'payload.loc_olc': '8R92G9WX+6HX', 'payload.env_temp': 25.6, 'payload.bat_voltage': 8.36, 'payload.dev_comms_failures': 1155, 'payload.dev_restarts': 501, 'payload.dev_free_memory': 53348, 'payload.dev_ntp_count': 1, 'payload.dev_last_failure': '', 'payload.service_uploaded': '2020-03-10T23:58:33Z', 'payload.service_transport': 'pointcast:121.95.25.8', 'payload.service_md5': '07c33e23ea4c2d96457a5400b299abc5', 'payload.service_handler': 'i-0c65ac97805549e0d', 'payload.ip_address': '121.95.25.8', 'payload.ip_country_code': 'JP', 'payload.ip_city': None, 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': None, 'payload.location': '37.54562,140.398995', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [ {'start': 10, 'end': 21, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '121.95.25.8'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '121.95.25.8'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 8, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '37.54562'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '140.398995'}]}}}}}, {'id': '5gxrz17lvrt2', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'ngeigie:74', 'payload.device_class': 'ngeigie', 'payload.device_sn': 'nGeigie #74', 'payload.device': 74, 'payload.when_captured': '2020-03-10T23:58:34Z', 'payload.loc_lat': 34.995197, 'payload.loc_lon': 135.764331, 'payload.loc_olc': '8Q6QXQW7+3PG', 'payload.lnd_7318u': 41, 'payload.service_uploaded': '2020-03-10T23:58:34Z', 'payload.service_transport': 'ngeigie:107.161.164.166', 'payload.service_md5': 'be9f5f5dcc6e8f308e5f44ccf2496eda', 'payload.service_handler': 'i-051a2a353509414f0', 'payload.ip_address': '107.161.164.166', 'payload.ip_country_code': 'US', 'payload.ip_city': 'New York', 'payload.ip_country_name': 'United States', 'payload.ip_subdivision': 'New York', 'payload.location': '34.995197,135.764331', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': {'labels': [ {'start': 8, 'end': 23, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '107.161.164.166'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 15, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '107.161.164.166'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 9, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '34.995197'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '135.764331'}]}}}}}, {'id': 'p6vn0z4ky9h1', 'ingest_time': 'foo', 'data': { 'payload.device_urn': 'pointcast:10042', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10042', 'payload.device': 10042, 'payload.when_captured': '2020-03-10T23:58:33Z', 'payload.loc_lat': 37.7233303, 'payload.loc_lon': 140.4767968, 'payload.loc_alt': 145, 'payload.loc_olc': '8R92PFFG+8PM', 'payload.lnd_7318u': 43, 'payload.service_uploaded': '2020-03-10T23:58:32Z', 'payload.service_transport': 'pointcast:103.67.223.44', 'payload.service_md5': '325d237c0f2fe8624e11d7baa00828a2', 'payload.service_handler': 'i-051a2a353509414f0', 'payload.ip_address': '103.67.223.44', 'payload.ip_country_code': 'JP', 'payload.ip_city': None, 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': None, 'payload.location': '37.7233303,140.4767968', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': { 'payload.service_transport': {'ner': {'labels': [ {'start': 10, 'end': 23, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 13, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '103.67.223.44'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '37.7233303'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '140.4767968'}]}}}}}, {'id': 'g7v9gjl1xoh5', 'ingest_time': 'foo', 'data': {'payload.device_urn': 'pointcast:10024', 'payload.device_class': 'pointcast', 'payload.device_sn': 'Pointcast #10024', 'payload.device': 10024, 'payload.when_captured': '2020-03-10T23:58:32Z', 'payload.loc_lat': 37.54562, 'payload.loc_lon': 140.398995, 'payload.loc_alt': 238, 'payload.loc_olc': '8R92G9WX+6HX', 'payload.lnd_7318u': 45, 'payload.service_uploaded': '2020-03-10T23:58:32Z', 'payload.service_transport': 'pointcast:121.95.25.8', 'payload.service_md5': '0c8d1523969e1834cfa56b3472a30e31', 'payload.service_handler': 'i-051cab8ec0fe30bcd', 'payload.ip_address': '121.95.25.8', 'payload.ip_country_code': 'JP', 'payload.ip_city': None, 'payload.ip_country_name': 'Japan', 'payload.ip_subdivision': None, 'payload.location': '37.54562,140.398995', 'origin': 'arn:aws:sns:us-west-2:985752656544:ingest-measurements-prd'}, 'metadata': {'fields': {'payload.service_transport': {'ner': { 'labels': [ {'start': 10, 'end': 21, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '121.95.25.8'}]}}, 'payload.ip_address': {'ner': {'labels': [ {'start': 0, 'end': 11, 'label': 'ip_address', 'score': 1, 'source': 'regex', 'text': '121.95.25.8'}]}}, 'payload.loc_lat': {'ner': {'labels': [ {'start': 0, 'end': 8, 'label': 'latitude', 'score': 1, 'source': 'regex', 'text': '37.54562'}]}}, 'payload.loc_lon': {'ner': {'labels': [ {'start': 0, 'end': 10, 'label': 'longitude', 'score': 1, 'source': 'regex', 'text': '140.398995'}]}}}}} ] } return {'data': records}

