text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: data-exp-lab/analysis_schema path: /analysis_schema/Previous_Analysis_Schema/stream_frontend.py
import time
from typing import Any, Dict, List, Optional, Sequence, Set, Tuple, Union
from pydantic import BaseModel, Schema, create_model
from .data_objects import DataObject
from .dataset import Da... | code_fim | hard | {
"lang": "python",
"repo": "data-exp-lab/analysis_schema",
"path": "/analysis_schema/Previous_Analysis_Schema/stream_frontend.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # helper method
def _listContains(self, l, entry):
"""Helper method to determine if a list contains an entry"""
for i in range(0, len(l)):
if l[i] == entry:
return True
return False
class CharacterSelectionContext:
def GetCharacterI... | code_fim | hard | {
"lang": "python",
"repo": "radtek/MultiverseClientServer",
"path": "/MultiverseClient/Scripts/CharacterCreation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: radtek/MultiverseClientServer path: /MultiverseClient/Scripts/CharacterCreation.py
#
#
# The Multiverse Platform is made available under the MIT License.
#
# Copyright (c) 2012 The Multiverse Foundation
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of thi... | code_fim | hard | {
"lang": "python",
"repo": "radtek/MultiverseClientServer",
"path": "/MultiverseClient/Scripts/CharacterCreation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def GetCharacterAttribute(self, characterId, attr):
"""Fetch the value of the given attribute for the given characterId."""
for charEntry in ClientAPI.GetCharacterEntries():
if charEntry.CharacterId == characterId:
return charEntry[attr]
return None
... | code_fim | hard | {
"lang": "python",
"repo": "radtek/MultiverseClientServer",
"path": "/MultiverseClient/Scripts/CharacterCreation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if PYQT5:
from PyQt5.QtDesigner import *
elif PYQT6:
from PyQt6.QtDesigner import *
elif PYSIDE2:
raise QtBindingMissingModuleError(name='QtDesigner')
elif PYSIDE6:
from PySide6.QtDesigner import *<|fim_prefix|># repo: winpython/winpython path: /winpython/_vendor/qtpy/tests/QtDesigner.py
... | code_fim | medium | {
"lang": "python",
"repo": "winpython/winpython",
"path": "/winpython/_vendor/qtpy/tests/QtDesigner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: winpython/winpython path: /winpython/_vendor/qtpy/tests/QtDesigner.py
# -----------------------------------------------------------------------------
# Copyright © 2014-2015 Colin Duquesnoy
#
# Licensed under the terms of the MIT License
# (see LICENSE.txt for details)
# -------------------------... | code_fim | medium | {
"lang": "python",
"repo": "winpython/winpython",
"path": "/winpython/_vendor/qtpy/tests/QtDesigner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from . import (
PYQT5,
PYQT6,
PYSIDE2,
PYSIDE6,
QtBindingMissingModuleError,
)
if PYQT5:
from PyQt5.QtDesigner import *
elif PYQT6:
from PyQt6.QtDesigner import *
elif PYSIDE2:
raise QtBindingMissingModuleError(name='QtDesigner')
elif PYSIDE6:
from PySide6.QtDesigner i... | code_fim | medium | {
"lang": "python",
"repo": "winpython/winpython",
"path": "/winpython/_vendor/qtpy/tests/QtDesigner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ahuang11/xskillscore path: /xskillscore/tests/test_contingency.py
import numpy as np
import numpy.testing as npt
import pytest
import xarray as xr
from sklearn.metrics import confusion_matrix
from xskillscore import Contingency
DIMS = (["time"], ["lon"], ["lat"], "time", ["lon", "lat", "time"])... | code_fim | hard | {
"lang": "python",
"repo": "ahuang11/xskillscore",
"path": "/xskillscore/tests/test_contingency.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.parametrize(
"method, expected",
[
("hits", 2),
("misses", 2),
("false_alarms", 1),
("correct_negatives", 2),
("bias_score", 3 / 4),
("hit_rate", 1 / 2),
("false_alarm_ratio", 1 / 3),
("false_alarm_rate", 1 / 3),
... | code_fim | hard | {
"lang": "python",
"repo": "ahuang11/xskillscore",
"path": "/xskillscore/tests/test_contingency.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.fixture
def dichotomous_Contingency():
observations = xr.DataArray(
np.array(2 * [0] + 2 * [1] + 1 * [0] + 2 * [1]), coords=[("x", np.arange(7))]
)
forecasts = xr.DataArray(
np.array(2 * [0] + 2 * [0] + 1 * [1] + 2 * [1]), coords=[("x", np.arange(7))]
)
category... | code_fim | hard | {
"lang": "python",
"repo": "ahuang11/xskillscore",
"path": "/xskillscore/tests/test_contingency.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HelenaNascimento/spyder path: /spyder/plugins/variableexplorer/widgets/tests/test_texteditor.py
# -*- coding: utf-8 -*-
#
# Copyright © Spyder Project Contributors
# Licensed under the terms of the MIT License
#
"""
Tests for texteditor.py
"""
# Test library imports
import pytest
# Local impor... | code_fim | medium | {
"lang": "python",
"repo": "HelenaNascimento/spyder",
"path": "/spyder/plugins/variableexplorer/widgets/tests/test_texteditor.py",
"mode": "psm",
"license": "LGPL-3.0-or-later",
"source": "the-stack-v2"
} |
<|fim_suffix|> import string
dig_its = string.digits
translate_digits = string.maketrans(dig_its,len(dig_its)*' ')
editor = TextEditor(None)
assert not editor.setup_and_check(translate_digits)
if __name__ == "__main__":
pytest.main()<|fim_prefix|># repo: HelenaNascimento/spyder path: /spyder/p... | code_fim | hard | {
"lang": "python",
"repo": "HelenaNascimento/spyder",
"path": "/spyder/plugins/variableexplorer/widgets/tests/test_texteditor.py",
"mode": "spm",
"license": "LGPL-3.0-or-later",
"source": "the-stack-v2"
} |
<|fim_suffix|> tupnomin = input(f'Digite a {unit+1}° palavra: ').lower().strip()
tupnom += (tupnomin,)
print(tupnom)
for palavra in tupnom:
print(f'\nNa palavra {palavra.capitalize()} temos ->', end=' ')
for letra in palavra:
if letra in 'aeiou':
print(letra, end=' ')<|fim_prefix|># re... | code_fim | medium | {
"lang": "python",
"repo": "Roberto-Mota/CursoemVideo",
"path": "/exercicios/ex077.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Roberto-Mota/CursoemVideo path: /exercicios/ex077.py
