text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>['rot'] = rot
items["idItem" + str(n)]["itemType"] = "door"
if k["item_name"] == 'Out Door':
items["idItem" + str(n)]["itemName"] = "exit" #Clave
items["idItem" + str(n)]["itemType"] = "poi"
items["idItem" + str(n)]["id"] = "out"
items["idItem" + str(n+1000)] = {"pos": { "x": ... | code_fim | hard | {
"lang": "python",
"repo": "gsi-upm/soba",
"path": "/soba/visualization/ramen/mapGenerator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># clip the dataset
clipper = vtk.vtkClipDataSet()
clipper.SetInputData(dataset.GetBlock(0).GetBlock(0))
plane = vtk.vtkPlane()
plane.SetNormal(0.5,0.5,0.5)
plane.SetOrigin(0.5,0.5,0.5)
clipper.SetClipFunction(plane)
clipper.Update()
# get surface representation to render
surfaceFilter = vtk.vtkDataSetSur... | code_fim | hard | {
"lang": "python",
"repo": "t3dbrida/VTK",
"path": "/Common/DataModel/Testing/Python/TestClipPolyhedra.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: t3dbrida/VTK path: /Common/DataModel/Testing/Python/TestClipPolyhedra.py
#!/usr/bin/env python
import vtk
from vtk.util.misc import vtkGetDataRoot
VTK_DATA_ROOT = vtkGetDataRoot()
# Create the RenderWindow, Renderer
#
ren = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer( ren... | code_fim | medium | {
"lang": "python",
"repo": "t3dbrida/VTK",
"path": "/Common/DataModel/Testing/Python/TestClipPolyhedra.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>ren.GetActiveCamera().SetPosition(-0.5,0.5,0)
ren.GetActiveCamera().SetFocalPoint(0.5, 0.5, 0.5)
ren.GetActiveCamera().SetViewUp(0.0820, 0.934, -0.348)
ren.ResetCamera()
renWin.Render()
iren.Start()<|fim_prefix|># repo: t3dbrida/VTK path: /Common/DataModel/Testing/Python/TestClipPolyhedra.py
#!/usr/bin/e... | code_fim | hard | {
"lang": "python",
"repo": "t3dbrida/VTK",
"path": "/Common/DataModel/Testing/Python/TestClipPolyhedra.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # TODO: Add news and reddit commands back
# def call_eda(self, _):
# try:
# df = fx_view.get_candles_dataframe(account, self.instrument, None)
# df = df.rename(columns={"Close": "Adj Close"})
# instrument = self.instrument
# s_start = pd.to_datet... | code_fim | hard | {
"lang": "python",
"repo": "kai-anderson/GamestonkTerminal",
"path": "/gamestonk_terminal/forex/forex_controller.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kai-anderson/GamestonkTerminal path: /gamestonk_terminal/forex/forex_controller.py
import argparse
from datetime import timedelta, datetime
from typing import List
import pandas as pd
from prompt_toolkit.completion import NestedCompleter
from colorama import Style
from gamestonk_terminal import ... | code_fim | hard | {
"lang": "python",
"repo": "kai-anderson/GamestonkTerminal",
"path": "/gamestonk_terminal/forex/forex_controller.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class J_crf(nn.Module):
def __init__(self):
super().__init__()
self.crf = ConditionalRandomField(num_tags=len(label_dic), constraints=constraints, include_start_end_transitions=False)
def forward(self, inputs, labels):
return -self.crf(inputs, labels)
import matplotlib.py... | code_fim | hard | {
"lang": "python",
"repo": "xsthunder/HMM_CRF_torch",
"path": "/exp/basic_test_for_crf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import matplotlib.pyplot as plt
def pxy(x, y, name='idk'):
name = str(name)
fig, = plt.plot(x,y, )
fig.set_label(name)
plt.legend()
# pxy([1,2], [3,2], '2')
# pxy([1,2], [5,6], '1')<|fim_prefix|># repo: xsthunder/HMM_CRF_torch path: /exp/basic_test_for_crf.py
############################... | code_fim | hard | {
"lang": "python",
"repo": "xsthunder/HMM_CRF_torch",
"path": "/exp/basic_test_for_crf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xsthunder/HMM_CRF_torch path: /exp/basic_test_for_crf.py
#################################################
### THIS FILE WAS AUTOGENERATED! DO NOT EDIT! ###
#################################################
# file to edit: ./nb/basic_test_for_crf.ipynb
import sys
if __name__ == '__main__': sys.... | code_fim | medium | {
"lang": "python",
"repo": "xsthunder/HMM_CRF_torch",
"path": "/exp/basic_test_for_crf.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if kind == 'Pre-correction':
kind = 'pre_correction'
elif kind == 'Post-correction':
kind = 'post_correction'
elif kind == 'Illumina':
kinda = 'illumina'
plt.tight_layout()
fname = '{}_{}_umis_v_barcodes.png'.format(oprefix, kind)
plt.savefig(fname)
plt.clf()<|fim_prefix|># repo: fairlieree... | code_fim | hard | {
"lang": "python",
"repo": "fairliereese/LR-splitpipe",
"path": "/LR-splitpipe/plot_ranked_barcodes.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fairliereese/LR-splitpipe path: /LR-splitpipe/plot_ranked_barcodes.py
def plot_umis_v_barcodes(df, oprefix, kind):
bc_cols = ['bc1', 'bc2', 'bc3']
# only want unique bc/umi combos
temp = df[bc_cols+['umi']].drop_duplicates()
# get the number of unique bc/umi combos
temp = temp[bc_cols+['um... | code_fim | medium | {
"lang": "python",
"repo": "fairliereese/LR-splitpipe",
"path": "/LR-splitpipe/plot_ranked_barcodes.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openstack/python-heatclient path: /heatclient/osc/v1/event.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": "openstack/python-heatclient",
"path": "/heatclient/osc/v1/event.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if parsed_args.sort:
sorts = []
sort_keys = []
for sort in parsed_args.sort:
if sort.startswith(":"):
sorts.append(":".join(["event_time", sort.lstrip(":")]))
else:
sorts.append(sort)
... | code_fim | hard | {
"lang": "python",
"repo": "openstack/python-heatclient",
"path": "/heatclient/osc/v1/event.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
x = PackedSequence(x,
sequence.batch_sizes,
sequence.sorted_indices,
sequence.unsorted_indices)
hx = torch.cat(h_n, 0), torch.cat(c_n, 0)
