xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

58b39d610eae8b36afa5ec0f450ede4efe4c78d4

342

py

Python

blog/views.py

artkapl/django-blog-project

16494465042dd6846f3a2cd560c0cfe7737cc8e0

[ "MIT" ]

null

blog/views.py

artkapl/django-blog-project

16494465042dd6846f3a2cd560c0cfe7737cc8e0

[ "MIT" ]

null

blog/views.py

artkapl/django-blog-project

16494465042dd6846f3a2cd560c0cfe7737cc8e0

[ "MIT" ]

null

from django.shortcuts import render from .models import Post def home(request): context = { 'posts': Post.objects.all() } return render(request=request, template_name='blog/home.html', context=context) def about(request): return render(request=request, template_name='blog/about.html', context={'title': 'About'})

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58ba74567e6fec0a65ad5136fbd9ca609c0ebda8

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py

Python

Python/6 - kyu/6 kyu - Detect Pangram.py

danielbom/codewars

d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27

[ "MIT" ]

null

Python/6 - kyu/6 kyu - Detect Pangram.py

danielbom/codewars

d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27

[ "MIT" ]

null

Python/6 - kyu/6 kyu - Detect Pangram.py

danielbom/codewars

d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27

[ "MIT" ]

null

# https://www.codewars.com/kata/detect-pangram/train/python # My solution import string def is_pangram(text): return len( {letter.lower() for letter in text if letter.isalpha()} ) == 26 # ... import string def is_pangram(s): return set(string.lowercase) <= set(s.lower()) # ... import string def is_pangram(s): s = s.lower() return all(letter in s for letter in string.lowercase)

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Python

src/mtvs/__init__.py

digsim/mtvs

d89d12d4cd65eafe732226e588a54874123db7f4

[ "Apache-2.0" ]

2

2017-11-19T05:51:31.000Z

2020-01-22T08:12:53.000Z

src/mtvs/__init__.py

digsim/mtvs

d89d12d4cd65eafe732226e588a54874123db7f4

[ "Apache-2.0" ]

3

2015-12-03T00:34:46.000Z

2016-01-04T15:49:14.000Z

src/mtvs/__init__.py

digsim/missingTvShows

f17660dc965c7a6eef1b0cfad9577d62087cba56

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import pkg_resources __version__ = pkg_resources.require("mtvs")[0].version

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py

Python

import_new_tournaments/process_hh_files/process/hands/extract/position_info/extract_stack_from_seat_line.py

michaelcukier/Poker-Hand-Tracker

9adae42fab9f640e6939ba06bd588ab1a2feb90f

[ "MIT" ]

5

2021-02-28T18:33:02.000Z

2022-03-12T01:43:40.000Z

import_new_tournaments/process_hh_files/process/hands/extract/position_info/extract_stack_from_seat_line.py

michaelcukier/Poker-Hand-Tracker

9adae42fab9f640e6939ba06bd588ab1a2feb90f

[ "MIT" ]

null

import_new_tournaments/process_hh_files/process/hands/extract/position_info/extract_stack_from_seat_line.py

michaelcukier/Poker-Hand-Tracker

9adae42fab9f640e6939ba06bd588ab1a2feb90f

[ "MIT" ]

2

2021-03-01T03:08:04.000Z

2021-12-31T17:53:46.000Z

def extract_stack_from_seat_line(seat_line: str) -> float or None: # Seat 3: PokerPete24 (40518.00) if 'will be allowed to play after the button' in seat_line: return None return float(seat_line.split(' (')[1].split(')')[0])

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58fc01c36853b26f8562e022eac13585ff61105f

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py

Python

nbviewerbot/__main__.py

JohnPaton/nbviewerbot

a9564655ba041e53db9a6916fb424e9582704321

[ "MIT" ]

7

2018-08-06T20:02:13.000Z

2021-04-12T06:04:46.000Z

nbviewerbot/__main__.py

JohnPaton/nbviewerbot

a9564655ba041e53db9a6916fb424e9582704321

[ "MIT" ]

5

2018-09-13T20:53:32.000Z

2021-03-31T18:55:48.000Z

nbviewerbot/__main__.py

JohnPaton/nbviewerbot

a9564655ba041e53db9a6916fb424e9582704321

[ "MIT" ]

null

import nbviewerbot if __name__ == "__main__": nbviewerbot.cli()

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py

Python

tests/hahm/test_config_flow.py

Voxxie/custom_homematic

d199f1fcc565febe42e686198a9eb33ef4d755f6

[ "MIT" ]

null

tests/hahm/test_config_flow.py

Voxxie/custom_homematic

d199f1fcc565febe42e686198a9eb33ef4d755f6

[ "MIT" ]

null

tests/hahm/test_config_flow.py

Voxxie/custom_homematic

d199f1fcc565febe42e686198a9eb33ef4d755f6

[ "MIT" ]

null

"""Test the HaHomematic config flow.""" from typing import Any from unittest.mock import patch from homeassistant import config_entries from homeassistant.components.hahm.config_flow import ( ATTR_BICDOS_RF_ENABLED, ATTR_BICDOS_RF_PORT, ATTR_HMIP_RF_ENABLED, ATTR_HOST, ATTR_HS485D_ENABLED, ATTR_INSTANCE_NAME, ATTR_PASSWORD, ATTR_PORT, ATTR_TLS, ATTR_USERNAME, ATTR_VIRTUAL_DEVICES_ENABLED, IF_BIDCOS_RF_NAME, IF_HMIP_RF_NAME, IF_HS485D_NAME, IF_VIRTUAL_DEVICES_NAME, CannotConnect, InvalidAuth, ) from homeassistant.components.hahm.const import DOMAIN from homeassistant.core import HomeAssistant from homeassistant.data_entry_flow import RESULT_TYPE_CREATE_ENTRY, RESULT_TYPE_FORM TEST_INSTANCE_NAME = "pytest" TEST_HOST = "1.1.1.1" TEST_USERNAME = "test-username" TEST_PASSWORD = "test-password" async def test_form(hass: HomeAssistant) -> None: """Test we get the form.""" interface = await async_check_form(hass, interface_data={}) if_hmip_rf = interface[IF_HMIP_RF_NAME] assert if_hmip_rf[ATTR_PORT] == 2010 if_bidcos_rf = interface[IF_BIDCOS_RF_NAME] assert if_bidcos_rf[ATTR_PORT] == 2001 if_virtual_devices = interface[IF_VIRTUAL_DEVICES_NAME] assert if_virtual_devices[ATTR_PORT] == 9292 assert interface.get(IF_HS485D_NAME) is None async def test_form_no_hmip_other_bidcos_port(hass: HomeAssistant) -> None: """Test we get the form.""" interface_data = {ATTR_HMIP_RF_ENABLED: False, ATTR_BICDOS_RF_PORT: 5555} interface = await async_check_form(hass, interface_data=interface_data) assert interface.get(IF_HMIP_RF_NAME) is None if_bidcos_rf = interface[IF_BIDCOS_RF_NAME] assert if_bidcos_rf[ATTR_PORT] == 5555 if_virtual_devices = interface[IF_VIRTUAL_DEVICES_NAME] assert if_virtual_devices[ATTR_PORT] == 9292 assert interface.get(IF_HS485D_NAME) is None async def test_form_only_hs485(hass: HomeAssistant) -> None: """Test we get the form.""" interface_data = { ATTR_HMIP_RF_ENABLED: False, ATTR_BICDOS_RF_ENABLED: False, ATTR_VIRTUAL_DEVICES_ENABLED: False, ATTR_HS485D_ENABLED: True, } interface = await async_check_form(hass, interface_data=interface_data) assert interface.get(IF_HMIP_RF_NAME) is None assert interface.get(IF_BIDCOS_RF_NAME) is None assert interface.get(IF_VIRTUAL_DEVICES_NAME) is None if_hs485d = interface[IF_HS485D_NAME] assert if_hs485d[ATTR_PORT] == 2000 async def test_form_tls(hass: HomeAssistant) -> None: """Test we get the form with tls.""" interface = await async_check_form(hass, interface_data={}, tls=True) if_hmip_rf = interface[IF_HMIP_RF_NAME] assert if_hmip_rf[ATTR_PORT] == 42010 if_bidcos_rf = interface[IF_BIDCOS_RF_NAME] assert if_bidcos_rf[ATTR_PORT] == 42001 if_virtual_devices = interface[IF_VIRTUAL_DEVICES_NAME] assert if_virtual_devices[ATTR_PORT] == 49292 assert interface.get(IF_HS485D_NAME) is None async def async_check_form( hass: HomeAssistant, interface_data: dict[str, Any], tls: bool = False ) -> dict[str, Any]: """Test we get the form.""" if interface_data is None: interface_data = {} result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["errors"] is None with patch( "homeassistant.components.hahm.config_flow.validate_input", return_value=True, ), patch( "homeassistant.components.hahm.async_setup_entry", return_value=True, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { ATTR_INSTANCE_NAME: TEST_INSTANCE_NAME, ATTR_HOST: TEST_HOST, ATTR_USERNAME: TEST_USERNAME, ATTR_PASSWORD: TEST_PASSWORD, ATTR_TLS: tls, }, ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_FORM assert result2["handler"] == DOMAIN assert result2["step_id"] == "interface" flow = next( flow for flow in hass.config_entries.flow.async_progress() if flow["flow_id"] == result["flow_id"] ) assert flow["context"]["unique_id"] == "pytest" result3 = await hass.config_entries.flow.async_configure( result["flow_id"], interface_data, ) await hass.async_block_till_done() assert result3["type"] == RESULT_TYPE_CREATE_ENTRY assert result3["handler"] == DOMAIN assert result3["title"] == TEST_INSTANCE_NAME data = result3["data"] assert data[ATTR_INSTANCE_NAME] == TEST_INSTANCE_NAME assert data[ATTR_HOST] == TEST_HOST assert data[ATTR_USERNAME] == TEST_USERNAME assert data[ATTR_PASSWORD] == TEST_PASSWORD return data["interface"] async def test_form_invalid_auth(hass: HomeAssistant) -> None: """Test we handle invalid auth.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["errors"] is None with patch( "homeassistant.components.hahm.config_flow.validate_input", side_effect=InvalidAuth, ), patch( "homeassistant.components.hahm.async_setup_entry", return_value=True, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { ATTR_INSTANCE_NAME: TEST_INSTANCE_NAME, ATTR_HOST: TEST_HOST, ATTR_USERNAME: TEST_USERNAME, ATTR_PASSWORD: TEST_PASSWORD, }, ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_FORM assert result2["handler"] == DOMAIN assert result2["step_id"] == "interface" flow = next( flow for flow in hass.config_entries.flow.async_progress() if flow["flow_id"] == result["flow_id"] ) assert flow["context"]["unique_id"] == "pytest" result3 = await hass.config_entries.flow.async_configure( result["flow_id"], {}, ) await hass.async_block_till_done() assert result3["type"] == RESULT_TYPE_FORM assert result3["errors"] == {"base": "invalid_auth"} async def test_form_cannot_connect(hass: HomeAssistant) -> None: """Test we handle cannot connect error.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == RESULT_TYPE_FORM assert result["errors"] is None with patch( "homeassistant.components.hahm.config_flow.validate_input", side_effect=CannotConnect, ), patch( "homeassistant.components.hahm.async_setup_entry", return_value=True, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], { ATTR_INSTANCE_NAME: TEST_INSTANCE_NAME, ATTR_HOST: TEST_HOST, ATTR_USERNAME: TEST_USERNAME, ATTR_PASSWORD: TEST_PASSWORD, }, ) await hass.async_block_till_done() assert result2["type"] == RESULT_TYPE_FORM assert result2["handler"] == DOMAIN assert result2["step_id"] == "interface" flow = next( flow for flow in hass.config_entries.flow.async_progress() if flow["flow_id"] == result["flow_id"] ) assert flow["context"]["unique_id"] == "pytest" result3 = await hass.config_entries.flow.async_configure( result["flow_id"], {}, ) await hass.async_block_till_done() assert result3["type"] == RESULT_TYPE_FORM assert result3["errors"] == {"base": "cannot_connect"}

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py

Python

project euler/q2.py

milkmeat/thomas

fbc72af34267488d931a4885d4e19fce22fea582

[ "MIT" ]

null

project euler/q2.py

milkmeat/thomas

fbc72af34267488d931a4885d4e19fce22fea582

[ "MIT" ]

null

project euler/q2.py

milkmeat/thomas

fbc72af34267488d931a4885d4e19fce22fea582

[ "MIT" ]

null

l=[0]*100 l[0]=1 l[1]=2 for x in range (2,100): l[x]=l[x-1]+l[x-2] #print l f=0 for c in l: if c%2==0 and c<4000000: f=f+c print f

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189105da68157256feb66cf959f48a9d4b0c8a3a

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py

Python

tests/development/destination/gcs/test_delete_bucket.py

denssk/backup

292d5f1b1a3765ce0ea8d3cab8bd1ae0c583f72e

[ "Apache-2.0" ]

69

2016-06-29T16:13:55.000Z

2022-03-21T06:38:37.000Z

tests/development/destination/gcs/test_delete_bucket.py

denssk/backup

292d5f1b1a3765ce0ea8d3cab8bd1ae0c583f72e

[ "Apache-2.0" ]

237

2016-09-28T02:12:34.000Z

2022-03-25T13:32:23.000Z

tests/development/destination/gcs/test_delete_bucket.py

denssk/backup

292d5f1b1a3765ce0ea8d3cab8bd1ae0c583f72e

[ "Apache-2.0" ]

45

2017-01-04T21:20:27.000Z

2021-12-29T10:42:22.000Z

def test_delete_bucket(gs): gs.delete_bucket()

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18b566b173e3af542df61de7dc132ac1fb281305

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py

Python

tests/WebkitGtkDriverBenchmarkTest.py

hiroshitoda/WebDriverBenchmark.py

74b643b9f299436ef6fb50741a60f04c0c69cf8c

[ "Apache-2.0" ]

null

tests/WebkitGtkDriverBenchmarkTest.py

hiroshitoda/WebDriverBenchmark.py

74b643b9f299436ef6fb50741a60f04c0c69cf8c

[ "Apache-2.0" ]

null

tests/WebkitGtkDriverBenchmarkTest.py

hiroshitoda/WebDriverBenchmark.py

74b643b9f299436ef6fb50741a60f04c0c69cf8c

[ "Apache-2.0" ]

null

import unittest from selenium import webdriver from tests import Base class WebKitGTKDriverBenchmarkTest(Base.Base): def getDriver(self): return webdriver.WebKitGTK() if __name__ == "__main__": unittest.main()

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18d67d5d9fabdd711ac5fef81a528edb66bc9e9b

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py

Python

lms_python/lms_app/admin.py

gabrielmdsantos/LMSBD

dff3001a560f8cccb938957bf2d5732d4ae3d163

[ "Apache-2.0" ]

null

lms_python/lms_app/admin.py

gabrielmdsantos/LMSBD

dff3001a560f8cccb938957bf2d5732d4ae3d163

[ "Apache-2.0" ]

null

lms_python/lms_app/admin.py

gabrielmdsantos/LMSBD

dff3001a560f8cccb938957bf2d5732d4ae3d163

[ "Apache-2.0" ]

null

from django.contrib import admin from lms_app.models import Professor admin.site.register(Professor) # Register your models here.

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py

Python

Exercício feitos pela primeira vez/ex004colorido.py

Claayton/pythonExerciciosLinux

696cdb16983638418bd0d0d4fe44dc72662b9c97

[ "MIT" ]

1

2021-01-23T15:43:34.000Z

Exercício feitos pela primeira vez/ex004colorido.py

Claayton/pythonExerciciosLinux

696cdb16983638418bd0d0d4fe44dc72662b9c97

[ "MIT" ]

null

Exercício feitos pela primeira vez/ex004colorido.py

Claayton/pythonExerciciosLinux

696cdb16983638418bd0d0d4fe44dc72662b9c97

[ "MIT" ]

null

#Ex004b algo = (input('\033[34m''Digite algo: ''\033[m')) print('São letras ou palavras?: \033[33m{}\033[m'.format(algo.isalpha())) print('Está em maiúsculo?: \033[34m{}\033[m'.format(algo.isupper())) print('Está em minúsculo?: \033[35m{}\033[m'.format(algo.islower())) print('Está captalizada?: \033[36m{}\033[m'.format(algo.istitle())) print('Só tem espaço?: \033[31m{}\033[m'.format(algo.isspace())) print('É numérico?: \033[32m{}\033[m'.format(algo.isnumeric())) print('xD')

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18e8661bfba7a01963831fc9dac3f2b59f8ea633

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py

Python

examples/set_holidaydates.py

ultratolido/ekmmetters

e15325023262e228b4dc037021c28a8d2b9b9b03

[ "MIT" ]

null

examples/set_holidaydates.py

ultratolido/ekmmetters

e15325023262e228b4dc037021c28a8d2b9b9b03

[ "MIT" ]

null

examples/set_holidaydates.py

ultratolido/ekmmetters

e15325023262e228b4dc037021c28a8d2b9b9b03

[ "MIT" ]

null

""" Simple example set holiday dates (c) 2016 EKM Metering. """ import random from ekmmeters import * #port setup my_port_name = "COM3" my_meter_address = "300001162" #log to console ekm_set_log(ekm_print_log) # init port and meter port = SerialPort(my_port_name) if (port.initPort() == True): my_meter = V4Meter(my_meter_address) my_meter.attachPort(port) else: print "Cannot open port" exit() # input over range(Extents.Holidays) for holiday in range(Extents.Holidays): day = random.randint(1,28) mon = random.randint(1,12) my_meter.assignHolidayDate(holiday, mon, day) my_meter.setHolidayDates() # input directly param_buf = OrderedDict() param_buf["Holiday_1_Month"] = 1 param_buf["Holiday_1_Day"] = 1 param_buf["Holiday_2_Month"] = 2 param_buf["Holiday_2_Day"] = 3 param_buf["Holiday_3_Month"] = 4 param_buf["Holiday_3_Day"] = 4 param_buf["Holiday_4_Month"] = 4 param_buf["Holiday_4_Day"] = 5 param_buf["Holiday_5_Month"] = 5 param_buf["Holiday_5_Day"] = 4 param_buf["Holiday_6_Month"] = 0 param_buf["Holiday_6_Day"] = 0 param_buf["Holiday_7_Month"] = 0 param_buf["Holiday_7_Day"] = 0 param_buf["Holiday_8_Month"] = 0 param_buf["Holiday_8_Day"] = 0 param_buf["Holiday_9_Month"] = 0 param_buf["Holiday_9_Day"] = 0 param_buf["Holiday_10_Month"] = 0 param_buf["Holiday_10_Day"] = 0 param_buf["Holiday_11_Month"] = 0 param_buf["Holiday_11_Day"] = 0 param_buf["Holiday_12_Month"] = 0 param_buf["Holiday_12_Day"] = 0 param_buf["Holiday_13_Month"] = 0 param_buf["Holiday_13_Day"] = 0 param_buf["Holiday_14_Month"] = 0 param_buf["Holiday_14_Day"] = 0 param_buf["Holiday_15_Month"] = 0 param_buf["Holiday_15_Day"] = 0 param_buf["Holiday_16_Month"] = 0 param_buf["Holiday_16_Day"] = 0 param_buf["Holiday_17_Month"] = 0 param_buf["Holiday_17_Day"] = 0 param_buf["Holiday_18_Month"] = 0 param_buf["Holiday_18_Day"] = 0 param_buf["Holiday_19_Month"] = 0 param_buf["Holiday_19_Day"] = 0 param_buf["Holiday_20_Month"] = 1 param_buf["Holiday_20_Day"] = 9 if my_meter.setHolidayDates(param_buf): print "Set holiday dates success." port.closePort()

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null

0

1

0

4

18ea8109933fbbfe2b0922e33bce91ae934e86e1

2,010

py

Python

StateTracing/tester_helper.py

junchenfeng/diagnosis_tracing

4e26e2ad0c7abc547f22774b6c9c299999a152c3

[ "MIT" ]

null

StateTracing/tester_helper.py

junchenfeng/diagnosis_tracing

4e26e2ad0c7abc547f22774b6c9c299999a152c3

[ "MIT" ]

null

StateTracing/tester_helper.py

junchenfeng/diagnosis_tracing

4e26e2ad0c7abc547f22774b6c9c299999a152c3

[ "MIT" ]

1

2020-09-08T13:42:16.000Z

# -*- coding: utf-8 -*- import numpy as np from torch import load as Tload from torch import tensor from dataloader import read_data,DataLoader,load_init from cdkt import CDKT if 'model' not in dir(): model = CDKT() model.load_state_dict(Tload('model.pkl')) # inits = load_init() data = """0 506123310064654031030450460312100605 0 506123310064654031230450460312100605 0 506123310064654031231450460312100605 0 506123310064654031231456460312100605 0 506123310064654031231456460312100645 0 506123310564654031231456460312100645 0 506123310564654231231456460312100645 0 506123310564654231231456460312100605 0 506123310564654231231456460312100645 0 506123312564654231231456460312100645 0 546123312564654231231456460312100645 0 546123312564654231231456465312100645 0 546123312564654231231456465312120645 0 546123312564654231231456465312123645 1 002163163050030425245001316542000000 1 002163163054030425245001316542000000 1 002163163054030425245001316542000006""" # 1 002163163054030425245001316542030006 # 1 002163163054030425245001316542000006 # 1 002163163054031425245001316542000006 # 1 002163163054631425245001316542000006 # 1 002163163254631425245001316542000006 # 1 002163163254631425245601316542000006 # 1 002163163254631425245631316542000006 # 1 052163163254631425245631316542000006 # 1 452163163254631425245631316542000006 # 1 452163163254631425245631316542000016 # 1 452163163254631425245631316542000316 # 1 452163163254631425245631316542003316 # 1 452163163254631425245631316542000316 # 1 452163163254631425245631316542500316 # 1 452163163254631425245631316542520316 # 1 452163163254631425245631316542524316""" data = [d.strip().split() for d in data.split('\n')] states = [list(map(int,s)) for i,s in data] states = tensor([states]) out = model.predicts(states) prds = np.argmax(out[0],axis=2).flatten()*np.array(inits[2])

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null

0

4

7a1607febbd34072033d2922ea13752164e46320

357

py

Python

src/__init__.py

w9PcJLyb/GFootball

b271238bd0dc922787a0a9b984a8ae598cea2b2b

[ "Apache-2.0" ]

null

src/__init__.py

w9PcJLyb/GFootball

b271238bd0dc922787a0a9b984a8ae598cea2b2b

[ "Apache-2.0" ]

null

src/__init__.py

w9PcJLyb/GFootball

b271238bd0dc922787a0a9b984a8ae598cea2b2b

[ "Apache-2.0" ]

null

from .board import Board from .slide import slide_action from .corner import corner_action from .control import control_action from .penalty import penalty_action from .throwin import throwin_action from .kickoff import kickoff_action from .goalkick import goalkick_action from .freekick import freekick_action from .without_ball import without_ball_action

32.454545

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1

0

1

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7a1eab82419109b15e6baf92f1df08cd9c6fa14b

856

py

Python

class_exercises/using_numpy.py

Eddz7/astr-19

380c6b45762e0207cd6c237fa28a4d796b1aef94

[ "MIT" ]

null

class_exercises/using_numpy.py

Eddz7/astr-19

380c6b45762e0207cd6c237fa28a4d796b1aef94

[ "MIT" ]

1

2022-03-31T17:57:17.000Z

class_exercises/using_numpy.py

Eddz7/astr-19

380c6b45762e0207cd6c237fa28a4d796b1aef94

[ "MIT" ]

null

import numpy as np x = 1.0 #define a float y = 2.0 #define another float #trigonometry print(f"np.sin({x}) = {np.sin(x)}") #sin(x) print(f"np.cos({x}) = {np.cos(x)}") #cos(x) print(f"np.tan({x}) = {np.tan(x)}") #tan(x) print(f"np.arcsin({x}) = {np.arcsin(x)}") #arcsin(x) print(f"np.arccos({x}) = {np.arccos(x)}") #arccos(x) print(f"np.arctan({x}) = {np.arctan(x)}") #arctan(x) print(f"np.arctan2({x}) = {np.arctan2(x,y)}") #arctan(x/y) print(f"np.rad2deg({x}) = {np.rad2deg(x)}") #convert rad to degree #hyperbolic functions print(f"np.sinh({x}) = {np.sinh(x)}") #sinh(x) print(f"np.cosh({x}) = {np.cosh(x)}") #cosh(x) print(f"np.tanh({x}) = {np.tanh(x)}") #tanh(x) print(f"np.arcsinh({x}) = {np.arcsinh(x)}") #arcsinh(x) print(f"np.arccosh({x}) = {np.arccosh(x)}") #arccosh(x) print(f"np.arctanh({x}) = {np.arctanh(x)}") #arctanh(x)

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e12ea6090b7a3fc25058fb7f99f94d6f336e2f07

17,628

py

Python

docs/pyqbdi.py

pbrunet/QBDI

39a936b2efd000f0c5def0a8ea27538d7d5fab47

[ "Apache-2.0" ]