55.019257

120

0.430861

3,505

39,999

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0.04507

0.057589

0.061822

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0.787946

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55.095041

0.553129

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0.005642

0.021157

0

null

0

1

0

null

0

6

a0f950e5e3607982753914db99c67d586eb130ca

48

py

Python

africanus/model/coherency/__init__.py

JoshVStaden/codex-africanus

4a38994431d51510b1749fa0e4b8b6190b8b530f

[ "BSD-3-Clause" ]

13

2018-04-06T09:36:13.000Z

2021-04-13T13:11:00.000Z

africanus/model/coherency/__init__.py

JoshVStaden/codex-africanus

4a38994431d51510b1749fa0e4b8b6190b8b530f

[ "BSD-3-Clause" ]

153

2018-03-28T14:13:48.000Z

2022-02-03T07:49:17.000Z

africanus/model/coherency/__init__.py

JoshVStaden/codex-africanus

4a38994431d51510b1749fa0e4b8b6190b8b530f

[ "BSD-3-Clause" ]

14

2018-03-29T13:30:52.000Z

2021-06-12T02:56:55.000Z

# flake8: noqa from .conversion import convert

12

31

0.770833

6

48

6.166667

1

0

0.025

0.166667

48

3

32

16

0.9

0.25

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true

0

1

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null

0

1

0

1

0

1

0

6

9d00ffeb24f296ab9a5978bd8878a0c43e2130c8

127

py

Python

daily/views.py

juthor/LikeLion_Hackaton_AltongE

97a0380d8fd5a6909d006d6ceae349b14a05b13f

[ "MIT" ]

1

2019-12-11T15:26:11.000Z

daily/views.py

juthor/LikeLion_Hackaton_AltongE

97a0380d8fd5a6909d006d6ceae349b14a05b13f

[ "MIT" ]

null

daily/views.py

juthor/LikeLion_Hackaton_AltongE

97a0380d8fd5a6909d006d6ceae349b14a05b13f

[ "MIT" ]

null

from django.shortcuts import render # Create your views here. def daily(request): return render(request, 'daily.html')

25.4

40

0.732283

17

127

5.470588

0.823529

0

0.173228

127

5

40

25.4

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0.181102

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0.10101

0

1

0.333333

false

0

0.333333

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null

0

1

0

null

0

1

0

1

0

6

9d3d8443aa121dec218463216a78f641047a50e8

478

py

Python

tests/unit/test_main.py

andrewnsk/cover_pass

6110a6d39c286958b1a2ab00e6e1bcfc4ef3de1b

[ "MIT" ]

null

tests/unit/test_main.py

andrewnsk/cover_pass

6110a6d39c286958b1a2ab00e6e1bcfc4ef3de1b

[ "MIT" ]

null

tests/unit/test_main.py

andrewnsk/cover_pass

6110a6d39c286958b1a2ab00e6e1bcfc4ef3de1b

[ "MIT" ]

null

import unittest from coverpass.main import * class Test(unittest.TestCase): def test_print_me(self): self.assertEqual(print_me(5), 15) self.assertEqual(print_me(8), 18) self.assertEqual(print_me(20), 30) self.assertEqual(print_me(0), 10) def test_return_val(self): self.assertEqual(return_val(1), 2) def test_return_val2(self): self.assertEqual(return_val2(1), 2) if __name__ == "__main__": unittest.main()

