text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: toakarsky/galactica path: /engine/input.py
import pygame
from galactica import settings
from .events import Events
class Input:
_input = None
class _Input:
def __init__(self, DEBUG):
<|fim_suffix|> self.handle_events()
def isKeyPressed(self, key):
... | code_fim | hard | {
"lang": "python",
"repo": "toakarsky/galactica",
"path": "/engine/input.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return key in self.pressedButtons
@staticmethod
def GetInput(DEBUG=None):
if Input._input == None:
Input._input = Input._Input(
DEBUG=DEBUG
)
return Input._input<|fim_prefix|># repo: toakarsky/galactica path: /engine/input.py
im... | code_fim | hard | {
"lang": "python",
"repo": "toakarsky/galactica",
"path": "/engine/input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def update(self):
self.handle_events()
def isKeyPressed(self, key):
return key in self.pressedButtons
@staticmethod
def GetInput(DEBUG=None):
if Input._input == None:
Input._input = Input._Input(
DEBUG=DEBUG
... | code_fim | hard | {
"lang": "python",
"repo": "toakarsky/galactica",
"path": "/engine/input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@command(description=XKCD_DESCRIPTION, aliases=["x"])
async def xkcd(self, ctx: Context) -> None:
"""
Fetch an XKCD comic and allow the user to
either get a random one (no params) or specify
a number
Parameters
-----------
ctx: Context
... | code_fim | medium | {
"lang": "python",
"repo": "fugwenna/bunkbot",
"path": "/src/xkcd/xkcd_cog.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fugwenna/bunkbot path: /src/xkcd/xkcd_cog.py
from discord.ext.commands import command, Context, Cog
from .xkcd_service import XKCDService
from ..bunkbot import BunkBot
from ..core.registry import XKCD_SERVICE
XKCD_DESCRIPTION: str = "Get a random XKCD comic or specify the comic number"
class ... | code_fim | hard | {
"lang": "python",
"repo": "fugwenna/bunkbot",
"path": "/src/xkcd/xkcd_cog.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> await ctx.send(embed=embed)
except Exception as ex:
print(ex)
def setup(bot: BunkBot) -> None:
bot.add_cog(XKCDCog(XKCD_SERVICE))<|fim_prefix|># repo: fugwenna/bunkbot path: /src/xkcd/xkcd_cog.py
from discord.ext.commands import command, Context, Cog
from .xkcd_... | code_fim | hard | {
"lang": "python",
"repo": "fugwenna/bunkbot",
"path": "/src/xkcd/xkcd_cog.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> copyfile(os.path.join(gif_folder, parcellation_f), os.path.join(save_folder, folder_num, 'parcellation.nii.gz'))
copyfile(os.path.join(gif_folder, circumference_f), os.path.join(save_folder, folder_num, 'circumference.nii.gz'))<|fim_prefix|># repo: EdgarRios111/pytorch-mri-segmentation-3D path: /utils/... | code_fim | hard | {
"lang": "python",
"repo": "EdgarRios111/pytorch-mri-segmentation-3D",
"path": "/utils/processGIFS.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EdgarRios111/pytorch-mri-segmentation-3D path: /utils/processGIFS.py
import os
import sys
import glob
from shutil import copyfile
gif_folders_path = '../../../T1s/results/'
save_folder = '../../Data/MS2017b/gifs/'
gif_folders = glob.glob(gif_folders_path + '*')
print(gif_folders_path)
if not... | code_fim | medium | {
"lang": "python",
"repo": "EdgarRios111/pytorch-mri-segmentation-3D",
"path": "/utils/processGIFS.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # node color, size
node_size = kwargs.get('node_size')
if node_size is None:
node_scale_by = kwargs.get('node_scale_by', 5000)
node_size = [node_scale_by*(len(_) / len(y)) for n,_ in G.nodes(data='members')]
node_color = [Counter(c_hex[_]).most_common()[0][0] for n,_ in G.n... | code_fim | hard | {
"lang": "python",
"repo": "braindynamicslab/dyneusr",
"path": "/dyneusr/tools/networkx_utils.py",
"mode": "spm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: braindynamicslab/dyneusr path: /dyneusr/tools/networkx_utils.py
"""
Network plotting helper functions.
