text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>me='property_created_by', to=settings.AUTH_USER_MODEL)),
],
),
migrations.CreateModel(
name='UrbanizedSector',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('n... | code_fim | hard | {
"lang": "python",
"repo": "dmatiasr/django-demo",
"path": "/mysite/RentApp/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>description_text_2 = StringVar()
e6 = Entry(tab2,textvariable=description_text_2,width=52)
e6.grid(row=0,column=1,columnspan=3)
manufacturer_text_2 = StringVar()
e7 = Entry(tab2,textvariable=manufacturer_text_2, state='disabled')
e7.grid(row=1,column=1)
quantity_text_2 = StringVar()
e8 = Entry(tab2,... | code_fim | hard | {
"lang": "python",
"repo": "ThayPedroso/myWarehouse",
"path": "/frontend.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ThayPedroso/myWarehouse path: /frontend.py
"""
A program that stores materials in a warehouse:
Description, Manufacturer, Code
Quantity, BarCode
User can:
View all records
Search an entry
Add entry
Update entry
Delete
Close
"""
from tkinter import *
from backend import Database
from tkinter i... | code_fim | hard | {
"lang": "python",
"repo": "ThayPedroso/myWarehouse",
"path": "/frontend.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>init = tf.keras.initializers.glorot_normal(seed=SEED)
encoder_model = tf.keras.Sequential([
tf.keras.layers.Conv2D(filters=32,kernel_size=3,strides=(2,2),activation=tf.nn.relu, padding="same",kernel_initializer=init),
tf.keras.layers.MaxPool2D(pool_size=(2, 2)),
tf.keras.layers.Conv2D(filters=... | code_fim | hard | {
"lang": "python",
"repo": "Rufaim/tensorflow-2-variational-autoencoder",
"path": "/train_vae.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Rufaim/tensorflow-2-variational-autoencoder path: /train_vae.py
import os
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as pyplot
from models import Encoder, VariationalAutoEncoder
BATCH_SIZE = 32
MNIST_SHAPE = [28, 28, 1]
LATENT_DIM = 12
EPOCHS = 25
LEARNING_RATE = 1e-3
... | code_fim | hard | {
"lang": "python",
"repo": "Rufaim/tensorflow-2-variational-autoencoder",
"path": "/train_vae.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> prediction = vae.predict(test_portion)
fig = pyplot.figure(figsize=(4,4))
for i in range(prediction.shape[0]):
pyplot.subplot(4,4,i+1)
pyplot.imshow(prediction[i,...,0],cmap="gray")
pyplot.axis("off")
pyplot.savefig(os.path.join(LOGDIR,f"epoch_{epoch}.png"))
pyp... | code_fim | hard | {
"lang": "python",
"repo": "Rufaim/tensorflow-2-variational-autoencoder",
"path": "/train_vae.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if args.x == 1:
f = f1
else:
f = f2
t = time.time()
f()
print(time.time() - t)
if __name__ == '__main__':
main()<|fim_prefix|># repo: xkumiyu/python-speed-comp path: /stdin.py
import time
import argparse
def f1():
N = int(input())
[int(input()) for _ i... | code_fim | medium | {
"lang": "python",
"repo": "xkumiyu/python-speed-comp",
"path": "/stdin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
parser = argparse.ArgumentParser()
parser.add_argument('x', type=int)
args = parser.parse_args()
if args.x == 1:
f = f1
else:
f = f2
t = time.time()
f()
print(time.time() - t)
if __name__ == '__main__':
main()<|fim_prefix|># repo: xkumiy... | code_fim | medium | {
"lang": "python",
"repo": "xkumiyu/python-speed-comp",
"path": "/stdin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xkumiyu/python-speed-comp path: /stdin.py
import time
import argparse
def f1():
N = int(input())
[int(input()) for _ in range(N)]
def f2():
import sys
input = sys.stdin.readline
<|fim_suffix|>
def main():
parser = argparse.ArgumentParser()
parser.add_argument('x', typ... | code_fim | easy | {
"lang": "python",
"repo": "xkumiyu/python-speed-comp",
"path": "/stdin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joshuabhk/tcr-dist path: /analyze_gene_frequencies.py
## look at frequencies and enrichments of genes
##
## what makes this a little tricky is that gene assignments can be ambiguous: sequence reads
## are often too short to uniquely define the gene, especially in mouse V-alpha where there are
## ... | code_fim | hard | {
"lang": "python",
"repo": "joshuabhk/tcr-dist",
"path": "/analyze_gene_frequencies.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if jsd<best_jsd:
#print '******'
best_logfile = logfile
best_jsd = jsd
best_bg_freq = bg_freq
best_tcr_freq = tcr_freq
else:
pass
#pri... | code_fim | hard | {
"lang": "python",
"repo": "joshuabhk/tcr-dist",
"path": "/analyze_gene_frequencies.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
vgg = vgg16.VGG16(weights='imagenet', include_top=True)
vgg.summary()
# load the vgg into the deoxys model
deo = Model(vgg)
# load an real image
img = load_image('../../test_img/cat.jpg')
# predict what is in that image
preds = deo.predict(img)... | code_fim | hard | {
"lang": "python",
"repo": "huynhngoc/deoxys",
"path": "/examples/visualization_vgg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: huynhngoc/deoxys path: /examples/visualization_vgg.py
from deoxys.model import load_model, Model
import numpy as np
import matplotlib.pyplot as plt
from deoxys.utils import is_keras_standalone
if is_keras_standalone():
from keras.applications import vgg16
from keras.applications.vgg16 imp... | code_fim | hard | {
"lang": "python",
"repo": "huynhngoc/deoxys",
"path": "/examples/visualization_vgg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # load an real image
img = load_image('../../test_img/cat.jpg')
# predict what is in that image
preds = deo.predict(img)
predicted_class = preds.argmax(axis=1)[0]