21.727273

43

0.66318

66

478

4.5

0.424242

0.30303

0.26936

0.296296

0

0.050532

0.213389

478

21

44

22.761905

0.739362

0

0.016771

0

0.428571

1

0.214286

false

0.071429

0.142857

0

0.428571

0.357143

0

null

1

0

null

0

1

0

1

0

1

0

6

c205818113c6eeb43224563c8b96aa4ff4c255cb

10,185

py

Python

tests/test_compose.py

amarshall/boiga

faef732a59b7308b0f3be0d1d1ea047a405d641d

[ "MIT" ]

2

2018-10-30T13:17:23.000Z

2018-11-19T06:39:49.000Z

tests/test_compose.py

amarshall/boiga

faef732a59b7308b0f3be0d1d1ea047a405d641d

[ "MIT" ]

2

2020-03-24T16:15:45.000Z

2020-03-31T00:02:27.000Z

tests/test_compose.py

amarshall/boiga

faef732a59b7308b0f3be0d1d1ea047a405d641d

[ "MIT" ]

null

from boiga.compose import ( compose2, compose3, compose4, compose5, compose6, compose7 ) from tests.typecheck_helper import TypecheckResult, typecheck # Ideally, these are @dataclass, but not in Python 3.6 class _Flow0: a: int def __init__(self, a: int) -> None: self.a = a # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow0) and (self.a == other.a) class _Flow1: # noqa: E302 b: int def __init__(self, b: int) -> None: self.b = b # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow1) and (self.b == other.b) class _Flow2: # noqa: E302 c: int def __init__(self, c: int) -> None: self.c = c # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow2) and (self.c == other.c) class _Flow3: # noqa: E302 d: int def __init__(self, d: int) -> None: self.d = d # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow3) and (self.d == other.d) class _Flow4: # noqa: E302 e: int def __init__(self, e: int) -> None: self.e = e # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow4) and (self.e == other.e) class _Flow5: # noqa: E302 f: int def __init__(self, f: int) -> None: self.f = f # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow5) and (self.f == other.f) class _Flow6: # noqa: E302 g: int def __init__(self, g: int) -> None: self.g = g # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow6) and (self.g == other.g) class _Flow7: # noqa: E302 h: int def __init__(self, h: int) -> None: self.h = h # noqa: E301 def __eq__(self, other: object) -> bool: # noqa: E301 return isinstance(other, _Flow7) and (self.h == other.h) def _flow0(x: _Flow0) -> _Flow1: return _Flow1(x.a) def _flow1(x: _Flow1) -> _Flow2: return _Flow2(x.b) # noqa: E302 def _flow2(x: _Flow2) -> _Flow3: return _Flow3(x.c) # noqa: E302 def _flow3(x: _Flow3) -> _Flow4: return _Flow4(x.d) # noqa: E302 def _flow4(x: _Flow4) -> _Flow5: return _Flow5(x.e) # noqa: E302 def _flow5(x: _Flow5) -> _Flow6: return _Flow6(x.f) # noqa: E302 def _flow6(x: _Flow6) -> _Flow7: return _Flow7(x.g) # noqa: E302 imports = [ 'from boiga.compose import compose2, compose3, compose4, compose5, compose6, compose7', 'from tests.test_compose import _flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow6', 'from tests.test_compose import _Flow0, _Flow1, _Flow2, _Flow3, _Flow4, _Flow5, _Flow6, _Flow7', ] def typecheck_flow(code: str) -> TypecheckResult: return typecheck([*imports, code]) class TestCompose2: def test_valid_flow_with_call(self) -> None: assert compose2(_flow0, _flow1)(_Flow0(42)) == _Flow2(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose2(_flow0, _flow1)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose2(_flow0, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 2 of "compose2"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow('compose2(_flow0, _flow1)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow('compose2(_flow0, _flow1)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow2" has no attribute "foo"' ] class TestCompose3: def test_valid_flow_with_call(self) -> None: flow = compose3(_flow0, _flow1, _flow2) assert flow(_Flow0(42)) == _Flow3(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose3(_flow0, _flow1, _flow2)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose3(_flow0, _flow1, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 3 of "compose3"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow('compose3(_flow0, _flow1, _flow2)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow('compose3(_flow0, _flow1, _flow2)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow3" has no attribute "foo"' ] class TestCompose4: def test_valid_flow_with_call(self) -> None: flow = compose4(_flow0, _flow1, _flow2, _flow3) assert flow(_Flow0(42)) == _Flow4(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose4(_flow0, _flow1, _flow2, _flow3)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose4(_flow0, _flow1, _flow2, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 4 of "compose4"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow('compose4(_flow0, _flow1, _flow2, _flow3)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow('compose4(_flow0, _flow1, _flow2, _flow3)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow4" has no attribute "foo"' ] class TestCompose5: def test_valid_flow_with_call(self) -> None: flow = compose5(_flow0, _flow1, _flow2, _flow3, _flow4) assert flow(_Flow0(42)) == _Flow5(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose5(_flow0, _flow1, _flow2, _flow3, _flow4)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose5(_flow0, _flow1, _flow2, _flow3, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 5 of "compose5"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow( 'compose5(_flow0, _flow1, _flow2, _flow3, _flow4)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow( 'compose5(_flow0, _flow1, _flow2, _flow3, _flow4)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow5" has no attribute "foo"' ] class TestCompose6: def test_valid_flow_with_call(self) -> None: flow = compose6(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5) assert flow(_Flow0(42)) == _Flow6(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose6(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose6(_flow0, _flow1, _flow2, _flow3, _flow4, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 6 of "compose6"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow( 'compose6(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow( 'compose6(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow6" has no attribute "foo"' ] class TestCompose7: def test_valid_flow_with_call(self) -> None: flow = compose7(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow6) assert flow(_Flow0(42)) == _Flow7(42) def test_valid_flow_typechecks(self) -> None: result = typecheck_flow('compose7(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow6)') assert result.ok def test_invalid_flow_fns(self) -> None: result = typecheck_flow('compose7(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow0)') assert not result.ok assert result.errors == [ '<string>:4: error: Cannot infer type argument 7 of "compose7"' ] def test_invalid_flow_call(self) -> None: result = typecheck_flow( 'compose7(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow6)(_Flow2(42))') assert not result.ok assert result.errors == [ '<string>:4: error: Argument 1 has incompatible type "_Flow2"; expected "_Flow0"' ] def test_invalid_flow_result(self) -> None: result = typecheck_flow( 'compose7(_flow0, _flow1, _flow2, _flow3, _flow4, _flow5, _flow6)(_Flow0(42)).foo') assert not result.ok assert result.errors == [ '<string>:4: error: "_Flow7" has no attribute "foo"' ]

39.324324

100

0.623957

1,271

10,185

4.666404

0.076318

0.053954

0.068285

0.09307

0.791941

0.769179

0.764289

0.756365

0.732254

0.679649

0

0.060084

0.253216

10,185

258

101

39.476744

0.719695

0.036426

0

0.431925

0

0.004695

0.268425

0.014106

0

0.225352

1

0.253521

false

0

0.032864

0.075117

0.431925

0

null

0

1

0

null

0

1

0

6

c22ebd720448595c97fe43fe5da3005e56efe8c7

7,312

py

Python

ui/faceForward.py

fsanges/glTools

8ff0899de43784a18bd4543285655e68e28fb5e5

[ "MIT" ]

165

2015-01-26T05:22:04.000Z

2022-03-22T02:50:41.000Z

ui/faceForward.py

qeeji/glTools

8ff0899de43784a18bd4543285655e68e28fb5e5

[ "MIT" ]