# Desafio 077 -> C. um programa que tenha uma tupla com várias palavras (ñ usar acentos).
# Depois disso, você deve mostrar, para cada palavra, quais são as sua vogais
tupnom = ()
print(dir(tupnom))
print('-=-'*5, 'Encontro das V... | code_fim | medium | {
"lang": "python",
"repo": "Roberto-Mota/CursoemVideo",
"path": "/exercicios/ex077.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>\nNa palavra {palavra.capitalize()} temos ->', end=' ')
for letra in palavra:
if letra in 'aeiou':
print(letra, end=' ')<|fim_prefix|># repo: Roberto-Mota/CursoemVideo path: /exercicios/ex077.py
# Desafio 077 -> C. um programa que tenha uma tupla com várias palavras (ñ usar acento... | code_fim | hard | {
"lang": "python",
"repo": "Roberto-Mota/CursoemVideo",
"path": "/exercicios/ex077.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Enmming/gorden_cralwer path: /gorden_crawler/spiders/kipling.py
# -*- coding: utf-8 -*-
from scrapy.spiders import Spider
from scrapy.selector import Selector
from gorden_crawler.items import BaseItem, ImageItem, SkuItem, Color
from scrapy import Request
from scrapy_redis.spiders import RedisSp... | code_fim | hard | {
"lang": "python",
"repo": "Enmming/gorden_cralwer",
"path": "/gorden_crawler/spiders/kipling.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> item = response.meta['item']
sel = Selector(response)
colorIds = response.meta['colorIds']
colorUrls = response.meta['colorUrls']
image_color_dict = {}
for colorId in colorIds:
images=[]
single_color_imgages = re.findall("[^\.{]*\/zoo... | code_fim | hard | {
"lang": "python",
"repo": "Enmming/gorden_cralwer",
"path": "/gorden_crawler/spiders/kipling.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: filipagh/kiwi.code.task path: /flight_routes/exporter.py
import json
import operator
import sys
from flight_routes.json_models.flight_json_model import FlightJsonModel
from flight_routes.json_models.plan_json_model import PlanJsonModel
def to_json(list_of_flights, indexed_flights, origin, dest... | code_fim | medium | {
"lang": "python",
"repo": "filipagh/kiwi.code.task",
"path": "/flight_routes/exporter.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return json.dumps(plans, default=lambda o: o.__dict__, indent=4)
def __get_time_string(total_time_in_sec):
h = int(total_time_in_sec / 60 / 60)
m = int(total_time_in_sec / 60) - h * 60
s = int(total_time_in_sec) - h * 60 * 60 - m * 60
h = __pad_to_len_2(h)
m = __pad_to_len_2(m)
... | code_fim | hard | {
"lang": "python",
"repo": "filipagh/kiwi.code.task",
"path": "/flight_routes/exporter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> flights.append(flight_json)
max_bags = min(max_bags, int(flight.bags_allowed))
total_price += float(flight.base_price) + float(flight.bag_price) * bags
plan = PlanJsonModel(flights, max_bags, bags, destination, origin, total_price,
... | code_fim | hard | {
"lang": "python",
"repo": "filipagh/kiwi.code.task",
"path": "/flight_routes/exporter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data_file = os.path.abspath("../data/seq_class_dataset.tsv")
train, val, test = pid.split_data(data_file, datatype='sequence',
problem_type='classification', num_classes=3)
assert (len(train) == 210) and (len(val) == 45) and (len(test) == 45) and (len(train[0... | code_fim | hard | {
"lang": "python",
"repo": "idptools/parrot",
"path": "/build/lib/parrot/tests/test_parrot.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: idptools/parrot path: /build/lib/parrot/tests/test_parrot.py
"""
Unit and regression tests for the PARROT package. Note that these tests are by no means comprehensive.
