text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> # pylint: disable=arguments-differ
def set_value(self, on_level):
"""Set the value of the state from the handlers."""
if on_level in FanSpeedRange.OFF:
fan_speed = FanSpeed.OFF
elif on_level in FanSpeedRange.LOW:
fan_speed = FanSpeed.LOW
elif... | code_fim | hard | {
"lang": "python",
"repo": "pyinsteon/pyinsteon",
"path": "/pyinsteon/groups/fan.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self, name: str, address: Address, group: int = 0, default: FanSpeed = None
):
"""Init the FanOnLevel class."""
super().__init__(name, address, group, default, value_type=FanSpeed)
# pylint: disable=arguments-differ
def set_value(self, on_level):
"""Set the val... | code_fim | medium | {
"lang": "python",
"repo": "pyinsteon/pyinsteon",
"path": "/pyinsteon/groups/fan.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_find_next_page() -> None:
"""Check if find_next_page method returns correct url"""
html_doc = """
<html>
<head><title>Example text</title></head>
<body><a class="_za9j7e" href="/test">Text to extract</a></body>
</html>
... | code_fim | hard | {
"lang": "python",
"repo": "GQ21/airbnb-scraper",
"path": "/tests/test_scraper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GQ21/airbnb-scraper path: /tests/test_scraper.py
import os
import sys
from bs4 import BeautifulSoup
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from airbnb.scraper import Scraper
scraper = Scraper()
def get_status() -> None:
"""Check if webdriver is... | code_fim | hard | {
"lang": "python",
"repo": "GQ21/airbnb-scraper",
"path": "/tests/test_scraper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_write_dataframe() -> None:
"""Check if write_dataframe method writes .csv file"""
scraper.write_dataframe()
assert os.path.isfile("Airbnb.csv") == True
scraper.quit()<|fim_prefix|># repo: GQ21/airbnb-scraper path: /tests/test_scraper.py
import os
import sys
from bs4 import Beautifu... | code_fim | hard | {
"lang": "python",
"repo": "GQ21/airbnb-scraper",
"path": "/tests/test_scraper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = [
"PushRuntimeDecisionContext",
"ReconfigurationRuntimeDecisionContext",
"smart_cache_workload_generator_config_space",
"smart_cache_workload_generator_default_config",
]<|fim_prefix|># repo: amueller/MLOS path: /source/Mlos.Python/mlos/Examples/SmartCache/MlosInterface/__i... | code_fim | hard | {
"lang": "python",
"repo": "amueller/MLOS",
"path": "/source/Mlos.Python/mlos/Examples/SmartCache/MlosInterface/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amueller/MLOS path: /source/Mlos.Python/mlos/Examples/SmartCache/MlosInterface/__init__.py
#
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
#
""" Contains all classes required for SmartCache to talk to Mlos
"""
<|fim_suffix|>__all__ = [
"PushRuntimeDecis... | code_fim | hard | {
"lang": "python",
"repo": "amueller/MLOS",
"path": "/source/Mlos.Python/mlos/Examples/SmartCache/MlosInterface/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: janelia-flyem/cluster-calclabels path: /CalcLabelOrchestration/orchestration/calclabels_cluster.py
args.append(options.roi)
if docomputeprob:
# program will handle the fact that there is a uniform buffer in the prediction file
args.append("--prediction-f... | code_fim | hard | {
"lang": "python",
"repo": "janelia-flyem/cluster-calclabels",
"path": "/CalcLabelOrchestration/orchestration/calclabels_cluster.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # wait for job completion
wait_for_jobs(cluster_session, job_ids, message, "agglomerate")
# write status: 'performed watershed'
message.write_status("performed agglomeration")
# launch reduce jobs and wait
job_ids = []
job_num = 0
... | code_fim | hard | {
"lang": "python",
"repo": "janelia-flyem/cluster-calclabels",
"path": "/CalcLabelOrchestration/orchestration/calclabels_cluster.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> config["offset"] = self.id_offset
config["bbox1"] = [self.roi.x1, self.roi.y1, self.roi.z1]
config["bbox2"] = [self.roi.x2, self.roi.y2, self.roi.z2]
config["border"] = self.border
config["labels"] = self.session_location + "/segmentation.h5"
config["labelso... | code_fim | hard | {
"lang": "python",
"repo": "janelia-flyem/cluster-calclabels",