hx = self.permute_hidden(hx, sequence.unsorted_indices)
return x, hx
class LstmCell(nn.Module):
def __init__(self, input_si... | code_fim | hard | {
"lang": "python",
"repo": "markhsia/CLNER",
"path": "/flair/models/biaffine_dp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#--------------lstm ---------------------
class BiLSTM_1(nn.Module):
def __init__(self, input_size, hidden_size, num_layers, dropout=None):
super(BiLSTM_1, self).__init__()
self.input_size = input_size #emb_size
self.hidden_size = hidden_size
self.num_layers = num_layers
self.dropout_rate =... | code_fim | hard | {
"lang": "python",
"repo": "markhsia/CLNER",
"path": "/flair/models/biaffine_dp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: markhsia/CLNER path: /flair/models/biaffine_dp.py
e=='eval':
# self.eval_dataloader = eval_dataloader(config)
# else:
# pdb.set_trace()
# def step(self):
# if self.batch_len is not None:
# batch = self.train_dataloader[self.global_step%self.batch_len]
# loss_step = self.forwar... | code_fim | hard | {
"lang": "python",
"repo": "markhsia/CLNER",
"path": "/flair/models/biaffine_dp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Setter for credentials.
Args:
config (array): Json object to fetch keys.
"""
self._app_id = config['here'][0]
self._app_code = config['here'][1]
def __set_timeout(self, timeout):
"""Setter for timeout.
Args:
timeout (int):... | code_fim | hard | {
"lang": "python",
"repo": "uvraj88/SimpleNetworkService",
"path": "/src/services/here_api.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def form_params(self, lat, long):
"""Form Url params given lat and long
Args:
lat (float): latitude of a location
long (float): longitude of a location
Returns:
A human readable address or None.
"""
data = {'mode': 'retrieveAddresse... | code_fim | hard | {
"lang": "python",
"repo": "uvraj88/SimpleNetworkService",
"path": "/src/services/here_api.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: uvraj88/SimpleNetworkService path: /src/services/here_api.py
import logging
class hereApi(object):
"""Base class for HERE Search,
which is used to fetch address using HERE.
"""
def __init__(self, config, timeout=None):
"""Returns a Api instance.
Args:
co... | code_fim | hard | {
"lang": "python",
"repo": "uvraj88/SimpleNetworkService",
"path": "/src/services/here_api.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _keys(self):
"""Return an iterator through the pickle files in this store."""
for name in listdir(abspath(self._path)):
key, ext = splitext(name)
if ext == ".pkl":
yield key
def _has(self, key):
"""Return whether a pickle file ex... | code_fim | hard | {
"lang": "python",
"repo": "Ilgrim/cwmud",
"path": "/cwmud/core/pickle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Ilgrim/cwmud path: /cwmud/core/pickle.py
# -*- coding: utf-8 -*-
"""Pickle serialization and storage."""
# Part of Clockwork MUD Server (https://github.com/whutch/cwmud)
# :copyright: (c) 2008 - 2017 Will Hutcheson
# :license: MIT (https://github.com/whutch/cwmud/blob/master/LICENSE.txt)
from os... | code_fim | hard | {
"lang": "python",
"repo": "Ilgrim/cwmud",
"path": "/cwmud/core/pickle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return driver.main()
if __name__ == '__main__':
sys.exit(main())<|fim_prefix|># repo: hqs2212586/qingcloud-cli path: /bin/qingcloud.py
# -*- coding:utf-8 -*-
__author__ = 'Qiushi Huang'
import os,sys,platform
<|fim_middle|>#for linux
if platform.system() == "Windows":
BASE_DIR = '\\'.join... | code_fim | hard | {
"lang": "python",
"repo": "hqs2212586/qingcloud-cli",
"path": "/bin/qingcloud.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
sys.exit(main())<|fim_prefix|># repo: hqs2212586/qingcloud-cli path: /bin/qingcloud.py
# -*- coding:utf-8 -*-
__author__ = 'Qiushi Huang'
import os,sys,platform
#for linux
if platform.system() == "Windows":
BASE_DIR = '\\'.join(os.path.abspath(os.path.dirname(__file_... | code_fim | easy | {
"lang": "python",
"repo": "hqs2212586/qingcloud-cli",
"path": "/bin/qingcloud.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hqs2212586/qingcloud-cli path: /bin/qingcloud.py
# -*- coding:utf-8 -*-
__author__ = 'Qiushi Huang'
import os,sys,platform
#for linux
if platform.system() == "Windows":
BASE_DIR = '\\'.join(os.path.abspath(os.path.dirname(__file__)).split('\\')[:-1])
print(BASE_DIR)
else:
BASE_DIR =... | code_fim | easy | {
"lang": "python",
"repo": "hqs2212586/qingcloud-cli",
"path": "/bin/qingcloud.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>d_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: BSD License",
],
python_requires='>=3.1',
)<|fim_prefix|># repo: apizzuto/v2_alert_stacking_FRA path: /setup.py
import setuptools
long_message = 'FRANCIS: Fast Response Analysis for... | code_fim | medium | {
"lang": "python",
"repo": "apizzuto/v2_alert_stacking_FRA",
"path": "/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: apizzuto/v2_alert_stacking_FRA path: /setup.py
import setuptools
long_message = 'FRANCIS: Fast Response Analysis for Neutrino Coincidences with IceCube Signals'
version = "0.0.1"
setuptools.setup(
name="fran<|fim_suffix|>essage,
#long_description_content_type="text/markdown",
url="h... | code_fim | medium | {
"lang": "python",
"repo": "apizzuto/v2_alert_stacking_FRA",
"path": "/setup.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>essage,
#long_description_content_type="text/markdown",
url="https://github.com/icecube/wg-nu-sources/2021_v2_alert_stacking_FRA",
packages=setuptools.find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: BSD License",
],
... | code_fim | medium | {
"lang": "python",
"repo": "apizzuto/v2_alert_stacking_FRA",
"path": "/setup.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: claudijd/honeycomb path: /honeycomb/commands/service/logs.py
# -*- coding: utf-8 -*-
"""Honeycomb service logs command."""