5

2015-12-02T02:39:44.000Z

2020-12-09T02:45:54.000Z

ui/faceForward.py

qeeji/glTools

8ff0899de43784a18bd4543285655e68e28fb5e5

[ "MIT" ]

83

2015-02-10T17:18:24.000Z

2022-02-10T07:16:47.000Z

import maya.cmds as mc import glTools.tools.faceForward import glTools.ui.utils class UserInputError(Exception): pass def faceForwardUI(): ''' ''' # Window win = 'faceForwardUI' if mc.window(win,q=True,ex=True): mc.deleteUI(win) win = mc.window(win,t='Face Forward') # Layout formLayout = mc.formLayout(numberOfDivisions=100) # Transform transformTFB = mc.textFieldButtonGrp('faceForwardTransformTFB',label='Transform',text='',buttonLabel='Load Selected') # Axis' axisList = ['X','Y','Z','-X','-Y','-Z'] aimOMG = mc.optionMenuGrp('faceForwardAimOMG',label='Aim Axis') for axis in axisList: mc.menuItem(label=axis) upOMG = mc.optionMenuGrp('faceForwardUpOMG',label='Up Axis') for axis in axisList: mc.menuItem(label=axis) # Up Vector upVecFFG = mc.floatFieldGrp('faceForwardUpVecFFG',label='Up Vector',numberOfFields=3,value1=0.0,value2=1.0,value3=0.0) upVecTypeOMG = mc.optionMenuGrp('faceForwardUpVecTypeOMG',label='Up Vector Type') for method in ['Current','Vector','Object','ObjectUp']: mc.menuItem(label=method) upVecObjTFB = mc.textFieldButtonGrp('faceForwardUpVecObjTFB',label='Up Vector Object',text='',buttonLabel='Load Selected') # Previous Frame prevFrameCBG = mc.checkBoxGrp('faceForwardPrevFrameCBG',label='Prev Frame Velocity',numberOfCheckBoxes=1) # Key keyframeCBG = mc.checkBoxGrp('faceForwardKeyCBG',label='Set Keyframe',numberOfCheckBoxes=1) # Buttons faceForwardB = mc.button(label='Face Forward',c='glTools.ui.faceForward.faceForwardFromUI()') cancelB = mc.button(label='Cancel',c='mc.deleteUI("'+win+'")') # UI Callbacks mc.textFieldButtonGrp(transformTFB,e=True,bc='glTools.ui.utils.loadTypeSel("'+transformTFB+'","","transform")') mc.textFieldButtonGrp(upVecObjTFB,e=True,bc='glTools.ui.utils.loadTypeSel("'+upVecObjTFB+'","","transform")') # Form Layout - MAIN mc.formLayout(formLayout,e=True,af=[(transformTFB,'left',5),(transformTFB,'top',5),(transformTFB,'right',5)]) mc.formLayout(formLayout,e=True,af=[(aimOMG,'left',5),(aimOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(aimOMG,'top',5,transformTFB)]) mc.formLayout(formLayout,e=True,af=[(upOMG,'left',5),(upOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upOMG,'top',5,aimOMG)]) mc.formLayout(formLayout,e=True,af=[(upVecFFG,'left',5),(upVecFFG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecFFG,'top',5,upOMG)]) mc.formLayout(formLayout,e=True,af=[(upVecTypeOMG,'left',5),(upVecTypeOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecTypeOMG,'top',5,upVecFFG)]) mc.formLayout(formLayout,e=True,af=[(upVecObjTFB,'left',5),(upVecObjTFB,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecObjTFB,'top',5,upVecTypeOMG)]) mc.formLayout(formLayout,e=True,af=[(prevFrameCBG,'left',5),(prevFrameCBG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(prevFrameCBG,'top',5,upVecObjTFB)]) mc.formLayout(formLayout,e=True,af=[(keyframeCBG,'left',5),(keyframeCBG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(keyframeCBG,'top',5,prevFrameCBG)]) mc.formLayout(formLayout,e=True,af=[(faceForwardB,'right',5),(faceForwardB,'bottom',5)]) mc.formLayout(formLayout,e=True,ac=[(faceForwardB,'top',5,keyframeCBG)]) mc.formLayout(formLayout,e=True,ap=[(faceForwardB,'left',5,50)]) mc.formLayout(formLayout,e=True,af=[(cancelB,'left',5),(cancelB,'bottom',5)]) mc.formLayout(formLayout,e=True,ac=[(cancelB,'top',5,keyframeCBG)]) mc.formLayout(formLayout,e=True,ap=[(cancelB,'right',5,50)]) # Show Window mc.showWindow(win) def faceForwardFromUI(): ''' ''' pass def