print("predicted top1 class:", predicted_class)
print('Predicted:', decode_predictions(preds, top=1)[0])
# V... | code_fim | hard | {
"lang": "python",
"repo": "huynhngoc/deoxys",
"path": "/examples/visualization_vgg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> corpus: ProviderBase,
title: Optional[str] = None,
set_type: SetType = SetType.DEV) -> Dict[str, float]:
"""
Function evaluates metrics for documents from corpus after processing with passed processo... | code_fim | hard | {
"lang": "python",
"repo": "serge-sotnyk/tesufr",
"path": "/tesufr/keysum_evaluator/evaluators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: serge-sotnyk/tesufr path: /tesufr/keysum_evaluator/evaluators.py
from collections import defaultdict
from typing import Dict, Set, List, Sequence, Optional
from tqdm.auto import tqdm
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
from nltk.tokenize import word_tokenize... | code_fim | hard | {
"lang": "python",
"repo": "serge-sotnyk/tesufr",
"path": "/tesufr/keysum_evaluator/evaluators.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def evaluate_processor_on_corpus(processor: Processor,
corpus: ProviderBase,
title: Optional[str] = None,
set_type: SetType = SetType.DEV) -> Dict[str, float]:
"""
Function evaluates metrics for doc... | code_fim | hard | {
"lang": "python",
"repo": "serge-sotnyk/tesufr",
"path": "/tesufr/keysum_evaluator/evaluators.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Honglongwu/bioinformatics-scripts path: /cafe_to_dupliphy_input.py
#!/usr/bin/env python
""" Lets the user convert a cafe input format file to a DupliPHY input format file
Requires the CAFE file to be in the format DESCRIPTION\tID\tSpecies1\tSpecies2... etc
Creates the new input file and a m... | code_fim | medium | {
"lang": "python",
"repo": "Honglongwu/bioinformatics-scripts",
"path": "/cafe_to_dupliphy_input.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># assign inputfile and check exists
inputfile = args[1]
if not os.path.exists(inputfile):
print "The filename (%s) you specified does not exist" % inputfile
sys.exit()
# set output filename and let user know we are converting
outputfile = inputfile.split('.')[0] + ".dupliphy"
mappingfile = outp... | code_fim | medium | {
"lang": "python",
"repo": "Honglongwu/bioinformatics-scripts",
"path": "/cafe_to_dupliphy_input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: riogesulgon/vimiv path: /vimiv/transform.py
# vim: ft=python fileencoding=utf-8 sw=4 et sts=4
"""Deals with transformations like rotate and flip and deleting files."""
import os
from threading import Thread
from gi.repository import GObject
from vimiv import imageactions
from vimiv.exceptions i... | code_fim | hard | {
"lang": "python",
"repo": "riogesulgon/vimiv",
"path": "/vimiv/transform.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Start thread for rotate and flip."""
# TODO improve this, it is currently not possible to find out what is
# being changed and what should still be done
if self.threads_running:
return
if settings["autosave_images"].get_value():
t = Thread... | code_fim | hard | {
"lang": "python",
"repo": "riogesulgon/vimiv",
"path": "/vimiv/transform.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DataEdgeSystems/datalake-etl-pipeline path: /test/aws_test/glue_job.py
import sys
from pyspark.context import SparkContext
# https://github.com/aws-samples/aws-glue-samples/tree/master/examples
<|fim_suffix|>def _commit_job(job):
job.commit()
def _get_glue_args(cli_args):
from awsgl... | code_fim | hard | {
"lang": "python",
"repo": "DataEdgeSystems/datalake-etl-pipeline",
"path": "/test/aws_test/glue_job.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> job.commit()
def _get_glue_args(cli_args):
from awsglue.utils import getResolvedOptions
glue_args = getResolvedOptions(args=cli_args, options=["JOB_NAME", "source", "destination"])
print(glue_args)
return glue_args
if __name__ == "__main__":
run(["source", "destination"])<|fim_... | code_fim | hard | {
"lang": "python",
"repo": "DataEdgeSystems/datalake-etl-pipeline",
"path": "/test/aws_test/glue_job.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> from awsglue.utils import getResolvedOptions
glue_args = getResolvedOptions(args=cli_args, options=["JOB_NAME", "source", "destination"])
print(glue_args)
return glue_args
if __name__ == "__main__":
run(["source", "destination"])<|fim_prefix|># repo: DataEdgeSystems/datalake-etl-pipe... | code_fim | hard | {
"lang": "python",
"repo": "DataEdgeSystems/datalake-etl-pipeline",
"path": "/test/aws_test/glue_job.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tonyle9/tensorimage path: /tensorimage/util/convnet_builder.py
from tensorimage.train import models
architectures = [
('AlexNet', models.AlexNet),
('RosNet', models.RosNet),
]
class ConvNetBuilder:
def __init__(self, architecture):
self.architecture = architecture
def... | code_fim | medium | {
"lang": "python",
"repo": "tonyle9/tensorimage",
"path": "/tensorimage/util/convnet_builder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for avarchs in architectures:
if self.architecture == avarchs[0]:
return avarchs[1]
def check_exist(architecture):
for avarch in architectures:
if architecture == avarch[0]:
return True
else:
continue
return False<|fim_p... | code_fim | medium | {
"lang": "python",
"repo": "tonyle9/tensorimage",
"path": "/tensorimage/util/convnet_builder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pranavlathigara/Raspberry-Pi-DIY-Projects path: /smart-projects/python-bluezero/bluezero/blinkt.py
"""
This is a simple API to access the Pimoroni Blinkt device.
