text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> r = requests.get(opts['url'], headers=opts['headers'],
params=opts['params'], timeout=30)
if r.status_code != 200:
logging.warning(opts['url'] + " returned status " + str(r.status_code))
return None
try:
jval = json.loads(r.text, parse_float=decimal.Decimal)
# jval = json.loads(r.text)
ex... | code_fim | medium | {
"lang": "python",
"repo": "CryptoGodfatherVA4/arbot",
"path": "/httputil.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: randName/50.008-Project path: /shop/views.py
from json import loads
from django.http import Http404
from django.shortcuts import render
from django.core.exceptions import PermissionDenied
from django.views.decorators.csrf import ensure_csrf_cookie
from common.db import sql, count, page
from com... | code_fim | hard | {
"lang": "python",
"repo": "randName/50.008-Project",
"path": "/shop/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == 'POST':
if not request.user.is_authenticated:
raise PermissionDenied(NOT_LOGGED_IN)
uid = request.user.id
s = """INSERT INTO feedback (user_id, item_id, score, review, made_on)
VALUES (%s, %s, %s, %s, NOW())"""
try:
... | code_fim | hard | {
"lang": "python",
"repo": "randName/50.008-Project",
"path": "/shop/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: netbox-community/netbox path: /netbox/utilities/tests/test_utils.py
from django.http import QueryDict
from django.test import TestCase
from utilities.utils import deepmerge, dict_to_filter_params, normalize_querydict
class DictToFilterParamsTest(TestCase):
"""
Validate the operation of... | code_fim | hard | {
"lang": "python",
"repo": "netbox-community/netbox",
"path": "/netbox/utilities/tests/test_utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Validate the behavior of the deepmerge() utility.
"""
def test_deepmerge(self):
dict1 = {
'active': True,
'foo': 123,
'fruits': {
'orange': 1,
'apple': 2,
'pear': 3,
},
... | code_fim | hard | {
"lang": "python",
"repo": "netbox-community/netbox",
"path": "/netbox/utilities/tests/test_utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if isinstance(add_config, configparser.ConfigParser):
add_config = config_to_dict(add_config)
base_config.read_dict(add_config)
return base_config
def reverse_data(data_config):
for section in data_config:
for option in data_config[section]:
value = parse(data_... | code_fim | hard | {
"lang": "python",
"repo": "THUNLP-MT/Mask-Align",
"path": "/thualign/utils/config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: THUNLP-MT/Mask-Align path: /thualign/utils/config.py
# coding=utf-8
# Copyright 2021-Present The THUAlign Authors
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import json
import configparser
import logging
def parse(valu... | code_fim | hard | {
"lang": "python",
"repo": "THUNLP-MT/Mask-Align",
"path": "/thualign/utils/config.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return json.dumps(self._params, sort_keys=True)
@classmethod
def read(cls, cfg, base=None, data=None, model=None, exp='DEFAULT'):
curdir = os.path.dirname(__file__)
if not os.path.exists(cfg):
cfg = os.path.join(curdir, \
'../configs/user/{}.con... | code_fim | hard | {
"lang": "python",
"repo": "THUNLP-MT/Mask-Align",
"path": "/thualign/utils/config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FedML-AI/FedML path: /python/fedml/data/reddit/data_loader.py
import os
import logging
import numpy as np
import torch
import torch.utils.data as data
import torchvision.transforms as transforms
from torch.nn.utils.rnn import pad_sequence
from .datasets import Reddit_dataset
from .divide_data ... | code_fim | hard | {
"lang": "python",
"repo": "FedML-AI/FedML",
"path": "/python/fedml/data/reddit/data_loader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> filter_client_idx = 0
num_clients = len(training_sets.partitions)
for client_idx in range(num_clients):
client_data = select_dataset(client_idx, training_sets,
batch_size=args.batch_size, args=args,
collat... | code_fim | hard | {
"lang": "python",
"repo": "FedML-AI/FedML",
"path": "/python/fedml/data/reddit/data_loader.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yennicks/kirby path: /tests/tests_api/test_api_context.py
import datetime
import multiprocessing
import os
import pytest
from kirby.api.context import ContextManager
from kirby.api.queue import Queue
def _load_config(q):
from kirby.api.context import ctx
assert ctx.HELLO == "WORLD"
... | code_fim | hard | {
"lang": "python",
"repo": "yennicks/kirby",
"path": "/tests/tests_api/test_api_context.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> offset = datetime.timedelta(seconds=5)
with kafka_topic_factory("kirby-test-integration"):
q = Queue("kirby-test-integration")
start = datetime.datetime.now()
q.append("too early", submitted=start - offset)
q.append("hello world", submitted=start + offset)
... | code_fim | hard | {
"lang": "python",
"repo": "yennicks/kirby",
"path": "/tests/tests_api/test_api_context.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.unit == 'tile':
df_idx = np.where((idx < self.df['n_tiles_end']) & (idx >= self.df['n_tiles_start']))[0][0]
elif self.unit == 'slide':
df_idx = idx
cancer = self.df.loc[df_idx, 'Type']
basename = self.df.loc[df_idx, 'basename']
... | code_fim | hard | {
"lang": "python",
"repo": "chsher/CAML",
"path": "/caml/datasets/tcga.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chsher/CAML path: /caml/datasets/tcga.py
import os
import sys
from os.path import dirname, realpath
sys.path.append(dirname(realpath(__file__)))
from caml.datasets import data_utils