"""
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from __future__ import unicode_literals
from collections import Counter
from ins... | code_fim | hard | {
"lang": "python",
"repo": "braindynamicslab/dyneusr",
"path": "/dyneusr/tools/networkx_utils.py",
"mode": "psm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
# new Cover API from kmapper==1.2.0
bins = np.copy(cover.centers_)
# transform each node
cover_cubes = {}
for i, center in enumerate(cover.centers_):
lower = center - cover.radius_
upper = center + cover.radius_
cove... | code_fim | hard | {
"lang": "python",
"repo": "braindynamicslab/dyneusr",
"path": "/dyneusr/tools/networkx_utils.py",
"mode": "spm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_suffix|> # binding.update({"timer_template": 'declare_timer_periodic'})
# self.timer_block.update({key: binding})
binding.update({"variable_template": [('declare_timer_periodic', 'TIMER_BINDING')]})
self.variables_block.update({key: ... | code_fim | hard | {
"lang": "python",
"repo": "bawilless/AzureSphereGenX",
"path": "/Generator/builders/timer_bindings.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bawilless/AzureSphereGenX path: /Generator/builders/timer_bindings.py
class Builder():
def __init__(self, data, signatures, variables_block, handlers_block, timer_block):
self.bindings = list(elem for elem in data.get('bindings').get('timers') if elem.get('enabled', True) == True)
<|... | code_fim | hard | {
"lang": "python",
"repo": "bawilless/AzureSphereGenX",
"path": "/Generator/builders/timer_bindings.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: greenblat/vlsistuff path: /axi_noc/tbx16/counts.py
nts += monitorStuff("tb.dut.merge215.axi_wr_4_merger.c_aw_fifo.int_count")
counts += monitorStuff("tb.dut.merge215.axi_wr_4_merger.c_b_fifo.next_count")
counts += monitorStuff("tb.dut.merge215.axi_wr_4_merger.c_b_fifo.count")
counts +... | code_fim | hard | {
"lang": "python",
"repo": "greenblat/vlsistuff",
"path": "/axi_noc/tbx16/counts.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.axi_wr_4_merger.panic_bcount"))
logs.log_info("SNP %x tb.dut.merge13.axi_wr_4_merger.panic_ccount" % logs.peek("tb.dut.merge13.axi_wr_4_merger.panic_ccount"))
logs.log_info("SNP %x tb.dut.merge13.axi_wr_4_merger.panic_dcount" % logs.peek("tb.dut.merge13.axi_wr_4_merger.panic_dcount"))
logs.... | code_fim | hard | {
"lang": "python",
"repo": "greenblat/vlsistuff",
"path": "/axi_noc/tbx16/counts.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: greenblat/vlsistuff path: /axi_noc/tbx16/counts.py
count")
counts += monitorStuff("tb.dut.split100.axi_wr_4_splitter.b_fifo.next_count")
counts += monitorStuff("tb.dut.split100.axi_wr_4_splitter.b_fifo.count")
counts += monitorStuff("tb.dut.split100.axi_wr_4_splitter.back_bid_a_fifo.c... | code_fim | hard | {
"lang": "python",
"repo": "greenblat/vlsistuff",
"path": "/axi_noc/tbx16/counts.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ansport as BiddingSeasonalityAdjustmentServiceGrpcTransport,
)<|fim_prefix|># repo: henribru/google-ads-stubs path: /google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi
from .base import (
BiddingSeasonalityAdjustmentServiceTr<|fim_middle|>a... | code_fim | medium | {
"lang": "python",
"repo": "henribru/google-ads-stubs",
"path": "/google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: henribru/google-ads-stubs path: /google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi
from .base import (
BiddingSeasonalityAdjustmentServiceTr<|fim_suffix|>m .grpc import (
BiddingSeasonalityAdjustmentServiceGrpcTransport as Bidd... | code_fim | medium | {
"lang": "python",
"repo": "henribru/google-ads-stubs",
"path": "/google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>m .grpc import (
BiddingSeasonalityAdjustmentServiceGrpcTransport as BiddingSeasonalityAdjustmentServiceGrpcTransport,
)<|fim_prefix|># repo: henribru/google-ads-stubs path: /google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi
from .base imp... | code_fim | medium | {
"lang": "python",
"repo": "henribru/google-ads-stubs",
"path": "/google-stubs/ads/googleads/v12/services/services/bidding_seasonality_adjustment_service/transports/__init__.pyi",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: srinuvasan-mentor/mtda path: /mtda/power/aviosys_8800.py
# ---------------------------------------------------------------------------
# aviosys power driver for MTDA
# ---------------------------------------------------------------------------
#
# This software is a part of MTDA.
# Copyright (c)... | code_fim | hard | {
"lang": "python",
"repo": "srinuvasan-mentor/mtda",
"path": "/mtda/power/aviosys_8800.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def command(self, args):
return False
def on(self):
""" Power on the attached device"""
status = self.dev.ctrl_transfer(0x40, 0x01, 0x0001, 0xa0, [])
if status == 0:
self.ev.set()
return (status == 0)
def off(self):
""" Power off th... | code_fim | hard | {
"lang": "python",
"repo": "srinuvasan-mentor/mtda",
"path": "/mtda/power/aviosys_8800.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sentiments = []
passed = 0
total = 0
with open("initial_data/movie_list.txt", 'r') as movie_file:
titles = movie_file.readlines()
for ctr , title in enumerate(titles):
try:
m_title = title.strip()
print(m_title)
scene_sentiments = get_sentiment_by_scene(... | code_fim | medium | {
"lang": "python",
"repo": "bdizon/Cinefy",
"path": "/scrape_movies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bdizon/Cinefy path: /scrape_movies.py
import json
from initial_data.titles import titles
from shared.sentiment import get_sentiment_by_scene
def average_sentiment(movie_sentiment_array):
keys = movie_sentiment_array[0].keys()
avg_senti = {}
for senti in movie_sentiment_array:
... | code_fim | medium | {
"lang": "python",
"repo": "bdizon/Cinefy",
"path": "/scrape_movies.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> total += 1
except:
print("skipped {}".format(title))
pass
with open("initial_data/initialdata.json", 'w') as fopen:
fopen.write(json.dumps(sentiments, indent=4))
print(passed / total)<|fim_prefix|># repo: bdizon/Cinefy path: /scrape_movies.py
import json
... | code_fim | hard | {
"lang": "python",
"repo": "bdizon/Cinefy",
"path": "/scrape_movies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pkalliok/almost-bad-poetry path: /runogen.cgi
#!/usr/bin/env python3
# coding: utf-8
from ingest import load_url, save_state, load_state
from measures import measure_map, generate_poem
import html, sys
STATE_FILE = 'used_stanzas.pickle'
HTTP_START = """Content-type: text/html; charset=utf-8
<... | code_fim | hard | {
"lang": "python",
"repo": "pkalliok/almost-bad-poetry",
"path": "/runogen.cgi",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def make_poem(measure, corpus_url):
if measure not in measure_map: raise ValueError("unknown measure")
p(HTTP_START.format(measure.capitalize() + ' sinulle'))
p('<p>(tässä saattaa kestää....)</p>')
state = load_url(corpus_url)
load_state(state, STATE_FILE)
p('<p>Tässä runosi, ole h... | code_fim | hard | {
"lang": "python",
"repo": "pkalliok/almost-bad-poetry",
"path": "/runogen.cgi",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def handle_request(form):
if 'tee_runo' in form:
make_poem(form.getfirst('tee_runo'), form.getfirst('url'))
else: show_form(form)
if __name__ == '__main__':
import cgi
try: handle_request(cgi.FieldStorage())
except: cgi.print_exception()<|fim_prefix|># repo: pkalliok/almost-ba... | code_fim | hard | {
"lang": "python",
"repo": "pkalliok/almost-bad-poetry",
"path": "/runogen.cgi",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DCnomics/hard_way_for_python path: /ex4.py
자동차 = 100
차_안_공간 = 4.0
운전사 = 30
승객 = 90
운행_안하는_차 = 자동차 - 운전사
운행하는_차 = 운전사
총_정원 = 운행하는_차 * 차_안_공간
차당_평균_승객 = 승객 / 운행하는_차
<|fim_suffix|>이름 = '정동철'
나이 = 31
키 = 177
몸무게 = 70
눈 = '갈색'
이 = '하양'
머리 = '갈색'
print(f"{이름}에 대해 이야기해 보죠.")