This is the central API. The peripheral is created with
examples/level100/blinkt_ble.py
"""
from time import sleep
import logging
try:... | code_fim | hard | {
"lang": "python",
"repo": "pranavlathigara/Raspberry-Pi-DIY-Projects",
"path": "/smart-projects/python-bluezero/bluezero/blinkt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.blnkt = device.Device(device_path[0])
self.blinkt_srv_path = None
self.blinkt_chrc_path = None
@property
def connected(self):
"""Indicate whether the remote device is currently connected."""
return self.blnkt.connected
def connect(self):
... | code_fim | hard | {
"lang": "python",
"repo": "pranavlathigara/Raspberry-Pi-DIY-Projects",
"path": "/smart-projects/python-bluezero/bluezero/blinkt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>inspect_file_attrs(file_path).close()<|fim_prefix|># repo: SDRAST/support path: /hdf5_util/examples/inspect_file_attrs_example.py
import os
import h5py
from support.hdf5_util import inspect_file_attrs
current_dir = os.path.dirname(os.path.abspath(__file__))
<|fim_middle|>file_path = os.path.join(curr... | code_fim | medium | {
"lang": "python",
"repo": "SDRAST/support",
"path": "/hdf5_util/examples/inspect_file_attrs_example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SDRAST/support path: /hdf5_util/examples/inspect_file_attrs_example.py
import os
import h5py
from support.hdf5_util import inspect_file_attrs
current_dir = os.path.dirname(os.path.abspath(__file__))
<|fim_suffix|>inspect_file_attrs(file_path).close()<|fim_middle|>file_path = os.path.join(curr... | code_fim | medium | {
"lang": "python",
"repo": "SDRAST/support",
"path": "/hdf5_util/examples/inspect_file_attrs_example.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>file_path = os.path.join(current_dir, "example.hdf5")
with h5py.File(file_path, "w") as f:
f.attrs["first_name"] = "dill"
f.attrs["last_name"] = "pickle"
f.attrs["age"] = 0.1
inspect_file_attrs(file_path).close()<|fim_prefix|># repo: SDRAST/support path: /hdf5_util/examples/inspect_file_attr... | code_fim | easy | {
"lang": "python",
"repo": "SDRAST/support",
"path": "/hdf5_util/examples/inspect_file_attrs_example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: appatsekhar/pytext path: /pytext/models/embeddings/char_embedding.py
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from typing import List, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from pytext.config.field_config... | code_fim | hard | {
"lang": "python",
"repo": "appatsekhar/pytext",
"path": "/pytext/models/embeddings/char_embedding.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Highway(nn.Module):
"""
A `Highway layer <https://arxiv.org/abs/1505.00387>`.
Adopted from the AllenNLP implementation.
"""
def __init__(self, input_dim: int, num_layers: int = 1):
super().__init__()
self.input_dim = input_dim
self.layers = nn.ModuleList(... | code_fim | hard | {
"lang": "python",
"repo": "appatsekhar/pytext",
"path": "/pytext/models/embeddings/char_embedding.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return aepe_with_hfem
elif add_hfem.lower() == 'edges' and edges is not None:
# Reshape into height x width (was batch x height x width x 1 to be fed to the network)
# aepe_hfem_edges = lambda * edges_img * epe_img
epe_times_edges = tf.multiply(epe, ... | code_fim | hard | {
"lang": "python",
"repo": "fperezgamonal/flownet2-tf",
"path": "/src/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fperezgamonal/flownet2-tf path: /src/utils.py
t(tf.pow(2, tf.cast(cycle - 1, tf.int32)), tf.float32))
if mode == 'exponential' and not one_cycle:
cmom = tf.multiply(tf.pow(gamma, global_step), cmom)
return tf.subtract(max_mom, cmom, name=op_name)
# Momentum is kep... | code_fim | hard | {
"lang": "python",
"repo": "fperezgamonal/flownet2-tf",
"path": "/src/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> indices = tf.stack([b, y, x], 3)
return tf.gather_nd(img, indices)
def tf_warp(img, flow, H, W):
# H = 256
# W = 256
x,y = tf.meshgrid(tf.range(W), tf.range(H))
x = tf.expand_dims(x,0)
x = tf.expand_dims(x,-1)
y = tf.expand_dims(y,0)
y = tf.expand_dims(y,-1)
... | code_fim | hard | {
"lang": "python",
"repo": "fperezgamonal/flownet2-tf",
"path": "/src/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bndl/bndl path: /bndl/compute/dataset.py
5, 15), (6, 16), (7, 17), (8, 18), (9, 19)]
'''
# TODO what if some partition is shorter/longer than another?
return self.zip_partitions(other, zip)
def zip_partitions(self, other, comb):
'''
Zip the partitions... | code_fim | hard | {
"lang": "python",
"repo": "bndl/bndl",
"path": "/bndl/compute/dataset.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _convert_for_save(self, mode, compression, ext):
if mode not in ('t', 'b'):
raise ValueError('mode should be t(ext) or b(inary)')
data = self
# compress if necessary
if compression is not None:
if mode == 't':
data = data.map(... | code_fim | hard | {
"lang": "python",
"repo": "bndl/bndl",
"path": "/bndl/compute/dataset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def itake(self, num):
'''
Take the first num elements from this dataset as iterator.