"path": "/CalcLabelOrchestration/orchestration/calclabels_cluster.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vnsai/python path: /DataScience/Python3/Level-2/AddofMatrix.py
#addition of two matrix elements
_author__ = "Dilipbobby"
<|fim_suffix|>Result = [[0,0,0],
[0,0,0],
[0,0,0]]
# iterate through rows
for i in range(len(X)):
# iterate through columns
... | code_fim | medium | {
"lang": "python",
"repo": "vnsai/python",
"path": "/DataScience/Python3/Level-2/AddofMatrix.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>Result = [[0,0,0],
[0,0,0],
[0,0,0]]
# iterate through rows
for i in range(len(X)):
# iterate through columns
for j in range(len(A[0])):
#aadition of elements
result[i][j] = A[i][j] + B[i][j]
for r in result:
print(r)<|fim_prefix|># repo: v... | code_fim | medium | {
"lang": "python",
"repo": "vnsai/python",
"path": "/DataScience/Python3/Level-2/AddofMatrix.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> A = [5, 9, 100, 9, 97, 6, 9, 98, 9]
self.assertEqual(mmm(A), (38.0, 9, 9))
if __name__=="__main__":
unittest.main()<|fim_prefix|># repo: JiniousChoi/encyclopedia-in-code path: /mooc/udacity/st101/my_avg.py
#!/usr/bin/env python3
import unittest
def mean(A):
return sum(A)/len(A)... | code_fim | medium | {
"lang": "python",
"repo": "JiniousChoi/encyclopedia-in-code",
"path": "/mooc/udacity/st101/my_avg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def mmm(A):
A.sort()
return mean(A), median(A), mode(A)
class MyAvgTest(unittest.TestCase):
def test_method1(self):
A = [5, 9, 100, 9, 97, 6, 9, 98, 9]
self.assertEqual(mmm(A), (38.0, 9, 9))
if __name__=="__main__":
unittest.main()<|fim_prefix|># repo: JiniousChoi/encyclo... | code_fim | medium | {
"lang": "python",
"repo": "JiniousChoi/encyclopedia-in-code",
"path": "/mooc/udacity/st101/my_avg.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JiniousChoi/encyclopedia-in-code path: /mooc/udacity/st101/my_avg.py
#!/usr/bin/env python3
import unittest
def mean(A):
return sum(A)/len(A)
def median(A):
<|fim_suffix|> A = [5, 9, 100, 9, 97, 6, 9, 98, 9]
self.assertEqual(mmm(A), (38.0, 9, 9))
if __name__=="__main__":
... | code_fim | hard | {
"lang": "python",
"repo": "JiniousChoi/encyclopedia-in-code",
"path": "/mooc/udacity/st101/my_avg.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from numpy import inf
name = "sc_paracrystal"
title = "Simple cubic lattice with paracrystalline distortion"
description = """
P(q)=(scale/Vp)*V_lattice*P(q)*Z(q)+bkg where scale is the volume
fraction of sphere,
Vp = volume of the primary particle,
V_lattice = volume corr... | code_fim | hard | {
"lang": "python",
"repo": "SasView/sasmodels",
"path": "/explore/sc.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SasView/sasmodels path: /explore/sc.py
r"""
Calculates the scattering from a **simple cubic lattice** with
paracrystalline distortion. Thermal vibrations are considered to be
negligible, and the size of the paracrystal is infinitely large.
Paracrystalline distortion is assumed to be isotropic and... | code_fim | hard | {
"lang": "python",
"repo": "SasView/sasmodels",
"path": "/explore/sc.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> CLONE = 'clone'
BACKUPNOW = 'backupNow'
FIELDMESSAGE = 'fieldMessage'
BULKINSTALLAPP = 'bulkInstallApp'
TIERING = 'tiering'
ANALYSIS = 'analysis'
AGENTUPGRADETASK = 'agentUpgradeTask'<|fim_prefix|># repo: cohesity/management-sdk-python path: /cohesity_management_sdk/mode... | code_fim | medium | {
"lang": "python",
"repo": "cohesity/management-sdk-python",
"path": "/cohesity_management_sdk/models/task_type_enum.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
RESTORE = 'restore'
CLONE = 'clone'
BACKUPNOW = 'backupNow'
FIELDMESSAGE = 'fieldMessage'
BULKINSTALLAPP = 'bulkInstallApp'
TIERING = 'tiering'
ANALYSIS = 'analysis'
AGENTUPGRADETASK = 'agentUpgradeTask'<|fim_prefix|># repo: cohesity/management-sdk-python p... | code_fim | hard | {
"lang": "python",
"repo": "cohesity/management-sdk-python",
"path": "/cohesity_management_sdk/models/task_type_enum.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cohesity/management-sdk-python path: /cohesity_management_sdk/models/task_type_enum.py
# -*- coding: utf-8 -*-
# Copyright 2023 Cohesity Inc.
class TaskTypeEnum(object):
"""Implementation of the 'TaskType' enum.