1

2019-10-01T08:32:41.000Z

docs/pyqbdi.py

pbrunet/QBDI

39a936b2efd000f0c5def0a8ea27538d7d5fab47

[ "Apache-2.0" ]

null

docs/pyqbdi.py

pbrunet/QBDI

39a936b2efd000f0c5def0a8ea27538d7d5fab47

[ "Apache-2.0" ]

null

# This file is only used to generate documentation # VM class class vm(): def getGPRState(): """Obtain the current general purpose register state. :returns: GPRState (an object containing the GPR state). """ pass def getFPRState(): """Obtain the current floating point register state. :returns: FPRState (an object containing the FPR state). """ pass def setGPRState(gprState): """Set the general purpose register state. :param grpState: An object containing the GPR state. """ pass def setFPRState(fprState): """Set the current floating point register state. :param fprState: An object containing the FPR state """ pass def run(start, stop): """Start the execution by the DBI from a given address (and stop when another is reached). :param start: Address of the first instruction to execute. :param stop: Stop the execution when this instruction is reached. :returns: True if at least one block has been executed. """ pass def call(function, args): """Call a function using the DBI (and its current state). :param function: Address of the function start instruction. :param args: The arguments as a list [arg0, arg1, arg2, ...]. :returns: (True, retValue) if at least one block has been executed. """ pass def addCodeCB(pos, cbk, data): """Register a callback event for a specific instruction event. :param pos: Relative position of the event callback (:py:const:`pyqbdi.PREINST` / :py:const:`pyqbdi.POSTINST`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addCodeAddrCB(address, pos, cbk, data): """Register a callback for when a specific address is executed. :param address: Code address which will trigger the callback. :param pos: Relative position of the event callback (:py:const:`pyqbdi.PREINST` / :py:const:`pyqbdi.POSTINST`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addCodeRangeCB(start, end, pos, cbk, data): """Register a callback for when a specific address range is executed. :param start: Start of the address range which will trigger the callback. :param end: End of the address range which will trigger the callback. :param pos: Relative position of the event callback (:py:const:`pyqbdi.PREINST` / :py:const:`pyqbdi.POSTINST`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addMnemonicCB(mnemonic, pos, cbk, data): """Register a callback event if the instruction matches the mnemonic. :param mnemonic: Mnemonic to match. :param pos: Relative position of the event callback (:py:const:`pyqbdi.PREINST` / :py:const:`pyqbdi.POSTINST`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def deleteInstrumentation(id): """Remove an instrumentation. :param id: The id of the instrumentation to remove. :returns: True if instrumentation has been removed. """ pass def deleteAllInstrumentations(): """Remove all the registered instrumentations. """ pass def addMemAddrCB(address, type, cbk, data): """Add a virtual callback which is triggered for any memory access at a specific address matching the access type. Virtual callbacks are called via callback forwarding by a gate callback triggered on every memory access. This incurs a high performance cost. :param address: Code address which will trigger the callback. :param type: A mode bitfield: either :py:const:`pyqbdi.MEMORY_READ`, :py:const:`pyqbdi.MEMORY_WRITE` or both (:py:const:`pyqbdi.MEMORY_READ_WRITE`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addMemRangeCB(start, end, type, cbk, data): """Add a virtual callback which is triggered for any memory access in a specific address range matching the access type. Virtual callbacks are called via callback forwarding by a gate callback triggered on every memory access. This incurs a high performance cost. :param start: Start of the address range which will trigger the callback. :param end: End of the address range which will trigger the callback. :param type: A mode bitfield: either :py:const:`pyqbdi.MEMORY_READ`, :py:const:`pyqbdi.MEMORY_WRITE` or both (:py:const:`pyqbdi.MEMORY_READ_WRITE`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addMemAccessCB(type, cbk, data): """Register a callback event for every memory access matching the type bitfield made by an instruction. :param type: A mode bitfield: either :py:const:`pyqbdi.MEMORY_READ`, :py:const:`pyqbdi.MEMORY_WRITE` or both (:py:const:`pyqbdi.MEMORY_READ_WRITE`). :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def recordMemoryAccess(type): """Add instrumentation rules to log memory access using inline instrumentation and instruction shadows. :param type: Memory mode bitfield to activate the logging for: either :py:const:`pyqbdi.MEMORY_READ`, :py:const:`pyqbdi.MEMORY_WRITE` or both (:py:const:`pyqbdi.MEMORY_READ_WRITE`). :returns: True if inline memory logging is supported, False if not or in case of error. """ pass def getInstAnalysis(type): """ Obtain the analysis of an instruction metadata. Analysis results are cached in the VM. The validity of the returned object is only guaranteed until the end of the callback, else a deepcopy of the object is required. :param type: Properties to retrieve during analysis (pyqbdi.ANALYSIS_INSTRUCTION, pyqbdi.ANALYSIS_DISASSEMBLY, pyqbdi.ANALYSIS_OPERANDS, pyqbdi.ANALYSIS_SYMBOL). :returns: A :py:class:`InstAnalysis` object containing the analysis result. """ pass def getInstMemoryAccess(): """Obtain the memory accesses made by the last executed instruction. :returns: A list of memory accesses (:py:class:`MemoryAccess`) made by the instruction. """ pass def getBBMemoryAccess(): """Obtain the memory accesses made by the last executed basic block. :returns: A list of memory accesses (:py:class:`MemoryAccess`) made by the basic block. """ pass def precacheBasicBlock(pc): """Pre-cache a known basic block :param pc: Start address of a basic block :returns: True if basic block has been inserted in cache. """ pass def clearCache(start, end): """Clear a specific address range from the translation cache. :param start: Start of the address range to clear from the cache. :param end: End of the address range to clear from the cache. """ pass def clearAllCache(): """Clear the entire translation cache. """ pass def addVMEventCB(mask, cbk, data): """Register a callback event for a specific VM event. :param mask: A mask of VM event type which will trigger the callback. :param cbk: A function to be called back. :param data: User defined data passed to the callback. :returns: The id of the registered instrumentation (or :py:const:`pyqbdi.INVALID_EVENTID` in case of failure). """ pass def addInstrumentedModule(name): """Add the executable address ranges of a module to the set of instrumented address ranges. :param name: The module's name. :returns: True if at least one range was added to the instrumented ranges. """ pass def addInstrumentedModuleFromAddr(addr): """ Add the executable address ranges of a module to the set of instrumented address ranges using an address belonging to the module. :param addr: An address contained by module's range. :returns: True if at least one range was added to the instrumented ranges. """ pass def addInstrumentedRange(start, end): """Add an address range to the set of instrumented address ranges. :param start: Start address of the range (included). :param end: End address of the range (excluded). """ pass def instrumentAllExecutableMaps(): """Adds all the executable memory maps to the instrumented range set. :returns: True if at least one range was added to the instrumented ranges. """ pass def removeAllInstrumentedRanges(): """Remove all instrumented ranges. """ pass def removeInstrumentedModule(name): """Remove the executable address ranges of a module from the set of instrumented address ranges. :param name: The module's name. :returns: True if at least one range was removed from the instrumented ranges. """ pass def removeInstrumentedModuleFromAddr(addr): """Remove the executable address ranges of a module from the set of instrumented address ranges using an address belonging to the module. :param addr: An address contained by module's range. :returns: True if at least one range was removed from the instrumented ranges. """ pass def removeInstrumentedRange(start, end): """Remove an address range from the set of instrumented address ranges. :param start: Start address of the range (included). :param end: End address of the range (excluded). """ pass # PyQBDI module functions def alignedAlloc(size, align): """Allocate a block of memory of a specified sized with an aligned base address. :param size: Allocation size in bytes. :param align: Base address alignement in bytes. :returns: Pointer to the allocated memory (as a long) or NULL in case an error was encountered. """ pass def alignedFree(): """ """ pass def allocateVirtualStack(ctx, stackSize): """Allocate a new stack and setup the GPRState accordingly. The allocated stack needs to be freed with alignedFree(). :param ctx: GPRState which will be setup to use the new stack. :param stackSize: Size of the stack to be allocated. :returns: A tuple (bool, stack) where 'bool' is true if stack allocation was successfull. And 'stack' the newly allocated stack pointer. """ pass def simulateCall(ctx, returnAddress, args): """Simulate a call by modifying the stack and registers accordingly. :param ctx: GPRState where the simulated call will be setup. The state needs to point to a valid stack for example setup with allocateVirtualStack(). :param returnAddress: Return address of the call to simulate. :param args: A list of arguments. """ pass def getModuleNames(): """ Get a list of all the module names loaded in the process memory. :returns: A list of strings, each one containing the name of a loaded module. """ pass def getCurrentProcessMaps(): """ Get a list of all the memory maps (regions) of the current process. :returns: A list of :py:class:`MemoryMap` object. """ pass def readMemory(address, size): """Read a memory content from a base address. :param address: Base address :param size: Read size :returns: Bytes of content. .. warning:: This API is hazardous as the whole process memory can be read. """ pass def writeMemory(address, bytes): """Write a memory content to a base address. :param address: Base address :param bytes: Memory content .. warning:: This API is hazardous as the whole process memory can be written. """ pass def decodeFloat(val): """ Decode a float stored as a long. :param val: Long value. """ pass def encodeFloat(val): """Encode a float as a long. :param val: Float value """ pass # Various objects class MemoryMap: """ Map of a memory area (region). """ range = (0, 0xffff) """ A range of memory (region), delimited between a start and an (excluded) end address. """ permission = 0 """ Region access rights (PF_READ, PF_WRITE, PF_EXEC). """ name = "" """ Region name (useful when a region is mapping a module). """ class InstAnalysis: """ Object containing analysis results of an instruction provided by the VM. """ mnemonic = "" """ LLVM mnemonic (warning: None if !ANALYSIS_INSTRUCTION) """ address = 0 """ Instruction address """ instSize = 0 """ Instruction size (in bytes) """ affectControlFlow = False """ true if instruction affects control flow """ isBranch = False """ true if instruction acts like a 'jump' """ isCall = False """ true if instruction acts like a 'call' """ isReturn = False """ true if instruction acts like a 'return' """ isCompare = False """ true if instruction is a comparison """ isPredicable = False """ true if instruction contains a predicate (~is conditional) """ mayLoad = False """ true if instruction 'may' load data from memory """ mayStore = False """ true if instruction 'may' store data to memory """ disassembly = "" """ Instruction disassembly (warning: None if !ANALYSIS_DISASSEMBLY) """ numOperands = 0 """ Number of operands used by the instruction """ operands = [] """ A list of :py:class:`OperandAnalysis` objects. (warning: empty if !ANALYSIS_OPERANDS) """ symbol = "" """ Instruction symbol (warning: None if !ANALYSIS_SYMBOL or not found) """ symbolOffset = 0 """ Instruction symbol offset """ module = "" """ Instruction module name (warning: None if !ANALYSIS_SYMBOL or not found) """ class OperandAnalysis: """ Object containing analysis results of an operand provided by the VM. """ # Common fields type = 0 """ Operand type (pyqbdi.OPERAND_IMM, pyqbdi.OPERAND_REG, pyqbdi.OPERAND_PRED) """ value = 0 """ Operand value (if immediate), or register Id """ size = 0 """ Operand size (in bytes) """ # Register specific fields regOff = 0 """ Sub-register offset in register (in bits) """ regCtxIdx = 0 """ Register index in VM state """ regName = "" """ Register name """ regAccess = 0 """ Register access type (pyqbdi.REGISTER_READ, pyqbdi.REGISTER_WRITE, pyqbdi.REGISTER_READ_WRITE) """ class VMState: """ Object describing the current VM state. """ event = 0 """ The event(s) which triggered the callback (must be checked using a mask: event & pyqbdi.BASIC_BLOCK_ENTRY). """ basicBlockStart = 0 """ The current basic block start address which can also be the execution transfer destination. """ basicBlockEnd = 0 """ The current basic block end address which can also be the execution transfer destination. """ sequenceStart = 0 """ The current sequence start address which can also be the execution transfer destination. """ sequenceEnd = 0 """ The current sequence end address which can also be the execution transfer destination. """ class MemoryAccess: """ Describe a memory access """ instAddress = 0 """ Address of instruction making the access. """ accessAddress = 0 """ Address of accessed memory. """ value = 0 """ Value read from / written to memory. """ size = 0 """ Size of memory access (in bytes). """ type = 0 """ Memory access type (pyqbdi.MEMORY_READ, pyqbdi.MEMORY_WRITE, pyqbdi.MEMORY_READ_WRITE). """ GPRState = None """ GPRState object, a binding to :cpp:type:`QBDI::GPRState` """ FPRState = None """ FPRState object, a binding to :cpp:type:`QBDI::FPRState` """

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e13042781e2e380894da0aab1c6ec72861b3ce01

227

py

Python

krkbipscraper/settings.py

pawmar/krkbipscraper

f2629bede33930cf91378caa7f2ee5d683cf1616

[ "BSD-3-Clause" ]

null

krkbipscraper/settings.py

pawmar/krkbipscraper

f2629bede33930cf91378caa7f2ee5d683cf1616

[ "BSD-3-Clause" ]

null

krkbipscraper/settings.py

pawmar/krkbipscraper

f2629bede33930cf91378caa7f2ee5d683cf1616

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """Scrapy settings.""" BOT_NAME = 'krkbipscraper' SPIDER_MODULES = ['krkbipscraper.spiders'] NEWSPIDER_MODULE = 'krkbipscraper.spiders' ITEM_PIPELINES = ['krkbipscraper.pipelines.JsonWriterPipeline']

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e13fba4b45b4ccda568c26a9f752c38c0cf1cb17

97

py

Python

venv/lib/python3.8/site-packages/pip/_internal/network/__init__.py

realxwx/leetcode-solve

3a7d7d8e92a5fd5fecc347d141a1c532b92e763e

[ "Apache-2.0" ]

null

venv/lib/python3.8/site-packages/pip/_internal/network/__init__.py

realxwx/leetcode-solve

3a7d7d8e92a5fd5fecc347d141a1c532b92e763e

[ "Apache-2.0" ]

null

venv/lib/python3.8/site-packages/pip/_internal/network/__init__.py

realxwx/leetcode-solve

3a7d7d8e92a5fd5fecc347d141a1c532b92e763e

[ "Apache-2.0" ]

null

16.166667

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e13fc219ca69c0c1e1bed3ebfc6ec504fbe94731

1,153

py

Python

server/global_config.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

1

2021-04-03T05:11:29.000Z

server/global_config.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

null

server/global_config.py

CLG0125/elemesdk

344466398bad7cf026e082e47c77d3ca98621ef3

[ "MIT" ]

null

class Global: sand_box = True app_key = None # your secret secret = None callback_url = None server_url = None log = None def __init__(self, config): Global.sand_box = config.get_env() Global.app_key = config.get_app_key() Global.secret = config.get_secret() Global.callback_url = config.get_callback_url() Global.log = config.get_log() @staticmethod def get_env(): return Global.sand_box @staticmethod def get_app_key(): return Global.app_key @staticmethod def get_secret(): return Global.secret @staticmethod def get_callback_url(): return Global.callback_url @staticmethod def get_log(): return Global.log @staticmethod def get_server_url(): return Global.server_url @staticmethod def get_access_token_url(): return Global.get_server_url() + "/token" @staticmethod def get_api_server_url(): return Global.get_server_url() + "/api/v1/" @staticmethod def get_authorize_url(): return Global.get_server_url() + "/authorize"

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e15f893232695e92454619ed0274fe5e5ba282b5

101

py

Python

src/myapp/admin.py

anmquangw/viu-upload-file

bfbff413cc92e454226fced5fe504b7cebc6c102

[ "MIT" ]

null

src/myapp/admin.py

anmquangw/viu-upload-file

bfbff413cc92e454226fced5fe504b7cebc6c102

[ "MIT" ]

2

2020-06-21T01:47:59.000Z

2020-06-27T12:39:24.000Z

src/myapp/admin.py

sonnhfit/DocShare

50d9b8c333144780385f970197519ddda61bd502

[ "MIT" ]

null

"""from django.contrib import admin from .models import DemoModel admin.site.register(DemoModel)"""

20.2

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null

0

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4

e163903fd0678839e9ef90435028e77dc1cbf097

103

py

Python

src/moredataframes/mdf_core.py

GlorifiedStatistics/MoreDataframes

147d5b8104d1cbd1cf2836220f43fb6c8ca099b7

[ "MIT" ]

null

src/moredataframes/mdf_core.py

GlorifiedStatistics/MoreDataframes

147d5b8104d1cbd1cf2836220f43fb6c8ca099b7

[ "MIT" ]

null

src/moredataframes/mdf_core.py

GlorifiedStatistics/MoreDataframes

147d5b8104d1cbd1cf2836220f43fb6c8ca099b7

[ "MIT" ]

null

""" A collection of useful functions for manipulating/encoding pandas dataframes for data science. """

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null

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e16c926aa6450fc30f72e50b4463f6a0fcd7d9ad

276

py

Python

venv/Lib/site-packages/numpy/typing/tests/data/fail/lib_utils.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

11

2020-06-28T04:30:26.000Z

2022-03-26T08:40:47.000Z

venv/Lib/site-packages/numpy/typing/tests/data/fail/lib_utils.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

150

2019-09-30T11:22:36.000Z

2021-08-02T06:19:29.000Z

venv/Lib/site-packages/numpy/typing/tests/data/fail/lib_utils.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

20

2021-11-07T13:55:56.000Z

2021-12-02T10:54:01.000Z

import numpy as np np.deprecate(1) # E: No overload variant np.deprecate_with_doc(1) # E: incompatible type np.byte_bounds(1) # E: incompatible type np.who(1) # E: incompatible type np.lookfor(None) # E: incompatible type np.safe_eval(None) # E: incompatible type

19.714286

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null

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1

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e1a1374935fa7cc8ec68a7212a8ba5b8c016fac8

2,107

py

Python

pyob/mixins/pyob_set_label.py

khunspoonzi/pyob

b1b134b708585add15d04fa75001f3364f31dd74

[ "MIT" ]

null

pyob/mixins/pyob_set_label.py

khunspoonzi/pyob

b1b134b708585add15d04fa75001f3364f31dd74

[ "MIT" ]

null

pyob/mixins/pyob_set_label.py

khunspoonzi/pyob

b1b134b708585add15d04fa75001f3364f31dd74

[ "MIT" ]

null

# ┌───────────────────────────────────────────────────────────────────────────────────── # │ PYOB SET LABEL MIXIN # └───────────────────────────────────────────────────────────────────────────────────── class PyObSetLabelMixin: """A mixin class for PyOb set label methods""" # ┌───────────────────────────────────────────────────────────────────────────────── # │ LABEL SINGULAR # └───────────────────────────────────────────────────────────────────────────────── @property def label_singular(self): """Returns a singular label for the PyOb set""" # Determine if PyOb set is mixed is_mixed = self.count() > 1 and self._PyObClass is None # Get PyOb label ob_label = "Mixed" if is_mixed else self.ob_label_singular # Return singular label return self.__class__.__name__.replace("Ob", ob_label + " ") # ┌───────────────────────────────────────────────────────────────────────────────── # │ LABEL PLURAL # └───────────────────────────────────────────────────────────────────────────────── @property def label_plural(self): """Returns a plural label for the PyOb set""" # Return plural label return self.label_singular + "s" # ┌───────────────────────────────────────────────────────────────────────────────── # │ OB LABEL SINGULAR # └───────────────────────────────────────────────────────────────────────────────── @property def ob_label_singular(self): """Returns a singular label based on related PyOb if any""" # Return singular label return (self._PyObClass and self._PyObClass.label_singular) or "Ob" # ┌───────────────────────────────────────────────────────────────────────────────── # │ OB LABEL PLURAL # └───────────────────────────────────────────────────────────────────────────────── @property def ob_label_plural(self): """Returns a plural label based on related object if any""" # Return plural label return (self._PyObClass and self._PyObClass.label_plural) or "Obs"

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1

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e1b1b1bf75362e9f77713c3b8bcaddbf1477de81

55

py

Python

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

import matplotlib.pyplot as plt plt.plot() plt.show()

11

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true

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null

0

1

0

1

0

4

e1b37b3b7be2be9f06bdec60a631822373a8b7f7

185

py

Python

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

null

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

4

2020-06-05T19:20:59.000Z

2021-09-08T00:32:49.000Z

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

null

from django import forms from .models import Project class ProjectForm(forms.ModelForm): class Meta: model = Project exclude = ['profile', 'posted_time', 'user']

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4

e1ba723285119341020fa35acb08aec8be4bb131

200

py

Python

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

4

2016-09-28T16:00:05.000Z

2018-08-16T16:14:10.000Z

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

229

2016-03-28T19:41:00.000Z

2022-03-16T15:02:15.000Z

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

18

2016-03-10T16:11:57.000Z

2021-06-01T10:01:49.000Z

"""Resolwe SDK for Python.""" from .collection_tables import CollectionTables # noqa from .resdk_logger import log_to_stdout, start_logging # noqa from .resolwe import Resolwe, ResolweQuery # noqa

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true

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4

bed0237d9ebc522d5a4384033d2b57c729cc7ede

39

py

Python

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

20

2016-05-03T13:29:09.000Z

2021-10-06T20:41:36.000Z

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

1

2018-04-21T15:32:07.000Z

2020-05-19T00:28:52.000Z

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

5

2015-04-21T00:27:49.000Z

2019-02-23T20:46:33.000Z

from itm import ITM __all__ = ['ITM']

9.75

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1

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null

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bef16a350cb321f3059e524b8af8bbcaac507956

123

py

Python

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

26

2015-04-14T18:24:54.000Z

2022-03-07T13:01:34.000Z

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

23

2015-06-23T02:40:39.000Z

2022-02-08T05:07:42.000Z

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

25

2015-02-04T16:16:05.000Z

2021-09-28T10:53:00.000Z

from django.apps import AppConfig class EmailLogConfig(AppConfig): name = 'email_log' verbose_name = "Email log"

17.571429

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null

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bef32dc0efa2656e8a84216ea747c7b952e1b452

43

py

Python

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

1

2018-12-16T01:16:22.000Z

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

null

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

null

__version__ = "0.3.9" __author__ = "C. W."

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null

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1

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1

0

null

0

4

bef57e6edf7a67698588bda9e271df4b1e689682

131

py

Python

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

3

2019-11-02T05:37:06.000Z

2020-01-13T02:26:07.000Z

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

null

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

1

2021-12-20T07:32:25.000Z

# flake8: noqa from .base import BaseExperiment from .config import ConfigExperiment from .supervised import SupervisedExperiment

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bef6dbd81f470e4f916903c6f30ebc2cb970bd0a

310

py

Python

url_shortener_client/exceptions/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

url_shortener_client/exceptions/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

url_shortener_client/exceptions/__init__.py

Andrelpoj/hire.me

79428e2094a6b56e762a7f958e1b75f395f59cef

[ "Apache-2.0" ]

null

class AliasNotFound(Exception): def __init__(self, alias): self.alias = alias class AliasAlreadyExists(Exception): def __init__(self, alias): self.alias = alias class UnexpectedServerResponse(Exception): def __init__(self, response): self.response = response

25.833333

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11

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1

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8316bb71d181ce8ce3eff4b2a0a627c1843d8260

485

py

Python

syndata/__init__.py

Menelau/synthetic_datasets

86fd99042cff6a8bbdfa195fe6eee938a9c9d8f5

[ "MIT" ]

6

2018-02-07T02:02:00.000Z

2020-01-22T10:33:01.000Z

syndata/__init__.py

Menelau/synthetic_datasets

86fd99042cff6a8bbdfa195fe6eee938a9c9d8f5

[ "MIT" ]

null

syndata/__init__.py

Menelau/synthetic_datasets

86fd99042cff6a8bbdfa195fe6eee938a9c9d8f5

[ "MIT" ]

null

# coding=utf-8 # Author: Rafael Menelau Oliveira e Cruz <rafaelmenelau@gmail.com> # # License: MIT """ The :mod:`deslib.util` This module includes various utilities. They are divided into three parts: syndata.synthethic_datasets - Provide functions to generate several 2D classification datasets. syndata.plot_tools - Provides some routines to easily plot datasets and decision borders of a scikit-learn classifier. """ from .plot_tools import * from .synthetic_datasets import *

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83404f40a03d9276b97c34aee6e5fb4ad81499f8

101

py

Python

gen_newsletter.py

pnijjar/google-calendar-rss

6f4e6b9acbeffcf74112e6b33d99eaf1ea912be4

[ "Apache-2.0" ]

1

2021-06-29T04:10:48.000Z

gen_newsletter.py

pnijjar/google-calendar-rss

6f4e6b9acbeffcf74112e6b33d99eaf1ea912be4

[ "Apache-2.0" ]

1

2021-06-29T05:03:36.000Z

gen_newsletter.py

pnijjar/google-calendar-rss

6f4e6b9acbeffcf74112e6b33d99eaf1ea912be4

[ "Apache-2.0" ]

2

2019-08-07T15:33:25.000Z

2021-06-29T04:37:21.000Z

#!/usr/bin/env python3 from gcal_helpers import helpers helpers.write_transformation("newsletter")

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55d7d78c6937d21c0eddc062cc73761c958ba202

1,175

py

Python

python/setup.py

chrisdembia/StateMint

53fdaabc7ba83fb477523ae9b79ccc964e791080

[ "BSD-3-Clause" ]

null

python/setup.py

chrisdembia/StateMint

53fdaabc7ba83fb477523ae9b79ccc964e791080

[ "BSD-3-Clause" ]

null

python/setup.py

chrisdembia/StateMint

53fdaabc7ba83fb477523ae9b79ccc964e791080

[ "BSD-3-Clause" ]

null

import setuptools with open('README.md') as f: long_description=f.read() setuptools.setup( name="StateMint", version="1.0.0", author="Cameron Devine", author_email="camdev@uw.edu", description="A library for finding State Space models of dynamical systems.", long_description=long_description, long_description_content_type='text/markdown', url="https://github.com/CameronDevine/StateMint", packages=setuptools.find_packages(), python_requires=">=2.7", install_requires=("sympy>=0.7.3",), classifiers=( "Development Status :: 4 - Beta", "Framework :: Jupyter", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.0", "Programming Language :: Python :: 3.1", "Programming Language :: Python :: 3.2", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Operating System :: OS Independent", ), )

31.756757

78

0.691064

140

1,175

5.728571

0.542857

0.236908

0.311721

0.259352

0.067332

0

0.026839

0.14383

1,175

36

79

32.638889

0.770378

0

0.628936

0

1

0

false

0

0.029412

0

0.029412

0

null

1

0

1

0

null

0

4

360246393544aa24389fdcd4c6b8786fa1b242b5

232

py

Python

src/CodeLearn/plaintextCode/BloomTech/BTU5W1/U5W1P2_Task3_w1.py

MingjunGeng/Code-Knowledge

5b376f6b3ff9e7fa0ab41c7b57e3a80313fa0daa

[ "MIT" ]

null

src/CodeLearn/plaintextCode/BloomTech/BTU5W1/U5W1P2_Task3_w1.py

MingjunGeng/Code-Knowledge

5b376f6b3ff9e7fa0ab41c7b57e3a80313fa0daa

[ "MIT" ]

null

src/CodeLearn/plaintextCode/BloomTech/BTU5W1/U5W1P2_Task3_w1.py

MingjunGeng/Code-Knowledge

5b376f6b3ff9e7fa0ab41c7b57e3a80313fa0daa

[ "MIT" ]

1

2022-03-18T04:52:10.000Z

#!/usr/bin/python3 # --- 001 > U5W2P1_Task3_w1 def solution(i): return float(i) if __name__ == "__main__": print('----------start------------') i = 12 print(solution( i )) print('------------end------------')

19.333333

40

0.465517

25

232

3.92

0.76

0.183673

0

0.058824

0.193966

232

11

41

21.090909

0.465241

0.185345

0

0.331551

0.28877

0

1

0.142857

false

0

0.142857

0.285714

0.428571

1

0

null

0

1

0

null

0

1

0

1

0

4

36087ed60369c020bd543832aa6b41bed88a5c17

100

py

Python

easyfl/test.py

weimingwill/easyfl-pypi

f9135ab14f8d486d4a1065fa62ade43fa14490a5

[ "MIT" ]