'''
assert self.ctx.running, 'context of dataset is not running'
remaining = num
sliced = self.map_partitions(partial(take, remaining))._itake_parts()
try:
... | code_fim | hard | {
"lang": "python",
"repo": "bndl/bndl",
"path": "/bndl/compute/dataset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tangermi/nlp path: /src/demo/_tensorflow/linear/linear.py
# -*- coding: utf-8 -*-
import tensorflow as tf
class Linear(tf.keras.Model):
def __init__(self):
super().__init__()
self.dense = tf.keras.layers.Dense(
units=1,
activation=None,
ke... | code_fim | medium | {
"lang": "python",
"repo": "tangermi/nlp",
"path": "/src/demo/_tensorflow/linear/linear.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
X = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
y = tf.constant([[10.0], [20.0]])
model = Linear()
optimizer = tf.keras.optimizers.SGD(learning_rate=0.01)
for i in range(100):
with tf.GradientTape() as tape:
y_pred = model(X) # 调用模型 ... | code_fim | medium | {
"lang": "python",
"repo": "tangermi/nlp",
"path": "/src/demo/_tensorflow/linear/linear.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> output = self.dense(input)
return output
if __name__ == '__main__':
X = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
y = tf.constant([[10.0], [20.0]])
model = Linear()
optimizer = tf.keras.optimizers.SGD(learning_rate=0.01)
for i in range(100):
with tf.Gra... | code_fim | hard | {
"lang": "python",
"repo": "tangermi/nlp",
"path": "/src/demo/_tensorflow/linear/linear.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> url = '/admin/webhooks/'
response = webhook_admin_client.get(url)
assert response.status_code == 200<|fim_prefix|># repo: byceps/byceps path: /tests/integration/blueprints/admin/webhook/test_views.py
"""
:Copyright: 2014-2023 Jochen Kupperschmidt
:License: Revised BSD (see `LICENSE` file for ... | code_fim | easy | {
"lang": "python",
"repo": "byceps/byceps",
"path": "/tests/integration/blueprints/admin/webhook/test_views.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: byceps/byceps path: /tests/integration/blueprints/admin/webhook/test_views.py
"""
:Copyright: 2014-2023 Jochen Kupperschmidt
:License: Revised BSD (see `LICENSE` file for details)
"""
<|fim_suffix|> url = '/admin/webhooks/'
response = webhook_admin_client.get(url)
assert response.stat... | code_fim | easy | {
"lang": "python",
"repo": "byceps/byceps",
"path": "/tests/integration/blueprints/admin/webhook/test_views.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wingify/vwo-python-sdk path: /vwo/api/get_feature_variable_value.py
# Copyright 2019-2022 Wingify Software Pvt. Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#... | code_fim | hard | {
"lang": "python",
"repo": "wingify/vwo-python-sdk",
"path": "/vwo/api/get_feature_variable_value.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not variable:
# Log variable not found
vwo_instance.logger.log(
LogLevelEnum.ERROR,
LogMessageEnum.ERROR_MESSAGES.VARIABLE_NOT_FOUND.format(
file=FILE,
variable_key=variable_key,
campaign_key=campaign_key,
... | code_fim | hard | {
"lang": "python",
"repo": "wingify/vwo-python-sdk",
"path": "/vwo/api/get_feature_variable_value.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = ["extent", "percentile"]<|fim_prefix|># repo: lace/polliwog path: /polliwog/pointcloud/__init__.py
"""
Functions for working with point clouds (i.e. unstructured sets of 3D points).
"""
<|fim_middle|>from ._pointcloud_functions import extent, percentile
| code_fim | easy | {
"lang": "python",
"repo": "lace/polliwog",
"path": "/polliwog/pointcloud/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lace/polliwog path: /polliwog/pointcloud/__init__.py
"""
Functions for working with point clouds (i.e. unstructured sets of 3D points).
"""
<|fim_suffix|>__all__ = ["extent", "percentile"]<|fim_middle|>from ._pointcloud_functions import extent, percentile
| code_fim | easy | {
"lang": "python",
"repo": "lace/polliwog",
"path": "/polliwog/pointcloud/__init__.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: FuckBrains/tw-fb-yt-datacollection path: /get_youtube_data.py
import requests, shutil,json,time, codecs, csv,sys
import pickle, os
from datetime import datetime
#Downloads data from YouTube. You may need to run this script several times as the API rate limit is limiting.
chans = ['YOUTUBE_ID_OF... | code_fim | hard | {
"lang": "python",
"repo": "FuckBrains/tw-fb-yt-datacollection",
"path": "/get_youtube_data.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
s=requests.Session()
for chan in chans:
if not chan.strip() or os.path.isfile('vidlist/%s.p'% chan):
continue
url = 'https://www.googleapis.com/youtube/v3/search?key=' + API_KEY +'&channelId=' + chan + '&part=snippet,id&order=date&maxResults=50'
print(chan)
first = datetime.... | code_fim | hard | {
"lang": "python",
"repo": "FuckBrains/tw-fb-yt-datacollection",
"path": "/get_youtube_data.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yaz/yaz path: /yaz/test/test_single_method.py
#!/usr/bin/env python3
import yaz
class SingleMethod(yaz.Plugin):
@yaz.task
def talk(self):
return "I have very little to say."
class Test(yaz.TestCase):
<|fim_suffix|> """When only a single plugin with only a single method... | code_fim | medium | {
"lang": "python",
"repo": "yaz/yaz",
"path": "/yaz/test/test_single_method.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Test(yaz.TestCase):
def test_010(self):
"""When only a single plugin with only a single method is available, then this should be called without needing to specify the plugin or task name"""
caller = self.get_caller([SingleMethod])
self.assertEqual("I have very little to ... | code_fim | medium | {
"lang": "python",
"repo": "yaz/yaz",
"path": "/yaz/test/test_single_method.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Get options
options = []
if length > 2:
options = sys.argv[2:length]
# Invoke the command
command.execute(options)
#print("Execute the command!")
