text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
def getEvent(self, index):
event = self._events[index]
if event[0] == "status":
return StatusEvent(*event)<|fim_prefix|># repo: freeekanayaka/testlogging path: /testlogging/testing.py
from collections import namedtuple
from testtools.testresult.doubles import StreamResul... | code_fim | easy | {
"lang": "python",
"repo": "freeekanayaka/testlogging",
"path": "/testlogging/testing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DavidNjoroge/idea-pitch path: /app/main/request.py
from ..models import Comment,User,Pitch,Category
<|fim_suffix|> cats=Category.query.all()
categories=[]
for cat in cats:
tem=str(cat)
temp=tem.split(' ')[1]
result=(temp,temp)
categories.append(result)
... | code_fim | easy | {
"lang": "python",
"repo": "DavidNjoroge/idea-pitch",
"path": "/app/main/request.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cats=Category.query.all()
categories=[]
for cat in cats:
tem=str(cat)
temp=tem.split(' ')[1]
result=(temp,temp)
categories.append(result)
# print (result)
return id<|fim_prefix|># repo: DavidNjoroge/idea-pitch path: /app/main/request.py
from ..model... | code_fim | easy | {
"lang": "python",
"repo": "DavidNjoroge/idea-pitch",
"path": "/app/main/request.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: blueyed/pytest path: /testing/deprecated_test.py
import inspect
import pytest
from _pytest import deprecated
from _pytest import nodes
@pytest.mark.parametrize(
"attribute",
(
"Collector",
"Module",
"Function",
"Instance",
"Session",
"Ite... | code_fim | hard | {
"lang": "python",
"repo": "blueyed/pytest",
"path": "/testing/deprecated_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> testdir.makepyfile(
"""
def test_foo():
pass
"""
)
assert_no_print_logs(testdir, ("--no-print-logs",))
@pytest.mark.filterwarnings("default")
def test_noprintlogs_is_deprecated_ini(testdir):
testdir.makeini(
"""
[pytest]
log_pr... | code_fim | hard | {
"lang": "python",
"repo": "blueyed/pytest",
"path": "/testing/deprecated_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.parametrize("junit_family", [None, "legacy", "xunit2"])
def test_warn_about_imminent_junit_family_default_change(testdir, junit_family):
"""Show a warning if junit_family is not defined and --junitxml is used (#6179)"""
testdir.makepyfile(
"""
def test_foo():
... | code_fim | hard | {
"lang": "python",
"repo": "blueyed/pytest",
"path": "/testing/deprecated_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def char2num(ch):
return {'0':0,'1':1,'2':2,'3':3,'4':4,'5':5,'6':6,'7':7,'8':8,'9':9,'.':-1}[ch]
nums = map(char2num,s)
point = 0
def toFloat(x,y):
nonlocal point
if y== -1:
point = 1
return x
if point==0:
return x*10+y;
else:
point = point*10
return x+y/point
return reduce(... | code_fim | hard | {
"lang": "python",
"repo": "tuhongwei/python-exercise",
"path": "/function/exercise1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># 利用map和reduce编写一个str2float函数，把字符串'123.456'转换成浮点数123.456
from functools import reduce
def str2float(s):
def char2num(ch):
return {'0':0,'1':1,'2':2,'3':3,'4':4,'5':5,'6':6,'7':7,'8':8,'9':9}[ch]
def str2int(s):
return reduce(lambda x,y: x*10+y,map(char2num,s))
try:
n = s.index('.')
s = s[:n] + ... | code_fim | medium | {
"lang": "python",
"repo": "tuhongwei/python-exercise",
"path": "/function/exercise1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tuhongwei/python-exercise path: /function/exercise1.py
#!/user/bin/env python3
# -*- coding: utf-8 -*-
# L1 = ['adam', 'LISA', 'barT']变成首字母大写
def normalize(name):
return str.capitalize(name)
L1 = ['adam', 'LISA', 'barT']
L2 = list(map(normalize,L1))
print(L2)
# 用lambda改写
L3 = list(map(lambda nam... | code_fim | hard | {
"lang": "python",
"repo": "tuhongwei/python-exercise",
"path": "/function/exercise1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BeryJu/supervisr path: /supervisr/mail/apps.py
"""Supervisr Mail app config"""
from supervisr.core.apps import SupervisrAppConfig
<|fim_suffix|> """Supervisr Mail app config"""
name = 'supervisr.mail'
label = 'supervisr_mail'
verbose_name = 'Supervisr Mail'
navbar_enabled = ... | code_fim | easy | {
"lang": "python",
"repo": "BeryJu/supervisr",
"path": "/supervisr/mail/apps.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Supervisr Mail app config"""
name = 'supervisr.mail'
label = 'supervisr_mail'
verbose_name = 'Supervisr Mail'
navbar_enabled = lambda self, request: True
title_modifier = lambda self, request: 'Mail'<|fim_prefix|># repo: BeryJu/supervisr path: /supervisr/mail/apps.py
"""Superv... | code_fim | easy | {
"lang": "python",
"repo": "BeryJu/supervisr",
