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<|fim_prefix|># repo: magnickolas/formal-grammars path: /formal_grammars/grammar.py from collections import defaultdict from collections import namedtuple from typing import NewType from typing import Union import yaml ## TYPES class Rule(namedtuple("Rule", ["left", "right"])): __slots__ = () def __repr__...
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{ "lang": "python", "repo": "magnickolas/formal-grammars", "path": "/formal_grammars/grammar.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def parse_rules(s): left, right = map(lambda x: "".join(x.split()), s.split(RULE_SEPARATOR)) right_parts = map( lambda x: "".join(x.split()), right.split(RULE_RIGHT_PARTS_SEPARATOR) ) return [Rule(left=left, right=right) for right in right_parts] EMPTY = Grammar["empty"] LAST = "...
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{ "lang": "python", "repo": "magnickolas/formal-grammars", "path": "/formal_grammars/grammar.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: LyonLee190/StringPullingMonitorLite path: /app/home/hardware_manager.py # Need to install advpistepper (have to be install by python setup.py) & hx711 (pip) import subprocess import logging import pigpio from hx711 import HX711 import sys from Motor import ULN2003 import busio import digitalio i...
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{ "lang": "python", "repo": "LyonLee190/StringPullingMonitorLite", "path": "/app/home/hardware_manager.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> else: # speed not equals to 0, run the motor with speed self.run_motor() speed.value = self.speed s.value = self.speed time.sleep(0.25) if self.distance.value >= steps: break # job...
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{ "lang": "python", "repo": "LyonLee190/StringPullingMonitorLite", "path": "/app/home/hardware_manager.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> fig, ax = plt.subplots() plt.title(title) ax.plot(numbers, data, label='steps') ax.plot(numbers, time_comp, dashes=[6, 2], label='time complexity') ax.legend() plt.show() if __name__ == '__main__': print(random_list(1024))<|fim_prefix|># repo: oierajenjo/q-Grover-Algorithm ...
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{ "lang": "python", "repo": "oierajenjo/q-Grover-Algorithm", "path": "/algorithm_comparison/utils.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> for i in range(0, n): numbers.append(2 ** i) fig, ax = plt.subplots() plt.title(title) ax.plot(numbers, data, label='steps') ax.plot(numbers, time_comp, dashes=[6, 2], label='time complexity') ax.legend() plt.show() if __name__ == '__main__': print(random_list(...
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{ "lang": "python", "repo": "oierajenjo/q-Grover-Algorithm", "path": "/algorithm_comparison/utils.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: oierajenjo/q-Grover-Algorithm path: /algorithm_comparison/utils.py import random import matplotlib.pyplot as plt def random_list(size): <|fim_suffix|> numbers = [] for i in range(0, n): numbers.append(2 ** i) fig, ax = plt.subplots() plt.title(title) ax.plot(numbe...
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{ "lang": "python", "repo": "oierajenjo/q-Grover-Algorithm", "path": "/algorithm_comparison/utils.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>@crawl_tasks.route('', methods=['POST']) @use_args(create_crawl_task_schema, locations=('json',)) def create_crawl_task(args): """ 创建爬虫任务 :param args: :return: """ crawl_task_biz = CrawlTaskBiz() data = crawl_task_biz.create_crawl_task(**args) return jsonify({ 'sta...
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{ "lang": "python", "repo": "turnsgreen/crawloop", "path": "/services/spider/webs/api/views/crawl_tasks.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """ 创建爬虫任务 :param args: :return: """ crawl_task_biz = CrawlTaskBiz() data = crawl_task_biz.create_crawl_task(**args) return jsonify({ 'status': True, 'data': data }), 201<|fim_prefix|># repo: turnsgreen/crawloop path: /services/spider/webs/api/views/cr...
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{ "lang": "python", "repo": "turnsgreen/crawloop", "path": "/services/spider/webs/api/views/crawl_tasks.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: turnsgreen/crawloop path: /services/spider/webs/api/views/crawl_tasks.py # -*- coding: utf-8 -*- from flask import Blueprint, jsonify from webargs.flaskparser import use_args from webs.api.bizs.crawl_task import CrawlTaskBiz from webs.api.schemas.crawl_tasks import create_crawl_task_schema <|f...
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{ "lang": "python", "repo": "turnsgreen/crawloop", "path": "/services/spider/webs/api/views/crawl_tasks.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> rm = Modification() assert Modification.is_zero(rm) == True rm.angle = 1. assert Modification.is_zero(rm) == False rm = Modification() assert Modification.is_zero(rm) == True rm.offset = Point(1., 0., 0.) assert Modification.is_zero(rm) ==...
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{ "lang": "python", "repo": "HuaiLeiTang/rosweld_tools", "path": "/src/tests/test_bead.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: HuaiLeiTang/rosweld_tools path: /src/tests/test_bead.py from ..rosweld.bead import Bead from ..rosweld.point import Point from ..rosweld.modification import Modification from ..rosweld.weldingstate import WeldingState class TestBead(object): def test_init(self): b1 = Bead(None, {}, {...