if __name__ == '__main__':
main()<|fim_prefix|># repo: thomaspenin/orchid-font-tool path: /... | code_fim | hard | {
"lang": "python",
"repo": "thomaspenin/orchid-font-tool",
"path": "/orchid",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thomaspenin/orchid-font-tool path: /orchid
#!/usr/bin/env python3
# Main entry point for the Orchid Font Tool
# Call "./orchid help" for a list of supported commands
<|fim_suffix|> # Invoke the command
command.execute(options)
#print("Execute the command!")
if __name__ =... | code_fim | hard | {
"lang": "python",
"repo": "thomaspenin/orchid-font-tool",
"path": "/orchid",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Acrisel/eventor path: /eventor/concepts/sshcmd_popen.py
#!/usr/bin/env python3
# adopted from https://gist.github.com/bortzmeyer/1284249
# Here is the right solution today:
<|fim_suffix|> ssh = subprocess.Popen(["ssh", where, command],
shell=False,
... | code_fim | hard | {
"lang": "python",
"repo": "Acrisel/eventor",
"path": "/eventor/concepts/sshcmd_popen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ssh = subprocess.Popen(["ssh", where, command],
shell=False,
stdin=stdin,
stdout=stdout,
stderr=stderr,)
return ssh
if __name__ == '__main__':
pcomm = sshcmd("acrisel", "ls -l",)
... | code_fim | hard | {
"lang": "python",
"repo": "Acrisel/eventor",
"path": "/eventor/concepts/sshcmd_popen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TestingIaCwithNewAccount/aws-advanced path: /lambda/codeCommit.py
import boto3
import json
from botocore.vendored import requests
import logging
import os
import sys
import base64
logger = logging.getLogger()
logger.setLevel(logging.INFO)
s3_client = boto3.client('s3')
s3 = boto3.resource('s3'... | code_fim | hard | {
"lang": "python",
"repo": "TestingIaCwithNewAccount/aws-advanced",
"path": "/lambda/codeCommit.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># # # # # # # # # # # # # # # code to try clone the Repo from CodeCommit and upload to S3
#cloning(bucket)
#bucket = os.environ['bucket']
#s3.Bucket(bucket).download_file(filename, '/tmp/error.html')
#s3.meta.client.upload_file('/tmp/index.html', bucket, 'index.html')
#print(os.pat... | code_fim | hard | {
"lang": "python",
"repo": "TestingIaCwithNewAccount/aws-advanced",
"path": "/lambda/codeCommit.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Create a fake resource
res = ResourceBase(manager=manager, interface=interf, resID='DEBUG')
res.open = mock.Mock(return_value=True)
res.isOpen = mock.Mock(return_value=True)
res.close = mock.Mock(return_value=True)
# Create a fake driver
driver = DriverBase
driver.open =... | code_fim | hard | {
"lang": "python",
"repo": "caizikun/labtronyx",
"path": "/tests/test_drivers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: caizikun/labtronyx path: /tests/test_drivers.py
import unittest
from nose.tools import * # PEP8 asserts
import mock
import labtronyx
from labtronyx.bases import ResourceBase, DriverBase, InterfaceBase
def test_drivers():
manager = labtronyx.InstrumentManager()
for driver_uuid, driver... | code_fim | hard | {
"lang": "python",
"repo": "caizikun/labtronyx",
"path": "/tests/test_drivers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return name.replace('pool','p').replace('norm','n')
# offline scripts configuration
caffevis_outputs_dir = base_folder + './models/indoor/outputs'
layers_to_output_in_offline_scripts = ['conv1', 'conv2', 'conv3', 'conv4', 'conv5', 'fc1', 'fc2', 'fc3', 'prob']<|fim_prefix|># repo: vpulab/MobiNetVideo_... | code_fim | medium | {
"lang": "python",
"repo": "vpulab/MobiNetVideo_CNN_Visualization",
"path": "/model_settings/settings_indoor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vpulab/MobiNetVideo_CNN_Visualization path: /model_settings/settings_indoor.py
# basic network configuration
base_folder = '%DVT_ROOT%/'
caffevis_deploy_prototxt = base_folder + './models/indoor/alexnet_indoor.prototxt'
caffevis_network_weights = base_folder + './models/indoor/alexnet_indoor.caf... | code_fim | medium | {
"lang": "python",
"repo": "vpulab/MobiNetVideo_CNN_Visualization",
"path": "/model_settings/settings_indoor.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: msincenselee/vnpy path: /vnpy/gateway/bitmex/bitmex_gateway.py
uest):
""""""
self.rest_api.cancel_order(req)
def query_account(self):
""""""
pass
def query_position(self):
""""""
pass
def query_history(self, req: HistoryRequest):
... | code_fim | hard | {
"lang": "python",
"repo": "msincenselee/vnpy",
"path": "/vnpy/gateway/bitmex/bitmex_gateway.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Record exception if not ConnectionError
if not issubclass(exception_type, ConnectionError):
self.on_error(exception_type, exception_value, tb, request)
def on_send_order(self, data, request):
"""Websocket will push a new order status"""
self.update_rate_l... | code_fim | hard | {
"lang": "python",
"repo": "msincenselee/vnpy",
"path": "/vnpy/gateway/bitmex/bitmex_gateway.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: msincenselee/vnpy path: /vnpy/gateway/bitmex/bitmex_gateway.py
pi.stop()
self.ws_api.stop()
def process_timer_event(self, event: Event):
""""""
self.rest_api.reset_rate_limit()
class BitmexRestApi(RestClient):
"""
BitMEX REST API
"""
def __init__(se... | code_fim | hard | {
"lang": "python",
"repo": "msincenselee/vnpy",
"path": "/vnpy/gateway/bitmex/bitmex_gateway.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Muntaha-Islam0019/HackerRank-Solutions path: /Problem Solving/Algorithms/Sherlock and Array.py
