text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: SamyMe/django-markdown-newsletter path: /build/django-markdown-newsletter/build/lib.linux-i686-2.7/django-markdown-newsletter/models.py
from django.db import models
class Subscribe(models.Model):
email = models.EmailField(unique=True)
newsletter = models.CharField(max_length=20,default='newsle... | code_fim | medium | {
"lang": "python",
"repo": "SamyMe/django-markdown-newsletter",
"path": "/build/django-markdown-newsletter/build/lib.linux-i686-2.7/django-markdown-newsletter/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Theosakamg/PiCar_ROS path: /picar_bringup/scripts/twist2ackermann.py
#!/usr/bin/env python3
import rospy, math
from geometry_msgs.msg import Twist
from ackermann_msgs.msg import AckermannDriveStamped
from ackermann_msgs.msg import AckermannDrive
from dynamic_reconfigure.server import Server as D... | code_fim | hard | {
"lang": "python",
"repo": "Theosakamg/PiCar_ROS",
"path": "/picar_bringup/scripts/twist2ackermann.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def convert_trans_rot_vel_to_steering_angle(self, speed, omega):
steering_angle = 0
if not (omega == 0 or speed == 0):
radius = speed / omega
steering_angle = math.atan(self.wheelbase / radius)
return steering_angle
def cmd_callback(self, data):
... | code_fim | hard | {
"lang": "python",
"repo": "Theosakamg/PiCar_ROS",
"path": "/picar_bringup/scripts/twist2ackermann.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TorchSpatiotemporal/tsl path: /tests/test_example_forecasting.py
import os
import shutil
import numpy as np
import pytest
import torch
from hydra import compose, initialize
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from tsl.data... | code_fim | hard | {
"lang": "python",
"repo": "TorchSpatiotemporal/tsl",
"path": "/tests/test_example_forecasting.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dm = SpatioTemporalDataModule(
dataset=torch_dataset,
scalers=transform,
splitter=dataset.get_splitter(**cfg.dataset.splitting),
batch_size=cfg.batch_size)
dm.setup()
########################################
# predictor #
####... | code_fim | hard | {
"lang": "python",
"repo": "TorchSpatiotemporal/tsl",
"path": "/tests/test_example_forecasting.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> checkpoint_callback = ModelCheckpoint(
dirpath=log_dir,
save_top_k=1,
monitor='val_mae',
mode='min',
)
trainer = Trainer(
max_epochs=cfg.epochs,
default_root_dir=log_dir,
logger=None,
accelerator='gpu' if torch.cuda.is_available(... | code_fim | hard | {
"lang": "python",
"repo": "TorchSpatiotemporal/tsl",
"path": "/tests/test_example_forecasting.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liupei101/libsurv path: /libsurv/ciboost/_ci_core.py
"""
L2 term of objective function in BecCox.
CI approximated by convex function F and its gradients.
Convex function F = [-(y_hat[i] - y_hat[j] - _GAMMA)] ** 2
"""
import numpy as np
_GAMMA = 0.01
def ci_loss(preds, dtrain):
"""
Com... | code_fim | hard | {
"lang": "python",
"repo": "liupei101/libsurv",
"path": "/libsurv/ciboost/_ci_core.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # firstly, compute gradients of numerator(\alpha) and denominator(\beta) in L2
for k in np.arange(n):
## gradients of denominator (\beta)
# For set s1 (i.e. \omega 1 in the paper)
# s1 = (k, i): E_k = 1 and T_k < T_i
s1 = E[k] * np.sum(T > T[k])
# For set s2... | code_fim | hard | {
"lang": "python",
"repo": "liupei101/libsurv",
"path": "/libsurv/ciboost/_ci_core.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return "ci_loss", loss
def _ci_grads(preds, dtrain):
"""
Gradient computation of custom objective function.
Parameters
----------
preds: numpy.array
An array with shape of (N, ), where N = #data.
