text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: hzmangel/wp2hugo path: /hugo_printer.py
import yaml
import os
import logging
import html2text
class HugoPrinter:
def __init__(self, *args, **kwargs):
accept_attributes = ["meta", "categories", "tags", "posts", "drafts", "basedir"]
for attr in accept_attributes:
... | code_fim | hard | {
"lang": "python",
"repo": "hzmangel/wp2hugo",
"path": "/hugo_printer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> actual = _moving_average(list(data.items()), chunk_size=2)
expected = {'2020-01-03': 15,
'2020-01-04': 30}
self.assertListEqual(actual, list(expected.items()))
def test_zero_and_negative_values(self):
"""
Tests to make sure that negative va... | code_fim | hard | {
"lang": "python",
"repo": "IanCostello/tools",
"path": "/covid19-dashboard/TestMovingAverage.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IanCostello/tools path: /covid19-dashboard/TestMovingAverage.py
# Copyright 2020 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
#
# https://www.apache.o... | code_fim | hard | {
"lang": "python",
"repo": "IanCostello/tools",
"path": "/covid19-dashboard/TestMovingAverage.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Tests to make sure that negative values and zeros
don't cause any issues. They are valid inputs.
"""
data = {'2020-01-02': -10,
'2020-01-03': 0,
'2020-01-04': 0}
actual = _moving_average(list(data.items()), chunk_size=2)
... | code_fim | hard | {
"lang": "python",
"repo": "IanCostello/tools",
"path": "/covid19-dashboard/TestMovingAverage.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>'
try:
return eval(erg)
except ValueError:
return 'Invalid calculation'<|fim_prefix|># repo: dskbrd/dascord-py path: /lib_calc.py
def calc(erg: str):
if erg.islower() or erg<|fim_middle|>.isupper():
return 'Invalid calculation | code_fim | easy | {
"lang": "python",
"repo": "dskbrd/dascord-py",
"path": "/lib_calc.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>ValueError:
return 'Invalid calculation'<|fim_prefix|># repo: dskbrd/dascord-py path: /lib_calc.py
def calc(erg: str):
if erg.islower() or erg.isupper():
return 'Invalid calculation<|fim_middle|>'
try:
return eval(erg)
except | code_fim | easy | {
"lang": "python",
"repo": "dskbrd/dascord-py",
"path": "/lib_calc.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dskbrd/dascord-py path: /lib_calc.py
def calc(erg: str):
if erg.islower() or erg.isupper():
return 'Invalid calculation<|fim_suffix|>ValueError:
return 'Invalid calculation'<|fim_middle|>'
try:
return eval(erg)
except | code_fim | easy | {
"lang": "python",
"repo": "dskbrd/dascord-py",
"path": "/lib_calc.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> stu1 = {
'id': 1,
'name': 'ping'
}
print('stu1 =', stu1)
msg = msgpack.packb(stu1)
print(type(msg))
print(len(msg))
print(msg)
stu2 = msgpack.unpackb(msg, use_list=False, encoding='utf-8')
print('stu2 =', stu2)
def main():
test1()
if __name__ =... | code_fim | easy | {
"lang": "python",
"repo": "MDGSF/PythonPractice",
"path": "/msgpackdemo/1/msgpackdemo.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MDGSF/PythonPractice path: /msgpackdemo/1/msgpackdemo.py
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
import msgpack
def test1():
stu1 = {
'id': 1,
'name': 'ping'
}
print('stu1 =', stu1)
<|fim_suffix|> stu2 = msgpack.unpackb(msg, use_list=False, encoding='utf-8... | code_fim | medium | {
"lang": "python",
"repo": "MDGSF/PythonPractice",
"path": "/msgpackdemo/1/msgpackdemo.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> test1()
if __name__ == "__main__":
main()<|fim_prefix|># repo: MDGSF/PythonPractice path: /msgpackdemo/1/msgpackdemo.py
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
<|fim_middle|>import msgpack
def test1():
stu1 = {
'id': 1,
'name': 'ping'
}
print('stu1 =', stu1)... | code_fim | hard | {
"lang": "python",
"repo": "MDGSF/PythonPractice",
"path": "/msgpackdemo/1/msgpackdemo.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pmnyc/Data_Engineering_Collections path: /django_flask_samples/tango_with_django-master/made_with_twd_project/showcase/models.py
from django.db import models
from django.contrib.auth.models import User
from django.conf import settings
class Category(models.Model):
name = models.CharField(max... | code_fim | hard | {
"lang": "python",
"repo": "pmnyc/Data_Engineering_Collections",
"path": "/django_flask_samples/tango_with_django-master/made_with_twd_project/showcase/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = models.CharField(max_length=64)
tagline = models.CharField(max_length=128)
description = models.CharField(max_length=512)
year = models.IntegerField(default=2014, choices=YEAR_CHOICES)
url = models.URLField()
live = models.BooleanField(default=True)
github_url = models.U... | code_fim | hard | {
"lang": "python",
"repo": "pmnyc/Data_Engineering_Collections",
"path": "/django_flask_samples/tango_with_django-master/made_with_twd_project/showcase/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># read serial
for d in datasets:
p = paths[1]
df = pandas.read_csv(d+p+'.csv', header=None)
df = df.min()
read_time = df[0]
csr_time = df[1]
mem_time = df[2]
exec_time = df[3]
stats['serial'].append(df[2])
stats['cilk'].append(df[3])
... | code_fim | hard | {
"lang": "python",
"repo": "KonstantinosChatziantoniou/GraphTrianglesCounting",
"path": "/scripts/res.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KonstantinosChatziantoniou/GraphTrianglesCounting path: /scripts/res.py
import pandas
import matplotlib.pyplot as plt
datasets = ['auto.mtx', 'delaunay_n22.mtx', 'great-britain_osm.mtx']
paths = ['cuda', 'serial_cilk']
stats = {}
stats['cuda'] = []
stats['serial'] = []
stats['cilk'] = []
stat... | code_fim | hard | {
"lang": "python",
"repo": "KonstantinosChatziantoniou/GraphTrianglesCounting",
"path": "/scripts/res.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># read cuda
for d in datasets:
p = paths[0]
df = pandas.read_csv(d+p+'.csv', header=None)
df = df.min()
read_time = df[0]
csr_time = df[1]
mem_time = df[2]
exec_time = df[3]
stats['cuda'].append(df[2] + df[3])
# read serial
for d in dataset... | code_fim | hard | {
"lang": "python",
"repo": "KonstantinosChatziantoniou/GraphTrianglesCounting",
"path": "/scripts/res.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhmsg/dms path: /Web/msg_web.py
#! /usr/bin/env python
# coding: utf-8
import sys
sys.path.append("..")