2

2021-11-08T12:24:06.000Z

2021-11-08T12:24:33.000Z

easyfl/test.py

weimingwill/easyfl-pypi

f9135ab14f8d486d4a1065fa62ade43fa14490a5

[ "MIT" ]

null

easyfl/test.py

weimingwill/easyfl-pypi

f9135ab14f8d486d4a1065fa62ade43fa14490a5

[ "MIT" ]

null

class Test: def __init__(self): pass def hi(self): print("hello world")

16.666667

28

0.52

12

100

4

0.833333

0

0.37

100

6

28

16.666667

0.761905

0

0.108911

0

1

0.4

false

0.2

0

0.6

0.2

1

0

null

0

1

0

null

0

1

0

1

0

4

3610620368663e7a20b5544000c84c6865a97120

88

py

Python

sum of digits using recursion.py

kingRovo/PythonCodingChalenge

b62938592df10ccafec9930b69c14c778e19ad37

[ "bzip2-1.0.6" ]

1

2021-08-02T16:52:55.000Z

sum of digits using recursion.py

kingRovo/PythonCodingChalenge

b62938592df10ccafec9930b69c14c778e19ad37

[ "bzip2-1.0.6" ]

null

sum of digits using recursion.py

kingRovo/PythonCodingChalenge

b62938592df10ccafec9930b69c14c778e19ad37

[ "bzip2-1.0.6" ]

null

def rec_sum(n): if(n<=1): return n else: return(n+rec_sum(n-1))

14.666667

30

0.477273

16

88

2.5

0.5

0.3

0.35

0

0.035088

0.352273

88

5

31

17.6

0.666667

0

1

0.2

false

0

0.4

0

1

0

null

1

0

1

0

null

0

4

36134c0670c8fbaeb545400c9c8d63641cf7bd8e

248

py

Python

accounts/management/commands/run-stats.py

ChristianJStarr/Scratch-Bowling-Series-Website

283c7b1b38ffce660464889de3f4dc8050b4008c

[ "MIT" ]

1

2021-05-19T19:30:40.000Z

accounts/management/commands/run-stats.py

ChristianJStarr/Scratch-Bowling-Series-Website

283c7b1b38ffce660464889de3f4dc8050b4008c

[ "MIT" ]

null

accounts/management/commands/run-stats.py

ChristianJStarr/Scratch-Bowling-Series-Website

283c7b1b38ffce660464889de3f4dc8050b4008c

[ "MIT" ]

null

from django.core.management.base import BaseCommand, CommandError from scoreboard.ranking import calculate_statistics class Command(BaseCommand): help = 'Run Statistics' def handle(self, *args, **options): calculate_statistics()

24.8

65

0.758065

27

248

6.888889

0.777778

0.204301

0

0.157258

248

10

66

24.8

0.889952

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0.056225

0

1

0.166667

false

0

0.333333

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0.833333

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1

0

null

1

0

null

0

1

0

1

0

4

36360d07dd0f1e6bcc68b6986125359b768850eb

885

py

Python

VersionMonitorDeamonForPy/deamon/ZTest.py

xblia/Upgrade-service-for-java-application

6118cb270daba5d6511f41a2b3f0784c5a444c17

[ "Apache-2.0" ]

null

VersionMonitorDeamonForPy/deamon/ZTest.py

xblia/Upgrade-service-for-java-application

6118cb270daba5d6511f41a2b3f0784c5a444c17

[ "Apache-2.0" ]

null

VersionMonitorDeamonForPy/deamon/ZTest.py

xblia/Upgrade-service-for-java-application

6118cb270daba5d6511f41a2b3f0784c5a444c17

[ "Apache-2.0" ]

null

#coding=utf-8 '''/* * Copyright 2015 lixiaobo * * VersionUpgrade project licenses this file to you under the Apache License, * version 2.0 (the "License"); you may not use this file except in compliance * with the License. You may obtain a copy of the License at: * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the * License for the specific language governing permissions and limitations * under the License. */''' ''' Created on 2015年12月30日 @author: xiaobolx ''' import os if __name__ == '__main__': os.rename(r"D:\eclipse_workspace\VersionMonitorDeamonForPy\build\aaa", r"D:\eclipse_workspace\VersionMonitorDeamonForPy\build\exe.win32xxxx")

34.038462

145

0.748023

125

885

5.216

0.68

0.092025

0.039877

0.04908

0.147239

0

0.025503

0.158192

885

26

145

34.038462

0.849664

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0

0.691489

0.648936

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1

0

true

0

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0

null

0

1

null

0

1

0

1

0

4

3662bd8e72712ef2032fb1273a5b29f2780ed323

144

py

Python

users.py

VinasRibeiro/DownStoriesInsta

56c8dc402b50a07db2b207c683e39e045fda83e1

[ "MIT" ]

null

users.py

VinasRibeiro/DownStoriesInsta

56c8dc402b50a07db2b207c683e39e045fda83e1

[ "MIT" ]

null

users.py

VinasRibeiro/DownStoriesInsta

56c8dc402b50a07db2b207c683e39e045fda83e1

[ "MIT" ]

null

class Users: usernamep = 'your_user_email' passwordp = 'your_password' linkp = 'https://www.instagram.com/stories/cznburak/'

18

57

0.666667

16

144

5.8125

0.9375

0

0.208333

144

7

58

20.571429

0.815789

0

0.496504

0

1

0

false

0.25

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

366b6bc762ff4618c8e2b630d09921664231bc91

53

py

Python

3_team/tests/unittest_sample_ng/sample.py

pyfirst/pymook-samplecode

82321237c34515d287f28bd51ea86f870c1f5514

[ "MIT" ]

31

2017-09-27T14:54:39.000Z

2021-05-26T14:03:44.000Z

3_team/tests/unittest_sample_ng/sample.py

pyfirst/pymook-samplecode

82321237c34515d287f28bd51ea86f870c1f5514

[ "MIT" ]

11

2018-03-11T05:28:14.000Z

2022-03-11T23:19:36.000Z

3_team/tests/unittest_sample_ng/sample.py

pyfirst/pymook-samplecode

82321237c34515d287f28bd51ea86f870c1f5514

[ "MIT" ]

41

2017-10-21T04:45:56.000Z

2021-07-16T14:12:33.000Z

def add(m, n): """mとnを加算して返す""" return m - n

13.25

20

0.490566

8

53

3.25

0.75

0.153846

0

0.301887

53

3

21

17.666667

0.702703

0.188679

0

1

0.5

false

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

369370477fede6ca05479665d356d7b8ddbbef42

211

py

Python

src/settings/settings.py

lamas1901/telegram__pdf-bot

995bd3a41edba744efc07a99296ff109427ed310

[ "MIT" ]

null

src/settings/settings.py

lamas1901/telegram__pdf-bot

995bd3a41edba744efc07a99296ff109427ed310

[ "MIT" ]

null

src/settings/settings.py

lamas1901/telegram__pdf-bot

995bd3a41edba744efc07a99296ff109427ed310

[ "MIT" ]

null

from ..utils import get_env_var from pathlib import Path BASE_DIR = Path(__file__).parent.parent TG_TOKEN = get_env_var('TG_TOKEN') YMONEY_TOKEN = get_env_var('YTOKEN') PROMO_CODE = get_env_var('PROMO_CODE')

21.1

39

0.78673

36

211

4.111111

0.5

0.162162

0.243243

0.189189

0

0.109005

211

9

40

23.444444

0.787234

0

0.113744

0

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false

0

0.333333

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0.333333

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null

0

1

0

1

0

null

0

1

0

4

36b8bfd65b80b877d57938c5b868d8f66abde496

65

py

Python

ml/av/io/__init__.py

necla-ml/ml

7ebd29382326e3958297607da7182c211865e7ff

[ "BSD-3-Clause" ]

1

2022-02-21T21:06:29.000Z

ml/av/io/__init__.py

necla-ml/ml

7ebd29382326e3958297607da7182c211865e7ff

[ "BSD-3-Clause" ]

null

ml/av/io/__init__.py

necla-ml/ml

7ebd29382326e3958297607da7182c211865e7ff

[ "BSD-3-Clause" ]

null

"""APIs from ml.vision.io and ml.audio.io """ from .api import *

16.25

41

0.661538

12

65

3.583333

0.75

0

0.153846

65

4

42

16.25

0.781818

0.584615

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

7fcd0efe44d52a8f5eb0ccaff5033e799faefab2

503

py

Python

json-read.py

ccoffrin/py-json-examples

c01bf6994e4480470939621ed0b4b7043b38819f

[ "MIT" ]

null

json-read.py

ccoffrin/py-json-examples

c01bf6994e4480470939621ed0b4b7043b38819f

[ "MIT" ]

null

json-read.py

ccoffrin/py-json-examples

c01bf6994e4480470939621ed0b4b7043b38819f

[ "MIT" ]

null

#!/usr/bin/env python3 import json data_json = {} with open('data/json_00.json', 'r') as file: data_json = json.load(file) print(data_json) print(data_json[0]) print(data_json[1]) print(data_json[2]) print(data_json[3]) print(data_json[4]) print(data_json[5]) print(data_json[6]) print(data_json[5][0]) print(data_json[5][1]) print(data_json[5][2]) print(data_json[5][3]) print(data_json[6]) print(data_json[6]["A"]) print(data_json[6]["B"]) print(data_json[6]["C"]) print(data_json[6]["D"])

16.766667

44

0.691849

97

503

3.381443

0.268041

0.487805

0.67378

0.256098

0.164634

0

0.05

0.085487

503

29

45

17.344828

0.663043

0.04175

0

0.095238

0

0.045738

0

1

0

false

0

0.047619

0

0.047619

0.809524

0

null

1

0

null

0

1

0

4

7fda7ecbf9da0226a54341ecb40e210f62c31957

1,951

py

Python

proj/python/Test/dictStock.py

jumib/BlackTensor

d66a4fb5289dbe86104900072284e4a881f55645

[ "MIT" ]

null

proj/python/Test/dictStock.py

jumib/BlackTensor

d66a4fb5289dbe86104900072284e4a881f55645

[ "MIT" ]

null

proj/python/Test/dictStock.py

jumib/BlackTensor

d66a4fb5289dbe86104900072284e4a881f55645

[ "MIT" ]

null

import requests # host = 'localhost:8080' # path = '/member/changeAppId' # payload = {'UserId' : userId } # r = requests.get('localhost:8080/member/changeAppId', params=payload) # import requests # import json # # # GET # res = requests.get('http://localhost:8080/member/changeAppId') # print(str(res.status_code) + " | " + res.text) # # # POST (JSON) # headers = {'Content-Type': 'application/json; chearset=utf-8'} # payload = {'UserId' : 'userId' } # res = requests.post('http://localhost:8080/member/changeAppId', payload=json.dumps(payload), headers=headers) # print(str(res.status_code) + " | " + res.text) # # class DictStock: # @app.route('/history/buy') # def PythonServerResponse(self, itemName, m_date, openPrice, highPrice, lowPrice, currentPrice, volumn, tradingValue): # print("It's operate") # # self.myViewController = vc.ViewController() # json_object = { # "name": itemName, # "일자": m_date, # "시가": openPrice, # "고가": highPrice, # "저가": lowPrice, # "현재가": currentPrice, # "거래량": volumn, # "거래대금": tradingValue # } # json_string = json.dumps(json_object) # print(json_string) # # return jsonify(json_object) # # app.run() # # # data = { # # # # 'itemName' : itemName, # # # 'date' : m_date, # # # 'openPrice' : openPrice # # # } # # # json_data = json.dumps(data) # # # print(json_data) # # # # # # # import json # # # # # # json_object = { # # # "id": 1, # # # "username": "Bret", # # # "email": "Sincere@april.biz", # # # "address": { # # # "street": "Kulas Light", # # # "suite": "Apt. 556", # # # "city": "Gwenborough", # # # "zipcode": "92998-3874" # # # }, # # # "admin": False, # # # "hobbies": None # # # } # # # # # # json_string = json.dumps(json_object) # # # print(json_string)

26.364865

123

0.538186

187

1,951

5.529412

0.491979

0.048356

0.055126

0.087041

0.205029

0.139265

0.085106

0

0.020935

0.265505

1,951

73

124

26.726027

0.700628

0.892363

0

1

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true

0

1

0

1

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null

0

1

0

null

0

1

0

1

0

1

0

4

7ff1b8e6fdd883cf61f529bf469c18df4b7174fc

166

py

Python

django_gotolong/bhav/apps.py

ParikhKadam/gotolong

839beb8aa37055a2078eaa289b8ae05b62e8905e

[ "BSD-2-Clause", "BSD-3-Clause" ]

15

2019-12-06T16:19:45.000Z

2021-08-20T13:22:22.000Z

django_gotolong/bhav/apps.py

ParikhKadam/gotolong

839beb8aa37055a2078eaa289b8ae05b62e8905e

[ "BSD-2-Clause", "BSD-3-Clause" ]

14

2020-12-08T10:45:05.000Z

2021-09-21T17:23:45.000Z

django_gotolong/bhav/apps.py

ParikhKadam/gotolong

839beb8aa37055a2078eaa289b8ae05b62e8905e

[ "BSD-2-Clause", "BSD-3-Clause" ]

9

2020-01-01T03:04:29.000Z

2021-04-18T08:42:30.000Z

from django.apps import AppConfig from django_gotolong.bhav.views import start class BhavConfig(AppConfig): name = 'bhav' def ready(self): start()

16.6

44

0.704819

21

166

5.52381

0.714286

0.172414

0

0.210843

166

9

45

18.444444

0.885496

0

0.024096

0

1

0.166667

false

0

0.333333

0

0.833333

0

1

0

null

0

1

0

null

0

1

0

1

0

4

7ff4886052822174f0f2c10e163f3567d0699ee7

133

py

Python

geotweet/tests/integration/twitter/__init__.py

meyersj/geotweet

1a6b55f98adf34d1b91f172d9187d599616412d9

[ "MIT" ]

6

2016-03-26T19:29:25.000Z

2020-07-12T02:18:22.000Z

geotweet/tests/integration/twitter/__init__.py

meyersj/geotweet

1a6b55f98adf34d1b91f172d9187d599616412d9

[ "MIT" ]

null

geotweet/tests/integration/twitter/__init__.py

meyersj/geotweet

1a6b55f98adf34d1b91f172d9187d599616412d9

[ "MIT" ]

1

2020-01-06T01:25:05.000Z

import os from os.path import dirname import sys ROOT = dirname(dirname(dirname(os.path.abspath(__file__)))) sys.path.append(ROOT)

16.625

59

0.774436

21

133

4.714286

0.47619

0.121212

0

0.105263

133

7

60

19

0.831933

0

1

0

false

0

0.6

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

4

7ffeda80306a79591e192335e97b6bc94abc7f4b

160

py

Python

DublinBusTest/forms.py

Eimg851/DublinBusApp_ResearchPracticum

41b2c559dc4608705fd1348480ce729c645d6d5a

[ "BSD-2-Clause" ]

null

DublinBusTest/forms.py

Eimg851/DublinBusApp_ResearchPracticum

41b2c559dc4608705fd1348480ce729c645d6d5a

[ "BSD-2-Clause" ]

null

DublinBusTest/forms.py

Eimg851/DublinBusApp_ResearchPracticum

41b2c559dc4608705fd1348480ce729c645d6d5a

[ "BSD-2-Clause" ]

1

2020-06-20T09:53:15.000Z

from django import forms from .models import * class routeForm(forms.ModelForm): class Meta: model = Routes fields = ('route_short_name',)

20

38

0.66875

19

160

5.526316

0.789474

0

0.24375

160

7

39

22.857143

0.867769

0

0.1

0

1

0

false

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

3d1b7856aab4b6896a8bd50f1e84b7518ab5535b

21

py

Python

custom_components/ztm/__init__.py

peetereczek/ztm

1fd4870720dca16863d085759a360f1ebdd9ab1f

[ "MIT" ]

4

2020-02-23T08:08:12.000Z

2021-06-26T15:46:27.000Z

custom_components/ztm/__init__.py

peetereczek/ztm

1fd4870720dca16863d085759a360f1ebdd9ab1f

[ "MIT" ]

15

2020-01-30T09:54:58.000Z

2022-02-02T11:13:32.000Z

custom_components/ztm/__init__.py

peetereczek/ztm

1fd4870720dca16863d085759a360f1ebdd9ab1f

[ "MIT" ]

1

2022-01-17T08:51:34.000Z

""" module init """

7

12

0.47619

2

21

5

1

0

0.238095

21

3

13

7

0.625

0.52381

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

3d319597951dce7996b3f7f4aeae76d89320c801

2,716

py

Python

ROS/my_initials.py

Vishwajeetiitb/Autumn-of-Automation

bd8c78662734f867b6aa6fd9179a12913387a01c

[ "MIT" ]

null

ROS/my_initials.py

Vishwajeetiitb/Autumn-of-Automation

bd8c78662734f867b6aa6fd9179a12913387a01c

[ "MIT" ]

null

ROS/my_initials.py

Vishwajeetiitb/Autumn-of-Automation

bd8c78662734f867b6aa6fd9179a12913387a01c

[ "MIT" ]

null

#!/usr/bin/env python import rospy from geometry_msgs.msg import Twist import math import os from turtlesim.msg import Pose import time os.system("rosrun") def callback(msg): global current_angle current_angle = msg.theta # print(msg) def move(): # Starts a new node rospy.init_node('robot_cleaner', anonymous=True) velocity_publisher = rospy.Publisher('/turtle1/cmd_vel', Twist, queue_size=10) sub = rospy.Subscriber("turtle1/pose",Pose,callback) time.sleep(1) vel_msg = Twist() speed = 2 distance = 4 angle = math.pi/3 angular_ve1 = 1 vel_msg.angular.z = 0 current_distance = 0 t0 = rospy.Time.now().to_sec() # t0 = rospy.Time.now().to_sec() vel_msg.linear.x = 0 vel_msg.angular.z = angular_ve1 while current_angle < angle: velocity_publisher.publish(vel_msg) #Takes actual time to velocity calculus t1=rospy.Time.now().to_sec() print(current_angle) vel_msg.linear.x = 0 vel_msg.angular.z = 0 velocity_publisher.publish(vel_msg) t0 = rospy.Time.now().to_sec() vel_msg.linear.x = speed vel_msg.angular.z =0 while current_distance < distance: velocity_publisher.publish(vel_msg) t1=rospy.Time.now().to_sec() current_distance = speed*(t1-t0) vel_msg.linear.x = 0 vel_msg.angular.z = 0 velocity_publisher.publish(vel_msg) t0 = rospy.Time.now().to_sec() vel_msg.linear.x = -speed vel_msg.angular.z =0 current_distance = 0 while current_distance < distance: velocity_publisher.publish(vel_msg) t1=rospy.Time.now().to_sec() current_distance = speed*(t1-t0) vel_msg.linear.x = 0 vel_msg.angular.z = 0 velocity_publisher.publish(vel_msg) t0 = rospy.Time.now().to_sec() vel_msg.linear.x = 0 vel_msg.angular.z = angular_ve1 while current_angle < 2*angle: velocity_publisher.publish(vel_msg) #Takes actual time to velocity calculus t1=rospy.Time.now().to_sec() print(current_angle) vel_msg.linear.x = 0 vel_msg.angular.z = 0 velocity_publisher.publish(vel_msg) t0 = rospy.Time.now().to_sec() vel_msg.linear.x = speed vel_msg.angular.z =0 current_distance = 0 while current_distance < distance: velocity_publisher.publish(vel_msg) t1=rospy.Time.now().to_sec() current_distance = speed*(t1-t0) vel_msg.linear.x = 0 vel_msg.angular.z = 0 velocity_publisher.publish(vel_msg) if __name__ == '__main__': try: #Testing our function move() except rospy.ROSInterruptException: pass

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0

null

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null

0

4

3d34e6acbf5b6084146e881a817272a730156e45

525

py

Python

performanceplatform/collector/ga/plugins/load_plugin.py

alphagov/performanceplatform-collector

de68ab4aa500c31e436e050fa1268fa928c522a5

[ "MIT" ]

3

2015-05-01T14:57:28.000Z

2016-04-08T12:53:59.000Z

performanceplatform/collector/ga/plugins/load_plugin.py

alphagov/performanceplatform-collector

de68ab4aa500c31e436e050fa1268fa928c522a5

[ "MIT" ]

15

2015-02-11T11:43:02.000Z

2021-03-24T10:54:35.000Z

performanceplatform/collector/ga/plugins/load_plugin.py

alphagov/performanceplatform-collector

de68ab4aa500c31e436e050fa1268fa928c522a5

[ "MIT" ]

7

2015-05-04T16:56:02.000Z

2021-04-10T19:42:35.000Z

""" load_plugin.py -------------- Responsible for taking plugin strings and returning plugin callables. """ # For the linter import __builtin__ import performanceplatform.collector.ga.plugins def load_plugins(plugin_names): return [load_plugin(plugin_name) for plugin_name in plugin_names] def load_plugin(plugin_name): expr = compile(plugin_name, "performanceplatform.collector plugin", "eval") return eval(expr, __builtin__.__dict__, performanceplatform.collector.ga.plugins.__dict__)

21

79

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525

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0.150476

525

24

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null

0

1

0

null

0

1

0

1

0

4

3d49f7eaf598f54df886dcfb77904d84e8c9f173

108

py

Python

nylas/util/__init__.py

nylas/nylas-production-python

a0979cd104a43f80750b2361aa580516b8dbfcfc

[ "Apache-2.0", "MIT" ]

19

2015-11-20T12:38:34.000Z

2022-01-13T15:40:25.000Z

nylas/api/__init__.py

nylas/nylas-production-python

a0979cd104a43f80750b2361aa580516b8dbfcfc

[ "Apache-2.0", "MIT" ]

null

nylas/api/__init__.py

nylas/nylas-production-python

a0979cd104a43f80750b2361aa580516b8dbfcfc

[ "Apache-2.0", "MIT" ]

10

2016-03-12T00:38:54.000Z

2018-12-13T05:58:13.000Z

from pkgutil import extend_path # Allow out-of-tree submodules. __path__ = extend_path(__path__, __name__)

21.6

42

0.805556

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108

4.866667

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0.273973

0

0.12037

108

4

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0

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null

1

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1

0

null

0

1

0

4

3d5394f2af4816cbcec8e499c06b15d66ed6fb8e

920

py

Python

simple_ml/__init__.py

Yangruipis/simple_ml

09657f6b017b973a5201aa611774d6ac8f0fc0a2

[ "MIT" ]

25

2018-04-17T04:38:51.000Z

2021-10-09T04:07:53.000Z

simple_ml/__init__.py

Yangruipis/simple_ml

09657f6b017b973a5201aa611774d6ac8f0fc0a2

[ "MIT" ]

null

simple_ml/__init__.py

Yangruipis/simple_ml

09657f6b017b973a5201aa611774d6ac8f0fc0a2

[ "MIT" ]

5

2018-04-17T05:27:00.000Z

2020-12-01T02:55:15.000Z

# -*- coding:utf-8 -*- """ ================================== Simple Machine Learning 一个简单的机器学习算法实现 ================================== """ from simple_ml.bayes import * from simple_ml.classify_data import * from simple_ml.auto import * from simple_ml.classify_data import * from simple_ml.ensemble import * from simple_ml.evaluation import * from simple_ml.feature_select import * from simple_ml.knn import * from simple_ml.logistic import * from simple_ml.neural_network import * from simple_ml.pca import * from simple_ml.regression import * from simple_ml.support_vector import * # from simple_ml.svm import * from simple_ml.tree import * __all__ = [ 'bayes', 'auto', 'classify_data', 'cluster', 'data_handle', 'ensemble', 'evaluation', 'feature_select', 'knn', 'svm', 'logistic', 'neural_network', 'pca', 'regression', 'support_vector', 'tree', ]

20

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109

920

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0.265957

0.319149

0.446809

0.170213

0

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0.176087

920

45

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20.444444

0.742744

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0

0.174434

0

1

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false

0

0.4375

0

0.4375

0

null

1

0

null

0

1

0

4

180d3a3f60ca987d84a73cb66042ea85d5cffea9

758

py

Python

tests/contrib/django/testapp/middleware.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

tests/contrib/django/testapp/middleware.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

tests/contrib/django/testapp/middleware.py

mvas/apm-agent-python

f4582e90eb5308b915ca51e2e98620fc22af09ec

[ "BSD-3-Clause" ]

null

try: from django.utils.deprecation import MiddlewareMixin except ImportError: # no-op class for Django < 1.10 class MiddlewareMixin(object): pass class BrokenRequestMiddleware(MiddlewareMixin): def process_request(self, request): raise ImportError('request') class BrokenResponseMiddleware(MiddlewareMixin): def process_response(self, request, response): raise ImportError('response') class BrokenViewMiddleware(MiddlewareMixin): def process_view(self, request, func, args, kwargs): raise ImportError('view') class MetricsNameOverrideMiddleware(MiddlewareMixin): def process_response(self, request, response): request._elasticapm_transaction_name = 'foobar' return response

27.071429

56

0.740106

73

758

7.589041

0.493151

0.129964

0.180505

0.119134

0.187726

0

0.004831

0.180739

758

27

57

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false

0.055556

0.277778

0

0.833333

0

null

0

1

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null

0

1

0

1

0

1

0

4

183cd22d8adcd570cdd6c5eceb4ba00ee9152282

61

py

Python

src/yookassa_payout/domain/response/__init__.py

yoomoney/yookassa-payout-sdk-python

f6953e97573bb4a4ee6f830f726a6fcfdf504e2a

[ "MIT" ]

5

2021-03-11T14:38:25.000Z

2021-08-13T10:41:50.000Z

src/yookassa_payout/domain/common/__init__.py

yoomoney/yookassa-payout-sdk-python

f6953e97573bb4a4ee6f830f726a6fcfdf504e2a

[ "MIT" ]

2

2021-02-15T18:18:34.000Z

2021-08-13T13:49:46.000Z

src/yookassa_payout/domain/request/__init__.py

yoomoney/yookassa-payout-sdk-python

f6953e97573bb4a4ee6f830f726a6fcfdf504e2a

[ "MIT" ]

1

2022-01-29T08:47:02.000Z

"""Package for YooKassa Payout API Python Client Library."""