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
import ... | code_fim | hard | {
"lang": "python",
"repo": "chsher/CAML",
"path": "/caml/datasets/tcga.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.apply_filter:
self.df = data_utils.filter_df(self.df, self.min_tiles, self.cancers, n_pts=self.n_pts, random_seed=self.random_seed)
idxs = np.arange(self.df.shape[0])
np.random.shuffle(idxs)
self.df = self.df.iloc[idxs, :]
self.df.reset_... | code_fim | hard | {
"lang": "python",
"repo": "chsher/CAML",
"path": "/caml/datasets/tcga.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>F-707-1-X-X-1", "npGsmRegistration"), ("DKSF-707-1-X-X-1", "npGsmStrength"))
if mibBuilder.loadTexts: npGsmTrap.setStatus('current')
npReboot = MibIdentifier((1, 3, 6, 1, 4, 1, 25728, 911))
npSoftReboot = MibScalar((1, 3, 6, 1, 4, 1, 25728, 911, 1), Integer32()).setMaxAccess("readwrite")
if mibBuilder.loa... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DKSF-707-1-X-X-1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/DKSF-707-1-X-X-1.py
#
# PySNMP MIB module DKSF-707-1-X-X-1 (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/DKSF-707-1-X-X-1
# Produced by pysmi-0.3.4 at Mon Apr 29 18:32:32 2019
# On host DAVWANG4-M-1475 pla... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DKSF-707-1-X-X-1.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>barX = []
for i in range(N+1):
count = sum([r == i for r in X_t])
barX.append(count)
plt.plot(barX)
plt.savefig('kmr0_frequency.png')
plt.show()
SD = mc_compute_stationary(P)
plt.hist(SD)
plt.savefig('kmr0_hist.png')
plt.show()<|fim_prefix|># repo: yohanashima/stochevolution path: /kmr.py
# -*- ... | code_fim | medium | {
"lang": "python",
"repo": "yohanashima/stochevolution",
"path": "/kmr.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yohanashima/stochevolution path: /kmr.py
# -*- coding: utf-8 -*-
from __future__ import division
import matplotlib.pyplot as plt
from random import randint
import numpy as np
from scipy.stats import binom
from discrete_rv import DiscreteRV
from mc_tools.py import mc_compute_stationary, mc_sampl... | code_fim | hard | {
"lang": "python",
"repo": "yohanashima/stochevolution",
"path": "/kmr.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def mk_matrix1(N, ep, p): #同時改訂
P = np.empty((N+1, N+1))
for i in range(N):
if i/N < p:
pro = ep/2
elif i/N == p:
pro = 1/2
else:
pro = 1-ep/2
P[i] = binom.pmf(range(N+1), N, pro)
return P
#変数
N = 15 #人数
T = 1000 #試行回数
ep = 0... | code_fim | hard | {
"lang": "python",
"repo": "yohanashima/stochevolution",
"path": "/kmr.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PavlidisLab/rnaseq-pipeline path: /rnaseq_pipeline/gemma.py
from getpass import getpass
import os
from os.path import join
import subprocess
import luigi
from luigi.contrib.external_program import ExternalProgramTask
import requests
from requests.auth import HTTPBasicAuth
from .config import rn... | code_fim | hard | {
"lang": "python",
"repo": "PavlidisLab/rnaseq-pipeline",
"path": "/rnaseq_pipeline/gemma.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def reference_id(self):
try:
return {'human': gemma_cfg.human_reference_id, 'mouse': gemma_cfg.mouse_reference_id, 'rat': gemma_cfg.rat_reference_id}[self.taxon]
except KeyError:
raise ValueError('Unsupported Gemma taxon {}.'.format(self.taxon))
... | code_fim | hard | {
"lang": "python",
"repo": "PavlidisLab/rnaseq-pipeline",
"path": "/rnaseq_pipeline/gemma.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> def datasets(self, experiment_id):
return self._query_api(join('datasets', experiment_id))
def samples(self, experiment_id):
return self._query_api(join('datasets', experiment_id, 'samples'))
def platforms(self, experiment_id):
return self._query_api(join('datasets', ... | code_fim | hard | {
"lang": "python",
"repo": "PavlidisLab/rnaseq-pipeline",
"path": "/rnaseq_pipeline/gemma.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#import the example submission file for its stucture
submit = pd.read_csv('C:/Users/Laurens/Documents/TeamGreaterThanBrains/Scripts/Ensembles/SubmissionFormat.csv',sep=',')
filename='128linearSubmission.csv'
#input for this has to be an array in the order of the testbusinesses in the submissionfile
#... | code_fim | hard | {
"lang": "python",
"repo": "LHagendoorn/TeamGreaterThanBrains",
"path": "/Project1/Scripts/Clustering (HBOW-EM)/MBKMtoPrediction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LHagendoorn/TeamGreaterThanBrains path: /Project1/Scripts/Clustering (HBOW-EM)/MBKMtoPrediction.py
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 11 16:03:55 2016
@author: Laurens
Takes a minibatch kmeans cluster and generates both the verification set prediction as well as the prediction for t... | code_fim | hard | {
"lang": "python",
"repo": "LHagendoorn/TeamGreaterThanBrains",
"path": "/Project1/Scripts/Clustering (HBOW-EM)/MBKMtoPrediction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
data = pd.read_csv('C:/Users/Laurens/Documents/uni/MLP/data/features/caffe_features_test.csv', header=None, sep=',', engine='c', dtype={c: np.float64 for c in np.ones(4096)})
photoToBiz = pd.read_csv('C:/Users/Laurens/Documents/uni/MLP/data/test_photo_to_biz.csv', sep=',')
testBizIds = photoToBiz.bu... | code_fim | hard | {
"lang": "python",
"repo": "LHagendoorn/TeamGreaterThanBrains",
"path": "/Project1/Scripts/Clustering (HBOW-EM)/MBKMtoPrediction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kevjeong/CSE450 path: /rply/lexer.py
from .errors import LexingError
from .token import SourcePosition, Token
