text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: yyht/sinkhorn-loss path: /Sentiment/dataset/train_test_split.py
import pandas as pd
import logging
from sklearn.model_selection import train_test_split
import sklearn
import torch
f_names = ['loc_Clothing_Shoes_and_Jewelry.csv',
'loc_Toys_and_Games.csv',
'loc_Cell_Phone... | code_fim | hard | {
"lang": "python",
"repo": "yyht/sinkhorn-loss",
"path": "/Sentiment/dataset/train_test_split.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
save train-test split
'''
train_test_split_dir = "../train_test_split"
import pickle as pk
pk.dump({
'train_labels':train_labels,
'train_texts':train_texts,
'val_labels':val_labels,
'val_texts':val_texts,
'test_lab... | code_fim | hard | {
"lang": "python",
"repo": "yyht/sinkhorn-loss",
"path": "/Sentiment/dataset/train_test_split.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kohnakagawa/ghidra_scripts path: /ghidra9.2.1_pyi/ghidra/feature/vt/api/impl/MatchSetImpl.pyi
import ghidra.feature.vt.api.impl
import ghidra.feature.vt.api.main
import ghidra.program.model.address
import java.lang
import java.util
class MatchSetImpl(object, ghidra.feature.vt.api.main.VTMatchSe... | code_fim | hard | {
"lang": "python",
"repo": "kohnakagawa/ghidra_scripts",
"path": "/ghidra9.2.1_pyi/ghidra/feature/vt/api/impl/MatchSetImpl.pyi",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def notifyAll(self) -> None: ...
def removeMatch(self, __a0: ghidra.feature.vt.api.main.VTMatch) -> bool: ...
def toString(self) -> unicode: ...
@overload
def wait(self) -> None: ...
@overload
def wait(self, __a0: long) -> None: ...
@overload
def wait(self, __a0: l... | code_fim | hard | {
"lang": "python",
"repo": "kohnakagawa/ghidra_scripts",
"path": "/ghidra9.2.1_pyi/ghidra/feature/vt/api/impl/MatchSetImpl.pyi",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ahlusar1989/probablepeople path: /tests/test_tokenizing.py
from probablepeople import tokenize
import unittest
class TestTokenizing(unittest.TestCase) :
def test_split_on_punc(self) :
<|fim_suffix|> assert tokenize('foo bar') == ['foo', 'bar']
assert tokenize('foo bar') == ... | code_fim | medium | {
"lang": "python",
"repo": "ahlusar1989/probablepeople",
"path": "/tests/test_tokenizing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert tokenize('robert (bob) belcher') == ['robert', '(bob)', 'belcher']
assert tokenize('robert(bob) belcher') == ['robert', '(bob)', 'belcher']
assert tokenize('robert (bob)belcher') == ['robert', '(bob)', 'belcher']
if __name__ == '__main__' :
unittest.main()<|fim_prefix|... | code_fim | hard | {
"lang": "python",
"repo": "ahlusar1989/probablepeople",
"path": "/tests/test_tokenizing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert tokenize('mr & mrs') == ['mr', '&', 'mrs']
def test_paren(self) :
assert tokenize('robert (bob) belcher') == ['robert', '(bob)', 'belcher']
assert tokenize('robert(bob) belcher') == ['robert', '(bob)', 'belcher']
assert tokenize('robert (bob)belcher') == ['rober... | code_fim | hard | {
"lang": "python",
"repo": "ahlusar1989/probablepeople",
"path": "/tests/test_tokenizing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
print(f"{WARNING}WARNING - file 'metric_explanation.txt' not found.{NORMAL}")
return prs
def pptx_ui_errors(slide, message: str):
"""PPTX UI Errors
Log errors as they occur, print on slide itself
Arguments:
slide {pptx-slide} -- pptx-slide object, for logging... | code_fim | hard | {
"lang": "python",
"repo": "nga-27/SecuritiesAnalysisTools",
"path": "/libs/ui_generation/pptx_resources/slide_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nga-27/SecuritiesAnalysisTools path: /libs/ui_generation/pptx_resources/slide_utils.py
""" slide utilities """
import os
from datetime import datetime
from pptx.util import Inches, Pt
from pptx.dml.color import RGBColor
from pptx.enum.text import PP_ALIGN # pylint: disable=no-name-in-module
fr... | code_fim | hard | {
"lang": "python",
"repo": "nga-27/SecuritiesAnalysisTools",
"path": "/libs/ui_generation/pptx_resources/slide_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Pass the location data from fund_content_slides.json and generate an object """
# pylint: disable=too-few-public-methods
left: Inches
top: Inches
height: Inches
width: Inches
def __init__(self):
self.left = 0.0
self.top = 0.0
self.height = 0.0
... | code_fim | hard | {
"lang": "python",
"repo": "nga-27/SecuritiesAnalysisTools",
"path": "/libs/ui_generation/pptx_resources/slide_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> alpha: float = 2.0,
gamma: float = 4.0,
reduction: str = 'mean',
loss_weight: float = 1.0,
pos_weight: float = 1.0,
neg_weight: float = 1.0) -> None:
super().__init__()
self.alpha = alpha
... | code_fim | hard | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/mmdet/models/losses/gaussian_focal_loss.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> More details can be found in the `paper
<https://arxiv.org/abs/1808.01244>`_
Code is modified from `kp_utils.py
<https://github.com/princeton-vl/CornerNet/blob/master/models/py_utils/kp_utils.py#L152>`_ # noqa: E501
Please notice that the target in GaussianFocalLoss is a gaussian heat... | code_fim | hard | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/mmdet/models/losses/gaussian_focal_loss.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alldatacenter/alldata path: /ai/mmdetection/mmdet/models/losses/gaussian_focal_loss.py