from flask import Flask
from flask_login import current_user
from Web import *
from Web.redis_session import RedisSessionInterface
__author__ = 'zhouheng'
def create_app():
msg_web = Fla... | code_fim | hard | {
"lang": "python",
"repo": "zhmsg/dms",
"path": "/Web/msg_web.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> env = msg_web.jinja_env
env.globals["current_env"] = current_env
# env.globals["role_value"] = control.role_value
env.globals["menu_url"] = dms_url_prefix + "/portal/"
env.globals["short_link_url"] = short_link_prefix
env.filters['unix_timestamp'] = unix_timestamp
env.filters['... | code_fim | hard | {
"lang": "python",
"repo": "zhmsg/dms",
"path": "/Web/msg_web.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wsp-sag/gtfs-router path: /src/gtfs_router/utils/misc.py
import logging
logger = logging.getLogger()
def log_stop_information(partridge_feed, stop_id):
stops = partridge_feed.stops
stop = stops[stops["stop_id"] == stop_id]
if stop.empty:
logger.waring("No stop_id found for:... | code_fim | hard | {
"lang": "python",
"repo": "wsp-sag/gtfs-router",
"path": "/src/gtfs_router/utils/misc.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i, p in enumerate(coords):
proj_dist = line.project(Point(p))
if proj_dist == distance:
return [LineString(coords[: i + 1]), LineString(coords[i:])]
if proj_dist > distance:
cp = line.interpolate(distance)
return [
LineStr... | code_fim | hard | {
"lang": "python",
"repo": "wsp-sag/gtfs-router",
"path": "/src/gtfs_router/utils/misc.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uonafya/mfl_api path: /common/migrations/0020_auto_20221205_0904.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.27 on 2022-12-05 09:04
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = ... | code_fim | medium | {
"lang": "python",
"repo": "uonafya/mfl_api",
"path": "/common/migrations/0020_auto_20221205_0904.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('common', '0019_auto_20191021_1227'),
]
operations = [
migrations.AlterField(
model_name='apiauthentication',
name='client_secret',
field=models.CharField(default=b'', max_length=255),
),
migrations.AlterFi... | code_fim | medium | {
"lang": "python",
"repo": "uonafya/mfl_api",
"path": "/common/migrations/0020_auto_20221205_0904.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.fname = filename
super(FileOutputProcessor, self).__init__(var_list, sample_interval)
def pre_run(self):
self.h5file = h5py.File(self.fname, 'w')
self.h5file.create_dataset('metadata',(),'i')
self.h5file['metadata'].attrs['start_time'] = self.start_tim... | code_fim | hard | {
"lang": "python",
"repo": "mkturkcan/neurodriver",
"path": "/neurokernel/LPU/OutputProcessors/FileOutputProcessor.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mkturkcan/neurodriver path: /neurokernel/LPU/OutputProcessors/FileOutputProcessor.py
import numpy as np
import h5py
from datetime import datetime
from neurokernel.LPU.OutputProcessors.BaseOutputProcessor import BaseOutputProcessor
class FileOutputProcessor(BaseOutputProcessor):
def __init__(s... | code_fim | hard | {
"lang": "python",
"repo": "mkturkcan/neurodriver",
"path": "/neurokernel/LPU/OutputProcessors/FileOutputProcessor.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> for var, d in self.variables.items():
self.h5file[var+'/data'].resize((self.h5file[var+'/data'].shape[0]+1,
len(d['uids'])))
self.h5file[var+'/data'][-1,:] = d['output'].reshape((1,-1))
def post_run(self):
... | code_fim | hard | {
"lang": "python",
"repo": "mkturkcan/neurodriver",
"path": "/neurokernel/LPU/OutputProcessors/FileOutputProcessor.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.topic_vectors = nn.Parameter(topic_vectors)
self.n_topics = n_topics
def forward(self, doc_weights):
"""Embed a batch of documents.
Arguments:
doc_weights: A float tensor of shape [batch_size, n_topics],
document distributions (logits)... | code_fim | hard | {
"lang": "python",
"repo": "Gwangfilm/Comparative-analysis-of-user-preference-factors-in-parks-using-big-data",
"path": "/lda2vec-pytorch-master/utils/lda2vec_loss.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Arguments:
pivot_words: A long tensor of shape [batch_size].
target_words: A long tensor of shape [batch_size, window_size].
Windows around pivot words.
doc_vectors: A float tensor of shape [batch_size, embedding_dim].