class Lexer(object):
tokens = (
"WHATEVR",
"VISIBLE",
"KTHXBAI",
"GIMME",
"MKAY",
"HAS",
"HAI",
"ITZ",
"OF",
... | code_fim | hard | {
"lang": "python",
"repo": "kevjeong/CSE450",
"path": "/rply/lexer.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.lexer = lexer
self.s = s
self.idx = 0
self._lineno = 1
def __iter__(self):
return self
def _update_pos(self, match):
self.idx = match.end
self._lineno += self.s.count("\n", match.start, match.end)
last_nl = self.s.rfind("\n", ... | code_fim | hard | {
"lang": "python",
"repo": "kevjeong/CSE450",
"path": "/rply/lexer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> E501
from tf_keras_vis.activation_maximization.callbacks import \
GifGenerator2D # noqa: F401 E402
from tf_keras_vis.activation_maximization.callbacks import \
GifGenerator2D as GifGenerator # noqa: F401 E402
from tf_keras_vis.activation_maximization.callbacks import \
PrintLogger as Print ... | code_fim | medium | {
"lang": "python",
"repo": "ZNHU-Forks/tf-keras-vis",
"path": "/tf_keras_vis/utils/callbacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ZNHU-Forks/tf-keras-vis path: /tf_keras_vis/utils/callbacks.py
import warnings
warnings.warn(('`tf_keras_vis.utils.callbacks` module is deprecated. '
'Please use `tf_keras_vis.activation_maximization.callbacks<|fim_suffix|>t \
GifGenerator2D as GifGenerator # noqa: F401 E402
... | code_fim | hard | {
"lang": "python",
"repo": "ZNHU-Forks/tf-keras-vis",
"path": "/tf_keras_vis/utils/callbacks.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>t \
GifGenerator2D as GifGenerator # noqa: F401 E402
from tf_keras_vis.activation_maximization.callbacks import \
PrintLogger as Print # noqa: F401 E402<|fim_prefix|># repo: ZNHU-Forks/tf-keras-vis path: /tf_keras_vis/utils/callbacks.py
import warnings
warnings.warn(('`tf_keras_vis.utils.callb... | code_fim | medium | {
"lang": "python",
"repo": "ZNHU-Forks/tf-keras-vis",
"path": "/tf_keras_vis/utils/callbacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cipher_text += chr(pos)
else:
cipher_text += i
return cipher_text
s = "www.abc.xy"
k = 87
print(caesarCipher(s, k))<|fim_prefix|># repo: DiyorbekAzimqulov/ProblemSolving path: /ceaserCipher.py
# https://www.hackerrank.com/challenges/caesar-cipher-1/problem
def cae... | code_fim | hard | {
"lang": "python",
"repo": "DiyorbekAzimqulov/ProblemSolving",
"path": "/ceaserCipher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DiyorbekAzimqulov/ProblemSolving path: /ceaserCipher.py
# https://www.hackerrank.com/challenges/caesar-cipher-1/problem
def caesarCipher(s: str, k: int):
k %= 26
cipher_text = ''
for i in s:
if i.isalpha():
if i.isupper():
pos = ord(i) + k
... | code_fim | hard | {
"lang": "python",
"repo": "DiyorbekAzimqulov/ProblemSolving",
"path": "/ceaserCipher.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: polmes/hackcu path: /justcaptionthis/justcaptionthis/listener.py
import tweepy
import requests
from utils import ocr, tweetsplitter
class MentionListener(tweepy.StreamListener):
def __init__(self, api, deepai):
self.api = api
self.key = deepai['key']
def on_status(self, status, firstcall... | code_fim | hard | {
"lang": "python",
"repo": "polmes/hackcu",
"path": "/justcaptionthis/justcaptionthis/listener.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Add OCR text if detected
if text is not None:
cap = 'The image shows ' + cap + ' and it says ' + text
caption.append(cap)
if caption:
# Build tweet
if len(caption) == 1:
tweet = caption[0]
else:
tweet = ''
for i, c in enumerate(caption):
tweet +... | code_fim | hard | {
"lang": "python",
"repo": "polmes/hackcu",
"path": "/justcaptionthis/justcaptionthis/listener.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Tweet (reply) the response
if len(tweet) <= 280:
self.api.update_status(tweet, in_reply_to_status_id=self.id, auto_populate_reply_metadata=True)
else:
tweets = tweetsplitter(tweet)
prev = self.id
for t in tweets:
latest = self.api.update_status(t, in_reply_to_status... | code_fim | hard | {
"lang": "python",
"repo": "polmes/hackcu",
"path": "/justcaptionthis/justcaptionthis/listener.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
Hold a NumPy array
'''
a = np.arange(1,n)
f = np.frompyfunc(lambda s, x: ((s + x) if (x % 2 == 0) else s), 2, 1)
return f.reduce(a, initial=0, dtype=np.int)
if __name__ == "__main__":
n=1000001
print((1 + ((n - 1) // 2)) * ((n - 1) // 2))
print(hold_a_lis... | code_fim | hard | {
"lang": "python",
"repo": "zettsu-t/cPlusPlusFriend",
"path": "/scripts/stock_price/memory_profile_list.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zettsu-t/cPlusPlusFriend path: /scripts/stock_price/memory_profile_list.py
#!/usr/bin/python3
# coding: utf-8
'''
Compare memory footprints. Based on
https://twitter.com/uuyr112/status/1160375090090876930
'''
<|fim_suffix|>if __name__ == "__main__":
n=1000001
print((1 + ((n - ... | code_fim | hard | {
"lang": "python",
"repo": "zettsu-t/cPlusPlusFriend",
"path": "/scripts/stock_price/memory_profile_list.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@profile
def use_a_np_array(n):
'''
Hold a NumPy array
'''
a = np.arange(1,n)
f = np.frompyfunc(lambda s, x: ((s + x) if (x % 2 == 0) else s), 2, 1)
return f.reduce(a, initial=0, dtype=np.int)
if __name__ == "__main__":
n=1000001
print((1 + ((n - 1) // 2)) * ((n... | code_fim | hard | {
"lang": "python",
"repo": "zettsu-t/cPlusPlusFriend",
"path": "/scripts/stock_price/memory_profile_list.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: data61/landshark path: /landshark/dataprocess.py
"""Process training and query data."""