# Copyright (c) OpenMMLab. All rights reserved.
from typing import Optional, Union
import torch.nn as nn
from torch import Tensor
from mmdet.registry import MODELS
from .utils import weight_reduce_loss, weigh... | code_fim | hard | {
"lang": "python",
"repo": "alldatacenter/alldata",
"path": "/ai/mmdetection/mmdet/models/losses/gaussian_focal_loss.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def loadAuth(self):
with open(self.AUTH_LOC, "r") as auth_file:
auth_string = json.load(auth_file)["token"]
return auth_string
def loadPackage(self):
with open(self.PACKAGE_LOC, "r") as package_file:
package = json.load(package_file)
return package
def loadGuilds(self):
try:
with... | code_fim | hard | {
"lang": "python",
"repo": "PikaBlue107/steve-content-warning",
"path": "/steveIO.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def loadGuilds(self):
try:
with open(self.GUILDS_LOC, "rb") as guilds_file: #will close guilds_file if json throws an error
guilds = pickle.load(guilds_file)
except FileNotFoundError: #catches FileNotFoundError so that we can create a fresh guilds file
print("No guilds file found. Creating ... | code_fim | medium | {
"lang": "python",
"repo": "PikaBlue107/steve-content-warning",
"path": "/steveIO.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PikaBlue107/steve-content-warning path: /steveIO.py
import json
import pickle
import sys
from history import History
class SteveIO:
AUTH_LOC_DEFAULT = "auth.json"
PACKAGE_LOC_DEFAULT = "package.json"
GUILDS_LOC_DEFAULT = "guilds.pickle"
def __init__(self, auth_loc=AUTH_LOC_DEFAULT, packa... | code_fim | hard | {
"lang": "python",
"repo": "PikaBlue107/steve-content-warning",
"path": "/steveIO.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pivoted_values_column_type = query.metadata_manager.retrieve_query_metadata_column_type_by_name(
step.value_column
)
query.metadata_manager.remove_query_metadata_columns(
query.metadata_manager.retrieve_query_metadata_columns_as_list(columns_filter=step.index)
)
query.m... | code_fim | hard | {
"lang": "python",
"repo": "davinov/weaverbird",
"path": "/server/weaverbird/backends/sql_translator/steps/pivot.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: davinov/weaverbird path: /server/weaverbird/backends/sql_translator/steps/pivot.py
from distutils import log
from weaverbird.backends.sql_translator.steps.utils.query_transformation import (
build_selection_query,
sanitize_column_name,
)
from weaverbird.backends.sql_translator.types impo... | code_fim | hard | {
"lang": "python",
"repo": "davinov/weaverbird",
"path": "/server/weaverbird/backends/sql_translator/steps/pivot.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rlfscin/bioinspirada path: /flappyBird/parent_selection.py
import setup as st
import recombination as rec
from random import randint
from copy import deepcopy
from individual import Individual
# =============================================================================
# =====================... | code_fim | hard | {
"lang": "python",
"repo": "rlfscin/bioinspirada",
"path": "/flappyBird/parent_selection.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rand1 = randint(0, len(population)-1)
rand2 = rand1
while rand2 == rand1:
rand2 = randint(0, len(population)-1)
return p1, p2
def global_uniform_selection(population):
objvar_lists = _choose_lists_from_pop(population, (lambda x: x.objvars))
sigma_lists = _choose_lists_fro... | code_fim | hard | {
"lang": "python",
"repo": "rlfscin/bioinspirada",
"path": "/flappyBird/parent_selection.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def approx_greater_equal_zero(value, rel_tol=0.0, abs_tol=1e-10):
return value >= 0 or math.isclose(value, 0, rel_tol=rel_tol, abs_tol=abs_tol)
def approx_eq(v1, v2, rel_tol=0.0, abs_tol=1e-10):
return math.isclose(v1, v2, rel_tol=rel_tol, abs_tol=abs_tol)
def assert_log(condition, message="", _... | code_fim | hard | {
"lang": "python",
"repo": "systems-explained/geb-simulations",
"path": "/models/system_model_v3/model/parts/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return value >= 0 or math.isclose(value, 0, rel_tol=rel_tol, abs_tol=abs_tol)
def approx_eq(v1, v2, rel_tol=0.0, abs_tol=1e-10):
return math.isclose(v1, v2, rel_tol=rel_tol, abs_tol=abs_tol)
def assert_log(condition, message="", _raise=True):
try:
assert condition, message
except... | code_fim | hard | {
"lang": "python",
"repo": "systems-explained/geb-simulations",
"path": "/models/system_model_v3/model/parts/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: systems-explained/geb-simulations path: /models/system_model_v3/model/parts/utils.py
from decimal import Decimal
import numpy as np
import pandas as pd
import math
import logging
import time
from functools import wraps
import models.system_model_v3.model.parts.failure_modes as failure
def apy_t... | code_fim | hard | {
"lang": "python",
"repo": "systems-explained/geb-simulations",
"path": "/models/system_model_v3/model/parts/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Raises
------
Exception
- given series is not a numpy array.
Returns
-------
Result : statsmodels.tsa.seasonal.DecomposeResult object
Object containing the decomposition results.
"""
assert isinstance(series, np.ndarray), "Series is no... | code_fim | hard | {
"lang": "python",
"repo": "AnaTomomi/tscfat",
"path": "/build/lib/Analysis/decompose_timeseries.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> fig1.tight_layout(pad=2)
return fig1
def STL_decomposition(series,
title,
test = False,
savepath = False,
savename = False,
ylabel = "Battery Level (%)",
... | code_fim | hard | {
"lang": "python",
"repo": "AnaTomomi/tscfat",
"path": "/build/lib/Analysis/decompose_timeseries.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AnaTomomi/tscfat path: /build/lib/Analysis/decompose_timeseries.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 1 14:40:46 2020
@author: arsi
Calculate STL decomposition for given time series and plot the components.