print(f"키는 {키} 센티미터구요.")
p... | code_fim | hard | {
"lang": "python",
"repo": "DCnomics/hard_way_for_python",
"path": "/ex4.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># 이 줄은 까다롭지만 정확히 따라하세요
합 = 나이 + 키 + 몸무게
print(f"{나이}, {키}, {몸무게}를 모두 더하면 {합} 랍니다.")<|fim_prefix|># repo: DCnomics/hard_way_for_python path: /ex4.py
자동차 = 100
차_안_공간 = 4.0
운전사 = 30
승객 = 90
운행_안하는_차 = 자동차 - 운전사
운행하는_차 = 운전사
총_정원 = 운행하는_차 * 차_안_공간
차당_평균_승객 = 승객 / 운행하는_차
<|fim_middle|>print("자동차", 자동차, "대가... | code_fim | hard | {
"lang": "python",
"repo": "DCnomics/hard_way_for_python",
"path": "/ex4.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lhericourt/trading path: /airflow/dags/candles_aggregation_dag.py
import logging
from airflow import DAG
from operators.candles_aggregation import CandleAggregation
<|fim_suffix|>with DAG(dag_id='trading_candles_aggregation', schedule_interval="@monthly", default_args=default_args) as dag:
... | code_fim | hard | {
"lang": "python",
"repo": "lhericourt/trading",
"path": "/airflow/dags/candles_aggregation_dag.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with DAG(dag_id='trading_candles_aggregation', schedule_interval="@monthly", default_args=default_args) as dag:
aggregated_candles = CandleAggregation(task_id='candles_aggregation', provide_context=True, scope='month')<|fim_prefix|># repo: lhericourt/trading path: /airflow/dags/candles_aggregation_d... | code_fim | hard | {
"lang": "python",
"repo": "lhericourt/trading",
"path": "/airflow/dags/candles_aggregation_dag.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>default_args = {
'start_date': datetime(2020, 12, 23),
'owner': 'airflow',
'retries': 3,
'retry_delay': timedelta(minutes=1),
'max_active_runs': 1,
'catchup': True
}
with DAG(dag_id='trading_candles_aggregation', schedule_interval="@monthly", default_args=default_args) as dag:
... | code_fim | medium | {
"lang": "python",
"repo": "lhericourt/trading",
"path": "/airflow/dags/candles_aggregation_dag.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lapic-ufjf/evolutionary-ACS-benchmark path: /experiments/004_plot_pareto_front.py
import os
from pprint import pprint
import numpy as np
from pymoo.factory import get_problem
from pymoo.visualization.scatter import Scatter
from acs.objective import reduce_objectives
from read.algorithm import ... | code_fim | hard | {
"lang": "python",
"repo": "lapic-ufjf/evolutionary-ACS-benchmark",
"path": "/experiments/004_plot_pareto_front.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# print('Comparing GA with NSGA-II using two objetives')
# print('=============================================\n')
# instances_results_name = create_results_name_list(instances, ['ga'], ['nsga_ii'], [2, 3])
# for (instance_name, results_name_list) in instances_results_name.items():
# print(instance... | code_fim | hard | {
"lang": "python",
"repo": "lapic-ufjf/evolutionary-ACS-benchmark",
"path": "/experiments/004_plot_pareto_front.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
print("Plotting initial points...")
plt.figure(1)
for trace in traces:
for point in trace:
plt.scatter(point[0], point[1], c='r', alpha=0.2)
print("Plotting preprocessed points...")
plt.figure(3)
for trace in processed_traces:
for point in trace:
plt.scatter(point[0], point[1... | code_fim | medium | {
"lang": "python",
"repo": "bhaveshk658/graphgen",
"path": "/random/gravity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
print("Plotting initial points...")
plt.figure(1)
for trace in traces:
for point in trace:
plt.scatter(point[0], point[1], c='r', alpha=0.2)
print("Plotting preprocessed points...")