# Copyright 2019 CSIRO (Data61)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at... | code_fim | hard | {
"lang": "python",
"repo": "data61/landshark",
"path": "/landshark/dataprocess.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#
# Functions for reading hdf5 query data directy
#
def _islice_batched(it: Iterator[np.ndarray], n: int) -> Iterator[np.ndarray]:
"""Slice an iterator which comes in batches."""
while n > 0:
arr: np.ndarray = next(it)
k = arr.shape[0]
yield arr[:n, :]
n -= k
d... | code_fim | hard | {
"lang": "python",
"repo": "data61/landshark",
"path": "/landshark/dataprocess.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Read feature data from HDF5 file."""
def __init__(
self,
hdf5_file: str,
halfwidth: int = 0,
nworkers: int = 1,
batch_mb: float = 1000,
) -> None:
self.file = hdf5_file
self.meta = read_feature_metadata(hdf5_file)
self.meta.ha... | code_fim | hard | {
"lang": "python",
"repo": "data61/landshark",
"path": "/landshark/dataprocess.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if seq1 == seq2:
return True
else:
return False
def _inorderTraverse(self, node, seq, val):
# exit condition
if node is None:
seq.append(val)
return
# in-order traversing
self._inorderTraverse(node.left, ... | code_fim | medium | {
"lang": "python",
"repo": "solomonovum/algorithms",
"path": "/leetcode/872_Leaf-Similar Trees.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: solomonovum/algorithms path: /leetcode/872_Leaf-Similar Trees.py
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
<|fim_suffix|> # exit condition
if nod... | code_fim | hard | {
"lang": "python",
"repo": "solomonovum/algorithms",
"path": "/leetcode/872_Leaf-Similar Trees.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("測試資料 x：")
print(prediction['input_data_x'])
print("測試資料 y：")
print(prediction['input_data_y'])
print("預測結果：")
print(prediction['prediction'])
print("W 平均錯誤率（Ein）：")
print(best_model.calculate_avg_error(best_model.train_X, best_model.tr... | code_fim | hard | {
"lang": "python",
"repo": "gogobook/fuku-ml",
"path": "/test_fuku_ml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> svm_bc = svm.BinaryClassifier()
svm_bc.load_train_data(input_train_data_file)
svm_bc.set_feature_transform('legendre', 3)
svm_bc.load_test_data(input_test_data_file)
svm_bc.set_param(svm_kernel='primal_hard_margin')
svm_bc.init_W()
W = svm_bc.train()... | code_fim | hard | {
"lang": "python",
"repo": "gogobook/fuku-ml",
"path": "/test_fuku_ml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gogobook/fuku-ml path: /test_fuku_ml.py
0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0... | code_fim | hard | {
"lang": "python",
"repo": "gogobook/fuku-ml",
"path": "/test_fuku_ml.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GowthamBA/Voice-Assistant path: /testingVoice.py
recording = sr.Recognizer()
with sr.Microphone() as source:
recording.adjust_for_ambient_noise(source)
print("Please Say something:"<|fim_suffix|> recording.recognize_google(audio))
except Exception as e:
print(e)<|fim_middle|>)
au... | code_fim | medium | {
"lang": "python",
"repo": "GowthamBA/Voice-Assistant",
"path": "/testingVoice.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>)
audio = recording.listen(source)
try:
print("You said: \n" + recording.recognize_google(audio))
except Exception as e:
print(e)<|fim_prefix|># repo: GowthamBA/Voice-Assistant path: /testingVoice.py
recording = sr.Recognizer()
with sr.Microphone() as source:
recor<|fim_middle|>ding.adju... | code_fim | medium | {
"lang": "python",
"repo": "GowthamBA/Voice-Assistant",
"path": "/testingVoice.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> recording.recognize_google(audio))
except Exception as e:
print(e)<|fim_prefix|># repo: GowthamBA/Voice-Assistant path: /testingVoice.py
recording = sr.Recognizer()
with sr.Microphone() as source:
recor<|fim_middle|>ding.adjust_for_ambient_noise(source)
print("Please Say something:")
au... | code_fim | medium | {
"lang": "python",
"repo": "GowthamBA/Voice-Assistant",
"path": "/testingVoice.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jellyear/niy path: /examples/colorizing_photos/model_b/get_sample.py
import os, glob
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
IMG_WIDTH = 64
IMG_HEIGHT = 64
def get_train_sample(filepath):
with Image.open(filepath) as img_color:
img_gray = img_color.convert('... | code_fim | hard | {
"lang": "python",
"repo": "jellyear/niy",
"path": "/examples/colorizing_photos/model_b/get_sample.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>paths = []
paths += glob.glob('files/Train/group1/64/*.png')
paths += glob.glob('files/Train/group2/64/*.png')
paths += glob.glob('files/Train/group3/64/*.png')