... | code_fim | hard | {
"lang": "python",
"repo": "Gwangfilm/Comparative-analysis-of-user-preference-factors-in-parks-using-big-data",
"path": "/lda2vec-pytorch-master/utils/lda2vec_loss.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Gwangfilm/Comparative-analysis-of-user-preference-factors-in-parks-using-big-data path: /lda2vec-pytorch-master/utils/lda2vec_loss.py
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from scipy.stats import ortho_g... | code_fim | hard | {
"lang": "python",
"repo": "Gwangfilm/Comparative-analysis-of-user-preference-factors-in-parks-using-big-data",
"path": "/lda2vec-pytorch-master/utils/lda2vec_loss.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paltrickontpb/Adafruit-IO-Control-Center path: /Code_uploader.py
from Adafruit_IO import Client
KEY = 'ADAFRUIT-IO-KEY'
<|fim_suffix|>code = raw_input('Enter the Code : ')
print("Input Code : "+str(code))
pyclient.send('data', code)
print("Code updated in cloud")<|fim_middle|>pyclient = Client... | code_fim | easy | {
"lang": "python",
"repo": "paltrickontpb/Adafruit-IO-Control-Center",
"path": "/Code_uploader.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>pyclient.send('data', code)
print("Code updated in cloud")<|fim_prefix|># repo: paltrickontpb/Adafruit-IO-Control-Center path: /Code_uploader.py
from Adafruit_IO import Client
KEY = 'ADAFRUIT-IO-KEY'
pyclient = Client(KEY)
<|fim_middle|>code = raw_input('Enter the Code : ')
print("Input Code : "+str(c... | code_fim | medium | {
"lang": "python",
"repo": "paltrickontpb/Adafruit-IO-Control-Center",
"path": "/Code_uploader.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Coding-Squad/givabit path: /src/givabit/ui_tests/login_test.py
import time
from givabit.ui_tests import ui_test_utils
from givabit.ui_tests.page_objects.login_page import LoginPage
from givabit.backend.user import User
from selenium import webdriver
from google.appengine.ext import testbed
c... | code_fim | medium | {
"lang": "python",
"repo": "Coding-Squad/givabit",
"path": "/src/givabit/ui_tests/login_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> sessions = self.session_repo.get_sessions(email=user.email)
session_ids = set([session.id for session in sessions])
self.assertSetEqual(session_ids, set([session_id]))
def get_session_id(self):
return self.get_cookie('sessionid')['value']<|fim_prefix|># repo: Coding-Sq... | code_fim | hard | {
"lang": "python",
"repo": "Coding-Squad/givabit",
"path": "/src/givabit/ui_tests/login_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EDRN/eke.biomarker path: /eke/biomarker/upgrades.py
# encoding: utf-8
# Copyright 2011 California Institute of Technology. ALL RIGHTS
# RESERVED. U.S. Government Sponsorship acknowledged.
from eke.biomarker import PROFILE_ID
from eke.biomarker.interfaces import IBiomarkerFolder
from Products.CMF... | code_fim | medium | {
"lang": "python",
"repo": "EDRN/eke.biomarker",
"path": "/eke/biomarker/upgrades.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''Set up faceted navigation and add disclaimers on all Biomarker Folders.'''
portal = _getPortal(setupTool)
request = portal.REQUEST
catalog = getToolByName(portal, 'portal_catalog')
results = [i.getObject() for i in catalog(object_provides=IBiomarkerFolder.__identifier__)]
if len... | code_fim | hard | {
"lang": "python",
"repo": "EDRN/eke.biomarker",
"path": "/eke/biomarker/upgrades.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_output_schema(self):
# Output of deid should use standard schema (DC-120)
o_dataset_ref = self.client.dataset(self.o_dataset)
for table_name in CDM_TABLE_NAMES:
table_ref = o_dataset_ref.table(table_name)
table = self.client.get_table(table_ref)... | code_fim | hard | {
"lang": "python",
"repo": "berneskaracay/curation",
"path": "/data_steward/deid/test/deid_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: berneskaracay/curation path: /data_steward/deid/test/deid_test.py
"""
This unit test requires a valid configuration at `deid/test_config.json` and the environment variables below.
I_DATASET: Input dataset_id.
O_DATASET: Output dataset_id. Note that tests currently assume that this has been popula... | code_fim | hard | {
"lang": "python",
"repo": "berneskaracay/curation",
"path": "/data_steward/deid/test/deid_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Table fields should have names and types from standard schema
# Note: We do not check nullability as deid may entail relaxing constraint
actual_items = [(item.name, item.field_type.lower()) for item in table.schema]
actual_schema = dict(actual_items)
... | code_fim | hard | {
"lang": "python",
"repo": "berneskaracay/curation",
"path": "/data_steward/deid/test/deid_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Adding converter for dateobject to schema.