plt.figure(3)
for trace in processed_traces:
for point in trace:
plt.scatter(point[0], point[... | code_fim | hard | {
"lang": "python",
"repo": "bhaveshk658/graphgen",
"path": "/random/gravity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bhaveshk658/graphgen path: /random/gravity.py
import graphgen
from graphgen.data import get_training_data, clean, gravity
from graphgen.graph import Graph, Node
from graphgen.generate import convert_to_graph
from graphgen.data.utils import direction
import numpy as np
import matplotlib.pyplot as... | code_fim | medium | {
"lang": "python",
"repo": "bhaveshk658/graphgen",
"path": "/random/gravity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # read the mask image
word_mask = np.array(Image.open(path.join(d, "./figures/circle_mask2.png")))
# construct wordcloud
wc = WordCloud(background_color="white", max_words=100, mask=word_mask,\
stopwords=STOPWORDS.add("and"))
print "generating word cloud ..."
for ... | code_fim | medium | {
"lang": "python",
"repo": "vsmolyakov/ml",
"path": "/lda/python/word_cloud.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vsmolyakov/ml path: /lda/python/word_cloud.py
#!/usr/bin/env python2
"""
Masked wordcloud
================
Using a mask you can generate wordclouds in arbitrary shapes.
"""
from os import path
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
from wordcloud import WordClo... | code_fim | hard | {
"lang": "python",
"repo": "vsmolyakov/ml",
"path": "/lda/python/word_cloud.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Filters out all tweets that are longer than
# The defined length, not including hashtags
def TweetsShorterThanMaximumLength(self, original_list, length):
short_list = list()
manipulator = TwitterUtils()
for status in original_list:
# Remove hashtags and then count the length
status_t... | code_fim | hard | {
"lang": "python",
"repo": "MosheBerman/brisket-mashup",
"path": "/source/TwitterFetcher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MosheBerman/brisket-mashup path: /source/TwitterFetcher.py
#
# This class downloads the movies from
# Twitter and parses them out for us.
#
from keys import APIKeys # Abstract out aPI keys for privacy
from TwitterUtils import TwitterUtils # Utility to manipulate Tweets
import twitter # Ba... | code_fim | hard | {
"lang": "python",
"repo": "MosheBerman/brisket-mashup",
"path": "/source/TwitterFetcher.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def generate_grammar(bnf_grammar, token_namespace):
"""
``bnf_text`` is a grammar in extended BNF (using * for repetition, + for
at-least-once repetition, [] for optional parts, | for alternatives and ()
for grouping).
It's not EBNF according to ISO/IEC 14977. It's a dialect Python us... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/parso/py2/parso/pgen2/generator.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: catboost/catboost path: /contrib/python/parso/py2/parso/pgen2/generator.py
# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
# Modifications:
# Copyright David Halter and Contributors
# Modifications are dual-licensed: MIT and PS... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/parso/py2/parso/pgen2/generator.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return '%s(%s)' % (self.__class__.__name__, self.value)
def _simplify_dfas(dfas):
"""
This is not theoretically optimal, but works well enough.
Algorithm: repeatedly look for two states that have the same
set of arcs (same labels pointing to the same nodes) and
unify them, un... | code_fim | hard | {
"lang": "python",
"repo": "catboost/catboost",
"path": "/contrib/python/parso/py2/parso/pgen2/generator.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wanyine/wanyine path: /home/tests.py
"""
This file demonstrates writing tests using the unittest module. These will pass
when you run "manage.py test".
Replace this with more appropriate tests for your application.
"""
from datetime import date, timedelta
from django.test import TestCase
from d... | code_fim | hard | {
"lang": "python",
"repo": "wanyine/wanyine",
"path": "/home/tests.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def create_profile(self, username = 'test', balance = 0):
user = models.User.objects.create_user(username)
profile = models.Profile(user = user, balance = balance)
profile.save()
return profile
def create_policy(self, sponsor, kickoff = date.today()):
poli... | code_fim | hard | {
"lang": "python",
"repo": "wanyine/wanyine",
"path": "/home/tests.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_sponse(self):
request = HttpRequest()
request.user = models.User.objects.create_user('test')
response = views.sponse(request)
self.assertTrue(response)
class AjaxTest(TestCase):
def test_sayHello(self):
response = ajax.sayHello(HttpRequest())
... | code_fim | hard | {
"lang": "python",
"repo": "wanyine/wanyine",
"path": "/home/tests.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for x in transaction.inputs:
if x.id not in unspent_ids:
failed1 = True
if x.id in used_ids_in_this_txn:
failed2 = True
used_ids_in_this_txn.append(x.id)
if failed1:
... | code_fim | hard | {
"lang": "python",
"repo": "n4kashu/yadacoin",
"path": "/yadacoin/miningpool.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def broadcast_block(cls, block):
Peers.init()
dup_test = Mongo.db.consensus.find_one({
'peer': 'me',
'index': block.index,
'block.version': BU.get_version_for_height(block.index)
})
if not dup_test:
print ... | code_fim | hard | {
"lang": "python",
"repo": "n4kashu/yadacoin",
"path": "/yadacoin/miningpool.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: n4kashu/yadacoin path: /yadacoin/miningpool.py
import time
import requests
from bitcoin.wallet import P2PKHBitcoinAddress
