text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>if __name__ == "__main__":
try:
suite = eval(sys.argv[1]) # Selected tests
except:
suite = None # All tests
nose.run(suite)<|fim_prefix|># repo: outbounder/amonone path: /runtests.py
import os
import sys
import nose
# Changes the enviroment in backends/mongodb
os.environ['AMON_TEST_ENV'] = "T... | code_fim | easy | {
"lang": "python",
"repo": "outbounder/amonone",
"path": "/runtests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: outbounder/amonone path: /runtests.py
import os
import sys
import nose
# Changes the enviroment in backends/mongodb
os.environ['AMON_TEST_ENV'] = "True"
<|fim_suffix|># Example usage
# python runtests -w amon/
if __name__ == "__main__":
try:
suite = eval(sys.argv[1]) # Selected tests
exce... | code_fim | medium | {
"lang": "python",
"repo": "outbounder/amonone",
"path": "/runtests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Example usage
# python runtests -w amon/
if __name__ == "__main__":
try:
suite = eval(sys.argv[1]) # Selected tests
except:
suite = None # All tests
nose.run(suite)<|fim_prefix|># repo: outbounder/amonone path: /runtests.py
import os
import sys
import nose
# Changes the enviroment in back... | code_fim | medium | {
"lang": "python",
"repo": "outbounder/amonone",
"path": "/runtests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mrcmac/CumulusCI path: /cumulusci/tasks/metadata/tests/test_modify.py
import os
import unittest
from glob import glob
from pathlib import Path
from tempfile import TemporaryDirectory
import lxml.etree as ET
from cumulusci.core.config import BaseGlobalConfig
from cumulusci.core.config import Bas... | code_fim | hard | {
"lang": "python",
"repo": "mrcmac/CumulusCI",
"path": "/cumulusci/tasks/metadata/tests/test_modify.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> files = glob(str(Path(__file__).parent / "/sample_package.xml"))
# If you fiddle with the salesforce encoder, the code below may be
# useful to ensure that it faithfully round-trips, but it only works
# if run in a directory with a parent-directory which contains a f... | code_fim | hard | {
"lang": "python",
"repo": "mrcmac/CumulusCI",
"path": "/cumulusci/tasks/metadata/tests/test_modify.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ideasincrypto/Etherisc-bima-bolt-api path: /src/process/business.py
from process.task import Task
class BusinessProcess(Task):
def __init__(self, id, log, *args, **kwargs):
self.log_handler = log
super().__init__(id, Task.TYPE_PROCESS, *args, **kwargs)
def b... | code_fim | medium | {
"lang": "python",
"repo": "ideasincrypto/Etherisc-bima-bolt-api",
"path": "/src/process/business.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def __init__(self, id, process, *args, **kwargs):
self.process = process
super().__init__(id, Task.TYPE_TASK, *args, **kwargs)
def start(self, blocking=True):
super().start(blocking)
def business_tx_log(self, message):
self.process.log_handler.lo... | code_fim | hard | {
"lang": "python",
"repo": "ideasincrypto/Etherisc-bima-bolt-api",
"path": "/src/process/business.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> conn = op.get_bind()
conn.execute(text("ALTER TABLE services ADD COLUMN ldap_enabled tinyint(1) default 1"))
conn.execute(text("UPDATE services SET ldap_enabled = 1"))
def downgrade():
pass<|fim_prefix|># repo: SURFscz/SBS path: /server/migrations/versions/5bde645fdb49_ldap_enabled_togg... | code_fim | medium | {
"lang": "python",
"repo": "SURFscz/SBS",
"path": "/server/migrations/versions/5bde645fdb49_ldap_enabled_toggle_for_services.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SURFscz/SBS path: /server/migrations/versions/5bde645fdb49_ldap_enabled_toggle_for_services.py
"""LDAP enabled toggle for services
Revision ID: 5bde645fdb49
Revises: aeb043834eb1
Create Date: 2023-03-24 13:49:10.543444
"""
from alembic import op
from sqlalchemy import text
<|fim_suffix|> co... | code_fim | medium | {
"lang": "python",
"repo": "SURFscz/SBS",
"path": "/server/migrations/versions/5bde645fdb49_ldap_enabled_toggle_for_services.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if feat_select=='tf' and nb_feat ==tf_feat:
qsub_train_plan(task_index)
time.sleep(0.5)
def train_missing_models():
Z=pickle.load(open('dodge_train_crf_plan.pickle'))
for task_index in Z:
model_src,feat_select,nb_feat,mid=Z[task_index]
model_name=g... | code_fim | hard | {
"lang": "python",
"repo": "Transkribus/TranskribusDU",
"path": "/TranskribusDU/tasks/make_exp.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def train_missing_models():
Z=pickle.load(open('dodge_train_crf_plan.pickle'))
for task_index in Z:
model_src,feat_select,nb_feat,mid=Z[task_index]
model_name=get_model_name(model_src,feat_select,nb_feat,mid=mid)
if mid !='crf':
model_file =os.path.join("./DODG... | code_fim | hard | {
"lang": "python",
"repo": "Transkribus/TranskribusDU",
"path": "/TranskribusDU/tasks/make_exp.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Transkribus/TranskribusDU path: /TranskribusDU/tasks/make_exp.py
from Dodge_Tasks import *
import pickle
def get_crf_jobid():
Z=pickle.load(open('dodge_train_crf_plan.pickle'))
L=[]
for task_index in Z:
model_src,feat_select,nb_feat,mid=Z[task_index]
if mid=='crf':
... | code_fim | hard | {
"lang": "python",
"repo": "Transkribus/TranskribusDU",
"path": "/TranskribusDU/tasks/make_exp.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def forward(self, *inputs, num_beams=0):
with torch.set_grad_enabled(self.training):
encoder_inputs, constraints, decoder_inputs = inputs # dims: [sl, bs] for encoder and decoder
# reset the states for the new batch
num_utterances, max_sl, bs = encoder_inpu... | code_fim | hard | {
"lang": "python",
"repo": "indeterminateoutcomesstudios/quick-nlp",
"path": "/src/quicknlp/models/hred_constrained.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dropoute = get_kwarg(kwargs, name="dropout_e", default_value=0.1) # encoder embedding dropout
dropoute = get_list(dropoute, 2)
dropouti = get_kwarg(kwargs, name="dropout_i", default_value=0.65) # input dropout
dropouti = get_list(dropouti, 2)
self.constraint_embed... | code_fim | hard | {
"lang": "python",
"repo": "indeterminateoutcomesstudios/quick-nlp",
"path": "/src/quicknlp/models/hred_constrained.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: indeterminateoutcomesstudios/quick-nlp path: /src/quicknlp/models/hred_constrained.py
from typing import List, Union
import torch
from quicknlp.modules import DropoutEmbeddings
from quicknlp.utils import get_kwarg, get_list
from .hred import HRED
HParam = Union[List[int], int]
class HREDCons... | code_fim | hard | {
"lang": "python",
"repo": "indeterminateoutcomesstudios/quick-nlp",
"path": "/src/quicknlp/models/hred_constrained.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yananzh/prokseq-v2.0 path: /scripts/libmod/errMsgFn.py
def fileErrMsg():
fileErrorMsg = """
File not created or found!
Please check if the file exists.
Please check the permission of the directory and give permission.
... | code_fim | hard | {
"lang": "python",
"repo": "yananzh/prokseq-v2.0",
"path": "/scripts/libmod/errMsgFn.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> samtools IS NOT FOUND!
Some features of the quality check will not be done.
Features such as, ... TO BE FILLED BY FIROJ
This will not hamper the overall pipeline.
User can also install the samtools and can specify the path
in the parameter file as
PATH SAMTOOLS path_to_sam_folder/sa... | code_fim | hard | {
"lang": "python",
"repo": "yananzh/prokseq-v2.0",
"path": "/scripts/libmod/errMsgFn.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(fastqcErrorMsg)
return 1
def DESeqErrMsg():
deseqErrorMsg = """
COMMON ERRORS:
Please chack library("DESeq2") and library("ggplot2") are installed.
"""
print(deseqErrorMsg)
return 1
def EdgeRErrMsg():
edgerErrorMsg = """
... | code_fim | hard | {
"lang": "python",
"repo": "yananzh/prokseq-v2.0",
"path": "/scripts/libmod/errMsgFn.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#NB: reduce imported symbols here a bit in a future release (possibly by
#wrapping the removed function and placing in obsolete.py);
from .exceptions import *
from .core import *
from .datasrc import *
from .constants import wl2ekin, ekin2wl, ekin2ksq, wl2k, wl2ksq, constant_boltzmann #TODO: only wl2ekin,... | code_fim | hard | {
"lang": "python",
"repo": "mctools/ncrystal",
"path": "/NCrystal/api.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mctools/ncrystal path: /NCrystal/api.py
"""
Meta-module providing the most commonly needed public API functions and classes
from NCrystal in a single module. It can be used as:
import NCrystal.api as NC
Which will for now do the same as "import NCrystal as NC". However, it might be
that we wil... | code_fim | hard | {
"lang": "python",
"repo": "mctools/ncrystal",
"path": "/NCrystal/api.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joshbelot/GettingStarted path: /tests/test_my_pkg.py
"""Tests the mathematical functions defined in my_pkg/trail.py
"""
import pytest
def test_square():
"""Tests the squaring function"""
from my_pkg.trial import square
assert 4 == square(2)
def test_factorial():
<|fim_suffix|... | code_fim | medium | {
"lang": "python",
"repo": "joshbelot/GettingStarted",
"path": "/tests/test_my_pkg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_factorial():
"""Tests the factorial function."""
from my_pkg.trial import factorial
assert 24 == factorial(4)
assert 6 == factorial(3.0)
assert 1 == factorial(0)
assert 1 == factorial(-1)
with pytest.raises(ValueError):
factorial(3.5)<|fim_prefix|># repo: jo... | code_fim | easy | {
"lang": "python",
"repo": "joshbelot/GettingStarted",
"path": "/tests/test_my_pkg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># headers = {
# 'service-api-key': service_api_key,
# 'nonce': nonce,
# 'timestamp': str(timestamp),
# 'Content-Type': 'application/json'
# }
# signature = get_signature('POST', path, nonce, timestamp, service_api_secret, body=request_body)
# headers['signa... | code_fim | hard | {
"lang": "python",
"repo": "qkrwnsgh1288/line-blockchain-api-caller",
"path": "/caller/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: qkrwnsgh1288/line-blockchain-api-caller path: /caller/utils.py
from network import get_signature
import os
import requests
import random
import string
import time
def get_transaction_info(
server_url: str,
service_api_key: str,
service_api_secret: str,
txHash: str
):
nonce ... | code_fim | hard | {
"lang": "python",
"repo": "qkrwnsgh1288/line-blockchain-api-caller",
"path": "/caller/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># request_body = {
# 'walletSecret': walletSecret,
# 'toAddress': toAddress,
# 'amount': amount
# }
# headers = {
# 'service-api-key': service_api_key,
# 'nonce': nonce,
# 'timestamp': str(timestamp),
# 'Content-Type': 'application/json'... | code_fim | hard | {
"lang": "python",
"repo": "qkrwnsgh1288/line-blockchain-api-caller",
"path": "/caller/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pwicks86/Weihnachtsmann path: /test_scripts/xmas_pixels.py
import board
import neopixel
import time
from math import floor
pixpin = board.D1
numpix = 60
strip = neopixel.NeoPixel(pixpin, numpix, brightness=0.3, auto_write=False)
<|fim_suffix|> while True:
for j in range(2):
... | code_fim | medium | {
"lang": "python",
"repo": "pwicks86/Weihnachtsmann",
"path": "/test_scripts/xmas_pixels.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def xmas_cycle():
while True:
for j in range(2):
for i in range(len(strip)):
dec = (floor(i / 2)) + j
print(dec)
if dec % 2 == 0:
strip[i] = (255,0,0)
else:
strip[i] = (0,255,0)
... | code_fim | medium | {
"lang": "python",
"repo": "pwicks86/Weihnachtsmann",
"path": "/test_scripts/xmas_pixels.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> mbs = mbs if mbs else size
case_generator = (lambda : get_valid_mnist())
cman = Caseman(cfunc=case_generator,vfrac=vfrac,tfrac=tfrac,cfrac=cfrac)
else:
data = load_data(path, cfrac)
size_in = len(data[0][0])
size_out = len(data[0][1])
layers =... | code_fim | hard | {
"lang": "python",
"repo": "MrWe/aiprog17",
"path": "/task3/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MrWe/aiprog17 path: /task3/main.py
from GANN import *
from casemanager import *
from load_dataset import load_data, get_valid_mnist
import tflowtools as TFT
import json
import random
random.seed(123)
np.random.seed(123)
tf.set_random_seed(123)
file_sets = ["wine", "glass", "gamma", "yeast"];
#... | code_fim | hard | {
"lang": "python",
"repo": "MrWe/aiprog17",
"path": "/task3/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#map_layers =
# map_dendrogram =
# display_weights =
# display_biases =
gradient_descent(epochs=epochs, dims=layers, cman=cman, lrate=lrate, showint=showint, mbs=mbs,
vfrac=vfrac, tfrac=tfrac, vint=vint, cfrac=cfrac, output_activation_function=output_activation_function,
h... | code_fim | hard | {
"lang": "python",
"repo": "MrWe/aiprog17",
"path": "/task3/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cancerregulome/gidget path: /commands/feature_matrix_construction/main/addIndicators.py
# -#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#
import miscClin
import tsvIO
import sys
# -#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#-#
NA_... | code_fim | hard | {
"lang": "python",
"repo": "cancerregulome/gidget",
"path": "/commands/feature_matrix_construction/main/addIndicators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # and then we add the pairwise indicator features ...
print " "
print " *** adding pairwise indicator features *** "
print labelList
print " "
for ak in range(len(labelList)):
aLabel = str(labelList[ak])
for bk in range(ak + 1, len(labelList)):
bLabel =... | code_fim | hard | {
"lang": "python",
"repo": "cancerregulome/gidget",
"path": "/commands/feature_matrix_construction/main/addIndicators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 笔多头平仓 ABCD
long_close_left_a = (s['30分钟_第N笔出井'] == '向上大井' or s['30分钟_五笔趋势类背驰'] == 'up') \
and s['30分钟_第N笔结束标记的分型强弱'] == 'strong'
long_close_left_b = s['30分钟_第N笔涨跌力度'] == '向上笔新高盘背' and s['30分钟_第N笔结束标记的分型强弱'] == 'strong'
long... | code_fim | hard | {
"lang": "python",
"repo": "dizzy21c/czsc",
"path": "/czsc/factors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dizzy21c/czsc path: /czsc/factors.py
# coding: utf-8
from collections import OrderedDict
from pyecharts.charts import Tab
from pyecharts.components import Table
from pyecharts.options import ComponentTitleOpts
from .signals import KlineSignals
from .utils.kline_generator import KlineGeneratorBy1M... | code_fim | hard | {
"lang": "python",
"repo": "dizzy21c/czsc",
"path": "/czsc/factors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> long_close_right_a = s['5分钟最近三根K线跌破30分钟第N笔下沿'] and s['30分钟_第N笔结束标记的分型强弱'] == 'strong'
long_close_right_b = s['5分钟_第N笔结束标记的上边沿'] < s['30分钟_第N笔结束标记的下边沿'] \
and "向上" in s['5分钟_第N笔涨跌力度']
long_close_right_c = s['5分钟_当下笔空头两重有效阻击'] or s['5分钟_当下... | code_fim | hard | {
"lang": "python",
"repo": "dizzy21c/czsc",
"path": "/czsc/factors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def i_conv(batchNorm, in_planes, out_planes, kernel_size=3, stride=1, bias=True):
if batchNorm:
conv2d = nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, pad_mode='pad',
padding=(kernel_size - 1) // 2, has_bias=bias)
batchNorm2d = nn.B... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/flownet2/src/submodels/submodules.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if batchnorm:
conv2d = nn.Conv2d(in_planes, out_planes, kernel_size=kernel_size, stride=stride, pad_mode='pad',
padding=(kernel_size - 1) // 2, has_bias=False)
batchNorm2d = nn.BatchNorm2d(out_planes)
leakyReLU = nn.LeakyReLU(0.1)
return nn.Se... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/flownet2/src/submodels/submodules.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mindspore-ai/models path: /research/cv/flownet2/src/submodels/submodules.py
# Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 a... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/cv/flownet2/src/submodels/submodules.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>0 + pennies/100
print("The total dollar amount is:", "$" + str(round(dollarAmount, 2)))
main()<|fim_prefix|># repo: Ikusey/itc110-sum2019 path: /ITC 110/projects/changeCounter.py
#change.py
def main():
print("This program calculates dollar amount from number or coins")
quarters = int... | code_fim | medium | {
"lang": "python",
"repo": "Ikusey/itc110-sum2019",
"path": "/ITC 110/projects/changeCounter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>kels: "))
pennies = int(input("Pennies: "))
dollarAmount = quarters/4 + dimes/10 + nickels/20 + pennies/100
print("The total dollar amount is:", "$" + str(round(dollarAmount, 2)))
main()<|fim_prefix|># repo: Ikusey/itc110-sum2019 path: /ITC 110/projects/changeCounter.py
#change.py
de... | code_fim | medium | {
"lang": "python",
"repo": "Ikusey/itc110-sum2019",
"path": "/ITC 110/projects/changeCounter.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ikusey/itc110-sum2019 path: /ITC 110/projects/changeCounter.py
#change.py
def main():
print("This program calculates dollar amount from number or coins")
<|fim_suffix|>kels: "))
pennies = int(input("Pennies: "))
dollarAmount = quarters/4 + dimes/10 + nickels/20 + pennies/100
... | code_fim | medium | {
"lang": "python",
"repo": "Ikusey/itc110-sum2019",
"path": "/ITC 110/projects/changeCounter.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = ['Bagging',
'HyperOpt',
'Utils']<|fim_prefix|># repo: Maxence-Labesse/AutoMxL path: /build/lib/AutoMxL/Modelisation/__init__.py
"""
Contains modules related to modelisation
<|fim_middle|>Modules :
- Bagging
- Classifiers
- Hyperopt
"""
| code_fim | easy | {
"lang": "python",
"repo": "Maxence-Labesse/AutoMxL",
"path": "/build/lib/AutoMxL/Modelisation/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Maxence-Labesse/AutoMxL path: /build/lib/AutoMxL/Modelisation/__init__.py
"""
Contains modules related to modelisation
<|fim_suffix|>__all__ = ['Bagging',
'HyperOpt',
'Utils']<|fim_middle|>Modules :
- Bagging
- Classifiers
- Hyperopt
"""
| code_fim | easy | {
"lang": "python",
"repo": "Maxence-Labesse/AutoMxL",
"path": "/build/lib/AutoMxL/Modelisation/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
__all__ = ['Bagging',
'HyperOpt',
'Utils']<|fim_prefix|># repo: Maxence-Labesse/AutoMxL path: /build/lib/AutoMxL/Modelisation/__init__.py
"""
Contains modules related to modelisation
<|fim_middle|>Modules :
- Bagging
- Classifiers
- Hyperopt
| code_fim | easy | {
"lang": "python",
"repo": "Maxence-Labesse/AutoMxL",
"path": "/build/lib/AutoMxL/Modelisation/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def divisorGen(n):
"""
http://stackoverflow.com/questions/171765/what-is-the-best-way-to-get-all-the-divisors-of-a-number
"""
factors = list(prime_factor_generator(n))
nfactors = len(factors)
if nfactors == 0:
return
f = [0] * nfactors
while True:
yield redu... | code_fim | hard | {
"lang": "python",
"repo": "danui/project-euler",
"path": "/solutions/python/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danui/project-euler path: /solutions/python/util.py
def n_choose_k(n, k):
if k > (n//2):
return n_choose_k(n, n-k)
x = 1
y = 1
for i in xrange(k):
x *= n-i
y *= 1+i
return x // y
def triangle_number(n):
return n * (n+1) // 2
def sum_of_range(s, t ... | code_fim | hard | {
"lang": "python",
"repo": "danui/project-euler",
"path": "/solutions/python/util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
http://stackoverflow.com/questions/171765/what-is-the-best-way-to-get-all-the-divisors-of-a-number
"""
factors = list(prime_factor_generator(n))
nfactors = len(factors)
if nfactors == 0:
return
f = [0] * nfactors
while True:
yield reduce(lambda x, y: x*y... | code_fim | hard | {
"lang": "python",
"repo": "danui/project-euler",
"path": "/solutions/python/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gamichaelh/fHDHR path: /fHDHR/plugins/plugin.py
import os
import imp
from .plugin_utils import Plugin_Utils
class Plugin():
"""
Methods for a Plugin.
"""
def __init__(self, config, logger, db, versions, plugin_name, plugin_path, plugin_conf, plugin_manifest):
self.conf... | code_fim | hard | {
"lang": "python",
"repo": "gamichaelh/fHDHR",
"path": "/fHDHR/plugins/plugin.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def version(self):
"""
Shortcut to plugin manifest value for version.
"""
return self.manifest["version"]
@property
def type(self):
"""
Shortcut to plugin manifest value for type.
"""
return self.manifest["type"]
... | code_fim | hard | {
"lang": "python",
"repo": "gamichaelh/fHDHR",
"path": "/fHDHR/plugins/plugin.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MurphyMarkW/python-flask-s3 path: /flasks3/drivers/driver.py
import abc
class S3StorageDriverABC(object):
"""S3 Storage driver abstract base class.
<|fim_suffix|> @abc.abstractmethod
def buckets(self, user=None):
"""Returns an iterable of buckets.
"""
raise N... | code_fim | medium | {
"lang": "python",
"repo": "MurphyMarkW/python-flask-s3",
"path": "/flasks3/drivers/driver.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Returns an iterable of buckets.
"""
raise NotImplementedError('TODO')
@abc.abstractmethod
def keys(self, bucket, user=None):
"""Returns an iterable of keys within a bucket.
"""
raise NotImplementedError('TODO')<|fim_prefix|># repo: MurphyMarkW/py... | code_fim | medium | {
"lang": "python",
"repo": "MurphyMarkW/python-flask-s3",
"path": "/flasks3/drivers/driver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Returns an iterable of keys within a bucket.
"""
raise NotImplementedError('TODO')<|fim_prefix|># repo: MurphyMarkW/python-flask-s3 path: /flasks3/drivers/driver.py
import abc
class S3StorageDriverABC(object):
"""S3 Storage driver abstract base class.
Defines interfa... | code_fim | hard | {
"lang": "python",
"repo": "MurphyMarkW/python-flask-s3",
"path": "/flasks3/drivers/driver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
class NA_MasterYi_Top_Morgana(Ratings):
pass
class NA_MasterYi_Top_Nami(Ratings):
pass
class NA_MasterYi_Top_Nasus(Ratings):
pass
class NA_MasterYi_Top_Nautilus(Ratings):
pass
class NA_MasterYi_Top_Nidalee(Ratings):
pass
class NA_MasterYi_Top_Nocturne(Ratings):
pass
... | code_fim | hard | {
"lang": "python",
"repo": "koliupy/loldib",
"path": "/loldib/getratings/models/NA/na_masteryi/na_masteryi_top.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: koliupy/loldib path: /loldib/getratings/models/NA/na_masteryi/na_masteryi_top.py
from getratings.models.ratings import Ratings
class NA_MasterYi_Top_Aatrox(Ratings):
pass
class NA_MasterYi_Top_Ahri(Ratings):
pass
class NA_MasterYi_Top_Akali(Ratings):
pass
class NA_MasterYi_Top_A... | code_fim | hard | {
"lang": "python",
"repo": "koliupy/loldib",
"path": "/loldib/getratings/models/NA/na_masteryi/na_masteryi_top.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(self.__data_list) == 0:
raise Exception("get_sorted_tup:尚未初始化数据")
else:
self.__sort()
return self.__data_list
def get_sorted_list(self):
return [x[1] for x in self.get_sorted_tup()]
def __sort(self):
N = len(self.__data_l... | code_fim | medium | {
"lang": "python",
"repo": "WhiteRobe/Python-alg",
"path": "/KeySort.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_sorted_list(self):
return [x[1] for x in self.get_sorted_tup()]
def __sort(self):
N = len(self.__data_list)
aux = [None for _ in range(0, N)]
count = [0 for _ in range(0, self.__R+1)]
for i in range(0, N):
count[self.__data_list[i][1][0]... | code_fim | hard | {
"lang": "python",
"repo": "WhiteRobe/Python-alg",
"path": "/KeySort.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WhiteRobe/Python-alg path: /KeySort.py
class KeySort:
# T(N) = 11N+2R+1
# D(N) = 2N+R
# Stable?
__data_list = []
__R = None
def set_data(self, data_tup, R):
# set data like [(0, 1), (index, value^)] value^ should be like (group_key, item_properties)
# $gro... | code_fim | hard | {
"lang": "python",
"repo": "WhiteRobe/Python-alg",
"path": "/KeySort.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WesIngwersen/perdu path: /perdu/searching/utils.py
import unicodedata
REPLACEMENTS = [
("market for ", ""),
("Market for ", ""),
(", at regional storehouse", ""),
(", at plant", ""),
(", AP-42", ""),
(", m3", ""),
]
REPLACEMENTS.extend([(", {}".format(x), "") for x in ran... | code_fim | medium | {
"lang": "python",
"repo": "WesIngwersen/perdu",
"path": "/perdu/searching/utils.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> string = unicodedata.normalize("NFKD", string).strip()
for x, y in REPLACEMENTS:
string = string.replace(x, y)
return string
def add_score(obj):
new = dict(obj.items())
new["score"] = obj.score
return new<|fim_prefix|># repo: WesIngwersen/perdu path: /perdu/searching/uti... | code_fim | medium | {
"lang": "python",
"repo": "WesIngwersen/perdu",
"path": "/perdu/searching/utils.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> local("python setup.py sdist")<|fim_prefix|># repo: yijiull/loopix-1 path: /fabfile.py
from fabric.api import env, sudo, run, settings, cd, local
from fabric.decorators import runs_once, roles, parallel
from fabric.tasks import execute
<|fim_middle|>@runs_once
def package():
| code_fim | easy | {
"lang": "python",
"repo": "yijiull/loopix-1",
"path": "/fabfile.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yijiull/loopix-1 path: /fabfile.py
from fabric.api import env, sudo, run, settings, cd, local
from fabric.decorators import runs_once, roles, parallel
from fabric.tasks import execute
<|fim_suffix|> local("python setup.py sdist")<|fim_middle|>@runs_once
def package():
| code_fim | easy | {
"lang": "python",
"repo": "yijiull/loopix-1",
"path": "/fabfile.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> vocab = list(idf)
wordids = dict((w,i) for i,w in enumerate(vocab))
X=[(i, wordids[w], ws[w]/sum(ws.values())*idf[w])
for i,ws in enumerate(docs) for w in ws
if w in wordids]
ii,jj,xx = zip(*X)
X=sparse.coo_matrix((xx, (ii, jj)), shape=[len(docs), len(vocab)])
X=X.toc... | code_fim | hard | {
"lang": "python",
"repo": "jseppanen/textpile",
"path": "/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> import warnings
# suppress a million of these:
# score += numpy.sum(cnt * logsumexp(Elogthetad + Elogbeta[:, id]) for id, cnt in doc)
# /usr/local/lib/python2.7/dist-packages/gensim/models/ldamodel.py:634: DeprecationWarning: using a non-integer number instead of an integer will result i... | code_fim | hard | {
"lang": "python",
"repo": "jseppanen/textpile",
"path": "/model.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jseppanen/textpile path: /model.py
from __future__ import division
from sklearn.linear_model import SGDClassifier
from sklearn.cross_validation import StratifiedKFold
from scipy import sparse
from collections import defaultdict
import re
import numpy as np
import sys
def train(docs, labels, regu... | code_fim | hard | {
"lang": "python",
"repo": "jseppanen/textpile",
"path": "/model.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> VR = V.Validate_NMR_Restraints()
self.assertAlmostEqual(
VR.get_dihedral_angle(array([-39.343, - 18.738, 25.524]), array([-38.452, - 19.489, 26.2]),
array([-38.82, - 20.666, 27.017]),
array([-39.206, - 20.263, ... | code_fim | hard | {
"lang": "python",
"repo": "kumar-physics/RestraintsValidation",
"path": "/test_validate_NMR_Restraints.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kumar-physics/RestraintsValidation path: /test_validate_NMR_Restraints.py
from unittest import TestCase
from numpy import array
import Validate_NMR_Restraints as V
class TestValidate_NMR_Restraints(TestCase):
# def test_generate_json(self):
# self.fail()
#
# def test_restrai... | code_fim | hard | {
"lang": "python",
"repo": "kumar-physics/RestraintsValidation",
"path": "/test_validate_NMR_Restraints.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif (val == 2): #Moves LEFT
new_xpos = x[-1] - 1
new_ypos = y[-1]
x = np.append(x, new_xpos)
y = np.append(y, new_ypos)
elif (val == 3): #Moves DOWN
new_xpos = x[-1]
new_ypos = y[-1] - 1
... | code_fim | hard | {
"lang": "python",
"repo": "DAguirreAg/Dragon-curve-generator",
"path": "/Dragon_Curve.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> elif (val == 1): #Moves UP
new_xpos = x[-1]
new_ypos = y[-1] + 1
x = np.append(x, new_xpos)
y = np.append(y, new_ypos)
elif (val == 2): #Moves LEFT
new_xpos = x[-1] - 1
new_ypos = y[-1]
... | code_fim | hard | {
"lang": "python",
"repo": "DAguirreAg/Dragon-curve-generator",
"path": "/Dragon_Curve.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DAguirreAg/Dragon-curve-generator path: /Dragon_Curve.py
##############################
# #
# Created by: Daniel Aguirre #
# Date: 2019/05/07 #
# #
##############################
# Imports
import numpy as np
import matplo... | code_fim | hard | {
"lang": "python",
"repo": "DAguirreAg/Dragon-curve-generator",
"path": "/Dragon_Curve.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> except: # catch all other exceptions, e.g. errors due to non-convergent training etc.
logging.exception("Error occured.")
avg_corr_after_train = None
avg_corr_before_train = None
last_step = None
# save parameters and results into csv
... | code_fim | hard | {
"lang": "python",
"repo": "ecker-lab/burg2021_learning_divisive_normalization",
"path": "/divisive_3x3_surround_net/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ecker-lab/burg2021_learning_divisive_normalization path: /divisive_3x3_surround_net/train.py
import csv
import logging
import os
import time
import matplotlib
import numpy as np
from divisivenormalization.data import Dataset, MonkeySubDataset
from divisivenormalization.models import DivisiveNet... | code_fim | hard | {
"lang": "python",
"repo": "ecker-lab/burg2021_learning_divisive_normalization",
"path": "/divisive_3x3_surround_net/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> training = model.train(
max_iter=max_iter,
learning_rate=learning_rate,
batch_size=batch_size,
val_steps=val_steps,
save_steps=1000,
early_stopping_steps=early_stopping_s... | code_fim | hard | {
"lang": "python",
"repo": "ecker-lab/burg2021_learning_divisive_normalization",
"path": "/divisive_3x3_surround_net/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print data_dict
return X[self.key]
def make_features_pipeline(features, vectorizers, clf):
transformer_list = []
for feature in features:
vectorizer = vectorizers[feature]
transformer = (feature, Pipeline([
('selector', ItemSelector(key=feature)),... | code_fim | hard | {
"lang": "python",
"repo": "stjordanis/ceo",
"path": "/ceo/selector.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stjordanis/ceo path: /ceo/selector.py
import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.pipeline import FeatureUnion
from sklearn.pipeline import Pipeline
from sklearn.svm import SVC
class DenseTransformer(BaseEstimator, TransformerMixin):
def transfo... | code_fim | hard | {
"lang": "python",
"repo": "stjordanis/ceo",
"path": "/ceo/selector.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> transformer_list = []
for feature in features:
vectorizer = vectorizers[feature]
transformer = (feature, Pipeline([
('selector', ItemSelector(key=feature)),
(feature+"-vectorizer", vectorizer),
('todense', DenseTransformer()),
... | code_fim | hard | {
"lang": "python",
"repo": "stjordanis/ceo",
"path": "/ceo/selector.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aesavas/HackerRank path: /Python/Sets/Set Add/solution.py
"""
author : Ali Emre SAVAS
Link : https://www.hackerrank.<|fim_suffix|> counter = int(input())
countries = set()
for _ in range(counter):
countries.add(input())
print(len(countries))<|fim_middle|>com/challeng... | code_fim | medium | {
"lang": "python",
"repo": "aesavas/HackerRank",
"path": "/Python/Sets/Set Add/solution.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>(counter):
countries.add(input())
print(len(countries))<|fim_prefix|># repo: aesavas/HackerRank path: /Python/Sets/Set Add/solution.py
"""
author : Ali Emre SAVAS
Link : https://www.hackerrank.com/challenges/py-set-add/problem
"""
if __name__ == "__main__":
<|fim_middle|> counter =... | code_fim | medium | {
"lang": "python",
"repo": "aesavas/HackerRank",
"path": "/Python/Sets/Set Add/solution.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nsbgit/IIT-S21-CS-484 path: /Old Materials/Additional Github/dvtate/cs484/assignment3/tree.py
# Load the necessary libraries
import matplotlib.pyplot as plt
import numpy
import pandas
import sklearn.cluster as cluster
import sklearn.metrics as metrics
import sklearn.tree as tree
# Read data
df =... | code_fim | hard | {
"lang": "python",
"repo": "nsbgit/IIT-S21-CS-484",
"path": "/Old Materials/Additional Github/dvtate/cs484/assignment3/tree.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Print column names that were assigned by pandas.get_dummies
print('Some labels:')
for i, col in enumerate(one_hot_inputs):
print('X[%s] = %s' % (i, col))
if i > 10:
break
print('\n')
# Find misclassification rate for test data
one_hot_inputs = pandas.get_dummies(
test_data[['CAR_T... | code_fim | hard | {
"lang": "python",
"repo": "nsbgit/IIT-S21-CS-484",
"path": "/Old Materials/Additional Github/dvtate/cs484/assignment3/tree.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Sorted List\n")
print(*list)
if __name__ == "__main__":
main()<|fim_prefix|># repo: AnupKumarPanwar/Python path: /sorts/odd_even_transposition_single_threaded.py
"""
This is a non-parallelized implementation of odd-even transpostiion sort.
Normally the swaps in each set happen simul... | code_fim | hard | {
"lang": "python",
"repo": "AnupKumarPanwar/Python",
"path": "/sorts/odd_even_transposition_single_threaded.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AnupKumarPanwar/Python path: /sorts/odd_even_transposition_single_threaded.py
"""
This is a non-parallelized implementation of odd-even transpostiion sort.
Normally the swaps in each set happen simultaneously, without that the algorithm
is no better than bubble sort.
"""
<|fim_suffix|> list... | code_fim | hard | {
"lang": "python",
"repo": "AnupKumarPanwar/Python",
"path": "/sorts/odd_even_transposition_single_threaded.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vallard/ucsmsdk_samples path: /ucsmsdk_samples/server/adapter_policy.py
# Copyright 2015 Cisco Systems, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://ww... | code_fim | hard | {
"lang": "python",
"repo": "vallard/ucsmsdk_samples",
"path": "/ucsmsdk_samples/server/adapter_policy.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
from ucsmsdk.mometa.adaptor.AdaptorHostEthIfProfile import \
AdaptorHostEthIfProfile
obj = handle.query_dn(parent_dn)
if not obj:
raise ValueError("org '%s' does not exist" % parent_dn)
mo = AdaptorHostEthIfProfile(parent_mo_or_dn=obj, name=name, descr=descr)
... | code_fim | hard | {
"lang": "python",
"repo": "vallard/ucsmsdk_samples",
"path": "/ucsmsdk_samples/server/adapter_policy.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #SeriesとDataFrameの計算 X Y X
series3 = dframe2.ix[2] #6.0 7.0 8.0
print(dframe2)
'''
X Y Z
A 0 1 2
B 3 4 5
C 6 7 8
'''
print(dframe2 - series3) #series3が、dframe2の全行から引かれる
'''
X Y Z
A -6 -6 -6
B -3 -3 -3
C 0... | code_fim | hard | {
"lang": "python",
"repo": "000ubird/PythonTest",
"path": "/src/セクション4/lecture20.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 000ubird/PythonTest path: /src/セクション4/lecture20.py
'''
Created on 2018/08/27
@author: User
'''
import numpy as np
from numpy.random import randn
from pandas import Series, DataFrame
from pandas.tests.frame.test_validate import dataframe
from bokeh.layouts import column
<|fim_suffix|> dframe... | code_fim | hard | {
"lang": "python",
"repo": "000ubird/PythonTest",
"path": "/src/セクション4/lecture20.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #もとのデータを入れたい場合
print(dframe1.add(dframe2, fill_value=0))
'''
X Y Z
A 0.0 2.0 2.0
B 5.0 7.0 5.0
C 6.0 7.0 8.0
'''
#SeriesとDataFrameの計算 X Y X
series3 = dframe2.ix[2] #6.0 7.0 8.0
print(dframe2)
'''
X Y Z
A ... | code_fim | hard | {
"lang": "python",
"repo": "000ubird/PythonTest",
"path": "/src/セクション4/lecture20.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if(config.debug):
log_debug("Current config:")
pprint(vars(config))
if not prompt_yesno_question("[DEBUG] Continue?"):
sys.exit()
maven = Maven(config, github)
input("\nPlease close all eclipse instances as of potential race conditions on maven builds causing errors. Press return if ... | code_fim | hard | {
"lang": "python",
"repo": "sanjaykumarcg/tools-cobigen",
"path": "/scripts/src/create_release.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sanjaykumarcg/tools-cobigen path: /scripts/src/create_release.py
import os
import sys
import logging
import yaml
from pprint import pprint
from github.Milestone import Milestone
from tools.config import Config
from tools.github import GitHub
from tools.git_repo import GitRepo
from tools.validat... | code_fim | hard | {
"lang": "python",
"repo": "sanjaykumarcg/tools-cobigen",
"path": "/scripts/src/create_release.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>#############################