import os
import logging
import threading
import click
from honeycomb.defs import SERVICES
from honeycomb.utils.tailer import Tailer
from honeycomb.servicemanager.defs imp... | code_fim | hard | {
"lang": "python",
"repo": "claudijd/honeycomb",
"path": "/honeycomb/commands/service/logs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@click.command(short_help="Show logs for a daemonized service.")
@click.option("-n", "--num", type=int, default=10, help="Number of lines to read from end of file", show_default=True)
@click.option("-f", "--follow", is_flag=True, default=False, help="Follow log output")
@click.argument("services", requir... | code_fim | hard | {
"lang": "python",
"repo": "claudijd/honeycomb",
"path": "/honeycomb/commands/service/logs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: contengee/kuma_utils path: /torch/hooks/simple_hook.py
from .base import HookTemplate
class SimpleHook(HookTemplate):
def __init__(self, evaluate_batch=False):
super().__init__()
self.evaluate_batch = evaluate_batch
def forward_train(self, trainer, inputs):
tar... | code_fim | hard | {
"lang": "python",
"repo": "contengee/kuma_utils",
"path": "/torch/hooks/simple_hook.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> storage = trainer.epoch_storage
if self.evaluate_batch: # Batch level evaluation
metric_total = storage['batch_metric'].mean(0)
monitor_metrics_total = storage['batch_monitor'].mean(0).tolist()
else: # Dataset level evaluation
if trainer.eval_me... | code_fim | hard | {
"lang": "python",
"repo": "contengee/kuma_utils",
"path": "/torch/hooks/simple_hook.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shish/context-demos path: /basic.py
#!/usr/bin/env python
from threading import Thread
from time import sleep
import sys
sys.path.append("../context-apis/python/")
import context.api as c
def thread_1():
c.log_bmark("Server thread spawned")
c.log_start("Logging in", bookmark=True)
... | code_fim | hard | {
"lang": "python",
"repo": "shish/context-demos",
"path": "/basic.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> c.log_start("Logging in", bookmark=True)
sleep(0.1)
c.log_start("Search database")
sleep(0.3)
c.log_endok("Search database")
c.log_start("Initialise session for 'laura'")
sleep(0.3)
c.log_endok("Initialise session for 'laura'")
c.log_start("Render")
sleep(0.1)
c... | code_fim | hard | {
"lang": "python",
"repo": "shish/context-demos",
"path": "/basic.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> c.log_start("Read article", bookmark=True)
sleep(0.05)
c.log_start("Search database")
sleep(0.3)
c.log_endok("Search database")
c.log_start("Render")
sleep(0.1)
c.log_endok("Render")
sleep(0.05)
c.log_endok("Read article")
if __name__ == "__main__":
c.set_log("... | code_fim | hard | {
"lang": "python",
"repo": "shish/context-demos",
"path": "/basic.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> val_acc_history = []
val_f1_history = []
best_model_wts = copy.deepcopy(model.state_dict())
best_acc = 0.0
best_f1 = 0.0
# Detect if we have a GPU available
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
for epoch in range(num_epochs):
pr... | code_fim | hard | {
"lang": "python",
"repo": "Leo-xxx/kissing-detector",
"path": "/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Leo-xxx/kissing-detector path: /train.py
# adapted from PyTorch tutorials
import copy
import time
from typing import List, Tuple, Optional
import torch
import torch.optim as optim
from torch import nn
from data import AudioVideo, AudioVideo3D
from kissing_detector import KissingDetector, Kissin... | code_fim | hard | {
"lang": "python",
"repo": "Leo-xxx/kissing-detector",
"path": "/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> best_model_wts = copy.deepcopy(model.state_dict())
best_acc = 0.0
best_f1 = 0.0
# Detect if we have a GPU available
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
for epoch in range(num_epochs):
print('Epoch {}/{}'.format(epoch, num_epochs - 1))
... | code_fim | hard | {
"lang": "python",
"repo": "Leo-xxx/kissing-detector",
"path": "/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mozilla/python_mozetl path: /mozetl/constants.py
# Restrict to a whitelist of search_source's to avoid double counting while
# we test our new search_count telemetry developed in:
# https://bugzilla.mozilla.org/show_bug.cgi?id=1367554
# https://bugzilla.mozil<|fim_suffix|>,
"newtab",
"con... | code_fim | medium | {
"lang": "python",
"repo": "mozilla/python_mozetl",
"path": "/mozetl/constants.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>,
"newtab",
"contextmenu",
"system",
"activitystream",
"webextension",
"alias",
]<|fim_prefix|># repo: mozilla/python_mozetl path: /mozetl/constants.py
# Restrict to a whitelist of search_source's to avoid double counting while
# we test our new search_count telemetry developed in... | code_fim | medium | {
"lang": "python",