30.5

60

0.754098

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61

1

61

0.867925

0.885246

0

null

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null

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null

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null

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null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

18412368254bcf43c33a2c706aa24bebe16b5a08

16

py

Python

roomai/games/__init__.py

tonyxxq/RoomAI

5f28e31e659dd7808127c3c3cc386e6892a93982

[ "MIT" ]

1

2018-11-29T01:57:18.000Z

roomai/models/texasholdem/__init__.py

tonyxxq/RoomAI

5f28e31e659dd7808127c3c3cc386e6892a93982

[ "MIT" ]

null

roomai/models/texasholdem/__init__.py

tonyxxq/RoomAI

5f28e31e659dd7808127c3c3cc386e6892a93982

[ "MIT" ]

null

#!/bin/python

4

13

0.5625

2

16

4.5

1

0

0.1875

16

3

14

5.333333

0.692308

0.75

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

1878e0fb7794287a25d9e67514272eb4ae4e8c3c

148

py

Python

WD/Cwiczenia/rzymskie.py

galursa/UWM

b7ab4a275662764a91af6c5bc79da0d98177d0ac

[ "MIT" ]

1

2020-02-29T14:38:33.000Z

WD/Cwiczenia/rzymskie.py

galursa/UWM

b7ab4a275662764a91af6c5bc79da0d98177d0ac

[ "MIT" ]

null

WD/Cwiczenia/rzymskie.py

galursa/UWM

b7ab4a275662764a91af6c5bc79da0d98177d0ac

[ "MIT" ]

null

rzymskie={'I':1,'II':2,'III':3,'IV':4,'V':5,'VI':6,'VII':7,'VIII':8} print(rzymskie) print('Jeden element slownika: \n') print(rzymskie['I'])

24.666667

69

0.587838

27

148

3.222222

0.814815

0.206897

0

0.059259

0.087838

148

5

70

29.6

0.585185

0

0.314685

0

1

0

false

0

0.75

1

0

null

1

0

1

0

null

0

1

0

4

43ebc0969b2793f79841f3adb90ba457341afae3

67,834

py

Python

sdk/python/pulumi_google_native/vmmigration/v1alpha1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

44

2021-04-18T23:00:48.000Z

2022-02-14T17:43:15.000Z

sdk/python/pulumi_google_native/vmmigration/v1alpha1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

354

2021-04-16T16:48:39.000Z

2022-03-31T17:16:39.000Z

sdk/python/pulumi_google_native/vmmigration/v1alpha1/outputs.py

AaronFriel/pulumi-google-native

75d1cda425e33d4610348972cd70bddf35f1770d

[ "Apache-2.0" ]

8

2021-04-24T17:46:51.000Z

2022-01-05T10:40:21.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities from . import outputs from ._enums import * __all__ = [ 'AppliedLicenseResponse', 'CloneJobResponse', 'ComputeEngineTargetDefaultsResponse', 'ComputeEngineTargetDetailsResponse', 'ComputeSchedulingResponse', 'CutoverJobResponse', 'NetworkInterfaceResponse', 'ReplicationCycleResponse', 'ReplicationSyncResponse', 'SchedulePolicyResponse', 'SchedulingNodeAffinityResponse', 'StatusResponse', 'VmUtilizationInfoResponse', 'VmUtilizationMetricsResponse', 'VmwareSourceDetailsResponse', 'VmwareVmDetailsResponse', ] @pulumi.output_type class AppliedLicenseResponse(dict): """ AppliedLicense holds the license data returned by adaptation module report. """ @staticmethod def __key_warning(key: str): suggest = None if key == "osLicense": suggest = "os_license" if suggest: pulumi.log.warn(f"Key '{key}' not found in AppliedLicenseResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: AppliedLicenseResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: AppliedLicenseResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, os_license: str, type: str): """ AppliedLicense holds the license data returned by adaptation module report. :param str os_license: The OS license returned from the adaptation module's report. :param str type: The license type that was used in OS adaptation. """ pulumi.set(__self__, "os_license", os_license) pulumi.set(__self__, "type", type) @property @pulumi.getter(name="osLicense") def os_license(self) -> str: """ The OS license returned from the adaptation module's report. """ return pulumi.get(self, "os_license") @property @pulumi.getter def type(self) -> str: """ The license type that was used in OS adaptation. """ return pulumi.get(self, "type") @pulumi.output_type class CloneJobResponse(dict): """ CloneJob describes the process of creating a clone of a MigratingVM to the requested target based on the latest successful uploaded snapshots. While the migration cycles of a MigratingVm take place, it is possible to verify the uploaded VM can be started in the cloud, by creating a clone. The clone can be created without any downtime, and it is created using the latest snapshots which are already in the cloud. The cloneJob is only responsible for its work, not its products, which means once it is finished, it will never touch the instance it created. It will only delete it in case of the CloneJob being cancelled or upon failure to clone. """ @staticmethod def __key_warning(key: str): suggest = None if key == "computeEngineTargetDetails": suggest = "compute_engine_target_details" elif key == "createTime": suggest = "create_time" elif key == "stateTime": suggest = "state_time" if suggest: pulumi.log.warn(f"Key '{key}' not found in CloneJobResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: CloneJobResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: CloneJobResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, compute_engine_target_details: 'outputs.ComputeEngineTargetDetailsResponse', create_time: str, error: 'outputs.StatusResponse', name: str, state: str, state_time: str): """ CloneJob describes the process of creating a clone of a MigratingVM to the requested target based on the latest successful uploaded snapshots. While the migration cycles of a MigratingVm take place, it is possible to verify the uploaded VM can be started in the cloud, by creating a clone. The clone can be created without any downtime, and it is created using the latest snapshots which are already in the cloud. The cloneJob is only responsible for its work, not its products, which means once it is finished, it will never touch the instance it created. It will only delete it in case of the CloneJob being cancelled or upon failure to clone. :param 'ComputeEngineTargetDetailsResponse' compute_engine_target_details: Details of the target VM in Compute Engine. :param str create_time: The time the clone job was created (as an API call, not when it was actually created in the target). :param 'StatusResponse' error: Provides details for the errors that led to the Clone Job's state. :param str name: The name of the clone. :param str state: State of the clone job. :param str state_time: The time the state was last updated. """ pulumi.set(__self__, "compute_engine_target_details", compute_engine_target_details) pulumi.set(__self__, "create_time", create_time) pulumi.set(__self__, "error", error) pulumi.set(__self__, "name", name) pulumi.set(__self__, "state", state) pulumi.set(__self__, "state_time", state_time) @property @pulumi.getter(name="computeEngineTargetDetails") def compute_engine_target_details(self) -> 'outputs.ComputeEngineTargetDetailsResponse': """ Details of the target VM in Compute Engine. """ return pulumi.get(self, "compute_engine_target_details") @property @pulumi.getter(name="createTime") def create_time(self) -> str: """ The time the clone job was created (as an API call, not when it was actually created in the target). """ return pulumi.get(self, "create_time") @property @pulumi.getter def error(self) -> 'outputs.StatusResponse': """ Provides details for the errors that led to the Clone Job's state. """ return pulumi.get(self, "error") @property @pulumi.getter def name(self) -> str: """ The name of the clone. """ return pulumi.get(self, "name") @property @pulumi.getter def state(self) -> str: """ State of the clone job. """ return pulumi.get(self, "state") @property @pulumi.getter(name="stateTime") def state_time(self) -> str: """ The time the state was last updated. """ return pulumi.get(self, "state_time") @pulumi.output_type class ComputeEngineTargetDefaultsResponse(dict): """ ComputeEngineTargetDefaults is a collection of details for creating a VM in a target Compute Engine project. """ @staticmethod def __key_warning(key: str): suggest = None if key == "additionalLicenses": suggest = "additional_licenses" elif key == "appliedLicense": suggest = "applied_license" elif key == "bootOption": suggest = "boot_option" elif key == "computeScheduling": suggest = "compute_scheduling" elif key == "diskType": suggest = "disk_type" elif key == "licenseType": suggest = "license_type" elif key == "machineType": suggest = "machine_type" elif key == "machineTypeSeries": suggest = "machine_type_series" elif key == "networkInterfaces": suggest = "network_interfaces" elif key == "networkTags": suggest = "network_tags" elif key == "secureBoot": suggest = "secure_boot" elif key == "serviceAccount": suggest = "service_account" elif key == "targetProject": suggest = "target_project" elif key == "vmName": suggest = "vm_name" if suggest: pulumi.log.warn(f"Key '{key}' not found in ComputeEngineTargetDefaultsResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: ComputeEngineTargetDefaultsResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: ComputeEngineTargetDefaultsResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, additional_licenses: Sequence[str], applied_license: 'outputs.AppliedLicenseResponse', boot_option: str, compute_scheduling: 'outputs.ComputeSchedulingResponse', disk_type: str, labels: Mapping[str, str], license_type: str, machine_type: str, machine_type_series: str, metadata: Mapping[str, str], network_interfaces: Sequence['outputs.NetworkInterfaceResponse'], network_tags: Sequence[str], secure_boot: bool, service_account: str, target_project: str, vm_name: str, zone: str): """ ComputeEngineTargetDefaults is a collection of details for creating a VM in a target Compute Engine project. :param Sequence[str] additional_licenses: Additional licenses to assign to the VM. :param 'AppliedLicenseResponse' applied_license: The OS license returned from the adaptation module report. :param str boot_option: The VM Boot Option, as set in the source vm. :param 'ComputeSchedulingResponse' compute_scheduling: Compute instance scheduling information (if empty default is used). :param str disk_type: The disk type to use in the VM. :param Mapping[str, str] labels: A map of labels to associate with the VM. :param str license_type: The license type to use in OS adaptation. :param str machine_type: The machine type to create the VM with. :param str machine_type_series: The machine type series to create the VM with. :param Mapping[str, str] metadata: The metadata key/value pairs to assign to the VM. :param Sequence['NetworkInterfaceResponse'] network_interfaces: List of NICs connected to this VM. :param Sequence[str] network_tags: A map of network tags to associate with the VM. :param bool secure_boot: Defines whether the instance has Secure Boot enabled. This can be set to true only if the vm boot option is EFI. :param str service_account: The service account to associate the VM with. :param str target_project: The full path of the resource of type TargetProject which represents the Compute Engine project in which to create this VM. :param str vm_name: The name of the VM to create. :param str zone: The zone in which to create the VM. """ pulumi.set(__self__, "additional_licenses", additional_licenses) pulumi.set(__self__, "applied_license", applied_license) pulumi.set(__self__, "boot_option", boot_option) pulumi.set(__self__, "compute_scheduling", compute_scheduling) pulumi.set(__self__, "disk_type", disk_type) pulumi.set(__self__, "labels", labels) pulumi.set(__self__, "license_type", license_type) pulumi.set(__self__, "machine_type", machine_type) pulumi.set(__self__, "machine_type_series", machine_type_series) pulumi.set(__self__, "metadata", metadata) pulumi.set(__self__, "network_interfaces", network_interfaces) pulumi.set(__self__, "network_tags", network_tags) pulumi.set(__self__, "secure_boot", secure_boot) pulumi.set(__self__, "service_account", service_account) pulumi.set(__self__, "target_project", target_project) pulumi.set(__self__, "vm_name", vm_name) pulumi.set(__self__, "zone", zone) @property @pulumi.getter(name="additionalLicenses") def additional_licenses(self) -> Sequence[str]: """ Additional licenses to assign to the VM. """ return pulumi.get(self, "additional_licenses") @property @pulumi.getter(name="appliedLicense") def applied_license(self) -> 'outputs.AppliedLicenseResponse': """ The OS license returned from the adaptation module report. """ return pulumi.get(self, "applied_license") @property @pulumi.getter(name="bootOption") def boot_option(self) -> str: """ The VM Boot Option, as set in the source vm. """ return pulumi.get(self, "boot_option") @property @pulumi.getter(name="computeScheduling") def compute_scheduling(self) -> 'outputs.ComputeSchedulingResponse': """ Compute instance scheduling information (if empty default is used). """ return pulumi.get(self, "compute_scheduling") @property @pulumi.getter(name="diskType") def disk_type(self) -> str: """ The disk type to use in the VM. """ return pulumi.get(self, "disk_type") @property @pulumi.getter def labels(self) -> Mapping[str, str]: """ A map of labels to associate with the VM. """ return pulumi.get(self, "labels") @property @pulumi.getter(name="licenseType") def license_type(self) -> str: """ The license type to use in OS adaptation. """ return pulumi.get(self, "license_type") @property @pulumi.getter(name="machineType") def machine_type(self) -> str: """ The machine type to create the VM with. """ return pulumi.get(self, "machine_type") @property @pulumi.getter(name="machineTypeSeries") def machine_type_series(self) -> str: """ The machine type series to create the VM with. """ return pulumi.get(self, "machine_type_series") @property @pulumi.getter def metadata(self) -> Mapping[str, str]: """ The metadata key/value pairs to assign to the VM. """ return pulumi.get(self, "metadata") @property @pulumi.getter(name="networkInterfaces") def network_interfaces(self) -> Sequence['outputs.NetworkInterfaceResponse']: """ List of NICs connected to this VM. """ return pulumi.get(self, "network_interfaces") @property @pulumi.getter(name="networkTags") def network_tags(self) -> Sequence[str]: """ A map of network tags to associate with the VM. """ return pulumi.get(self, "network_tags") @property @pulumi.getter(name="secureBoot") def secure_boot(self) -> bool: """ Defines whether the instance has Secure Boot enabled. This can be set to true only if the vm boot option is EFI. """ return pulumi.get(self, "secure_boot") @property @pulumi.getter(name="serviceAccount") def service_account(self) -> str: """ The service account to associate the VM with. """ return pulumi.get(self, "service_account") @property @pulumi.getter(name="targetProject") def target_project(self) -> str: """ The full path of the resource of type TargetProject which represents the Compute Engine project in which to create this VM. """ return pulumi.get(self, "target_project") @property @pulumi.getter(name="vmName") def vm_name(self) -> str: """ The name of the VM to create. """ return pulumi.get(self, "vm_name") @property @pulumi.getter def zone(self) -> str: """ The zone in which to create the VM. """ return pulumi.get(self, "zone") @pulumi.output_type class ComputeEngineTargetDetailsResponse(dict): """ ComputeEngineTargetDetails is a collection of details for creating a VM in a target Compute Engine project. """ @staticmethod def __key_warning(key: str): suggest = None if key == "additionalLicenses": suggest = "additional_licenses" elif key == "appliedLicense": suggest = "applied_license" elif key == "bootOption": suggest = "boot_option" elif key == "computeScheduling": suggest = "compute_scheduling" elif key == "diskType": suggest = "disk_type" elif key == "licenseType": suggest = "license_type" elif key == "machineType": suggest = "machine_type" elif key == "machineTypeSeries": suggest = "machine_type_series" elif key == "networkInterfaces": suggest = "network_interfaces" elif key == "networkTags": suggest = "network_tags" elif key == "secureBoot": suggest = "secure_boot" elif key == "serviceAccount": suggest = "service_account" elif key == "vmName": suggest = "vm_name" if suggest: pulumi.log.warn(f"Key '{key}' not found in ComputeEngineTargetDetailsResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: ComputeEngineTargetDetailsResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: ComputeEngineTargetDetailsResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, additional_licenses: Sequence[str], applied_license: 'outputs.AppliedLicenseResponse', boot_option: str, compute_scheduling: 'outputs.ComputeSchedulingResponse', disk_type: str, labels: Mapping[str, str], license_type: str, machine_type: str, machine_type_series: str, metadata: Mapping[str, str], network_interfaces: Sequence['outputs.NetworkInterfaceResponse'], network_tags: Sequence[str], project: str, secure_boot: bool, service_account: str, vm_name: str, zone: str): """ ComputeEngineTargetDetails is a collection of details for creating a VM in a target Compute Engine project. :param Sequence[str] additional_licenses: Additional licenses to assign to the VM. :param 'AppliedLicenseResponse' applied_license: The OS license returned from the adaptation module report. :param str boot_option: The VM Boot Option, as set in the source vm. :param 'ComputeSchedulingResponse' compute_scheduling: Compute instance scheduling information (if empty default is used). :param str disk_type: The disk type to use in the VM. :param Mapping[str, str] labels: A map of labels to associate with the VM. :param str license_type: The license type to use in OS adaptation. :param str machine_type: The machine type to create the VM with. :param str machine_type_series: The machine type series to create the VM with. :param Mapping[str, str] metadata: The metadata key/value pairs to assign to the VM. :param Sequence['NetworkInterfaceResponse'] network_interfaces: List of NICs connected to this VM. :param Sequence[str] network_tags: A map of network tags to associate with the VM. :param str project: The GCP target project ID or project name. :param bool secure_boot: Defines whether the instance has Secure Boot enabled. This can be set to true only if the vm boot option is EFI. :param str service_account: The service account to associate the VM with. :param str vm_name: The name of the VM to create. :param str zone: The zone in which to create the VM. """ pulumi.set(__self__, "additional_licenses", additional_licenses) pulumi.set(__self__, "applied_license", applied_license) pulumi.set(__self__, "boot_option", boot_option) pulumi.set(__self__, "compute_scheduling", compute_scheduling) pulumi.set(__self__, "disk_type", disk_type) pulumi.set(__self__, "labels", labels) pulumi.set(__self__, "license_type", license_type) pulumi.set(__self__, "machine_type", machine_type) pulumi.set(__self__, "machine_type_series", machine_type_series) pulumi.set(__self__, "metadata", metadata) pulumi.set(__self__, "network_interfaces", network_interfaces) pulumi.set(__self__, "network_tags", network_tags) pulumi.set(__self__, "project", project) pulumi.set(__self__, "secure_boot", secure_boot) pulumi.set(__self__, "service_account", service_account) pulumi.set(__self__, "vm_name", vm_name) pulumi.set(__self__, "zone", zone) @property @pulumi.getter(name="additionalLicenses") def additional_licenses(self) -> Sequence[str]: """ Additional licenses to assign to the VM. """ return pulumi.get(self, "additional_licenses") @property @pulumi.getter(name="appliedLicense") def applied_license(self) -> 'outputs.AppliedLicenseResponse': """ The OS license returned from the adaptation module report. """ return pulumi.get(self, "applied_license") @property @pulumi.getter(name="bootOption") def boot_option(self) -> str: """ The VM Boot Option, as set in the source vm. """ return pulumi.get(self, "boot_option") @property @pulumi.getter(name="computeScheduling") def compute_scheduling(self) -> 'outputs.ComputeSchedulingResponse': """ Compute instance scheduling information (if empty default is used). """ return pulumi.get(self, "compute_scheduling") @property @pulumi.getter(name="diskType") def disk_type(self) -> str: """ The disk type to use in the VM. """ return pulumi.get(self, "disk_type") @property @pulumi.getter def labels(self) -> Mapping[str, str]: """ A map of labels to associate with the VM. """ return pulumi.get(self, "labels") @property @pulumi.getter(name="licenseType") def license_type(self) -> str: """ The license type to use in OS adaptation. """ return pulumi.get(self, "license_type") @property @pulumi.getter(name="machineType") def machine_type(self) -> str: """ The machine type to create the VM with. """ return pulumi.get(self, "machine_type") @property @pulumi.getter(name="machineTypeSeries") def machine_type_series(self) -> str: """ The machine type series to create the VM with. """ return pulumi.get(self, "machine_type_series") @property @pulumi.getter def metadata(self) -> Mapping[str, str]: """ The metadata key/value pairs to assign to the VM. """ return pulumi.get(self, "metadata") @property @pulumi.getter(name="networkInterfaces") def network_interfaces(self) -> Sequence['outputs.NetworkInterfaceResponse']: """ List of NICs connected to this VM. """ return pulumi.get(self, "network_interfaces") @property @pulumi.getter(name="networkTags") def network_tags(self) -> Sequence[str]: """ A map of network tags to associate with the VM. """ return pulumi.get(self, "network_tags") @property @pulumi.getter def project(self) -> str: """ The GCP target project ID or project name. """ return pulumi.get(self, "project") @property @pulumi.getter(name="secureBoot") def secure_boot(self) -> bool: """ Defines whether the instance has Secure Boot enabled. This can be set to true only if the vm boot option is EFI. """ return pulumi.get(self, "secure_boot") @property @pulumi.getter(name="serviceAccount") def service_account(self) -> str: """ The service account to associate the VM with. """ return pulumi.get(self, "service_account") @property @pulumi.getter(name="vmName") def vm_name(self) -> str: """ The name of the VM to create. """ return pulumi.get(self, "vm_name") @property @pulumi.getter def zone(self) -> str: """ The zone in which to create the VM. """ return pulumi.get(self, "zone") @pulumi.output_type class ComputeSchedulingResponse(dict): """ Scheduling information for VM on maintenance/restart behaviour and node allocation in sole tenant nodes. """ @staticmethod def __key_warning(key: str): suggest = None if key == "automaticRestart": suggest = "automatic_restart" elif key == "minNodeCpus": suggest = "min_node_cpus" elif key == "nodeAffinities": suggest = "node_affinities" elif key == "onHostMaintenance": suggest = "on_host_maintenance" elif key == "restartType": suggest = "restart_type" if suggest: pulumi.log.warn(f"Key '{key}' not found in ComputeSchedulingResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: ComputeSchedulingResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: ComputeSchedulingResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, automatic_restart: bool, min_node_cpus: int, node_affinities: Sequence['outputs.SchedulingNodeAffinityResponse'], on_host_maintenance: str, restart_type: str): """ Scheduling information for VM on maintenance/restart behaviour and node allocation in sole tenant nodes. :param int min_node_cpus: The minimum number of virtual CPUs this instance will consume when running on a sole-tenant node. Ignored if no node_affinites are configured. :param Sequence['SchedulingNodeAffinityResponse'] node_affinities: A set of node affinity and anti-affinity configurations for sole tenant nodes. :param str on_host_maintenance: How the instance should behave when the host machine undergoes maintenance that may temporarily impact instance performance. :param str restart_type: Whether the Instance should be automatically restarted whenever it is terminated by Compute Engine (not terminated by user). This configuration is identical to `automaticRestart` field in Compute Engine create instance under scheduling. It was changed to an enum (instead of a boolean) to match the default value in Compute Engine which is automatic restart. """ pulumi.set(__self__, "automatic_restart", automatic_restart) pulumi.set(__self__, "min_node_cpus", min_node_cpus) pulumi.set(__self__, "node_affinities", node_affinities) pulumi.set(__self__, "on_host_maintenance", on_host_maintenance) pulumi.set(__self__, "restart_type", restart_type) @property @pulumi.getter(name="automaticRestart") def automatic_restart(self) -> bool: return pulumi.get(self, "automatic_restart") @property @pulumi.getter(name="minNodeCpus") def min_node_cpus(self) -> int: """ The minimum number of virtual CPUs this instance will consume when running on a sole-tenant node. Ignored if no node_affinites are configured. """ return pulumi.get(self, "min_node_cpus") @property @pulumi.getter(name="nodeAffinities") def node_affinities(self) -> Sequence['outputs.SchedulingNodeAffinityResponse']: """ A set of node affinity and anti-affinity configurations for sole tenant nodes. """ return pulumi.get(self, "node_affinities") @property @pulumi.getter(name="onHostMaintenance") def on_host_maintenance(self) -> str: """ How the instance should behave when the host machine undergoes maintenance that may temporarily impact instance performance. """ return pulumi.get(self, "on_host_maintenance") @property @pulumi.getter(name="restartType") def restart_type(self) -> str: """ Whether the Instance should be automatically restarted whenever it is terminated by Compute Engine (not terminated by user). This configuration is identical to `automaticRestart` field in Compute Engine create instance under scheduling. It was changed to an enum (instead of a boolean) to match the default value in Compute Engine which is automatic restart. """ return pulumi.get(self, "restart_type") @pulumi.output_type class CutoverJobResponse(dict): """ CutoverJob message describes a cutover of a migrating VM. The CutoverJob is the operation of shutting down the VM, creating a snapshot and clonning the VM using the replicated snapshot. """ @staticmethod def __key_warning(key: str): suggest = None if key == "computeEngineTargetDetails": suggest = "compute_engine_target_details" elif key == "createTime": suggest = "create_time" elif key == "progressPercent": suggest = "progress_percent" elif key == "stateMessage": suggest = "state_message" elif key == "stateTime": suggest = "state_time" if suggest: pulumi.log.warn(f"Key '{key}' not found in CutoverJobResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: CutoverJobResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: CutoverJobResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, compute_engine_target_details: 'outputs.ComputeEngineTargetDetailsResponse', create_time: str, error: 'outputs.StatusResponse', name: str, progress: int, progress_percent: int, state: str, state_message: str, state_time: str): """ CutoverJob message describes a cutover of a migrating VM. The CutoverJob is the operation of shutting down the VM, creating a snapshot and clonning the VM using the replicated snapshot. :param 'ComputeEngineTargetDetailsResponse' compute_engine_target_details: Details of the target VM in Compute Engine. :param str create_time: The time the cutover job was created (as an API call, not when it was actually created in the target). :param 'StatusResponse' error: Provides details for the errors that led to the Cutover Job's state. :param str name: The name of the cutover job. :param