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{ "lang": "python", "repo": "HuaiLeiTang/rosweld_tools", "path": "/src/tests/test_bead.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> ws = WeldingState() ws.amperage = 111. rm.welding_parameters = ws assert Modification.is_zero(rm) == False rm = Modification() assert Modification.is_zero(rm) == True rm.angle = 1. assert Modification.is_zero(rm) == False rm = Modi...
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{ "lang": "python", "repo": "HuaiLeiTang/rosweld_tools", "path": "/src/tests/test_bead.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: uptick/gitops path: /gitops/utils/cli.py from colorama import Fore def colourise(value, colour, condition=None): """Colour a piece of text. If a condition callback is passed in, the text will only be coloured if the condition is met. """ if condition is not None: if not ...
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{ "lang": "python", "repo": "uptick/gitops", "path": "/gitops/utils/cli.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> def confirm_dangerous_command(): message = ( "You are about to execute a dangerous command against a" f" {colourise('production' , Fore.RED)} environment. Please ensure you are pairing with" " someone else." ) # TODO. Include an actual multi person MFA to proceed. ...
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{ "lang": "python", "repo": "uptick/gitops", "path": "/gitops/utils/cli.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: cieske/exercises path: /Beakjoon/1316.py n = int(input()) x = [] for i in range(n): s = str(input()) d <|fim_suffix|> s = s[num:] if d: x.append(1) print(x) print(x.count(1))<|fim_middle|>= True while len(s) != 0: num = s.count(s[0]) if s[:num].count(s[0]...
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{ "lang": "python", "repo": "cieske/exercises", "path": "/Beakjoon/1316.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> s = s[num:] if d: x.append(1) print(x) print(x.count(1))<|fim_prefix|># repo: cieske/exercises path: /Beakjoon/1316.py n = int(input()) x = [] for i in range(n): s = str(input()) d <|fim_middle|>= True while len(s) != 0: num = s.count(s[0]) if s[:num].count(s[0]...
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{ "lang": "python", "repo": "cieske/exercises", "path": "/Beakjoon/1316.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: finalwee/Cloudia path: /core/tool.py import os import subprocess import numpy as np from cv2 import cv2 import time class adbKit(): def __init__(self, device, NOX=False, debug=False) -> None: self.path = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) self.debug ...
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{ "lang": "python", "repo": "finalwee/Cloudia", "path": "/core/tool.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def load_template(self, img_path, template_list): imgs = [] for template in template_list: img = os.path.join(img_path, template) imgs.append(self.cv_read(img)) return imgs def compare(self, img_list, gach=False, acc=0.85): imgs = [] ...
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{ "lang": "python", "repo": "finalwee/Cloudia", "path": "/core/tool.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: lemonnader/LeetCode-Solution-Well-Formed path: /hash-table/Python/0454-4sum-ii-2.py from typing import List class Solution: def fourSumCount(self, A: List[int], B: List[int], C: List[int], D: List[int]) -> int: <|fim_suffix|> res = 0 for num1 in A: for num2 in B: ...
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{ "lang": "python", "repo": "lemonnader/LeetCode-Solution-Well-Formed", "path": "/hash-table/Python/0454-4sum-ii-2.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> res = 0 for num1 in A: for num2 in B: s = num1 + num2 if -s in hash_map: res += hash_map[-s] return res<|fim_prefix|># repo: lemonnader/LeetCode-Solution-Well-Formed path: /hash-table/Python/0454-4sum-ii-2.py from typ...
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{ "lang": "python", "repo": "lemonnader/LeetCode-Solution-Well-Formed", "path": "/hash-table/Python/0454-4sum-ii-2.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: cctbx/cctbx_project path: /mmtbx/command_line/map_to_structure_factors.py from __future__ import absolute_import, division, print_function # LIBTBX_SET_DISPATCHER_NAME phenix.map_to_structure_factors import iotbx.ccp4_map from cctbx.array_family import flex import mmtbx.utils import sys from lib...
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{ "lang": "python", "repo": "cctbx/cctbx_project", "path": "/mmtbx/command_line/map_to_structure_factors.py", "mode": "psm", "license": "BSD-3-Clause-LBNL", "source": "the-stack-v2" }
<|fim_suffix|> # shift_cart is shift away from (0,0,0) if new_origin != (0,0,0,): shift_cart=get_shift_cart(map_data=mm.map_data(), crystal_symmetry=mm.crystal_symmetry(), origin=new_origin) else: shift_cart=(0,0,0,) # Shift the map data if necessary mm.shift_origin() f_obs_cmpl = mm.map_as_f...
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{ "lang": "python", "repo": "cctbx/cctbx_project", "path": "/mmtbx/command_line/map_to_structure_factors.py", "mode": "spm", "license": "BSD-3-Clause-LBNL", "source": "the-stack-v2" }
<|fim_suffix|>class RegistrationForm(UserCreationForm): # extending from superclass email = forms.EmailField(required=True) # define meta data class Meta: model = User fields = ( 'username', 'first_name', 'last_name', 'email', 'p...
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{ "lang": "python", "repo": "MFOSSociety/NSP", "path": "/accounts/forms.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> model = User fields = ( 'username', 'first_name', 'last_name', 'email', 'password1', 'password2' ) def __init__(self, *args, **kwargs): super(RegistrationForm, self).__init__(*args, **kwargs) ...