AlbumSchema.CONVERTER_MAP[DateObject] = DateConverter
def test_validate_df(spark_session):
input_data = [
{"title": "valid_1", "release_date": date(2020, 1, 10)},
{"title": "valid_2", "release_date": date(2020, 1, 11)},
{"title": "... | code_fim | hard | {
"lang": "python",
"repo": "hammond756/marshmallow-pyspark",
"path": "/tests/test_custom_field.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_validate_df(spark_session):
input_data = [
{"title": "valid_1", "release_date": date(2020, 1, 10)},
{"title": "valid_2", "release_date": date(2020, 1, 11)},
{"title": "valid_3", "release_date": date(2020, 1, 11)},
{"title": "valid_4", "release_date": date(2020,... | code_fim | hard | {
"lang": "python",
"repo": "hammond756/marshmallow-pyspark",
"path": "/tests/test_custom_field.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hammond756/marshmallow-pyspark path: /tests/test_custom_field.py
"""
Test custom field
"""
from datetime import date
from marshmallow import fields, ValidationError
from marshmallow_pyspark import Schema
from marshmallow_pyspark.converters import DateConverter
class DateObject(fields.Fie... | code_fim | hard | {
"lang": "python",
"repo": "hammond756/marshmallow-pyspark",
"path": "/tests/test_custom_field.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return np.sqrt(w1*w2).content<|fim_prefix|># repo: lgray/dazsle-hbb-recipes path: /dazsle_hbb_recipes/kfactors/top_kfactors.py
""" kfactors / reweighting for ttbar """
from fnal_column_analysis_tools.util import numpy as np
from fnal_column_analysis_tools.util import awkward
def calculateTopKFactor... | code_fim | medium | {
"lang": "python",
"repo": "lgray/dazsle-hbb-recipes",
"path": "/dazsle_hbb_recipes/kfactors/top_kfactors.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def calculateTopKFactor(top_pts,antitop_pts):
w1 = np.exp(0.0615 - 0.0005*top_pts);
w2 = np.exp(0.0615 - 0.0005*antitop_pts);
return np.sqrt(w1*w2).content<|fim_prefix|># repo: lgray/dazsle-hbb-recipes path: /dazsle_hbb_recipes/kfactors/top_kfactors.py
""" kfactors / reweighting for ttbar ""... | code_fim | medium | {
"lang": "python",
"repo": "lgray/dazsle-hbb-recipes",
"path": "/dazsle_hbb_recipes/kfactors/top_kfactors.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lgray/dazsle-hbb-recipes path: /dazsle_hbb_recipes/kfactors/top_kfactors.py
""" kfactors / reweighting for ttbar """
<|fim_suffix|> w1 = np.exp(0.0615 - 0.0005*top_pts);
w2 = np.exp(0.0615 - 0.0005*antitop_pts);
return np.sqrt(w1*w2).content<|fim_middle|>from fnal_column_analysis_too... | code_fim | medium | {
"lang": "python",
"repo": "lgray/dazsle-hbb-recipes",
"path": "/dazsle_hbb_recipes/kfactors/top_kfactors.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> module_dir = os.path.join(
proj_path,
const.DIR_NAME_FILES,
const.DIR_NAME_FILES_MODULES,
module_name,
const.DIR_NAME_GLUECODE,
)
# clean old generated src
file.remove_dir(os.path.join(module_dir, "generated-src"))
file.remove_dir(os.path.join(m... | code_fim | hard | {
"lang": "python",
"repo": "rockonedege/ezored",
"path": "/files/core/gluecode.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rockonedege/ezored path: /files/core/gluecode.py
"""Module: Glue code"""
import os
from files.core import const
from files.core import file
from files.core import log
from files.core import runner
from files.core import util
# ------------------------------------------------------------------... | code_fim | hard | {
"lang": "python",
"repo": "rockonedege/ezored",
"path": "/files/core/gluecode.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CalPolyDnD/DnDCapstone path: /dmsite/backend/dmsite/tests/classes.py
class TestTable:
def __init__(self):
self.file = []
self.data = []
def add_data(self, data):
self.file = data
def query(self, IndexName=None, KeyConditionExpression=None):
dict = {}
... | code_fim | hard | {
"lang": "python",
"repo": "CalPolyDnD/DnDCapstone",
"path": "/dmsite/backend/dmsite/tests/classes.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(0, len(self.data)):
if self.data[i]['Item']['name'] == Key['name']:
return self.data[i]
return {}
def response(self, key):
for i in range(0, len(self.data)):
item = self.data[i]['Item']
if 'name' in key and 'na... | code_fim | hard | {
"lang": "python",
"repo": "CalPolyDnD/DnDCapstone",
"path": "/dmsite/backend/dmsite/tests/classes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def update_item(self, Key = None,
UpdateExpression=None,
ExpressionAttributeNames=None,
ExpressionAttributeValues = None):
for i in range(0, len(self.data)):
if 'name' in self.data[i]['Item'] and self.dat... | code_fim | hard | {
"lang": "python",
"repo": "CalPolyDnD/DnDCapstone",
"path": "/dmsite/backend/dmsite/tests/classes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>.models.deletion.CASCADE, to='projectsTestsQuestions.Project')),
],
),
migrations.CreateModel(
name='testsApply',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
... | code_fim | hard | {
"lang": "python",
"repo": "ATOM27/TFF",
"path": "/School/apply/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ATOM27/TFF path: /School/apply/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.10 on 2017-05-13 13:33
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial... | code_fim | hard | {
"lang": "python",
"repo": "ATOM27/TFF",
"path": "/School/apply/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _conv_dw(inp, oup, stride=1, padding=0, expand_ratio=1):
"""
Introduction
------------
采用MobileNet的结构减少参数，压缩模型
Parameters
----------
inp: 输入通道数
oup: 输出通道数
stride: 卷积步长
padding: 卷积padding大小
expand_ratio: 维度扩充比例
Returns:
-------... | code_fim | hard | {
"lang": "python",
"repo": "aloyschen/SSD-Pytorch",
"path": "/models/SSDLite.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aloyschen/SSD-Pytorch path: /models/SSDLite.py
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.Modules import L2Norm
class SSDLite(nn.Module):
def __init__(self, BaseModel, extras, head, feature_layer, num_class):
"""
Introduction
------... | code_fim | hard | {
"lang": "python",
"repo": "aloyschen/SSD-Pytorch",
"path": "/models/SSDLite.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def add_extras(base, feature_layer, mbox, num_classes):
"""
Introduction
------------
将基础模型特征基础上提取多尺度特征，再使用卷积进行box坐标和类别的回归
Parameters
----------
base: 基础模型
feature_layer: 特征层参数
mbox: 每层特征预测box的数量
num_classes: 数据集类别数量
"""
extra_layers = []... | code_fim | hard | {
"lang": "python",
"repo": "aloyschen/SSD-Pytorch",
"path": "/models/SSDLite.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HassamSheikh/VIP_Protection_Envs path: /policy/interactive.py
#!/usr/bin/env python
import os,sys
sys.path.insert(1, os.path.join(sys.path[0], '..'))