from config import Config
from mongo import Mongo
from peers import Peers
from block import Block, BlockFactory
from blockchain import Blockchain
from blockchainutils import B... | code_fim | hard | {
"lang": "python",
"repo": "n4kashu/yadacoin",
"path": "/yadacoin/miningpool.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0D0AResearch/gym-bandits path: /gym_bandits/scoreboard.py
from gym.scoreboard.registration import add_task, add_group
add_group(
id='bandits',
name='Bandits',
description='Various N-Armed Bandit environments'
)
add_task(
id='BanditTwoArmedDeterministicFixed-v0',
group='band... | code_fim | hard | {
"lang": "python",
"repo": "0D0AResearch/gym-bandits",
"path": "/gym_bandits/scoreboard.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Every bandit always pays out
Each action has a reward mean (selected from a normal distribution with mean 0 and std 1), and the actual
reward returns is selected with a std of 1 around the selected mean
""",
background="Described on page 30 of Sutton and Barto's [Reinforcement Learning... | code_fim | hard | {
"lang": "python",
"repo": "0D0AResearch/gym-bandits",
"path": "/gym_bandits/scoreboard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Import a global unit registry as each initialization is incompatible with each other
from .stdVars import ureg
# Table and combined table
from .table import Combined, TexTable<|fim_prefix|># repo: htrojan/TexUtils path: /__init__.py
import os
import sys
import math
# Import often used modules
import n... | code_fim | medium | {
"lang": "python",
"repo": "htrojan/TexUtils",
"path": "/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: htrojan/TexUtils path: /__init__.py
import os
import sys
import math
# Import often used modules
import numpy as np
from pint import UnitRegistry
from scipy import constants as const
from scipy.optimize import curve_fit
from uncertainties import ufloat
from uncertainties import unumpy as unp
<|... | code_fim | medium | {
"lang": "python",
"repo": "htrojan/TexUtils",
"path": "/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>html', sidB + '.html'
if os.path.exists(fA):
shutil.copy(fA, fB)
elif os.path.exists(fB):
shutil.copy(fB, fA)
else:
print('Neither %s nor %s found' % (fA, fB))<|fim_prefix|># repo: thotypous/moodle-assign-scripts path: /copy_pairs.py
#!/usr/bin/... | code_fim | medium | {
"lang": "python",
"repo": "thotypous/moodle-assign-scripts",
"path": "/copy_pairs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thotypous/moodle-assign-scripts path: /copy_pairs.py
#!/usr/bin/python3
import re
import sys
import os
import shutil
for line in sys.stdin:
if ',' in line:
sidA, sidB = [re.search(r'^\s*(\d+)', x).group(1) for x in line.split(',')]
fA, fB = sidA + '.<|fim_suffix|>sts(fB):
... | code_fim | medium | {
"lang": "python",
"repo": "thotypous/moodle-assign-scripts",
"path": "/copy_pairs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sts(fB):
shutil.copy(fB, fA)
else:
print('Neither %s nor %s found' % (fA, fB))<|fim_prefix|># repo: thotypous/moodle-assign-scripts path: /copy_pairs.py
#!/usr/bin/python3
import re
import sys
import os
import shutil
for line in sys.stdin:
if ',' in line:
<|fim_middl... | code_fim | hard | {
"lang": "python",
"repo": "thotypous/moodle-assign-scripts",
"path": "/copy_pairs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i, row in enumerate( gsagtab[gsag_ext].data ):
lx = row['lx']
ly = row['ly']
dx = row['dx']
dy = row['dy']
if not i:
ax.plot( [lx, lx+dx, lx+dx, lx, lx], [ly, ly, ly+dy, ly+dy, ly], color='r', label='Flagged Low Gain' )
else:
... | code_fim | hard | {
"lang": "python",
"repo": "jhunkeler/cosmo",
"path": "/cos_monitoring/simulations/show_blue.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> ax.set_xlim(0, 16384)
ax.set_ylim(300, 800)
ax.legend( shadow=True, numpoints=1 )
ax.set_xlabel('XCORR')
ax.set_ylabel('YCORR')
ax.set_title('%s at HV=163 and LP2' % segment)
raw_input()
fig.savefig( 'LP2_%s_blue_extraction.pdf' % (segment), bbox_inches='tight' )
i... | code_fim | hard | {
"lang": "python",
"repo": "jhunkeler/cosmo",
"path": "/cos_monitoring/simulations/show_blue.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jhunkeler/cosmo path: /cos_monitoring/simulations/show_blue.py
import matplotlib.pyplot as plt
import pyfits
import numpy as np
#plt.ioff()
plt.ion()
gsagtab = pyfits.open('/grp/hst/cdbs/lref/x6l1439el_gsag.fits')
xtractab = pyfits.open('/grp/hst/cdbs/lref/x6q17586l_1dx.fits')
gainmap = pyfits.... | code_fim | hard | {
"lang": "python",
"repo": "jhunkeler/cosmo",
"path": "/cos_monitoring/simulations/show_blue.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wuchen-huawei/huaweicloud-sdk-python-v3 path: /huaweicloud-sdk-swr/huaweicloudsdkswr/v2/swr_async_client.py
_params = request.get_file_stream()
response_headers = []
header_params['Content-Type'] = http_utils.select_header_content_type(
['application/json'])
... | code_fim | hard | {
"lang": "python",
"repo": "wuchen-huawei/huaweicloud-sdk-python-v3",
"path": "/huaweicloud-sdk-swr/huaweicloudsdkswr/v2/swr_async_client.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param DeleteUserRepositoryAuthRequest request
:return: DeleteUserRepositoryAuthResponse
"""
return self.delete_user_repository_auth_with_http_info(request)
def delete_user_repository_auth_with_http_info(self, request):
"""删除镜像权限
删除镜像权限
:param... | code_fim | hard | {
"lang": "python",
"repo": "wuchen-huawei/huaweicloud-sdk-python-v3",
"path": "/huaweicloud-sdk-swr/huaweicloudsdkswr/v2/swr_async_client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sjpacwa/SBChain path: /node.py
"""
node.py
This file defines the Node class which is used to store node specific
information.