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{ "lang": "python", "repo": "MFOSSociety/NSP", "path": "/accounts/forms.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: MFOSSociety/NSP path: /accounts/forms.py from django import forms from django.contrib.auth.forms import UserCreationForm, UserChangeForm from accounts.models import ( Skill, UserProfile, User, ) class ImageFileUploadForm(forms.ModelForm): class Meta: model = UserProfile...
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{ "lang": "python", "repo": "MFOSSociety/NSP", "path": "/accounts/forms.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gurizab/NAS_Predictors path: /naslib/search_spaces/nasbench101/graph.py import os import pickle import numpy as np import copy import random import torch import torch.nn as nn from naslib.search_spaces.core import primitives as ops from naslib.search_spaces.core.graph import Graph, EdgeData from...
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{ "lang": "python", "repo": "gurizab/NAS_Predictors", "path": "/naslib/search_spaces/nasbench101/graph.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> random.shuffle(nbhd) return nbhd def get_type(self): return 'nasbench101' def _set_node_ops(current_edge_data, C): ops = [ ReLUConvBN(C, C, kernel_size=1), # ops.Zero(stride=1), #! recheck about the hardcoded second operation ReLUConvBN(C, C...
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{ "lang": "python", "repo": "gurizab/NAS_Predictors", "path": "/naslib/search_spaces/nasbench101/graph.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> wait_on_job(jobids) if __name__=='__main__': import sys input = sys.argv[1] commands = ['qsub -v input=%s blat_job.sh' % (input)] print commands launch_job(commands)<|fim_prefix|># repo: RobinQi/BioUtils path: /qsub.py '''The code is a modified version of cluster_utils.py from M...
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{ "lang": "python", "repo": "RobinQi/BioUtils", "path": "/qsub.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: RobinQi/BioUtils path: /qsub.py '''The code is a modified version of cluster_utils.py from MISO package. ''' import time import subprocess def check_job(jobid): '''Returns True is a job is finished, otherwise False. ''' output = subprocess.Popen('qstat %i' %(jobid), ...
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{ "lang": "python", "repo": "RobinQi/BioUtils", "path": "/qsub.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> result = obj.findRuntime(values, params) # print( "RESULT: ", result ) return result x = np.array([point[f'p{i}'] for i in range(len(point))]) results = plopper_func(x) print('OUTPUT:%f',results) return results Problem = TuningProblem( task_space=None, input_space=input_space...
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{ "lang": "python", "repo": "E4S-Project/testsuite", "path": "/validation_tests/llvm/SOLLVE/pragmas/tau-module/adi/problem.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: E4S-Project/testsuite path: /validation_tests/llvm/SOLLVE/pragmas/tau-module/adi/problem.py import numpy as np from numpy import abs, cos, exp, mean, pi, prod, sin, sqrt, sum from autotune import TuningProblem from autotune.space import * import os import sys import time import json import math ...
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{ "lang": "python", "repo": "E4S-Project/testsuite", "path": "/validation_tests/llvm/SOLLVE/pragmas/tau-module/adi/problem.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def plopper_func(x): x = np.asarray_chkfinite(x) # ValueError if any NaN or Inf values = [ point[k] for k in x1 ] print('VALUES:',point[x1[0]]) # params = ["P0","P1","P2","P3","L0","L1","L2","L3","L4","L5","L6","L7"] params = ["P0","P1","P2","P3","L0","L1"] # params = ["P0","P1"...
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{ "lang": "python", "repo": "E4S-Project/testsuite", "path": "/validation_tests/llvm/SOLLVE/pragmas/tau-module/adi/problem.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if self.mode == "STUDENT_INFO": pass elif self.mode == "COURSEWORK": self.base.change_state(CombatState) elif self.mode == "OPTIONS": pass elif self.mode == "QUIT": sys.exit() def escape(self): if self.mode is not None: super(LobbyState, self).escape() self.ui_selecti...
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{ "lang": "python", "repo": "Moguri/odin", "path": "/src/main.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Moguri/odin path: /src/main.py import sys import os os.environ['PANDA_PRC_DIR'] = os.path.join(os.path.dirname(__file__), 'etc') # This import should be kept near the top to avoid issues with CEF/Chromium hooking malloc from cefpanda import CEFPanda from direct.showbase.ShowBase import ShowB...
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{ "lang": "python", "repo": "Moguri/odin", "path": "/src/main.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: princesinghtomar/Classic-Brick-Breaker path: /fire.py from headerfile import * from items import * from inherit_brick import * from bricks import * class fire: def __init__(self,x,y): self.cur_x = x self.cur_y = y self.initial_x = x self.initial_y = y ...
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{ "lang": "python", "repo": "princesinghtomar/Classic-Brick-Breaker", "path": "/fire.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> #flag = True , draw otherwise clear def fdraw(self,screen_array,flag): if(self.alive): if(flag): screen_array[self.cur_x][self.cur_y] = '.' else: screen_array[self.cur_x][self.cur_y] = ' '<|fim_prefix|># repo: princesinghtomar/Classi...