dtrain: xgboost.DMatrix
Training data with type of `xgboost.... | code_fim | hard | {
"lang": "python",
"repo": "liupei101/libsurv",
"path": "/libsurv/ciboost/_ci_core.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.name = "ALLEGES"
self.definitions = allege
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.basic = ['allege']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_alleges.py
#calss header
class _ALLEGES():
<|fim_middle|> def __in... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_alleges.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_alleges.py
#calss header
class _ALLEGES():
<|fim_suffix|> self.basic = ['allege']<|fim_middle|> def __init__(self,):
self.name = "ALLEGES"
self.definitions = allege
self.parents = []
self.childen = []
self.properties = []
self.js... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_alleges.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.basic = ['allege']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_alleges.py
#calss header
class _ALLEGES():
def __init__(self,):
<|fim_middle|> self.name = "ALLEGES"
self.definitions = allege
self.parents = []
self.childen = []
self.properties = []
self.js... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_alleges.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bbarney213/PyLendingClub path: /tests/wrapper/wrapper_test.py
import requests
from pylendingclub.wrapper.session import LendingClubSession
if __name__ == '__main__':
import sys
from os.path import dirname, abspath, join
package_path = join(dirname(dirname(dirname(abspath(__file__)))... | code_fim | hard | {
"lang": "python",
"repo": "bbarney213/PyLendingClub",
"path": "/tests/wrapper/wrapper_test.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
Tests Missing:
Session:
create_portfolio
- No way to delete portfolio, so portfolios would become croweded over time
submit_orders
submit_order
AccountSummary:
- Extends the account_summary response. Allows a persisted summary that refreshes
... | code_fim | hard | {
"lang": "python",
"repo": "bbarney213/PyLendingClub",
"path": "/tests/wrapper/wrapper_test.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> source = """
flow "send_slack_message" {
task "slack_api_call" "this" {
client = {
token = "ANY"
}
channel = "#random"
text = "hello world"
}
task "file_write" "output" {
filename = "/dev/stdout"
content = tojson(eval(str(task.sla... | code_fim | hard | {
"lang": "python",
"repo": "soasme/runflow",
"path": "/tests/community/test_slack.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: soasme/runflow path: /tests/community/test_slack.py
import pytest
from slack_sdk.errors import SlackApiError
from runflow import runflow
pytest.importorskip('slack_sdk')
def test_slack_api_call_invalid_token(mocker, capsys):
async def chat_postMessage(**kwargs):
raise SlackApiErr... | code_fim | hard | {
"lang": "python",
"repo": "soasme/runflow",
"path": "/tests/community/test_slack.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> runflow(source="""
flow "send_slack_message" {
task "slack_api_call" "this" {
client = {
token = "ANY"
some_random_argument = 1
}
api_method = "chat.postMessage"
channel = "#random"
text = "hello world"
}
task "file_write" "ou... | code_fim | hard | {
"lang": "python",
"repo": "soasme/runflow",
"path": "/tests/community/test_slack.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sichkar-valentyn/Collatz_conjecture path: /Collatz_conjecture.py
# File: Collatz_conjecture.py
# Description: Implementing Collatz conjecture by recursive function
# Environment: PyCharm and Anaconda environment
#
# MIT License
# Copyright (c) 2018 Valentyn N Sichkar
# github.com/sichkar-valentyn... | code_fim | hard | {
"lang": "python",
"repo": "sichkar-valentyn/Collatz_conjecture",
"path": "/Collatz_conjecture.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(number, end=' ') # Printing the number
# Checking if the current calculated number is still more then 1
if number > 1:
# Checking if the current number is even
if number % 2 == 0:
# Calling the recursive function and printing the integer division of current n... | code_fim | medium | {
"lang": "python",
"repo": "sichkar-valentyn/Collatz_conjecture",
"path": "/Collatz_conjecture.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Recursive function for calculating Collatz' sequence of numbers
def Collatz(number):
print(number, end=' ') # Printing the number
# Checking if the current calculated number is still more then 1
if number > 1:
# Checking if the current number is even
if number % 2 == 0:
... | code_fim | medium | {
"lang": "python",
"repo": "sichkar-valentyn/Collatz_conjecture",
"path": "/Collatz_conjecture.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ErinClaudio/log-my-exercise path: /app/services/strava.py
import os
from datetime import datetime
import requests
from authlib.integrations.requests_client import OAuth2Session
from flask import current_app
from app import db
from app.main import routes
from app.models import StravaAthlete, Act... | code_fim | hard | {
"lang": "python",
"repo": "ErinClaudio/log-my-exercise",
"path": "/app/services/strava.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def tell_strava_deauth(strava_athlete):
"""
sends a command to strava informing them of the deauthorisation of this user
:param strava_athlete: the strava athlete
:type strava_athlete:
:return: True if Strava acknowledged success, False otherwise
:rtype: boolean
"""
access_... | code_fim | hard | {
"lang": "python",
"repo": "ErinClaudio/log-my-exercise",
"path": "/app/services/strava.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ### commands auto generated by Alembic - please adjust! ###
op.add_column('parent', sa.Column('about_me', sa.String(length=300), nullable=True))
op.add_column('parent', sa.Column('last_seen', sa.DateTime(), nullable=True))
# ### end Alembic commands ###
def downgrade():
# ### comma... | code_fim | hard | {
"lang": "python",
"repo": "majidshirazi13666/somasoma-eLearning-app",
"path": "/version1/migrations/versions/b63b46d48623_new_fields_in_parent_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: majidshirazi13666/somasoma-eLearning-app path: /version1/migrations/versions/b63b46d48623_new_fields_in_parent_model.py
"""new fields in parent model
Revision ID: b63b46d48623
Revises: b53db8b2f9b9
Create Date: 2021-04-26 05:14:40.769477
"""
from alembic import op
import sqlalchemy as sa
<|fi... | code_fim | hard | {
"lang": "python",
"repo": "majidshirazi13666/somasoma-eLearning-app",
"path": "/version1/migrations/versions/b63b46d48623_new_fields_in_parent_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ### commands auto generated by Alembic - please adjust! ###
op.drop_column('parent', 'last_seen')
op.drop_column('parent', 'about_me')
# ### end Alembic commands ###<|fim_prefix|># repo: majidshirazi13666/somasoma-eLearning-app path: /version1/migrations/versions/b63b46d48623_new_fields... | code_fim | hard | {
"lang": "python",
"repo": "majidshirazi13666/somasoma-eLearning-app",
"path": "/version1/migrations/versions/b63b46d48623_new_fields_in_parent_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _post_zip_file(config, app_slug, in_file):
boundary = '----------ThIs_Is_tHe_bouNdaRY_$'
body = '\r\n'.join([
'--' + boundary,
'Content-Disposition: form-data; name="archive"; filename="archive.zip"',
'Content-Type: application/zip',
'',
in_file.getvalue... | code_fim | hard | {
"lang": "python",
"repo": "abhimir/clutchclient",
"path": "/clutchclient/commands/upload.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> namespace = APP_PARSER.parse_args()
config = get_config(namespace)
dirname = os.path.abspath(os.path.expanduser(namespace.directory))
app_slug = get_app_slug(namespace)
if not os.path.isdir(dirname):
error_msg = 'Sorry, but %s is not a directory' % (dirname,)
print ... | code_fim | hard | {
"lang": "python",
"repo": "abhimir/clutchclient",
"path": "/clutchclient/commands/upload.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abhimir/clutchclient path: /clutchclient/commands/upload.py
# Copyright 2012 Twitter
#
# 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": "abhimir/clutchclient",
"path": "/clutchclient/commands/upload.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def spec_write_tab_file(scenario_directory, subproblem, stage, spec_project_params):
spec_params_filepath = os.path.join(
scenario_directory,
str(subproblem),
str(stage),
"inputs",
"spec_capacity_period_params.tab",
)
# If spec_capacity_period_params.ta... | code_fim | hard | {
"lang": "python",
"repo": "blue-marble/gridpath",
"path": "/gridpath/project/capacity/capacity_types/common_methods.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: blue-marble/gridpath path: /gridpath/project/capacity/capacity_types/common_methods.py
r the License.