2020 Stephen Pacwa and Daniel Okazaki
Santa Clara University
"""
# Standard library imports
from hashlib import sha1
# Local imports
from blockchain import Blockchain
... | code_fim | hard | {
"lang": "python",
"repo": "sjpacwa/SBChain",
"path": "/node.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if benchmark:
from threading import Semaphore
self.metadata['benchmark_lock'] = Semaphore(0)
if self.metadata['uuid'] == 'SYSTEM':
raise InvalidID
initialize_log(self.metadata['uuid'], debug)
# Create the Blockchain object.
sel... | code_fim | hard | {
"lang": "python",
"repo": "sjpacwa/SBChain",
"path": "/node.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lichao88/rcaudio path: /demo.py
from rcaudio import *
import time
import logging
logging.basicConfig(level=logging.INFO,
format='%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s')
def demo1():
CR = CoreRecorder(
time = 10,
sr = 1000,
... | code_fim | hard | {
"lang": "python",
"repo": "lichao88/rcaudio",
"path": "/demo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> SR = SimpleRecorder(sr = 20000)
BA = BeatAnalyzer(rec_time = 15, initial_bpm = 120, smooth_ratio = .8)
VA = VolumeAnalyzer(rec_time = 1)
SR.register(BA)
SR.register(VA)
SR.start()
low_volume_count = 0
while True:
v = VA.get_volume()
if v < 50:
l... | code_fim | hard | {
"lang": "python",
"repo": "lichao88/rcaudio",
"path": "/demo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: criteo-forks/hue path: /desktop/core/ext-py/pytest-django-3.10.0/pytest_django_test/settings_postgres.py
from .settings_base import * # noqa: F401 F403
# PyPy compatibility
try:
from psycopg2ct import compat
<|fim_suffix|>DATABASES = {
"default": {
"ENGINE": "django.db.backends... | code_fim | easy | {
"lang": "python",
"repo": "criteo-forks/hue",
"path": "/desktop/core/ext-py/pytest-django-3.10.0/pytest_django_test/settings_postgres.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>DATABASES = {
"default": {
"ENGINE": "django.db.backends.postgresql_psycopg2",
"NAME": "pytest_django_should_never_get_accessed",
"HOST": "localhost",
"USER": "",
}
}<|fim_prefix|># repo: criteo-forks/hue path: /desktop/core/ext-py/pytest-django-3.10.0/pytest_djang... | code_fim | medium | {
"lang": "python",
"repo": "criteo-forks/hue",
"path": "/desktop/core/ext-py/pytest-django-3.10.0/pytest_django_test/settings_postgres.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mehta-lab/microDL path: /tests/test_zarr_reading.py
#!/usr/bin/python
'''
Script for testing .zarr reading. Compares with .tiff reader to show that output preprocessed tiles and
metadata are the same from both inputs:
'''
from copy import deepcopy
import numpy as np
import numpy.testing
import ... | code_fim | hard | {
"lang": "python",
"repo": "mehta-lab/microDL",
"path": "/tests/test_zarr_reading.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Run tests
print('Running tests on tiles metadata and files')
# Get output config files
file_name = os.path.join(zarr_preprocess_config['output_dir'], 'preprocess_config.json')
zarr_out_config = aux_utils.read_json(file_name)
file_name = os.path.join(tiff_preprocess_config['output... | code_fim | hard | {
"lang": "python",
"repo": "mehta-lab/microDL",
"path": "/tests/test_zarr_reading.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lasofivec/slmp path: /main.py
#! /usr/bin/python
from geometry import z, X_mat, Y_mat, jac, eta1, eta2, npatchs, list_patchs
from scipy.sparse.linalg import spsolve, splu
from scipy.interpolate import interp2d
from scipy.io import mmread, mmwrite
import igakit.nurbs as nurbs
from scipy import int... | code_fim | hard | {
"lang": "python",
"repo": "lasofivec/slmp",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
zn = np.copy(znp1)
zn[np.where(abs(zn) < 10**-10)] = 0.