#!/bin/python3
import math
import os
import random
import re
import sys
#
# Complete the 'balancedSums' function below.
#
# The function is expected to return arr STRING.
# The function accepts INTEGE... | code_fim | hard | {
"lang": "python",
"repo": "Muntaha-Islam0019/HackerRank-Solutions",
"path": "/Problem Solving/Algorithms/Sherlock and Array.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> T = int(input().strip())
for T_itr in range(T):
n = int(input().strip())
arr = list(map(int, input().rstrip().split()))
result = balancedSums(arr)
fptr.write(result + '\n')
fptr.close()<|fim_prefix|># repo: Muntaha-Islam0019/HackerRank-Solutions path: /Pro... | code_fim | medium | {
"lang": "python",
"repo": "Muntaha-Islam0019/HackerRank-Solutions",
"path": "/Problem Solving/Algorithms/Sherlock and Array.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: naoki-mizuno/initialpose_publisher path: /nodes/initialpose_publisher.py
#!/usr/bin/env python2
import rospy
import tf2_ros
from geometry_msgs.msg import PoseWithCovarianceStamped
from geometry_msgs.msg import PoseStamped
import sys
if __name__ != '__main__':
sys.stderr('This program nee... | code_fim | hard | {
"lang": "python",
"repo": "naoki-mizuno/initialpose_publisher",
"path": "/nodes/initialpose_publisher.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
try:
transform = buf.lookup_transform(map_frame_id,
base_frame_id,
rospy.Time(0),
rospy.Duration(3))
break
except t... | code_fim | medium | {
"lang": "python",
"repo": "naoki-mizuno/initialpose_publisher",
"path": "/nodes/initialpose_publisher.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _verify_sudo():
''' we just check if the user is sudoers '''
sudo('cd .')
def _add_postgres9_ppa():
''' add postgresql 9.x ppa '''
if 'Ubuntu 12.04' not in sudo('cat /etc/issue.net'):
sudo('add-apt-repository ppa:pitti/postgresql')
def _install_dependencies():
''' Ensu... | code_fim | hard | {
"lang": "python",
"repo": "denimboy/pg_fabrep",
"path": "/pg_fabrep/tasks.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def parameter_default_values():
if 'postgres_version' not in env:
env.postgres_version = '9.1'
if 'cluster_name' not in env:
env.cluster_name = 'main'
if 'cluster_port' not in env:
env.cluster_port = 5432
if 'pgmaster_ip' not in env:
env.pgmaster_ip = ''
... | code_fim | hard | {
"lang": "python",
"repo": "denimboy/pg_fabrep",
"path": "/pg_fabrep/tasks.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: denimboy/pg_fabrep path: /pg_fabrep/tasks.py
')
pg_fabrep_path = dirname(abspath(__file__))
#########################
## START pg_fabrep tasks ##
#########################
@task
def setup():
parameter_default_values()
# test configuration start
if not test_configuration():
... | code_fim | hard | {
"lang": "python",
"repo": "denimboy/pg_fabrep",
"path": "/pg_fabrep/tasks.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frank-bailey/axonius_api_client path: /axonius_api_client/tests/tests_cli/test_cli_serial.py
# -*- coding: utf-8 -*-
"""Test suite for axonius_api_client.tools."""
from __future__ import absolute_import, division, print_function, unicode_literals
import pytest
from axonius_api_client import cli... | code_fim | hard | {
"lang": "python",
"repo": "frank-bailey/axonius_api_client",
"path": "/axonius_api_client/tests/tests_cli/test_cli_serial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Pass."""
rows = [{"cnx": [{"id": "1"}]}, {"id": "2"}, {"cnx": {"id": "3"}}]
x = cli.serial.collapse_rows(rows=rows, key="cnx")
exp = [{"id": "1"}, {"id": "2"}, {"id": "3"}]
assert x == exp
class TestCliObjToCsv(object):
"""Pass."""
def test_default(sel... | code_fim | hard | {
"lang": "python",
"repo": "frank-bailey/axonius_api_client",
"path": "/axonius_api_client/tests/tests_cli/test_cli_serial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_default(self):
"""Pass."""