Task type denotes which type of task this notification is for. This param
... | code_fim | medium | {
"lang": "python",
"repo": "cohesity/management-sdk-python",
"path": "/cohesity_management_sdk/models/task_type_enum.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: maxoyed/CQU_2021_Spring_Python018 path: /题库/第2至3章练习/编程题/4.计算跑道长度/__main__.py
name = input()
a = float(input())
v = float(input())
leng<|fim_suffix|> the shortest take-off runway length is {length:.2f} M.")<|fim_middle|>th = v * v / (2 * a)
print(f"The acceleration of {name} is {a:.2f} M / s, the ... | code_fim | medium | {
"lang": "python",
"repo": "maxoyed/CQU_2021_Spring_Python018",
"path": "/题库/第2至3章练习/编程题/4.计算跑道长度/__main__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> the shortest take-off runway length is {length:.2f} M.")<|fim_prefix|># repo: maxoyed/CQU_2021_Spring_Python018 path: /题库/第2至3章练习/编程题/4.计算跑道长度/__main__.py
name = input()
a = float(input())
v = float(input())
leng<|fim_middle|>th = v * v / (2 * a)
print(f"The acceleration of {name} is {a:.2f} M / s, the ... | code_fim | medium | {
"lang": "python",
"repo": "maxoyed/CQU_2021_Spring_Python018",
"path": "/题库/第2至3章练习/编程题/4.计算跑道长度/__main__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sweattep/EditFrontMatter path: /examples/example1/example1.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
*Basic Front Matter Editing Example*
====================================
.. module:: example1
.. program:: example1
:Synopsis: Example program that performs the following actions:... | code_fim | hard | {
"lang": "python",
"repo": "sweattep/EditFrontMatter",
"path": "/examples/example1/example1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
# generic path - overridden by env var `TEST_DATA_DIR`
DATA_PATH = "../data/"
if "TEST_DATA_DIR" in os.environ:
DATA_PATH = os.path.abspath(os.environ.get("TEST_DATA_DIR")) + "/"
# set path to input file
file_path = os.path.abspath(DATA_PATH + "example1.md")
# i... | code_fim | hard | {
"lang": "python",
"repo": "sweattep/EditFrontMatter",
"path": "/examples/example1/example1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> a, b, c = logit_probs.shape[0], logit_probs.shape[1], logit_probs.shape[2]
logit_probs = self.logsoftmax(self.reshape(logit_probs, (-1, c)))
logit_probs = self.reshape(logit_probs, (a, b, c))
log_probs = log_probs + logit_probs
if self.reduce:
return -s... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/audio/wavenet/wavenet_vocoder/mixture.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mindspore-ai/models path: /research/audio/wavenet/wavenet_vocoder/mixture.py
# Copyright 2021 Huawei Technologies Co., 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 ... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/audio/wavenet/wavenet_vocoder/mixture.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.log_op(1 + self.exp_op(- self.abs_op(x))) + self.relu_op(x)
class discretized_mix_logistic_loss(nn.Cell):
"""
Discretized_mix_logistic_loss
Args:
num_classes (int): Num_classes
log_scale_min (float): Log scale minimum value
"""
def __init__(self... | code_fim | hard | {
"lang": "python",
"repo": "mindspore-ai/models",
"path": "/research/audio/wavenet/wavenet_vocoder/mixture.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not pid and not name:
rc, out, err = j.sal.process.execute("ps ax")
click.echo(out)
elif name:
click.echo(j.sal.process.psfind(name))
elif pid:
click.echo(j.sal.process.getProcessPid(pid))
if __name__ == "__main__":
list_processes()<|fim_prefix|># repo: ... | code_fim | hard | {
"lang": "python",
"repo": "AhmedSa-mir/cl-tools",
"path": "/scripts/list-processes.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AhmedSa-mir/cl-tools path: /scripts/list-processes.py
#!/usr/bin/env python3
from Jumpscale import j
import click
@click.command()
@click.option('--pid', '-p', help='Get PID of process with this name')
@click.option('--name', '-n', help='Check whether a process with this name exists or not')
de... | code_fim | medium | {