# -----------------------------------------------
# Printing of results and time-relative error
#------------------------------------------------
if ((tstep == 1)or(tstep%viewstep == 0)or(tstep == nstep-1)) :
list_ti... | code_fim | hard | {
"lang": "python",
"repo": "lasofivec/slmp",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Computing the characteristics' origin
char_eta1, char_eta2, where_char = get_pat_char(eta1, eta2, advec, dt)
# Extracting the particles that stay in their own domain:
char_eta1_id = np.copy(char_eta1)
char_eta2_id = np.copy(char_eta2)
tab_ind_out = []
for npat in list_patchs:
ind_out_pat = np.whe... | code_fim | hard | {
"lang": "python",
"repo": "lasofivec/slmp",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>while True:
try:
select = input("Enter the S.No corresponding the match: ")
if select.strip() == 'q':
break
details(x[int(select)][0])
except:
print("Invalid input!")<|fim_prefix|># repo: debasishbai/Cricket-Scorecard--python path: /Cricket-Scorecard/cricket-scorecard.py
import json
... | code_fim | medium | {
"lang": "python",
"repo": "debasishbai/Cricket-Scorecard--python",
"path": "/Cricket-Scorecard/cricket-scorecard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: debasishbai/Cricket-Scorecard--python path: /Cricket-Scorecard/cricket-scorecard.py
import json
from time import sleep
import requests
def match():
d = {}
count = 1
template1 = "http://cricapi.com/api/cricket"
data = requests.get(template1)
js = data.json()
if js['cache']:
for... | code_fim | hard | {
"lang": "python",
"repo": "debasishbai/Cricket-Scorecard--python",
"path": "/Cricket-Scorecard/cricket-scorecard.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> template2 = "http://cricapi.com/api/cricketScore?unique_id="
url = template2 + str(y)
data = requests.get(url)
js = data.json()
print()
if js['cache']:
print(js['team-1'],"Vs",js['team-2'])
print(js['score'])
print(js['innings-requirement'])
print()
x = match()
print("No.of Ongoi... | code_fim | medium | {
"lang": "python",
"repo": "debasishbai/Cricket-Scorecard--python",
"path": "/Cricket-Scorecard/cricket-scorecard.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hunsteve/NNEF-Tools path: /nnef_tools/core/matcher.py
# Copyright (c) 2017 The Khronos Group Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apa... | code_fim | hard | {
"lang": "python",
"repo": "hunsteve/NNEF-Tools",
"path": "/nnef_tools/core/matcher.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def copy(self,
dict_so_far=None,
allow_multi_consumer=None,
allow_multi_consumer_inside=None,
follow_producer=None):
return _MatchSettings(dict_so_far=utils.first_set(dict_so_far, self.dict_so_far),
allow_multi_c... | code_fim | hard | {
"lang": "python",
"repo": "hunsteve/NNEF-Tools",
"path": "/nnef_tools/core/matcher.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def operations(self):
assert self._did_match
return list(set(v for v in six.itervalues(self._dict) if isinstance(v, BaseOperation)))
def __nonzero__(self): # for python 2
return self._did_match
def __bool__(self): # for python 3
return self._di... | code_fim | hard | {
"lang": "python",
"repo": "hunsteve/NNEF-Tools",
"path": "/nnef_tools/core/matcher.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skelsec/minidump path: /minidump/streams/__init__.py
from .CommentStreamA import *
from .CommentStreamW import *
from .ContextStream import *
from .ExceptionStream import *
from .FunctionTableStream import *
from .HandleDataStream import *
from .HandleOperationListStream import *
from .JavaScript... | code_fim | hard | {
"lang": "python",
"repo": "skelsec/minidump",
"path": "/minidump/streams/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = __CommentStreamA__ + __CommentStreamW__ + __ContextStream__ + __ExceptionStream__ + __FunctionTableStream__ + __HandleDataStream__ + __HandleOperationListStream__ + __JavaScriptDataStream__ + __LastReservedStream__ + __Memory64ListStream__ + __MemoryInfoListStream__ + __MemoryListStream__ + __Mi... | code_fim | hard | {
"lang": "python",
"repo": "skelsec/minidump",
"path": "/minidump/streams/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Oscar-Rod/SnakeGame path: /snakegame/game/button.py
import pygame
colors_dictionary = {
"red": (200, 0, 0),
"green": (0, 200, 0),
"white": (255, 255, 255),
"black": (0, 0, 0)
}
class Button:
stop_the_game = "Button to stop the game"
start_the_game = "Button to start the... | code_fim | hard | {
"lang": "python",
"repo": "Oscar-Rod/SnakeGame",
"path": "/snakegame/game/button.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.color = color
self.text = text
pygame.draw.rect(self.screen, self.color, (
self.center[0] - self.width / 2, self.center[1] - self.height / 2,
self.width, self.height))
self.text_surface = self.font.render(self.text, True, self.text_color)
... | code_fim | medium | {
"lang": "python",
"repo": "Oscar-Rod/SnakeGame",
"path": "/snakegame/game/button.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._update(self.text, self.color)
self.screen.blit(self.text_surface, self.rect)
def _update(self, text, color):
self.color = color
self.text = text
pygame.draw.rect(self.screen, self.color, (
self.center[0] - self.width / 2, self.center[1] - self... | code_fim | medium | {
"lang": "python",
"repo": "Oscar-Rod/SnakeGame",
"path": "/snakegame/game/button.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keep-learning-cmd/noisyFER path: /loader/dataloader_raf.py
import torch
import scipy.misc as m
import os
import csv
import numpy as np
from tqdm import tqdm
from torch.utils import data
import cv2
from transforms import initAlignTransfer
import time
# RAF: 1: surprise, 2: fear, 3: disgust, 4: ha... | code_fim | hard | {
"lang": "python",
"repo": "keep-learning-cmd/noisyFER",
"path": "/loader/dataloader_raf.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> img = img.transpose((2, 0, 1)) # [H,W,C] --> [C,H,W]
img = ((img / 255.0 - 0.5) / 0.5) # normalize to [-1, 1]
img = torch.from_numpy(img).float()
exp_lbl = self.lbl_list[index]
return img, exp_lbl, img_path<|fim_prefix|># repo: keep-learning-cmd/noisyFER path: /... | code_fim | hard | {