import argparse
import pandas as pd
import gc
from collections import defaultdict
from multiagent.environment import MultiAgentEnv
from multiagent.... | code_fim | hard | {
"lang": "python",
"repo": "HassamSheikh/VIP_Protection_Envs",
"path": "/policy/interactive.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
# parse arguments
parser = argparse.ArgumentParser(description=None, allow_abbrev=False)
parser.add_argument("--data-path", default='./data/trajectory_data.csv', help="Path for saving trajectories")
parser.add_argument("--scenario", type=str, default="simple", he... | code_fim | hard | {
"lang": "python",
"repo": "HassamSheikh/VIP_Protection_Envs",
"path": "/policy/interactive.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for idx, p_vel in enumerate(agent.state.p_vel):
key_name = agent.name + "_p_vel_" + axis[idx]
episode_data[key_name].append(p_vel)
for idx, agent in enumerate(world.policy_agents):
episode_data[agent.name + "_actions"].append([agent.action.u])
episode_d... | code_fim | hard | {
"lang": "python",
"repo": "HassamSheikh/VIP_Protection_Envs",
"path": "/policy/interactive.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0xPrateek/ML-Algorithms path: /Algorithms/Linear Regression/LinearRegression.py
############################################################################################################################
'''
Linear Regression implementation in Python 3
By - Prateek ... | code_fim | hard | {
"lang": "python",
"repo": "0xPrateek/ML-Algorithms",
"path": "/Algorithms/Linear Regression/LinearRegression.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
data = pd.read_csv('../../Datasets/linearRegression_Dataset.txt', header = None) #Loading dataset file and storing in 'data' variable.
x = data.iloc[:,0] #sepratly storing the coloumn 0 in x.
y = data.iloc[:,1] #sepratly storing the coloumn 1 ... | code_fim | hard | {
"lang": "python",
"repo": "0xPrateek/ML-Algorithms",
"path": "/Algorithms/Linear Regression/LinearRegression.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
data = pd.read_csv('../../Datasets/linearRegression_Dataset.txt', header = None) #Loading dataset file and storing in 'data' variable.
x = data.iloc[:,0] #sepratly storing the coloumn 0 in x.
y = data.iloc[:,1] #sepratly storing the coloumn 1 i... | code_fim | hard | {
"lang": "python",
"repo": "0xPrateek/ML-Algorithms",
"path": "/Algorithms/Linear Regression/LinearRegression.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Spookz0r/Temporal_Insanity path: /Martin/exp2.py
from __future__ import print_function
import numpy as np
#np.random.seed(1337) # for reproducibility
from keras.datasets import mnist
from keras.layers.core import TimeDistributedDense, Activation, Dropout
from keras.models import Sequential
f... | code_fim | medium | {
"lang": "python",
"repo": "Spookz0r/Temporal_Insanity",
"path": "/Martin/exp2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>nr = np.random.randint(0,9999)
print("Sample nr ", nr)
pic = copy.deepcopy(X_test[nr])
img = X_test[nr]
img = img.reshape(1,1,28,28)
img = img.astype('float32')
img /= 255
model = load_model("muh_model.h5")
start = time.time()
x = model.predict(img, batch_size = 1, verbose = 1)
end = time.time()
prin... | code_fim | medium | {
"lang": "python",
"repo": "Spookz0r/Temporal_Insanity",
"path": "/Martin/exp2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
model = load_model("muh_model.h5")
start = time.time()
x = model.predict(img, batch_size = 1, verbose = 1)
end = time.time()
print("Prediction is: ", x[0][0])
print("Answer is: ", y_test[nr])
print("It took: ", end-start, " seconds")
plt.imshow(pic)
plt.show()<|fim_prefix|># repo: Spookz0r/Temporal_Insan... | code_fim | hard | {
"lang": "python",
"repo": "Spookz0r/Temporal_Insanity",
"path": "/Martin/exp2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Nico769/HPCA-Project-Code path: /core/algos/monte_carlo_pi.py
"""Estimate pi using a parallel Monte Carlo simulation.
Implements an MPI version of a parallel Monte Carlo simulation for estimating pi.
MPI's default channel is used.