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{ "lang": "python", "repo": "princesinghtomar/Classic-Brick-Breaker", "path": "/fire.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pncnmnp/Movie-Recommendation path: /fetch_posters.py from file_paths import * import pandas as pd import requests from PIL import Image import time import os <|fim_suffix|>for i in range(0, 45466): if os.path.exists("./flask/static/posters/" + poster_df["id"][i] + ".jpg"): if int(poster_df["i...
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{ "lang": "python", "repo": "pncnmnp/Movie-Recommendation", "path": "/fetch_posters.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>poster_df = pd.read_csv(PATH_POSTERS) poster_df["poster_path"] = POSTER_BASE_URL + poster_df["poster_path"] movie_ids = pd.read_csv(PATH_MOVIES)["id"].tolist() for i in range(0, 45466): if os.path.exists("./flask/static/posters/" + poster_df["id"][i] + ".jpg"): if int(poster_df["id"][i]) in movie_ids...
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{ "lang": "python", "repo": "pncnmnp/Movie-Recommendation", "path": "/fetch_posters.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@router.get('/cars', response_model=list[CarRead]) async def get_cars(session: AsyncSession = Depends(get_session)) -> list[Car]: """ List all cars in the database """ result = await session.execute(select(Car)) return [Car(name=car.name, manufacturer=car.manufacturer, id=car.id) for c...
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{ "lang": "python", "repo": "daniwk/templates", "path": "/fastapi/{{ cookiecutter.project_name }}/app/api/api_v1/endpoints/cars.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: daniwk/templates path: /fastapi/{{ cookiecutter.project_name }}/app/api/api_v1/endpoints/cars.py from fastapi import APIRouter, Depends from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession <|fim_suffix|>@router.post('/cars', response_model=CarRead) async def add_car(car:...
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{ "lang": "python", "repo": "daniwk/templates", "path": "/fastapi/{{ cookiecutter.project_name }}/app/api/api_v1/endpoints/cars.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Leterax/code-jam-6 path: /wandering-warriors/modules/operations.py from kivy.uix.widget import Widget from kivy.uix.image import Image <|fim_suffix|> return f'assets/graphics/{operation}.png' def send_operation(self, operation: str) -> None: img_source = self.button_image(op...
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{ "lang": "python", "repo": "Leterax/code-jam-6", "path": "/wandering-warriors/modules/operations.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> img_source = self.button_image(operation) self.parent.children[2].add_middle(Image(source=img_source))<|fim_prefix|># repo: Leterax/code-jam-6 path: /wandering-warriors/modules/operations.py from kivy.uix.widget import Widget from kivy.uix.image import Image <|fim_middle|>class Operatio...
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{ "lang": "python", "repo": "Leterax/code-jam-6", "path": "/wandering-warriors/modules/operations.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: rohit-shekhar26/py4e path: /code/pagerank/sprank.py import sqlite3 conn = sqlite3.connect('spider.sqlite') cur = conn.cursor() # Βρείτε τα αναγνωριστικά που στέλνουν την κατάταξη σελίδων - μας ενδιαφέρουν # μόνο οι σελίδες στο SCC που έχουν συνδέσμους εισόδου και εξόδου cur.execute('''S...
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{ "lang": "python", "repo": "rohit-shekhar26/py4e", "path": "/code/pagerank/sprank.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # rotate prev_ranks = next_ranks # Τοποθέτηση ξανά των τελικών βαθμολογιών στη βάση δεδομένων print(list(next_ranks.items())[:5]) cur.execute('''UPDATE Pages SET old_rank=new_rank''') for (id, new_rank) in list(next_ranks.items()) : cur.execute('''UPDATE Pages SET new_rank=? WHERE id=?...
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{ "lang": "python", "repo": "rohit-shekhar26/py4e", "path": "/code/pagerank/sprank.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: yosef-gao/aqidatapuller path: /bin/data_puller.py import urllib2 import json import socket import re class DataPuller(object): # URL = 'http://aqicn.org/aqicn/json/android/%s/json' URL = 'http://aqicn.org/map/world' TRYTIMES = 10 <|fim_suffix|> if data: fullMapJso...
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{ "lang": "python", "repo": "yosef-gao/aqidatapuller", "path": "/bin/data_puller.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if data: fullMapJsonString = re.search("(?<=mapInitWithData\()\[.*\](?=\))", data) cities = None if fullMapJsonString: self.cities = json.loads(fullMapJsonString.group(0)) def pull_data(self, site_id): for city in self.cities: ...
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{ "lang": "python", "repo": "yosef-gao/aqidatapuller", "path": "/bin/data_puller.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: yichuanluanma/douban path: /douban/spiders/movie.py #-*- coding: utf-8 -*- import random import re import sys import logging import requests import utils import config from scrapy.http import HtmlResponse from scrapy.http import Request from scrapy.spiders import Rule from scrapy.spiders import...
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{ "lang": "python", "repo": "yichuanluanma/douban", "path": "/douban/spiders/movie.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> command = ( "CREATE TABLE IF NOT EXISTS {} (" "`id` INT(8) NOT NULL AUTO_INCREMENT UNIQUE ," "`title` TEXT NOT NULL," "`average` FLOAT NOT NULL," "`rating_people` INT(7) DEFAULT NULL," "`rating_five` CHAR(5) DEFAULT NULL," ...