For unexplained issues, please reach out on the GitHub page:
https://github.com/idptools/parrot/issues
"""
# Import package, tes... | code_fim | hard | {
"lang": "python",
"repo": "idptools/parrot",
"path": "/build/lib/parrot/tests/test_parrot.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: phrenault/kindle_weatherdisplay_with-regional-air-quality-data path: /Server/get_uba_airquality.py
#!/usr/bin/python3
def get_uba_airquality(state):
#############################################################################
# Skript zum Auslesen der UBA Luftqualitätsdaten ... | code_fim | hard | {
"lang": "python",
"repo": "phrenault/kindle_weatherdisplay_with-regional-air-quality-data",
"path": "/Server/get_uba_airquality.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
##############
# Libraries
import csv
import codecs
import io
import urllib.request
from datetime import datetime, time, timedelta
import pymysql
#import pprint
###########
# Variables
stations = ['1372','1129'] # Jackerath, Niederzier as example
minus2st = timedelta(hours=-2) # Data are u... | code_fim | hard | {
"lang": "python",
"repo": "phrenault/kindle_weatherdisplay_with-regional-air-quality-data",
"path": "/Server/get_uba_airquality.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> __slots__ = ('retry_after', 'is_global')
def __init__(self, response, message):
super().__init__(response, message)
self.retry_after = message['retry_after'] / 1000.0
self.is_global = message.get('global', False)
class InternalServerError(HTTPException):
"""Excepti... | code_fim | hard | {
"lang": "python",
"repo": "Yandawl/restcord.py",
"path": "/restcord/errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Yandawl/restcord.py path: /restcord/errors.py
# -*- coding: utf-8 -*-
"""
The MIT License (MIT)
Copyright (c) 2015-2020 Rapptz
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the "Software"),
to deal in the Softwa... | code_fim | hard | {
"lang": "python",
"repo": "Yandawl/restcord.py",
"path": "/restcord/errors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class BadRequest(HTTPException):
"""Exception that's thrown for when status code 400 occurs."""
pass
class Forbidden(HTTPException):
"""Exception that's thrown for when status code 403 occurs."""
pass
class NotFound(HTTPException):
"""Exception that's thrown for when status cod... | code_fim | hard | {
"lang": "python",
"repo": "Yandawl/restcord.py",
"path": "/restcord/errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: psorus/grapa path: /grapa/mergelayers.py
import os
from os.path import isfile
fold="layers/"
fold="layerfiles/"
exit()
imps=[]
clas=[]
<|fim_suffix|> for ii in i.keys():
if "import" in ii:continue
if len(ii)==0:continue
if ii[0]=="#":continue
f.write(ii+"\n")
for cl ... | code_fim | hard | {
"lang": "python",
"repo": "psorus/grapa",
"path": "/grapa/mergelayers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ac1=ac[:ac.find("\nclass ")]
ac2=ac[ac.find("\nclass "):]
imps.append(ac1)
clas.append(ac2)
i={}
for imp in imps:
for lin in imp.split("\n"):
if not lin in i.keys():i[lin]=1.0
for ii in i.keys():
if not "import" in ii:continue
if len(ii)==0:continue... | code_fim | hard | {
"lang": "python",
"repo": "psorus/grapa",
"path": "/grapa/mergelayers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: b1tg/masm_shc path: /demos/knock_test.py
import socket
import sys
import argparse
def main():
parser = argparse.ArgumentParser(description="Send to the Crackme")
parser.add_argument('--port', dest="port", default="1337", help="Port to conne<|fim_suffix|> print "[+] Response: " + ... | code_fim | hard | {
"lang": "python",
"repo": "b1tg/masm_shc",
"path": "/demos/knock_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> = args.buf
try:
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect(('127.0.0.1', my_port))
s.send(key)
result = s.recv(512)
if result is not None:
print "[+] Response: " + result
s.close()
except socket.error:
print ... | code_fim | hard | {
"lang": "python",
"repo": "b1tg/masm_shc",
"path": "/demos/knock_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OualidBenkarim/BrainStat path: /brainstat/tests/test_SLM.py
from sklearn.model_selection import ParameterGrid
import numpy as np
from brainstat.stats.terms import FixedEffect, MixedEffect
from brainstat.stats.SLM import SLM
from brainstat.context.utils import read_surface_gz
from nilearn.datasets... | code_fim | hard | {
"lang": "python",
"repo": "OualidBenkarim/BrainStat",
"path": "/brainstat/tests/test_SLM.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns
-------
ParameterGrid
All pairings of parameters to be run through the SLM class.