"path": "/supervisr/mail/apps.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = 'supervisr.mail'
label = 'supervisr_mail'
verbose_name = 'Supervisr Mail'
navbar_enabled = lambda self, request: True
title_modifier = lambda self, request: 'Mail'<|fim_prefix|># repo: BeryJu/supervisr path: /supervisr/mail/apps.py
"""Supervisr Mail app config"""
from supervis... | code_fim | medium | {
"lang": "python",
"repo": "BeryJu/supervisr",
"path": "/supervisr/mail/apps.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: UCLA-StarAI/LearnSDD path: /code/movieExperiments.py
import sys, threading, time, math, random, os, re
import acQueryMaker, sddQueryMaker
from timeout_subprocess import run_with_timeout
pos_words = [69,87,88,105,80,282,283,285,300,357,358,378,392,413,439,447,451,589,614,631,632,847,875,864,9... | code_fim | hard | {
"lang": "python",
"repo": "UCLA-StarAI/LearnSDD",
"path": "/code/movieExperiments.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> queries ={"pos":lambda param: to_count_ac_query(param,pos_words,threshold),
"neg":lambda param: to_count_ac_query(param,neg_words,threshold),
"group":lambda param: to_group_ac_query(param,pos_words,neg_words),
"parity":lambda param: to_parity_ac_query(param),
"conj":lambda ... | code_fim | hard | {
"lang": "python",
"repo": "UCLA-StarAI/LearnSDD",
"path": "/code/movieExperiments.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> from ACquery import queryAC
start = time.time()
query = queryfun(param)
mid = time.time()
probability, nbClauses , makefile_time, ac_time = run_with_timeout(queryAC, (modelpath, query, nbvars, fname,evidence), timeout, (float('nan'),float('nan'),float('nan'),float('nan')))
end = time.time()
... | code_fim | hard | {
"lang": "python",
"repo": "UCLA-StarAI/LearnSDD",
"path": "/code/movieExperiments.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>code('utf8')
#for line in sys.stdin:
# sys.stdout.write(urllib.unquote(line)) decoding uri<|fim_prefix|># repo: zendannyy/Test_Scripts path: /freq/uri_decode.py
#!/usr/bin/python
import urllib, sys, time
#import urllib.parse
#def urldecode(url):
# return urllib.parse.unquote(url)
url = input("Ente... | code_fim | medium | {
"lang": "python",
"repo": "zendannyy/Test_Scripts",
"path": "/freq/uri_decode.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>urllib.unquote(url).decode('utf8')
print("Here is your output")
print urllib.unquote(url).decode('utf8')
#for line in sys.stdin:
# sys.stdout.write(urllib.unquote(line)) decoding uri<|fim_prefix|># repo: zendannyy/Test_Scripts path: /freq/uri_decode.py
#!/usr/bin/python
import urllib, sys, time
#impo... | code_fim | medium | {
"lang": "python",
"repo": "zendannyy/Test_Scripts",
"path": "/freq/uri_decode.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zendannyy/Test_Scripts path: /freq/uri_decode.py
#!/usr/bin/python
import urllib, sys, time
#import urllib.parse
#def urldecode(url):
# r<|fim_suffix|>code('utf8')
#for line in sys.stdin:
# sys.stdout.write(urllib.unquote(line)) decoding uri<|fim_middle|>eturn urllib.parse.unquote(url)
url... | code_fim | medium | {
"lang": "python",
"repo": "zendannyy/Test_Scripts",
"path": "/freq/uri_decode.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: masaomi/intro-machine-learning-training path: /python_notebooks/utils2.py
)/wei[i][1]],
color=dico_color[i],ls='--')
idx = (y_pred == k)
if idx.any():
ax[k].scatter(X[idx, 0], X[idx, 1], marker='o', c=[dico_color[h] for h in y[idx]], edgecolor='k'... | code_fim | hard | {
"lang": "python",
"repo": "masaomi/intro-machine-learning-training",
"path": "/python_notebooks/utils2.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: masaomi/intro-machine-learning-training path: /python_notebooks/utils2.py
dth=4)
plt.plot(fpr["macro"], tpr["macro"],
label='macro-average ROC curve (area = {0:0.2f})'
''.format(roc_auc["macro"]),
color='navy', linestyle=':', linew... | code_fim | hard | {
"lang": "python",
"repo": "masaomi/intro-machine-learning-training",
"path": "/python_notebooks/utils2.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> plot_contours(ax1, models, xx, yy,cmap=plt.cm.coolwarm, alpha=0.8)
ax1.scatter(X0, X1, c=y, cmap=plt.cm.coolwarm, s=20, edgecolors='k')
interc=models.intercept_
wei=models.coef_
for i in range(len(interc)):
ax1.plot([xx.min(),xx.max()],[-(interc[i]+wei[i][0]*xx.min())/wei[i][1]... | code_fim | hard | {
"lang": "python",
"repo": "masaomi/intro-machine-learning-training",
"path": "/python_notebooks/utils2.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Builds a Servient with both the TD catalogue and the DNS-SD service enabled."""