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{ "lang": "python", "repo": "yichuanluanma/douban", "path": "/douban/spiders/movie.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: akshah/iodb path: /back-end/src/analysis/NeuralNet/655/nn_reducer.py #!/usr/bin/env python # # Adapted from an example by Michael G. Noll at: # # http://www.michael-noll.com/wiki/Writing_An_Hadoop_MapReduce_Program_In_Python # from __future__ import with_statement from operator import itemgetter...
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{ "lang": "python", "repo": "akshah/iodb", "path": "/back-end/src/analysis/NeuralNet/655/nn_reducer.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>X = data[:,1:] T = data[:,0].reshape((-1,1)) trainf = 0.8 c1I,_ = np.where(T == 1) c2I,_ = np.where(T == 2) c3I,_ = np.where(T == 3) c1I = np.random.permutation(c1I) c2I = np.random.permutation(c2I) c3I = np.random.permutation(c3I) nc1 = len(c1I) nc2 = len(c2I) nc3 = len(c3I) n = round(trainf*len(c1I)...
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{ "lang": "python", "repo": "akshah/iodb", "path": "/back-end/src/analysis/NeuralNet/655/nn_reducer.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>@pytest.fixture(scope="session") def parted_alltypes(client): return client.table("functional_alltypes_parted") @pytest.fixture(scope="session") def parted_df(parted_alltypes): return parted_alltypes.execute() @pytest.fixture(scope="session") def struct_table(client): return client.table("...
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{ "lang": "python", "repo": "stjordanis/ibis-bigquery", "path": "/tests/system/conftest.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> return client.table("numeric_table") @pytest.fixture(scope="session") def public(project_id, credentials): return bq.connect( project_id=project_id, dataset_id="bigquery-public-data.stackoverflow", credentials=credentials, )<|fim_prefix|># repo: stjordanis/ibis-bigque...
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{ "lang": "python", "repo": "stjordanis/ibis-bigquery", "path": "/tests/system/conftest.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: stjordanis/ibis-bigquery path: /tests/system/conftest.py import os import ibis # noqa: F401 import pytest from google.oauth2 import service_account import ibis_bigquery PROJECT_ID = os.environ.get("GOOGLE_BIGQUERY_PROJECT_ID", "ibis-gbq") DATASET_ID = "testing" bq = ibis_bigquery.Backend() ...
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{ "lang": "python", "repo": "stjordanis/ibis-bigquery", "path": "/tests/system/conftest.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # Read linear Acceleration data # accel_x,accel_y,accel_z = bno.read_linear_acceleration() # Read full acceleration data (with gravity) accel_x, accel_y, accel_z = bno.read_line...
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{ "lang": "python", "repo": "tunnelsnake/SnakeNDOF", "path": "/IMU/ServerV2/server.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> print("System Confirmed.") time.sleep(.25) while True: p = Process(target=self.startlistener, args=(bno,)) while True: if(self.active_connection): while True: if(self.kill_proc == True): ...
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{ "lang": "python", "repo": "tunnelsnake/SnakeNDOF", "path": "/IMU/ServerV2/server.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: tunnelsnake/SnakeNDOF path: /IMU/ServerV2/server.py import socket import time from multiprocessing import Process from Adafruit_BNO055 import BNO055 class Server(): logfile = "logs/rawdata.csv" host = "192.168.0.104" port = "8080" active_connection = False collect_data =...
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{ "lang": "python", "repo": "tunnelsnake/SnakeNDOF", "path": "/IMU/ServerV2/server.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mopidy/mopidy path: /mopidy/commands.py lp, ) def __call__( self, parser, namespace, values, option_string=None # noqa: ARG002 ) -> NoReturn: raise _HelpError class Command: """Command parser and runner for building trees of commands. This class provid...
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{ "lang": "python", "repo": "mopidy/mopidy", "path": "/mopidy/commands.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self, config: config_lib.Config, mixer: Optional[MixerProxy], ) -> AudioProxy: logger.info("Starting Mopidy audio") return cast(AudioProxy, Audio.start(config=config, mixer=mixer).proxy()) def start_backends( self, config: config_lib.Config,...
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{ "lang": "python", "repo": "mopidy/mopidy", "path": "/mopidy/commands.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: mopidy/mopidy path: /mopidy/commands.py tion_string=None # noqa: ARG002 ) -> NoReturn: raise _HelpError class Command: """Command parser and runner for building trees of commands. This class provides a wraper around :class:`argparse.ArgumentParser` for handling this ty...
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{ "lang": "python", "repo": "mopidy/mopidy", "path": "/mopidy/commands.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: engapa/modeldb-basic path: /modeldb/thrift/modeldb/ModelDBService.py __(self, other): return not (self == other) class storeTransformEvent_args(object): """ Attributes: - te """ thrift_spec = ( None, # 0 (1, TType.STRUCT, 'te', (TransformEvent, Tra...