int progress: The current progress in percentage of the cutover job. :param int progress_percent: The current progress in percentage of the cutover job. :param str state: State of the cutover job. :param str state_message: A message providing possible extra details about the current state. :param str state_time: The time the state was last updated. """ pulumi.set(__self__, "compute_engine_target_details", compute_engine_target_details) pulumi.set(__self__, "create_time", create_time) pulumi.set(__self__, "error", error) pulumi.set(__self__, "name", name) pulumi.set(__self__, "progress", progress) pulumi.set(__self__, "progress_percent", progress_percent) pulumi.set(__self__, "state", state) pulumi.set(__self__, "state_message", state_message) pulumi.set(__self__, "state_time", state_time) @property @pulumi.getter(name="computeEngineTargetDetails") def compute_engine_target_details(self) -> 'outputs.ComputeEngineTargetDetailsResponse': """ Details of the target VM in Compute Engine. """ return pulumi.get(self, "compute_engine_target_details") @property @pulumi.getter(name="createTime") def create_time(self) -> str: """ The time the cutover job was created (as an API call, not when it was actually created in the target). """ return pulumi.get(self, "create_time") @property @pulumi.getter def error(self) -> 'outputs.StatusResponse': """ Provides details for the errors that led to the Cutover Job's state. """ return pulumi.get(self, "error") @property @pulumi.getter def name(self) -> str: """ The name of the cutover job. """ return pulumi.get(self, "name") @property @pulumi.getter def progress(self) -> int: """ The current progress in percentage of the cutover job. """ return pulumi.get(self, "progress") @property @pulumi.getter(name="progressPercent") def progress_percent(self) -> int: """ The current progress in percentage of the cutover job. """ return pulumi.get(self, "progress_percent") @property @pulumi.getter def state(self) -> str: """ State of the cutover job. """ return pulumi.get(self, "state") @property @pulumi.getter(name="stateMessage") def state_message(self) -> str: """ A message providing possible extra details about the current state. """ return pulumi.get(self, "state_message") @property @pulumi.getter(name="stateTime") def state_time(self) -> str: """ The time the state was last updated. """ return pulumi.get(self, "state_time") @pulumi.output_type class NetworkInterfaceResponse(dict): """ NetworkInterface represents a NIC of a VM. """ @staticmethod def __key_warning(key: str): suggest = None if key == "externalIp": suggest = "external_ip" elif key == "internalIp": suggest = "internal_ip" if suggest: pulumi.log.warn(f"Key '{key}' not found in NetworkInterfaceResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: NetworkInterfaceResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: NetworkInterfaceResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, external_ip: str, internal_ip: str, network: str, subnetwork: str): """ NetworkInterface represents a NIC of a VM. :param str external_ip: The external IP to define in the NIC. :param str internal_ip: The internal IP to define in the NIC. The formats accepted are: `ephemeral` \ ipv4 address \ a named address resource full path. :param str network: The network to connect the NIC to. :param str subnetwork: The subnetwork to connect the NIC to. """ pulumi.set(__self__, "external_ip", external_ip) pulumi.set(__self__, "internal_ip", internal_ip) pulumi.set(__self__, "network", network) pulumi.set(__self__, "subnetwork", subnetwork) @property @pulumi.getter(name="externalIp") def external_ip(self) -> str: """ The external IP to define in the NIC. """ return pulumi.get(self, "external_ip") @property @pulumi.getter(name="internalIp") def internal_ip(self) -> str: """ The internal IP to define in the NIC. The formats accepted are: `ephemeral` \ ipv4 address \ a named address resource full path. """ return pulumi.get(self, "internal_ip") @property @pulumi.getter def network(self) -> str: """ The network to connect the NIC to. """ return pulumi.get(self, "network") @property @pulumi.getter def subnetwork(self) -> str: """ The subnetwork to connect the NIC to. """ return pulumi.get(self, "subnetwork") @pulumi.output_type class ReplicationCycleResponse(dict): """ ReplicationCycle contains information about the current replication cycle status. """ @staticmethod def __key_warning(key: str): suggest = None if key == "progressPercent": suggest = "progress_percent" elif key == "startTime": suggest = "start_time" if suggest: pulumi.log.warn(f"Key '{key}' not found in ReplicationCycleResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: ReplicationCycleResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: ReplicationCycleResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, progress: int, progress_percent: int, start_time: str): """ ReplicationCycle contains information about the current replication cycle status. :param int progress: The current progress in percentage of this cycle. :param int progress_percent: The current progress in percentage of this cycle. :param str start_time: The time the replication cycle has started. """ pulumi.set(__self__, "progress", progress) pulumi.set(__self__, "progress_percent", progress_percent) pulumi.set(__self__, "start_time", start_time) @property @pulumi.getter def progress(self) -> int: """ The current progress in percentage of this cycle. """ return pulumi.get(self, "progress") @property @pulumi.getter(name="progressPercent") def progress_percent(self) -> int: """ The current progress in percentage of this cycle. """ return pulumi.get(self, "progress_percent") @property @pulumi.getter(name="startTime") def start_time(self) -> str: """ The time the replication cycle has started. """ return pulumi.get(self, "start_time") @pulumi.output_type class ReplicationSyncResponse(dict): """ ReplicationSync contain information about the last replica sync to the cloud. """ @staticmethod def __key_warning(key: str): suggest = None if key == "lastSyncTime": suggest = "last_sync_time" if suggest: pulumi.log.warn(f"Key '{key}' not found in ReplicationSyncResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: ReplicationSyncResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: ReplicationSyncResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, last_sync_time: str): """ ReplicationSync contain information about the last replica sync to the cloud. :param str last_sync_time: The most updated snapshot created time in the source that finished replication. """ pulumi.set(__self__, "last_sync_time", last_sync_time) @property @pulumi.getter(name="lastSyncTime") def last_sync_time(self) -> str: """ The most updated snapshot created time in the source that finished replication. """ return pulumi.get(self, "last_sync_time") @pulumi.output_type class SchedulePolicyResponse(dict): """ A policy for scheduling replications. """ @staticmethod def __key_warning(key: str): suggest = None if key == "idleDuration": suggest = "idle_duration" elif key == "skipOsAdaptation": suggest = "skip_os_adaptation" if suggest: pulumi.log.warn(f"Key '{key}' not found in SchedulePolicyResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: SchedulePolicyResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: SchedulePolicyResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, idle_duration: str, skip_os_adaptation: bool): """ A policy for scheduling replications. :param str idle_duration: The idle duration between replication stages. :param bool skip_os_adaptation: A flag to indicate whether to skip OS adaptation during the replication sync. OS adaptation is a process where the VM's operating system undergoes changes and adaptations to fully function on Compute Engine. """ pulumi.set(__self__, "idle_duration", idle_duration) pulumi.set(__self__, "skip_os_adaptation", skip_os_adaptation) @property @pulumi.getter(name="idleDuration") def idle_duration(self) -> str: """ The idle duration between replication stages. """ return pulumi.get(self, "idle_duration") @property @pulumi.getter(name="skipOsAdaptation") def skip_os_adaptation(self) -> bool: """ A flag to indicate whether to skip OS adaptation during the replication sync. OS adaptation is a process where the VM's operating system undergoes changes and adaptations to fully function on Compute Engine. """ return pulumi.get(self, "skip_os_adaptation") @pulumi.output_type class SchedulingNodeAffinityResponse(dict): """ Node Affinity: the configuration of desired nodes onto which this Instance could be scheduled. Based on https://cloud.google.com/compute/docs/reference/rest/v1/instances/setScheduling """ def __init__(__self__, *, key: str, operator: str, values: Sequence[str]): """ Node Affinity: the configuration of desired nodes onto which this Instance could be scheduled. Based on https://cloud.google.com/compute/docs/reference/rest/v1/instances/setScheduling :param str key: The label key of Node resource to reference. :param str operator: The operator to use for the node resources specified in the `values` parameter. :param Sequence[str] values: Corresponds to the label values of Node resource. """ pulumi.set(__self__, "key", key) pulumi.set(__self__, "operator", operator) pulumi.set(__self__, "values", values) @property @pulumi.getter def key(self) -> str: """ The label key of Node resource to reference. """ return pulumi.get(self, "key") @property @pulumi.getter def operator(self) -> str: """ The operator to use for the node resources specified in the `values` parameter. """ return pulumi.get(self, "operator") @property @pulumi.getter def values(self) -> Sequence[str]: """ Corresponds to the label values of Node resource. """ return pulumi.get(self, "values") @pulumi.output_type class StatusResponse(dict): """ The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). """ def __init__(__self__, *, code: int, details: Sequence[Mapping[str, str]], message: str): """ The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). :param int code: The status code, which should be an enum value of google.rpc.Code. :param Sequence[Mapping[str, str]] details: A list of messages that carry the error details. There is a common set of message types for APIs to use. :param str message: A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client. """ pulumi.set(__self__, "code", code) pulumi.set(__self__, "details", details) pulumi.set(__self__, "message", message) @property @pulumi.getter def code(self) -> int: """ The status code, which should be an enum value of google.rpc.Code. """ return pulumi.get(self, "code") @property @pulumi.getter def details(self) -> Sequence[Mapping[str, str]]: """ A list of messages that carry the error details. There is a common set of message types for APIs to use. """ return pulumi.get(self, "details") @property @pulumi.getter def message(self) -> str: """ A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client. """ return pulumi.get(self, "message") @pulumi.output_type class VmUtilizationInfoResponse(dict): """ Utilization information of a single VM. """ @staticmethod def __key_warning(key: str): suggest = None if key == "vmId": suggest = "vm_id" elif key == "vmwareVmDetails": suggest = "vmware_vm_details" if suggest: pulumi.log.warn(f"Key '{key}' not found in VmUtilizationInfoResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: VmUtilizationInfoResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: VmUtilizationInfoResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, utilization: 'outputs.VmUtilizationMetricsResponse', vm_id: str, vmware_vm_details: 'outputs.VmwareVmDetailsResponse'): """ Utilization information of a single VM. :param 'VmUtilizationMetricsResponse' utilization: Utilization metrics for this VM. :param str vm_id: The VM's ID in the source. :param 'VmwareVmDetailsResponse' vmware_vm_details: The description of the VM in a Source of type Vmware. """ pulumi.set(__self__, "utilization", utilization) pulumi.set(__self__, "vm_id", vm_id) pulumi.set(__self__, "vmware_vm_details", vmware_vm_details) @property @pulumi.getter def utilization(self) -> 'outputs.VmUtilizationMetricsResponse': """ Utilization metrics for this VM. """ return pulumi.get(self, "utilization") @property @pulumi.getter(name="vmId") def vm_id(self) -> str: """ The VM's ID in the source. """ return pulumi.get(self, "vm_id") @property @pulumi.getter(name="vmwareVmDetails") def vmware_vm_details(self) -> 'outputs.VmwareVmDetailsResponse': """ The description of the VM in a Source of type Vmware. """ return pulumi.get(self, "vmware_vm_details") @pulumi.output_type class VmUtilizationMetricsResponse(dict): """ Utilization metrics values for a single VM. """ @staticmethod def __key_warning(key: str): suggest = None if key == "cpuAverage": suggest = "cpu_average" elif key == "cpuAveragePercent": suggest = "cpu_average_percent" elif key == "cpuMax": suggest = "cpu_max" elif key == "cpuMaxPercent": suggest = "cpu_max_percent" elif key == "diskIoRateAverage": suggest = "disk_io_rate_average" elif key == "diskIoRateAverageKbps": suggest = "disk_io_rate_average_kbps" elif key == "diskIoRateMax": suggest = "disk_io_rate_max" elif key == "diskIoRateMaxKbps": suggest = "disk_io_rate_max_kbps" elif key == "memoryAverage": suggest = "memory_average" elif key == "memoryAveragePercent": suggest = "memory_average_percent" elif key == "memoryMax": suggest = "memory_max" elif key == "memoryMaxPercent": suggest = "memory_max_percent" elif key == "networkThroughputAverage": suggest = "network_throughput_average" elif key == "networkThroughputAverageKbps": suggest = "network_throughput_average_kbps" elif key == "networkThroughputMax": suggest = "network_throughput_max" elif key == "networkThroughputMaxKbps": suggest = "network_throughput_max_kbps" if suggest: pulumi.log.warn(f"Key '{key}' not found in VmUtilizationMetricsResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: VmUtilizationMetricsResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: VmUtilizationMetricsResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, cpu_average: int, cpu_average_percent: int, cpu_max: int, cpu_max_percent: int, disk_io_rate_average: str, disk_io_rate_average_kbps: str, disk_io_rate_max: str, disk_io_rate_max_kbps: str, memory_average: int, memory_average_percent: int, memory_max: int, memory_max_percent: int, network_throughput_average: str, network_throughput_average_kbps: str, network_throughput_max: str, network_throughput_max_kbps: str): """ Utilization metrics values for a single VM. :param int cpu_average: Average CPU usage, percent. :param int cpu_average_percent: Average CPU usage, percent. :param int cpu_max: Max CPU usage, percent. :param int cpu_max_percent: Max CPU usage, percent. :param str disk_io_rate_average: Average disk IO rate, in kilobytes per second. :param str disk_io_rate_average_kbps: Average disk IO rate, in kilobytes per second. :param str disk_io_rate_max: Max disk IO rate, in kilobytes per second. :param str disk_io_rate_max_kbps: Max disk IO rate, in kilobytes per second. :param int memory_average: Average memory usage, percent. :param int memory_average_percent: Average memory usage, percent. :param int memory_max: Max memory usage, percent. :param int memory_max_percent: Max memory usage, percent. :param str network_throughput_average: Average network throughput (combined transmit-rates and receive-rates), in kilobytes per second. :param str network_throughput_average_kbps: Average network throughput (combined transmit-rates and receive-rates), in kilobytes per second. :param str network_throughput_max: Max network throughput (combined transmit-rates and receive-rates), in kilobytes per second. :param str network_throughput_max_kbps: Max network throughput (combined transmit-rates and receive-rates), in kilobytes per second. """ pulumi.set(__self__, "cpu_average", cpu_average) pulumi.set(__self__, "cpu_average_percent", cpu_average_percent) pulumi.set(__self__, "cpu_max", cpu_max) pulumi.set(__self__, "cpu_max_percent", cpu_max_percent) pulumi.set(__self__, "disk_io_rate_average", disk_io_rate_average) pulumi.set(__self__, "disk_io_rate_average_kbps", disk_io_rate_average_kbps) pulumi.set(__self__, "disk_io_rate_max", disk_io_rate_max) pulumi.set(__self__, "disk_io_rate_max_kbps", disk_io_rate_max_kbps) pulumi.set(__self__, "memory_average", memory_average) pulumi.set(__self__, "memory_average_percent", memory_average_percent) pulumi.set(__self__, "memory_max", memory_max) pulumi.set(__self__, "memory_max_percent", memory_max_percent) pulumi.set(__self__, "network_throughput_average", network_throughput_average) pulumi.set(__self__, "network_throughput_average_kbps", network_throughput_average_kbps) pulumi.set(__self__, "network_throughput_max", network_throughput_max) pulumi.set(__self__, "network_throughput_max_kbps", network_throughput_max_kbps) @property @pulumi.getter(name="cpuAverage") def cpu_average(self) -> int: """ Average CPU usage, percent. """ return pulumi.get(self, "cpu_average") @property @pulumi.getter(name="cpuAveragePercent") def cpu_average_percent(self) -> int: """ Average CPU usage, percent. """ return pulumi.get(self, "cpu_average_percent") @property @pulumi.getter(name="cpuMax") def cpu_max(self) -> int: """ Max CPU usage, percent. """ return pulumi.get(self, "cpu_max") @property @pulumi.getter(name="cpuMaxPercent") def cpu_max_percent(self) -> int: """ Max CPU usage, percent. """ return pulumi.get(self, "cpu_max_percent") @property @pulumi.getter(name="diskIoRateAverage") def disk_io_rate_average(self) -> str: """ Average disk IO rate, in kilobytes per second. """ return pulumi.get(self, "disk_io_rate_average") @property @pulumi.getter(name="diskIoRateAverageKbps") def disk_io_rate_average_kbps(self) -> str: """ Average disk IO rate, in kilobytes per second. """ return pulumi.get(self, "disk_io_rate_average_kbps") @property @pulumi.getter(name="diskIoRateMax") def disk_io_rate_max(self) -> str: """ Max disk IO rate, in kilobytes per second. """ return pulumi.get(self, "disk_io_rate_max") @property @pulumi.getter(name="diskIoRateMaxKbps") def disk_io_rate_max_kbps(self) -> str: """ Max disk IO rate, in kilobytes per second. """ return pulumi.get(self, "disk_io_rate_max_kbps") @property @pulumi.getter(name="memoryAverage") def memory_average(self) -> int: """ Average memory usage, percent. """ return pulumi.get(self, "memory_average") @property @pulumi.getter(name="memoryAveragePercent") def memory_average_percent(self) -> int: """ Average memory usage, percent. """ return pulumi.get(self, "memory_average_percent") @property @pulumi.getter(name="memoryMax") def memory_max(self) -> int: """ Max memory usage, percent. """ return pulumi.get(self, "memory_max") @property @pulumi.getter(name="memoryMaxPercent") def memory_max_percent(self) -> int: """ Max memory usage, percent. """ return pulumi.get(self, "memory_max_percent") @property @pulumi.getter(name="networkThroughputAverage") def network_throughput_average(self) -> str: """ Average network throughput (combined transmit-rates and receive-rates), in kilobytes per second. """ return pulumi.get(self, "network_throughput_average") @property @pulumi.getter(name="networkThroughputAverageKbps") def network_throughput_average_kbps(self) -> str: """ Average network throughput (combined transmit-rates and receive-rates), in kilobytes per second. """ return pulumi.get(self, "network_throughput_average_kbps") @property @pulumi.getter(name="networkThroughputMax") def network_throughput_max(self) -> str: """ Max network throughput (combined transmit-rates and receive-rates), in kilobytes per second. """ return pulumi.get(self, "network_throughput_max") @property @pulumi.getter(name="networkThroughputMaxKbps") def network_throughput_max_kbps(self) -> str: """ Max network throughput (combined transmit-rates and receive-rates), in kilobytes per second. """ return pulumi.get(self, "network_throughput_max_kbps") @pulumi.output_type class VmwareSourceDetailsResponse(dict): """ VmwareSourceDetails message describes a specific source details for the vmware source type. """ @staticmethod def __key_warning(key: str): suggest = None if key == "vcenterIp": suggest = "vcenter_ip" if suggest: pulumi.log.warn(f"Key '{key}' not found in VmwareSourceDetailsResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: VmwareSourceDetailsResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: VmwareSourceDetailsResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, password: str, thumbprint: str, username: str, vcenter_ip: str): """ VmwareSourceDetails message describes a specific source details for the vmware source type. :param str password: Input only. The credentials password. This is write only and can not be read in a GET operation. :param str thumbprint: The thumbprint representing the certificate for the vcenter. :param str username: The credentials username. :param str vcenter_ip: The ip address of the vcenter this Source represents. """ pulumi.set(__self__, "password", password) pulumi.set(__self__, "thumbprint", thumbprint) pulumi.set(__self__, "username", username) pulumi.set(__self__, "vcenter_ip", vcenter_ip) @property @pulumi.getter def password(self) -> str: """ Input only. The credentials password. This is write only and can not be read in a GET operation. """ return pulumi.get(self, "password") @property @pulumi.getter def thumbprint(self) -> str: """ The thumbprint representing the certificate for the vcenter. """ return pulumi.get(self, "thumbprint") @property @pulumi.getter def username(self) -> str: """ The credentials username. """ return pulumi.get(self, "username") @property @pulumi.getter(name="vcenterIp") def vcenter_ip(self) -> str: """ The ip address of the vcenter this Source represents. """ return pulumi.get(self, "vcenter_ip") @pulumi.output_type class VmwareVmDetailsResponse(dict): """ VmwareVmDetails describes a VM in vCenter. """ @staticmethod def __key_warning(key: str): suggest = None if key == "bootOption": suggest = "boot_option" elif key == "committedStorage": suggest = "committed_storage" elif key == "committedStorageMb": suggest = "committed_storage_mb" elif key == "cpuCount": suggest = "cpu_count" elif key == "datacenterDescription": suggest = "datacenter_description" elif key == "datacenterId": suggest = "datacenter_id" elif key == "diskCount": suggest = "disk_count" elif key == "displayName": suggest = "display_name" elif key == "guestDescription": suggest = "guest_description" elif key == "memoryMb": suggest = "memory_mb" elif key == "powerState": suggest = "power_state" elif key == "vmId": suggest = "vm_id" if suggest: pulumi.log.warn(f"Key '{key}' not found in VmwareVmDetailsResponse. Access the value via the '{suggest}' property getter instead.") def __getitem__(self, key: str) -> Any: VmwareVmDetailsResponse.__key_warning(key) return super().__getitem__(key) def get(self, key: str, default = None) -> Any: VmwareVmDetailsResponse.__key_warning(key) return super().get(key, default) def __init__(__self__, *, boot_option: str, committed_storage: str, committed_storage_mb: str, cpu_count: int, datacenter_description: str, datacenter_id: str, disk_count: int, display_name: str, guest_description: str, memory_mb: int, power_state: str, uuid: str, vm_id: str): """ VmwareVmDetails describes a VM in vCenter. :param str boot_option: The VM Boot Option. :param str committed_storage: The total size of the storage allocated to the VM in MB. :param str committed_storage_mb: The total size of the storage allocated to the VM in MB. :param int cpu_count: The number of cpus in the VM. :param str datacenter_description: The descriptive name of the vCenter's datacenter this VM is contained in. :param str datacenter_id: The id of the vCenter's datacenter this VM is contained in. :param int disk_count: The number of disks the VM has. :param str display_name: The display name of the VM. Note that this is not necessarily unique. :param str guest_description: The VM's OS. See for example https://pubs.vmware.com/vi-sdk/visdk250/ReferenceGuide/vim.vm.GuestOsDescriptor.GuestOsIdentifier.html for types of strings this might hold. :param int memory_mb: The size of the memory of the VM in MB. :param str power_state: The power state of the VM at the moment list was taken. :param str uuid: The unique identifier of the VM in vCenter. :param str vm_id: The VM's id in the source (note that this is not the MigratingVm's id). This is the moref id of the VM. """ pulumi.set(__self__, "boot_option", boot_option) pulumi.set(__self__, "committed_storage", committed_storage) pulumi.set(__self__, "committed_storage_mb", committed_storage_mb) pulumi.set(__self__, "cpu_count", cpu_count) pulumi.set(__self__, "datacenter_description", datacenter_description) pulumi.set(__self__, "datacenter_id", datacenter_id) pulumi.set(__self__, "disk_count", disk_count) pulumi.set(__self__, "display_name", display_name) pulumi.set(__self__, "guest_description", guest_description) pulumi.set(__self__, "memory_mb", memory_mb) pulumi.set(__self__, "power_state", power_state) pulumi.set(__self__, "uuid", uuid) pulumi.set(__self__, "vm_id", vm_id) @property @pulumi.getter(name="bootOption") def boot_option(self) -> str: """ The VM Boot Option. """ return pulumi.get(self, "boot_option") @property @pulumi.getter(name="committedStorage") def committed_storage(self) -> str: """ The total size of the storage allocated to the VM in MB. """ return pulumi.get(self, "committed_storage") @property @pulumi.getter(name="committedStorageMb") def committed_storage_mb(self) -> str: """ The total size of the storage allocated to the VM in MB. """ return pulumi.get(self, "committed_storage_mb") @property @pulumi.getter(name="cpuCount") def cpu_count(self) -> int: """ The number of cpus in the VM. """ return pulumi.get(self, "cpu_count") @property @pulumi.getter(name="datacenterDescription") def datacenter_description(self) -> str: """ The descriptive name of the vCenter's datacenter this VM is contained in. """ return pulumi.get(self, "datacenter_description") @property @pulumi.getter(name="datacenterId") def datacenter_id(self) -> str: """ The id of the vCenter's datacenter this VM is contained in. """ return pulumi.get(self, "datacenter_id") @property @pulumi.getter(name="diskCount") def disk_count(self) -> int: """ The number of disks the VM has. """ return pulumi.get(self, "disk_count") @property @pulumi.getter(name="displayName") def display_name(self) -> str: """ The display name of the VM. Note that this is not necessarily unique. """ return pulumi.get(self, "display_name") @property @pulumi.getter(name="guestDescription") def guest_description(self) -> str: """ The VM's OS. See for example https://pubs.vmware.com/vi-sdk/visdk250/ReferenceGuide/vim.vm.GuestOsDescriptor.GuestOsIdentifier.html for types of strings this might hold. """ return pulumi.get(self, "guest_description") @property @pulumi.getter(name="memoryMb") def memory_mb(self) -> int: """ The size of the memory of the VM in MB. """ return pulumi.get(self, "memory_mb") @property @pulumi.getter(name="powerState") def power_state(self) -> str: """ The power state of the VM at the moment list was taken. """ return pulumi.get(self, "power_state") @property @pulumi.getter def uuid(self) -> str: """ The unique identifier of the VM in vCenter. """ return pulumi.get(self, "uuid") @property @pulumi.getter(name="vmId") def vm_id(self) -> str: """ The VM's id in the source (note that this is not the MigratingVm's id). This is the moref id of the VM. """ return pulumi.get(self, "vm_id")