servient = Servient(
catalogue_port=find_free_port(),
dnssd_enabled=True,
dnssd_instance_name=Faker().pystr())
yield servient
@tornado.gen.coroutine
def shutdown():
yie... | code_fim | hard | {
"lang": "python",
"repo": "agmangas/wot-py",
"path": "/tests/wot/discovery/dnssd/conftest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agmangas/wot-py path: /tests/wot/discovery/dnssd/conftest.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import collections
import logging
import socket
import pytest
import tornado.gen
import tornado.ioloop
from faker import Faker
from tests.utils import find_free_port
from wotpy.support im... | code_fim | hard | {
"lang": "python",
"repo": "agmangas/wot-py",
"path": "/tests/wot/discovery/dnssd/conftest.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> from test_rospy.srv import TransitiveSrvRequest
m = TransitiveSrvRequest()
# invoking serialize should be enough to expose issue. The bug
# was that genmsg_py was failing to include the imports of
# embedded messages. Because messages are flattened, this
# c... | code_fim | hard | {
"lang": "python",
"repo": "minxuanjun/basalt_class",
"path": "/thirdparty/ros/ros_comm/test/test_rospy/test/unit/test_gensrv_py.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: minxuanjun/basalt_class path: /thirdparty/ros/ros_comm/test/test_rospy/test/unit/test_gensrv_py.py
#!/usr/bin/env python
# Software License Agreement (BSD License)
#
# Copyright (c) 2008, Willow Garage, Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or wit... | code_fim | hard | {
"lang": "python",
"repo": "minxuanjun/basalt_class",
"path": "/thirdparty/ros/ros_comm/test/test_rospy/test/unit/test_gensrv_py.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> ## #2133/2139
def test_test_rospy_TransitiveImport(self):
from test_rospy.srv import TransitiveSrvRequest
m = TransitiveSrvRequest()
# invoking serialize should be enough to expose issue. The bug
# was that genmsg_py was failing to include the imports of
# e... | code_fim | hard | {
"lang": "python",
"repo": "minxuanjun/basalt_class",
"path": "/thirdparty/ros/ros_comm/test/test_rospy/test/unit/test_gensrv_py.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeffbass/imagezmq path: /examples/t2_recv_images_via_sub.py
"""t2_recv_images_via_sub.py -- receive images using PUB/SUB messaging pattern.
This example program uses imagezmq to receive images from a matching program
that is sending images. This test pair uses the PUB/SUB messaging pattern.
1.... | code_fim | hard | {
"lang": "python",
"repo": "jeffbass/imagezmq",
"path": "/examples/t2_recv_images_via_sub.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>To end the programs, press Ctrl-C in the terminal window of each program. It is
normal to get error messages when pressing Ctrl-C. There is no error trapping in
this simple example program.
"""
import cv2
import imagezmq
# Instantiate and provide the first publisher address
image_hub = imagezmq.ImageHub... | code_fim | hard | {
"lang": "python",
"repo": "jeffbass/imagezmq",
"path": "/examples/t2_recv_images_via_sub.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> image properly. K3b, CDRecord and Burn 2.4.1u are reported to burn the anyboot image properly, without even needing to rename the file to *.iso. </p>""",
'cd' :"""<h1>Below are ISO CD Images</h1>
<p>They are designed for installing Haiku from a compact disc.</p>"""}<|fim_prefix|># repo: jrabbit/haiku-fil... | code_fim | hard | {
"lang": "python",
"repo": "jrabbit/haiku-files-redesign",
"path": "/paragraphs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jrabbit/haiku-files-redesign path: /paragraphs.py
instructions = {'raw': """<h1>Below are Raw Images</h1>
<p>They can be used with Qemu, written directly to a USB flash device, or mounted within Haiku.</p>""",
'vmware' : """<h1>Below are VMWare Images</h1>
<p>These images can be used with either... | code_fim | hard | {
"lang": "python",
"repo": "jrabbit/haiku-files-redesign",
"path": "/paragraphs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lcoghill/phyloboost path: /pipeline/purge-outliers.py
from Bio import SeqIO
import glob
handle = open('outlier-results.txt', 'r')
outliers = {}
out_dir = ''
<|fim_suffix|>## open the flagged alignment, remove any sequences that have the
## suspected misidentified TI values
for key, val in out... | code_fim | hard | {
"lang": "python",
"repo": "lcoghill/phyloboost",
"path": "/pipeline/purge-outliers.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>## open the flagged alignment, remove any sequences that have the
## suspected misidentified TI values
for key, val in outliers.items() :
sequences = list(SeqIO.parse(open(key), 'fasta'))
good_seqs = []
for s in sequences :
ti = s.id.split("|")[1][2:]
if ti not in val :
... | code_fim | hard | {
"lang": "python",
"repo": "lcoghill/phyloboost",
"path": "/pipeline/purge-outliers.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: longfeide2008/anchore-engine path: /anchore_engine/services/policy_engine/engine/policy/formatting.py
import datetime
import uuid
policy_line_format='{gate}:{trigger}:{action}'
param_format='{name}={value} '
whitelist_format='{gate} {trigger}'
def policy_json_to_txt(policy_json):
"""
Ta... | code_fim | hard | {
"lang": "python",
"repo": "longfeide2008/anchore-engine",
"path": "/anchore_engine/services/policy_engine/engine/policy/formatting.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return ret
def policy_txt_to_json(policy_txt):
"""
Convert a newline delimited string (e.g. read from a file) to a policy json in v1_0 format
:param policy_txt: single string of all lines with \n intact
:return: json object of 1_0 version policy object
"""
gen_date = datetime... | code_fim | hard | {
"lang": "python",
"repo": "longfeide2008/anchore-engine",
"path": "/anchore_engine/services/policy_engine/engine/policy/formatting.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ret = []