Usage:
python monte_carlo_pi.py [total_nu... | code_fim | hard | {
"lang": "python",
"repo": "Nico769/HPCA-Project-Code",
"path": "/core/algos/monte_carlo_pi.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
points_fallen_inside_circle = 0
# draw a pair (x,y) from an uniform distribution
# between 0 and 1 for each trial
# NOTE: each child process has its own seed
# since np.random.seed() hasn't been invoked
# This is good for randomness but terrible for
# reproducibi... | code_fim | hard | {
"lang": "python",
"repo": "Nico769/HPCA-Project-Code",
"path": "/core/algos/monte_carlo_pi.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># for trail in map_dict:
# if "view" in map_dict[trail]:
# method_path = map_dict[trail]["model"]
# __get_method(method_path=method_path)<|fim_prefix|># repo: conrad-strughold/GamestonkTerminal path: /tests/openbb_terminal/test_sdk.py
# pylint: disable=import-outside-t... | code_fim | hard | {
"lang": "python",
"repo": "conrad-strughold/GamestonkTerminal",
"path": "/tests/openbb_terminal/test_sdk.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: conrad-strughold/GamestonkTerminal path: /tests/openbb_terminal/test_sdk.py
# pylint: disable=import-outside-toplevel
# def test_openbb():
# """Test the openbb function"""
# from openbb_terminal.sdk import openbb
# assert "stocks" in dir(openbb)
# assert "economy" in dir(openbb... | code_fim | hard | {
"lang": "python",
"repo": "conrad-strughold/GamestonkTerminal",
"path": "/tests/openbb_terminal/test_sdk.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># def __get_method(method_path: str) -> Callable:
# module_path, function_name = method_path.rsplit(".", 1)
# module = import_module(module_path)
# method = getattr(module, function_name)
# return method
# def test_load_models():
# map_dict = trail_map.map_dict
# for trail in m... | code_fim | medium | {
"lang": "python",
"repo": "conrad-strughold/GamestonkTerminal",
"path": "/tests/openbb_terminal/test_sdk.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SeyZ/baboon path: /baboon/baboon/plugins/git/monitor_git.py
import os
import sys
import re
import fnmatch
if sys.version_info < (2, 7):
# Python < 2.7 doesn't have the cmp_to_key function.
from baboon.common.utils import cmp_to_key
else:
from functools import cmp_to_key
from baboon.... | code_fim | hard | {
"lang": "python",
"repo": "SeyZ/baboon",
"path": "/baboon/baboon/plugins/git/monitor_git.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # First, check if the modified file is the gitignore file. If it's the
# case, update include/exclude paths lists.
if rel_path == self.gitignore_path:
self._populate_gitignore_items()
# Return True only if rel_path matches an exclude pattern AND does NOT
... | code_fim | hard | {
"lang": "python",
"repo": "SeyZ/baboon",
"path": "/baboon/baboon/plugins/git/monitor_git.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juancprzs/semantic-embeddings path: /learn_classifier.py
import numpy as np
import argparse
import pickle
import os
import shutil
from collections import OrderedDict
import keras
from keras import backend as K
import utils
from datasets import get_data_generator
def transform_inputs(X, y, n... | code_fim | hard | {
"lang": "python",
"repo": "juancprzs/semantic-embeddings",
"path": "/learn_classifier.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Configure environment
K.set_session(K.tf.Session(config = K.tf.ConfigProto(gpu_options = { 'allow_growth' : True })))
# Load dataset
if args.class_list is not None:
with open(args.class_list) as class_file:
class_list = list(OrderedDict((l.strip().split()[0], None) f... | code_fim | hard | {
"lang": "python",
"repo": "juancprzs/semantic-embeddings",
"path": "/learn_classifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if args.max_decay > 0:
decay = (1.0/args.max_decay - 1) / ((data_generator.num_train // args.batch_size) * (args.epochs if args.epochs else num_epochs))
else:
decay = 0.0
par_model.compile(optimizer = keras.optimizers.SGD(lr=args.sgd_lr, decay=decay, momentum=0.9, nesterov=args... | code_fim | hard | {
"lang": "python",
"repo": "juancprzs/semantic-embeddings",
"path": "/learn_classifier.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: starlingx/distcloud path: /distributedcloud/dcorch/engine/initial_sync_manager.py
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licens... | code_fim | hard | {
"lang": "python",
"repo": "starlingx/distcloud",
"path": "/distributedcloud/dcorch/engine/initial_sync_manager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Indicate that initial sync has started
self.gsm.update_subcloud_state(
subcloud_name,
initial_sync_state=consts.INITIAL_SYNC_STATE_IN_PROGRESS)
# Initial sync. It's synchronous so that identity
# get synced before fernet token keys are synced. Thi... | code_fim | hard | {
"lang": "python",
"repo": "starlingx/distcloud",
"path": "/distributedcloud/dcorch/engine/initial_sync_manager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def normalize_num_clients_and_default_num_clients(
num_clients: Optional[int], default_num_clients: int) -> int:
if num_clients is not None:
warnings.warn('num_clients is deprecated; please use default_num_clients '
'instead.')
py_typecheck.check_type(num_clients, int)
... | code_fim | hard | {
"lang": "python",
"repo": "Saiprasad16/federated",
"path": "/tensorflow_federated/python/core/impl/executors/executor_stacks.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Saiprasad16/federated path: /tensorflow_federated/python/core/impl/executors/executor_stacks.py
l:
return 1
return dtype.size * 8
def _calculate_bit_size(self, history: sizing_executor.SizeAndDTypes) -> int:
"""Takes a list of 2 element lists and calculates the number of bits rep... | code_fim | hard | {
"lang": "python",
"repo": "Saiprasad16/federated",
"path": "/tensorflow_federated/python/core/impl/executors/executor_stacks.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> num_clients: Optional[int], default_num_clients: int) -> int:
if num_clients is not None:
warnings.warn('num_clients is deprecated; please use default_num_clients '
'instead.')