import csv
import os.path
import pandas as pd
from db.common_functions import spin_on_database_lock
from gridpath.project.common_functions import get_column_row_value
def relevant_periods_by_... | code_fim | hard | {
"lang": "python",
"repo": "blue-marble/gridpath",
"path": "/gridpath/project/capacity/capacity_types/common_methods.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Helper function for writing the spec project param inputs to avoid
redundant code in spec_write_tab_file().
"""
for row in spec_project_params:
[
project,
period,
specified_capacity_mw,
hyb_gen_specified_capacity_mw,
... | code_fim | hard | {
"lang": "python",
"repo": "blue-marble/gridpath",
"path": "/gridpath/project/capacity/capacity_types/common_methods.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openwsn-berkeley/coap path: /bin/test_client.py
import os
import sys
here = sys.path[0]
sys.path.insert(0, os.path.join(here,'..'))
import time
import binascii
from coap import coap
from coap import coapOption as o
from coap import coapObjectSecurity as oscore
<|fim_s... | code_fim | hard | {
"lang": "python",
"repo": "openwsn-berkeley/coap",
"path": "/bin/test_client.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>try:
# retrieve value of 'test' resource
p = c.GET('coap://[{0}]/test'.format(SERVER_IP),
confirmable=True,
options=[objectSecurity])
print('=====')
print(''.join([chr(b) for b in p]))
print('=====')
except Exception as err:
print(err)
# cl... | code_fim | hard | {
"lang": "python",
"repo": "openwsn-berkeley/coap",
"path": "/bin/test_client.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> #check if the ip is already in some port, if on port - delete, add to new port
self.check_time()
dp = self.cache.get(dpid)
if dp is not None:
ip_adr = ip_interface(ip)
record = self.cache[dpid].get(ip_adr)
if record is not None:
... | code_fim | hard | {
"lang": "python",
"repo": "Konstantin-Minachkin/Ryu_SDN_Controller",
"path": "/arp_cache.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Konstantin-Minachkin/Ryu_SDN_Controller path: /arp_cache.py
# -*- coding: utf-8 -*-
import time
from helper_methods import props
from collections import defaultdict
from ipaddress import ip_interface
DEFAULT_DEAD_TIME = 3600 #сколько помнить хост в секундах (dead time)
class ArpCache:... | code_fim | hard | {
"lang": "python",
"repo": "Konstantin-Minachkin/Ryu_SDN_Controller",
"path": "/arp_cache.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_host(self, dp_id, ip):
dp = self.cache.get(dp_id)
record = None
if dp is not None:
record = self.cache[dp_id].get(mac)
return record
def get_all_dps(self, ip):
#возвращает все {dp_id:port}, в которых есть этот ip
dps = {... | code_fim | hard | {
"lang": "python",
"repo": "Konstantin-Minachkin/Ryu_SDN_Controller",
"path": "/arp_cache.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aiqm/torchani path: /tools/generate-unit-test-expect/tripeptide-md.py
import ase
import ase.io
import ase.optimize
import ase.md.velocitydistribution
import ase.md.verlet
import os
from neurochem_calculator import NeuroChem, path
import torchani
import pickle
<|fim_suffix|>ase.md.velocitydistrib... | code_fim | hard | {
"lang": "python",
"repo": "aiqm/torchani",
"path": "/tools/generate-unit-test-expect/tripeptide-md.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ase.md.velocitydistribution.MaxwellBoltzmannDistribution(molecule, temp, force_temp=True)
ase.md.velocitydistribution.Stationary(molecule)
ase.md.velocitydistribution.ZeroRotation(molecule)
print("Initial temperature from velocities %.2f" % molecule.get_temperature())
molecule.set_calculator(torchani.mo... | code_fim | hard | {
"lang": "python",
"repo": "aiqm/torchani",
"path": "/tools/generate-unit-test-expect/tripeptide-md.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from SimTracker.TrackerHitAssociation.tpClusterProducer_cfi import tpClusterProducer
from SimTracker.TrackAssociatorProducers.quickTrackAssociatorByHits_cfi import quickTrackAssociatorByHits
from SimTracker.TrackAssociation.trackTimeValueMapProducer_cfi import trackTimeValueMapProducer
from RecoMTD.Timing... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoVertex/Configuration/python/RecoVertex_phase2_timing_cff.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cms-sw/cmssw path: /RecoVertex/Configuration/python/RecoVertex_phase2_timing_cff.py
import FWCore.ParameterSet.Config as cms
from RecoVertex.Configuration.RecoVertex_cff import unsortedOfflinePrimaryVertices, trackWithVertexRefSelector, trackRefsForJets, sortedPrimaryVertices, offlinePrimaryVerti... | code_fim | hard | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoVertex/Configuration/python/RecoVertex_phase2_timing_cff.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Set Button 動作
def get_user_input():
area = user_input_area.get()
x = user_input_x.get()
y = user_input_y.get()
# 轉換輸入值(str -> float)
new_area = converter.area_proportion(ast.literal_eval(area), area_array[2])