if whitelist_json.get('version',None) == '1_0':
for item in whitelist_json['items']:
ret.append(whitelist_format.format(gate=item['gate'], trigger=item['trigger_id']))
return ret
def policy_txt_to_json(policy_txt):
"""
Convert a newline delimited string ... | code_fim | hard | {
"lang": "python",
"repo": "longfeide2008/anchore-engine",
"path": "/anchore_engine/services/policy_engine/engine/policy/formatting.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> now = datetime.now()
if self._start_time + timedelta(seconds=30) > now:
return timedelta()
return datetime.now() - self._start_time
def _reset_start_time(self) -> None:
self._start_time = datetime.now()<|fim_prefix|># repo: grapl-security/grapl path: /src/... | code_fim | hard | {
"lang": "python",
"repo": "grapl-security/grapl",
"path": "/src/python/grapl-plugin-sdk/grapl_plugin_sdk/analyzer/analyzer_context.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@final
@dataclass(slots=True)
class AnalyzerContext:
_analyzer_name: AnalyzerName
_graph_client: GraphQueryProxyClient
_start_time: datetime
_allowed: dict[Uid, timedelta | None]
def get_graph_client(self) -> GraphQueryProxyClient:
return self._graph_client
def get_remai... | code_fim | hard | {
"lang": "python",
"repo": "grapl-security/grapl",
"path": "/src/python/grapl-plugin-sdk/grapl_plugin_sdk/analyzer/analyzer_context.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: grapl-security/grapl path: /src/python/grapl-plugin-sdk/grapl_plugin_sdk/analyzer/analyzer_context.py
from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import final
<|fim_suffix|> return self._graph_client
def g... | code_fim | hard | {
"lang": "python",
"repo": "grapl-security/grapl",
"path": "/src/python/grapl-plugin-sdk/grapl_plugin_sdk/analyzer/analyzer_context.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: igorcmag/tp_sim path: /tp_sim/envs/tp_sim_env.py
import gym
from collections import OrderedDict
from gym.spaces import Discrete, Box, Dict, MultiBinary
import pandas as pd
import numpy as np
import random
import tp_sim.envs.naive
# Auxiliary functions
# Convert permit number to permit tuple
def ... | code_fim | hard | {
"lang": "python",
"repo": "igorcmag/tp_sim",
"path": "/tp_sim/envs/tp_sim_env.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Update state
self.state = update_state(self.book, self.last_trans, self.in_poss[0], self.credits[0], self.t + 1)
# Increase timestamp by 1
self.t += 1
# Calculate reward
reward = reward_eval(self.state)
# Check if episode is done
if self... | code_fim | hard | {
"lang": "python",
"repo": "igorcmag/tp_sim",
"path": "/tp_sim/envs/tp_sim_env.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>on__ = "2.0.3"
__all__ = ["FfmpegQualityMetrics", "FfmpegQualityMetricsError", "__version__"]<|fim_prefix|># repo: morphline/ffmpeg-quality-metrics path: /ffmpeg_quality_metrics/__init__.py
from .ffmpeg_quality_metrics import FfmpegQual<|fim_middle|>ityMetrics, FfmpegQualityMetricsError
__versi | code_fim | easy | {
"lang": "python",
"repo": "morphline/ffmpeg-quality-metrics",
"path": "/ffmpeg_quality_metrics/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: morphline/ffmpeg-quality-metrics path: /ffmpeg_quality_metrics/__init__.py
from .ffmpeg_quality_metrics import FfmpegQual<|fim_suffix|>s", "FfmpegQualityMetricsError", "__version__"]<|fim_middle|>ityMetrics, FfmpegQualityMetricsError
__version__ = "2.0.3"
__all__ = ["FfmpegQualityMetric | code_fim | medium | {
"lang": "python",
"repo": "morphline/ffmpeg-quality-metrics",
"path": "/ffmpeg_quality_metrics/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def temporary_file_path(self):
return self.filepath
class TestScoutSuiteParser(TestCase):
def setup(self, testfile):
file = MockFileObject(testfile)
product_type = Product_Type(critical_product=True, key_product=False)
product_type.save()
test_type = Test... | code_fim | medium | {
"lang": "python",
"repo": "TarlogicSecurity/django-DefectDojo",
"path": "/dojo/unittests/tools/test_scoutsuite_parser.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TestScoutSuiteParser(TestCase):
def setup(self, testfile):
file = MockFileObject(testfile)
product_type = Product_Type(critical_product=True, key_product=False)
product_type.save()
test_type = Test_Type(static_tool=True, dynamic_tool=False)
test_type.save... | code_fim | medium | {
"lang": "python",
"repo": "TarlogicSecurity/django-DefectDojo",
"path": "/dojo/unittests/tools/test_scoutsuite_parser.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TarlogicSecurity/django-DefectDojo path: /dojo/unittests/tools/test_scoutsuite_parser.py
from django.test import TestCase
from dojo.tools.scout_suite.parser import ScoutSuiteParser
from django.utils import timezone
from dojo.models import Test, Engagement, Product, Product_Type, Test_Type
class... | code_fim | medium | {
"lang": "python",
"repo": "TarlogicSecurity/django-DefectDojo",
"path": "/dojo/unittests/tools/test_scoutsuite_parser.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> while queue != []:
n = queue.pop(0)
# for k in S[n]:
for k in sorted(S[n]):
if k not in postOrder and S[n][k] == 'green':
postOrder.insert(postOrder.index(n), k)
queue.append(k)
return {n:(i + 1) for i, n in enumerate(postOrd... | code_fim | hard | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/Udacity/Bridges.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def descendantsList(G, root):
bfs = BFS(G, root)
parent = bfs['parent']
# deep = bfs['deep']
descendants = {}
for k in G:
descendants[k] = [k]
for k in parent:
n = k
# for _ in xrange(deep[n]):
while parent[n] != None:
n = paren... | code_fim | hard | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/Udacity/Bridges.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Camiloasc1/AlgorithmsUNAL path: /Udacity/Bridges.py