ctx = utils.get_mockctx()
rows = [{"id": "1"}, {"id": "2"}, {"id": "3"}]
this_cmd = "bad wolf check --rows"
src_cmds = ["bad wolf get"]
keys = ["id"]
cli.serial.ensure_keys(
ctx=ctx,
row... | code_fim | hard | {
"lang": "python",
"repo": "frank-bailey/axonius_api_client",
"path": "/axonius_api_client/tests/tests_cli/test_cli_serial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hihellobolke/nomadgen path: /examples/redis.py
from nomadgen.jobspec.ttypes import *
from nomadgen.jobspec.constants import *
from nomadgen.util import export_if_last
from common.resources import CommonResources
from copy import deepcopy
job=Job(
Name='redis',
ID='redis',
Datacenters... | code_fim | hard | {
"lang": "python",
"repo": "hihellobolke/nomadgen",
"path": "/examples/redis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>rkt_task.Driver="rkt"
rkt_task.Config.image="docker://redis:3.2"
rkt_task.Config.port_map=[{'db': '6379-tcp'}]
qemu_tg = deepcopy(tg)
qemu_task = deepcopy(task)
qemu_tg.Name='qemu'
qemu_task.Driver="qemu"
qemu_task.Config=Config(
image_path="osv-redis-memonly-v0.24.qemu.qcow2",
accelerator="kvm... | code_fim | hard | {
"lang": "python",
"repo": "hihellobolke/nomadgen",
"path": "/examples/redis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def is_malformed(self):
return True<|fim_prefix|># repo: bobjects/BobStack path: /bobstack/sipmessaging/malformedSIPMessage.py
from sipMessage import SIPMessage
<|fim_middle|>
class MalformedSIPMessage(SIPMessage):
@classmethod
def new_for_attributes(cls, start_line=Non... | code_fim | hard | {
"lang": "python",
"repo": "bobjects/BobStack",
"path": "/bobstack/sipmessaging/malformedSIPMessage.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bobjects/BobStack path: /bobstack/sipmessaging/malformedSIPMessage.py
from sipMessage import SIPMessage
class MalformedSIPMessage(SIPMessage):
<|fim_suffix|> @property
def is_malformed(self):
return True<|fim_middle|> @classmethod
def new_for_attributes(cls, start_line=Non... | code_fim | medium | {
"lang": "python",
"repo": "bobjects/BobStack",
"path": "/bobstack/sipmessaging/malformedSIPMessage.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zachwood0s/dnd-inventory path: /sanctum_dnd/commands/help_text.py
DICE_FMT = '<dice_fmt>'
PLAYER = '<player>'
TRAIT = '<trait>'
ITEM_ID = '<it<|fim_suffix|>ABILITY = '<players_ability>'
EFFECT_ID = '<effect_id>'
PLAYERS_EFFECT = '<players_effect>'
ANY_ID = '<any_id>'
VALUE = '<value>'
OBJ_TYPE = ... | code_fim | medium | {
"lang": "python",
"repo": "zachwood0s/dnd-inventory",
"path": "/sanctum_dnd/commands/help_text.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>layers_effect>'
ANY_ID = '<any_id>'
VALUE = '<value>'
OBJ_TYPE = '<obj_type>'<|fim_prefix|># repo: zachwood0s/dnd-inventory path: /sanctum_dnd/commands/help_text.py
DICE_FMT = '<dice_fmt>'
PLAYER = '<player>'
TRAIT = '<trait>'
ITEM_ID = '<it<|fim_middle|>em_id>'
PLAYERS_ITEM = '<players_item>'
ABILITY_ID... | code_fim | medium | {
"lang": "python",
"repo": "zachwood0s/dnd-inventory",
"path": "/sanctum_dnd/commands/help_text.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wangyum/Anaconda path: /pkgs/networkx-1.11-py27_0/lib/python2.7/site-packages/networkx/testing/utils.py
import operator
from nose.tools import *
__all__ = ['assert_nodes_equal', 'assert_edges_equal','assert_graphs_equal']
def assert_nodes_equal(nlist1, nlist2):
# Assumes lists are either nod... | code_fim | hard | {
"lang": "python",
"repo": "wangyum/Anaconda",
"path": "/pkgs/networkx-1.11-py27_0/lib/python2.7/site-packages/networkx/testing/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def assert_graphs_equal(graph1, graph2):
if graph1.is_multigraph():
edges1 = graph1.edges(data=True,keys=True)
else:
edges1 = graph1.edges(data=True)
if graph2.is_multigraph():
edges2 = graph2.edges(data=True,keys=True)
else:
edges2 = graph2.edges(data=True... | code_fim | hard | {
"lang": "python",
"repo": "wangyum/Anaconda",
"path": "/pkgs/networkx-1.11-py27_0/lib/python2.7/site-packages/networkx/testing/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kyaing/KDYSample path: /kYPython/Spider/spider_basic/spider_teiba.py
#coding: utf-8
import urllib.request
import ssl
""" 抓取百度贴吧数据 """
def loadPage(url, fileName):
""" 通过url发送请求，获取服务器响应文件 """
request = urllib.request.Request(url)
context = ssl._create_unverified_context()
response = urllib... | code_fim | medium | {
"lang": "python",
"repo": "kyaing/KDYSample",
"path": "/kYPython/Spider/spider_basic/spider_teiba.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ 将html内容写到本地 """
with open(fileName, 'w') as f:
f.write(fileName)
def teibaSpider(url, beginPage, endPage):
for page in range(beginPage, endPage+1):
if beginPage == 0:
pn = 0
else:
pn = (page - 1) * 50
fileName = "第" + str(page) + "页.html"
fullUrl = url + "&pn=" + str(pn)
loadPa... | code_fim | medium | {
"lang": "python",
"repo": "kyaing/KDYSample",
"path": "/kYPython/Spider/spider_basic/spider_teiba.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: getlogbook/logbook path: /tests/test_logger.py
import pytest
import logbook
def test_level_properties(logger):
assert logger.level == logbook.NOTSET
assert logger.level_name == "NOTSET"
logger.level_name = "WARNING"
assert logger.level == logbook.WARNING
logger.level = logb... | code_fim | medium | {
"lang": "python",
"repo": "getlogbook/logbook",
"path": "/tests/test_logger.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_disabled_property():
class MyLogger(logbook.Logger):
@property
def disabled(self):
return True
logger = MyLogger()
with pytest.raises(AttributeError):
logger.enable()
with pytest.raises(AttributeError):
logger.disable()<|fim_prefix|>... | code_fim | hard | {
"lang": "python",
"repo": "getlogbook/logbook",