new_x = float(x)
new_y = float(y)
# 建立設定參數
x_coor = area_array... | code_fim | hard | {
"lang": "python",
"repo": "vuncrychen/osu-wacom-linux-gui",
"path": "/owl_gui.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vuncrychen/osu-wacom-linux-gui path: /owl_gui.py
import tkinter as tk
import owl_lib
import converter
import ast
# 視窗設定
root = tk.Tk()
root.title("osu-wacom-linux-gui")
root.geometry("600x400+700+200")
# 實體化 Entry Box
<|fim_suffix|> x_coor = area_array[2] * (float(new_area/100))
y_coor... | code_fim | hard | {
"lang": "python",
"repo": "vuncrychen/osu-wacom-linux-gui",
"path": "/owl_gui.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># 設定
owl_lib.set_area(0 + x_off, 0 + y_off, x_coor + x_off, y_coor + y_off)
owl_lib.no_smoothing()
# 實體化 Set Button
set_button = tk.Button(
root, text="Set",
command=get_user_input
)
# rotate 設定
def rotate_y():
owl_lib.rotate("y")
def rotate_n():
owl_lib.rotate("n")
select... | code_fim | hard | {
"lang": "python",
"repo": "vuncrychen/osu-wacom-linux-gui",
"path": "/owl_gui.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from .troc import troctoken_middleware
from .jwt import jwt_middleware
__all__ = ["troctoken_middleware", "jwt_middleware"]<|fim_prefix|># repo: kiniamogh/navigator-api path: /navigator/auth/middlewares/__init__.py
"""Nav Middleware.
<|fim_middle|>Navigator Authorization Middlewares.
"""
| code_fim | easy | {
"lang": "python",
"repo": "kiniamogh/navigator-api",
"path": "/navigator/auth/middlewares/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = ["troctoken_middleware", "jwt_middleware"]<|fim_prefix|># repo: kiniamogh/navigator-api path: /navigator/auth/middlewares/__init__.py
"""Nav Middleware.
Navigator Authorization Middlewares.
"""
<|fim_middle|>from .troc import troctoken_middleware
from .jwt import jwt_middleware
| code_fim | medium | {
"lang": "python",
"repo": "kiniamogh/navigator-api",
"path": "/navigator/auth/middlewares/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kiniamogh/navigator-api path: /navigator/auth/middlewares/__init__.py
"""Nav Middleware.
<|fim_suffix|>__all__ = ["troctoken_middleware", "jwt_middleware"]<|fim_middle|>Navigator Authorization Middlewares.
"""
from .troc import troctoken_middleware
from .jwt import jwt_middleware
| code_fim | medium | {
"lang": "python",
"repo": "kiniamogh/navigator-api",
"path": "/navigator/auth/middlewares/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # input image dimensions
self.img_rows, self.img_cols, self.img_chns = self.img_rows, self.img_cols, 1
if K.image_dim_ordering() == 'th':
original_img_size = (self.img_chns, self.img_rows, self.img_cols)
input_shape = (1, self.img_rows, self.img_cols)
... | code_fim | hard | {
"lang": "python",
"repo": "WN1695173791/molecules-deprecated",
"path": "/molecules/models/supervised/layer_output/layer_output.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WN1695173791/molecules-deprecated path: /molecules/models/supervised/layer_output/layer_output.py
#%matplotlib inline
from __future__ import print_function
import numpy as np
import gzip
from six.moves import cPickle
import sys
from keras import backend as K
from keras.utils import np_utils... | code_fim | hard | {
"lang": "python",
"repo": "WN1695173791/molecules-deprecated",
"path": "/molecules/models/supervised/layer_output/layer_output.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> arr = np.array([1.86644691e-05, 3.86592014e-03, 1.35335283e-01, 8.00737403e-01,
8.00737403e-01, 1.35335283e-01, 3.86592014e-03, 1.86644691e-05,
1.52299797e-08, 2.10040929e-12, 4.89586526e-17])
assert(np.allclose(w, arr))
assert (np.allclose(w, w2))
return None
def test_cl... | code_fim | hard | {
"lang": "python",
"repo": "msc-acse/acse-9-independent-research-project-dekape",
"path": "/tests/test_siganalysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_dataspec():
dir_path = os.path.abspath(os.path.dirname(__file__))
OBS_PATH = os.path.join(dir_path, "test_data/ucalc_shot_1.sgy")
OBS = tools.load(OBS_PATH, model=False, verbose=1)
OBS.dt = [4] # fix sampling rate and number of samples
OBS.samples = [1501]
dataspec1 ... | code_fim | hard | {
"lang": "python",
"repo": "msc-acse/acse-9-independent-research-project-dekape",
"path": "/tests/test_siganalysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: msc-acse/acse-9-independent-research-project-dekape path: /tests/test_siganalysis.py
#!/usr/bin/env python
# Deborah Pelacani Cruz
# https://github.com/dekape
import context
import fullwaveqc.siganalysis as sig
import os
import fullwaveqc.tools as tools
import copy
import numpy as np
def test_t... | code_fim | hard | {
"lang": "python",
"repo": "msc-acse/acse-9-independent-research-project-dekape",
"path": "/tests/test_siganalysis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: log2timeline/plaso path: /plaso/multi_process/engine.py
# -*- coding: utf-8 -*-
"""The multi-process processing engine."""