# Bridge Edges v4
#
# Find the bridge edges in a graph given the
# algorithm in lecture.
# Complete the intermediate steps
# - create_rooted_spanning_tree
# - post_order
# - number_of_descendants
# - lowest_post_order
# - highest_post_order... | code_fim | hard | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/Udacity/Bridges.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def open(self, file_name, **keywords):
BookReader.open(self, file_name, **keywords)
self._load_from_file()
def open_stream(self, file_stream, **keywords):
if not hasattr(file_stream, "seek"):
# python 2
# Hei zipfile in odfpy would do a seek
... | code_fim | hard | {
"lang": "python",
"repo": "mobanbot/pyexcel-xlsxr",
"path": "/pyexcel_xlsxr/xlsxr.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mobanbot/pyexcel-xlsxr path: /pyexcel_xlsxr/xlsxr.py
"""
pyexcel_xlsxr.xlsxr
~~~~~~~~~~~~~~~~~~~
The lower level xlsx file format handler
:copyright: (c) 2017 by Onni Software Ltd & its contributors
:license: New BSD License
"""
from datetime import datetime, date, time
from ... | code_fim | hard | {
"lang": "python",
"repo": "mobanbot/pyexcel-xlsxr",
"path": "/pyexcel_xlsxr/xlsxr.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return result
def read_sheet(self, native_sheet):
"""read one native sheet"""
sheet = XLSXSheet(native_sheet, **self._keywords)
return {sheet.name: sheet.to_array()}
def _load_from_memory(self):
self._native_book = XLSXBookSet(self._file_stream)
def _... | code_fim | hard | {
"lang": "python",
"repo": "mobanbot/pyexcel-xlsxr",
"path": "/pyexcel_xlsxr/xlsxr.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wayne009007/sdcflows path: /sdcflows/workflows/fit/syn.py
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""
Estimating the susceptibility distortions without fieldmaps.
.. testsetup::
>>> tmpdir = getfixture('tmpdir')
>... | code_fim | hard | {
"lang": "python",
"repo": "wayne009007/sdcflows",
"path": "/sdcflows/workflows/fit/syn.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _fixed_masks_arg(mask):
"""
Prepare the ``fixed_image_masks`` argument of SyN.
Example
-------
>>> _fixed_masks_arg("atlas_mask.nii.gz")
['NULL', 'atlas_mask.nii.gz']
"""
return ["NULL", mask]
def _extract_field(in_file, epi_meta):
"""
Extract the nonzero c... | code_fim | hard | {
"lang": "python",
"repo": "wayne009007/sdcflows",
"path": "/sdcflows/workflows/fit/syn.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # fmt: off
workflow.connect([
(inputnode, transform_list, [("anat2epi_xfm", "in1"),
("std2anat_xfm", "in2")]),
(inputnode, invert_t1w, [("anat_brain", "in_file"),
(("epi_ref", _pop), "ref_file")]),
(input... | code_fim | hard | {
"lang": "python",
"repo": "wayne009007/sdcflows",
"path": "/sdcflows/workflows/fit/syn.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tpdn/python-winscard path: /winscard/__init__.py
__author__ = 'tpdn'
from ctypes import *
<|fim_suffix|>from types import *
from error import *
from const import *
from utils import *
from reader import *
from scard import *<|fim_middle|>scard_dll = WinDLL('winscard.dll')
| code_fim | easy | {
"lang": "python",
"repo": "tpdn/python-winscard",
"path": "/winscard/__init__.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>from types import *
from error import *
from const import *
from utils import *
from reader import *
from scard import *<|fim_prefix|># repo: tpdn/python-winscard path: /winscard/__init__.py
__author__ = 'tpdn'
from ctypes import *
<|fim_middle|>scard_dll = WinDLL('winscard.dll')
| code_fim | easy | {
"lang": "python",
"repo": "tpdn/python-winscard",
"path": "/winscard/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class SQLDebugPanel(DebugPanel):
'''
Panel that displays information about the SQL queries run while processing
the request.
'''
name = 'SQL'
template = 'debug_toolbar/panels/sql.html'
has_content = True
def __init__(self, *args, **kwargs):
super(SQLDebugPanel, se... | code_fim | hard | {
"lang": "python",
"repo": "tschellenbach/django-debug-toolbar",
"path": "/debug_toolbar/panels/sql.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tschellenbach/django-debug-toolbar path: /debug_toolbar/panels/sql.py
import re
import uuid
from django.db.backends import BaseDatabaseWrapper
from django.utils.html import escape
from django.utils.safestring import mark_safe
from django.utils.translation import ugettext_lazy as _, ungettext_laz... | code_fim | hard | {
"lang": "python",
"repo": "tschellenbach/django-debug-toolbar",
"path": "/debug_toolbar/panels/sql.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if trans_id:
self._queries[i-1][1]['ends_trans'] = True
# Should we check for duplicate queries?
dupe_queries = None
if _get_setting('SQL_DUPLICATES'):
dupe_queries = self._get_dupe_queries()
self.record_stats({
'databas... | code_fim | hard | {
"lang": "python",
"repo": "tschellenbach/django-debug-toolbar",
"path": "/debug_toolbar/panels/sql.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ahmad31/Web_Flask_Cassandra path: /flask/lib/python2.7/site-packages/whoosh/lang/snowball/english.py
f the algorithm.
:type __step1a_suffixes: tuple
:cvar __step1b_suffixes: Suffixes to be deleted in step 1b of the algorithm.