"repo": "mozilla/python_mozetl",
"path": "/mozetl/constants.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: airqo-platform/AirQo-frontend path: /website/backend/event/migrations/0003_alter_session_options.py
# Generated by Django 4.1.7 on 2023-03-23 10:33
from django.db import migrations
<|fim_suffix|> dependencies = [
('event', '0002_session_order'),
]
operations = [
migr... | code_fim | easy | {
"lang": "python",
"repo": "airqo-platform/AirQo-frontend",
"path": "/website/backend/event/migrations/0003_alter_session_options.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Migration(migrations.Migration):
dependencies = [
('event', '0002_session_order'),
]
operations = [
migrations.AlterModelOptions(
name='session',
options={'ordering': ['order']},
),
]<|fim_prefix|># repo: airqo-platform/AirQo-frontend... | code_fim | easy | {
"lang": "python",
"repo": "airqo-platform/AirQo-frontend",
"path": "/website/backend/event/migrations/0003_alter_session_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('event', '0002_session_order'),
]
operations = [
migrations.AlterModelOptions(
name='session',
options={'ordering': ['order']},
),
]<|fim_prefix|># repo: airqo-platform/AirQo-frontend path: /website/backend/event/migration... | code_fim | easy | {
"lang": "python",
"repo": "airqo-platform/AirQo-frontend",
"path": "/website/backend/event/migrations/0003_alter_session_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Cguilliman/django-ib-menus path: /menus/models/queysets.py
from django.db import models
from mptt.models import TreeManager
<|fim_suffix|> return super().get_queryset()
def get_by_position(self, position):
"""Get objects by position"""
return self.get_queryset().fil... | code_fim | hard | {
"lang": "python",
"repo": "Cguilliman/django-ib-menus",
"path": "/menus/models/queysets.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Get objects by position"""
return self.get_queryset().filter(position=position)<|fim_prefix|># repo: Cguilliman/django-ib-menus path: /menus/models/queysets.py
from django.db import models
from mptt.models import TreeManager
<|fim_middle|>__all__ = ("BaseMenuManager", )
class Base... | code_fim | hard | {
"lang": "python",
"repo": "Cguilliman/django-ib-menus",
"path": "/menus/models/queysets.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> state = self.hass.states.get(self.entity.entity_id)
self.assertTrue(state.attributes.get(ATTR_HIDDEN))
def test_overwriting_hidden_property_to_true(self):
""" Test we can overwrite hidden property to True. """
entity.Entity.overwrite_attribute(self.entity.entity_id,
... | code_fim | hard | {
"lang": "python",
"repo": "maddox/home-assistant",
"path": "/tests/helpers/test_entity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: maddox/home-assistant path: /tests/helpers/test_entity.py
"""
tests.test_helper_entity
~~~~~~~~~~~~~~~~~~~~~~~~
Tests the entity helper.
"""
# pylint: disable=protected-access,too-many-public-methods
import unittest
import homeassistant.core as ha
import homeassistant.helpers.entity as entity
f... | code_fim | hard | {
"lang": "python",
"repo": "maddox/home-assistant",
"path": "/tests/helpers/test_entity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Stop down stuff we started. """
self.hass.stop()
entity.Entity.overwrite_attribute(self.entity.entity_id,
[ATTR_HIDDEN], [None])
def test_default_hidden_not_in_attributes(self):
""" Test that the default hidden property is ... | code_fim | hard | {
"lang": "python",
"repo": "maddox/home-assistant",
"path": "/tests/helpers/test_entity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.basic = ['free']<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_freeing.py
#calss header
class _FREEING():
def __init__(self,):
self.name = "FREEING"
self.definitions = free
<|fim_middle|> self.parents = []
self.childen = []
self.properties = []
self.jsonda... | code_fim | medium | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_freeing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/otherforms/_freeing.py
#calss header
class _FREEING():
<|fim_suffix|> self.name = "FREEING"
self.definitions = free
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.basic = ['free']<|fim_middle|> def __init__... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/otherforms/_freeing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@classmethod
def handler(cls, message):
responses = CommandHandler.inner_handler(message)
output_responses = []
for (response_to, response) in responses:
if response_to == "" and response == "":
break
if response_to == "*":
... | code_fim | hard | {
"lang": "python",
"repo": "georgeteo/samsu-assasins",
"path": "/model/handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Return [(number, msg),...]"""