"lang": "python",
"repo": "AhmedSa-mir/cl-tools",
"path": "/scripts/list-processes.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
acc_avg_steps = 100
SPL_avg_steps = 250
metrics_to_plot = ["train_acc", "valid_acc", "SPL"] # , "sparse_reward"
parent_dir = os.path.join("rslts", "1022_log")
if not os.path.exists("plots"):
os.mkdir("plots")
performance_dict = {}
... | code_fim | hard | {
"lang": "python",
"repo": "junyaoshi/feedback-navigation",
"path": "/feedback-robot-learning/simulation_and_analysis/husky_hf_loss_analysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> array_to_avg = np.asarray(list_to_avg)
array_to_avg = array_to_avg.reshape(array_to_avg.shape[0], -1)
array_to_avg = np.where(np.isnan(array_to_avg), 0, array_to_avg)
array_cum_sum = np.copy(array_to_avg)
for i in range(1, array_to_avg.shape[1]):
array_cum_sum[:, i] = arra... | code_fim | hard | {
"lang": "python",
"repo": "junyaoshi/feedback-navigation",
"path": "/feedback-robot-learning/simulation_and_analysis/husky_hf_loss_analysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: junyaoshi/feedback-navigation path: /feedback-robot-learning/simulation_and_analysis/husky_hf_loss_analysis.py
import os
import json
import math
import pickle
import numpy as np
import matplotlib.pyplot as plt
def append_or_create_list_for_key(dict, key, ele):
if key in dict:
... | code_fim | hard | {
"lang": "python",
"repo": "junyaoshi/feedback-navigation",
"path": "/feedback-robot-learning/simulation_and_analysis/husky_hf_loss_analysis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param genomes: The list of genomes to evolve in some way.
:param pool: The pool of processes to use for work.
:param params: The dictionary of user-specified parameters.
:return: A new list of modified genomes.
"""
pass<|fim_prefix|># repo: wbknez/evored-wa... | code_fim | hard | {
"lang": "python",
"repo": "wbknez/evored-warrior",
"path": "/evored/algorithm/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wbknez/evored-warrior path: /evored/algorithm/__init__.py
"""
Contains all classes and functions designed to make a uniform API for
performing different evolutionary operations on a list of genomes.
"""
from abc import abstractmethod, ABCMeta
class EvolvingAlgorithm(metaclass=ABCMeta):
"""
... | code_fim | hard | {
"lang": "python",
"repo": "wbknez/evored-warrior",
"path": "/evored/algorithm/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>graph = [[(1, 10), (2, 7), (3, 3)], [(0, 10), (3, 5), (4, 20)], [(0, 7), (4, 11), (7, 8)],
[(0, 3), (1, 5), (4, 14), (5, 5)], [(1, 20), (2, 11), (3, 14), (6, 8)], [(3, 5), (6, 9)],
[(4, 8), (5, 9), (7, 13)], [(2, 8), (6, 13), (8, 10)], [(7, 10)]]
t = 3
print(safe_flight(graph, t, 8))<|fi... | code_fim | hard | {
"lang": "python",
"repo": "adam147g/ASD_exercises_solutions",
"path": "/Exercises/Exercise_08/09_exercise.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adam147g/ASD_exercises_solutions path: /Exercises/Exercise_08/09_exercise.py
# Dany jest graf G = (V, E), którego wierzchołki reprezentują punkty nawigacyjne nad Bajtocją,
# a krawędzie reprezentują korytarze powietrzne między tymi punktami. Każdy korytarz powietrzny
# e[i] ∈ E powiązany jest z o... | code_fim | hard | {
"lang": "python",
"repo": "adam147g/ASD_exercises_solutions",
"path": "/Exercises/Exercise_08/09_exercise.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (func_result):
if not result:
result = func_result
else:
result += func_result
return result<|fim_prefix|># repo: DanPalmz/pyecwid path: /pyecwid/ecwidutils.py
def get_attribute_json(attribute_id, value):
return {
"attrib... | code_fim | hard | {
"lang": "python",
"repo": "DanPalmz/pyecwid",
"path": "/pyecwid/ecwidutils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DanPalmz/pyecwid path: /pyecwid/ecwidutils.py
def get_attribute_json(attribute_id, value):
return {
"attributes": [
{
"id": attribute_id,
"value": value
},
]
}
<|fim_suffix|> result = False
for item in items:... | code_fim | hard | {
"lang": "python",