:type __step1b_suffixes: tuple
:cvar __step2_suffixes: ... | code_fim | hard | {
"lang": "python",
"repo": "Ahmad31/Web_Flask_Cassandra",
"path": "/flask/lib/python2.7/site-packages/whoosh/lang/snowball/english.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(r2) >= 1:
r2 = "".join((r2[:-1], "e"))
else:
r2 = ""
elif suffix == "entli":
word = word[:-2]
r1 = r1[:-2]
... | code_fim | hard | {
"lang": "python",
"repo": "Ahmad31/Web_Flask_Cassandra",
"path": "/flask/lib/python2.7/site-packages/whoosh/lang/snowball/english.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def is_addr_open(url, default_port=None):
o = urlparse(url)
return _is_service_open(o.hostname, o.port or default_port, socket.SOCK_STREAM)
def check_tcp_service(name, addr, port):
attempt = 1
trace = "checking TCP service %s on %s:%d..." % (name, addr, port)
print("%s %d." % (trace... | code_fim | hard | {
"lang": "python",
"repo": "GeneralCommission/kraken",
"path": "/server/kraken/server/srvcheck.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> attempt = 1
trace = "checking TCP service %s on %s:%d..." % (name, addr, port)
print("%s %d." % (trace, attempt))
while not _is_service_open(addr, port, socket.SOCK_STREAM):
if attempt < 3:
time.sleep(2)
elif attempt < 10:
time.sleep(5)
else:... | code_fim | hard | {
"lang": "python",
"repo": "GeneralCommission/kraken",
"path": "/server/kraken/server/srvcheck.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GeneralCommission/kraken path: /server/kraken/server/srvcheck.py
# Copyright 2020 The Kraken Authors
#
# 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.... | code_fim | hard | {
"lang": "python",
"repo": "GeneralCommission/kraken",
"path": "/server/kraken/server/srvcheck.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class NER_Dataset_for_Adapter(Dataset):
def __init__(self, tokenizer, df, label_name):
self.label_name = label_name
self.mode = "train"
self.positive_label, self.sentences, self.tags \
= get_training_label_ane_data_by_df_according_to_label_name_and_alias(df... | code_fim | hard | {
"lang": "python",
"repo": "EasonC13/labs-cicero-classify-api",
"path": "/utils/trainer/NER.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EasonC13/labs-cicero-classify-api path: /utils/trainer/NER.py
import pandas as pd
import pymongo
import numpy as np
from core.config import (
MONGODB_URL,DATABASE_NAME,
NER_LABEL_COLLECTION,
LABEL_COLLECTION,
LABEL_TRAIN_JOB_COLLECTION,
CONFIG_COLLECTION,
NER_TRAINER_DATA... | code_fim | hard | {
"lang": "python",
"repo": "EasonC13/labs-cicero-classify-api",
"path": "/utils/trainer/NER.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>for q, sg in result:
print(str(q) + ":\t" + str(sg.subgroup_description))
# print WRAccQF().evaluate_from_dataset(data, Subgroup(target, []))<|fim_prefix|># repo: flemmerich/pysubgroup path: /tests/t_simple_dfs.py
from timeit import default_timer as timer
import pysubgroup as ps
from pysubgroup.dat... | code_fim | medium | {
"lang": "python",
"repo": "flemmerich/pysubgroup",
"path": "/tests/t_simple_dfs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: flemmerich/pysubgroup path: /tests/t_simple_dfs.py
from timeit import default_timer as timer
import pysubgroup as ps
from pysubgroup.datasets import get_credit_data
<|fim_suffix|>for q, sg in result:
print(str(q) + ":\t" + str(sg.subgroup_description))
# print WRAccQF().evaluate_from_datas... | code_fim | hard | {
"lang": "python",
"repo": "flemmerich/pysubgroup",
"path": "/tests/t_simple_dfs.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> tag, name = TextUtils.tag_and_namespace_from_text("{}")
self.assertIsNotNone(tag)
self.assertEqual("{}", tag)
self.assertIsNone(name)
tag, name = TextUtils.tag_and_namespace_from_text("{http://alicebot.org/2001/AIML}")
self.assertIsNotNone(tag)
self... | code_fim | hard | {
"lang": "python",
"repo": "keiffster/program-y",
"path": "/test/programytest/utils/text/test_text.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keiffster/program-y path: /test/programytest/utils/text/test_text.py
import os
import unittest
from programy.utils.text.text import TextUtils
#############################################################################
#
class TextUtilsTests(unittest.TestCase):
def test_get_tabs(self):
... | code_fim | hard | {
"lang": "python",
"repo": "keiffster/program-y",
"path": "/test/programytest/utils/text/test_text.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> tag, name = TextUtils.tag_and_namespace_from_text("text")
self.assertIsNotNone(tag)
self.assertEqual("text", tag)
self.assertIsNone(name)
tag, name = TextUtils.tag_and_namespace_from_text("{}")
self.assertIsNotNone(tag)
self.assertEqual("{}", tag)
... | code_fim | hard | {
"lang": "python",
"repo": "keiffster/program-y",
"path": "/test/programytest/utils/text/test_text.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sx14/open-relation.pytorch path: /open_relation/dataset/lib/to_pascal_format.py
import os
import shutil
import xml.dom.minidom
def output_pascal_format(mid_data, output_path):
# mid_data:
# filename
# width
# height
# depth
# objects
# -- xmin
# -- ymin
#... | code_fim | hard | {
"lang": "python",
"repo": "sx14/open-relation.pytorch",
"path": "/open_relation/dataset/lib/to_pascal_format.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>s_truncated_node = des_xml_dom.createElement('truncated')
des_truncated_node.appendChild(des_truncated)
des_object_node.appendChild(des_truncated_node)
# difficult
des_object_difficult = des_xml_dom.createTextNode(str(org_object['difficult']))
des_object_difficult_n... | code_fim | hard | {
"lang": "python",
"repo": "sx14/open-relation.pytorch",
"path": "/open_relation/dataset/lib/to_pascal_format.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _return_package_url(project_root, package):
# See if there is a different index set.
config_file = os.path.join(project_root, CONFIG_DIR, CONFIG_FILE)
if os.path.exists(config_file):
kwargs = load_yaml_file(config_file)
index_url = kwargs['package_index']
logging.in... | code_fim | hard | {
"lang": "python",
"repo": "CarmeLabs/carme",
"path": "/src/cli/commands/package.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CarmeLabs/carme path: /src/cli/commands/package.py
'''
Manage project packages
'''
import os
import sys
import ruamel
import logging
import click
from ...modules.packager import Packager
from ...modules.gitwrapper import Git
from ...modules.base import setup_logger, get_project_root, CONFIG_DIR... | code_fim | hard | {
"lang": "python",
"repo": "CarmeLabs/carme",
"path": "/src/cli/commands/package.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Some packages can be install multiple packages.