paths += glob.glob('files/Train/group4/64/*.png')
paths += glob.glob('files/Train/group5/64/*.png')
paths += glob.glob('files/Train/group6/64/*.p... | code_fim | hard | {
"lang": "python",
"repo": "jellyear/niy",
"path": "/examples/colorizing_photos/model_b/get_sample.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tgsnopec/pysegyutils path: /pysegyutils/ops/negation.py
import segyio
from ..core import is_segy_valid, SegyFile
from ..core.file_copy_utils import fast_copy
def negate_file(input_file, output_file, iline=9, xline=21):
<|fim_suffix|> try:
fast_copy(input_file, output_file)
excep... | code_fim | hard | {
"lang": "python",
"repo": "tgsnopec/pysegyutils",
"path": "/pysegyutils/ops/negation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
fast_copy(input_file, output_file)
except OSError as o:
# TODO
raise o
output_segy_file = segyio.open(output_file, mode='r+', ignore_geometry=True,
strict=False, iline=iline, xline=xline)
for it in range(output_segy_file.tr... | code_fim | hard | {
"lang": "python",
"repo": "tgsnopec/pysegyutils",
"path": "/pysegyutils/ops/negation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for it in range(output_segy_file.tracecount):
output_segy_file.trace[it] *= -1
output_segy_file.close()<|fim_prefix|># repo: tgsnopec/pysegyutils path: /pysegyutils/ops/negation.py
import segyio
from ..core import is_segy_valid, SegyFile
from ..core.file_copy_utils import fast_copy... | code_fim | hard | {
"lang": "python",
"repo": "tgsnopec/pysegyutils",
"path": "/pysegyutils/ops/negation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))<|fim_prefix|># repo: schferbe/glucometerutils path: /test/__init__.py
# -*- coding: utf-8 -*-
#
# SPDX-License-Identifier: MIT
"""Add the top-level module to the PYTHONPATH."""
<|fim_middle|>import os
import sys
| code_fim | easy | {
"lang": "python",
"repo": "schferbe/glucometerutils",
"path": "/test/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: schferbe/glucometerutils path: /test/__init__.py
# -*- coding: utf-8 -*-
#
# SPDX-License-Identifier: MIT
"""Add the top-level module to the PYTHONPATH."""
<|fim_suffix|>sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))<|fim_middle|>import os
import sys
| code_fim | easy | {
"lang": "python",
"repo": "schferbe/glucometerutils",
"path": "/test/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Here we test the examples in the documentation automatically using
doctest. We set up an environment which is similar to what a
rule writer might see - a 'sshd_config' variable that has been
passed in as a parameter to the rule declaration. This saves doing
this setup in the ... | code_fim | hard | {
"lang": "python",
"repo": "eduardocerqueira/insights-core",
"path": "/docs/examples/parsers/tests/test_secure_shell.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eduardocerqueira/insights-core path: /docs/examples/parsers/tests/test_secure_shell.py
from insights.parsers.secure_shell import SshDConfig
from insights.parsers import secure_shell
from insights.tests import context_wrap
import doctest
SSHD_CONFIG_INPUT = """
# $OpenBSD: sshd_config,v 1.93 2... | code_fim | hard | {
"lang": "python",
"repo": "eduardocerqueira/insights-core",
"path": "/docs/examples/parsers/tests/test_secure_shell.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> uuid = models.UUIDField(default=uuid4, primary_key=True)
name = models.TextField(null=False)
type = models.TextField(null=False)
provider = models.ForeignKey("api.Provider", on_delete=models.CASCADE, null=True)
class SubsLastProcessed(models.Model):
"""A model for storing last proces... | code_fim | medium | {
"lang": "python",
"repo": "project-koku/koku",
"path": "/koku/reporting/provider/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: project-koku/koku path: /koku/reporting/provider/models.py
#
# Copyright 2023 Red Hat Inc.
# SPDX-License-Identifier: Apache-2.0
#
"""Models for provider management."""
from uuid import uuid4
from django.db import models
class TenantAPIProvider(models.Model):
<|fim_suffix|>class SubsLastProces... | code_fim | hard | {
"lang": "python",
"repo": "project-koku/koku",
"path": "/koku/reporting/provider/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> source_uuid = models.ForeignKey(
"reporting.TenantAPIProvider", on_delete=models.CASCADE, unique=False, null=False, db_column="source_uuid"
)
year = models.CharField(null=False, max_length=4)
month = models.CharField(null=False, max_length=2)
latest_processed_time = models.Date... | code_fim | hard | {
"lang": "python",
"repo": "project-koku/koku",
"path": "/koku/reporting/provider/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Return
------
str
Return the URI of destination.