"""
model = [
FixedEffect(1)
+ FixedEffect(np.random.rand(samples, predictors), names=["y1", "y2", "y3"])
]
Y_idx = [1, 2, 3]
contrast = [np.random.rand(sample... | code_fim | hard | {
"lang": "python",
"repo": "OualidBenkarim/BrainStat",
"path": "/brainstat/tests/test_SLM.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>lit('\n')
except:
description = 'None'
rating = soup.find('span',{'itemprop':'ratingValue'}).text.strip()
try:
series = soup.find('a',{'class':'greyText'}).text.strip()
except:
series = 'N/A'
pages = soup.find("span", {"itemprop":"numberOfPages"}).text
... | code_fim | hard | {
"lang": "python",
"repo": "Immortal000/booksearch",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Immortal000/booksearch path: /main.py
from bs4 import BeautifulSoup
import requests
while True:
links =[]
search_query = input()
website = requests.get('https://www.goodreads.com/search?q='+search_query).text
soup = BeautifulSoup(website,'lxml')
for a in soup.find_all('... | code_fim | hard | {
"lang": "python",
"repo": "Immortal000/booksearch",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>/search?searchTerm='+book_title).text
soup = BeautifulSoup(website,'lxml')
b = soup.find('div',{'class':'price-wrap'}).text.strip().split()
book_price = b[0]
print(f"Book Title:{book_title}\nBook Series:{series}\nBook Author:{author[2:]}\nBook Rating:{rating}\nLength of the book:{pages... | code_fim | hard | {
"lang": "python",
"repo": "Immortal000/booksearch",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: deborrrrrah/Clustering path: /Metric.py
from sklearn.metrics import accuracy_score
from copy import deepcopy
import numpy as np
from itertools import repeat, permutations
NumberTypes = ['int32', 'int64', 'float32', 'float64']
ArrayTypes = (np.ndarray)
dummy_number = -1
def clustering_accuracy_s... | code_fim | hard | {
"lang": "python",
"repo": "deborrrrrah/Clustering",
"path": "/Metric.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> max_dict_result = dict(zip(cluster_true, repeat(None)))
max_accuracy = dummy_number
if (len(cluster_true) > len(cluster_pred)) :
permutations_list = [dict(zip(cluster_true, x)) for x in permutations(cluster_pred,len(cluster_pred))]
else :
permutations_list = [dict(zip(clust... | code_fim | medium | {
"lang": "python",
"repo": "deborrrrrah/Clustering",
"path": "/Metric.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LauraForde/FitKit-API path: /providers/couchProvider.py
import requests
import couchdb
ADMIN_USERNAME = 'admin'
ADMIN_PASSWORD = 'pass'
COUCHDB_URL = 'http://'+ADMIN_USERNAME+':'+ADMIN_PASSWORD+'@localhost:5984/'
#COUCHDB_URL = 'http://54.68.14.217:5984/'
couch = couchdb.Server(COUCHDB_URL)
<|f... | code_fim | hard | {
"lang": "python",
"repo": "LauraForde/FitKit-API",
"path": "/providers/couchProvider.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def read_user(self, user_id):
db = couch['login']
if(user_id in db):
user = db[user_id]
return user, 200
else:
return {"error": "User not found."}, 400<|fim_prefix|># repo: LauraForde/FitKit-API path: /providers/couchProvider.py
import reque... | code_fim | medium | {
"lang": "python",
"repo": "LauraForde/FitKit-API",
"path": "/providers/couchProvider.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> db = couch['login']
if(user_id in db):
user = db[user_id]
return user, 200
else:
return {"error": "User not found."}, 400<|fim_prefix|># repo: LauraForde/FitKit-API path: /providers/couchProvider.py
import requests
import couchdb
ADMIN_USERNAME ... | code_fim | hard | {
"lang": "python",
"repo": "LauraForde/FitKit-API",
"path": "/providers/couchProvider.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: victorwyee/lungbox path: /tests/test_training_data.py
# -*- coding: utf-8 -*-
"""
Unit Tests for high level training data generation.
Usage:
python -m unittest tests/test_training_data.py
"""
import sys
import unittest
import numpy as np
# os.chdir('/projects/lungbox')
# os.chdir('..') # ... | code_fim | hard | {
"lang": "python",
"repo": "victorwyee/lungbox",
"path": "/tests/test_training_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_load_mask(self):
dataset_train = self.exdata.get_dataset_train()
mask_00 = dataset_train.load_mask(0)
image_mask_00 = mask_00[0]
class_00 = mask_00[1]
self.assertEqual(image_mask_00.shape, (1024, 1024, 2))
np.testing.assert_array_equal(class_00,... | code_fim | hard | {
"lang": "python",
"repo": "victorwyee/lungbox",
"path": "/tests/test_training_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dataset_train = self.exdata.get_dataset_train()
# Order should be the retained (when comparing lists)
self.assertEqual(dataset_train.patient_ids[0], self.exdata.patient_id_train)
self.assertEqual(dataset_train.annotation_dict, self.exdata.annotation_dict)
self.asse... | code_fim | hard | {
"lang": "python",
"repo": "victorwyee/lungbox",
"path": "/tests/test_training_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
train_features: dictionary of feature tensors that can be used for training
metadata_features: dictionary of feature tensors that can be used as additional metadata
"""
train_features, metadata_features = define_feature_layer(
feature_co... | code_fim | hard | {
"lang": "python",
"repo": "yakkanti/ml4ir",
"path": "/python/ml4ir/base/model/scoring/interaction_model.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yakkanti/ml4ir path: /python/ml4ir/base/model/scoring/interaction_model.py
from tensorflow.keras import Input
import tensorflow as tf
from ml4ir.base.features.feature_config import FeatureConfig
from ml4ir.base.features.feature_layer import FeatureLayerMap
from ml4ir.base.features.feature_layer ... | code_fim | hard | {
"lang": "python",
"repo": "yakkanti/ml4ir",
"path": "/python/ml4ir/base/model/scoring/interaction_model.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self, train_features: Dict[str, tf.Tensor], metadata_features: Dict[str, tf.Tensor]
):
"""
Transform train_features and metadata_features after the
univariate feature_layer fns have been applied.