"lang": "python",
"repo": "keep-learning-cmd/noisyFER",
"path": "/loader/dataloader_raf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Haldir65/Jimmy path: /tutorial/hello.py
#!/usr/bin/python3
print("COntent-type:text/html\r\n<|fim_suffix|>ello there"+str(i)+" </h2>")
print("</body></html>")<|fim_middle|>\r\n")
print("<html><body>")
print("<h1>It works really ! </h>")
for i in range(5):
print("<h2>H | code_fim | medium | {
"lang": "python",
"repo": "Haldir65/Jimmy",
"path": "/tutorial/hello.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Haldir65/Jimmy path: /tutorial/hello.py
#!/usr/bin/python3
print("COntent-type:text/html\r\n\r\n")
print("<html><body>")
print("<h1>It works rea<|fim_suffix|>ello there"+str(i)+" </h2>")
print("</body></html>")<|fim_middle|>lly ! </h>")
for i in range(5):
print("<h2>H | code_fim | easy | {
"lang": "python",
"repo": "Haldir65/Jimmy",
"path": "/tutorial/hello.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>ello there"+str(i)+" </h2>")
print("</body></html>")<|fim_prefix|># repo: Haldir65/Jimmy path: /tutorial/hello.py
#!/usr/bin/python3
print("COntent-type:text/html\r\n\r\n")
print("<html><body>")
print("<h1>It works rea<|fim_middle|>lly ! </h>")
for i in range(5):
print("<h2>H | code_fim | easy | {
"lang": "python",
"repo": "Haldir65/Jimmy",
"path": "/tutorial/hello.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BrianSipple/dedupe path: /test/test_haversine.py
import unittest
from dedupe.distance.haversine import compareLatLong
import numpy
class TestHaversine(unittest.TestCase):
<|fim_suffix|> def test_haversine_na(self):
km_dist_na = compareLatLong((0.0, 0.0), (1.0, 2.0))
assert num... | code_fim | hard | {
"lang": "python",
"repo": "BrianSipple/dedupe",
"path": "/test/test_haversine.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertAlmostEqual(km_dist_val, 2964, -1)
def test_haversine_zero(self):
km_dist_zero = compareLatLong(self.ord, self.ord)
self.assertAlmostEqual(km_dist_zero, 0.0, 0)
def test_haversine_na(self):
km_dist_na = compareLatLong((0.0, 0.0), (1.0, 2.0))
ass... | code_fim | medium | {
"lang": "python",
"repo": "BrianSipple/dedupe",
"path": "/test/test_haversine.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_haversine_zero(self):
km_dist_zero = compareLatLong(self.ord, self.ord)
self.assertAlmostEqual(km_dist_zero, 0.0, 0)
def test_haversine_na(self):
km_dist_na = compareLatLong((0.0, 0.0), (1.0, 2.0))
assert numpy.isnan(km_dist_na)
km_dist_na = compar... | code_fim | hard | {
"lang": "python",
"repo": "BrianSipple/dedupe",
"path": "/test/test_haversine.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Scratch microengine is the same as the default behavior"""
pass<|fim_prefix|># repo: polyswarm/microengine path: /src/microengine/scratch.py
from microengine import Microengine
<|fim_middle|>class ScratchMicroengine(Microengine):
| code_fim | easy | {
"lang": "python",
"repo": "polyswarm/microengine",
"path": "/src/microengine/scratch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: polyswarm/microengine path: /src/microengine/scratch.py
from microengine import Microengine
<|fim_suffix|> """Scratch microengine is the same as the default behavior"""
pass<|fim_middle|>class ScratchMicroengine(Microengine):
| code_fim | easy | {
"lang": "python",
"repo": "polyswarm/microengine",
"path": "/src/microengine/scratch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bhorda/BFRBAnticipationDataset path: /BFRB_Detection_Data/pipeline/1+_WindowSplit.py
import numpy as np
import pandas as ps
import math
import sys
### Positive windows
# prediction window and labeled window length in seconds
directory = sys.argv[1]
xSize = int(sys.argv[2]) # xwindow size
ySize ... | code_fim | hard | {
"lang": "python",
"repo": "Bhorda/BFRBAnticipationDataset",
"path": "/BFRB_Detection_Data/pipeline/1+_WindowSplit.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def BehaviourSelect(behaviourName):
if behaviourName == 'skin picking':
return 1
elif behaviourName == 'face touching':
return 2
elif behaviourName == 'fidgeting':
return 3
elif behaviourName == 'skin biting':
return 4
elif behaviourName == 'hand scratch... | code_fim | hard | {
"lang": "python",
"repo": "Bhorda/BFRBAnticipationDataset",
"path": "/BFRB_Detection_Data/pipeline/1+_WindowSplit.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: swdotcom/swdc-sublime path: /vendor/celery/backends/cassandra.py
# -* coding: utf-8 -*-
"""Apache Cassandra result store backend using the DataStax driver."""
from __future__ import absolute_import, unicode_literals
import sys
import threading
from celery import states
from celery.exceptions im... | code_fim | hard | {
"lang": "python",
"repo": "swdotcom/swdc-sublime",
"path": "/vendor/celery/backends/cassandra.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return 'cassandra://'
def _get_task_meta_for(self, task_id):
"""Get task meta-data for a task by id."""
self._get_connection()
res = self._session.execute(self._read_stmt, (task_id, )).one()
if not res:
return {'status': states.PENDING, 'result': N... | code_fim | hard | {
"lang": "python",
"repo": "swdotcom/swdc-sublime",
"path": "/vendor/celery/backends/cassandra.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @abc.abstractmethod
def get_stored_data(self, currency):
pass
@abc.abstractmethod
def save_over_data(self, currency, df):
pass
@abc.abstractmethod
def save_indicators(self, df, currency, ts):
pass
def sanitize(self, currency):
df = self.get_st... | code_fim | hard | {
"lang": "python",
"repo": "retorno/aquitania",
"path": "/aquitania/data_source/storage/abstract_storage_system.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_indicator_filename(self, finsec, ts):
generate_folder('{}/{}/'.format(self.indicator_output_folder, finsec))
return '{}/{}/{}{}'.format(self.indicator_output_folder, finsec, ts, self.extension)
def get_candles_filename(self, finsec):
generate_folder('{}/{}/'.format... | code_fim | hard | {
"lang": "python",
"repo": "retorno/aquitania",
"path": "/aquitania/data_source/storage/abstract_storage_system.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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