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{ "lang": "python", "repo": "engapa/modeldb-basic", "path": "/modeldb/thrift/modeldb/ModelDBService.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.success = success self.rnfEx = rnfEx self.ioEx = ioEx self.brEx = brEx self.svEx = svEx def read(self, iprot): if iprot._fast_decode is not None and isinstance(iprot.trans, TTransport.CReadableTransport) and self.thrift_spec is not None: ...
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{ "lang": "python", "repo": "engapa/modeldb-basic", "path": "/modeldb/thrift/modeldb/ModelDBService.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> args = storeGridSearchCrossValidationEvent_args() args.read(iprot) iprot.readMessageEnd() result = storeGridSearchCrossValidationEvent_result() try: result.success = self._handler.storeGridSearchCrossValidationEvent(args.gscve) msg_type = TMe...
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{ "lang": "python", "repo": "engapa/modeldb-basic", "path": "/modeldb/thrift/modeldb/ModelDBService.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: greglandrum/rdkit path: /Contrib/FreeWilson/freewilson.py tAtomMapNum() if atommap: atommaps[atommap] = idx counts[atommap] += 1 next_atommap = max(atommaps) + 1 add_atommap = [] for fragment in frags[1:]: for idx in fragment: a...
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{ "lang": "python", "repo": "greglandrum/rdkit", "path": "/Contrib/FreeWilson/freewilson.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> def __init__(self, rgroups, rgroup_to_descriptor_idx, fitter, r2, descriptors, row_decomposition, num_training, num_reconstructed): self.rgroups = rgroups # dictionary 'Core':[core1, core1], 'R1': [rgroup1, rgroup2], ... self.rgroup_to...
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{ "lang": "python", "repo": "greglandrum/rdkit", "path": "/Contrib/FreeWilson/freewilson.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> decomposer.Process() logger.info(f"Matched {len(matched_scores)} out of {len(mols)}") if not(matched_scores): logger.error("No scaffolds matched the input molecules") return decomposition = decomposer.GetRGroupsAsRows(asSmiles=True) logger.info("Get unique rgroups..."...
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{ "lang": "python", "repo": "greglandrum/rdkit", "path": "/Contrib/FreeWilson/freewilson.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: Lenchik13/Testing path: /test/test_edit_contact.py from model.contact import Contact import random def test_edit_contact(app, db, check_ui): app.open_home_page() if app.contact.count() == 0: app.contact.create(Contact(firstname="Contact", lastname="", nickname="", ...
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{ "lang": "python", "repo": "Lenchik13/Testing", "path": "/test/test_edit_contact.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>old_contacts.remove(rcontact) old_contacts.append(contact) assert sorted(old_contacts, key=Contact.id_or_max) == sorted(new_contacts, key=Contact.id_or_max) if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max)<...
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{ "lang": "python", "repo": "Lenchik13/Testing", "path": "/test/test_edit_contact.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: khoehlein/fV-SRN-Ensemble-Compression path: /inference/model/latent_features/marginal/temporal_features.py from typing import Optional, Tuple, List, Any from torch import Tensor from inference.model.latent_features.indexing.time_indexer import TimeIndexer from inference.model.latent_features.in...
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{ "lang": "python", "repo": "khoehlein/fV-SRN-Ensemble-Compression", "path": "/inference/model/latent_features/marginal/temporal_features.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __init__( self, key_times: List[Any], num_channels: int, initializer: Optional[IInitializer] = None, debug: Optional[bool] = False, dtype=None, device=None ): super(TemporalFeatureVector, self).__init__(key_times, 3, num_chan...
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{ "lang": "python", "repo": "khoehlein/fV-SRN-Ensemble-Compression", "path": "/inference/model/latent_features/marginal/temporal_features.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> raise NotImplementedError() class TemporalFeatureVector(ITemporalFeatures): def __init__( self, key_times: List[Any], num_channels: int, initializer: Optional[IInitializer] = None, debug: Optional[bool] = False, dtype=None, device=...
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{ "lang": "python", "repo": "khoehlein/fV-SRN-Ensemble-Compression", "path": "/inference/model/latent_features/marginal/temporal_features.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: sugarsack/sugar path: /sugar/lib/loader/virtual.py # coding: utf-8 """ Module loader for virtual objects """ import os import abc import importlib import sugar.lib.exceptions from sugar.lib.loader.base import BaseModuleLoader from sugar.lib.loader.util import RunnerDataValidator class VirtualM...
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{ "lang": "python", "repo": "sugarsack/sugar", "path": "/sugar/lib/loader/virtual.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def defer_to_call(*args, **kwargs): """ Defer bound method for a post-call for validation. :param args: generic arguments :param kwargs: generic keywords :return: generic object """ ...
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{ "lang": "python", "repo": "sugarsack/sugar", "path": "/sugar/lib/loader/virtual.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: hasancaslan/3D_multiview_reg path: /train.py import sys import os import logging import torch import time import argparse import numpy as np import torch.optim as optim from tensorboardX import SummaryWriter import lib.config as config from lib.utils import load_config from lib.data import make_...
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{ "lang": "python", "repo": "hasancaslan/3D_multiview_reg", "path": "/train.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if metric_val_best == np.inf or metric_val_best == -np.inf: metric_val_best = -model_selection_sign * np.inf logger.info('Current best validation metric ({}): {:.5f}'.format( model_selection_metric, metric_val_best)) # Training parameters stat_interval = cfg['train']['sta...