Args:
train_features: dictionary of feature tensors t... | code_fim | hard | {
"lang": "python",
"repo": "yakkanti/ml4ir",
"path": "/python/ml4ir/base/model/scoring/interaction_model.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bhinz/salt-formula-ceph path: /ceph/files/testinfra/test_health.py
import pytest
testinfra_hosts = ['salt://I@ceph:mon']
<|fim_suffix|> print(cmd.stdout)
assert 'HEALTH_OK' in cmd.stdout<|fim_middle|>@pytest.mark.parametrize('cmd', [
'ceph health',
'ceph status',
'ceph osd tr... | code_fim | hard | {
"lang": "python",
"repo": "bhinz/salt-formula-ceph",
"path": "/ceph/files/testinfra/test_health.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(cmd.stdout)
assert 'HEALTH_OK' in cmd.stdout<|fim_prefix|># repo: bhinz/salt-formula-ceph path: /ceph/files/testinfra/test_health.py
import pytest
testinfra_hosts = ['salt://I@ceph:mon']
@pytest.mark.parametrize('cmd', [
'ceph health',
'ceph status',
'ceph osd tree',
'ceph... | code_fim | medium | {
"lang": "python",
"repo": "bhinz/salt-formula-ceph",
"path": "/ceph/files/testinfra/test_health.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mnhan32/DIT path: /dit_flow/dit_widget/minsec_to_decimal.py
#! /usr/bin/python
import re
import csv
import rill
@rill.component
@rill.inport('INFILE')
@rill.inport('OUTFILE')
@rill.outport('OUTFILE_OUT')
def minsec_to_decimal(INFILE, OUTFILE, OUTFILE_OUT):
"""Convert lat/long coordinates f... | code_fim | hard | {
"lang": "python",
"repo": "mnhan32/DIT",
"path": "/dit_flow/dit_widget/minsec_to_decimal.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# data = io.pull(infile, str)
#
# out = []
# for coord in data:
# # Splits each coordinate pair into degrees, minutes, seconds, and
# # hemisphere marker.
# coord = ','.join(coord)
# coord = coord.upper()
# subs = re.split(r'\s*[\xb0"\',]\s*|.(?=[NESW])... | code_fim | hard | {
"lang": "python",
"repo": "mnhan32/DIT",
"path": "/dit_flow/dit_widget/minsec_to_decimal.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: urvashikhanna/DAMS path: /src/preprocess.py
# encoding=utf-8
import argparse
from others.logging import init_logger
from prepro import json_to_data as data_builder
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1'):
return True
elif v.lower() in ('no', 'false', 'f'... | code_fim | hard | {
"lang": "python",
"repo": "urvashikhanna/DAMS",
"path": "/src/preprocess.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # json_to_data args
parser.add_argument('-log_file', default='logs/json_to_data.log')
parser.add_argument("-bert_dir", default='bert/bert_base_uncased')
parser.add_argument('-min_src_ntokens_per_sent', default=2, type=int)
parser.add_argument('-max_src_ntokens_per_sent', default=50, ty... | code_fim | hard | {
"lang": "python",
"repo": "urvashikhanna/DAMS",
"path": "/src/preprocess.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ethanperez/Snakelet path: /digitalocean/__init__.py
from .account import Account
from .actions import Action
from .domain import Domain
from .record import Record
from .droplet import Droplet
from .image import Image
from .key import Key
from .region import Region
from .size import Size
<|fim_su... | code_fim | medium | {
"lang": "python",
"repo": "ethanperez/Snakelet",
"path": "/digitalocean/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.account = Account(token)
self.action = Action(token)
self.domain = Domain(token)
self.record = Record(token)
self.droplet = Droplet(token)
self.image = Image(token)
self.key = Key(token)
self.region = Region(token)
self.size = Size(token)<|fim_prefix|># repo: ethan... | code_fim | medium | {
"lang": "python",
"repo": "ethanperez/Snakelet",
"path": "/digitalocean/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if -1 < _r < row and -1 < _c < col and (_r, _c) not in visited:
visited.add((_r, _c))
if image[_r][_c] == cur_color:
image[_r][_c] = newColor
que.append((_r, _c))
return None
while que:
r, ... | code_fim | hard | {
"lang": "python",
"repo": "lih627/python-algorithm-templates",
"path": "/LeetCodeSolutions/LeetCode_0733.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while que:
r, c = que.pop()
helper(r + 1, c)
helper(r - 1, c)
helper(r, c + 1)
helper(r, c - 1)
return image<|fim_prefix|># repo: lih627/python-algorithm-templates path: /LeetCodeSolutions/LeetCode_0733.py
class Solution:
def... | code_fim | hard | {
"lang": "python",
"repo": "lih627/python-algorithm-templates",
"path": "/LeetCodeSolutions/LeetCode_0733.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lih627/python-algorithm-templates path: /LeetCodeSolutions/LeetCode_0733.py
class Solution:
def floodFill(self, image: List[List[int]], sr: int, sc: int, newColor: int) -> List[List[int]]:
<|fim_suffix|> if -1 < _r < row and -1 < _c < col and (_r, _c) not in visited:
... | code_fim | hard | {
"lang": "python",
"repo": "lih627/python-algorithm-templates",
"path": "/LeetCodeSolutions/LeetCode_0733.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: geoffreynyaga/ANGA-UTM path: /flight_plans/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.3 on 2018-01-11 08:07
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.gis.db.models.fields
from django.db import migration... | code_fim | hard | {
"lang": "python",
"repo": "geoffreynyaga/ANGA-UTM",
"path": "/flight_plans/migrations/0001_initial.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>Field(max_length=20)),
('location', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='flight_plans.MissionLocation')),
],
),
migrations.AddField(
model_name='preflight',
name='sitesurvey',