"""
source = _normalize_uri(source)
dest = _normalize_uri(dest)
parsed_source = urlparse(source)
if dest and dest.endswith("/"):
dest = join(dest, basename(parsed_source.path))
parsed_dest = urlparse(dest)... | code_fim | hard | {
"lang": "python",
"repo": "adRise/rikai",
"path": "/python/rikai/io.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adRise/rikai path: /python/rikai/io.py
# Copyright 2020 Rikai Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | code_fim | hard | {
"lang": "python",
"repo": "adRise/rikai",
"path": "/python/rikai/io.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> attribute_filter = AttributeFilter.from_model(UserREST(), False)
attribute_filter.first_name = True
adapted_users = sqlalchemy.adapt_persistent_collection(users, UserREST, attribute_filter)
self.assertEqual(adapted_users[0].first_name, "James")
self.assertIsNone(ad... | code_fim | hard | {
"lang": "python",
"repo": "anomaly/prestans",
"path": "/tests/issues/test_issue84.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_correct_adaption_collection(self):
user = UserPersistent()
user.first_name = "James"
user.last_name = "Hetfield"
users = [user]
attribute_filter = AttributeFilter.from_model(UserREST(), False)
attribute_filter.first_name = True
adapt... | code_fim | hard | {
"lang": "python",
"repo": "anomaly/prestans",
"path": "/tests/issues/test_issue84.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anomaly/prestans path: /tests/issues/test_issue84.py
from prestans.ext.data import adapters
from prestans.ext.data.adapters import sqlalchemy
from prestans.parser.attribute_filter import AttributeFilter
from prestans import types
import unittest
class UserPersistent(object):
first_name = "... | code_fim | hard | {
"lang": "python",
"repo": "anomaly/prestans",
"path": "/tests/issues/test_issue84.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JosemyDuarte/aws_python_terraform_poc path: /downloader/downloader.py
import requests
def handler(event, context):
<|fim_suffix|> print("Downloading page from [{}] ...".format(path))
return requests.get(path).content<|fim_middle|> print("Starting request with event [{}] and context [{... | code_fim | medium | {
"lang": "python",
"repo": "JosemyDuarte/aws_python_terraform_poc",
"path": "/downloader/downloader.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Downloading page from [{}] ...".format(path))
return requests.get(path).content<|fim_prefix|># repo: JosemyDuarte/aws_python_terraform_poc path: /downloader/downloader.py
import requests
def handler(event, context):
<|fim_middle|> print("Starting request with event [{}] and context [{... | code_fim | medium | {
"lang": "python",
"repo": "JosemyDuarte/aws_python_terraform_poc",
"path": "/downloader/downloader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> app.conf.beat_schedule = {
'update-feeds-and-items': {
'task': 'rss_feed.feeds.tasks.periodic_update_feeds_and_items',
'schedule': crontab(minute='*/30'), # every 30 minutes
}
}<|fim_prefix|># repo: MahmoudFarid/rss_feed path: /config/celery_beat.py
from c... | code_fim | easy | {
"lang": "python",
"repo": "MahmoudFarid/rss_feed",
"path": "/config/celery_beat.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MahmoudFarid/rss_feed path: /config/celery_beat.py
from celery.schedules import crontab
<|fim_suffix|> app.conf.beat_schedule = {
'update-feeds-and-items': {
'task': 'rss_feed.feeds.tasks.periodic_update_feeds_and_items',
'schedule': crontab(minute='*/30'), # ... | code_fim | easy | {
"lang": "python",
"repo": "MahmoudFarid/rss_feed",
"path": "/config/celery_beat.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Write header
writer.writerow(HEURISTICS_CSV_HEADERS)
# Run experiments
for experiment in experiments:
try:
# Log
logger.info(
'Starting experiment timeout={} dataset={}'
.format(*experi... | code_fim | hard | {
"lang": "python",
"repo": "TheoryInPractice/practical-oct",
"path": "/experiments/heuristic/cplex.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheoryInPractice/practical-oct path: /experiments/heuristic/cplex.py
"""Run cplex experiments."""