faceForwardAnimUI(): ''' ''' # Window win = 'faceForwardAnimUI' if mc.window(win,q=True,ex=True): mc.deleteUI(win) win = mc.window(win,t='Face Forward Anim') # Layout formLayout = mc.formLayout(numberOfDivisions=100) # Transform transformTFB = mc.textFieldButtonGrp('faceForwardAnimTransformTFB',label='Transform',text='',buttonLabel='Load Selected') # Axis' axisList = ['X','Y','Z','-X','-Y','-Z'] aimOMG = mc.optionMenuGrp('faceForwardAnimAimOMG',label='Aim Axis') for axis in axisList: mc.menuItem(label=axis) upOMG = mc.optionMenuGrp('faceForwardAnimUpOMG',label='Up Axis') for axis in axisList: mc.menuItem(label=axis) # Up Vector upVecFFG = mc.floatFieldGrp('faceForwardAnimUpVecFFG',label='Up Vector',numberOfFields=3,value1=0.0,value2=1.0,value3=0.0) upVecTypeOMG = mc.optionMenuGrp('faceForwardAnimUpVecTypeOMG',label='Up Vector Type') for method in ['Current','Vector','Object','ObjectUp']: mc.menuItem(label=method) upVecObjTFB = mc.textFieldButtonGrp('faceForwardAnimUpVecObjTFB',label='Up Vector Object',text='',buttonLabel='Load Selected') # Start / End Frame rangeFFG = mc.floatFieldGrp('faceForwardAnimRangeFFG',label='Start/End Frame',numberOfFields=2,value1=-1.0,value2=-1.0) # Samples samplesIFG = mc.intFieldGrp('faceForwardAnimSampleIFG',label='Samples',numberOfFields=1) # Previous Frame prevFrameCBG = mc.checkBoxGrp('faceForwardAnimPrevFrameCBG',label='Prev Frame Velocity',numberOfCheckBoxes=1) # Buttons faceForwardAnimB = mc.button(label='Face Forward',c='glTools.ui.faceForward.faceForwardAnimFromUI()') cancelB = mc.button(label='Cancel',c='mc.deleteUI("'+win+'")') # UI Callbacks mc.textFieldButtonGrp(transformTFB,e=True,bc='glTools.ui.utils.loadTypeSel("'+transformTFB+'","","transform")') mc.textFieldButtonGrp(upVecObjTFB,e=True,bc='glTools.ui.utils.loadTypeSel("'+upVecObjTFB+'","","transform")') # Form Layout - MAIN mc.formLayout(formLayout,e=True,af=[(transformTFB,'left',5),(transformTFB,'top',5),(transformTFB,'right',5)]) mc.formLayout(formLayout,e=True,af=[(aimOMG,'left',5),(aimOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(aimOMG,'top',5,transformTFB)]) mc.formLayout(formLayout,e=True,af=[(upOMG,'left',5),(upOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upOMG,'top',5,aimOMG)]) mc.formLayout(formLayout,e=True,af=[(upVecFFG,'left',5),(upVecFFG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecFFG,'top',5,upOMG)]) mc.formLayout(formLayout,e=True,af=[(upVecTypeOMG,'left',5),(upVecTypeOMG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecTypeOMG,'top',5,upVecFFG)]) mc.formLayout(formLayout,e=True,af=[(upVecObjTFB,'left',5),(upVecObjTFB,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(upVecObjTFB,'top',5,upVecTypeOMG)]) mc.formLayout(formLayout,e=True,af=[(rangeFFG,'left',5),(rangeFFG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(rangeFFG,'top',5,upVecObjTFB)]) mc.formLayout(formLayout,e=True,af=[(samplesIFG,'left',5),(samplesIFG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(samplesIFG,'top',5,rangeFFG)]) mc.formLayout(formLayout,e=True,af=[(prevFrameCBG,'left',5),(prevFrameCBG,'right',5)]) mc.formLayout(formLayout,e=True,ac=[(prevFrameCBG,'top',5,samplesIFG)]) mc.formLayout(formLayout,e=True,af=[(faceForwardAnimB,'right',5),(faceForwardAnimB,'bottom',5)]) mc.formLayout(formLayout,e=True,ac=[(faceForwardAnimB,'top',5,prevFrameCBG)]) mc.formLayout(formLayout,e=True,ap=[(faceForwardAnimB,'left',5,50)]) mc.formLayout(formLayout,e=True,af=[(cancelB,'left',5),(cancelB,'bottom',5)]) mc.formLayout(formLayout,e=True,ac=[(cancelB,'top',5,prevFrameCBG)]) mc.formLayout(formLayout,e=True,ap=[(cancelB,'right',5,50)]) # Show Window mc.showWindow(win) def faceForwardAnimFromUI(): ''' ''' pass

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c23e08dbe819a23eb0927f62afa3675776d81143

42

py

Python

slackbucket/tests/test_nothing.py

micole/slackbucket

e3cd4cd8db086011548a4c3bfeb233d4ded2270a

[ "MIT" ]

2

2018-02-12T19:11:05.000Z

2018-02-15T14:35:03.000Z

slackbucket/tests/test_nothing.py

micole/slackbucket

e3cd4cd8db086011548a4c3bfeb233d4ded2270a

[ "MIT" ]

1

2021-06-01T21:52:25.000Z

slackbucket/tests/test_nothing.py

micole/slackbucket

e3cd4cd8db086011548a4c3bfeb233d4ded2270a

[ "MIT" ]

1

2018-02-12T19:17:54.000Z

def test_testing_setup(): assert True

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df9cffee43a7b86b9eebe28d02d6b6d42be4a58c

5,368

py

Python

tests/test_utils.py

vishalbelsare/category_encoders

55636b5ae11dc45075a0c248028f17f9df93bbb9

[ "BSD-3-Clause" ]

1,178

2016-11-21T14:52:45.000Z

2020-04-24T17:04:55.000Z

tests/test_utils.py

vishalbelsare/category_encoders

55636b5ae11dc45075a0c248028f17f9df93bbb9

[ "BSD-3-Clause" ]

213

2016-11-28T15:33:57.000Z

2020-04-27T14:15:57.000Z

tests/test_utils.py

vishalbelsare/category_encoders

55636b5ae11dc45075a0c248028f17f9df93bbb9

[ "BSD-3-Clause" ]