import abc
import ctypes
import os
import signal
import sys
import threading
import time
from plaso.engine import engine
from plaso.engine import process_info
from plaso.li... | code_fim | hard | {
"lang": "python",
"repo": "log2timeline/plaso",
"path": "/plaso/multi_process/engine.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Starts the status update thread."""
self._status_update_active = True
self._status_update_thread = threading.Thread(
name='Status update', target=self._StatusUpdateThreadMain)
self._status_update_thread.start()
def _StatusUpdateThreadMain(self):
"""Main function of the st... | code_fim | hard | {
"lang": "python",
"repo": "log2timeline/plaso",
"path": "/plaso/multi_process/engine.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> logger.debug('Stopped monitoring process: {0:s} (PID: {1:d})'.format(
process.name, pid))
def _StopMonitoringProcesses(self):
"""Stops monitoring all processes."""
# We need to make a copy of the list of pids since we are changing
# the dict in the loop.
for pid in list(self... | code_fim | hard | {
"lang": "python",
"repo": "log2timeline/plaso",
"path": "/plaso/multi_process/engine.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _get_sql_create_table(self, table_attr):
"""
Generate create database statement
:param table_attr: table attrs
:return: SQL statement for creating
"""
template = 'CREATE TABLE IF NOT EXISTS "%s" (\n %s );'
columns_pri, columns_ref, columns, c... | code_fim | hard | {
"lang": "python",
"repo": "ggarri/mysql2psql",
"path": "/libs/PsqlParser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ggarri/mysql2psql path: /libs/PsqlParser.py
code, mysql_parser)
output.write(users_sql)
output.close()
def generate_sql_schema(self, schema, schema_name, psql_tables_path):
"""
Generate sql queries from given schema
:param schema: Psql schema
... | code_fim | hard | {
"lang": "python",
"repo": "ggarri/mysql2psql",
"path": "/libs/PsqlParser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> GRANT USAGE ON SCHEMA %s TO %s;
GRANT ALL ON ALL SEQUENCES IN SCHEMA %s TO %s;
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA %s TO %s;
GRANT USAGE ON SCHEMA %s TO %s;
GRANT ALL ON ALL SEQUENCES IN SCHEMA %s TO %s;
GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA ... | code_fim | hard | {
"lang": "python",
"repo": "ggarri/mysql2psql",
"path": "/libs/PsqlParser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: przor3n/kodownik path: /tests/test_result_screen.py
import unittest
# ResultScreenTestCase
# test_if_is
from kivy.uix.button import Button
from kivy.uix.gridlayout import GridLayout
from kodownik.widget.screen.ResultScreen import ResultScreen
class ResultScreenTestCase(unittest.TestCase):
... | code_fim | hard | {
"lang": "python",
"repo": "przor3n/kodownik",
"path": "/tests/test_result_screen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertIsInstance(
self.result_screen.result_buttons.back_button,
Button
)
if __name__ == '__main__':
unittest.main()<|fim_prefix|># repo: przor3n/kodownik path: /tests/test_result_screen.py
import unittest
# ResultScreenTestCase
# test_if_is
from kivy.u... | code_fim | medium | {
"lang": "python",
"repo": "przor3n/kodownik",
"path": "/tests/test_result_screen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
def test_if_is(self):
self.assertTrue(self.result_screen)
def test_if_has_test_results(self):
self.assertTrue(self.result_screen.test_result)
self.assertIsInstance(
self.result_screen.test_result,
GridLayout
)
def test_if_... | code_fim | medium | {
"lang": "python",
"repo": "przor3n/kodownik",
"path": "/tests/test_result_screen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def hide_editor_ui():
from .main_editor import MainEditorWindow
MainEditorWindow.hideWindow()
def is_editor_ui_showing() -> bool:
from .main_editor import MainEditorWindow
return MainEditorWindow.isRaised()
def tear_down_ui():
"""
Hide and delete UI elements and registered ca... | code_fim | medium | {
"lang": "python",
"repo": "bohdon/maya-pulse",
"path": "/src/pulse/scripts/pulse/ui/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def destroy_all_pulse_windows():
"""
Destroy all PulseWindows and their workspace controls.
Intended for development reloading purposes.
"""
from .core import PulseWindow
for cls in PulseWindow.__subclasses__():
cls.destroyWindow()
def destroy_ui_model_instances():
"... | code_fim | hard | {
"lang": "python",
"repo": "bohdon/maya-pulse",
"path": "/src/pulse/scripts/pulse/ui/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bohdon/maya-pulse path: /src/pulse/scripts/pulse/ui/__init__.py
"""
The main package containing all UI and menu functionality.