"repo": "DanPalmz/pyecwid",
"path": "/pyecwid/ecwidutils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> root.startRendering()
## [ogre_to_np]
mem = np.empty((win.getHeight(), win.getWidth(), 3), dtype=np.uint8)
pb = Ogre.PixelBox(win.getWidth(), win.getHeight(), 1, Ogre.PF_BYTE_RGB, mem)
win.copyContentsToMemory(pb, pb)
## [ogre_to_np]
## [zero_copy_view]
pyplot.ims... | code_fim | hard | {
"lang": "python",
"repo": "OGRECave/ogre",
"path": "/Samples/Python/numpy_sample.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ## [ogre_to_np]
mem = np.empty((win.getHeight(), win.getWidth(), 3), dtype=np.uint8)
pb = Ogre.PixelBox(win.getWidth(), win.getHeight(), 1, Ogre.PF_BYTE_RGB, mem)
win.copyContentsToMemory(pb, pb)
## [ogre_to_np]
## [zero_copy_view]
pyplot.imsave("screenshot.png", mem)
... | code_fim | hard | {
"lang": "python",
"repo": "OGRECave/ogre",
"path": "/Samples/Python/numpy_sample.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OGRECave/ogre path: /Samples/Python/numpy_sample.py
import Ogre
import Ogre.Bites
import Ogre.RTShader
import numpy as np
from matplotlib import pyplot
def main():
app = Ogre.Bites.ApplicationContext("PySample")
app.initApp()
root = app.getRoot()
scn_mgr = root.createSceneM... | code_fim | hard | {
"lang": "python",
"repo": "OGRECave/ogre",
"path": "/Samples/Python/numpy_sample.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # for i in range(len(weights)):
# if weights[i] > 1.0:
# weights[i] = 1.0
# else:
# continue
total = np.sum(weights)
return np.asarray(weights / total, order='C')
def train_classify(self, clf, trans_data, trans_la... | code_fim | hard | {
"lang": "python",
"repo": "holacola1985/tradaboost",
"path": "/Fed_main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def train_classify(self, clf, trans_data, trans_label, test_data, P): # AdaBoost
clf.fit(trans_data, trans_label, sample_weight=P[0:len(trans_label), ])
updated_model = clf
# for clf, w in zip(clf.estimators_, clf.estimator_weights_):
# updated_model.append(clf... | code_fim | hard | {
"lang": "python",
"repo": "holacola1985/tradaboost",
"path": "/Fed_main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: holacola1985/tradaboost path: /Fed_main.py
# -*- coding: UTF-8 -*-
import numpy
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn import metrics
import pickle
from sklearn import tree
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import... | code_fim | hard | {
"lang": "python",
"repo": "holacola1985/tradaboost",
"path": "/Fed_main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># phi(m*n) = phi(m)*phi(n) if gcd(m,n) == 1
# prime phi(p) = p-1
def phi(number):
root = math.floor(math.sqrt(number))
result = 1
i = 0
t = prime[i]
while t <= root:
count = 0
while number%t == 0:
count += 1
number = number//t
if count > ... | code_fim | medium | {
"lang": "python",
"repo": "Adamssss/projectEuler",
"path": "/Problem 001-150 Python/pb069.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Adamssss/projectEuler path: /Problem 001-150 Python/pb069.py
import math
import time
t1 = time.time()
prime = [2,3]
b = 3
while True:
if b > 1000:
break
while True:
b = b+2
i = 0
t = True
while (prime[i]*prime[i] < b):
i=i+1
... | code_fim | hard | {
"lang": "python",
"repo": "Adamssss/projectEuler",
"path": "/Problem 001-150 Python/pb069.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ps = [0,1]
# phi(m*n) = phi(m)*phi(n) if gcd(m,n) == 1
# prime phi(p) = p-1
def phi(number):
root = math.floor(math.sqrt(number))
result = 1
i = 0
t = prime[i]
while t <= root:
count = 0
while number%t == 0:
count += 1
number = number//t
... | code_fim | medium | {
"lang": "python",
"repo": "Adamssss/projectEuler",
"path": "/Problem 001-150 Python/pb069.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> del01_prostori = forms.BooleanField(initial=False, required=False)
# prostori = forms.BooleanField(initial=False, required=False)<|fim_prefix|># repo: vasjapavlovic/eda5 path: /eda5/import/forms/import_lokacija_forms.py
from django import forms