# Imports
from experiments import (
logger,
SNAP_DATA_DIR,
SNAP_DATA_EXT,
PREPROCESSING_TIMEOUTS
)
from experiments.datasets import preprocessed
from experiments.heuristic import (
... | code_fim | hard | {
"lang": "python",
"repo": "TheoryInPractice/practical-oct",
"path": "/experiments/heuristic/cplex.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def display(self):
puts(bold + uline, "Issues in Repo:")
clear()
nl()
for issue in self.data:
SingleIssueDisplayObject(issue).display()
putln(black, '=' * CONSOLE_WIDTH)
nl()
class SingleLongIssueDisplayObject(DisplayObject):
de... | code_fim | hard | {
"lang": "python",
"repo": "elunico/guppy",
"path": "/issue_display.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def display(self):
SingleIssueDisplayObject(self.data).display()
puts(' ')
putln(uline + bold, 'Body:')
clear()
body = self.data['body']
LongTextDisplayObject(body, CONSOLE_WIDTH - 4, 4).display(magenta)
clear()
nl()
class SingleIssueD... | code_fim | hard | {
"lang": "python",
"repo": "elunico/guppy",
"path": "/issue_display.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: elunico/guppy path: /issue_display.py
from colors import *
import requests
from utils import *
from repo_display import *
from display import *
from caching import *
def fetch_issue(repo, issue, issues_url, caching=CACHING_ACTIVE):
"""
Retrieves an issue for a partiular repo either from... | code_fim | hard | {
"lang": "python",
"repo": "elunico/guppy",
"path": "/issue_display.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
with h5py.File(h5file, "r") as f:
data = f[vid_name]['data'][:]
length = data.shape[0]
start_idx = length//2 - 30//2
end_idx = length//2 + 30//2
cliped = data[start_idx:end_idx]
print(cliped.shape)
return cliped
name = "/home/butlely/PycharmPro... | code_fim | hard | {
"lang": "python",
"repo": "songys96/yolact",
"path": "/convertToNpy.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: songys96/yolact path: /convertToNpy.py
import os
import time
import h5py
import numpy as np
import cv2
def run():
src = '/home/butlely/Desktop/Dataset/aihub/source_7/20201024_cat-grooming-000052.mp4'
image_list = os.listdir(src)
image_list = sorted(image_list, key=lambda x: int(x.sp... | code_fim | hard | {
"lang": "python",
"repo": "songys96/yolact",
"path": "/convertToNpy.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Detect faces
face_ids = []
faces = face_client.face.detect_with_stream(image)
for face in faces:
face_ids.append(face.face_id)
# Identify faces
results = face_client.face.identify(face_ids, PERSON_GROUP_ID)
print('Identifying faces in {}'.format(os.path.basename(image.name)))
if not results:
pr... | code_fim | hard | {
"lang": "python",
"repo": "pjgpetecodes/mscognitive",
"path": "/pythonface/pyface-group.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pjgpetecodes/mscognitive path: /pythonface/pyface-group.py
from azure.cognitiveservices.vision.face import FaceClient
from msrest.authentication import CognitiveServicesCredentials
from azure.cognitiveservices.vision.face.models import TrainingStatusType, Person
import os
import uuid
import glob... | code_fim | hard | {
"lang": "python",
"repo": "pjgpetecodes/mscognitive",
"path": "/pythonface/pyface-group.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def deleteNode(self, data):
p = self.root
while p.ptr and p.ptr.data != data:
p = p.ptr
if p.ptr:
sleep(1)
print("Deleting {} from linked list...".format(data))
temp = p.ptr
p.ptr = p.ptr.ptr
temp = None
... | code_fim | hard | {
"lang": "python",
"repo": "AamirAnwar/PythonLab",
"path": "/linkedList.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def testLinkedList():
ll = LinkedList()
data = [random.randint(1, 1000) for x in range(10)]
for i in data:
ll.addNode(i)
for i in range(len(data)):
randIndex = random.randint(0, len(data) - 1)
ll.deleteNode(data[randIndex])
print(ll)<|fim_prefix|># repo: Aami... | code_fim | hard | {
"lang": "python",
"repo": "AamirAnwar/PythonLab",
"path": "/linkedList.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AamirAnwar/PythonLab path: /linkedList.py
'''Linked list data structure using lists'''
from time import sleep
# Linked list node structure
class Node:
def __init__(self, data, ptr):
self.ptr = ptr
self.data = data
class LinkedList:
def __init__(self):
self.root ... | code_fim | hard | {
"lang": "python",
"repo": "AamirAnwar/PythonLab",
"path": "/linkedList.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: collector-m/DI-store path: /di_store/storage/storage_server_pb2.py
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: storage_server.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf imp... | code_fim | hard | {
"lang": "python",
"repo": "collector-m/DI-store",
"path": "/di_store/storage/storage_server_pb2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>FetchResponse = _reflection.GeneratedProtocolMessageType('FetchResponse', (_message.Message,), {
'DESCRIPTOR' : _FETCHRESPONSE,
'__module__' : 'storage_server_pb2'
# @@protoc_insertion_point(class_scope:di_store.storage_server.FetchResponse)
})
_sym_db.RegisterMessage(FetchResponse)
GetRequest = ... | code_fim | hard | {
"lang": "python",
"repo": "collector-m/DI-store",
"path": "/di_store/storage/storage_server_pb2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>_GETRESPONSE = _descriptor.Descriptor(
name='GetResponse',
full_name='di_store.storage_server.GetResponse',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='not_found', full_name='di_store... | code_fim | hard | {
"lang": "python",
"repo": "collector-m/DI-store",
"path": "/di_store/storage/storage_server_pb2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> super(OrganizationPeriodicUsage, self).__init__(item, **kwargs)
self.unit_of_measure = item.get('unitOfMeasure', None)
self.metric = item.get('metric', None)
self.usage = item.get('usage', None)
self.usage_per_day = item.get('usagePerDay', None)
self.date_r... | code_fim | hard | {
"lang": "python",
"repo": "contentful/contentful-management.py",
"path": "/contentful_management/organization_periodic_usage.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: contentful/contentful-management.py path: /contentful_management/organization_periodic_usage.py
from .resource import Resource
"""
contentful_management.organization_periodic_usage
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This module implements the OrganizationPeriodicUsage class.