py_typecheck.check_type(num_clients, int)
return num_clients
return default_num_clients
d... | code_fim | hard | {
"lang": "python",
"repo": "Saiprasad16/federated",
"path": "/tensorflow_federated/python/core/impl/executors/executor_stacks.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.rect.y = y
# Sets change x
def setChangeX(self, x):
self.changex = x
# Sets change y
def setChangeY(self, y):
self.changey = y<|fim_prefix|># repo: Programming-2/Lil-Sheds-Get-Good-In path: /src/Entity.py
import pygame
# Basic structure for entities
class ... | code_fim | hard | {
"lang": "python",
"repo": "Programming-2/Lil-Sheds-Get-Good-In",
"path": "/src/Entity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Programming-2/Lil-Sheds-Get-Good-In path: /src/Entity.py
import pygame
# Basic structure for entities
class Entity(pygame.sprite.Sprite):
def __init__(self, startx, starty, xchange, ychange, image):
super().__init__()
self.xchange = xchange
self.ychange = ychange
... | code_fim | medium | {
"lang": "python",
"repo": "Programming-2/Lil-Sheds-Get-Good-In",
"path": "/src/Entity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: modelica-3rdparty/BuildingSystems path: /BuildingSystems/Resources/Scripts/JModelica/Buildings/Constructions/Examples/Window.py
# paths and info
import os, sys
homeDir = os.environ['HOMEPATH']
jmodDir = os.environ['JMODELICA_HOME']
workDir = "Desktop" # has to be adapted by the user !!!
moLiDir =... | code_fim | medium | {
"lang": "python",
"repo": "modelica-3rdparty/BuildingSystems",
"path": "/BuildingSystems/Resources/Scripts/JModelica/Buildings/Constructions/Examples/Window.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># plotting of the results
import pylab as P
fig = P.figure(1)
P.clf()
# Temperatures
y1 = res['ambience.TAirRef']
y2 = res['window.toSurfacePort_1.heatPort.T']
y3 = res['window.heatTransfer.T']
y4 = res['window.toSurfacePort_2.heatPort.T']
t = res['time']
P.subplot(3,1,1)
P.plot(t, y1, t, y2, t, y3, t, y4... | code_fim | hard | {
"lang": "python",
"repo": "modelica-3rdparty/BuildingSystems",
"path": "/BuildingSystems/Resources/Scripts/JModelica/Buildings/Constructions/Examples/Window.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openshift/openshift-tools path: /scripts/monitoring/cron-send-disk-metrics.py
#!/usr/bin/env python
'''
Command to send dynamic disk information to Zagg
'''
# vim: expandtab:tabstop=4:shiftwidth=4
#
# Copyright 2015 Red Hat Inc.
#
# Licensed under the Apache License, Version 2.0 (the "Licen... | code_fim | hard | {
"lang": "python",
"repo": "openshift/openshift-tools",
"path": "/scripts/monitoring/cron-send-disk-metrics.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> # do TPS checks; use disk.dev.total
filtered_disk_totals = clean_up_metric_dict(pcp_metrics_divided[pcp_disk_dev_metrics[0]],
pcp_disk_dev_metrics[0] + '.')
# Add dynamic items
metric_sender.add_dynamic_metric(discovery_key_disk, item_protot... | code_fim | hard | {
"lang": "python",
"repo": "openshift/openshift-tools",
"path": "/scripts/monitoring/cron-send-disk-metrics.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
cli.archive_esnet_snmp with out-of-bounds
"""
tokiotest.TEMP_FILE.close()
# Calculate new bounds that are a subset of the actual data that will be returned
orig_start_dt = datetime.datetime.strptime(tokiotest.SAMPLE_ESNET_SNMP_START,
... | code_fim | hard | {
"lang": "python",
"repo": "NERSC/pytokio",
"path": "/tests/test_cli_archive_esnet_snmp.py",
"mode": "spm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_suffix|> """retain some properties of each dataset in an hdf5 file"""
if isinstance(obj_data, h5py.Dataset):
summary['shapes'][obj_name] = obj_data.shape
# note that this will break if the hdf5 file contains non-numeric datasets
summary['sums'][obj_name] = obj_da... | code_fim | hard | {
"lang": "python",
"repo": "NERSC/pytokio",
"path": "/tests/test_cli_archive_esnet_snmp.py",
"mode": "spm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NERSC/pytokio path: /tests/test_cli_archive_esnet_snmp.py
#!/usr/bin/env python
"""Test the archive_esnet_snmp.py tool
"""
import os
import datetime
import warnings
import nose
import h5py
import tokiotest
import tokio.connectors.hdf5
import tokio.cli.archive_esnet_snmp
def generate_tts(output_... | code_fim | hard | {
"lang": "python",
"repo": "NERSC/pytokio",
"path": "/tests/test_cli_archive_esnet_snmp.py",
"mode": "psm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Interbotix/interbotix_ros_manipulators path: /interbotix_ros_xsarms/interbotix_xsarm_perception/scripts/pick_place.py
import time
from interbotix_xs_modules.arm import InterbotixManipulatorXS
from interbotix_perception_modules.armtag import InterbotixArmTagInterface
from interbotix_perception_mod... | code_fim | hard | {
"lang": "python",
"repo": "Interbotix/interbotix_ros_manipulators",
"path": "/interbotix_ros_xsarms/interbotix_xsarm_perception/scripts/pick_place.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # pick up all the objects and drop them in a virtual basket in front of the robot
for cluster in clusters:
x, y, z = cluster["position"]
bot.arm.set_ee_pose_components(x=x, y=y, z=z+0.05, pitch=0.5)
bot.arm.set_ee_pose_components(x=x, y=y, z=z, pitch=0.5)
bot.grippe... | code_fim | hard | {
"lang": "python",
"repo": "Interbotix/interbotix_ros_manipulators",
"path": "/interbotix_ros_xsarms/interbotix_xsarm_perception/scripts/pick_place.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> max_array_length = 0
for index in range(len(arrays)):
length = len(arrays[index])
if length > max_array_length:
max_array_length = length
#write headers
l1 = l2 = ''
for index in range(len(headers)):
header = '**' + escape_string(headers[index]) + '**'
l1 += '|'
l1 += ... | code_fim | hard | {
"lang": "python",
"repo": "gerald1248/kanban-builder",
"path": "/src/main/python/kanban_builder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gerald1248/kanban-builder path: /src/main/python/kanban_builder.py
"""
Creates Markdown Kanban boards from Yaml input
"""
import os
import sys
import yaml
import re
import string
USAGE = """
Usage: python [relative/path/to/]kanban_builder.py [input.yml]
Arguments:
--rows=N: display no more tha... | code_fim | hard | {
"lang": "python",
"repo": "gerald1248/kanban-builder",
"path": "/src/main/python/kanban_builder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> headers = []
arrays = []
max_string_lengths = []
for column in obj:
key = column.keys()[0]
headers.append(key) #headers
arr = column[key]
arrays.append(arr) #arrays
max_string_length = len(key) + 4; #leave room for bold markers
for s in arr:
length = len(s)
if ... | code_fim | hard | {
"lang": "python",
"repo": "gerald1248/kanban-builder",
"path": "/src/main/python/kanban_builder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: odero/django-pesapal path: /django_pesapal/urls.py
# -*- coding: utf-8 -*-
from django.conf.urls import url
<|fim_suffix|>urlpatterns = [
url(
r"^transaction/completed/$",
views.TransactionCompletedView.as_view(),
name="transaction_completed",
),
url(
... | code_fim | easy | {
"lang": "python",
"repo": "odero/django-pesapal",
"path": "/django_pesapal/urls.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = [
url(
r"^transaction/completed/$",
views.TransactionCompletedView.as_view(),
name="transaction_completed",
),
url(
r"^transaction/status/$",
views.TransactionStatusView.as_view(),
name="transaction_status",
),
url(r"^transa... | code_fim | easy | {
"lang": "python",
"repo": "odero/django-pesapal",
"path": "/django_pesapal/urls.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GuillaumeCisco/substra-tools path: /tests/test_metrics.py
import json
import sys
from substratools import metrics
from substratools.workspace import Workspace
from substratools.utils import import_module
import pytest
@pytest.fixture()
def write_pred_file():
workspace = Workspace()
da... | code_fim | medium | {
"lang": "python",
"repo": "GuillaumeCisco/substra-tools",
"path": "/tests/test_metrics.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> DummyMetrics()
def test_score():
m = DummyMetrics()
wp = metrics.MetricsWrapper(m)
s = wp.score()
assert s == 15
def test_execute(load_metrics_module):
s = metrics.execute()
assert s == 15
@pytest.mark.parametrize("dry_run_mode,expected_score", [
(False, 15),
(Tru... | code_fim | hard | {
"lang": "python",
"repo": "GuillaumeCisco/substra-tools",
"path": "/tests/test_metrics.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return sum(y_true) + sum(y_pred)
"""
import_module('metrics', code)
yield
del sys.modules['metrics']
@pytest.fixture(autouse=True)
def setup(valid_opener, write_pred_file):
pass
class DummyMetrics(metrics.Metrics):
def score(self, y_true, y_pred):
return sum(y_true)... | code_fim | medium | {
"lang": "python",
"repo": "GuillaumeCisco/substra-tools",
"path": "/tests/test_metrics.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> while b != 0:
carry = a & b
a = a ^ b
b = carry << 1
return a
print(no_plus_sign(1, 4))<|fim_prefix|># repo: samirsaravia/Python_101 path: /BrushingUp/challenge-1.0/1.5.1.py
"""
Write a function to add two positive integers together without using the
'+' operator.
https:... | code_fim | easy | {
"lang": "python",
"repo": "samirsaravia/Python_101",
"path": "/BrushingUp/challenge-1.0/1.5.1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samirsaravia/Python_101 path: /BrushingUp/challenge-1.0/1.5.1.py
"""
Write a function to add two positive integers together without using the
'+' operator.
https://en.wikipedia.org/wiki/Bitwise_operation
Explanation: https://stackoverflow.com/questions/17342042/why-this-code-for-additionusing-bit... | code_fim | easy | {
"lang": "python",
"repo": "samirsaravia/Python_101",
"path": "/BrushingUp/challenge-1.0/1.5.1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def port_is_locked(port):
try:
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(("127.0.0.1", port))
s.close()
return False
except socket.error as e:
if e.errno == errno.EADDRINUSE:
return True
def busy_ports(start, end):
busy =... | code_fim | hard | {
"lang": "python",
"repo": "kapily/portlock",
"path": "/portlock/portlock.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kapily/portlock path: /portlock/portlock.py
import socket
import sys
import logging
import errno
import time
socket_singleton = None
def ensure_singleton(port, log_error=True):
"""After calling this method, you can be assured no other script will be running with this port.
Otherwise, s... | code_fim | hard | {
"lang": "python",
"repo": "kapily/portlock",
"path": "/portlock/portlock.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ykanggit/web2py-appliances path: /RadioScheduleLogs/controllers/default.py
# -*- coding: utf-8 -*-
#########################################################################
## This is a samples controller
## - index is the default action of any application
## - user is required for authenticati... | code_fim | hard | {
"lang": "python",
"repo": "ykanggit/web2py-appliances",
"path": "/RadioScheduleLogs/controllers/default.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
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