action, params = CommandHandler.get_command(message.Body)
attacker = Util.get_attacker(message.From)
if action == "KILL":
return Kill.handler(attacker, params)
elif action[1:] == "REPLY":
ref = params.pop(0)... | code_fim | hard | {
"lang": "python",
"repo": "georgeteo/samsu-assasins",
"path": "/model/handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: georgeteo/samsu-assasins path: /model/handler.py
from model.reply import Reply
from model.kill import Kill
from model.util import Util
from model.error import CommandError
import logging
from model.bomb import Bomb
from model.disarm import Disarm
from model.player import Player
from model.snipe i... | code_fim | hard | {
"lang": "python",
"repo": "georgeteo/samsu-assasins",
"path": "/model/handler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zhoufei9/python path: /application/models/sharesHotTop100.py
# -*- coding: utf-8 -*-
from .base import ModelsBase
class sharesHotTop100(ModelsBase):
<|fim_suffix|> def shuchu(self):
print('表名sharesHotTop100' + self.a)
"调用子类构造方法"<|fim_middle|> def __init__(self,a):
s... | code_fim | medium | {
"lang": "python",
"repo": "zhoufei9/python",
"path": "/application/models/sharesHotTop100.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print('表名sharesHotTop100' + self.a)
"调用子类构造方法"<|fim_prefix|># repo: zhoufei9/python path: /application/models/sharesHotTop100.py
# -*- coding: utf-8 -*-
from .base import ModelsBase
class sharesHotTop100(ModelsBase):
def __init__(self,a):
self.a = a
print('111')
<|fi... | code_fim | easy | {
"lang": "python",
"repo": "zhoufei9/python",
"path": "/application/models/sharesHotTop100.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Learn grammar
lex.learn('datasets/{}/{}_training.txt'.format(args.language_name,
args.language_name),
'datasets/{}/{}_constraints.txt'.format(args.language_name,
args.language_name),
'dat... | code_fim | hard | {
"lang": "python",
"repo": "bhallen/pyparadigms",
"path": "/learn.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bhallen/pyparadigms path: /learn.py
"""
Command-line interface for learning a grammar using Sublexical Morphology
"""
import paradigms
import argparse
#####################################################################
## Parse command line arguments ##
##... | code_fim | hard | {
"lang": "python",
"repo": "bhallen/pyparadigms",
"path": "/learn.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cohen39/fixedwing_gazebo path: /tools/stl_tools.py
import os
import subprocess
from pathlib import Path
from typing import List
parts_subdivide = []
parts_decimate = []
def openscad_stl_export(scad_file: Path, part: str, out_dir: Path):
"""
Export stl components from an openscad model.
... | code_fim | hard | {
"lang": "python",
"repo": "cohen39/fixedwing_gazebo",
"path": "/tools/stl_tools.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def decimate(file_in: Path, file_out: Path, ratio: float):
assert ratio > 0 and ratio < 1
script = decimate_script.format(**{
'file_in': str(file_in), 'file_out': str(file_out), 'ratio': ratio})
#print(script)
with open("/tmp/decimate.py", "w") as f:
f.write(script)
sub... | code_fim | hard | {
"lang": "python",
"repo": "cohen39/fixedwing_gazebo",
"path": "/tools/stl_tools.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xue-yuan/lingram path: /bot/utils/__init__.py
from config import config as CONFIG
<|fim_suffix|> for f in os.listdir(CONFIG.APP.TMP_FOLDER):
if f == '.gitkeep': continue
shutil.rmtree(f'{CONFIG.APP.TMP_FOLDER}/{f}')<|fim_middle|>def clean_tmp_folder():
import os
import... | code_fim | easy | {
"lang": "python",
"repo": "xue-yuan/lingram",
"path": "/bot/utils/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for f in os.listdir(CONFIG.APP.TMP_FOLDER):
if f == '.gitkeep': continue
shutil.rmtree(f'{CONFIG.APP.TMP_FOLDER}/{f}')<|fim_prefix|># repo: xue-yuan/lingram path: /bot/utils/__init__.py
from config import config as CONFIG
<|fim_middle|>def clean_tmp_folder():
import os
import... | code_fim | easy | {
"lang": "python",
"repo": "xue-yuan/lingram",
"path": "/bot/utils/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if args.awesome_list_mode:
collector.mapAwesomeListsToGithubLinks()
if args.githublinks_file:
collector.dumpGithubLinks(args.githublinks_file)
if args.redownload:
collector.downloadReadmeFiles(args.readme_folder)
collector.createDatabase(args.outfolder, args.readme_folder)
elif args... | code_fim | hard | {
"lang": "python",
"repo": "SoftwareUnderstanding/rolf",
"path": "/src/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SoftwareUnderstanding/rolf path: /src/main.py
import json
import sys
from typing import List
import pandas as pd
import argparse
from sklearn.model_selection import train_test_split
import logthis
from preprocessing import preprocess_file
from util.utils import BASE_CATEGORIES, getCategories
fro... | code_fim | hard | {
"lang": "python",
"repo": "SoftwareUnderstanding/rolf",
"path": "/src/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def push_note(self, device_iden, title, body):
"""Push note to a device"""
self.session.post(
PUSH_URL,
json={
"device_iden": device_iden,
"type": "note",
"title": title,
"body": body
})... | code_fim | hard | {
"lang": "python",
"repo": "Kokan/syslogng-pushbullet",
"path": "/syslogng_pushbullet/pushbullet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Kokan/syslogng-pushbullet path: /syslogng_pushbullet/pushbullet.py
# -*- coding: utf-8 -*-
import requests
PUSH_URL = "https://api.pushbullet.com/v2/pushes"
DEVICES_URL = "https://api.pushbullet.com/v2/devices"
class PushbulletClient(object):
"""Pushbullet client"""
def __init__(self... | code_fim | hard | {
"lang": "python",
"repo": "Kokan/syslogng-pushbullet",
"path": "/syslogng_pushbullet/pushbullet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#train_dir = '/mnt/c/Users/sophi/Documents/phd/data/coliee2019/task1/task1_train'
#
# load directory structure
#
list_dir = [x for x in os.walk(args.train_dir)]
for sub_dir in list_dir[0][1]:
with jsonlines.open(os.path.join(args.train_dir, sub_dir, 'candidates.jsonl'), mode='w') as wr... | code_fim | medium | {
"lang": "python",
"repo": "keshava/bert-pli",
"path": "/preprocessing/coliee19_task1_index_jsonl.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keshava/bert-pli path: /preprocessing/coliee19_task1_index_jsonl.py
import os
import argparse
import random
import jsonlines
random.seed(42)
#
# config
#
parser = argparse.ArgumentParser()
parser.add_argument('--train-dir', action='store', dest='train_dir',
help=... | code_fim | medium | {
"lang": "python",
"repo": "keshava/bert-pli",
"path": "/preprocessing/coliee19_task1_index_jsonl.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for sub_dir in list_dir[0][1]:
with jsonlines.open(os.path.join(args.train_dir, sub_dir, 'candidates.jsonl'), mode='w') as writer:
# read in all paragraphs with their names and then choose the relevant ones and sample irrelevant ones!
list_sub_dir_paragraphs = [x for x in os.walk(os... | code_fim | medium | {
"lang": "python",
"repo": "keshava/bert-pli",
"path": "/preprocessing/coliee19_task1_index_jsonl.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def submitter(url):
driver = init_Driver()
# Start survey
nxt = WebDriverWait(driver, 10).until(EC.presence_of_element_located((By.XPATH, '/html/body/div/form/div[2]/div[3]/input')))
nxt.click()
# Sends full name
fn = driver.find_element_by_name('t50100775')
fn.send_keys(... | code_fim | hard | {
"lang": "python",
"repo": "GeekMuch/autoapplyvaxx",
"path": "/vaxx_region_hovedstad.py",
"mode": "spm",
"license": "LicenseRef-scancode-wtfpl-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GeekMuch/autoapplyvaxx path: /vaxx_region_hovedstad.py
#!/usr/bin/python
#!/usr/local/bin/python
import os
import sys
import time
import platform
from termcolor import colored
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by... | code_fim | hard | {
"lang": "python",
"repo": "GeekMuch/autoapplyvaxx",
"path": "/vaxx_region_hovedstad.py",
"mode": "psm",
"license": "LicenseRef-scancode-wtfpl-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IFRCGo/go-api path: /country_plan/tests/test_commands.py
from unittest import mock
from django.core.management import call_command
from main.test_case import APITestCase
from api.factories.country import CountryFactory
from country_plan.factories import CountryPlanFactory
from country_plan.model... | code_fim | hard | {
"lang": "python",
"repo": "IFRCGo/go-api",
"path": "/country_plan/tests/test_commands.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> headers = {
'Content-Type': 'application/pdf',
'Content-Disposition': 'attachment;filename=Sample_document_2023.pdf',
}
if url.endswith('NOOP'):
headers['Content-Type'] = 'html/text'
elif url.endswith('000004'):
headers['Conte... | code_fim | hard | {
"lang": "python",
"repo": "IFRCGo/go-api",
"path": "/country_plan/tests/test_commands.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Make sure the manifests directory exists
mkdir_p(os.path.dirname(self.manifests['exe'].path))
# Set flag to auto-scan input directories
self.scaninputs = self.manifest_config.get('scaninputs', True)
if self.reproduce['input'] and self.scaninputs:
pri... | code_fim | hard | {
"lang": "python",
"repo": "aekiss/payu",
"path": "/payu/manifest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aekiss/payu path: /payu/manifest.py
"""payu.manifest
===============
Provides an manifest class to store manifest data, which uses a
subclassed yamanifest PayuManifest class
:copyright: Copyright 2019 Aidan Heerdegen, see AUTHORS for details.