if isinstance(package, ruamel.yaml.comments.CommentedSeq):
# Loop through packages
for x in package:
logging.info('Multiple packages, installing: '+x)
x_url = _return_package_url(project_root, str(x))
... | code_fim | hard | {
"lang": "python",
"repo": "CarmeLabs/carme",
"path": "/src/cli/commands/package.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ghicheon/CVND---Image-Captioning-Project path: /model.py
import torch
import torch.nn as nn
import torchvision.models as models
import numpy as np
class EncoderCNN(nn.Module):
def __init__(self, embed_size):
super(EncoderCNN, self).__init__()
resnet = models.resne... | code_fim | hard | {
"lang": "python",
"repo": "ghicheon/CVND---Image-Captioning-Project",
"path": "/model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def forward(self, images):
features = self.resnet(images)
features = features.view(features.size(0), -1)
features = self.embed(features)
return features
class DecoderRNN(nn.Module):
def __init__(self, embed_size, hidden_size, vocab_size, num_layers=1):... | code_fim | medium | {
"lang": "python",
"repo": "ghicheon/CVND---Image-Captioning-Project",
"path": "/model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def sample(self, inputs, states=None, max_len=20):
" accepts pre-processed image tensor (inputs) and returns predicted sentence (list of tensor ids of length max_len) "
#print("input.shape ", inputs.shape) # 1 1 512
ret=[]
for i in range(max_len):
... | code_fim | hard | {
"lang": "python",
"repo": "ghicheon/CVND---Image-Captioning-Project",
"path": "/model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: opnfv/fds path: /networking-odl/networking_odl/db/models.py
# Copyright (c) 2015 OpenStack Foundation
# All Rights Reserved.
#
# 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 t... | code_fim | medium | {
"lang": "python",
"repo": "opnfv/fds",
"path": "/networking-odl/networking_odl/db/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> object_type = sa.Column(sa.String(36), nullable=False)
object_uuid = sa.Column(sa.String(36), nullable=False)
operation = sa.Column(sa.String(36), nullable=False)
data = sa.Column(sa.PickleType, nullable=True)
state = sa.Column(sa.Enum(odl_const.PENDING, odl_const.FAILED,
... | code_fim | medium | {
"lang": "python",
"repo": "opnfv/fds",
"path": "/networking-odl/networking_odl/db/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> __tablename__ = 'opendaylightjournal'
object_type = sa.Column(sa.String(36), nullable=False)
object_uuid = sa.Column(sa.String(36), nullable=False)
operation = sa.Column(sa.String(36), nullable=False)
data = sa.Column(sa.PickleType, nullable=True)
state = sa.Column(sa.Enum(odl_con... | code_fim | hard | {
"lang": "python",
"repo": "opnfv/fds",
"path": "/networking-odl/networking_odl/db/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leonardorccosta/Machine-Learning-Repo path: /Hidden Markov Model.py
import pandas as pd
import numpy as np
#loads datasets
X = pd.read_csv(path_X)
# X is composed of 16 numerical and categorical features and 40 categorical sequential answers to questions
# either A, B, C, D, E
#Label ... | code_fim | hard | {
"lang": "python",
"repo": "leonardorccosta/Machine-Learning-Repo",
"path": "/Hidden Markov Model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#second approach
remodel = hmm.GaussianHMM(n_components=5, covariance_type="full", n_iter=100)
X_markov = entireData3.reshape(entireData3.shape[0], entireData3.shape[1])
X_markov2 = pd.DataFrame(X_markov)
X_markov2 = X_markov2.values.flatten()
lengths =[]
#for j in range(np.size(X_markov,0))
for i ... | code_fim | hard | {
"lang": "python",
"repo": "leonardorccosta/Machine-Learning-Repo",
"path": "/Hidden Markov Model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>np.random.seed(9)
#initializing the model
modelmm = hmm.GaussianHMM(n_components=7, covariance_type="full")
# transition weights, assuming they are known
modelmm.startprob_ = np.array([0.001, 0.049, 0.19, 0.19, 0.19, 0.19, 0.19])
modelmm.transmat_ = np.array([[0.001, 0.049, 0.19, 0.19, 0.19, 0.19, ... | code_fim | hard | {
"lang": "python",
"repo": "leonardorccosta/Machine-Learning-Repo",
"path": "/Hidden Markov Model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openstack/neutron path: /neutron/agent/dhcp_agent.py