The decomposition is based on statsmodels ST... | code_fim | hard | {
"lang": "python",
"repo": "AnaTomomi/tscfat",
"path": "/build/lib/Analysis/decompose_timeseries.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fayazazam/acovrp path: /tsplibparser.py
#!python2
import math
import re
class TSPLIBParser(object):
@staticmethod
def d_euc2d(i, j):
xd = i[0] - j[0]
yd = i[1] - j[1]
return int(round(math.sqrt(xd*xd + yd*yd)))
KEYS_SPEC = ['NAME', 'TYPE', 'COMMENT', 'DIMENSION', 'CAPACI... | code_fim | hard | {
"lang": "python",
"repo": "fayazazam/acovrp",
"path": "/tsplibparser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open(self.filename, 'r') as file:
for line in file:
if any(value for key, value in sections.iteritems()):
if sections['node_coords']:
try:
counter += 1
m = re.match(r'\s*(\d+)\s+(\-?\d+(\.\d+)?)\s+(\-?\d+(\.\d+)?)(\s+(\-?\d+(\.\d+)?))?\s*\n', line)
if '... | code_fim | hard | {
"lang": "python",
"repo": "fayazazam/acovrp",
"path": "/tsplibparser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: soodraghav/Data-Structures path: /Data Structures/1_ArraysAndLists/2_LinkedListExercises/4_reverse_ll_same_LL.py
# Helper Code
#Return Same LinkedList
class Node:
def __init__(self, value):
self.value = value
self.next = None
class LinkedList:
def __init__(self):
... | code_fim | medium | {
"lang": "python",
"repo": "soodraghav/Data-Structures",
"path": "/Data Structures/1_ArraysAndLists/2_LinkedListExercises/4_reverse_ll_same_LL.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __repr__(self):
return str([v for v in self])
def reverse(linked_list):
"""
Reverse the inputted linked list
Args:
linked_list(obj): Linked List to be reversed
Returns:
obj: Reveresed Linked List
"""
prev = None
current_node = linked_list.h... | code_fim | hard | {
"lang": "python",
"repo": "soodraghav/Data-Structures",
"path": "/Data Structures/1_ArraysAndLists/2_LinkedListExercises/4_reverse_ll_same_LL.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> while current_node != None:
next = current_node.next
current_node.next = prev
prev = current_node
current_node = next
# print(prev.value)
linked_list.head = prev
return linked_list
# Tests
llist = LinkedList... | code_fim | hard | {
"lang": "python",
"repo": "soodraghav/Data-Structures",
"path": "/Data Structures/1_ArraysAndLists/2_LinkedListExercises/4_reverse_ll_same_LL.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liuyyy111/BCAN path: /data.py
from queue import Queue
from threading import Thread
import h5py
import nltk
import torch
import torch.utils.data as data
import os
import numpy as np
import json
from torch.utils.data import DataLoader
from prefetch_generator import BackgroundGenerator
... | code_fim | hard | {
"lang": "python",
"repo": "liuyyy111/BCAN",
"path": "/data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> images, captions, ids, img_ids = zip(*data)
# Merge images (convert tuple of 3D tensor to 4D tensor)
images = torch.stack(images, 0)
# Merget captions (convert tuple of 1D tensor to 2D tensor)
lengths = torch.LongTensor([len(cap) for cap in captions])
targets = torch.zeros... | code_fim | hard | {
"lang": "python",
"repo": "liuyyy111/BCAN",
"path": "/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if text==palindrom_text:
print("Palindrome")
else:
print("Not Palindrome")<|fim_prefix|># repo: Shobhits7/Programming-Basics path: /Python/palindrome.py
# First we take an input which is assigned to the variable "text"
# Then we use the python string slice method to reverse the string
# When both... | code_fim | medium | {
"lang": "python",
"repo": "Shobhits7/Programming-Basics",
"path": "/Python/palindrome.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Shobhits7/Programming-Basics path: /Python/palindrome.py
# First we take an input which is assigned to the variable "text"
# Then we use the python string slice method to reverse the string
# When both the strings are compared and an appropriate output is made
<|fim_suffix|>if text==palindrom_te... | code_fim | medium | {
"lang": "python",
"repo": "Shobhits7/Programming-Basics",
"path": "/Python/palindrome.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> bl = fake.create_blacklist(owner_reddit_name='AuthorName', blocked_reddit_name='MemberName')
blacklist_user.return_value = (bl, True)
app, reply, message, match = fake.create_all()
Blacklist(app).run(reply, message, match)
blacklist_user.assert_called_once_with('AuthorName', 'Member... | code_fim | hard | {
"lang": "python",
"repo": "c17r/TagTrain",
"path": "/tests/tagtrain/test_blacklist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: c17r/TagTrain path: /tests/tagtrain/test_blacklist.py
from unittest.mock import MagicMock, patch
from tagtrain import data
from . import fake
from tagtrain.tagtrain.tt_blacklist import Blacklist