AP... | code_fim | hard | {
"lang": "python",
"repo": "contentful/contentful-management.py",
"path": "/contentful_management/organization_periodic_usage.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.format != 'html':
raise Exception('URL can only be obtained for an html report')
request = requests.get(str(self))
return '{0}{1}'.format(self.PRESTIFY_SERVICE_URL, request.headers['Location'])
def __str__(self):
return '{0}/reports/{1}?{2}'.format(
self.PRESTIFY_SERVICE_URL,
s... | code_fim | hard | {
"lang": "python",
"repo": "omarkhd/prestify-client-py",
"path": "/prestify/client.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: omarkhd/prestify-client-py path: /prestify/client.py
# -*- coding: utf-8 -*-
import base64
import json
try:
from urllib.parse import urlencode
except ImportError:
from urllib import urlencode
import requests
class Report(object):
PRESTIFY_SERVICE_URL = None
_VALID_FORMATS = ('pdf', 'rtf', ... | code_fim | medium | {
"lang": "python",
"repo": "omarkhd/prestify-client-py",
"path": "/prestify/client.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def collect_itsm_status(self, collect_config_id):
collect_config = CollectorConfig.objects.get(collector_config_id=collect_config_id)
ret = {
"collect_itsm_status": collect_config.itsm_ticket_status,
"collect_itsm_status_display": CollectItsmStatus.get_choice_la... | code_fim | hard | {
"lang": "python",
"repo": "jiazhizhong/bk-log",
"path": "/apps/log_databus/handlers/itsm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jiazhizhong/bk-log path: /apps/log_databus/handlers/itsm.py
# -*- coding: utf-8 -*-
"""
Tencent is pleased to support the open source community by making BK-LOG 蓝鲸日志平台 available.
Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
BK-LOG 蓝鲸日志平台 is licensed under the MIT L... | code_fim | hard | {
"lang": "python",
"repo": "jiazhizhong/bk-log",
"path": "/apps/log_databus/handlers/itsm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> collector_process = CollectorConfig.objects.get(itsm_ticket_sn=ticket_info.get("sn"))
ticket_detail_info = self.ticket_info(ticket_info.get("sn"))
collector_process.set_can_use_es_cluster(self._get_can_use_es_cluster(ticket_detail_info))
if self._ticket_is_finish(ticket_inf... | code_fim | hard | {
"lang": "python",
"repo": "jiazhizhong/bk-log",
"path": "/apps/log_databus/handlers/itsm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_queryset(self, request):
return Declaration.objects.all_with_deleted()
admin.site.register(Report, ReportAdmin)
admin.site.register(Resolution, ResolutionAdmin)
admin.site.register(Declaration, DeclarationAdmin)<|fim_prefix|># repo: un-project/un-project.org path: /web/declarations/... | code_fim | medium | {
"lang": "python",
"repo": "un-project/un-project.org",
"path": "/web/declarations/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class DeclarationAdmin(admin.ModelAdmin):
list_display = ("text", "resolution", "is_deleted")
list_filter = ("is_deleted",)
def get_queryset(self, request):
return Declaration.objects.all_with_deleted()
admin.site.register(Report, ReportAdmin)
admin.site.register(Resolution, Resolu... | code_fim | hard | {
"lang": "python",
"repo": "un-project/un-project.org",
"path": "/web/declarations/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: un-project/un-project.org path: /web/declarations/admin.py
from django.contrib import admin
from django.db import models
from django.db.models import Count
from django.forms import Textarea
from declarations.models import Resolution, Declaration, Report
class ReportAdmin(admin.ModelAdmin):
... | code_fim | hard | {
"lang": "python",
"repo": "un-project/un-project.org",
"path": "/web/declarations/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Force sending of all messages
producer.flush()<|fim_prefix|># repo: drednout/site_checker path: /src/scripts/kafka_producer.py
from kafka import KafkaProducer
producer = KafkaProducer(
bootstrap_servers="kafka-aiven-site-checker-drednout-7f62.aivencloud.com:14798",
security_protocol="SSL",
... | code_fim | medium | {
"lang": "python",
"repo": "drednout/site_checker",
"path": "/src/scripts/kafka_producer.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: drednout/site_checker path: /src/scripts/kafka_producer.py
from kafka import KafkaProducer
producer = KafkaProducer(
bootstrap_servers="kafka-aiven-site-checker-drednout-7f62.aivencloud.com:14798",
security_protocol="SSL",
ssl_cafile="ca.pem",
ssl_certfile="service.cert",
ss... | code_fim | medium | {
"lang": "python",
"repo": "drednout/site_checker",
"path": "/src/scripts/kafka_producer.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
key = random.randint(0,10)
value = ''.join([random.choice(string.ascii_letters) for _ in range(10)])
if random.choice([0,1]):
await dhash.read(key)
else:
await dhash.write(key, value)
if __name__ == '__main__':
loop = asyncio.get_event_loop()
dhash = ASyncDHash()
tasks = [
... | code_fim | hard | {
"lang": "python",
"repo": "lightning-pro/dhash",
"path": "/asdhash.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lightning-pro/dhash path: /asdhash.py
import asyncio
import time
import random
import string
class ASyncDHash(object):
def __init__(self):
self.nodes = [ASyncNodes('#1'), ASyncNodes('#2')]
<|fim_suffix|>class ASyncNodes(object):
def __init__(self, name):
self.name = name
self.storage =... | code_fim | hard | {
"lang": "python",
"repo": "lightning-pro/dhash",
"path": "/asdhash.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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