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{ "lang": "python", "repo": "hasancaslan/3D_multiview_reg", "path": "/train.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> predictions = {} for key, value in self._predictions_map.items(): predictions[key] = value # Unnest if it wasn't a dictionary to begin with. default_predictions_key = util.default_dict_key( eval_constants.PREDICTIONS_NAME) if list(predictions) == [default_predictions_key]...
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{ "lang": "python", "repo": "tensorflow/model-analysis", "path": "/tensorflow_model_analysis/eval_metrics_graph/eval_metrics_graph.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # Lock should be acquired before calling this function. return self._session.run(fetches=self._metric_variable_nodes) def get_metric_variables(self) -> List[Any]: """Returns a list containing the metric variable values.""" with self._lock: return self._get_metric_variables() de...
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{ "lang": "python", "repo": "tensorflow/model-analysis", "path": "/tensorflow_model_analysis/eval_metrics_graph/eval_metrics_graph.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: tensorflow/model-analysis path: /tensorflow_model_analysis/eval_metrics_graph/eval_metrics_graph.py 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. """Abstract ...
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{ "lang": "python", "repo": "tensorflow/model-analysis", "path": "/tensorflow_model_analysis/eval_metrics_graph/eval_metrics_graph.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> N = len(var_names) n = 0 i = 0 while n <= N: print("Plotting {:} of {:}".format(n, N)) plot_vars = var_names[n : n + max_panel] az.plot_trace(trace, var_names=plot_vars) plt.savefig(figstem.format(i)) plt.close("all") n += max_panel ...
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{ "lang": "python", "repo": "iancze/TWA-3-orbit", "path": "/src/twa/plot_utils.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: iancze/TWA-3-orbit path: /src/twa/plot_utils.py import collections import arviz as az import matplotlib.colors import matplotlib.pyplot as plt import numpy as np from matplotlib.collections import LineCollection from matplotlib.colors import LinearSegmentedColormap # Create our own custom color...
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{ "lang": "python", "repo": "iancze/TWA-3-orbit", "path": "/src/twa/plot_utils.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __init__(self, game, x, y, width, height): self.groups = game.walls pg.sprite.Sprite.__init__(self, self.groups) self.game = game self.rect = pg.Rect(x, y, width, height) self.x = x self.y = y self.rect.x = x self.rect.y = y<|fim_pre...
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{ "lang": "python", "repo": "mohan488/zombie-game", "path": "/zombie_game/walls.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: mohan488/zombie-game path: /zombie_game/walls.py # python from __future__ import unicode_literals # libs from zombie_game.settings import * <|fim_suffix|> def __init__(self, game, x, y, width, height): self.groups = game.walls pg.sprite.Sprite.__init__(self, self.groups) ...
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{ "lang": "python", "repo": "mohan488/zombie-game", "path": "/zombie_game/walls.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def exclude_directories(self): excluded_dirs = list() for f in self.file_list: if os.path.isdir(f): excluded_dirs.append(f) log.debug(u"Directories are removed from list: {}".format(repr(excluded_dirs))) self.file_list = set(self.file_list).s...
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{ "lang": "python", "repo": "luis12614/File2Mail", "path": "/file_ops.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: luis12614/File2Mail path: /file_ops.py # -*- coding: utf-8 -*- """ Application file operations """ import mimetypes import os import shutil import time from logger import log from settings import SETTINGS __author__ = 'Sencer Hamarat' class FSTools(): """ File System Tools Class cr...
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{ "lang": "python", "repo": "luis12614/File2Mail", "path": "/file_ops.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @property def user_path(self): return os.path.expanduser(u"~") def target_dir_path(self): return os.path.join(self.user_path, self.directory) def make_directory(self): created = False try: os.makedirs(self.target_dir_path()) created...
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{ "lang": "python", "repo": "luis12614/File2Mail", "path": "/file_ops.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: shadesdhiman/InterviewBit-Solutions path: /Heaps and Maps/Profit Maximisation.py # -*- coding: utf-8 -*- """ Created on Tue Jul 6 22:58:57 2021 @author: Dhiman """ <|fim_suffix|> A = [2, 3] B = 3 obj = Solution() print(obj.solve(A,B))<|fim_middle|>class Solution: # @par...
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{ "lang": "python", "repo": "shadesdhiman/InterviewBit-Solutions", "path": "/Heaps and Maps/Profit Maximisation.py", "mode": "psm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_suffix|> import heapq H = [] heapq.heapify(H) for i in range(len(A)): heapq.heappush(H, -1 * A[i]) profit = 0 for i in range(B): x= -1*heapq.heappop(H) profit+=x x=x-1 heapq.heappush(H, -x) ...
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{ "lang": "python", "repo": "shadesdhiman/InterviewBit-Solutions", "path": "/Heaps and Maps/Profit Maximisation.py", "mode": "spm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_suffix|> A = [2, 3] B = 3 obj = Solution() print(obj.solve(A,B))<|fim_prefix|># repo: shadesdhiman/InterviewBit-Solutions path: /Heaps and Maps/Profit Maximisation.py # -*- coding: utf-8 -*- """ Created on Tue Jul 6 22:58:57 2021 @author: Dhiman """ class Solution: # @param A : l...