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0.668316

0.655754

0.640502

0

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0.26873

67,834

1,759

654

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0.839069

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1

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0.20527

0.060905

0

1

0.160697

false

0.003872

0.006776

0.000968

0.314618

0.003872

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0

1

0

1

0

1

0

null

0

4

a10b1c87fe2ffd2a2fe1dee4b23ec1fe16f8cf15

287

py

Python

electroPyy/io/__init__.py

ludo67100/electroPyy_Dev

3b940adbfdf005dd8231e7ac61aca708033d5a95

[ "OML" ]

null

electroPyy/io/__init__.py

ludo67100/electroPyy_Dev

3b940adbfdf005dd8231e7ac61aca708033d5a95

[ "OML" ]

null

electroPyy/io/__init__.py

ludo67100/electroPyy_Dev

3b940adbfdf005dd8231e7ac61aca708033d5a95

[ "OML" ]

null

# -*- coding: utf-8 -*- """ Created on Thu Nov 21 14:54:51 2019 @author: Ludovic.SPAETH """ from electroPyy.io.BaseRawIO import BaseRawIO from electroPyy.io.HdF5IO import HdF5IO from electroPyy.io.NeuroExIO import NeuroExIO from electroPyy.io.WinWcpRawIO import WinWcpRawIO

23.916667

50

0.745645

39

287

5.487179

0.589744

0.261682

0.299065

0

0.061983

0.156794

287

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true

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1

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null

0

1

0

1

0

4

a14dc76d87023f8e5ab3f4a7babd9708c41bf004

34,030

py

Python

Project1/cl1_p1_wsd.py

Sanghyun-Hong/NLPProjects

9f81fa680946648f64ac25e5ca8197e9f3386deb

[ "MIT" ]

null

Project1/cl1_p1_wsd.py

Sanghyun-Hong/NLPProjects

9f81fa680946648f64ac25e5ca8197e9f3386deb

[ "MIT" ]

null

Project1/cl1_p1_wsd.py

Sanghyun-Hong/NLPProjects

9f81fa680946648f64ac25e5ca8197e9f3386deb

[ "MIT" ]

null

import numpy as np import operator # SHHONG: custom modules imported import json import random import itertools from math import pow, log from collections import Counter import os import sys sys.stdout = open(os.devnull, 'w') """ CMSC723 / INST725 / LING723 -- Fall 2016 Project 1: Implementing Word Sense Disambiguation Systems """ """ read one of train, dev, test subsets subset - one of train, dev, test output is a tuple of three lists labels: one of the 6 possible senses <cord, division, formation, phone, product, text > targets: the index within the text of the token to be disambiguated texts: a list of tokenized and normalized text input (note that there can be multiple sentences) """ import nltk #### added dev_manual to the subset of allowable files def read_dataset(subset): labels = [] texts = [] targets = [] if subset in ['train', 'dev', 'test', 'dev_manual']: with open('data/wsd_'+subset+'.txt') as inp_hndl: for example in inp_hndl: label, text = example.strip().split('\t') text = nltk.word_tokenize(text.lower().replace('" ','"')) if 'line' in text: ambig_ix = text.index('line') elif 'lines' in text: ambig_ix = text.index('lines') else: ldjal targets.append(ambig_ix) labels.append(label) texts.append(text) return (labels, targets, texts) else: print '>>>> invalid input !!! <<<<<' """ computes f1-score of the classification accuracy gold_labels - is a list of the gold labels predicted_labels - is a list of the predicted labels output is a tuple of the micro averaged score and the macro averaged score """ import sklearn.metrics #### changed method name from eval because of naming conflict with python keyword def eval_performance(gold_labels, predicted_labels): return ( sklearn.metrics.f1_score(gold_labels, predicted_labels, average='micro'), sklearn.metrics.f1_score(gold_labels, predicted_labels, average='macro') ) """ a helper method that takes a list of predictions and writes them to a file (1 prediction per line) predictions - list of predictions (strings) file_name - name of the output file """ def write_predictions(predictions, file_name): with open(file_name, 'w') as outh: for p in predictions: outh.write(p+'\n') """ Trains a naive bayes model with bag of words features and computes the accuracy on the test set train_texts, train_targets, train_labels are as described in read_dataset above The same thing applies to the reset of the parameters. """ def run_bow_naivebayes_classifier(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels): # control variables improved = True alpha = 0.04 silent = True # Part 2.1 (c_s/c_sw) c_s = dict.fromkeys(set(train_labels), 0) multiples = list(itertools.product(c_s.keys(), ['time', 'loss', 'export'])) c_sw = dict.fromkeys(multiples, 0) t_w = [each_word for each_text in train_texts for each_word in each_text] multiples = list(itertools.product(c_s.keys(), t_w)) t_sw = dict.fromkeys(multiples, 0) for idx, label in enumerate(train_labels): cur_text = train_texts[idx] # compute c_s c_s[label] += len(cur_text) # compute c_sw time_cnt = cur_text.count('time') loss_cnt = cur_text.count('loss') export_cnt = cur_text.count('export') c_sw[(label, 'time')] += time_cnt c_sw[(label, 'loss')] += loss_cnt c_sw[(label, 'export')] += export_cnt # compute t_sw (total occurances): of (label, word): occurances for each_word in cur_text: t_sw[(label, each_word)] += 1 # total # of distinct words: will be used for smoothing t_dw = Counter(t_w) if not silent: print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('s', 'cord', 'division', 'formation', 'phone', 'product', 'text') print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s)', c_s['cord'], c_s['division'], c_s['formation'], c_s['phone'], c_s['product'], c_s['text']) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,time)', c_sw[('cord', 'time')], c_sw[('division', 'time')], c_sw[('formation', 'time')], \ c_sw[('phone', 'time')], c_sw[('product', 'time')], c_sw[('text', 'time')]) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,loss)', c_sw[('cord', 'loss')], c_sw[('division', 'loss')], c_sw[('formation', 'loss')], \ c_sw[('phone', 'loss')], c_sw[('product', 'loss')], c_sw[('text', 'loss')]) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,export)', c_sw[('cord', 'export')], c_sw[('division', 'export')], c_sw[('formation', 'export')], \ c_sw[('phone', 'export')], c_sw[('product', 'export')], c_sw[('text', 'export')]) print '------------------------------------------------------------------------------------------' print ' total distinct words: %d ' % (len(t_dw.keys())) # Part 2.2 (p_s/p_ws) total_occurances = float(sum(c_s.values())) label_count = Counter(train_labels) p_s = {key: (value / float( sum( label_count.values() )) ) for key, value in label_count.iteritems()} if improved: p_ws = {key: ( (value + alpha) / \ (float(c_s[key[0]]) + alpha*len(t_dw.keys())) ) \ for key, value in c_sw.iteritems()} t_ws = {key: ( (value + alpha) / \ (float(c_s[key[0]]) + alpha*len(t_dw.keys())) ) \ for key, value in t_sw.iteritems()} else: p_ws = {key: (value / float(c_s[key[0]])) for key, value in c_sw.iteritems()} t_ws = {key: (value / float(c_s[key[0]])) for key, value in t_sw.iteritems()} # normalization steps norm_denominators = { 'time': 0.0, 'loss': 0.0, 'export': 0.0 } for key, value in p_ws.iteritems(): norm_denominators[key[1]] += value p_ws_norm = {key: (value / norm_denominators[key[1]]) for key, value in p_ws.iteritems()} p_ws = p_ws_norm if not silent: print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(s)', p_s['cord'], p_s['division'], p_s['formation'], p_s['phone'], p_s['product'], p_s['text']) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(time|s)', p_ws[('cord', 'time')], p_ws[('division', 'time')], p_ws[('formation', 'time')], \ p_ws[('phone', 'time')], p_ws[('product', 'time')], p_ws[('text', 'time')]) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(loss|s)', p_ws[('cord', 'loss')], p_ws[('division', 'loss')], p_ws[('formation', 'loss')], \ p_ws[('phone', 'loss')], p_ws[('product', 'loss')], p_ws[('text', 'loss')]) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(export|s)', p_ws[('cord', 'export')], p_ws[('division', 'export')], p_ws[('formation', 'export')], \ p_ws[('phone', 'export')], p_ws[('product', 'export')], p_ws[('text', 'export')]) # Part 2.3 (p_sxd, on the 1st line on test set) p_sxd = dict.fromkeys(c_s.keys(), 0.0) lp_sxd = dict.fromkeys(c_s.keys(), 0.0) cur_text = dev_texts[0] for key in p_sxd.keys(): # compute p for each class if improved: tp_sxd = p_s[key] tlp_sxd = log(p_s[key]) else: tp_sxd = p_s[key] # compute for each word for each_word in cur_text: if t_ws.has_key((key, each_word)): if improved: tp_sxd *= t_ws[(key, each_word)] tlp_sxd += log(t_ws[(key, each_word)]) else: tp_sxd *= t_ws[(key, each_word)] # add to the dict if improved: p_sxd[key] = tp_sxd lp_sxd[key] = tlp_sxd else: p_sxd[key] = tp_sxd if not silent: print '------------------------------------------------------------------------------------------' print ' %s | %s | %s | %s | %s | %s | %s |' % \ ('p(s|X)', p_sxd['cord'], p_sxd['division'], p_sxd['formation'], \ p_sxd['phone'], p_sxd['product'], p_sxd['text']) print '------------------------------------------------------------------------------------------' print ' 1st label in dev : %s ' % (dev_labels[0]) print ' 1st text in dev[:5]: %s ' % (dev_texts[0][:5]) if improved: print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('log(p(s|X))', lp_sxd['cord'], lp_sxd['division'], lp_sxd['formation'], \ lp_sxd['phone'], lp_sxd['product'], lp_sxd['text']) # Part 2.4: compute all the prob on the test dataset p_sx = list() for idx, text in enumerate(test_texts): t_prob = dict.fromkeys(c_s.keys(), 0.0) for key in t_prob.keys(): # compute p for each class if improved: tp_sxt = log(p_s[key]) else: tp_sxt = p_s[key] for each_word in text: if t_ws.has_key((key, each_word)): if improved: tp_sxt += log(t_ws[(key, each_word)]) else: tp_sxt *= t_ws[(key, each_word)] # add to the dict t_prob[key] = tp_sxt # add dict to the entire list p_sx.append(t_prob) # Part 2.4 (run the classifier for all) labels_predicted = list() for idx, label in enumerate(test_labels): maximum_probs = max(p_sx[idx].values()) label_prediction = [key for key, value in p_sx[idx].iteritems() if value == maximum_probs] label_prediction = random.choice(label_prediction) # based on the prob labels_predicted.append(label_prediction) naivebayes_performance = eval_performance(test_labels, labels_predicted) # save the implementation to the file with open('q4p2.txt', 'wb') as q4p2_output: for each_label in labels_predicted: q4p2_output.write(each_label+'\n') # Part 2.5 (do more tuning for the classifier) # - Laplace smoothing # - Log likelihoods if not silent: print '------------------------------------------------------------------------------------------' return 'Naive Bayes: micro/macro = [%.2f, %.2f] @ (alpha: %s)' % \ (naivebayes_performance[0]*100, naivebayes_performance[1]*100, alpha) ## extract all the distinct words from a set of texts ## return a dictionary {word:index} that maps each word to a unique index def extract_all_words(texts,prev_set=set()): all_words = prev_set for t in texts: for w in t: all_words.add(w) all_words_idx = {} for i,w in enumerate(all_words): all_words_idx[w] = i return all_words_idx ## extract all distinct labels from a dataset ## return a dictionary {label:index} that maps each label to a unique index def extract_all_labels(labels): distinct_labels = list(set(labels)) all_labels_idx = {} for i,l in enumerate(distinct_labels): all_labels_idx[l] = i return all_labels_idx ## construct a bow feature matrix for a set of instances ## the returned matrix has the size NUM_INSTANCES X NUM_FEATURES def extract_features(all_words_idx,all_labels_idx,texts): NUM_FEATURES = len(all_words_idx.keys()) NUM_INSTANCES = len(texts) features_matrix = np.zeros((NUM_INSTANCES,NUM_FEATURES)) for i,instance in enumerate(texts): for word in instance: if all_words_idx.get(word,None) is None: continue features_matrix[i][all_words_idx[word]] += 1 return features_matrix ## compute the feature vector for a set of words and a given label ## the features are computed as described in Slide #19 of: ## http://www.cs.umd.edu/class/fall2016/cmsc723/slides/slides_02.pdf def get_features_for_label(instance,label,class_labels): num_labels = len(class_labels) num_feats = len(instance) feats = np.zeros(len(instance)*num_labels+1) assert len(feats[num_feats*label:num_feats*label+num_feats]) == len(instance) feats[num_feats*label:num_feats*label+num_feats] = instance return feats ## get the predicted label for a given instance ## the predicted label is the one with the highest dot product of theta*feature_vector ## return the predicted label, the dot product scores for all labels and the features computed for all labels for that instance def get_predicted_label(inst,class_labels,theta): all_labels_scores = {} all_labels_features = {} for lbl in class_labels: feat_vec = get_features_for_label(inst,lbl,class_labels) assert len(feat_vec) == len(theta) all_labels_scores[lbl] = np.dot(feat_vec,theta) predicted_label = max(all_labels_scores.iteritems(), key=operator.itemgetter(1))[0] return predicted_label ## train the perceptron by iterating over the entire training dataset ## the algorithm is an implementation of the pseudocode from Slide #23 of: ## http://www.cs.umd.edu/class/fall2016/cmsc723/slides/slides_03.pdf def train_perceptron(train_features,train_labels,class_labels,num_features): NO_MAX_ITERATIONS = 20 np.random.seed(0) theta = np.zeros(num_features) print '# Training Instances:',len(train_features) num_iterations = 0 cnt_updates_total = 0 cnt_updates_prev = 0 m = np.zeros(num_features) print '# Total Updates / # Current Iteration Updates:' for piter in range(NO_MAX_ITERATIONS): shuffled_indices = np.arange(len(train_features)) np.random.shuffle(shuffled_indices) cnt_updates_crt = 0 for i in shuffled_indices: inst = train_features[i] actual_label = train_labels[i] predicted_label = get_predicted_label(inst,class_labels,theta) if predicted_label != actual_label: cnt_updates_total += 1 cnt_updates_crt += 1 theta = theta + get_features_for_label(inst,actual_label,class_labels) - get_features_for_label(inst,predicted_label,class_labels) m = m + theta num_iterations += 1 print cnt_updates_total,'/',cnt_updates_crt if cnt_updates_crt == 0: break theta = m/cnt_updates_total print '# Iterations:',piter print '# Iterations over instances:',num_iterations print '# Total Updates:',cnt_updates_total return theta ## return the predictions of the perceptron on a test set def test_perceptron(theta,test_features,test_labels,class_labels): predictions = [] for inst in test_features: predicted_label = get_predicted_label(inst,class_labels,theta) predictions.append(predicted_label) return predictions """ Trains a perceptron model with bag of words features and computes the accuracy on the test set train_texts, train_targets, train_labels are as described in read_dataset above The same thing applies to the reset of the parameters. """ def run_bow_perceptron_classifier(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels): all_words_idx = extract_all_words(train_texts) all_labels_idx = extract_all_labels(train_labels) num_features = len(all_words_idx.keys())*len(all_labels_idx.keys())+1 class_labels = all_labels_idx.values() train_features = extract_features(all_words_idx,all_labels_idx,train_texts) train_labels = map(lambda e: all_labels_idx[e],train_labels) test_features = extract_features(all_words_idx,all_labels_idx,test_texts) test_labels = map(lambda e: all_labels_idx[e],test_labels) for l in class_labels: inst = train_features[0] ffl = get_features_for_label(inst,l,class_labels) assert False not in (inst == ffl[l*len(inst):(l+1)*len(inst)]) theta = train_perceptron(train_features,train_labels,class_labels,num_features) test_predictions = test_perceptron(theta,test_features,test_labels,class_labels) eval_test = eval_performance(test_labels,test_predictions) inverse_labels_index = {} for k in all_labels_idx.keys(): inverse_labels_index[all_labels_idx[k]] = k test_predictions_names = map(lambda e: inverse_labels_index[e],test_predictions) with open('q3p3.txt', 'wb') as file_output: for each_label in test_predictions_names: file_output.write(each_label+'\n') return ('test-micro=%d%%, test-macro=%d%%' % (int(eval_test[0]*100),int(eval_test[1]*100))) """ Trains a naive bayes model with bag of words features + two additional features and computes the accuracy on the test set train_texts, train_targets, train_labels are as described in read_dataset above The same thing applies to the reset of the parameters. """ def run_extended_bow_naivebayes_classifier(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels): # control variables improved = True alpha = 0.04 silent = True RUN_EXP = 'Both' # set to 'B', None, or 'Both' # feature extensions (A) if 'A' in RUN_EXP: train_features, dev_features, test_features = get_feature_A(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels) for idx, each_text in enumerate(train_texts): each_text.append(str(float(train_features[idx]))) for idx, each_text in enumerate(dev_texts): each_text.append(str(float(dev_features[idx]))) for idx, each_text in enumerate(test_texts): each_text.append(str(float(test_features[idx]))) # feature extensions (B) elif 'B' in RUN_EXP: train_features, dev_features, test_features = get_feature_B(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels) for idx, each_text in enumerate(train_texts): each_text.append(str(int(train_features[idx]))) for idx, each_text in enumerate(dev_texts): each_text.append(str(int(dev_features[idx]))) for idx, each_text in enumerate(test_texts): each_text.append(str(int(test_features[idx]))) # feature extensions with both two A and B elif 'Both' in RUN_EXP: train_features_A, dev_features_A, test_features_A = get_feature_A(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels) train_features_B, dev_features_B, test_features_B = get_feature_B(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels) for idx, each_text in enumerate(train_texts): each_text.append(str(float(train_features_A[idx]))) each_text.append(str(int(train_features_B[idx]))) for idx, each_text in enumerate(dev_texts): each_text.append(str(float(dev_features_A[idx]))) each_text.append(str(intern(train_features_B[idx]))) for idx, each_text in enumerate(test_texts): each_text.append(str(float(test_features_A[idx]))) each_text.append(str(int(train_features_B[idx]))) else: train_features, dev_features, test_features = None, None, None if not silent: print ' extension of the Naive Bayes classifier w. feature set: [%s] ' % (RUN_EXP) print '------------------------------------------------------------------------------------------' # Part 2.1 (c_s/c_sw) c_s = dict.fromkeys(set(train_labels), 0) multiples = list(itertools.product(c_s.keys(), ['time', 'loss', 'export'])) c_sw = dict.fromkeys(multiples, 0) t_w = [each_word for each_text in train_texts for each_word in each_text] multiples = list(itertools.product(c_s.keys(), t_w)) t_sw = dict.fromkeys(multiples, 0) for idx, label in enumerate(train_labels): cur_text = train_texts[idx] # compute c_s c_s[label] += len(cur_text) # compute c_sw time_cnt = cur_text.count('time') loss_cnt = cur_text.count('loss') export_cnt = cur_text.count('export') c_sw[(label, 'time')] += time_cnt c_sw[(label, 'loss')] += loss_cnt c_sw[(label, 'export')] += export_cnt # compute t_sw (total occurances): of (label, word): occurances for each_word in cur_text: t_sw[(label, each_word)] += 1 # total # of distinct words: will be used for smoothing t_dw = Counter(t_w) if not silent: print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('s', 'cord', 'division', 'formation', 'phone', 'product', 'text') print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s)', c_s['cord'], c_s['division'], c_s['formation'], c_s['phone'], c_s['product'], c_s['text']) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,time)', c_sw[('cord', 'time')], c_sw[('division', 'time')], c_sw[('formation', 'time')], \ c_sw[('phone', 'time')], c_sw[('product', 'time')], c_sw[('text', 'time')]) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,loss)', c_sw[('cord', 'loss')], c_sw[('division', 'loss')], c_sw[('formation', 'loss')], \ c_sw[('phone', 'loss')], c_sw[('product', 'loss')], c_sw[('text', 'loss')]) print '{:<11} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} | {:<10} |'.\ format('c(s,export)', c_sw[('cord', 'export')], c_sw[('division', 'export')], c_sw[('formation', 'export')], \ c_sw[('phone', 'export')], c_sw[('product', 'export')], c_sw[('text', 'export')]) print '------------------------------------------------------------------------------------------' print ' total distinct words: %d ' % (len(t_dw.keys())) # Part 2.2 (p_s/p_ws) total_occurances = float(sum(c_s.values())) label_count = Counter(train_labels) p_s = {key: (value / float( sum( label_count.values() )) ) for key, value in label_count.iteritems()} if improved: p_ws = {key: ( (value + alpha) / \ (float(c_s[key[0]]) + alpha*len(t_dw.keys())) ) \ for key, value in c_sw.iteritems()} t_ws = {key: ( (value + alpha) / \ (float(c_s[key[0]]) + alpha*len(t_dw.keys())) ) \ for key, value in t_sw.iteritems()} else: p_ws = {key: (value / float(c_s[key[0]])) for key, value in c_sw.iteritems()} t_ws = {key: (value / float(c_s[key[0]])) for key, value in t_sw.iteritems()} # normalization steps norm_denominators = { 'time': 0.0, 'loss': 0.0, 'export': 0.0 } for key, value in p_ws.iteritems(): norm_denominators[key[1]] += value p_ws_norm = {key: (value / norm_denominators[key[1]]) for key, value in p_ws.iteritems()} p_ws = p_ws_norm if not silent: print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(s)', p_s['cord'], p_s['division'], p_s['formation'], p_s['phone'], p_s['product'], p_s['text']) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(time|s)', p_ws[('cord', 'time')], p_ws[('division', 'time')], p_ws[('formation', 'time')], \ p_ws[('phone', 'time')], p_ws[('product', 'time')], p_ws[('text', 'time')]) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(loss|s)', p_ws[('cord', 'loss')], p_ws[('division', 'loss')], p_ws[('formation', 'loss')], \ p_ws[('phone', 'loss')], p_ws[('product', 'loss')], p_ws[('text', 'loss')]) print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('p(export|s)', p_ws[('cord', 'export')], p_ws[('division', 'export')], p_ws[('formation', 'export')], \ p_ws[('phone', 'export')], p_ws[('product', 'export')], p_ws[('text', 'export')]) # Part 2.3 (p_sxd, on the 1st line on test set) p_sxd = dict.fromkeys(c_s.keys(), 0.0) lp_sxd = dict.fromkeys(c_s.keys(), 0.0) cur_text = dev_texts[0] for key in p_sxd.keys(): # compute p for each class if improved: tp_sxd = p_s[key] tlp_sxd = log(p_s[key]) else: tp_sxd = p_s[key] # compute for each word for each_word in cur_text: if t_ws.has_key((key, each_word)): if improved: tp_sxd *= t_ws[(key, each_word)] tlp_sxd += log(t_ws[(key, each_word)]) else: tp_sxd *= t_ws[(key, each_word)] # add to the dict if improved: p_sxd[key] = tp_sxd lp_sxd[key] = tlp_sxd else: p_sxd[key] = tp_sxd if not silent: print '------------------------------------------------------------------------------------------' print ' %s | %s | %s | %s | %s | %s | %s |' % \ ('p(s|X)', p_sxd['cord'], p_sxd['division'], p_sxd['formation'], \ p_sxd['phone'], p_sxd['product'], p_sxd['text']) print '------------------------------------------------------------------------------------------' print ' 1st label in dev : %s ' % (dev_labels[0]) print ' 1st text in dev[:5]: %s ' % (dev_texts[0][:5]) if improved: print '------------------------------------------------------------------------------------------' print '{:<11} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} | {:<10.8f} |'.\ format('log(p(s|X))', lp_sxd['cord'], lp_sxd['division'], lp_sxd['formation'], \ lp_sxd['phone'], lp_sxd['product'], lp_sxd['text']) # Part 2.4: compute all the prob on the test dataset p_sx = list() for idx, text in enumerate(test_texts): t_prob = dict.fromkeys(c_s.keys(), 0.0) for key in t_prob.keys(): # compute p for each class if improved: tp_sxt = log(p_s[key]) else: tp_sxt = p_s[key] for each_word in text: if t_ws.has_key((key, each_word)): if improved: tp_sxt += log(t_ws[(key, each_word)]) else: tp_sxt *= t_ws[(key, each_word)] # add to the dict t_prob[key] = tp_sxt # add dict to the entire list p_sx.append(t_prob) # Part 2.4 (run the classifier for all) labels_predicted = list() for idx, label in enumerate(test_labels): maximum_probs = max(p_sx[idx].values()) label_prediction = [key for key, value in p_sx[idx].iteritems() if value == maximum_probs] label_prediction = random.choice(label_prediction) # based on the prob labels_predicted.append(label_prediction) naivebayes_performance = eval_performance(test_labels, labels_predicted) # save the implementation to the file with open('q4p4_nb.txt', 'wb') as q4p4_nb_output: for each_label in labels_predicted: q4p4_nb_output.write(each_label+'\n') # Part 2.5 (do more tuning for the classifier) # - Laplace smoothing # - Log likelihoods if not silent: print '------------------------------------------------------------------------------------------' return 'Naive Bayes: micro/macro = [%.2f, %.2f] @ (alpha: %s)' % \ (naivebayes_performance[0]*100, naivebayes_performance[1]*100, alpha) ## this feature is just a random number generated for each instance def get_feature_A(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_label): # call this everytime, makes the same random number np.random.seed(0) train_feature_vector = np.random.random_sample((len(train_texts),)) dev_feature_vector = np.random.random_sample((len(dev_texts),)) test_feature_vector = np.random.random_sample((len(test_texts),)) return train_feature_vector,dev_feature_vector,test_feature_vector ## this feature encodes the number of distinct words in each instance def get_feature_B(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_label): train_feature_vector = np.zeros(len(train_texts)) dev_feature_vector = np.zeros(len(dev_texts)) test_feature_vector = np.zeros(len(test_texts)) for i,text in enumerate(train_texts): nw = len(set(text)) train_feature_vector[i] = nw for i,text in enumerate(dev_texts): nw = len(set(text)) dev_feature_vector[i] = nw for i,text in enumerate(test_texts): nw = len(set(text)) test_feature_vector[i] = nw return train_feature_vector,dev_feature_vector,test_feature_vector """ Trains a perceptron model with bag of words features + two additional features and computes the accuracy on the test set train_texts, train_targets, train_labels are as described in read_dataset above The same thing applies to the reset of the parameters. """ def run_extended_bow_perceptron_classifier(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels): RUN_EXP_A = True # set to True for running on feature A RUN_EXP_B = True # set to True for running on feature B num_extra_features = 0 if RUN_EXP_A: train_new_feature_vectorA,dev_new_feature_vectorA,test_new_feature_vectorA = get_feature_A(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels) num_extra_features += 1 if RUN_EXP_B: train_new_feature_vectorB,dev_new_feature_vectorB,test_new_feature_vectorB = get_feature_B(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels) num_extra_features += 1 all_words_idx = extract_all_words(train_texts) all_labels_idx = extract_all_labels(train_labels) num_features = (len(all_words_idx.keys())+num_extra_features)*len(all_labels_idx.keys())+1 class_labels = all_labels_idx.values() train_features = extract_features(all_words_idx,all_labels_idx,train_texts) train_labels = map(lambda e: all_labels_idx[e],train_labels) test_features = extract_features(all_words_idx,all_labels_idx,test_texts) test_labels = map(lambda e: all_labels_idx[e],test_labels) if RUN_EXP_A: train_features = np.c_[train_features, train_new_feature_vectorA] test_features = np.c_[test_features, test_new_feature_vectorA] if RUN_EXP_B: train_features = np.c_[train_features, train_new_feature_vectorB] test_features = np.c_[test_features, test_new_feature_vectorB] for l in class_labels: inst = train_features[0] ffl = get_features_for_label(inst,l,class_labels) assert False not in (inst == ffl[l*len(inst):(l+1)*len(inst)]) theta = train_perceptron(train_features,train_labels,class_labels,num_features) test_predictions = test_perceptron(theta,test_features,test_labels,class_labels) eval_test = eval_performance(test_labels,test_predictions) inverse_labels_index = {} for k in all_labels_idx.keys(): inverse_labels_index[all_labels_idx[k]] = k test_predictions_names = map(lambda e: inverse_labels_index[e],test_predictions) with open('q4p4_pn.txt', 'wb') as file_output: for each_label in test_predictions_names: file_output.write(each_label+'\n') return ('test-micro=%d%%, test-macro=%d%%' % (int(eval_test[0]*100),int(eval_test[1]*100))) # Part 1.1 def run_most_frequent_class_classifier(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels): labels_freq = {} for l in train_labels: if labels_freq.get(l,None) is None: labels_freq[l] = 0 labels_freq[l] += 1 most_frequent_label = max(labels_freq.iteritems(), key=operator.itemgetter(1))[0] train_pred = [most_frequent_label]*len(train_labels) dev_pred = [most_frequent_label]*len(dev_labels) assert train_pred[2] == train_labels[2] eval_train = eval_performance(train_labels,train_pred) eval_dev = eval_performance(dev_labels,dev_pred) return ('training-micro=%d%%, training-macro=%d%%, dev-micro=%d%%, dev-macro=%d%%' % (int(eval_train[0]*100),int(eval_train[1]*100),int(eval_dev[0]*100),int(eval_dev[1]*100))) # Part 1.2 def run_inner_annotator_agreement(train_texts, train_targets,train_labels, dev_texts, dev_targets,dev_labels, test_texts, test_targets, test_labels): dev_labels_manual, dev_targets_manual, dev_texts_manual = read_dataset('dev_manual') return '%.2f' % sklearn.metrics.cohen_kappa_score(dev_labels[:20],dev_labels_manual) """ Main (able to change the classifier to other ones) """ if __name__ == "__main__": # reading, tokenizing, and normalizing data train_labels, train_targets, train_texts = read_dataset('train') dev_labels, dev_targets, dev_texts = read_dataset('dev') test_labels, test_targets, test_texts = read_dataset('test') #running the classifier test_scores = run_bow_perceptron_classifier(train_texts, train_targets, train_labels, dev_texts, dev_targets, dev_labels, test_texts, test_targets, test_labels) print test_scores