# Copyright 2015 OpenStack Foundation
#
# All Rights Reserved.
#
# 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 Licens... | code_fim | hard | {
"lang": "python",
"repo": "openstack/neutron",
"path": "/neutron/agent/dhcp_agent.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
register_options(cfg.CONF)
common_config.init(sys.argv[1:])
config.setup_logging()
config.setup_privsep()
server = neutron_service.Service.create(
binary=constants.AGENT_PROCESS_DHCP,
topic=topics.DHCP_AGENT,
report_interval=cfg.CONF.AGENT.report_in... | code_fim | hard | {
"lang": "python",
"repo": "openstack/neutron",
"path": "/neutron/agent/dhcp_agent.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mobilityhouse/resin-release-tool path: /tests/integration/test_info.py
from balena.exceptions import ApplicationNotFound
from click.testing import CliRunner
from resin_release_tool.cli import cli
<|fim_suffix|> result = runner.invoke(cli, ["info"])
assert result.exit_code == 1
assert... | code_fim | hard | {
"lang": "python",
"repo": "mobilityhouse/resin-release-tool",
"path": "/tests/integration/test_info.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> monkeypatch.setenv("RESIN_TOKEN", "fake")
monkeypatch.setenv("RESIN_APP", "123")
monkeypatch.setenv("TEST", "true")
assert os.getenv("RESIN_TOKEN") == "fake"
assert os.getenv("RESIN_APP") == "123"
runner = CliRunner()
result = runner.invoke(cli, ["info"])
assert result.e... | code_fim | hard | {
"lang": "python",
"repo": "mobilityhouse/resin-release-tool",
"path": "/tests/integration/test_info.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rc14193/leetCodeSolns path: /DesignHashSet.py
# https://leetcode.com/explore/learn/card/hash-table/182/practical-applications/1139/
# According to trial 160ms and 18.6mb
# 78.74 % time and 92.01% space
class MyHashSet:
def __init__(self):
"""
Initialize your data structure h... | code_fim | medium | {
"lang": "python",
"repo": "rc14193/leetCodeSolns",
"path": "/DesignHashSet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Returns true if this set contains the specified element
"""
y = key % 80
return key in self.arr[y]
# Your MyHashSet object will be instantiated and called as such:
# obj = MyHashSet()
# obj.add(key)
# obj.remove(key)
# param_3 = obj.contains(key)<|fim_prefix|... | code_fim | hard | {
"lang": "python",
"repo": "rc14193/leetCodeSolns",
"path": "/DesignHashSet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def item_outcomes(i):
if i == 0:
return "ERROR"
elif i == 1:
return "Extremely cursed item"
elif i < 4:
return "Cursed item"
elif i < 8:
return "Mostly useless item"
elif i < 12:
return "Mediocre item"
elif i < 15:
return "Good item"
... | code_fim | hard | {
"lang": "python",
"repo": "moose705/moosebot",
"path": "/outcome_tables.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: moose705/moosebot path: /outcome_tables.py
def action_outcomes(i):
if i == 0:
return "ERROR"
elif i == 1:
return "Overwhelming failure"
elif i < 4:
return "Failure"
elif i < 8:
return "Failure, but not completely"
elif i < 12:
return "Ne... | code_fim | medium | {
"lang": "python",
"repo": "moose705/moosebot",
"path": "/outcome_tables.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def testNotify(self):
db=DataBuffer(2,9,1)
mat=np.array([[1,1,1],[2,2,2]]).transpose()
chunk=DataChunk(mat.shape[1],mat.shape[0],mat)
db.notify(chunk)
self.assertTrue((db.getBuff()==self.step1).all())
#step 2
mat=np.array([[3,3,3],[4,4,4]]).transpose()
chunk=DataChunk(mat.shape[1],mat.... | code_fim | hard | {
"lang": "python",
"repo": "capitancambio/brainz",
"path": "/brainz/data/DataBufferTest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def testNotify(self):
db=DataBuffer(2,9,1)
mat=np.array([[1,1,1],[2,2,2]]).transpose()
chunk=DataChunk(mat.shape[1],mat.shape[0],mat)
db.notify(chunk)
self.assertTrue((db.getBuff()==self.step1).all())
#step 2
mat=np.array([[3,3,3],[4,4,4]]).transpose()
chunk=DataChunk(mat.shape[1],mat.sha... | code_fim | hard | {
"lang": "python",
"repo": "capitancambio/brainz",
"path": "/brainz/data/DataBufferTest.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: capitancambio/brainz path: /brainz/data/DataBufferTest.py
import unittest
from data.bus import DataBuffer,DataChunk
import numpy as np
class DataBufferTest(unittest.TestCase):
"""unit tests"""
def __init__(self, name):
super(DataBufferTest, self).__init__(name)
self.name = name
<|fim_suf... | code_fim | hard | {
"lang": "python",
"repo": "capitancambio/brainz",
"path": "/brainz/data/DataBufferTest.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zagaran/instant-census path: /app.py
import sys
import traceback
import jinja2
from bson import ObjectId
from flask import Flask, render_template, redirect, session, request, flash
from flaskext.markdown import Markdown
from mongolia import ID_KEY
from raven.contrib.flask import Sentry
from rave... | code_fim | hard | {
"lang": "python",
"repo": "zagaran/instant-census",
"path": "/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@app.route('/broken')
def broken_page():
[][0]
return {}
@app.context_processor
def inject_unhandled_users_count():
# hacky fix for when user is not logged in, do not inject unhandled users count
if not NEEDS_REVIEW_COUNTS or not session or "admin_id" not in session:
return {"unha... | code_fim | hard | {
"lang": "python",
"repo": "zagaran/instant-census",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> [][0]
return {}
@app.context_processor
def inject_unhandled_users_count():
# hacky fix for when user is not logged in, do not inject unhandled users count
if not NEEDS_REVIEW_COUNTS or not session or "admin_id" not in session:
return {"unhandled_user_count": ""}
users_filter_k... | code_fim | hard | {
"lang": "python",
"repo": "zagaran/instant-census",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: qfizik/tket path: /pytket/pytket/backends/status.py
# Copyright 2019-2021 Cambridge Quantum Computing
#
# 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... | code_fim | hard | {
"lang": "python",
"repo": "qfizik/tket",
"path": "/pytket/pytket/backends/status.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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