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{ "lang": "python", "repo": "shadesdhiman/InterviewBit-Solutions", "path": "/Heaps and Maps/Profit Maximisation.py", "mode": "spm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_prefix|># repo: vipermu/bigotis path: /server/models/taming/taming_decoder.py import os import yaml import math import glob from typing import * import torch import torchvision.transforms as T import torchvision.transforms.functional as TF import torch.nn.functional as F from PIL import Image import numpy as np...
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{ "lang": "python", "repo": "vipermu/bigotis", "path": "/server/models/taming/taming_decoder.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> optimizer = torch.optim.AdamW( params=[z_logits], lr=lr, betas=(0.9, 0.999), weight_decay=0.1, ) gen_img_list = [] z_logits_list = [] for step in range(num_generations): with torch.no_grad...
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{ "lang": "python", "repo": "vipermu/bigotis", "path": "/server/models/taming/taming_decoder.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: oussa/bootcamp-ihealth path: /bootcamp/core/tryton.py __author__ = 'oussama' from django.conf import settings import sys, os import warnings warnings.filterwarnings("ignore", message="Old style callback, usecb_func(ok, store) instead") TRYTOND_PATH = settings.TRYTOND_PATH DIR = os.path.abspath...
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{ "lang": "python", "repo": "oussa/bootcamp-ihealth", "path": "/bootcamp/core/tryton.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># Instantiate the database and the pool DB = Database(settings.TRYTON_DB).connect() POOL = Pool(settings.TRYTON_DB) POOL.init() user_obj = POOL.get('res.user') cursor = DB.cursor() Cache.clean(settings.TRYTON_DB) try: # User 0 is root user. We use it to get the user id: USER = user_obj.search(curs...
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{ "lang": "python", "repo": "oussa/bootcamp-ihealth", "path": "/bootcamp/core/tryton.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: danielogen/msc_research path: /utils/popc/ds_class_clustering.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Mon Apr 6 14:42:06 2020 @author: danielogenrwot """ from sklearn.cluster import KMeans #import numpy as np import pandas as pd from disp import display from popc impor...
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{ "lang": "python", "repo": "danielogen/msc_research", "path": "/utils/popc/ds_class_clustering.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># locate the binary file data_k9_binary = pd.read_csv('../Analytics/Results/csv/all_labeled_data_desktop_18_01_2021.csv') X = data_k9_binary.iloc[:, [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21]].values kmeans = KMeans(n_clusters=6, random_state=0).fit(X) result = [] for i in range(l...
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{ "lang": "python", "repo": "danielogen/msc_research", "path": "/utils/popc/ds_class_clustering.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>kmeans = KMeans(n_clusters=6, random_state=0).fit(X) result = [] for i in range(len(X)): result.append([kmeans.labels_[i], X[i]]) display(result, 'kmeans') labels = popc(X) print(labels) # add new column to the dataframe data_k9_binary['cluster'] = labels # write new dataframe to csv data_k9_bin...
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{ "lang": "python", "repo": "danielogen/msc_research", "path": "/utils/popc/ds_class_clustering.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>thread1 = Sleeper( "4 second thread done!", 4 ) thread1.start() thread2 = Sleeper( "2 second thread done!", 2 ) thread2.start() raw_input( "Waiting for threads to exit.\n\n" )<|fim_prefix|># repo: verhulstm/python-training path: /kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py #...
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{ "lang": "python", "repo": "verhulstm/python-training", "path": "/kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: verhulstm/python-training path: /kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py #------------------------------------------------------------------------------ # Name: sleeper_thread_class.py # Author: Kevin Harris # Last Modified: 02/13/04 # Descripti...
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{ "lang": "python", "repo": "verhulstm/python-training", "path": "/kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>thread2 = Sleeper( "2 second thread done!", 2 ) thread2.start() raw_input( "Waiting for threads to exit.\n\n" )<|fim_prefix|># repo: verhulstm/python-training path: /kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py #--------------------------------------------------------------------...
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{ "lang": "python", "repo": "verhulstm/python-training", "path": "/kevin-harris-python-tutorial/py_threading/sleeper_thread_class.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> usrepr = observed_coo.represent_as(UnitSphericalRepresentation) lon = usrepr.lon.to_value(u.radian) lat = usrepr.lat.to_value(u.radian) if isinstance(observed_coo, AltAz): # the 'A' indicates zen/az inputs coord_type = "A" lat = PIOVER2 - lat else: coor...
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{ "lang": "python", "repo": "astropy/astropy", "path": "/astropy/coordinates/builtin_frames/icrs_observed_transforms.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # Create loopback transformations frame_transform_graph._add_merged_transform(AltAz, ICRS, AltAz) frame_transform_graph._add_merged_transform(HADec, ICRS, HADec) # for now we just implement this through ICRS to make sure we get everything # covered # Before, this was using CIRS as intermediate frame, how...
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{ "lang": "python", "repo": "astropy/astropy", "path": "/astropy/coordinates/builtin_frames/icrs_observed_transforms.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }