text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> def __repr__(self):
record = AttendanceCodes.query.filter_by(id = cid).first()
return "<attendance_record uid=%s cid=%s>" % (self.uid, record.cid)
@classmethod
def count(self, user):
if isinstance(user, int):
uid = user
else:
uid = user.id
return self.query.filter_by... | code_fim | hard | {
"lang": "python",
"repo": "CS-Center/CS-Center",
"path": "/wcics/database/models/attendance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CS-Center/CS-Center path: /wcics/database/models/attendance.py
# -*- coding: utf-8 -*-
from ..consts.attendance import ATTENDANCE_CODE_MAX_LENGTH
from .aliases import *
from .helper import Helper
from wcics.utils.time import get_time
from wcics.utils.url import get_org_id
class attendance_cod... | code_fim | hard | {
"lang": "python",
"repo": "CS-Center/CS-Center",
"path": "/wcics/database/models/attendance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mlsendian/nessus-report-parser path: /nessus_report_parser/model/report.py
from collections import UserDict
from lxml import etree
from .report_host import ReportHost
class Report(UserDict):
<|fim_suffix|> assert isinstance(properties, dict)
self.data = properties
@staticm... | code_fim | medium | {
"lang": "python",
"repo": "mlsendian/nessus-report-parser",
"path": "/nessus_report_parser/model/report.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Report(UserDict):
def __init__(self, properties):
assert isinstance(properties, dict)
self.data = properties
@staticmethod
def from_etree(elem):
assert isinstance(elem, etree._Element)
assert elem.tag == 'Report'
properties = {
'name'... | code_fim | medium | {
"lang": "python",
"repo": "mlsendian/nessus-report-parser",
"path": "/nessus_report_parser/model/report.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FFMG/myoddweb.piger path: /myodd/boost/libs/python/config/cxx.py
#
# Copyright (c) 2016 Stefan Seefeld
# All rights reserved.
#
# Distributed under the Boost Software License, Version 1.0.
# (See accompanying file LICENSE_1_0.txt or copy at
# http://www.boost.org/LICENSE_1_0.txt)
<|fim_suffix|>
... | code_fim | medium | {
"lang": "python",
"repo": "FFMG/myoddweb.piger",
"path": "/myodd/boost/libs/python/config/cxx.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> context.Message('Checking for C++11 support...')
if not context.TryCompile(source, '.cpp'):
context.env['CXX11'] = False
context.Result(0)
else:
context.env['CXX11'] = True
context.Result(1)
return True<|fim_prefix|># repo: FFMG/myoddweb.piger path: /myodd... | code_fim | medium | {
"lang": "python",
"repo": "FFMG/myoddweb.piger",
"path": "/myodd/boost/libs/python/config/cxx.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> T=transition_matrix.transition_matrix_non_reversible(self.C1).toarray()
assert_allclose(T, self.T1.toarray())
if __name__=="__main__":
unittest.main()<|fim_prefix|># repo: kziolkowska/PyEMMA path: /pyemma/msm/estimation/sparse/transition_matrix_test.py
import unittest
... | code_fim | medium | {
"lang": "python",
"repo": "kziolkowska/PyEMMA",
"path": "/pyemma/msm/estimation/sparse/transition_matrix_test.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kziolkowska/PyEMMA path: /pyemma/msm/estimation/sparse/transition_matrix_test.py
import unittest
import numpy as np
from pyemma.util.numeric import assert_allclose
import scipy.sparse
import transition_matrix
"""Unit tests for the transition_matrix module"""
class TestTransitionMatrixNonRever... | code_fim | hard | {
"lang": "python",
"repo": "kziolkowska/PyEMMA",
"path": "/pyemma/msm/estimation/sparse/transition_matrix_test.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_count_matrix(self):
"""Small test cases"""
T=transition_matrix.transition_matrix_non_reversible(self.C1).toarray()
assert_allclose(T, self.T1.toarray())
T=transition_matrix.transition_matrix_non_reversible(self.C1).toarray()
assert_allclose(T, ... | code_fim | hard | {
"lang": "python",
"repo": "kziolkowska/PyEMMA",
"path": "/pyemma/msm/estimation/sparse/transition_matrix_test.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument(
'--use_mixer',
type=int,
default=0, # 1
help='Use schedule sampling')
parser.add_argument(
'--mixer_from',
type=int,
default=-1,
help='If -1, then an annealing scheme will be used, based on mixer_descrease_every.\... | code_fim | hard | {
"lang": "python",
"repo": "meunal/Attributes_SVO_Video_Captioning",
"path": "/opts.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: meunal/Attributes_SVO_Video_Captioning path: /opts.py
import argparse
# set for MSR-VTT defaults
def parse_opts():
parser = argparse.ArgumentParser()
parser.add_argument(
'--dataset',
type=str,
default='msvd',
choices=[
'msvd',
'm... | code_fim | hard | {
"lang": "python",
"repo": "meunal/Attributes_SVO_Video_Captioning",
"path": "/opts.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BCCWAI/Konverter path: /konverter/__main__.py
from tensorflow import keras
from konverter import Konverter
import typer
def main(input_model:str, output_script:str, indentation:int=2, verbose:bool=True, use_watermark:bool=True):
model = keras.models.load_model(input_model)
konverter = Konve... | code_fim | easy | {
"lang": "python",
"repo": "BCCWAI/Konverter",
"path": "/konverter/__main__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = keras.models.load_model(input_model)
konverter = Konverter(model, output_file=output_script, indent_spaces=indentation,
verbose=verbose, use_watermark=use_watermark)
def run():
typer.run(main)
if __name__ == '__main__':
run()<|fim_prefix|># repo: BCCWAI/Konverte... | code_fim | medium | {
"lang": "python",
"repo": "BCCWAI/Konverter",
"path": "/konverter/__main__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aroodooteam/azxts path: /aro_account_fiscalyear_close/models/base_agency.py
# -*- coding: utf-8 -*-
import logging
logger = logging.getLogger(__name__)
from . import agency_account as agac
from openerp import api, exceptions, fields, models, _
<|fim_suffix|> account_ids = fields.One2many(co... | code_fim | medium | {
"lang": "python",
"repo": "aroodooteam/azxts",
"path": "/aro_account_fiscalyear_close/models/base_agency.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> account_obj = self.env['account.account']
agac_obj = self.env['base.agency.account']
agac_ids = agac_obj.search([('agency_id', '=', self.id)])
agac_ids.unlink()
for k,v in agac.ALL_AGENCY.iteritems():
if k[-2:] == self.code:
for account i... | code_fim | medium | {
"lang": "python",
"repo": "aroodooteam/azxts",
"path": "/aro_account_fiscalyear_close/models/base_agency.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhouronghua/daisycloud-core path: /code/daisy/daisy/db/sqlalchemy/migrate_repo/versions/001_add_daisy_tables.py
), primary_key=True,
nullable=False),
Column('role_id', String(36), ForeignKey('roles.id'),
n... | code_fim | hard | {
"lang": "python",
"repo": "zhouronghua/daisycloud-core",
"path": "/code/daisy/daisy/db/sqlalchemy/migrate_repo/versions/001_add_daisy_tables.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def define_dns_nameservers_table(meta):
dns_nameservers = Table('dns_nameservers',
meta,
Column('id', String(36), primary_key=True,
nullable=False),
Column('dns', String(128)),
... | code_fim | hard | {
"lang": "python",
"repo": "zhouronghua/daisycloud-core",
"path": "/code/daisy/daisy/db/sqlalchemy/migrate_repo/versions/001_add_daisy_tables.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def make_ethereum_address() -> ChecksumEthAddress:
return to_checksum_address('0x' + make_random_bytes(20).hex())
UNIT_BTC_ADDRESS1 = '1BvBMSEYstWetqTFn5Au4m4GFg7xJaNVN2'
UNIT_BTC_ADDRESS2 = '1CounterpartyXXXXXXXXXXXXXXXUWLpVr'
UNIT_BTC_ADDRESS3 = '18ddjB7HWTVxzvTbLp1nWvaBxU3U2oTZF2'
ZERO_ETH_ADDRE... | code_fim | hard | {
"lang": "python",
"repo": "tuanggo/rotki",
"path": "/rotkehlchen/tests/utils/factories.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tuanggo/rotki path: /rotkehlchen/tests/utils/factories.py
import base64
import random
import string
from typing import Optional
from eth_utils.address import to_checksum_address
from rotkehlchen.fval import FVal
from rotkehlchen.serialization.deserialize import deserialize_ethereum_address
from... | code_fim | medium | {
"lang": "python",
"repo": "tuanggo/rotki",
"path": "/rotkehlchen/tests/utils/factories.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def make_random_positive_fval(max_num: int = 1000000) -> FVal:
return FVal(random.uniform(0, max_num))
def make_random_timestamp(
start: Optional[Timestamp] = DEFAULT_START_TS,
end: Optional[Timestamp] = None,
) -> Timestamp:
if end is None:
end = ts_now()
if start is... | code_fim | hard | {
"lang": "python",
"repo": "tuanggo/rotki",
"path": "/rotkehlchen/tests/utils/factories.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TheNikomo/PiMorse path: /run.py
#!/usr/bin/env python3
import control
from morse import morse
<|fim_suffix|> for character in userinput:
signals = morse[character.upper()]
for signal in signals:
print(signal, end="", flush=True)
control.blink(signal)
... | code_fim | medium | {
"lang": "python",
"repo": "TheNikomo/PiMorse",
"path": "/run.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> for character in userinput:
signals = morse[character.upper()]
for signal in signals:
print(signal, end="", flush=True)
control.blink(signal)
print()<|fim_prefix|># repo: TheNikomo/PiMorse path: /run.py
#!/usr/bin/env python3
import control
from morse impo... | code_fim | medium | {
"lang": "python",
"repo": "TheNikomo/PiMorse",
"path": "/run.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nevoband/ansible-role-firewalld path: /molecule/default/tests/test_default.py
import os
import testinfra.utils.ansible_runner
testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner(
os.environ['MOLECULE_INVENTORY_FILE']).get_hosts('all')
<|fim_suffix|> content = [
"<ser... | code_fim | hard | {
"lang": "python",
"repo": "nevoband/ansible-role-firewalld",
"path": "/molecule/default/tests/test_default.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> content = [
"<service name=\"http\"/>",
"<port protocol=\"tcp\" port=\"4444\"/>",
"<port protocol=\"tcp\" port=\"80\"/>",
"<source address=\"127.0.0.1\"/>"
]
file = host.file("/etc/firewalld/zones/public.xml")
assert file.exists
for line in content:
... | code_fim | medium | {
"lang": "python",
"repo": "nevoband/ansible-role-firewalld",
"path": "/molecule/default/tests/test_default.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main(excel_workbook_name):
validate_workbook(excel_workbook_name)
loader = ExcelTestLoader()
tests = loader.load_tests_from_workbook(excel_workbook_name)
test_runner = TextTestRunner(verbosity=1,
failfast=None,
buff... | code_fim | hard | {
"lang": "python",
"repo": "dataunit/dataunit",
"path": "/dataunit/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> validate_workbook(excel_workbook_name)
loader = ExcelTestLoader()
tests = loader.load_tests_from_workbook(excel_workbook_name)
test_runner = TextTestRunner(verbosity=1,
failfast=None,
buffer=None,
... | code_fim | hard | {
"lang": "python",
"repo": "dataunit/dataunit",
"path": "/dataunit/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dataunit/dataunit path: /dataunit/main.py
from argparse import ArgumentParser
from unittest.runner import TextTestRunner
from dataunit.excel.loader import ExcelTestLoader
from dataunit.excel.validator import validate_workbook
def parse_args(argv: list):
parser = ArgumentParser()
parser.... | code_fim | hard | {
"lang": "python",
"repo": "dataunit/dataunit",
"path": "/dataunit/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eBioKit/ebiokit-site path: /server/applications/migrations/0005_application_raw_options.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.4 on 2017-10-24 11:04
from __future__ import unicode_literals
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
('appl... | code_fim | easy | {
"lang": "python",
"repo": "eBioKit/ebiokit-site",
"path": "/server/applications/migrations/0005_application_raw_options.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='application',
name='raw_options',
field=models.CharField(default=b'', max_length=2000),
),
]<|fim_prefix|># repo: eBioKit/ebiokit-site path: /server/applications/migrations/0005_application_raw_opt... | code_fim | medium | {
"lang": "python",
"repo": "eBioKit/ebiokit-site",
"path": "/server/applications/migrations/0005_application_raw_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Migration(migrations.Migration):
dependencies = [
('applications', '0004_task_incompatible'),
]
operations = [
migrations.AddField(
model_name='application',
name='raw_options',
field=models.CharField(default=b'', max_length=2000),
... | code_fim | easy | {
"lang": "python",
"repo": "eBioKit/ebiokit-site",
"path": "/server/applications/migrations/0005_application_raw_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Enables the pile-up correction for jets in a PF2PAT+PAT sequence
to be called after the usePF2PAT function.
"""
enablePileUpCorrectionInPF2PAT( process, postfix, sequence)
enablePileUpCorrectionInPAT( process, postfix, sequence)<|fim_prefix|># repo: cms-sw/cmssw path: /Common... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/CommonTools/ParticleFlow/python/Tools/enablePileUpCorrection.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> jetCorrFactors = getattr(process,"patJetCorrFactors"+postfix)
# using non-pileup-charged-hadron-substracted kt6PFJets consistently with JetMET recommendation
jetCorrFactors.rho = cms.InputTag("fixedGridRhoFastjetAll")
def enablePileUpCorrection( process, postfix, sequence='patPF2PATSequence'... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/CommonTools/ParticleFlow/python/Tools/enablePileUpCorrection.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cms-sw/cmssw path: /CommonTools/ParticleFlow/python/Tools/enablePileUpCorrection.py
import FWCore.ParameterSet.Config as cms
def enablePileUpCorrectionInPF2PAT( process, postfix, sequence='PF2PAT'):
"""
Modifies the PF2PAT sequence according to the recipe of JetMET:
"""
# pile u... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/CommonTools/ParticleFlow/python/Tools/enablePileUpCorrection.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ericmjl/protein-systematic-characterization path: /src/apps/mutagenesis.py
from calculators import mutagenesis as mt
from flask import Flask, render_template, request
import numpy as np
import math
app = Flask(__name__)
mut_freq_mass = dict(low=500, med=100, high=50)
mut_freq_fold = dict(low=5... | code_fim | medium | {
"lang": "python",
"repo": "ericmjl/protein-systematic-characterization",
"path": "/src/apps/mutagenesis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Access the necessary variables.
target_mass = mut_freq_mass[mut_freq]
fold_amp = mut_freq_fold[mut_freq]
# Compute what needs to be computed.
input_mass = mt.input_plasmid_mass(target_len, plasmid_len, target_mass)
input_volume = mt.input_volume(input_mass, input_conc)
num_c... | code_fim | hard | {
"lang": "python",
"repo": "ericmjl/protein-systematic-characterization",
"path": "/src/apps/mutagenesis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> subparsers = parser.add_subparsers(title='commands')
dl_all = subparsers.add_parser('download_all',
help='generate queries & download')
dl_all.set_defaults(func=download_all)
dl = subparsers.add_parser('download',
help='create/generat... | code_fim | hard | {
"lang": "python",
"repo": "Jonnyblacklabel/gsc_sa_downloader",
"path": "/gsc_sa_downloader/gsc_sa_downloader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
for job in tqdm(list(jobs), desc='jobs', leave=False):
queue = db.get_query_queue_items(property_['id'],
job['id'],
finished = False,
attempts = {'<=': 5})
thread_queue_ite... | code_fim | hard | {
"lang": "python",
"repo": "Jonnyblacklabel/gsc_sa_downloader",
"path": "/gsc_sa_downloader/gsc_sa_downloader.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jonnyblacklabel/gsc_sa_downloader path: /gsc_sa_downloader/gsc_sa_downloader.py
# _ __ __ __ __ __ __
# (_)___ ____ ____ __ __/ /_ / /___ ______/ /__/ /___ _/ /_ ___ / /
# / / __ \/ __ \/ __ \/ / / / __ \/ / __ `/ ___/ //_/... | code_fim | hard | {
"lang": "python",
"repo": "Jonnyblacklabel/gsc_sa_downloader",
"path": "/gsc_sa_downloader/gsc_sa_downloader.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not product:
abort(404, description="The product with the product ID does not exist")
product_json = {
"id": product.id,
"title": product.title,
"description": product.description,
"price": product.price,
"image_url": product.image_url,
}
... | code_fim | hard | {
"lang": "python",
"repo": "SaiMounikaP/lcc-ecommerce-api",
"path": "/endpoints.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SaiMounikaP/lcc-ecommerce-api path: /endpoints.py
from flask import Blueprint, abort, jsonify
import crud
from db import SessionLocal
bp = Blueprint("endpoints", __name__, url_prefix="/")
@bp.get("/categories")
def read_categories():
db_session = SessionLocal()
categories = crud.get_c... | code_fim | hard | {
"lang": "python",
"repo": "SaiMounikaP/lcc-ecommerce-api",
"path": "/endpoints.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rows = []
# append header row (from sessions table).
rows.append([request, format_timestamp(started_at), coordinator, 0])
# append main rows (from events table).
for activity, event_id, source, source_elapsed in events:
rows.append([activity, format_time... | code_fim | hard | {
"lang": "python",
"repo": "lalithsuresh/cassandra-c3",
"path": "/pylib/cqlshlib/tracing.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lalithsuresh/cassandra-c3 path: /pylib/cqlshlib/tracing.py
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this fi... | code_fim | hard | {
"lang": "python",
"repo": "lalithsuresh/cassandra-c3",
"path": "/pylib/cqlshlib/tracing.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ arte_plus_7 main function """
opts = parser().parse_args()
if opts.verbose:
LOGGER.setLevel(logging.DEBUG)
# Get programs
if opts.url:
programs = [Plus7Program.by_url(opts.url)]
elif opts.program:
programs = ArtePlus7.program(opts.program)
elif opts... | code_fim | hard | {
"lang": "python",
"repo": "cladmi/arte_plus7",
"path": "/arte_plus7.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cladmi/arte_plus7 path: /arte_plus7.py
#! /usr/bin/python
# -*- coding:utf-8 -*-
""" arte_plus_7 is a script to help download arte videos
It's only configured for French at the moment.
Usage:
The following commands will return the videos urls found
# The generic program page
./arte_pl... | code_fim | hard | {
"lang": "python",
"repo": "cladmi/arte_plus7",
"path": "/arte_plus7.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Download the video."""
url = self.urls[quality]
directory = directory or '.'
dl_name = '{name}_{quality}.mp4'
dl_name = dl_name.format(name=self.full_name, quality=quality)
dl_name = os.path.join(directory, dl_name)
cmd = ['wget', '--continue',... | code_fim | hard | {
"lang": "python",
"repo": "cladmi/arte_plus7",
"path": "/arte_plus7.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juliencombattelli/BE-RDS path: /tp1/grasp.py
#!/usr/bin/ipython
import numpy as np
from robot import Robot
from scipy.optimize import fmin_bfgs, fmin_slsqp
import pinocchio as se3
from pinocchio.utils import *
import time
from FootSteps import *
robot = Robot()
i = 0
<|fim_suffix|>'''
# Optimi... | code_fim | hard | {
"lang": "python",
"repo": "juliencombattelli/BE-RDS",
"path": "/tp1/grasp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.nfeval = 1
def __call__(self,x):
print '===CBK=== {0:4d} {1: 3.6f} {2: 3.6f}'.format(self.nfeval, x[0], x[1], cost(x))
self.nfeval += 1
robot.display(robot.q0)
q = robot.q0
for i in range(0,20):
# Optimize cost without any constraints in BFGS, with traces.
try:
xopt_bfgs = fmin_bfgs... | code_fim | hard | {
"lang": "python",
"repo": "juliencombattelli/BE-RDS",
"path": "/tp1/grasp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GoogleCloudPlatform/cloud-opensource-python path: /compatibility_server/views.py
# Copyright 2019 Google LLC
#
# 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
#
# htt... | code_fim | medium | {
"lang": "python",
"repo": "GoogleCloudPlatform/cloud-opensource-python",
"path": "/compatibility_server/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># docker error
DOCKER_ERROR_MEASURE = measure_module.MeasureInt(
'docker_error', 'The number of docker errors.', 'Errors')
DOCKER_ERROR_VIEW = view_module.View(
"docker_error_count",
"The number of the docker errors",
[],
DOCKER_ERROR_MEASURE,
aggregation_module.CountAggregation())... | code_fim | medium | {
"lang": "python",
"repo": "GoogleCloudPlatform/cloud-opensource-python",
"path": "/compatibility_server/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: helq/pytropos path: /tests/inputs/lists-tuples/outputs/10-list-test-store.py
from pytropos.internals.values.builtin_values import *
from pytropos.internals.values.python_values import PythonValue as PV
<|fim_suffix|>store = {
'_': PV.top(),
'c': PV.top(),
'b': PV.top(),
'a': PV.t... | code_fim | easy | {
"lang": "python",
"repo": "helq/pytropos",
"path": "/tests/inputs/lists-tuples/outputs/10-list-test-store.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>store = {
'_': PV.top(),
'c': PV.top(),
'b': PV.top(),
'a': PV.top(),
}<|fim_prefix|># repo: helq/pytropos path: /tests/inputs/lists-tuples/outputs/10-list-test-store.py
from pytropos.internals.values.builtin_values import *
from pytropos.internals.values.python_values import PythonValue ... | code_fim | easy | {
"lang": "python",
"repo": "helq/pytropos",
"path": "/tests/inputs/lists-tuples/outputs/10-list-test-store.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sampling_rate = 1 / pq.s
spiketrains = [neo.SpikeTrain([1, 5, 9, 11, 13, 20] * pq.s,
t_stop=21*pq.s),
neo.SpikeTrain([1, 4, 7, 12, 16, 18] * pq.s,
t_stop=21*pq.s)]
correct_annotatio... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/elephant",
"path": "/elephant/test/test_spike_train_synchrony.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NeuralEnsemble/elephant path: /elephant/test/test_spike_train_synchrony.py
ue)
self.assertEqual(synchrony, max(trace.synchrony))
self.assertEqual(len(trace.contrast), len(trace.active_spiketrains))
self.assertEqual(len(trace.active_spiketrains), len(trace.synchrony))
... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/elephant",
"path": "/elephant/test/test_spike_train_synchrony.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> spiketrains = [neo.SpikeTrain([1, 5, 9, 11, 13, 20] * pq.s,
t_stop=21*pq.s),
neo.SpikeTrain([1, 4, 7, 12, 16, 18] * pq.s,
t_stop=21*pq.s)]
correct_annotations = np.array([[2, 2, 1, 3, 3, 1],... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/elephant",
"path": "/elephant/test/test_spike_train_synchrony.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> model, num_epochs, train_loader,
valid_loader, test_loader, optimizer,
device, logging_interval=50,
best_model_save_path=None,
scheduler=None,
skip_train_acc=False,
scheduler_on='valid_acc'):
start_time = time.time()
minibatch_loss_list, tra... | code_fim | hard | {
"lang": "python",
"repo": "ashishpatel26/deeplearning-models",
"path": "/pytorch_ipynb/helper_train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return log_dict
def train_classifier_simple_v2(
model, num_epochs, train_loader,
valid_loader, test_loader, optimizer,
device, logging_interval=50,
best_model_save_path=None,
scheduler=None,
skip_train_acc=False,
scheduler_on='valid_acc'):
... | code_fim | hard | {
"lang": "python",
"repo": "ashishpatel26/deeplearning-models",
"path": "/pytorch_ipynb/helper_train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ashishpatel26/deeplearning-models path: /pytorch_ipynb/helper_train.py
from helper_evaluate import compute_accuracy
from helper_evaluate import compute_epoch_loss
import time
import torch
import torch.nn.functional as F
from collections import OrderedDict
import json
import subprocess
import sy... | code_fim | hard | {
"lang": "python",
"repo": "ashishpatel26/deeplearning-models",
"path": "/pytorch_ipynb/helper_train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> clf_ecg = pickle.load(open('/home/a/stress_classifier/classifier_for_ecg.p','rb'))
predicted = clf_ecg.predict_proba(fm)
df = pd.DataFrame(index = np.arange(0, len(data['timestamp'].values)), columns=['user', 'timestamp', 'stress_probability'])
user = data['user'].values[0]
for c in r... | code_fim | medium | {
"lang": "python",
"repo": "aungkonazim/CerebralCortex-Kernel_archived",
"path": "/cerebralcortex/algorithms/stress_prediction/stress_prediction.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aungkonazim/CerebralCortex-Kernel_archived path: /cerebralcortex/algorithms/stress_prediction/stress_prediction.py
# Copyright (c) 2017, MD2K Center of Excellence
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided t... | code_fim | hard | {
"lang": "python",
"repo": "aungkonazim/CerebralCortex-Kernel_archived",
"path": "/cerebralcortex/algorithms/stress_prediction/stress_prediction.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if os.path.exists('HIRES_history2b.csv'):
os.remove('HIRES_history2b.csv')
with open('HIRES_history2b.csv', 'w') as OFO:
for line in lines:
OFO.write('{}\n'.format(line.encode('utf-8').decode()))
if __name__ == '__main__':
# main()
fix_csv()<|fim_prefi... | code_fim | hard | {
"lang": "python",
"repo": "joshwalawender/KeckUtilities",
"path": "/HIRES-history/instrument_history.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joshwalawender/KeckUtilities path: /HIRES-history/instrument_history.py
from __future__ import division, print_function
## Import General Tools
import sys
import os
from astropy.table import Table, Column
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rcParams['font.size'] = 24
... | code_fim | hard | {
"lang": "python",
"repo": "joshwalawender/KeckUtilities",
"path": "/HIRES-history/instrument_history.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
with open('HIRES_history2.csv', 'r') as FO:
contents = FO.read()
lines = contents.split('\n')
if os.path.exists('HIRES_history2b.csv'):
os.remove('HIRES_history2b.csv')
with open('HIRES_history2b.csv', 'w') as OFO:
for line in lines:
OFO.write('{}\n'.f... | code_fim | hard | {
"lang": "python",
"repo": "joshwalawender/KeckUtilities",
"path": "/HIRES-history/instrument_history.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pyccel/pyccel path: /tests/epyccel/test_arrays_multiple_assignments.py
# pylint: disable=missing-function-docstring, missing-module-docstring
import os
import sys
import warnings
import pytest
from pyccel.epyccel import epyccel
from pyccel.decorators import stack_array
from pyccel.errors.errors ... | code_fim | hard | {
"lang": "python",
"repo": "pyccel/pyccel",
"path": "/tests/epyccel/test_arrays_multiple_assignments.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@stack_array('x')
def f():
import numpy as np
for i in range(3):
x = np.ones(i, dtype=int)
return x.sum()
# Initialize singleton that stores Pyccel errors
errors = Errors()
# epyccel should raise an Exception
with pytest.raises(PyccelSemanticE... | code_fim | hard | {
"lang": "python",
"repo": "pyccel/pyccel",
"path": "/tests/epyccel/test_arrays_multiple_assignments.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def Finalize(self):
super().Finalize()
self._CalculateVolumes()
def _CalculateVolumes(self):
spheres_mp = self.model.GetModelPart('SpheresPart')
fluid_mp = self.model.GetModelPart('FluidModelPart')
# Adding up DEM particles' volume and making sure it is no... | code_fim | hard | {
"lang": "python",
"repo": "KratosMultiphysics/Kratos",
"path": "/applications/SwimmingDEMApplication/tests/tests_python_scripts/backward_coupling_scripts/backward_coupling_test_analysis.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KratosMultiphysics/Kratos path: /applications/SwimmingDEMApplication/tests/tests_python_scripts/backward_coupling_scripts/backward_coupling_test_analysis.py
import KratosMultiphysics as Kratos
from KratosMultiphysics import Parameters
import KratosMultiphysics.SwimmingDEMApplication.swimming_DEM_... | code_fim | hard | {
"lang": "python",
"repo": "KratosMultiphysics/Kratos",
"path": "/applications/SwimmingDEMApplication/tests/tests_python_scripts/backward_coupling_scripts/backward_coupling_test_analysis.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: savander10/AdviseMe path: /adviseme-database/Build/create.py
from subprocess import call
<|fim_suffix|>call(["node", "DatabaseBuildFiles/create_db.js"])
call(["node", "DatabaseBuildFiles/insert_student.js"])
call(["node", "DatabaseBuildFiles/insert_appointment.js"])
call(["python3", "Database... | code_fim | easy | {
"lang": "python",
"repo": "savander10/AdviseMe",
"path": "/adviseme-database/Build/create.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>call(["node", "DatabaseBuildFiles/create_db.js"])
call(["node", "DatabaseBuildFiles/insert_student.js"])
call(["node", "DatabaseBuildFiles/insert_appointment.js"])
call(["python3", "DatabaseBuildFiles/insert.py"])<|fim_prefix|># repo: savander10/AdviseMe path: /adviseme-database/Build/create.py
from s... | code_fim | easy | {
"lang": "python",
"repo": "savander10/AdviseMe",
"path": "/adviseme-database/Build/create.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # sub-method to generate all permutations
generate(list(S), 0, len(S) - 1)
# sort the list of permutations generated
result.sort()
return result
# Complexity Analysis
# Time Complexity: O(N * N!), where N is the length of input string.
# Space Complexity: O(N) wh... | code_fim | hard | {
"lang": "python",
"repo": "htrahddis-hub/DSA-Together-HacktoberFest",
"path": "/strings/Easy/permutations_of_a_string.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: htrahddis-hub/DSA-Together-HacktoberFest path: /strings/Easy/permutations_of_a_string.py
# Link : https://practice.geeksforgeeks.org/problems/permutations-of-a-given-string2041/1
# Approach
# To generate permutations of a string, we start with one particular index and try to swap
# this index wi... | code_fim | hard | {
"lang": "python",
"repo": "htrahddis-hub/DSA-Together-HacktoberFest",
"path": "/strings/Easy/permutations_of_a_string.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print "Pull from remote repo"
repo.remotes.origin.pull()
# TODO: Add checking that git stash apply worked ok
if stashed:
git.stash("apply")
if migration:
os.system(
"python {0} --mode=test db upgrade -d {1}".format(
MANAGE_COLLECTOR, DB_MIGR... | code_fim | hard | {
"lang": "python",
"repo": "fuel-infra/puppet-manifests",
"path": "/modules/fuel_stats/files/github-poller.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # TODO: Add checking that git stash apply worked ok
if stashed:
git.stash("apply")
if migration:
os.system(
"python {0} --mode=test db upgrade -d {1}".format(
MANAGE_COLLECTOR, DB_MIGRATION
)
)
os.system("sudo service uwsgi re... | code_fim | medium | {
"lang": "python",
"repo": "fuel-infra/puppet-manifests",
"path": "/modules/fuel_stats/files/github-poller.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fuel-infra/puppet-manifests path: /modules/fuel_stats/files/github-poller.py
#!/usr/bin/python
from git import *
import re
import os
REPO_LOCAL = os.environ.get("REPO_LOCAL", "")
if re.match("^~", REPO_LOCAL):
REPO_LOCAL = os.path.expanduser(REPO_LOCAL)
REPO_LOCAL = os.path.abspath(REPO_LOC... | code_fim | hard | {
"lang": "python",
"repo": "fuel-infra/puppet-manifests",
"path": "/modules/fuel_stats/files/github-poller.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: futursolo/hiyori path: /hiyori/connection.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2021 Kaede Hoshikawa
#
# 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 ... | code_fim | hard | {
"lang": "python",
"repo": "futursolo/hiyori",
"path": "/hiyori/connection.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self._idle_timer is not None:
self._idle_timer.cancel()
self._idle_timer = None
async def get_ready(self) -> None:
self._cancel_idle_timeout()
if self.closing():
raise RuntimeError("This connection is closing.")
if (
... | code_fim | hard | {
"lang": "python",
"repo": "futursolo/hiyori",
"path": "/hiyori/connection.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> field_names = Parameter._get_field_names(csvreader.fieldnames, accepted_field_names)
if field_names['param_name'] is None:
warn('No param name column was found, could not load parameter')
return param_dict
if field_names['mechanism'] is ... | code_fim | hard | {
"lang": "python",
"repo": "MaheshJethalia/BioCRNPyler",
"path": "/biocrnpyler/parameter.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.name = name.strip()
self.param_type = param_type.strip()
self.comment = comment.strip()
# Set the value of the parameter
if debug:
print("%s [%s] = %s" % (self.name, self.param_type, value))
if param_type.strip() == 'Numeric':
s... | code_fim | hard | {
"lang": "python",
"repo": "MaheshJethalia/BioCRNPyler",
"path": "/biocrnpyler/parameter.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MaheshJethalia/BioCRNPyler path: /biocrnpyler/parameter.py
# parameter.py - parameter processing
# RMM, 19 Aug 2018
#
# This file contains the Parameter class that is used for representing
# parameters, as well as utility functions for manipulating
# parameters.
#
# Copyright (c) 2018, Build-A-Ce... | code_fim | hard | {
"lang": "python",
"repo": "MaheshJethalia/BioCRNPyler",
"path": "/biocrnpyler/parameter.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: webclinic017/investtrack path: /investors/migrations/0068_auto_20200626_1124.py
# Generated by Django 3.0.7 on 2020-06-26 03:24
from django.db import migrations, models
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='tradestrategy',
name='appl... | code_fim | medium | {
"lang": "python",
"repo": "webclinic017/investtrack",
"path": "/investors/migrations/0068_auto_20200626_1124.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('investors', '0067_auto_20200625_2224'),
]
operations = [
migrations.AlterField(
model_name='tradestrategy',
name='applied_period',
field=models.CharField(blank=True, choices=[('30', '30分钟'), ('D', '日线'), ('15', '15分钟'), ('... | code_fim | medium | {
"lang": "python",
"repo": "webclinic017/investtrack",
"path": "/investors/migrations/0068_auto_20200626_1124.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='BigTen',
fields=[
('name', models.CharField(db_index=True, max_length=45, primary_key=True, serialize=False, unique=True)),
('created', models.DateTimeField(auto_now_add=True)),
... | code_fim | hard | {
"lang": "python",
"repo": "5h3rr1ll/Goodbuy",
"path": "/goodbuyDatabase/migrations/0002_bigten.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 5h3rr1ll/Goodbuy path: /goodbuyDatabase/migrations/0002_bigten.py
# Generated by Django 3.0.1 on 2020-02-20 09:58
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
('goodbuyDatabase', '0001_initial'),
]
operations = [
migrations.CreateModel(
... | code_fim | hard | {
"lang": "python",
"repo": "5h3rr1ll/Goodbuy",
"path": "/goodbuyDatabase/migrations/0002_bigten.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lensvol/pypiece path: /pypiece/pypiece.py
# coding: utf-8
import click
import os
import subprocess
class VenvNotFoundError(Exception):
pass
class PipNotFoundError(Exception):
pass
def fatal(msg, **kwargs):
txt = msg.format(**kwargs)
click.echo(click.style(txt, fg="red"))
... | code_fim | hard | {
"lang": "python",
"repo": "lensvol/pypiece",
"path": "/pypiece/pypiece.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with click.progressbar(lines,
label="Processing packages",
bar_template="%(label)s [%(bar)s] %(info)s",
item_show_func=show_item,
show_eta=False,
... | code_fim | hard | {
"lang": "python",
"repo": "lensvol/pypiece",
"path": "/pypiece/pypiece.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: linneudm/sysnut path: /sysnut/core/views.py
# -*- coding: utf-8 -*-
from django.shortcuts import render
from django.contrib.auth import login
#from sysnut.settings import *
# Página inicial
def index(request):
return render(request, 'index.html')
def instructions(request):
return render(req... | code_fim | medium | {
"lang": "python",
"repo": "linneudm/sysnut",
"path": "/sysnut/core/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def page_not_found(request):
response = render_to_response('404.html', {},
context_instance=RequestContext(request))
response.status_code = 404
return response<|fim_prefix|># repo: linneudm/sysnut path: /sysnut/core/views.py
# -*- coding: utf-8 -*-
from dja... | code_fim | hard | {
"lang": "python",
"repo": "linneudm/sysnut",
"path": "/sysnut/core/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gslmota/Programs-PYTHON path: /Exercícios/Mundo 3/Projeto/projeto.py
from lib.interface import *
from lib.arquivo import *
from time import sleep
arquivo = 'projeto.txt'
if not arqExiste(arquivo):
criarArq(arquivo)
cabecalho('Sistema Ar<|fim_suffix|>lif resposta == 3:
cabecalho('Sain... | code_fim | hard | {
"lang": "python",
"repo": "gslmota/Programs-PYTHON",
"path": "/Exercícios/Mundo 3/Projeto/projeto.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>2:
cabecalho('Novo Cadastro')
nome = str(input('Digite o nome: '))
idade = leiaInt('Digite a idade: ')
cadastrar(arquivo, nome, idade)
elif resposta == 3:
cabecalho('Saindo do Sistema!')
break
else:
print('\033[31m ERRO: Por favor digite uma ... | code_fim | medium | {
"lang": "python",
"repo": "gslmota/Programs-PYTHON",
"path": "/Exercícios/Mundo 3/Projeto/projeto.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class DjopConfig(AppConfig):
""" Application configuration for DJango Object Permission """
name = 'djop'<|fim_prefix|># repo: blenq/djop path: /djop/apps.py
""" Application configuration for DJango Object Permission """
<|fim_middle|>from django.apps import AppConfig
| code_fim | easy | {
"lang": "python",
"repo": "blenq/djop",
"path": "/djop/apps.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: blenq/djop path: /djop/apps.py
""" Application configuration for DJango Object Permission """
<|fim_suffix|>class DjopConfig(AppConfig):
""" Application configuration for DJango Object Permission """
name = 'djop'<|fim_middle|>from django.apps import AppConfig
| code_fim | easy | {
"lang": "python",
"repo": "blenq/djop",
"path": "/djop/apps.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rodluger/paper path: /src/figures/infer_sigma.py
# ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.13.0
# kernelspec:
# display_name: Python 3 (i... | code_fim | hard | {
"lang": "python",
"repo": "rodluger/paper",
"path": "/src/figures/infer_sigma.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>init = {
"log_sigma": 0.5 * np.log(np.median(sample_variance)),
"log_k": np.log(np.sqrt(sample_variance)),
}
guide = numpyro.infer.autoguide.AutoNormal(
model, init_loc_fn=numpyro.infer.init_to_value(values=init)
)
optimizer = numpyro.optim.Adam(step_size=1e-3)
svi = numpyro.infer.SVI(
mod... | code_fim | hard | {
"lang": "python",
"repo": "rodluger/paper",
"path": "/src/figures/infer_sigma.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>jax_config.update("jax_enable_x64", True)
def model(num_transit, statistic=None):
log_sigma = numpyro.sample("log_sigma", dist.Normal(0.0, 10.0))
with numpyro.plate("targets", len(num_transit)):
log_k = numpyro.sample("log_k", dist.Normal(0.0, 10.0))
lam = num_transit * 0.5 * jn... | code_fim | hard | {
"lang": "python",
"repo": "rodluger/paper",
"path": "/src/figures/infer_sigma.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Declare fundamental placeholder and weights to use for model"""
self.inputs = tf.placeholder(tf.int32, shape=(None,self.n_input), name='inputs')
self.inputs_mask = tf.placeholder(tf.float32, shape=(None, self.n_input), name='inputs_mask')
self.targets = tf.place... | code_fim | hard | {
"lang": "python",
"repo": "Koomook/semantic-classifier",
"path": "/classifier/model.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Koomook/semantic-classifier path: /classifier/model.py
import tensorflow as tf
from tensorflow.python.layers.core import dense
import numpy as np
from .utils import *
class AttentionMLP(object):
"""This Model is based on self-attention frame work.
as called transformer : https://arxiv.or... | code_fim | hard | {
"lang": "python",
"repo": "Koomook/semantic-classifier",
"path": "/classifier/model.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: texas/tx_elevators path: /tx_elevators/management/commands/loadgeo.py
from __future__ import division
from __future__ import unicode_literals
import csv
import logging
<|fim_suffix|> logger = logging.getLogger(__name__)
with open(path) as csvfile:
for total, row in e... | code_fim | hard | {
"lang": "python",
"repo": "texas/tx_elevators",
"path": "/tx_elevators/management/commands/loadgeo.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> from tx_elevators.models import Building
logger = logging.getLogger(__name__)
with open(path) as csvfile:
for total, row in enumerate(csvfile, start=1):
pass
csvfile.seek(0)
reader = csv.reader(csvfile)
for row in tq... | code_fim | hard | {
"lang": "python",
"repo": "texas/tx_elevators",
"path": "/tx_elevators/management/commands/loadgeo.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DarkFisk/django-exchange path: /exchange/adapters/xe_exchangerates.py
from __future__ import absolute_import
import logging
import datetime
import bs4
from django.core.mail import mail_admins
from exchange.models import Currency, ExchangeRate
from django.conf import settings
from exchange.adap... | code_fim | hard | {
"lang": "python",
"repo": "DarkFisk/django-exchange",
"path": "/exchange/adapters/xe_exchangerates.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for source in Currency.objects.filter(code__in=self.base_curr).all():
exchange_rates = self.get_exchangerates_by_day(source.code, date)
if exchange_rates:
exchange_rates.pop(source.code)
for code, rate in exchange_rates.iteritems():
... | code_fim | hard | {
"lang": "python",
"repo": "DarkFisk/django-exchange",
"path": "/exchange/adapters/xe_exchangerates.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> tokens = {
'commentsandwhitespace': [
(r'\s+', Text),
(r'<!--', Comment),
(r'//.*?\n', Comment.Single),
(r'/\*.*?\*/', Comment.Multiline)
],
'slashstartsregex': [
include('commentsandwhitespace'),
(r'/(\\.|... | code_fim | hard | {
"lang": "python",
"repo": "wongjiahau/Pineapple",
"path": "/pineapple.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.