@patch('tagtrain.data.by_owner.blacklist_user')
def test_unknown_group(blacklist_user):
blackli... | code_fim | hard | {
"lang": "python",
"repo": "c17r/TagTrain",
"path": "/tests/tagtrain/test_blacklist.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JeyDi/Mispelling path: /code/words_perturbation/perturbation.py
import os
import re
import math
import random
import sys
import json
import itertools
from random import randint
from string import ascii_letters
from os import path, listdir
from configparser import ConfigParser
pathname = o... | code_fim | hard | {
"lang": "python",
"repo": "JeyDi/Mispelling",
"path": "/code/words_perturbation/perturbation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> result_path = config["config"]["perturbed_tweets_folder"]
#result_path = "..\\..\\tweets\\perturbed" Only for test purposes
result_path = path.join(result_path,filename + ".txt")
with open(result_path, "w") as text_file:
for index, i in enumerate(result):
if index ... | code_fim | hard | {
"lang": "python",
"repo": "JeyDi/Mispelling",
"path": "/code/words_perturbation/perturbation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nat-n/copier path: /tests/test_migrations.py
import json
import platform
from pathlib import Path
from shutil import copytree
import pytest
import yaml
from plumbum import local
from plumbum.cmd import git
from copier import run_copy, run_update
from copier.errors import UserMessageError
from ... | code_fim | hard | {
"lang": "python",
"repo": "nat-n/copier",
"path": "/tests/test_migrations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Build template in v1
with local.cwd(src):
git("init")
build_file_tree(
{
"[[ _copier_conf.answers_file ]].jinja": "[[_copier_answers|to_nice_yaml]]",
"copier.yml": (
f"""\
_envops: {BRACKET_ENVOPS... | code_fim | hard | {
"lang": "python",
"repo": "nat-n/copier",
"path": "/tests/test_migrations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Plot data
plt.plot_date(formatted_dates, karma_totals,
marker="", linestyle="-",
lw=constants.width, color=constants.color)
# Configure settings
ax.grid(constants.show_grid)
plt.xticks()
locator = mpd.AutoDateLocator(interval_multiples=False)
... | code_fim | hard | {
"lang": "python",
"repo": "paramt/trackarma",
"path": "/src/generate_chart.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
if max(karma_totals) > 1000000:
karma_totals = [int(x) / 1000000 for x in karma_totals]
ylabel = "(millions)"
elif max(karma_totals) > 1000:
karma_totals = [int(x) / 1000 for x in karma_totals]
ylabel = "(thousands)"
except (Inde... | code_fim | medium | {
"lang": "python",
"repo": "paramt/trackarma",
"path": "/src/generate_chart.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paramt/trackarma path: /src/generate_chart.py
import datetime
import matplotlib.pyplot as plt
import matplotlib.dates as mpd
import src.constants as constants
def main():
plt.switch_backend('Agg')
plt.rcParams["figure.figsize"] = (10, 6)
# Open dates.txt
with open("data/dates.t... | code_fim | medium | {
"lang": "python",
"repo": "paramt/trackarma",
"path": "/src/generate_chart.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: saroad2/briefcase path: /tests/integrations/linuxdeploy/test_LinuxDeployBase__upgrade.py
import pytest
from briefcase.exceptions import MissingToolError, NetworkFailure
from briefcase.integrations.linuxdeploy import LinuxDeployBase
from tests.integrations.linuxdeploy.utils import side_effect_cre... | code_fim | hard | {
"lang": "python",
"repo": "saroad2/briefcase",
"path": "/tests/integrations/linuxdeploy/test_LinuxDeployBase__upgrade.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Mock a successful download
mock_tools.download.file.side_effect = side_effect_create_mock_appimage(
appimage_path
)
# Create a linuxdeploy wrapper, then upgrade it
linuxdeploy.upgrade()
# The mock file should exist as the upgraded version
assert appimage_path.exists... | code_fim | hard | {
"lang": "python",
"repo": "saroad2/briefcase",
"path": "/tests/integrations/linuxdeploy/test_LinuxDeployBase__upgrade.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>',name)
else:
print('Псевдоним введен не верно!')
input ('Нажмите Enter для выхода')<|fim_prefix|># repo: Gerashenko/pythontask path: /zadanie_3.py
# Геращенко Мария Yur`evich
# Variant 5
print('Герой нашей сегодняшней программы - Чарльз Лютвидж Доджсон.\nПод каким же именем мы знаем этого человек... | code_fim | medium | {
"lang": "python",
"repo": "Gerashenko/pythontask",
"path": "/zadanie_3.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Gerashenko/pythontask path: /zadanie_3.py
# Геращенко Мария Yur`evich
# Variant 5
print('Герой нашей сегодняшней программы -<|fim_suffix|>'Ваш ответ: ')
if name=='Льюис Кэрролл':
print ('Все верно: Чарльз Лютвидж Доджсон -',name)
else:
print('Псевдоним введен не верно!')