:license: Apache License, Version 2.0... | code_fim | hard | {
"lang": "python",
"repo": "aekiss/payu",
"path": "/payu/manifest.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if copy:
self.data[filepath]['copy'] = copy
if filepath in self.existing_filepaths:
self.existing_filepaths.remove(filepath)
return True
def add_fast(self, filepath, hashfn=None, force=False):
"""
Bespoke function to add filepaths but ... | code_fim | hard | {
"lang": "python",
"repo": "aekiss/payu",
"path": "/payu/manifest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_registered():
from ezdxf.entities.factory import ENTITY_CLASSES
assert "TOLERANCE" in ENTITY_CLASSES
def test_default_init():
entity = Tolerance()
assert entity.dxftype() == "TOLERANCE"
assert entity.dxf.handle is None
assert entity.dxf.owner is None
def test_default_... | code_fim | hard | {
"lang": "python",
"repo": "mozman/ezdxf",
"path": "/tests/test_02_dxf_graphics/test_238_tolerance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_load_from_text(entity):
assert entity.dxf.layer == "0"
assert entity.dxf.color == 256, "default color is 256 (by layer)"
assert entity.dxf.dimstyle == "Standard"
assert entity.dxf.insert == (0, 0, 0)
assert entity.dxf.extrusion == (0, 0, 1) # default value
assert entity.... | code_fim | hard | {
"lang": "python",
"repo": "mozman/ezdxf",
"path": "/tests/test_02_dxf_graphics/test_238_tolerance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mozman/ezdxf path: /tests/test_02_dxf_graphics/test_238_tolerance.py
# Copyright (c) 2019 Manfred Moitzi
# License: MIT License
import pytest
import ezdxf
from ezdxf.entities.tolerance import Tolerance
from ezdxf.lldxf.tagwriter import TagCollector, basic_tags_from_text
TOLERANCE = """0
TOLERANC... | code_fim | hard | {
"lang": "python",
"repo": "mozman/ezdxf",
"path": "/tests/test_02_dxf_graphics/test_238_tolerance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cabrittin/volumetric_analysis path: /scripts/dist_adj_subgrp2.py
"""
dist_adj_subgrp2.py
Plots adjacency degree distributions broken down by anatomical groups
created: Christopher Brittin
date: 01 November 2018
"""
import sys
sys.path.append(r'./volumetric_analysis')
import matplotlib.pyplot... | code_fim | hard | {
"lang": "python",
"repo": "cabrittin/volumetric_analysis",
"path": "/scripts/dist_adj_subgrp2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data = []
for i in range(len(n2u)):
data.append(n2u[i])
data.append(jsh[i])
fig,ax = plt.subplots(1,1,figsize=(15,10))
dist_adj_subgroups2(ax,data,fout=fout)
ax.xaxis.set_tick_params(labelsize=20)
plt.show()
if __name__ == '__main__':
run()<|fim_pref... | code_fim | hard | {
"lang": "python",
"repo": "cabrittin/volumetric_analysis",
"path": "/scripts/dist_adj_subgrp2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def group_degrees(db,_neuron_class):
_remove = ['VC01','VD01','VB01','VB02']
nclass = aux.read.into_dict(_neuron_class)
C = from_db(db,adjacency=True,remove=_remove)
C.A.assign_membership_dict(nclass,key='group')
sp_idx = get_group_index(C.A,['Sp1','Sp2'])
i1_idx = get_group_... | code_fim | hard | {
"lang": "python",
"repo": "cabrittin/volumetric_analysis",
"path": "/scripts/dist_adj_subgrp2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> hamster_files = glob.glob(osp.join(hamster_dir, jpeg))
hare_files = glob.glob(osp.join(hare_dir, jpeg))
all_files = list(hamster_files) + list(hare_files)
all_labels = [0] * len(hamster_files) + [1] * len(hare_files)
shuffle_lists(all_files, all_labels)
train_idx = int(len(all... | code_fim | hard | {
"lang": "python",
"repo": "hoangtnm/deep-learning",
"path": "/tutorials/Intel-TF101-Class8/helpers_07.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> hamster_dir = osp.join(parent_dir, "hamsterhare", "hamster")
hare_dir = osp.join(parent_dir, "hamsterhare", "hare")
jpeg = "*.JPEG"
hamster_files = glob.glob(osp.join(hamster_dir, jpeg))
hare_files = glob.glob(osp.join(hare_dir, jpeg))
all_files = list(hamster_files) + list(h... | code_fim | hard | {
"lang": "python",
"repo": "hoangtnm/deep-learning",
"path": "/tutorials/Intel-TF101-Class8/helpers_07.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hoangtnm/deep-learning path: /tutorials/Intel-TF101-Class8/helpers_07.py
import random, glob, sys
import os.path as osp
import tensorflow as tf
import numpy as np
from helpers_05 import grouper, flatten, fully_connected_layer
from helpers_06 import maybe_download, maybe_extract
def shuffle_arr... | code_fim | hard | {
"lang": "python",
"repo": "hoangtnm/deep-learning",
"path": "/tutorials/Intel-TF101-Class8/helpers_07.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wachjose88/local-lti-consumer path: /lti_consumer/manage.py
#!/usr/bin/env python
# Copyright (c) 2018 Josef Wachtler
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software... | code_fim | medium | {
"lang": "python",
"repo": "wachjose88/local-lti-consumer",
"path": "/lti_consumer/manage.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import os
import sys
if __name__ == "__main__":
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "lti_consumer.settings")
try:
from django.core.management import execute_from_command_line
except ImportError:
# The above import may fail for some other reason. Ensure that the
... | code_fim | medium | {
"lang": "python",
"repo": "wachjose88/local-lti-consumer",
"path": "/lti_consumer/manage.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gabrielgts/itapecerica-simulation path: /MapGenerator/mapGraphKepler.py
import matplotlib.pyplot as plt
import pandas as pd
import os
from six.moves import urllib
import pandas as pd # importing the Pandas Library as 'pd'
from keplergl import KeplerGl # importing KeplerGl
import geopandas as g... | code_fim | medium | {
"lang": "python",
"repo": "gabrielgts/itapecerica-simulation",
"path": "/MapGenerator/mapGraphKepler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>map.add_data(data=gdf, name="IQA") # add geoenabled dataframe to map
map.save_to_html(file_name='GeoViz.html')
map<|fim_prefix|># repo: gabrielgts/itapecerica-simulation path: /MapGenerator/mapGraphKepler.py