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null

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1

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4

a173546fb4be8c1b52e29b792d62de5b919bbc8f

97

py

Python

Python/Phani.py

baroood/Hacktoberfest-2k17

87383df4bf705358866a5a4120dd678a3f2acd3e

[ "MIT" ]

28

2017-10-04T19:42:26.000Z

2021-03-26T04:00:48.000Z

Python/Phani.py

baroood/Hacktoberfest-2k17

87383df4bf705358866a5a4120dd678a3f2acd3e

[ "MIT" ]

375

2017-09-28T02:58:37.000Z

2019-10-31T09:10:38.000Z

Python/Phani.py

baroood/Hacktoberfest-2k17

87383df4bf705358866a5a4120dd678a3f2acd3e

[ "MIT" ]

519

2017-09-28T02:40:29.000Z

2021-02-15T08:29:17.000Z

a = input("Enter the first number") b = input("Enter the second number") print('the sum is',a+b)

24.25

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1

0

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0

null

0

4

a1841c43709e67515946480883952c56edc55654

57

py

Python

run.py

JonLMyers/MetroTransitAPI

d8f467570368cd563d69564b680cfdd47ad6b622

[ "MIT" ]

null

run.py

JonLMyers/MetroTransitAPI

d8f467570368cd563d69564b680cfdd47ad6b622

[ "MIT" ]

null

run.py

JonLMyers/MetroTransitAPI

d8f467570368cd563d69564b680cfdd47ad6b622

[ "MIT" ]

null

""" Runs the server """ from aaxus import app app.run()

11.4

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9

57

4.111111

0.888889

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0.192982

57

4

24

14.25

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null

0

1

0

1

0

4

a1ab946e745fb18496c5d63e37229b34b0071a28

112

py

Python

libs/test_utils.py

bongnv/sublime-go

9f5f4f9795357ec595f73c1f71e479eca694b61e

[ "MIT" ]

6

2018-05-12T04:43:36.000Z

2018-09-21T17:44:53.000Z

libs/test_utils.py

bongnv/sublime-go

9f5f4f9795357ec595f73c1f71e479eca694b61e

[ "MIT" ]

null

libs/test_utils.py

bongnv/sublime-go

9f5f4f9795357ec595f73c1f71e479eca694b61e

[ "MIT" ]

null

import unittest class TestIsGoView(unittest.TestCase): def test_nil(self): self.assertFalse(None)

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38

0.723214

13

112

6.153846

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0.1875

112

6

39

18.666667

0.879121

0

0.25

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0.25

false

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null

0

1

0

null

0

1

0

1

0

4

a1d4680a92b1711d0003c4bd4a72a28789727f68

221

py

Python

Muta3DMaps/core/__init__.py

NatureGeorge/SIFTS_Plus_Muta_Maps

60f84e6024508e65ee3791103762b95666d3c646

[ "MIT" ]

null

Muta3DMaps/core/__init__.py

NatureGeorge/SIFTS_Plus_Muta_Maps

60f84e6024508e65ee3791103762b95666d3c646

[ "MIT" ]

null

Muta3DMaps/core/__init__.py

NatureGeorge/SIFTS_Plus_Muta_Maps

60f84e6024508e65ee3791103762b95666d3c646

[ "MIT" ]

null

# @Created Date: 2019-11-24 09:07:07 pm # @Filename: __init__.py # @Email: 1730416009@stu.suda.edu.cn # @Author: ZeFeng Zhu # @Last Modified: 2019-12-23 04:23:51 pm # @Copyright (c) 2019 MinghuiGroup, Soochow University

31.571429

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0.714932

36

221

4.277778

0.861111

0

0.219895

0.135747

221

6

55

36.833333

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null

0

1

0

4

62a6cdcc5cf9bca5a11b6dc4e9f38e91015abe52

502

py

Python

cortex/export/__init__.py

mvdoc/pycortex

bc8a93cac9518e3c1cd89650c703f9f3814e805b

[ "BSD-2-Clause" ]

423

2015-01-06T02:46:46.000Z

2022-03-23T17:20:38.000Z

cortex/export/__init__.py

mvdoc/pycortex

bc8a93cac9518e3c1cd89650c703f9f3814e805b

[ "BSD-2-Clause" ]

243

2015-01-03T02:10:03.000Z

2022-03-31T19:29:48.000Z

cortex/export/__init__.py

mvdoc/pycortex

bc8a93cac9518e3c1cd89650c703f9f3814e805b

[ "BSD-2-Clause" ]

136

2015-03-23T20:35:59.000Z

2022-03-09T13:39:10.000Z

from .save_views import save_3d_views from .panels import plot_panels from ._default_params import ( params_inflatedless_lateral_medial_ventral, params_flatmap_lateral_medial, params_occipital_triple_view, params_inflated_dorsal_lateral_medial_ventral, ) __all__ = [ "save_3d_views", "plot_panels", "params_flatmap_lateral_medial", "params_occipital_triple_view", "params_inflatedless_lateral_medial_ventral", "params_inflated_dorsal_lateral_medial_ventral", ]

27.888889

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502

6.016667

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0.221607

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0.004608

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17

53

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null

1

0

1

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null

0

4

62bd6807be95587bd7a23aaac66d6f7511aacb65

156

py

Python

tensorflowonspark/__init__.py

DerekRen/TensorFlowOnSpark

52dda7b006f2dd0d98f0cc5d362de555263623fd

[ "Apache-2.0" ]

1

2020-11-06T08:30:30.000Z

tensorflowonspark/__init__.py

DerekRen/TensorFlowOnSpark

52dda7b006f2dd0d98f0cc5d362de555263623fd

[ "Apache-2.0" ]

null

tensorflowonspark/__init__.py

DerekRen/TensorFlowOnSpark

52dda7b006f2dd0d98f0cc5d362de555263623fd

[ "Apache-2.0" ]

null

import logging logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s (%(threadName)s-%(process)d) %(message)s") __version__ = "2.2.0"

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156

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null

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1

0

4

62dd4a508db411e5b7ff314613aafdeaeb5656d2

376

py

Python

muon/__init__.py

WeilerP/muon

8e0988f07ae23be4fa913bb297ef059e5ab702a0

[ "BSD-3-Clause" ]

null

muon/__init__.py

WeilerP/muon

8e0988f07ae23be4fa913bb297ef059e5ab702a0

[ "BSD-3-Clause" ]

null

muon/__init__.py

WeilerP/muon

8e0988f07ae23be4fa913bb297ef059e5ab702a0

[ "BSD-3-Clause" ]

null

"""Multimodal omics analysis framework""" from ._core.mudata import MuData from ._core import preproc as pp from ._core import tools as tl from ._core import plot as pl from ._core import utils from ._core.io import * from ._core.config import set_options from . import atac from . import prot __version__ = "0.1.0" __mudataversion__ = "0.1.0" __anndataversion__ = "0.1.0"

22.117647

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4.474576

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0

0.028302

0.154255

376

16

42

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null

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null

0

1

0

1

0

4

1a018ecb1b4832d82200c28fb3048b3345de111f

33

py

Python

gmocoin/__init__.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

null

gmocoin/__init__.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

null

gmocoin/__init__.py

makotookamura/GmoCoin

025d3e68364bf52418dbc3445987ff21528db732

[ "Apache-2.0" ]

1

2021-07-17T16:56:03.000Z

#!python3 __version__ = '0.0.12'

11

22

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5

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3.6

0.8

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0.121212

33

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16.5

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1

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null

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4

1a11560f409eb43a0ed24b3b54e89719dbd21b76

171

py

Python

Theseus/Tests/__init__.py

amias-iohk/theseus

88d9294721e3bbbb756b983f55df6d669e632da4

[ "MIT" ]

4

2018-08-08T07:11:29.000Z

2018-11-08T02:43:11.000Z

Theseus/Tests/__init__.py

amias-iohk/theseus

88d9294721e3bbbb756b983f55df6d669e632da4

[ "MIT" ]

null

Theseus/Tests/__init__.py

amias-iohk/theseus

88d9294721e3bbbb756b983f55df6d669e632da4

[ "MIT" ]

3

2018-10-18T13:42:24.000Z

2021-01-20T15:21:25.000Z

__author__ = 'Amias Channer <amias.channer@iohk.io> for IOHK' __doc__ = 'Daedalus Testing functions' from .Cardano import * from .Daedalus import * from .Common import *

24.428571

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4

1a12b43b837e725bb85bfe8e14b6c166c2be8e99

691

py

Python

model/sample/adg.py

sdy99/PowerAI

ef40bacddbad72322e3e423417ae13d478d56a6d

[ "MIT" ]

7

2020-04-11T03:28:50.000Z

2021-03-29T14:53:36.000Z

model/sample/adg.py

sdy99/PowerAI

ef40bacddbad72322e3e423417ae13d478d56a6d

[ "MIT" ]

null

model/sample/adg.py

sdy99/PowerAI

ef40bacddbad72322e3e423417ae13d478d56a6d

[ "MIT" ]

5

2020-04-11T03:28:52.000Z

2021-11-27T05:23:12.000Z

# coding: gbk """ @author: sdy @email: sdy@epri.sgcc.com.cn Abstract distribution and generation class """ class ADG(object): def __init__(self, work_path, fmt): self.work_path = work_path self.fmt = fmt self.features = None self.mode = 'all' def distribution_assess(self): raise NotImplementedError def generate_all(self): raise NotImplementedError def choose_samples(self, size): raise NotImplementedError def generate_one(self, power, idx, out_path): raise NotImplementedError def remove_samples(self): raise NotImplementedError def done(self): raise NotImplementedError

20.323529

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0.662808

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691

5.705128

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0.208989

0

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691

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0

null

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null

0

1

0

4

a7de746c56c67620e56b1437e51a6c5e5965554a

1,102

py

Python

rssfly/tests/common.py

lidavidm/rssfly

1cfb893a249e4095412b966a1bf50fc3de7744e7

[ "Apache-2.0" ]

1

2021-02-14T03:44:35.000Z

rssfly/tests/common.py

lidavidm/rssfly

1cfb893a249e4095412b966a1bf50fc3de7744e7

[ "Apache-2.0" ]

6

2021-07-15T13:03:19.000Z

2022-03-26T14:14:14.000Z

rssfly/tests/common.py

lidavidm/rssfly

1cfb893a249e4095412b966a1bf50fc3de7744e7

[ "Apache-2.0" ]

null

# Copyright 2021 David Li # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os from pathlib import Path from typing import Dict class FakeContext: def __init__(self, urls: Dict[str, str]): self._urls = urls def get_text(self, url, **kwargs): # TODO: raise proper error return self._urls[url] def get_bytes(self, url, **kwargs): # TODO: raise proper error return self._urls[url] def get_test_data(path: str) -> str: root = Path(os.environ.get("RSSFLY_TEST_DATA_ROOT", ".")) / path with root.open("rb") as f: return f.read()

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null

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1

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1

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4

a7f04cab3ce9aa87269ec6d3083f5676dec9b76a

421

py

Python

Algorithm/Mathematical/453. Minimum Moves to Equal Array Elements.py

smsubham/Data-Structure-Algorithms-Questions

45da68231907068ef4e4a0444ffdac69b337fa7c

[ "Apache-2.0" ]

null

Algorithm/Mathematical/453. Minimum Moves to Equal Array Elements.py

smsubham/Data-Structure-Algorithms-Questions

45da68231907068ef4e4a0444ffdac69b337fa7c

[ "Apache-2.0" ]

null

Algorithm/Mathematical/453. Minimum Moves to Equal Array Elements.py

smsubham/Data-Structure-Algorithms-Questions

45da68231907068ef4e4a0444ffdac69b337fa7c

[ "Apache-2.0" ]

null

# https://leetcode.com/problems/minimum-moves-to-equal-array-elements/ # Explanation: https://leetcode.com/problems/minimum-moves-to-equal-array-elements/discuss/93817/It-is-a-math-question # Source: https://leetcode.com/problems/minimum-moves-to-equal-array-elements/discuss/272994/Python-Greedy-Sum-Min*Len class Solution: def minMoves(self, nums: List[int]) -> int: return sum(nums) - min(nums)*len(nums)

60.142857

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421

5.112903

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0

4

a7fa41d77e47cb4e42dcb175ead24d162418cceb

363

py

Python

Python Backend/diarization/build/lib/s4d/__init__.py

AdityaK1211/Final_Year_Project_SCET

1a6092e1345dad473375ada787fb5cb00ee7515f

[ "MIT" ]

1

2022-02-15T02:49:22.000Z

Python Backend/diarization/build/lib/s4d/__init__.py

AdityaK1211/Final_Year_Project_SCET

1a6092e1345dad473375ada787fb5cb00ee7515f

[ "MIT" ]

null

Python Backend/diarization/build/lib/s4d/__init__.py

AdityaK1211/Final_Year_Project_SCET

1a6092e1345dad473375ada787fb5cb00ee7515f

[ "MIT" ]

2

2021-07-11T12:42:43.000Z

2022-02-15T02:49:24.000Z

__author__ = 'meignier' import s4d.clustering.hac_bic import s4d.clustering.hac_clr import s4d.clustering.hac_iv import s4d.clustering.hac_utils import s4d.model_iv from s4d.clustering.cc_iv import ConnectedComponent from s4d.diar import Diar from s4d.segmentation import sanity_check, bic_linear, div_gauss from s4d.viterbi import Viterbi __version__ = "0.0.1"

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4

c50ac3b029d23e93f95a2998c1cb8c9b33f3b8ee

294

py

Python

core/middleware/scheduler.py

jiangxuewen16/hq-crawler

f03ec1e454513307e335943f224f4d927eaf2bbf

[ "MIT" ]

1

2021-02-25T08:33:40.000Z

core/middleware/scheduler.py

jiangxuewen16/hq-crawler

f03ec1e454513307e335943f224f4d927eaf2bbf

[ "MIT" ]

null

core/middleware/scheduler.py

jiangxuewen16/hq-crawler

f03ec1e454513307e335943f224f4d927eaf2bbf

[ "MIT" ]

2

2021-03-08T07:25:16.000Z

2021-12-07T15:28:02.000Z

from django.utils.deprecation import MiddlewareMixin from django.utils.autoreload import logger class Scheduler(MiddlewareMixin): def process_request(self, request): pass # logger.info(request) def process_response(self, request, response): return response

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null

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1

0

1

0

4

c522238afd1828d1190c7360573f7b8dc442a5a0

1,537

py

Python

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

6

2019-07-09T19:40:01.000Z

2022-01-24T12:01:37.000Z

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

null

SourceWatch/buffer.py

spezifanta/SourceWatch

aaf2cf1ba00015947689181daf77b80bde9b4feb

[ "MIT" ]

1

2020-11-07T13:06:58.000Z

import io import struct class SteamPacketBuffer(io.BytesIO): """In-memory byte buffer.""" def __len__(self): return len(self.getvalue()) def __repr__(self): return '<PacketBuffer: {}: {}>'.format(len(self), self.getvalue()) def __str__(self): return str(self.getvalue()) def read_byte(self): return struct.unpack('<B', self.read(1))[0] def write_byte(self, value): self.write(struct.pack('<B', value)) def read_short(self): return struct.unpack('<h', self.read(2))[0] def write_short(self, value): self.write(struct.pack('<h', value)) def read_float(self): return struct.unpack('<f', self.read(4))[0] def write_float(self, value): self.write(struct.pack('<f', value)) def read_long(self): return struct.unpack('<l', self.read(4))[0] def write_long(self, value): self.write(struct.pack('<l', value)) def read_long_long(self): return struct.unpack('<Q', self.read(8))[0] def write_long_long(self, value): self.write(struct.pack('<Q', value)) def read_string(self): # TODO: find a more pythonic way doing this value = [] while True: char = self.read(1) if char == b'\x00': break else: value.append(char) return ''.join(map(lambda char: chr(ord(char)), value)) def write_string(self, value): self.write(bytearray('{0}\x00'.format(value), 'utf-8'))

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null

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1

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1

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1

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4

c53ebab62d8ce95d55ec92330a072c34d445b216

296

py

Python

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

188

2017-11-27T18:59:34.000Z

2021-12-31T02:28:33.000Z

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

95

2017-11-13T01:21:48.000Z

2020-10-30T06:38:14.000Z

tests/polynomials.py

mernst/cozy

d7b2c0ee575057dea4ebec201d579f0ecd785b1b

[ "Apache-2.0" ]

16

2018-02-13T04:49:09.000Z

2021-02-06T13:26:46.000Z

import unittest from cozy.polynomials import Polynomial class TestPolynomials(unittest.TestCase): def test_sorting(self): self.assertLess(Polynomial([2019, 944, 95]), Polynomial([2012, 945, 95])) self.assertGreater(Polynomial([2012, 945, 95]), Polynomial([2019, 944, 95]))

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9

85

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null

0

1

0

1

0

4

c55a6c83c0c4deda47ef169a2a79ced739a7f4c8

106

py

Python

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

src/invoice_medicine/apps.py

vandana0608/Pharmacy-Managament

f99bdec11c24027a432858daa19247a21cecc092

[ "bzip2-1.0.6" ]

null

from django.apps import AppConfig class InvoiceMedicineConfig(AppConfig): name = 'invoice_medicine'

17.666667

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0.792453

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106

7.545455

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0.141509

106

5

40

21.2

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0

1

0

false

0

0.333333

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1

0

1

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null

0

1

0

null

0

1

0

1

0

4

c570fd6a05953760ae560c4fbed0f8ac9f2fd02d

100

py

Python

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

src/cattrs/errors.py

aha79/cattrs

50ba769c8349f5891b157d2bb7f06602822ac0a3

[ "MIT" ]

null

from cattr.errors import StructureHandlerNotFoundError __all__ = ["StructureHandlerNotFoundError"]

25

54

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7

100

11.714286

0.857143

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0.08

100

3

55

33.333333

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0

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0.5

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1

null

0

1

0

null

0

1

0

4

3dfe1030cd691567d0eb0ceab815ccdf039f3393

269

py

Python

python-crypt-service/services/dbservice.py

Shirish-Singh/crypt-analysis

eed6d00925389ee0973733e6b7397cd460f97f99

[ "Apache-2.0" ]

null

python-crypt-service/services/dbservice.py

Shirish-Singh/crypt-analysis

eed6d00925389ee0973733e6b7397cd460f97f99

[ "Apache-2.0" ]

null

python-crypt-service/services/dbservice.py

Shirish-Singh/crypt-analysis

eed6d00925389ee0973733e6b7397cd460f97f99

[ "Apache-2.0" ]

null

from __future__ import print_function from configurations import configuration from pymongo import MongoClient MONGO_HOST= configuration.MONGO_HOST client = MongoClient(MONGO_HOST) class DBConnection(): def getConnection(self): return client.analyticsDB

20.692308

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269

7.033333

0.633333

0.127962

0.189573

0

0.141264

269

12

41

22.416667

0.91342

0

1

0.125

false

0

0.375

0.125

0.75

0.125

0

null

0

1

0

null

0

1

0

4

9a91a0bb1c2222107ec4d2fbb68724bb0b797301

247

py

Python

paperplane/backends/click/choice.py

abhilash1in/paperplane

1dfda182dc8a70fe08fa2284ea63b434246c394b

[ "MIT" ]

null

paperplane/backends/click/choice.py

abhilash1in/paperplane

1dfda182dc8a70fe08fa2284ea63b434246c394b

[ "MIT" ]

null

paperplane/backends/click/choice.py

abhilash1in/paperplane

1dfda182dc8a70fe08fa2284ea63b434246c394b

[ "MIT" ]

null

import click from typing import Any, Optional from paperplane.backends.click import _prompt def run(prompt: str, choices: list, default: Optional[Any] = None): return _prompt(text=prompt, default=default, type=click.Choice(choices=choices))

30.875

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247

5.588235

0.588235

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0.121457

247

7

85

35.285714

0.875576

0

1

0.2

false

0

0.6

0.2

1

0

null

0

1

0

null

0

1

0

4

9aa8e28e915cdb48539530ca48ffdc1fa280bc82

140

py

Python

setup.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

27

2018-06-04T19:11:42.000Z

2022-02-23T22:46:39.000Z

setup.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

7

2018-06-09T15:27:51.000Z

2021-03-11T20:00:35.000Z

setup.py

adrienbrunet/mixt

d725ec752ce430d135e993bc988bfdf2b8457c4b

[ "MIT" ]

3

2018-07-29T10:20:02.000Z

2021-11-18T19:55:07.000Z

#!/usr/bin/env python """Setup file for the ``mixt`` module. Configuration is in ``setup.cfg``.""" from setuptools import setup setup()

15.555556

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140

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0.85

0

0.15

140

8

77

17.5

0.798319

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0

1

0

true

0

0.5

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0

null

0

1

0

1

0

4

9aaf20b86321deb4ac2d2c3951af5c3c52764470

115

py

Python

rplint/__main__.py

lpozo/rplint

907cb5342827b2c38e79721bc2dc99b3b6f7912b

[ "MIT" ]

7

2020-09-10T15:39:07.000Z

2021-02-15T17:45:04.000Z

rplint/__main__.py

lpozo/rplint

907cb5342827b2c38e79721bc2dc99b3b6f7912b

[ "MIT" ]

6

2020-11-11T02:42:37.000Z

2021-03-17T01:00:27.000Z

rplint/__main__.py

lpozo/rplint

907cb5342827b2c38e79721bc2dc99b3b6f7912b

[ "MIT" ]

3

2020-11-11T02:10:22.000Z

2020-12-12T01:02:29.000Z

#!/usr/bin/env python3 from .main import rplint if __name__ == "__main__": rplint.main(prog_name=__package__)

19.166667

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115

4.4375

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0

0.010101

0.13913

115

5

39

23

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0

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0

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true

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0

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null

0

1

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1

0

4

9ac1c767370071e77aa1a0a522794a49b7886db3

205

py

Python

python/test/is_prime.test.py

hotate29/kyopro_lib

20085381372d2555439980c79887ca6b0809bb77

[ "MIT" ]

null

python/test/is_prime.test.py

hotate29/kyopro_lib

20085381372d2555439980c79887ca6b0809bb77

[ "MIT" ]

2

2020-10-13T17:02:12.000Z

2020-10-17T16:04:48.000Z

python/test/is_prime.test.py

hotate29/kyopro_lib

20085381372d2555439980c79887ca6b0809bb77

[ "MIT" ]

null

# verification-helper: PROBLEM http://judge.u-aizu.ac.jp/onlinejudge/description.jsp?id=ALDS1_1_C from python.lib.is_prime import isprime print(sum(isprime(int(input())) for _ in range(int(input()))))

25.625

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205

4.575758

0.909091

0.10596

0

0.010638

0.082927

205

7

98

29.285714

0.792553

0.463415

0

1

0

true

0

0.5

0

0.5

0

null

0

1

0

null

0

1

0

1

0

1

0

4

9acd4db9f55911f16eb79b057e6fc8abf0b3c6d4

210

py

Python

resident/views.py

felipeue/SmartBuilding

57d904c6166c87f836bc8fada9eb5a2bc82069b8

[ "MIT" ]

null

resident/views.py

felipeue/SmartBuilding

57d904c6166c87f836bc8fada9eb5a2bc82069b8

[ "MIT" ]

null

resident/views.py

felipeue/SmartBuilding

57d904c6166c87f836bc8fada9eb5a2bc82069b8

[ "MIT" ]

null

from django.views.generic import TemplateView from main.permissions import ResidentLoginRequiredMixin class DashboardView(ResidentLoginRequiredMixin, TemplateView): template_name = "index_dashboard.html"

30

62

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6

63

35

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false

0

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0

1

0

null

0

1

0

1

0

4

9ae1bc0d9c8249afc93cd2e786ee58fa70373ce4

2,544

py

Python

tests/importing/test_read_genes.py

EKingma/Transposonmapper

1413bda16a0bd5f5f3ccf84d86193c2dba0ab01b

[ "Apache-2.0" ]

2

2021-11-23T09:39:35.000Z

2022-01-25T15:49:45.000Z

tests/importing/test_read_genes.py

EKingma/Transposonmapper

1413bda16a0bd5f5f3ccf84d86193c2dba0ab01b

[ "Apache-2.0" ]

76

2021-07-07T18:31:44.000Z

2022-03-22T10:04:40.000Z

tests/importing/test_read_genes.py

EKingma/Transposonmapper

1413bda16a0bd5f5f3ccf84d86193c2dba0ab01b

[ "Apache-2.0" ]