input ('Нажмите ... | code_fim | medium | {
"lang": "python",
"repo": "Gerashenko/pythontask",
"path": "/zadanie_3.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mpsonntag/snippets path: /python/odml/test_scripts/datacite_ns_collapse_test.py
import os
import odmltools.importers.import_datacite as dimp
<|fim_suffix|># test fail
dimp.handle_document(extra_file, out_dir)
# test ns escape
extra_nspace = ["http://datacite.org/schema/kernel-2"]
dimp.handle_d... | code_fim | hard | {
"lang": "python",
"repo": "mpsonntag/snippets",
"path": "/python/odml/test_scripts/datacite_ns_collapse_test.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># test fail
dimp.handle_document(extra_file, out_dir)
# test ns escape
extra_nspace = ["http://datacite.org/schema/kernel-2"]
dimp.handle_document(extra_file, out_dir, extra_ns=extra_nspace)<|fim_prefix|># repo: mpsonntag/snippets path: /python/odml/test_scripts/datacite_ns_collapse_test.py
import os
i... | code_fim | hard | {
"lang": "python",
"repo": "mpsonntag/snippets",
"path": "/python/odml/test_scripts/datacite_ns_collapse_test.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MRYLH/MASS-Multi-task-Anthropomorphic-Speech-Synthesis-Framework path: /code/WaveRNN-master/extract_sp+f0/process_sp+f0.py
import librosa
import numpy as np
import os, sys
os.environ["CUDA_VISIBLE_DEVICES"] = "3"
import argparse
# import pyworld
from multiprocessing import cpu_count
from concurr... | code_fim | hard | {
"lang": "python",
"repo": "MRYLH/MASS-Multi-task-Anthropomorphic-Speech-Synthesis-Framework",
"path": "/code/WaveRNN-master/extract_sp+f0/process_sp+f0.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def split_data(paths):
indices = np.arange(len(paths))
test_size = 0.005
train_indices, test_indices = train_test_split(indices, test_size=test_size, random_state=1234)
train_paths = list(np.array(paths)[train_indices])
test_paths = list(np.array(paths)[test_indices])
return train... | code_fim | hard | {
"lang": "python",
"repo": "MRYLH/MASS-Multi-task-Anthropomorphic-Speech-Synthesis-Framework",
"path": "/code/WaveRNN-master/extract_sp+f0/process_sp+f0.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: huseyinozdemir/pythontr_api path: /recipe/serializers/serializer_message.py
from rest_framework import serializers
from core.models import Message
class MessageSerializer(serializers.ModelSerializer):
<|fim_suffix|> model = Message
fields = ('id', 'create_at', 'sender', 'user',... | code_fim | easy | {
"lang": "python",
"repo": "huseyinozdemir/pythontr_api",
"path": "/recipe/serializers/serializer_message.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Meta:
model = Message
fields = ('id', 'create_at', 'sender', 'user', 'subject', 'content',
'ip', 'is_read', 'is_delete',)
read_only_fields = ('id',)<|fim_prefix|># repo: huseyinozdemir/pythontr_api path: /recipe/serializers/serializer_message.py
from r... | code_fim | easy | {
"lang": "python",
"repo": "huseyinozdemir/pythontr_api",
"path": "/recipe/serializers/serializer_message.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>uction! It will wipe the database.")
else:
unittest.main()<|fim_prefix|># repo: SuperTux88/MediaCrush path: /tests.py
from mediacrush.tests import *
from mediacrush.config import config
import unittest
if __name__ == '__main__':
if config.get('meta', <|fim_middle|>'environment') != 'dev'... | code_fim | medium | {
"lang": "python",
"repo": "SuperTux88/MediaCrush",
"path": "/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SuperTux88/MediaCrush path: /tests.py
from mediacrush.tests import *
from mediacrush.config import config
import unittest
if __name__ == '__main__':
if config.get('meta', <|fim_suffix|>uction! It will wipe the database.")
else:
unittest.main()<|fim_middle|>'environment') != 'dev'... | code_fim | medium | {
"lang": "python",
"repo": "SuperTux88/MediaCrush",
"path": "/tests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>'environment') != 'dev':
print("Do NOT run unit tests in production! It will wipe the database.")
else:
unittest.main()<|fim_prefix|># repo: SuperTux88/MediaCrush path: /tests.py
from mediacrush.tests import *
from mediacrush.config import config
i<|fim_middle|>mport unittest
if __na... | code_fim | medium | {
"lang": "python",
"repo": "SuperTux88/MediaCrush",
"path": "/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='sharekitmetadataharvest',
name='is_extracted',
field=models.BooleanField(default=False),
),
]<|fim_prefix|># repo: surfedushare/search-portal path: /harvester/sharekit/migrations/0003_is_extracted.... | code_fim | medium | {
"lang": "python",
"repo": "surfedushare/search-portal",
"path": "/harvester/sharekit/migrations/0003_is_extracted.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: surfedushare/search-portal path: /harvester/sharekit/migrations/0003_is_extracted.py
# Generated by Django 3.2.12 on 2022-04-19 11:37
from django.db import migrations, models
<|fim_suffix|> operations = [
migrations.AddField(
model_name='sharekitmetadataharvest',
... | code_fim | medium | {
"lang": "python",
"repo": "surfedushare/search-portal",
"path": "/harvester/sharekit/migrations/0003_is_extracted.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MattesR/search path: /hoover/site/wsgi.py
import os
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "hoover.site.settings")
from django.core.wsgi import get_wsgi_application
<|fim_suffix|>from whitenoise.django import DjangoWhiteNoise
application = DjangoWhiteNoise(application)
from . import e... | code_fim | easy | {
"lang": "python",
"repo": "MattesR/search",
"path": "/hoover/site/wsgi.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from whitenoise.django import DjangoWhiteNoise
application = DjangoWhiteNoise(application)
from . import events<|fim_prefix|># repo: MattesR/search path: /hoover/site/wsgi.py
import os
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "hoover.site.settings")
<|fim_middle|>from django.core.wsgi import get... | code_fim | medium | {
"lang": "python",
"repo": "MattesR/search",
"path": "/hoover/site/wsgi.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> tag = datacatalog.Tag()
prepare.BaseTagFactory._set_bool_field(tag, 'bool', None)
self.assertNotIn('bool', tag.fields)
def test_set_bool_field_should_set_given_value(self):
tag = datacatalog.Tag()
prepare.BaseTagFactory._set_bool_field(tag, 'bool', False)
... | code_fim | hard | {
"lang": "python",
"repo": "codingnuub/datacatalog-connectors",
"path": "/google-datacatalog-connectors-commons/tests/google/datacatalog_connectors/commons/prepare/base_tag_factory_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(1996, len(tag.fields['string'].string_value))
self.assertEqual(u'{}{}...'.format('a' * 1990, str_value),
tag.fields['string'].string_value)
self.assertEqual(
1999, len(tag.fields['string'].string_value.encode('UTF-8')))
def... | code_fim | hard | {
"lang": "python",
"repo": "codingnuub/datacatalog-connectors",
"path": "/google-datacatalog-connectors-commons/tests/google/datacatalog_connectors/commons/prepare/base_tag_factory_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: codingnuub/datacatalog-connectors path: /google-datacatalog-connectors-commons/tests/google/datacatalog_connectors/commons/prepare/base_tag_factory_test.py
#!/usr/bin/python
# coding=utf-8
#
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may ... | code_fim | hard | {
"lang": "python",
"repo": "codingnuub/datacatalog-connectors",
"path": "/google-datacatalog-connectors-commons/tests/google/datacatalog_connectors/commons/prepare/base_tag_factory_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>## Using the database to store task state and results.