field=models.... | code_fim | hard | {
"lang": "python",
"repo": "geoffreynyaga/ANGA-UTM",
"path": "/flight_plans/migrations/0001_initial.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('objective', models.CharField(choices=[('TRAIN', 'Training'), ('MAPP', 'Mapping'), ('3DM', '3D Mapping'), ('DELV', 'Delivery'), ('INSP', 'Inspection')... | code_fim | hard | {
"lang": "python",
"repo": "geoffreynyaga/ANGA-UTM",
"path": "/flight_plans/migrations/0001_initial.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class MorphologyMeanCenterer(PointTranslater):
def __init__(self, morph, PtSrc=None):
PtSrc = SVVisitorFactory.Array3AllPoints() if PtSrc == None else PtSrc
offset = getMean(PtSrc(morph)) * -1.0
super(MorphologyMeanCenterer, self).__init__(offset)
class MorphologyPCARotato... | code_fim | hard | {
"lang": "python",
"repo": "unidesigner/morphforge",
"path": "/src/morphforge/morphology/ui/morphmaths.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class PointTranslater(object):
def __init__(self, offset):
self.offset = offset
def __call__(self, pt):
return pt + self.offset
class MorphologyMeanCenterer(PointTranslater):
def __init__(self, morph, PtSrc=None):
PtSrc = SVVisitorFactory.Array3AllPoints() if P... | code_fim | hard | {
"lang": "python",
"repo": "unidesigner/morphforge",
"path": "/src/morphforge/morphology/ui/morphmaths.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: unidesigner/morphforge path: /src/morphforge/morphology/ui/morphmaths.py
#-------------------------------------------------------------------------------
# Copyright (c) 2012 Michael Hull.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification,... | code_fim | hard | {
"lang": "python",
"repo": "unidesigner/morphforge",
"path": "/src/morphforge/morphology/ui/morphmaths.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ensembl/tark path: /tark/tark_web/tests/test_sequtils.py
"""
.. See the NOTICE file distributed with this work for additional information
regarding copyright ownership.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with th... | code_fim | medium | {
"lang": "python",
"repo": "Ensembl/tark",
"path": "/tark/tark_web/tests/test_sequtils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from django.test.testcases import TestCase
from tark_web.utils.sequtils import TarkSeqUtils
import os
class SeqUtilsTest(TestCase):
# ./manage.py test tark_web.tests.test_sequtils --settings=tark.settings.test
def test_format_fasta(self):
sequence = "GATTGCGCCACTGCACTCCAGCCTGGGCGTGCAGAT... | code_fim | hard | {
"lang": "python",
"repo": "Ensembl/tark",
"path": "/tark/tark_web/tests/test_sequtils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rmjarvis/TreeCorr path: /treecorr/kgcorrelation.py
rms,
# with or without modification, are permitted provided that the following
# conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions, and the disclaimer given in the accom... | code_fim | hard | {
"lang": "python",
"repo": "rmjarvis/TreeCorr",
"path": "/treecorr/kgcorrelation.py",
"mode": "psm",
"license": "BSD-2-Clause-Views",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._process_all_cross(cat1, cat2, metric, num_threads, comm, low_mem)
if finalize:
vark = calculateVarK(cat1, low_mem=low_mem)
varg = calculateVarG(cat2, low_mem=low_mem)
self.logger.info("vark = %f: sig_k = %f",vark,math.sqrt(vark))
self.... | code_fim | hard | {
"lang": "python",
"repo": "rmjarvis/TreeCorr",
"path": "/treecorr/kgcorrelation.py",
"mode": "spm",
"license": "BSD-2-Clause-Views",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Clear the data vectors
"""
self.xi.ravel()[:] = 0
self.xi_im.ravel()[:] = 0
self.meanr.ravel()[:] = 0
self.meanlogr.ravel()[:] = 0
self.weight.ravel()[:] = 0
self.npairs.ravel()[:] = 0
self._varxi = None
self._cov = None
... | code_fim | hard | {
"lang": "python",
"repo": "rmjarvis/TreeCorr",
"path": "/treecorr/kgcorrelation.py",
"mode": "spm",
"license": "BSD-2-Clause-Views",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cheunhong/dynamic-singer path: /target-bigquery/setup.py
#!/usr/bin/env python
from setuptools import setup
setup(
name = 'target-bigquery',
version = '1.6.0',
description = 'Singer.io target for writing data to Google BigQuery<|fim_suffix|>0',
'google-cloud-bigquery>=1.9.0'... | code_fim | hard | {
"lang": "python",
"repo": "cheunhong/dynamic-singer",
"path": "/target-bigquery/setup.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>0',
'google-cloud-bigquery>=1.9.0',
'oauth2client',
],
entry_points = """
[console_scripts]
target-bigquery=target_bigquery:main
""",
)<|fim_prefix|># repo: cheunhong/dynamic-singer path: /target-bigquery/setup.py
#!/usr/bin/env python
from setuptools im... | code_fim | hard | {
"lang": "python",
"repo": "cheunhong/dynamic-singer",
"path": "/target-bigquery/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class TestCase3(TestBincountOp):
# empty input
def init_test_case(self):
self.minlength = 0
self.np_input = np.array([], dtype=np.int64)
self.Out = np.bincount(self.np_input, minlength=self.minlength)
class TestCase4(TestBincountOp):
# with input(INT32)
def init_... | code_fim | hard | {
"lang": "python",
"repo": "PaddlePaddle/Paddle",
"path": "/test/legacy_test/test_bincount_op.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> paddle.disable_static()
paddle.seed(2022)
self.temp_dir = tempfile.TemporaryDirectory()
self.save_path = os.path.join(
self.temp_dir.name, 'tensor_minlength_bincount'
)
self.place = (
paddle.CUDAPlace(0)
if paddle.is_compi... | code_fim | hard | {
"lang": "python",
"repo": "PaddlePaddle/Paddle",