2

2021-09-16T10:56:20.000Z

2022-01-25T12:33:25.000Z

from transposonmapper.importing import ( load_default_files,read_genes ) def test_output_format(): a,b,c=load_default_files(gff_file=None,essentials_file=None,gene_names_file=None) a_0,b_0,c_0=read_genes(gff_file=a,essentials_file=b,gene_names_file=c) assert type(a_0)==dict, "the gene coordinates have to be a dict" assert type(b_0)==dict, "the gene coordinates have to be a dict" assert type(c_0)==dict, "the gene coordinates have to be a dict" def test_output_length(): a,b,c=load_default_files(gff_file=None,essentials_file=None,gene_names_file=None) a_0,b_0,c_0=read_genes(gff_file=a,essentials_file=b,gene_names_file=c) assert len(a_0)>=6600, "the total number of genes should not be less than 6600" assert len(b_0)<6600, "the total number of essential genes should not be more than the number of genes" assert len(c_0)>=6600, "the total number of genes should not be less than 6600" def test_output_content_gff(): a,b,c=load_default_files(gff_file=None,essentials_file=None,gene_names_file=None) a_0,b_0,c_0=read_genes(gff_file=a,essentials_file=b,gene_names_file=c) #read the first value of the dict first_value=next(iter(a_0.values())) # read the first key first_key=next(iter(a_0)) assert first_value==['I', 335, 649, '+'], "The first value of the gene coordinates is wrong" assert first_key== 'YAL069W', "The first gene in the array should be YAL069W" def test_output_content_essentials(): a,b,c=load_default_files(gff_file=None,essentials_file=None,gene_names_file=None) a_0,b_0,c_0=read_genes(gff_file=a,essentials_file=b,gene_names_file=c) #read the first value of the dict first_value=next(iter(b_0.values())) # read the first key first_key=next(iter(b_0)) assert first_value==['I', 147594, 151166, '-'], "The first value of the gene coordinates is wrong" assert first_key== 'YAL001C', "The first gene in the array should be YAL001C" def test_output_content_names(): a,b,c=load_default_files(gff_file=None,essentials_file=None,gene_names_file=None) a_0,b_0,c_0=read_genes(gff_file=a,essentials_file=b,gene_names_file=c) #read the first value of the dict first_value=next(iter(c_0.values())) # read the first key first_key=next(iter(c_0)) assert first_value==['AAC1'], "The first value of the gene names is wrong" assert first_key== 'YMR056C', "The first gene in the array should be YMR056C"

39.138462

107

0.717374

447

2,544

3.836689

0.14094

0.069971

0.075802

0.052478

0.797085

0.763848

0.738776

0.686297

0

0.040191

0.178459

2,544

65

108

39.138462

0.780383

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0

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0.333333

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0

null

0

1

0

1

0

null

0

4

9aff8c7e14210fed3124a5e6c2fdfe6fc51837d4

58

py

Python

contest/abc106/A.py

mola1129/atcoder

1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db

[ "MIT" ]

null

contest/abc106/A.py

mola1129/atcoder

1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db

[ "MIT" ]

null

contest/abc106/A.py

mola1129/atcoder

1d3b18cb92d0ba18c41172f49bfcd0dd8d29f9db

[ "MIT" ]

null

A, B = map(int, input().split()) print((A - 1) * (B - 1))

19.333333

32

0.465517

11

58

2.454545

0.727273

0

0.043478

0.206897

58

2

33

29

0.543478

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

4

b114d5a538b75c9a4b75747db2d55272076b7fcc

232

py

Python

oldcontrib/media/image/servee_registry.py

servee/django-servee-oldcontrib

836447ebbd53db0b53879a35468c02e57f65105f

[ "BSD-Source-Code" ]

null

oldcontrib/media/image/servee_registry.py

servee/django-servee-oldcontrib

836447ebbd53db0b53879a35468c02e57f65105f

[ "BSD-Source-Code" ]

null

oldcontrib/media/image/servee_registry.py

servee/django-servee-oldcontrib

836447ebbd53db0b53879a35468c02e57f65105f

[ "BSD-Source-Code" ]

null

from servee import frontendadmin from servee.frontendadmin.insert import ModelInsert from oldcontrib.media.image.models import Image class ImageInsert(ModelInsert): model = Image frontendadmin.site.register_insert(ImageInsert)

29

51

0.844828

27

232

7.222222

0.555556

0.102564

0

0.099138

232

8

52

29

0.933014

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1

0

false

0

0.5

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0.833333

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1

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null

0

1

0

null

0

1

0

1

0

4

b12709adc431ec818c3f1dc683d016b6ef1c240b

508

py

Python

mamba/exceptions.py

bmintz/mamba-lang

f63e205dc4de5e8ba3308e2b47b1675a9b508e70

[ "MIT" ]

20

2015-01-15T19:40:33.000Z

2021-09-22T15:26:27.000Z

mamba/exceptions.py

bmintz/mamba-lang

f63e205dc4de5e8ba3308e2b47b1675a9b508e70

[ "MIT" ]

3

2015-03-25T21:53:48.000Z

2017-05-07T12:22:20.000Z

mamba/exceptions.py

bmintz/mamba-lang

f63e205dc4de5e8ba3308e2b47b1675a9b508e70

[ "MIT" ]

11

2017-09-15T21:41:04.000Z

2021-09-22T15:15:58.000Z

class InterpreterException(Exception): def __init__(self, message): self.message = message def __str__(self): return self.message class SymbolNotFound(InterpreterException): pass class UnexpectedCharacter(InterpreterException): pass class ParserSyntaxError(InterpreterException): pass class DuplicateSymbol(InterpreterException): pass class InterpreterRuntimeError(InterpreterException): pass class InvalidParamCount(InterpreterRuntimeError): pass

16.933333

52

0.761811

40

508

9.475

0.4

0.316623

0.382586

0

0.177165

508

30

53

16.933333

0.906699

0

0.352941

0

1

0.117647

false

0.352941

0

0.058824

0.588235

0

null

1

0

null

0

1

0

1

0

4

b1318eb081bf81d3b2433e9aac0b4bedfc511b35

186

py

Python

notes/notebook/apps.py

spam128/notes

100008b7e0a2afa5677c15826588105027f52883

[ "MIT" ]

null

notes/notebook/apps.py

spam128/notes

100008b7e0a2afa5677c15826588105027f52883

[ "MIT" ]

null

notes/notebook/apps.py

spam128/notes

100008b7e0a2afa5677c15826588105027f52883

[ "MIT" ]

null

from django.apps import AppConfig from django.utils.translation import gettext_lazy as _ class NotebookConfig(AppConfig): name = "notes.notebook" verbose_name = _("Notebook")

20.666667

54

0.763441

22

186

6.272727

0.727273

0.144928

0

0.155914

186

8

55

23.25

0.878981

0

0.118919

0

1

0

false

0

0.4

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

b133ecf4dd2609e5dbd8da4502d3368bb3abe2c9

172

py

Python

test.py

uuidd/SimilarCharacter

22e5f4b0b2798d903435aeb989ff2d0a4ad59d70

[ "MIT" ]

199

2019-09-09T08:44:19.000Z

2022-03-24T12:42:04.000Z

test.py

uuidd/SimilarCharacter

22e5f4b0b2798d903435aeb989ff2d0a4ad59d70

[ "MIT" ]

4

2020-08-06T08:03:28.000Z

2022-01-06T15:14:36.000Z

test.py

uuidd/SimilarCharacter

22e5f4b0b2798d903435aeb989ff2d0a4ad59d70

[ "MIT" ]

58

2019-10-10T06:56:43.000Z

2022-03-21T02:58:01.000Z

import cv2 import ProcessWithCV2 img1 = cv2.imread("D:/py/chinese/7.png") img2 = cv2.imread("D:/py/chinese/8.png") a = ProcessWithCV2.dHash(img1, img2, 1) print(a)

21.5

41

0.686047

28

172

4.214286

0.571429

0.152542

0.169492

0.20339

0.322034

0

0.081081

0.139535

172

7

42

24.571429

0.716216

0

0.230303

0

1

0

false

0

0.333333

0

0.333333

0.166667

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null

0

1

0

1

0

null

0

1

0

4

b14a72da64d12a7c8066ba502beb5c9606168931

147

py

Python

Booleans/4.2.4 If/4.2.5 Fix the problem.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

Booleans/4.2.4 If/4.2.5 Fix the problem.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

Booleans/4.2.4 If/4.2.5 Fix the problem.py

ferrerinicolas/python_samples

107cead4fbee30b275a5e2be1257833129ce5e46

[ "MIT" ]

null

can_juggle = True # The code below has problems. See if # you can fix them! #if can_juggle print("I can juggle!") #else print("I can't juggle.")

16.333333

37

0.693878

27

147

3.703704

0.62963

0.27

0.18

0

0.183673

147

8

38

18.375

0.833333

0.632653

0

0.3125

0

1

0

false

0

0.5

1

0

null

1

0

1

0

null

0

1

0

4

b1542cd589e62fb7173b027c1b40c713b7897ca2

615

py

Python

sample_project/env/lib/python3.9/site-packages/qtpy/tests/test_qtprintsupport.py

Istiakmorsalin/ML-Data-Science

681e68059b146343ef55b0671432dc946970730d

[ "MIT" ]

4

2021-11-19T03:25:13.000Z

2022-02-24T15:32:30.000Z

sample_project/env/lib/python3.9/site-packages/qtpy/tests/test_qtprintsupport.py

Istiakmorsalin/ML-Data-Science

681e68059b146343ef55b0671432dc946970730d

[ "MIT" ]

null

sample_project/env/lib/python3.9/site-packages/qtpy/tests/test_qtprintsupport.py

Istiakmorsalin/ML-Data-Science

681e68059b146343ef55b0671432dc946970730d

[ "MIT" ]

3

2020-08-04T02:48:32.000Z

2020-08-17T01:20:09.000Z

from __future__ import absolute_import import pytest from qtpy import QtPrintSupport def test_qtprintsupport(): """Test the qtpy.QtPrintSupport namespace""" assert QtPrintSupport.QAbstractPrintDialog is not None assert QtPrintSupport.QPageSetupDialog is not None assert QtPrintSupport.QPrintDialog is not None assert QtPrintSupport.QPrintPreviewDialog is not None assert QtPrintSupport.QPrintEngine is not None assert QtPrintSupport.QPrinter is not None assert QtPrintSupport.QPrinterInfo is not None assert QtPrintSupport.QPrintPreviewWidget is not None

32.368421

59

0.782114

67

615

7.089552

0.343284

0.336842

0.151579

0.221053

0.427368

0

0.188618

615

18

60

34.166667

0.951904

0.061789

0

0.666667

1

0.083333

true

0

0.25

0

0.333333

0.083333

0

null

1

0

1

0

null

0

1

0

1

0

4

b16bfa5767e1c86af8aeaefb5fff8896cc5aa5cc

1,523

py

Python

dxlnmapclient/constants.py

camilastock/opendxl-nmap-client-python

2221adcb154a412c14925935159afc67ed9ba7a5

[ "Apache-2.0" ]

null

dxlnmapclient/constants.py

camilastock/opendxl-nmap-client-python

2221adcb154a412c14925935159afc67ed9ba7a5

[ "Apache-2.0" ]

null

dxlnmapclient/constants.py

camilastock/opendxl-nmap-client-python

2221adcb154a412c14925935159afc67ed9ba7a5

[ "Apache-2.0" ]

1

2018-02-12T18:20:18.000Z

60.92

88

0.169402

47

1,523

5.382979

0.553191

0.166008

0

0.512147

1,523

24

89

63.458333

0.340511

0.86671

0

0.07377

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

1

0

4

b16c522c8657dbedfb8cc24e18349f5784c77002

8,203

py

Python

2019/intcode/intcode/tests/test_intcode.py

Ganon11/AdventCode

eebf3413c8e73c45d0e0a65a80e57eaf594baead

[ "MIT" ]

null

2019/intcode/intcode/tests/test_intcode.py

Ganon11/AdventCode

eebf3413c8e73c45d0e0a65a80e57eaf594baead

[ "MIT" ]

null

2019/intcode/intcode/tests/test_intcode.py

Ganon11/AdventCode

eebf3413c8e73c45d0e0a65a80e57eaf594baead

[ "MIT" ]

null

import intcode def test_default_constructor(): # pylint: disable=C0116 values = [0, 1, 2, 0, 99] program = intcode.IntCodeProgram(values) assert program.instruction_pointer == 0 assert program.memory == values def test_noun_verb(): # pylint: disable=C0116 values = [0, 1, 2, 0, 99] program = intcode.IntCodeProgram(values) assert program.instruction_pointer == 0 assert program.memory == values program.set_noun(7) assert program.memory[1] == 7 program.set_verb(3) assert program.memory[2] == 3 def test_from_text(): # pylint: disable=C0116 values = [0, 1, 2, 0, 99] program = intcode.IntCodeProgram.from_text("0,1,2,0,99") assert program.instruction_pointer == 0 assert program.memory == values program2 = intcode.IntCodeProgram.from_text("0, 1, 2, 0, 99") assert program2.instruction_pointer == 0 assert program2.memory == values program3 = intcode.IntCodeProgram.from_text(" 0, 1 , 2 , 0, 99 ") assert program3.instruction_pointer == 0 assert program3.memory == values def test_execute_add(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1, 1, 2, 0, 99]) output = program.execute() assert output == 3 assert program.instruction_pointer == 4 def test_execute_mul(): # pylint: disable=C0116 program = intcode.IntCodeProgram([2, 1, 2, 0, 99]) output = program.execute() assert output == 2 assert program.instruction_pointer == 4 def test_execute_input(): # pylint: disable=C0116 values = [3, 0, 99] program = intcode.IntCodeProgram(values, user_input=[77]) output = program.execute() assert program.instruction_pointer == 2 assert program.memory[0] == 77 assert output == 77 program2 = intcode.IntCodeProgram(values, user_input=77) output2 = program2.execute() assert program2.instruction_pointer == 2 assert program2.memory[0] == 77 assert output2 == 77 def test_multiple_input(): # pylint: disable=C0116 values = [3, 0, 3, 1, 99] program = intcode.IntCodeProgram(values, user_input=[1, 2]) output = program.execute() assert program.instruction_pointer == 4 assert program.memory[0] == 1 assert program.memory[1] == 2 assert output == 1 program2 = intcode.IntCodeProgram(values, user_input=1) program2.provide_input(2) output2 = program2.execute() assert program2.instruction_pointer == 4 assert program2.memory[0] == 1 assert program2.memory[1] == 2 assert output2 == 1 def test_execute_output(): # pylint: disable=C0116 program = intcode.IntCodeProgram([4, 0, 99]) output = program.execute() assert program.instruction_pointer == 2 assert output == 4 assert len(program.output) == 1 assert 4 in program.output def test_execute_output_immediate_mode(): # pylint: disable=C0116 program = intcode.IntCodeProgram([104, 50, 99]) output = program.execute() assert program.instruction_pointer == 2 assert output == 104 assert len(program.output) == 1 assert 50 in program.output def test_execute_multiple_output(): # pylint: disable=C0116 program = intcode.IntCodeProgram([4, 0, 104, 50, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 4 assert len(program.output) == 2 assert 4 in program.output assert 50 in program.output def test_execute_add_immediate_mode(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1101, 50, 60, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 110 def test_execute_add_mixed_modes(): # pylint: disable=C0116 program = intcode.IntCodeProgram([101, 50, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 151 program = intcode.IntCodeProgram([1001, 0, 50, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 1051 def test_execute_mul_immediate_mode(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1102, 5, 6, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 30 def test_execute_mul_mixed_modes(): # pylint: disable=C0116 program = intcode.IntCodeProgram([102, 2, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 204 program = intcode.IntCodeProgram([1002, 0, 2, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 2004 def test_execute_jump_if_true(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1105, 1, 7, 1102, 0, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 7 assert output == 1105 program = intcode.IntCodeProgram([1105, 0, 7, 1102, 0, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 7 assert output == 0 def test_execute_jump_if_false(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1106, 1, 7, 1102, 0, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 7 assert output == 0 program = intcode.IntCodeProgram([1106, 0, 7, 1102, 0, 0, 0, 99]) output = program.execute() assert program.instruction_pointer == 7 assert output == 1106 def test_execute_less_than(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1107, 1, 2, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 1 program = intcode.IntCodeProgram([1107, 2, 2, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 0 program = intcode.IntCodeProgram([1107, 2, 1, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 0 def test_execute_equals(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1108, 1, 2, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 0 program = intcode.IntCodeProgram([1108, 2, 2, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 1 program = intcode.IntCodeProgram([1108, 2, 1, 0, 99]) output = program.execute() assert program.instruction_pointer == 4 assert output == 0 def test_step(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1108, 1, 2, 0, 1108, 2, 2, 0, 1108, 2, 1, 0, 99]) program.step() assert not program.has_halted assert program.instruction_pointer == 4 program.step() assert not program.has_halted assert program.instruction_pointer == 8 program.step() assert not program.has_halted assert program.instruction_pointer == 12 program.step() assert program.has_halted assert program.instruction_pointer == 12 def test_step_without_input_is_no_op(): # pylint: disable=C0116 program = intcode.IntCodeProgram([3, 1, 99]) program.step() assert program.instruction_pointer == 0 assert not program.has_halted program.provide_input(103) program.step() assert program.instruction_pointer == 2 assert not program.has_halted program.step() assert program.instruction_pointer == 2 assert program.has_halted def test_execute_will_return_early_if_waiting_for_input(): # pylint: disable=C0116 program = intcode.IntCodeProgram([3, 1, 99]) program.execute() assert not program.has_halted assert program.instruction_pointer == 0 program.provide_input(103) program.execute() assert program.instruction_pointer == 2 assert program.has_halted def test_update_relative_base(): # pylint: disable=C0116 program = intcode.IntCodeProgram([201, 2, 1, 17, 109, 17, 2201, 0, 0, 19, 99]) program.execute() assert program.instruction_pointer == 10 assert program.has_halted assert program._relative_base == 17 # pylint: disable=W0212 def test_increased_available_memory(): # pylint: disable=C0116 program = intcode.IntCodeProgram([1101, 1, 2, 17, 99]) program.execute() assert len(program.memory) == 18 assert program.instruction_pointer == 4 assert program.has_halted def test_reddit(): # pylint: disable=C0116 program = intcode.IntCodeProgram([109, 1, 203, 2, 204, 2, 99]) program.provide_input(77) program.execute() print(program) print(program.output) if __name__ == "__main__": test_reddit()

31.30916

85

0.720224

1,098

8,203

5.24408

0.098361

0.115144

0.15422

0.199201

0.80462

0.784995

0.661167

0.589614

0.491316

0.417332

0

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8,203

261

86

31.429119

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0

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0

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1

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false

0

0.004717

0

0.117925

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0

null

0

1

0

null

0

1

0

4

b17454e4938df93dd6729a10260ca6df34c9564c

84

py

Python

scripts/python/make-dist-cfg.py

brakmic/cm3

b99e280eca00c322e04e0586951de50108e51343

[ "BSD-4-Clause-UC", "BSD-4-Clause", "BSD-3-Clause" ]

2

2015-03-02T17:01:32.000Z

2021-12-29T14:34:46.000Z

scripts/python/make-dist-cfg.py

ganeshbabuNN/cm3

9fb432d44a2ba89575febb38f7c1eb3dca6a3879

[ "BSD-4-Clause-UC", "BSD-4-Clause", "BSD-3-Clause" ]

1

2015-07-23T07:51:22.000Z

scripts/python/make-dist-cfg.py

RodneyBates/M3Devel

7b8dd3fc8f5b05d1c69774d92234ea50d143a692

[ "BSD-4-Clause-UC", "BSD-4-Clause" ]

1

2021-12-29T14:35:47.000Z

#! /usr/bin/env python from pylib import * CopyConfigForDistribution(InstallRoot)

14

38

0.785714

9

84

7.333333

1

0

0.119048

84

5

39

16.8

0.891892

0.25

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

b1784fe113bca2d558cd14a80d284029cd03a532

92

py

Python

tests/samples/importing/nested/base.py

machinable-org/machinable

9d96e942dde05d68699bc7bc0c3d062ee18652ad

[ "MIT" ]

23

2020-02-28T14:29:04.000Z

2021-12-23T20:50:54.000Z

tests/samples/importing/nested/base.py

machinable-org/machinable

9d96e942dde05d68699bc7bc0c3d062ee18652ad

[ "MIT" ]

172

2020-02-24T12:12:11.000Z

2022-03-29T03:08:24.000Z

tests/samples/importing/nested/base.py

machinable-org/machinable

9d96e942dde05d68699bc7bc0c3d062ee18652ad

[ "MIT" ]

1

2020-11-23T22:42:20.000Z

from machinable import Component class BaseComponent(Component): """Base component"""

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b17998122b0c9414fb547e0a5c5bf8d5f8b4473a

63

py

Python

src/oscar/apps/customer/__init__.py

QueoLda/django-oscar

8dd992d82e31d26c929b3caa0e08b57e9701d097

[ "BSD-3-Clause" ]

4,639

2015-01-01T00:42:33.000Z

2022-03-29T18:32:12.000Z

src/oscar/apps/customer/__init__.py

QueoLda/django-oscar

8dd992d82e31d26c929b3caa0e08b57e9701d097

[ "BSD-3-Clause" ]

2,215

2015-01-02T22:32:51.000Z

2022-03-29T12:16:23.000Z

src/oscar/apps/customer/__init__.py

QueoLda/django-oscar

8dd992d82e31d26c929b3caa0e08b57e9701d097

[ "BSD-3-Clause" ]

2,187

2015-01-02T06:33:31.000Z

2022-03-31T15:32:36.000Z

default_app_config = 'oscar.apps.customer.apps.CustomerConfig'

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b17eab4940677c2202b0aa8a880f82fca874b795

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py

Python

examples/example_hello_world.py

clbarnes/figurefirst

ed38e246a96f28530bf663eb6920da1c3ccee610

[ "MIT" ]

67

2016-06-03T20:37:56.000Z

2022-03-08T19:05:06.000Z

examples/example_hello_world.py

clbarnes/figurefirst

ed38e246a96f28530bf663eb6920da1c3ccee610

[ "MIT" ]

56

2016-05-23T17:44:04.000Z

2021-11-18T19:23:52.000Z

examples/example_hello_world.py

clbarnes/figurefirst

ed38e246a96f28530bf663eb6920da1c3ccee610

[ "MIT" ]

11

2017-07-13T14:25:08.000Z

2021-12-01T00:15:01.000Z

#!/usr/bin/env python import numpy as np import matplotlib.pyplot as plt plt.ion() from figurefirst import FigureLayout layout = FigureLayout('example_hello_world_layout.svg') layout.make_mplfigures() d = np.array([[144, 57], [138, 57], [138, 59], [141, 61], [141, 82], [138, 84], [138, 85], [142, 85], [147, 85], [147, 84], [144, 82], [144, 57], [144, 57], [155, 57], [149, 57], [149, 59], [152, 61], [152, 82], [149, 84], [149, 85], [153, 85], [158, 85], [158, 84], [155, 82], [155, 57], [155, 57], [273, 57], [267, 57], [267, 59], [270, 61], [270, 82], [267, 84], [267, 85], [271, 85], [276, 85], [276, 84], [273, 82], [273, 57], [273, 57], [295, 57], [289, 57], [289, 59], [292, 61], [292, 70], [287, 67], [278, 76], [287, 85], [292, 83], [292, 85], [298, 85], [298, 84], [295, 81], [295, 57], [295, 57], [90, 57], [90, 59], [91, 59], [94, 61], [94, 82], [91, 84], [90, 84], [90, 85], [96, 85], [102, 85], [102, 84], [101, 84], [98, 82], [98, 71], [110, 71], [110, 82], [107, 84], [106, 84], [106, 85], [112, 85], [118, 85], [118, 84], [117, 84], [113, 82], [113, 61], [117, 59], [118, 59], [118, 57], [112, 58], [106, 57], [106, 59], [107, 59], [110, 61], [110, 70], [98, 70], [98, 61], [101, 59], [102, 59], [102, 57], [96, 58], [90, 57], [90, 57], [193, 57], [193, 59], [197, 60], [205, 85], [205, 86], [206, 85], [213, 65], [219, 85], [220, 86], [221, 85], [229, 61], [233, 59], [233, 57], [229, 58], [224, 57], [224, 59], [228, 61], [227, 62], [221, 80], [215, 60], [215, 60], [218, 59], [218, 57], [213, 58], [208, 57], [208, 59], [211, 60], [212, 63], [207, 80], [200, 60], [200, 60], [203, 59], [203, 57], [198, 58], [193, 57], [193, 57], [128, 67], [120, 76], [129, 85], [135, 80], [135, 80], [134, 80], [129, 84], [125, 82], [123, 76], [134, 76], [135, 75], [128, 67], [128, 67], [169, 67], [160, 76], [169, 85], [178, 76], [169, 67], [169, 67], [240, 67], [231, 76], [240, 85], [249, 76], [240, 67], [240, 67], [257, 67], [251, 68], [251, 69], [254, 71], [254, 82], [251, 84], [251, 85], [256, 85], [261, 85], [261, 84], [260, 84], [257, 82], [257, 75], [262, 68], [262, 68], [261, 70], [263, 71], [265, 70], [262, 67], [257, 71], [257, 67], [257, 67], [128, 68], [133, 75], [123, 75], [128, 68], [128, 68], [169, 68], [173, 70], [174, 76], [173, 81], [169, 84], [164, 82], [163, 76], [164, 70], [169, 68], [169, 68], [240, 68], [244, 70], [246, 76], [245, 81], [240, 84], [235, 82], [234, 76], [235, 70], [240, 68], [240, 68], [287, 68], [292, 70], [292, 72], [292, 80], [292, 82], [287, 84], [283, 82], [281, 76], [283, 71], [287, 68], [287, 68]]) ax = layout.axes['ax_name']['axis'] ax.plot(d[:,0], -d[:,1], lw=4) layout.insert_figures('target_layer_name') layout.write_svg('example_hello_world_output.svg')

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b1a93d370fc62aa987aa9250ab1bac4da3444f9c

35

py

Python

tests/__init__.py

jsta/nhdpy

38f52a68907e4d838715c77b18e61450eb775c72

[ "MIT" ]

null

tests/__init__.py

jsta/nhdpy

38f52a68907e4d838715c77b18e61450eb775c72

[ "MIT" ]

8

2020-11-12T16:42:23.000Z

2021-03-04T19:00:09.000Z

tests/__init__.py

jsta/nhdpy

38f52a68907e4d838715c77b18e61450eb775c72

[ "MIT" ]

null

"""Unit test package for nhdpy."""

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b1ac9e7af9abde201568a2b9eff7f851241bb02a

168

py

Python

configs/tsmnet/tsmnet_r50-d1_769x769_40k_cityscapes_video.py

labdeeman7/TRDP_temporal_stability_semantic_segmentation

efe0f13c2ed4e203d1caa41810e39e09152b508e

[ "Apache-2.0" ]

null

configs/tsmnet/tsmnet_r50-d1_769x769_40k_cityscapes_video.py

labdeeman7/TRDP_temporal_stability_semantic_segmentation

efe0f13c2ed4e203d1caa41810e39e09152b508e

[ "Apache-2.0" ]

null

configs/tsmnet/tsmnet_r50-d1_769x769_40k_cityscapes_video.py

labdeeman7/TRDP_temporal_stability_semantic_segmentation

efe0f13c2ed4e203d1caa41810e39e09152b508e

[ "Apache-2.0" ]

null

_base_ = [ '../_base_/models/tsm_r50-d8.py', '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py' ]

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