<|fim_middle|># potrditev ali žeiliš uvoziti ali ne... | code_fim | medium | {
"lang": "python",
"repo": "vasjapavlovic/eda5",
"path": "/eda5/import/forms/import_lokacija_forms.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vasjapavlovic/eda5 path: /eda5/import/forms/import_lokacija_forms.py
from django import forms
<|fim_suffix|> del01_prostori = forms.BooleanField(initial=False, required=False)
# prostori = forms.BooleanField(initial=False, required=False)<|fim_middle|># potrditev ali žeiliš uvoziti ali ne... | code_fim | medium | {
"lang": "python",
"repo": "vasjapavlovic/eda5",
"path": "/eda5/import/forms/import_lokacija_forms.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def initialize(self, opt):
self.opt = opt
# directories
self.dataroot = opt.dataroot
self.image_dir = os.path.join(opt.dataroot, 'images')
self.uvs_dir = os.path.join(opt.dataroot, 'uvs')
# debug print
if opt.verbose:
print('load se... | code_fim | hard | {
"lang": "python",
"repo": "suzhenwang86/NeuralTexGen",
"path": "/data/uv_dataset.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> UV = transforms.ToTensor()(uv_numpy.astype(np.float32))
UV = torch.where(UV > 1.0, torch.zeros_like(UV), UV)
UV = torch.where(UV < 0.0, torch.zeros_like(UV), UV)
UV = 2.0 * UV - 1.0
## img
img_fname = os.path.join(self.image_dir, str(id) + '.jpg')
i... | code_fim | hard | {
"lang": "python",
"repo": "suzhenwang86/NeuralTexGen",
"path": "/data/uv_dataset.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suzhenwang86/NeuralTexGen path: /data/uv_dataset.py
import os.path
import random
import torchvision.transforms as transforms
import torch
import numpy as np
from data.base_dataset import BaseDataset
from PIL import Image
from util import util
from scipy.misc import imresize
def make_dataset_exr_... | code_fim | hard | {
"lang": "python",
"repo": "suzhenwang86/NeuralTexGen",
"path": "/data/uv_dataset.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: david58/gradertools path: /gradertools/compilation/interface.py
class CompilerInterface:
def __init__(self, sourcepath):
self.sourcepath = sourcepath
self._binarypath = None
self._status = None
self._error = None
def compile(self, isolator):
... | code_fim | easy | {
"lang": "python",
"repo": "david58/gradertools",
"path": "/gradertools/compilation/interface.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_status(self):
return self._status
def get_error(self):
return self._error<|fim_prefix|># repo: david58/gradertools path: /gradertools/compilation/interface.py
class CompilerInterface:
def __init__(self, sourcepath):
self.sourcepath = sourcepath
se... | code_fim | medium | {
"lang": "python",
"repo": "david58/gradertools",
"path": "/gradertools/compilation/interface.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_error(self):
return self._error<|fim_prefix|># repo: david58/gradertools path: /gradertools/compilation/interface.py
class CompilerInterface:
def __init__(self, sourcepath):
self.sourcepath = sourcepath
self._binarypath = None
self._status = None
... | code_fim | medium | {
"lang": "python",
"repo": "david58/gradertools",
"path": "/gradertools/compilation/interface.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xz725/TFSecured path: /python/encrypt_model.py
import base64
import hashlib
import os
import sys
import string
import random
try:
from Crypto import Random
from Crypto.Cipher import AES
except:
raise Exception('Install Crypto! \n pip install pycrypto')
try:
import tensorflow as t... | code_fim | hard | {
"lang": "python",
"repo": "xz725/TFSecured",
"path": "/python/encrypt_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def read_arg(index, default=None, err_msg=None):
def print_error():
if err_msg is not None:
raise Exception(err_msg)
else:
raise Exception('Not found arg with index %s' % index)
if len(sys.argv) <= index:
if default is not None:
return d... | code_fim | hard | {
"lang": "python",
"repo": "xz725/TFSecured",
"path": "/python/encrypt_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: laincloud/redis-libs path: /test/write_data.py