"path": "/test/legacy_test/test_bincount_op.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PaddlePaddle/Paddle path: /test/legacy_test/test_bincount_op.py
# Copyright (c) 2019 PaddlePaddle Authors. 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 L... | code_fim | hard | {
"lang": "python",
"repo": "PaddlePaddle/Paddle",
"path": "/test/legacy_test/test_bincount_op.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: VanessaVieiraVV/autocomplete path: /controle.py
from palavra import *
from lista import Lista
''' Você também deve implementar a classe Controle, que é responsável por fornecer as funcionalidades de carregarDados
e find para carregar o arquivo de consultas e ordená-las (OK), e encontrar a lista d... | code_fim | hard | {
"lang": "python",
"repo": "VanessaVieiraVV/autocomplete",
"path": "/controle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __firstIndexOf(self, prefixo):
inicio = 0
fim = self.numeroTermos-1 #numeroTermos eh uma variavel gerada em carregarDados(), com a primeira linha do arquivo.txt
pos = -1
while inicio <= fim:
meio = (inicio+fim)//2
if meio > -1:
... | code_fim | hard | {
"lang": "python",
"repo": "VanessaVieiraVV/autocomplete",
"path": "/controle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> lista_de_sugestoes = list() #lista simples onde serao guardadas TODAS as ocorrencias que tem o prefixo em ordem lexicografica
indice = self.__firstIndexOf(prefixo)
ultimoIndice = self.__lastIndexOf(prefixo)
if indice != None and ultimoIndice != None:
if indice >... | code_fim | hard | {
"lang": "python",
"repo": "VanessaVieiraVV/autocomplete",
"path": "/controle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MrDLontheway/spark path: /python/pyspark/sql/tests/connect/test_connect_function.py
#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
... | code_fim | hard | {
"lang": "python",
"repo": "MrDLontheway/spark",
"path": "/python/pyspark/sql/tests/connect/test_connect_function.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> cdf = self.connect.sql(query)
sdf = self.spark.sql(query)
for c in ["a", "b", "c"]:
self.assert_eq(
cdf.orderBy(CF.asc(c)).toPandas(),
sdf.orderBy(SF.asc(c)).toPandas(),
)
self.assert_eq(
cdf.order... | code_fim | hard | {
"lang": "python",
"repo": "MrDLontheway/spark",
"path": "/python/pyspark/sql/tests/connect/test_connect_function.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> _MUMMY.__init__(self)
self.name = "MUMMIES"
self.specie = 'nouns'
self.basic = "mummy"
self.jsondata = {}<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_mummies.py
from xai.brain.wordbase.nouns._mummy import _MUMMY
#calss header
class _MUMMIES(_MUMMY, ):
<|fim_middle|> de... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_mummies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_mummies.py
from xai.brain.wordbase.nouns._mummy import _MUMMY
<|fim_suffix|> _MUMMY.__init__(self)
self.name = "MUMMIES"
self.specie = 'nouns'
self.basic = "mummy"
self.jsondata = {}<|fim_middle|>#calss header
class _MUMMIES(_MUMMY, ):
de... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_mummies.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self,):
_MUMMY.__init__(self)
self.name = "MUMMIES"
self.specie = 'nouns'
self.basic = "mummy"
self.jsondata = {}<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_mummies.py
from xai.brain.wordbase.nouns._mummy import _MUMMY
<|fim_middle|>#calss header
class ... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_mummies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = Post
fields=('title', 'title_tag','body')
widgets ={
'title': forms.TextInput(attrs={'class': 'form-control','placeholder':'Title'}),
'title_tag': forms.TextInput(attrs={'class': 'form-control','placeholder':'Title Tag'}),
'body': forms.T... | code_fim | medium | {
"lang": "python",
"repo": "Sergiogd112/notesapp",
"path": "/noteapp/notify/forms.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Sergiogd112/notesapp path: /noteapp/notify/forms.py
from django import forms
from .models import Post
class PostForm(forms.ModelForm):
class Meta:
model = Post
fields=('title', 'title_tag','author','body')
widgets ={
'title': forms.TextInput(attrs={'clas... | code_fim | medium | {
"lang": "python",
"repo": "Sergiogd112/notesapp",
"path": "/noteapp/notify/forms.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not token:
logger.warning(f'skipping { self.target } in { self.name }, no token')
return
gauges = self.generate_gauges('stats', self.name, self.vrops_entity_name,
['vcenter', 'vccluster', 'datacenter'])
if not gauges... | code_fim | hard | {
"lang": "python",
"repo": "asotirov0/vrops-exporter",
"path": "/collectors/ClusterStatsCollector.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> token = self.get_target_tokens()
token = token.setdefault(self.target, None)
if not token:
logger.warning(f'skipping { self.target } in { self.name }, no token')
return
gauges = self.generate_gauges('stats', self.name, self.vrops_entity_name,
... | code_fim | hard | {
"lang": "python",
"repo": "asotirov0/vrops-exporter",
"path": "/collectors/ClusterStatsCollector.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asotirov0/vrops-exporter path: /collectors/ClusterStatsCollector.py
from BaseCollector import BaseCollector
from tools.Vrops import Vrops
import logging
logger = logging.getLogger('vrops-exporter')
class ClusterStatsCollector(BaseCollector):
def __init__(self):
super().__init__()
... | code_fim | hard | {
"lang": "python",
"repo": "asotirov0/vrops-exporter",