result_backend = 'db+sqlite:///results.db'
task_default_delivery_mode = "transient"
task_annotations = {'tasks.add': {'rate_limit': '10/s'}}<|fim_prefix|># repo: Patola/desafiocit path: /celeryconfig.py
## Broker settings.
broker_url = 'amqp://gues... | code_fim | medium | {
"lang": "python",
"repo": "Patola/desafiocit",
"path": "/celeryconfig.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Patola/desafiocit path: /celeryconfig.py
## Broker settings.
broker_url = 'amqp://guest:guest@127.0.0.1:5672//'
# serializer
celery_task_serializer = 'pickle'
#CELERY_TASK_SERIALIZER = 'pickle'
<|fim_suffix|>broker_heartbeat=0
## Using the database to store task state and results.
result_backe... | code_fim | medium | {
"lang": "python",
"repo": "Patola/desafiocit",
"path": "/celeryconfig.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Tests for get_website_user()."""
def test_get_website_user_returns_user(self):
"""Test if something is returned."""
user = get_website_user()
self.assertTrue(user)
def test_get_website_user_returns_same_user(self):
"""Test if the same user is returned over ... | code_fim | medium | {
"lang": "python",
"repo": "thecut/thecut-authorship",
"path": "/thecut/authorship/tests/test_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_get_website_user_returns_same_user(self):
"""Test if the same user is returned over multiple calls."""
user = get_website_user()
self.assertEqual(get_website_user(), user)<|fim_prefix|># repo: thecut/thecut-authorship path: /thecut/authorship/tests/test_utils.py
# -*-... | code_fim | medium | {
"lang": "python",
"repo": "thecut/thecut-authorship",
"path": "/thecut/authorship/tests/test_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thecut/thecut-authorship path: /thecut/authorship/tests/test_utils.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from ..utils import get_website_user
from django.test import TestCase
<|fim_suffix|> def test_get_website_user_returns_user(self):
""... | code_fim | medium | {
"lang": "python",
"repo": "thecut/thecut-authorship",
"path": "/thecut/authorship/tests/test_utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wcsjtu/tordj path: /tordj/global_settings.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
"""default settings. all attribute here can be overridden"""
DATABASES = {
'session': {
'ENGINE': 'redis',
'OPTIONS':{
'host': 'localhost',
'p... | code_fim | hard | {
"lang": "python",
"repo": "wcsjtu/tordj",
"path": "/tordj/global_settings.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>GRPC_SERVICES = {} # with format like this {'service module': {'env': 'environment module'}, }
# eg. {
# "tordj.grpcio.dbservice": {
# "context": "path to context dict", # if has not special context, just let empty
... | code_fim | medium | {
"lang": "python",
"repo": "wcsjtu/tordj",
"path": "/tordj/global_settings.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> new_rsvp = {
"meetupId": len(self.db) + 1,
"topic": topic,
"status": status
}
self.db.append(new_rsvp)
return new_rsvp<|fim_prefix|># repo: SolomonMacharia/Questioner path: /app/api/v1/models/rsvp_models.py
all_rsvps = []
class RsvpMo... | code_fim | medium | {
"lang": "python",
"repo": "SolomonMacharia/Questioner",
"path": "/app/api/v1/models/rsvp_models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SolomonMacharia/Questioner path: /app/api/v1/models/rsvp_models.py
all_rsvps = []
class RsvpModel:
<|fim_suffix|> self.db = all_rsvps
def create_rsvp(self, topic, status):
new_rsvp = {
"meetupId": len(self.db) + 1,
"topic": topic,
"status"... | code_fim | easy | {
"lang": "python",
"repo": "SolomonMacharia/Questioner",
"path": "/app/api/v1/models/rsvp_models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _read_one_field(iprot, ftype):
if ftype == TType.BOOL:
return iprot.readBool()
elif ftype == TType.BYTE:
return iprot.readByte()
elif ftype == TType.I08:
return iprot.readI08()
elif ftype == TType.I16:
return iprot.readI16()
elif ftype == TType.I32:
return iprot.readI32()... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/commons",
"path": "/src/python/twitter/thrift/util/generic_struct_parser.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarvex/commons path: /src/python/twitter/thrift/util/generic_struct_parser.py
# Copyright 2011 Twitter Inc. All rights reserved
__author__ = 'ugo' # Ugo Di Girolamo
import traceback
from thrift.Thrift import TType
def _type_name(ftype):
return TType._VALUES_TO_NAMES[ftype]
def read(iprot):... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/commons",
"path": "/src/python/twitter/thrift/util/generic_struct_parser.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: boconlonton/python-deep-dive path: /part-3/1-dictionaries/exercise-1.py
"""
Write a function that will create and return a dictionary from another dictionary but sorted by value
"""
<|fim_suffix|>d1 = {'a': 2, 'b': 1, 'c': 4}
d2 = dictionary_constructor1(d1)
print(d2)
d3 = dictionary_constructo... | code_fim | hard | {
"lang": "python",
"repo": "boconlonton/python-deep-dive",
"path": "/part-3/1-dictionaries/exercise-1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>d1 = {'a': 2, 'b': 1, 'c': 4}
d2 = dictionary_constructor1(d1)
print(d2)
d3 = dictionary_constructor2(d1)
print(d3)<|fim_prefix|># repo: boconlonton/python-deep-dive path: /part-3/1-dictionaries/exercise-1.py
"""
Write a function that will create and return a dictionary from another dictionary but sorted... | code_fim | medium | {
"lang": "python",
"repo": "boconlonton/python-deep-dive",
"path": "/part-3/1-dictionaries/exercise-1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
The plugin for L{twisted.lore.lmath} can be discovered by querying for
L{IProcessor} plugins.