"""
def toggle_editor_ui():
from .main_editor import MainEditorWindow
MainEditorWindow.toggleWindow()
def show_editor_ui(enable_context_menus=True):
from... | code_fim | hard | {
"lang": "python",
"repo": "bohdon/maya-pulse",
"path": "/src/pulse/scripts/pulse/ui/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def normalise(norm):
def _normalise(v):
# Numba linear algebra operations are only supported on
# contiguous arrays
v = np.ascontiguousarray(v)
return normalise_vector(v, order)
if norm == 'l1':
order = 1
if norm == 'l... | code_fim | hard | {
"lang": "python",
"repo": "topher-lo/automl-rdatasets",
"path": "/src/search.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: topher-lo/automl-rdatasets path: /src/search.py
"""Functions for spaCy language processing pipeline and computing
cosine similarity on spacy `Doc`s' word embeddings.
"""
import numpy as np
from tqdm import tqdm
from typing import List
from typing import Mapping
from typing import Union
from .ut... | code_fim | hard | {
"lang": "python",
"repo": "topher-lo/automl-rdatasets",
"path": "/src/search.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShreeshaN/VConvNet path: /vconv/visualiser/conv_visualiser.py
# -*- coding: utf-8 -*-
"""
@created on: 11/27/19,
@author: Shreesha N,
@version: v0.0.1
@system name: badgod
Description:
..todo::
"""
import torch
from vconv.networks.conv_network import SmallConvNet, VariableConvNet
from vconv.ut... | code_fim | hard | {
"lang": "python",
"repo": "ShreeshaN/VConvNet",
"path": "/vconv/visualiser/conv_visualiser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def run(self):
with torch.no_grad():
print(self.images_to_visualise + "/*")
print(glob.glob(self.images_to_visualise + "/*"))
for file in glob.glob(self.images_to_visualise + "/*"):
print('Reading image ', file)
image = cv2.im... | code_fim | hard | {
"lang": "python",
"repo": "ShreeshaN/VConvNet",
"path": "/vconv/visualiser/conv_visualiser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def plot_kernals(self):
convs = ['conv1.weight', 'conv2.weight', 'conv3.weight']
for conv in convs:
print('Plotting ', conv)
kernal = self.network.state_dict()[conv]
if conv != 'conv1.weight':
print(kernal.numpy().shape)
... | code_fim | hard | {
"lang": "python",
"repo": "ShreeshaN/VConvNet",
"path": "/vconv/visualiser/conv_visualiser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> mdl.save_plot_latent_space(model, directory, prefix="final")
mdl.save_plot_latent_vs_generated(model, directory, prefix="final")
mdl.save_plot_training_vs_generated(model, directory, prefix="final")
filename = directory + "/final_generated.bvh"
nframes = 200
x_path = model.run_ge... | code_fim | hard | {
"lang": "python",
"repo": "dmytrov/gaussianprocess",
"path": "/code/ml/gptheano/vecgpdm/paper_walk.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmytrov/gaussianprocess path: /code/ml/gptheano/vecgpdm/paper_walk.py
import numpy as np
import matplotlibex as plx
import ml.gptheano.vecgpdm.model as mdl
import numerical.numpytheano.theanopool as tp
import numerical.numpytheano as nt
import matplotlibex.mlplot as plx
import bvhrwroutines.bvhr... | code_fim | hard | {
"lang": "python",
"repo": "dmytrov/gaussianprocess",
"path": "/code/ml/gptheano/vecgpdm/paper_walk.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: diamanto/pypore path: /src/pyporegui/graphicsItems/path_item.py
from PySide import QtGui, QtCore
import pyqtgraph as pg
<|fim_suffix|> def __init__(self, x, y, conn='all'):
xr = x.min(), x.max()
yr = y.min(), y.max()
self._bounds = QtCore.QRectF(xr[0], yr[0], xr[1] - ... | code_fim | easy | {
"lang": "python",
"repo": "diamanto/pypore",
"path": "/src/pyporegui/graphicsItems/path_item.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def boundingRect(self):
return self._bounds<|fim_prefix|># repo: diamanto/pypore path: /src/pyporegui/graphicsItems/path_item.py
from PySide import QtGui, QtCore
import pyqtgraph as pg
class PathItem(QtGui.QGraphicsPathItem):
def __init__(self, x, y, conn='all'):
<|fim_middle|> x... | code_fim | hard | {
"lang": "python",
"repo": "diamanto/pypore",
"path": "/src/pyporegui/graphicsItems/path_item.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __call__(self):
value = self._rejection_sampling()
out = np.round(value, n_decimals)
if self._positive_definite:
out = abs(out)
return out
def _rejection_sampling(self):
param_min, param_max = self.parameter_values[0], self.parameter_value... | code_fim | hard | {
"lang": "python",
"repo": "dangilman/LenstronomyWrapper",
"path": "/lenstronomywrapper/Sampler/probability_distributions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dangilman/LenstronomyWrapper path: /lenstronomywrapper/Sampler/probability_distributions.py
import numpy as np
from scipy.interpolate import interp1d
n_decimals = 6
class Uniform(object):
def __init__(self, low, high, positive_definite=False):
self._low, self._high = low, high
... | code_fim | hard | {
"lang": "python",
"repo": "dangilman/LenstronomyWrapper",
"path": "/lenstronomywrapper/Sampler/probability_distributions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leo566491/csci-homework path: /4155/assignments/a4/q1.py
"""
@author Alex Moriarty
CSCI 4155 Machine Learning: Assignment 4.
Gradient decent to learn regression of X,Y data.