"path": "/collectors/ClusterStatsCollector.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pombredanne/pykit path: /pykit/adt/tests/test_linkedlist.py
# -*- coding: utf-8 -*-
from __future__ import print_function, division, absolute_import
import unittest
from pykit.adt import LinkableItem, LinkedList
class TestADT(unittest.TestCase):
def test_linkedlist(self):
<|fim_suffix|> ... | code_fim | medium | {
"lang": "python",
"repo": "pombredanne/pykit",
"path": "/pykit/adt/tests/test_linkedlist.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> l.insert_before(foo, items[2])
l.insert_after(bar, items[2])
l.insert_before(head, items[0])
l.append(five)
l.insert_after(tail, five)
l.remove(items[4])
expected = ["head", 0, 1, "foo", 2, "bar", 3, 5, "tail"]
self.assertEqual(list(l), list... | code_fim | hard | {
"lang": "python",
"repo": "pombredanne/pykit",
"path": "/pykit/adt/tests/test_linkedlist.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: osteotek/yamr path: /cfg.py
from configparser import ConfigParser
<|fim_suffix|> print(config_path)
config = ConfigParser()
config.read(config_path)
return dict(config.items("YAMR"))<|fim_middle|>def load(config_path):
| code_fim | easy | {
"lang": "python",
"repo": "osteotek/yamr",
"path": "/cfg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(config_path)
config = ConfigParser()
config.read(config_path)
return dict(config.items("YAMR"))<|fim_prefix|># repo: osteotek/yamr path: /cfg.py
from configparser import ConfigParser
<|fim_middle|>def load(config_path):
| code_fim | easy | {
"lang": "python",
"repo": "osteotek/yamr",
"path": "/cfg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> callback = util.make_save_policy_callback("data/")
policy.learn(total_timesteps, callback=callback)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--gin_config", default='configs/cartpole_data_collect.gin')
args = parser.parse_args()
... | code_fim | hard | {
"lang": "python",
"repo": "hyzcn/imitation",
"path": "/scripts/data_collect.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hyzcn/imitation path: /scripts/data_collect.py
import argparse
import gin.tf
import imitation.util as util
import stable_baselines
import tensorflow as tf
def make_PPO2(env_name):
"""
Hyperparameters and a vectorized environment for training a PPO2 expert.
"""
env = util.make_v... | code_fim | medium | {
"lang": "python",
"repo": "hyzcn/imitation",
"path": "/scripts/data_collect.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--gin_config", default='configs/cartpole_data_collect.gin')
args = parser.parse_args()
gin.parse_config_file(args.gin_config)
main()<|fim_prefix|># repo: hyzcn/imitation path: /scripts/da... | code_fim | medium | {
"lang": "python",
"repo": "hyzcn/imitation",
"path": "/scripts/data_collect.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> s = Solution()
assert [1, 2, 3, 1] == s.distributeCandies(7, 4)
assert [5, 2, 3] == s.distributeCandies(10, 3)<|fim_prefix|># repo: linshaoyong/leetcode path: /python/array/1103_distribute_candies_to_people.py
class Solution(object):
def distributeCandies(self, candies, num_people):
... | code_fim | hard | {
"lang": "python",
"repo": "linshaoyong/leetcode",
"path": "/python/array/1103_distribute_candies_to_people.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: linshaoyong/leetcode path: /python/array/1103_distribute_candies_to_people.py
class Solution(object):
def distributeCandies(self, candies, num_people):
"""
:type candies: int
:type num_people: int
:rtype: List[int]
"""
res = [0] * num_people
... | code_fim | hard | {
"lang": "python",
"repo": "linshaoyong/leetcode",
"path": "/python/array/1103_distribute_candies_to_people.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmicev/Python4ScientificComputing_Fundamentals path: /assignment4_Micev/assignment3_step2_Micev_new.py
def wall_calc(layers_in_series,layers_in_paralel,fraction):
Materials_library={"glassfiber_90mm":2.52,"stucco_25mm":0.037,"facebrick_100mm":0.075,"wood_25mm":0.22,
"woodstud_90mm":0.63,"wood... | code_fim | hard | {
"lang": "python",
"repo": "dmicev/Python4ScientificComputing_Fundamentals",
"path": "/assignment4_Micev/assignment3_step2_Micev_new.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> material.append(Materials_library[anyLayer])
resistances.append(anyLayer)
library=dict(zip(resistances,material))
return library, Rsum, Utot
series_materials=["wood_bevel","gypsum_13mm","fiberboard_13mm"]
paralel_materials=["glassfiber_90mm","woodstud_90mm"]
fraction=0.75
wall... | code_fim | hard | {
"lang": "python",
"repo": "dmicev/Python4ScientificComputing_Fundamentals",
"path": "/assignment4_Micev/assignment3_step2_Micev_new.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gregcaporaso/q2-types path: /q2_types/metadata/_format.py
# ----------------------------------------------------------------------------
# Copyright (c) 2016-2023, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, d... | code_fim | medium | {
"lang": "python",
"repo": "gregcaporaso/q2-types",
"path": "/q2_types/metadata/_format.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
plugin.register_formats(ImmutableMetadataFormat,
ImmutableMetadataDirectoryFormat)<|fim_prefix|># repo: gregcaporaso/q2-types path: /q2_types/metadata/_format.py
# ----------------------------------------------------------------------------
# Copyright (c) 2016-2023, QIIME 2 deve... | code_fim | hard | {
"lang": "python",
"repo": "gregcaporaso/q2-types",
"path": "/q2_types/metadata/_format.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
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