__log_step("Validate merge commit...")
#############################
list_of_changed_files = git_repo.get_changed_files_of_last_commit()
is_pom_changed = False
for file_name in list_of_changed_files:
file_name = file_name.replace('/', os.sep)
if not file_name.startswi... | code_fim | hard | {
"lang": "python",
"repo": "sanjaykumarcg/tools-cobigen",
"path": "/scripts/src/create_release.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> organization.add_post(role='Mayor', label=self.division_name, division_id=self.division_id)
for seat_number in range(1, 9):
organization.add_post(role='Councillor', label='Surrey (seat {})'.format(seat_number), division_id=self.division_id)
yield organization<|fim_pref... | code_fim | medium | {
"lang": "python",
"repo": "cmonagle/scrapers-ca",
"path": "/ca_bc_surrey/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_organizations(self):
organization = Organization(self.name, classification=self.classification)
organization.add_post(role='Mayor', label=self.division_name, division_id=self.division_id)
for seat_number in range(1, 9):
organization.add_post(role='Councillo... | code_fim | hard | {
"lang": "python",
"repo": "cmonagle/scrapers-ca",
"path": "/ca_bc_surrey/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cmonagle/scrapers-ca path: /ca_bc_surrey/__init__.py
from __future__ import unicode_literals
from utils import CanadianJurisdiction
from pupa.scrape import Organization
<|fim_suffix|> classification = 'legislature'
division_id = 'ocd-division/country:ca/csd:5915004'
division_name = 'S... | code_fim | medium | {
"lang": "python",
"repo": "cmonagle/scrapers-ca",
"path": "/ca_bc_surrey/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> resp = self.api.locateMyIP()
self.assertFalse(resp.country_code is None)
resp = self.api.locateGivenIP("8.8.8.8")
self.assertFalse(resp.country_code is "US")<|fim_prefix|># repo: taxamo/taxamo-python path: /taxamo/test/test_geoip_api.py
"""
Copyright 2014-2021 by Taxamo... | code_fim | medium | {
"lang": "python",
"repo": "taxamo/taxamo-python",
"path": "/taxamo/test/test_geoip_api.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> resp = self.api.locateGivenIP("8.8.8.8")
self.assertFalse(resp.country_code is "US")<|fim_prefix|># repo: taxamo/taxamo-python path: /taxamo/test/test_geoip_api.py
"""
Copyright 2014-2021 by Taxamo
Licensed under the Apache License, Version 2.0 (the "License");
you may not use t... | code_fim | hard | {
"lang": "python",
"repo": "taxamo/taxamo-python",
"path": "/taxamo/test/test_geoip_api.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: taxamo/taxamo-python path: /taxamo/test/test_geoip_api.py
"""
Copyright 2014-2021 by Taxamo
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apa... | code_fim | medium | {
"lang": "python",
"repo": "taxamo/taxamo-python",
"path": "/taxamo/test/test_geoip_api.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/DLGHWINF-MIB.py
", "MibTableRow", "MibTableColumn", "Integer32", "MibIdentifier", "IpAddress", "Counter32", "ObjectIdentity", "Counter64", "Unsigned32", "Gauge32")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvent... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DLGHWINF-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/DLGHWINF-MIB.py
oduced by pysmi-0.3.4 at Mon Apr 29 18:32:47 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
OctetString, ObjectIdentifier, Integer = mibBui... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DLGHWINF-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>dentServiceChangeDate.setStatus('mandatory')
dlgHiIdentTrapMask = MibScalar((1, 3, 6, 1, 4, 1, 3028, 1, 1, 2, 2, 5), Integer32()).setMaxAccess("readwrite")
if mibBuilder.loadTexts: dlgHiIdentTrapMask.setStatus('mandatory')
dlgHiIdentSystemServicesTable = MibTable((1, 3, 6, 1, 4, 1, 3028, 1, 1, 2, 2, 6), )... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/DLGHWINF-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(uf.find(1), 1)
self.assertEqual(uf.find(2), 1)
def test_union(self):
uf = UnionFind([[1,2,3],[4,5],[6,7,8,9,0]])
self.assertEqual(uf.find(2), 1)
self.assertEqual(uf.find(5), 4)
uf.union(2,5)
self.assertEqual(uf.find(1), 1)
... | code_fim | hard | {
"lang": "python",
"repo": "santoshpy/algorithms-1",
"path": "/test_union_find.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: santoshpy/algorithms-1 path: /test_union_find.py
import unittest
from union_find import UnionFind
class TestUnionFind(unittest.TestCase):
def test_find(self):
uf = UnionFind([[1,2,3],[4,5],[6,7,8,9,0]])
self.assertEqual(uf.find(1), 1)
self.assertEqual(uf.find(2), 1)
... | code_fim | hard | {
"lang": "python",
"repo": "santoshpy/algorithms-1",
"path": "/test_union_find.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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