"""
plugins = getPlugins(IProcessor)
lmath = [p for p in plugins if p.name == "mlore"]
self.assertEqual(len(lmath), 1, "Did not find math lore plu... | code_fim | medium | {
"lang": "python",
"repo": "baojunli/FastCAE",
"path": "/VTK/vtk_7.1.1_x64_Debug/lib/python2.7/site-packages/twisted/lore/test/test_lmath.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: baojunli/FastCAE path: /VTK/vtk_7.1.1_x64_Debug/lib/python2.7/site-packages/twisted/lore/test/test_lmath.py
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
"""
Tests for L{twisted.lore.lmath}.
"""
from xml.dom.minidom import Element, Text
from twisted.trial.uni... | code_fim | hard | {
"lang": "python",
"repo": "baojunli/FastCAE",
"path": "/VTK/vtk_7.1.1_x64_Debug/lib/python2.7/site-packages/twisted/lore/test/test_lmath.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> result = ''
for number, roman in symbols:
result += roman * (n // number) # 符號出現次數
n %= number # 剩餘位數
return result<|fim_prefix|># repo: RevansChen/online-judge path: /Codewars/4kyu/roman-numerals-encoder/Python/solutions2.py
# Python - 2.7.6
# 列出所有可能的進位值
... | code_fim | easy | {
"lang": "python",
"repo": "RevansChen/online-judge",
"path": "/Codewars/4kyu/roman-numerals-encoder/Python/solutions2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RevansChen/online-judge path: /Codewars/4kyu/roman-numerals-encoder/Python/solutions2.py
# Python - 2.7.6
# 列出所有可能的進位值
symbols = [
(1000, 'M'),
(900, 'CM'), (500, 'D'), (400, 'CD'), (100, 'C'),
(90, 'XC'), (50, 'L'), (40, 'XL'), (10, 'X'),
(9, 'IX'), (5, 'V'), (4, 'IV'), (1, '... | code_fim | easy | {
"lang": "python",
"repo": "RevansChen/online-judge",
"path": "/Codewars/4kyu/roman-numerals-encoder/Python/solutions2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_loss(output_dict, gt_labels, **kwargs):
return nn.CrossEntropyLoss()(output_dict['logits'], gt_labels.long()) + \
nn.CrossEntropyLoss()(output_dict['logit_b'], gt_labels.long())<|fim_prefix|># repo: clovaai/wsolevaluation path: /wsol/method/acol.py
"""
Original repository: https://... | code_fim | hard | {
"lang": "python",
"repo": "clovaai/wsolevaluation",
"path": "/wsol/method/acol.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: clovaai/wsolevaluation path: /wsol/method/acol.py
"""
Original repository: https://github.com/xiaomengyc/ACoL
"""
import torch
import torch.nn as nn
from .util import get_attention
__all__ = ['AcolBase']
class AcolBase(nn.Module):
def _acol_logits(self, feature, labels, drop_threshold):
... | code_fim | hard | {
"lang": "python",
"repo": "clovaai/wsolevaluation",
"path": "/wsol/method/acol.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_loss(output_dict, gt_labels, **kwargs):
return nn.CrossEntropyLoss()(output_dict['logits'], gt_labels.long()) + \
nn.CrossEntropyLoss()(output_dict['logit_b'], gt_labels.long())<|fim_prefix|># repo: clovaai/wsolevaluation path: /wsol/method/acol.py
"""
Original repository: https:/... | code_fim | hard | {
"lang": "python",
"repo": "clovaai/wsolevaluation",
"path": "/wsol/method/acol.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: strigazi/athena path: /Trigger/TriggerCommon/TriggerMenu/python/calibcosmicmon/generateBeamspotChainDefs.py
# Copyright (C) 2002-2019 CERN for the benefit of the ATLAS collaboration
##########################################################################################
#######################... | code_fim | medium | {
"lang": "python",
"repo": "strigazi/athena",
"path": "/Trigger/TriggerCommon/TriggerMenu/python/calibcosmicmon/generateBeamspotChainDefs.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(listOfChainDefs)>1:
theChainDef = mergeChainDefs(listOfChainDefs)
else:
theChainDef = listOfChainDefs[0]
return theChainDef<|fim_prefix|># repo: strigazi/athena path: /Trigger/TriggerCommon/TriggerMenu/python/calibcosmicmon/generateBeamspotChainDefs.py
# Copyright (C) ... | code_fim | hard | {
"lang": "python",
"repo": "strigazi/athena",
"path": "/Trigger/TriggerCommon/TriggerMenu/python/calibcosmicmon/generateBeamspotChainDefs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jonebeabout/nwhcc path: /scripts/update-commons.py
from bs4 import BeautifulSoup
with open('../public_html/commons/head.html','r') as f:
head_src = BeautifulSoup(f,'html.parser')
head = head_src.find('meta').prettify('utf-8')
with open('../public_html/commons/footer.html','r') as f:
footer... | code_fim | hard | {
"lang": "python",
"repo": "jonebeabout/nwhcc",
"path": "/scripts/update-commons.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open('../public_html/events.html', 'r+') as f:
events = BeautifulSoup(f,'html.parser')
events.head.string = head
events.footer.string = footer
t = events.find(id='fh5co-counter')
t.string = times
f.seek(0)
str = events.prettify('utf-8').replace('<','<')
str = str.replace('>','>'... | code_fim | hard | {
"lang": "python",
"repo": "jonebeabout/nwhcc",
"path": "/scripts/update-commons.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open('../public_html/beliefs.html', 'r+') as f:
beliefs = BeautifulSoup(f,'html.parser')
beliefs.head.string = head