"path": "/tests/test_logger.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: StorjOld/upstream path: /tests/test_streamer.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# The MIT License (MIT)
#
# Copyright (c) 2014 Paul Durivage for Storj Labs
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentati... | code_fim | hard | {
"lang": "python",
"repo": "StorjOld/upstream",
"path": "/tests/test_streamer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @mock.patch('requests.post')
def test_upload_sharded_encoded(self, post):
with self.assertRaises(NotImplementedError):
self.stream._upload_sharded_encoded('http://fake.url', 'fake.path')
@mock.patch('requests.post')
def test_filestream(self, post):
with self.as... | code_fim | hard | {
"lang": "python",
"repo": "StorjOld/upstream",
"path": "/tests/test_streamer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = "NextIO.vNet"
pattern_syntax_error = rb"^ERROR: Invalid command -"
pattern_operation_error = rb"^ERROR: "
pattern_prompt = rb"^(?P<hostname>\S+)> "<|fim_prefix|># repo: nocproject/noc path: /sa/profiles/NextIO/vNet/profile.py
# -----------------------------------------------------... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/sa/profiles/NextIO/vNet/profile.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Profile(BaseProfile):
name = "NextIO.vNet"
pattern_syntax_error = rb"^ERROR: Invalid command -"
pattern_operation_error = rb"^ERROR: "
pattern_prompt = rb"^(?P<hostname>\S+)> "<|fim_prefix|># repo: nocproject/noc path: /sa/profiles/NextIO/vNet/profile.py
# ------------------------... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/sa/profiles/NextIO/vNet/profile.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nocproject/noc path: /sa/profiles/NextIO/vNet/profile.py
# ---------------------------------------------------------------------
# Vendor: NextIO
# OS: vNet
# ---------------------------------------------------------------------
# Copyright (C) 2007-2013 The NOC Project
# See LICENSE for deta... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/sa/profiles/NextIO/vNet/profile.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = [
'bounding_box',
'calculate_origin_offset',
'max_energy_slice',
'sitk_new_blank_image',
'sitk_resample_to_spacing',
'sitk_resample_to_shape', 'sitk_resample_to_image',
'subdirs',
'now',
'LookupConfig'
]<|fim_prefix|># repo: mahdeto/delira path: /delira/utils... | code_fim | medium | {
"lang": "python",
"repo": "mahdeto/delira",
"path": "/delira/utils/__init__.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mahdeto/delira path: /delira/utils/__init__.py
from .imageops import bounding_box, calculate_origin_offset, max_energy_slice, \
sitk_new_blank_image, sitk_resample_to_image, sitk_resample_to_shape, \
sitk_resample_to_spacing
<|fim_suffix|>from .config import LookupConfig
__all__ = [
... | code_fim | medium | {
"lang": "python",
"repo": "mahdeto/delira",
"path": "/delira/utils/__init__.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> for job in as_completed(futures):
job.result()
r = futures[job]
logging.info("Part {} Completed.".format(r))
logging.info('Distances calculated.')
t1 = time()
logging.info('Time : {}m'.format((t1-t0)/60))
return
def calc_distances(self, compactDegree = False):
logging.in... | code_fim | hard | {
"lang": "python",
"repo": "leoribeiro/struc2vec",
"path": "/src/struc2vec.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leoribeiro/struc2vec path: /src/struc2vec.py
# -*- coding: utf-8 -*-
import numpy as np
import random,sys,logging
from concurrent.futures import ProcessPoolExecutor, as_completed
from multiprocessing import Manager
from time import time
from collections import deque
from utils import *
from alg... | code_fim | hard | {
"lang": "python",
"repo": "leoribeiro/struc2vec",
"path": "/src/struc2vec.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
with ProcessPoolExecutor(max_workers = self.workers) as executor:
part = 1
for c in chunks:
logging.info("Executing part {}...".format(part))
job = executor.submit(calc_distances, part, compactDegree = compactDegree)
futures[job] = part
part += 1
logging.info("Receiving res... | code_fim | hard | {
"lang": "python",
"repo": "leoribeiro/struc2vec",
"path": "/src/struc2vec.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gganssle/mixture-density-networks path: /scripts/numba_test.py
import numba
import numpy as np
<|fim_suffix|>%%timeit
mully(one,two)<|fim_middle|>one = np.ones((10000,10000))
two = np.ones((10000,10000))
def mully(a,b):
np.matmul(a,b)
%%timeit
mully(one, two)
@numba.jit
def mully(a,b):
... | code_fim | medium | {
"lang": "python",
"repo": "gganssle/mixture-density-networks",
"path": "/scripts/numba_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gganssle/mixture-density-networks path: /scripts/numba_test.py
import numba
import numpy as np
one = np.ones((10000,10000))
two = np.ones((10000,10000))
<|fim_suffix|>%%timeit
mully(one,two)<|fim_middle|>def mully(a,b):
np.matmul(a,b)
%%timeit
mully(one, two)
@numba.jit
def mully(a,b):
... | code_fim | medium | {
"lang": "python",
"repo": "gganssle/mixture-density-networks",
"path": "/scripts/numba_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>%%timeit
mully(one, two)
@numba.jit
def mully(a,b):
np.matmul(a,b)
%%timeit
mully(one,two)<|fim_prefix|># repo: gganssle/mixture-density-networks path: /scripts/numba_test.py
import numba
import numpy as np
one = np.ones((10000,10000))
two = np.ones((10000,10000))
def mully(a,b):
<|fim_middle|> ... | code_fim | easy | {
"lang": "python",
"repo": "gganssle/mixture-density-networks",
"path": "/scripts/numba_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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