"""
import numpy as np
from sklearn.svm import SVR
import matplotlib.pyplot as plt
# Input Data
DATA_FILE = 'A4Q1_data.n... | code_fim | hard | {
"lang": "python",
"repo": "leo566491/csci-homework",
"path": "/4155/assignments/a4/q1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>X = Data[0,:]
Y = Data[1,:]
myX = np.random.randn(10,1)
myY = np.random.randn(10)
print X.shape
print Y.shape
clf = SVR()
clf.fit(myX,myY)
print "the guess by SVR for x=20 is", clf.predict(20)
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
p1a, = ax1.plot(X,Y,'o')
m = float(Y.size)
# add a column o... | code_fim | medium | {
"lang": "python",
"repo": "leo566491/csci-homework",
"path": "/4155/assignments/a4/q1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aguilerapy/kingfisher-process path: /docs/conf.py
master_doc = 'index'
<|fim_suffix|>html_static_path = ['database-tables.png']<|fim_middle|>project = 'OCDS Kingfisher Process Tool'
copyright = '2018, Open Contracting Data Standard'
| code_fim | medium | {
"lang": "python",
"repo": "aguilerapy/kingfisher-process",
"path": "/docs/conf.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>html_static_path = ['database-tables.png']<|fim_prefix|># repo: aguilerapy/kingfisher-process path: /docs/conf.py
master_doc = 'index'
<|fim_middle|>project = 'OCDS Kingfisher Process Tool'
copyright = '2018, Open Contracting Data Standard'
| code_fim | medium | {
"lang": "python",
"repo": "aguilerapy/kingfisher-process",
"path": "/docs/conf.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tylertrimble/viswaternet path: /tests/test_viswaternet.py
#!/usr/bin/env python
"""Tests for `viswaternet` package."""
import unittest
import viswaternet
import os
import matplotlib.pyplot as plt
import numpy as np
model = viswaternet.VisWNModel("tests/net1.inp")
class TestViswaternet(unittes... | code_fim | hard | {
"lang": "python",
"repo": "tylertrimble/viswaternet",
"path": "/tests/test_viswaternet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TestParameterBinning(unittest.TestCase):
"""Tests data binning."""
def test_interval_naming(self):
self.model = {}
self.model['node_names'] = ['E1','E2','E3','E4','E5','E6']
dummy_data=[1,2,3,5,6,7]
interval_results, interval_names = viswaternet.... | code_fim | hard | {
"lang": "python",
"repo": "tylertrimble/viswaternet",
"path": "/tests/test_viswaternet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hideo55/node-murmurhash3 path: /binding.gyp
{
'targets': [
{
'target_name': 'murmurhash3',
'sources': ['src/MurmurHash3.cpp', 'src/node_murmurhash3.cc'],
'cflags': ['-fexceptions'],
'cflags_cc': [<|fim_suffix|>ditions': [
['OS=="win"', {
'msvs_set... | code_fim | medium | {
"lang": "python",
"repo": "hideo55/node-murmurhash3",
"path": "/binding.gyp",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> }
],
['OS=="mac"', {
'xcode_settings': {
'GCC_ENABLE_CPP_EXCEPTIONS': 'YES'
}
}
]
]
}
]
}<|fim_prefix|># repo: hideo55/node-murmurhash3 path: /binding.gyp
{
'targets': [
{
'target_name': 'murmurhash3... | code_fim | medium | {
"lang": "python",
"repo": "hideo55/node-murmurhash3",
"path": "/binding.gyp",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertResultIsBlock(
CloudKit.CKDiscoverUserIdentitiesOperation.discoverUserIdentitiesCompletionBlock, # noqa: B950
b"v@",
)
self.assertArgIsBlock(
CloudKit.CKDiscoverUserIdentitiesOperation.setDiscoverUserIdentitie... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/pyobjc",
"path": "/pyobjc-framework-CloudKit/PyObjCTest/test_ckdiscoveruseridentitiesoperation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 5l1v3r1/pyobjc path: /pyobjc-framework-CloudKit/PyObjCTest/test_ckdiscoveruseridentitiesoperation.py
import sys
if sys.maxsize > 2 ** 32:
from PyObjCTools.TestSupport import TestCase, min_os_level
import CloudKit
class TestCKDiscoverUserIdentitiesOperation(TestCase):
<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/pyobjc",
"path": "/pyobjc-framework-CloudKit/PyObjCTest/test_ckdiscoveruseridentitiesoperation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertResultIsBlock(
CloudKit.CKDiscoverUserIdentitiesOperation.userIdentityDiscoveredBlock,
b"v@@",
)
self.assertArgIsBlock(
CloudKit.CKDiscoverUserIdentitiesOperation.setUserIdentityDiscoveredBlock_,
... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/pyobjc",
"path": "/pyobjc-framework-CloudKit/PyObjCTest/test_ckdiscoveruseridentitiesoperation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _get_generated_data(self, sample_size, label):
num_batches = sample_size // self.config.batch_size
result = []
for idx in xrange(num_batches):
z_sample = np.random.uniform(-1, 1, size=[int(self.config.batch_size), self.model.z_dim])
y_one_hot = np.ze... | code_fim | hard | {
"lang": "python",
"repo": "rparrapy/DCGAN-tensorflow",
"path": "/discriminator_evaluator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rparrapy/DCGAN-tensorflow path: /discriminator_evaluator.py
from nideep.datasets.celeba.celeba import CelebA
from utils import *
import os
class DiscriminatorEvaluator(object):
def __init__(self, sess, model, config, cache_dir='/mnt/raid/data/ni/dnn/rparra/cache/'):
self.sess = ses... | code_fim | hard | {
"lang": "python",