beliefs.footer.string = footer
t = beliefs.find(id='fh5co-counter')
t.string = times
f.seek(0)
str = beliefs.prettify('utf-8').replace('<','<')
str = str.replace('>... | code_fim | hard | {
"lang": "python",
"repo": "jonebeabout/nwhcc",
"path": "/scripts/update-commons.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: densikat/PyRobotSim path: /Direction.py
class Direction:
directions = {
1: "NORTH",
2: "EAST",
3: "SOUTH",
4: "WEST"
}
def __init__(self):
pass
<|fim_suffix|> return Direction.directions[directionindex]
@staticmethod
def getdi... | code_fim | hard | {
"lang": "python",
"repo": "densikat/PyRobotSim",
"path": "/Direction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for index, direction in Direction.directions.items():
if direction == directionname:
return index<|fim_prefix|># repo: densikat/PyRobotSim path: /Direction.py
class Direction:
directions = {
1: "NORTH",
2: "EAST",
3: "SOUTH",
4: "WE... | code_fim | hard | {
"lang": "python",
"repo": "densikat/PyRobotSim",
"path": "/Direction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>summary = defaultdict(list)
for i,line in enumerate(gzip.open('mOTU.nr.padded.motu.linkage.map.gz', 'r')):
if i == 0:
continue
tokens = line.rstrip('\n').split('\t')
if tokens[0] in percog:
summary[tokens[10]].append(percog[tokens[0]])
write("\t")
write("\t".join(headers))
wr... | code_fim | hard | {
"lang": "python",
"repo": "montoias/ngless",
"path": "/Modules/motus.ngm/motus-summary.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: montoias/ngless path: /Modules/motus.ngm/motus-summary.py
from collections import defaultdict
import gzip
import sys
input_counts = sys.argv[1]
write = sys.stdout.write
# This could probably be done faster & simpler with a few numpy + pandas
# functions, but we prefer to not depend on those pa... | code_fim | hard | {
"lang": "python",
"repo": "montoias/ngless",
"path": "/Modules/motus.ngm/motus-summary.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
percog = {}
for i,line in enumerate(open(input_counts)):
tokens = line.rstrip().split('\t')
if i == 0:
headers = tokens[1:]
else:
counts = [float(v) for v in tokens[1:]]
percog[tokens[0]] = counts
summary = defaultdict(list)
for i,line in enumerate(gzip.open('mOTU.nr... | code_fim | hard | {
"lang": "python",
"repo": "montoias/ngless",
"path": "/Modules/motus.ngm/motus-summary.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>hash_functions = {
"md5": md5,
"sha1": sha1,
"sha224": sha224,
"sha256": sha256,
"sha384": sha384,
"sha512": sha512,
"blake2b": blake2b,
"blake2s": blake2s,
"sha3_224": sha3_224,
"sha3_256": sha3_256,
"sha3_384": sha3_384,
"sha3_512": sha3_512,
"adler32"... | code_fim | hard | {
"lang": "python",
"repo": "mlkra/various-algorithms",
"path": "/mincount/hashfunctions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mlkra/various-algorithms path: /mincount/hashfunctions.py
from typing import Callable
import hashlib
import zlib
def __common(n: int, h: Callable, digest_size: int, b=0) -> float:
assert b <= digest_size
if b == 0:
return int.from_bytes(h(n.to_bytes(8, "big")).digest(), 'big') /... | code_fim | hard | {
"lang": "python",
"repo": "mlkra/various-algorithms",
"path": "/mincount/hashfunctions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return __common(n, hashlib.sha3_512, 512, b)
def adler32(n: int, b=0) -> float:
if b == 0:
return zlib.adler32(n.to_bytes(8, "big")) / 2**32
else:
return (zlib.adler32(n.to_bytes(8, "big")) >> (32 - b)) / 2**b
def adler322(n: int) -> int:
return zlib.adler32(n.to_bytes(... | code_fim | hard | {
"lang": "python",
"repo": "mlkra/various-algorithms",
"path": "/mincount/hashfunctions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: unfoldingWord-dev/door43-acceptance-tests path: /app_code/cli/bible-test.py
from __future__ import unicode_literals, print_function
import argparse
import json
import urllib
import sys
from urllib2 import HTTPError
from bs4 import BeautifulSoup
from general_tools.print_utils import print_error, p... | code_fim | hard | {
"lang": "python",
"repo": "unfoldingWord-dev/door43-acceptance-tests",
"path": "/app_code/cli/bible-test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> args = parser.parse_args(sys.argv[1:])
test_errors = []
test_warnings = []
print_ok('STARTING: ', 'Acceptance test for {0}\n'.format(args.gitrepo))
with BibleTest(test_errors, test_warnings) as test:
success = test.run(args.gitrepo)
if test_errors:
print_notice('... | code_fim | hard | {
"lang": "python",
"repo": "unfoldingWord-dev/door43-acceptance-tests",
"path": "/app_code/cli/bible-test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: apache/spark path: /python/pyspark/pandas/tests/series/test_stat.py
h MultiIndex some of index is NaN.
pser.index = pd.MultiIndex.from_tuples(
[("x", "a"), None, ("y", "c"), ("x", "a"), ("y", "c"), ("x", "a")]
)
psser = ps.from_pandas(pser)
self.assert... | code_fim | hard | {
"lang": "python",
"repo": "apache/spark",
"path": "/python/pyspark/pandas/tests/series/test_stat.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
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