262

2016-12-19T15:58:16.000Z

2020-04-25T07:24:38.000Z

from unittest import TestCase # or `from unittest import ...` if on Python 3.4+ from category_encoders.utils import convert_input_vector, convert_inputs import pandas as pd import numpy as np class TestUtils(TestCase): def test_convert_input_vector(self): index = [2, 3, 4] result = convert_input_vector([0, 1, 0], index) # list self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector([[0, 1, 0]], index) # list of lists (row) self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector([[0], [1], [0]], index) # list of lists (column) self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector(np.array([1, 0, 1]), index) # np vector self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector(np.array([[1, 0, 1]]), index) # np matrix row self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector(np.array([[1], [0], [1]]), index) # np matrix column self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector(pd.Series([0, 1, 0], index=[4, 5, 6]), index) # series self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [4, 5, 6], 'We want to preserve the original index') result = convert_input_vector(pd.DataFrame({'y': [0, 1, 0]}, index=[4, 5, 6]), index) # dataFrame self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [4, 5, 6], 'We want to preserve the original index') result = convert_input_vector((0, 1, 0), index) # tuple self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(3, len(result)) np.testing.assert_array_equal(result.index, [2, 3, 4]) result = convert_input_vector(0, [2]) # scalar self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(1, len(result)) self.assertTrue(result.index == [2]) result = convert_input_vector('a', [2]) # scalar self.assertTrue(isinstance(result, pd.Series)) self.assertEqual(1, len(result)) self.assertTrue(result.index == [2]) # multiple columns and rows should cause an error because it is unclear which column/row to use as the target self.assertRaises(ValueError, convert_input_vector, (pd.DataFrame({'col1': [0, 1, 0], 'col2': [1, 0, 1]})), index) self.assertRaises(ValueError, convert_input_vector, (np.array([[0, 1], [1, 0], [0, 1]])), index) self.assertRaises(ValueError, convert_input_vector, ([[0, 1], [1, 0], [0, 1]]), index) # edge scenarios (it is ok to raise an exception but please, provide then a helpful exception text) _ = convert_input_vector(pd.Series(dtype=float), []) _ = convert_input_vector([], []) _ = convert_input_vector([[]], []) _ = convert_input_vector(pd.DataFrame(), []) def test_convert_inputs(self): aindex = [2, 4, 5] bindex = [1, 3, 4] alist = [5, 3, 6] aseries = pd.Series(alist, aindex) barray = np.array([[7, 9], [4, 3], [0, 1]]) bframe = pd.DataFrame(barray, bindex) X, y = convert_inputs(barray, alist) self.assertTrue(isinstance(X, pd.DataFrame)) self.assertTrue(isinstance(y, pd.Series)) self.assertEqual((3, 2), X.shape) self.assertEqual(3, len(y)) self.assertTrue(list(X.index) == list(y.index) == [0, 1, 2]) X, y = convert_inputs(barray, alist, index=aindex) self.assertTrue(isinstance(X, pd.DataFrame)) self.assertTrue(isinstance(y, pd.Series)) self.assertEqual((3, 2), X.shape) self.assertEqual(3, len(y)) self.assertTrue(list(X.index) == list(y.index) == aindex) X, y = convert_inputs(barray, aseries, index=bindex) self.assertTrue(isinstance(X, pd.DataFrame)) self.assertTrue(isinstance(y, pd.Series)) self.assertEqual((3, 2), X.shape) self.assertEqual(3, len(y)) self.assertTrue(list(X.index) == list(y.index) == aindex) X, y = convert_inputs(bframe, alist, index=[3, 1, 4]) self.assertTrue(isinstance(X, pd.DataFrame)) self.assertTrue(isinstance(y, pd.Series)) self.assertEqual((3, 2), X.shape) self.assertEqual(3, len(y)) self.assertTrue(list(X.index) == list(y.index) == bindex) self.assertRaises(ValueError, convert_inputs, bframe, aseries) # shape mismatch self.assertRaises(ValueError, convert_inputs, barray, [1, 2, 3, 4])

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6

5f1f28192d34bf5dfea7b6f978148aed15012091

94

py

Python

office365/sharepoint/directory/user.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

office365/sharepoint/directory/user.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

office365/sharepoint/directory/user.py

wreiner/Office365-REST-Python-Client

476bbce4f5928a140b4f5d33475d0ac9b0783530

[ "MIT" ]

null

from office365.runtime.client_object import ClientObject class User(ClientObject): pass

15.666667

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6

a02f848a044372d09ed7f566b0f7a24a31be37c3

203

py

Python

channel-api/src/api/utils.py

xcantera/demo-provide-baseline

985f391973fa6ca0761104b55077fded28f152fc

[ "CC0-1.0" ]

3

2020-11-17T23:19:20.000Z

2021-03-29T15:08:56.000Z

channel-api/src/api/utils.py

xcantera/demo-provide-baseline

985f391973fa6ca0761104b55077fded28f152fc

[ "CC0-1.0" ]

null

channel-api/src/api/utils.py

xcantera/demo-provide-baseline

985f391973fa6ca0761104b55077fded28f152fc

[ "CC0-1.0" ]

1

2020-12-11T00:26:33.000Z

from functools import wraps from flask import request def form(func): @wraps(func) def wrapped(*args, **kwrags): return func(request.form.to_dict(), *args, **kwrags) return wrapped

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