import matplotlib.pyplot as plt
import pandas as pd
import os
from six.moves import urllib
<|... | code_fim | hard | {
"lang": "python",
"repo": "gabrielgts/itapecerica-simulation",
"path": "/MapGenerator/mapGraphKepler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>dataset.head()
#Create a basemap
map = KeplerGl(height=600, width=800)
# Create a geodataframe
gdf = gpd.GeoDataFrame(
dataset, geometry=gpd.points_from_xy(dataset.latitude, dataset.longitude))
#make sure that your latitude and longitude are named as they are in your csv
map.add_data(data=gdf, n... | code_fim | medium | {
"lang": "python",
"repo": "gabrielgts/itapecerica-simulation",
"path": "/MapGenerator/mapGraphKepler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pipeline_builder = sdc_builder.get_pipeline_builder()
# Dev raw data source
dev_raw_data_source = pipeline_builder.add_stage('Dev Raw Data Source')
dev_raw_data_source.set_attributes(data_format='JSON',
raw_data=data,
... | code_fim | hard | {
"lang": "python",
"repo": "streamsets/datacollector-tests",
"path": "/stage/test_google_bigquery_enterprise_destination.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: streamsets/datacollector-tests path: /stage/test_google_bigquery_enterprise_destination.py
er_first_batch=True)
# Google BigQuery destination stage
bigquery = pipeline_builder.add_stage(name=DESTINATION_STAGE_NAME)
bigquery.set_attributes(project_id=gcp.project_id,
... | code_fim | hard | {
"lang": "python",
"repo": "streamsets/datacollector-tests",
"path": "/stage/test_google_bigquery_enterprise_destination.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
logger.info(f'Creating temporary bucket {bucket_name}')
bucket = gcp.retry_429(gcp.storage_client.create_bucket)(bucket_name)
logger.info('Creating dataset %s using Google BigQuery client ...', dataset_name)
bigquery_client.create_dataset(dataset_ref)
sdc... | code_fim | hard | {
"lang": "python",
"repo": "streamsets/datacollector-tests",
"path": "/stage/test_google_bigquery_enterprise_destination.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: soeque1/bert_torchserve path: /get_bert.py
from transformers import BertModel, BertTokenizer
def main():
<|fim_suffix|>if __name__ == "__main__":
main()<|fim_middle|> tokenizer = BertTokenizer.from_pretrained("bert-base-uncased", unk_token="<|unkwn|>")
tokenizer.save_vocabulary('bert'... | code_fim | hard | {
"lang": "python",
"repo": "soeque1/bert_torchserve",
"path": "/get_bert.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
main()<|fim_prefix|># repo: soeque1/bert_torchserve path: /get_bert.py
from transformers import BertModel, BertTokenizer
<|fim_middle|>def main():
tokenizer = BertTokenizer.from_pretrained("bert-base-uncased", unk_token="<|unkwn|>")
tokenizer.save_vocabulary('bert'... | code_fim | hard | {
"lang": "python",
"repo": "soeque1/bert_torchserve",
"path": "/get_bert.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> schema_stdout = capsys.readouterr().out
schema = yaml.load(schema_stdout, Loader=yaml.SafeLoader)
assert 'openapi' in schema
assert 'info' in schema
assert 'paths' in schema<|fim_prefix|># repo: MissiaL/drf-spectacular path: /tests/test_command.py
import yaml
from django.core import m... | code_fim | medium | {
"lang": "python",
"repo": "MissiaL/drf-spectacular",
"path": "/tests/test_command.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MissiaL/drf-spectacular path: /tests/test_command.py
import yaml
from django.core import management
<|fim_suffix|> schema_stdout = capsys.readouterr().out
schema = yaml.load(schema_stdout, Loader=yaml.SafeLoader)
assert 'openapi' in schema
assert 'info' in schema
assert 'paths... | code_fim | medium | {
"lang": "python",
"repo": "MissiaL/drf-spectacular",
"path": "/tests/test_command.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
exists = False
if get_occurrence_of_key(lookup_dict, key) > 0:
exists = True
return exists
def _key_list_search(self, keys_list, lookup_dict):
"""
Return the final value returned after iterating over keys_list.
In order to hand... | code_fim | hard | {
"lang": "python",
"repo": "ABORGT/PyConvertAlert",
"path": "/pyconvertalert/py_convert_alert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> lookup_key : str
This is the key we are looking up in our arbitrary alert json
structure to be assigned as the value of the transform_key.
lookup_dict : dict
This is the arbitrary alert we are searching for values to be
assigned to our trans... | code_fim | hard | {
"lang": "python",
"repo": "ABORGT/PyConvertAlert",
"path": "/pyconvertalert/py_convert_alert.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ABORGT/PyConvertAlert path: /pyconvertalert/py_convert_alert.py
#!/usr/bin/env python3
# -*_ coding: utf-8 -*-
#
"""
Simple library to convert an alert from an arbitrary alerting system to an
Alert Manager alert based on config.
"""
import json
import pathlib
import copy
from nested_lookup impor... | code_fim | hard | {
"lang": "python",
"repo": "ABORGT/PyConvertAlert",
"path": "/pyconvertalert/py_convert_alert.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mobiusklein/glycresoft path: /src/glycan_profiling/cli/base.py
import logging
import multiprocessing
import click
from glycan_profiling import version
from glycan_profiling.cli.logger_config import make_log_file_logger, LOG_FILE_MODE, LOG_LEVEL
CONTEXT_SETTINGS = dict(help_option_names=['-h', ... | code_fim | hard | {
"lang": "python",
"repo": "mobiusklein/glycresoft",
"path": "/src/glycan_profiling/cli/base.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
click.option = option
click.argument = argument
processes_option = click.option(
"-p", "--processes", 'processes', type=click.IntRange(1, multiprocessing.cpu_count()),
default=min(multiprocessing.cpu_count(), 4), help=('Number of worker processes to use. Defaults to 4 '
... | code_fim | medium | {
"lang": "python",
"repo": "mobiusklein/glycresoft",
"path": "/src/glycan_profiling/cli/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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