"repo": "rparrapy/DCGAN-tensorflow",
"path": "/discriminator_evaluator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for idx in xrange(0, batch_idxs):
batch_labels = data_y[idx * self.config.batch_size:(idx + 1) * self.config.batch_size]
batch_files = data[idx * self.config.batch_size:(idx + 1) * self.config.batch_size]
batch = [
get_image(batch_file,
... | code_fim | hard | {
"lang": "python",
"repo": "rparrapy/DCGAN-tensorflow",
"path": "/discriminator_evaluator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NomadXD/covid19-tracker path: /cases.py
ation':{'lat':8.087345,'lng': 81.177059,'value':'Kandakadu'},
'status':'Hospitalized'
},
'6':{
'case_no':6,
'detected_date':'2020-03-14',
'age':4... | code_fim | hard | {
"lang": "python",
"repo": "NomadXD/covid19-tracker",
"path": "/cases.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> 'status':'Hospitalized'
},
'39':{
'case_no':39,
'detected_date':'2020-03-17',
'detected':'Kandakadu',
'detected_prefecture':'Polonnaruwa',
'origin':'Italy',
... | code_fim | hard | {
"lang": "python",
"repo": "NomadXD/covid19-tracker",
"path": "/cases.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NomadXD/covid19-tracker path: /cases.py
'detected_date':'2020-03-14',
'age':17,
'gender':'F',
'detected':'Mattegoda',
'detected_prefecture':'Colombo',
'origin':'Italy',
... | code_fim | hard | {
"lang": "python",
"repo": "NomadXD/covid19-tracker",
"path": "/cases.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Confirm the resize
run("nova resize-confirm %s" % server_name)
return True
def test_migrate(context):
count, args = context
server_name = "server%d" % count
cleanup = args.cleanup
with server_built(server_name, args.image, cleanup=cleanup):
# Migrate A -> B
... | code_fim | hard | {
"lang": "python",
"repo": "starlingx-staging/stx-nova",
"path": "/tools/xenserver/stress_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: starlingx-staging/stx-nova path: /tools/xenserver/stress_test.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/licenses/LICENSE-2.0
#... | code_fim | hard | {
"lang": "python",
"repo": "starlingx-staging/stx-nova",
"path": "/tools/xenserver/stress_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument('-i', '--image', help="image to build from",
required=True)
parser.add_argument('-n', '--num-runs', type=int, help="number of runs",
default=1)
parser.add_argument('-c', '--concurrency', type=int, default=5,
... | code_fim | hard | {
"lang": "python",
"repo": "starlingx-staging/stx-nova",
"path": "/tools/xenserver/stress_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TeamRoquette/PyRat path: /lib/travelHeuristics.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import lib.shortestPaths as sp
def generateMetaGraph (mazeMap, playerLocation, coins):
"""
Generate a metaGraph from mazeMap, containing all coins and the player.
This function is built... | code_fim | hard | {
"lang": "python",
"repo": "TeamRoquette/PyRat",
"path": "/lib/travelHeuristics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> TSM_auxi(nodeStart, nodes, distance, path)
return bestDistance, bestPaths
def backTrack(metaGraph, startNode, path, deep):
"""
Implementation of the backTracking algorithm.
"""
global bestDistance
global bestPaths
bestDistance = float('inf')
bestPaths = []
... | code_fim | hard | {
"lang": "python",
"repo": "TeamRoquette/PyRat",
"path": "/lib/travelHeuristics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frangiz/AdventOfCode2017 path: /test/test_day15.py
from days import day15
from ddt import ddt, data, unpack
import unittest
import util
@ddt
class MyTestCase(unittest.TestCase):
@data(
[['Generator A starts with 65', 'Generator B starts with 8921'], '588'])
@unpack
... | code_fim | hard | {
"lang": "python",
"repo": "frangiz/AdventOfCode2017",
"path": "/test/test_day15.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_answer_part_a(self):
result = day15.part_a(util.get_file_contents('day15.txt'))
self.assertEqual(result, '567')
@data(
[['Generator A starts with 65', 'Generator B starts with 8921'], '309'])
@unpack
def test_example_b(self, test_input, expected):
... | code_fim | hard | {
"lang": "python",
"repo": "frangiz/AdventOfCode2017",
"path": "/test/test_day15.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cms-sw/cmssw path: /RecoMuon/L3MuonProducer/python/L3TkMuonProducer_cfi.py
import FWCore.ParameterSet.Config as cm<|fim_suffix|>InputTag( "hltL3TkTracksFromL2NoVtx" )
)<|fim_middle|>s
hltL3MuonsNoVtx = cms.EDProducer( "L3TkMuonProducer",
InputObjects = cms. | code_fim | medium | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoMuon/L3MuonProducer/python/L3TkMuonProducer_cfi.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>InputTag( "hltL3TkTracksFromL2NoVtx" )
)<|fim_prefix|># repo: cms-sw/cmssw path: /RecoMuon/L3MuonProducer/python/L3TkMuonProducer_cfi.py
import FWCore.ParameterSet.Config as cm<|fim_middle|>s
hltL3MuonsNoVtx = cms.EDProducer( "L3TkMuonProducer",
InputObjects = cms. | code_fim | medium | {
"lang": "python",
"repo": "cms-sw/cmssw",
"path": "/RecoMuon/L3MuonProducer/python/L3TkMuonProducer_cfi.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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