import random
import redis
import logging
import time
REDIS_HOST = '127.0.0.1'
REDIS_PORT = 7001
DEBUG = 1
TIMEOUT = 10
r = redis.StrictRedis(host=REDIS_HOST,port=REDIS_PORT,socket_timeout=TIMEOUT)
<|fim_suffix|> try:
global key
... | code_fim | medium | {
"lang": "python",
"repo": "laincloud/redis-libs",
"path": "/test/write_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def write_data_with_redis_client(*args):
try:
global key
key = random.randint(1,100000)
value = random.randint(1,100000)
res = str(r.set(key,value))
print 'redisclient set '+ str(key) + '\'s value: '+ str(value) + " : "+ str(res)
except Exception as e:
... | code_fim | medium | {
"lang": "python",
"repo": "laincloud/redis-libs",
"path": "/test/write_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
while True:
write_data_with_redis_client()
time.sleep(1)<|fim_prefix|># repo: laincloud/redis-libs path: /test/write_data.py
import random
import redis
import logging
import time
REDIS_HOST = '127.0.0.1'
REDIS_PORT = 7001
DEBUG = 1
TIMEOUT = 10
r = redis.S... | code_fim | hard | {
"lang": "python",
"repo": "laincloud/redis-libs",
"path": "/test/write_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>pos = parser.airdump_parser(ap_list, client_list, refresh_time=100, elast_time=99999999, save_file_name="aaaa", is_show=False)
'''
for i in range(10):
pos = monitor.airdump_parser(ap_list, client_list, pos)
'''
print(pos)<|fim_prefix|># repo: lanfis/WiFi_Monitor path: /test.py
#!/usr/bin/env pyt... | code_fim | hard | {
"lang": "python",
"repo": "lanfis/WiFi_Monitor",
"path": "/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lanfis/WiFi_Monitor path: /test.py
#!/usr/bin/env python
# license removed for brevity
import os
import sys
current_folder = os.path.dirname(os.path.realpath(__file__))
sys.path.append(current_folder)
import numpy as np
from parser import PARSER
parser = PARSER()
'''
monitor.init()
... | code_fim | medium | {
"lang": "python",
"repo": "lanfis/WiFi_Monitor",
"path": "/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ort Network
from .optimizer import Optimizer<|fim_prefix|># repo: yubin1219/GAN path: /StyleGAN/dnnlib/tflib/__init__.py
from . import autosummary
from . import netw<|fim_middle|>ork
from . import optimizer
from . import tfutil
from .tfutil import *
from .network imp | code_fim | medium | {
"lang": "python",
"repo": "yubin1219/GAN",
"path": "/StyleGAN/dnnlib/tflib/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yubin1219/GAN path: /StyleGAN/dnnlib/tflib/__init__.py
from . import autosummary
from . import netw<|fim_suffix|>util
from .tfutil import *
from .network import Network
from .optimizer import Optimizer<|fim_middle|>ork
from . import optimizer
from . import tf | code_fim | easy | {
"lang": "python",
"repo": "yubin1219/GAN",
"path": "/StyleGAN/dnnlib/tflib/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bmoretz/Python-Playground path: /src/Classes/MSDS400/Module 7/drug_reaction.py
from sympy import symbols, integrate, Rational, lambdify, sqrt
import matplotlib.pyplot as plt
import numpy as np
<|fim_suffix|>t = symbols( 't', positive = True )
dR = ( 2 / ( t + 1 ) ) + ( 2 / sqrt( t + 1 ) )
# wh... | code_fim | medium | {
"lang": "python",
"repo": "bmoretz/Python-Playground",
"path": "/src/Classes/MSDS400/Module 7/drug_reaction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>x_vals = np.linspace( g_xlim[0], g_xlim[1], 1000, endpoint=True )
y_vals = lam_p( x_vals )
plt.plot( x_vals, y_vals )
plt.show()<|fim_prefix|># repo: bmoretz/Python-Playground path: /src/Classes/MSDS400/Module 7/drug_reaction.py
from sympy import symbols, integrate, Rational, lambdify, sqrt
import matplo... | code_fim | hard | {
"lang": "python",
"repo": "bmoretz/Python-Playground",
"path": "/src/Classes/MSDS400/Module 7/drug_reaction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
print
cc = ca.code[:1] \
+ [(LOAD_CONST, 4)] \
+ ca.code[2:4] \
+ [(LOAD_CONST, 2),(STORE_FAST, 'b'),(SetLineno, 4)] \
+ ca.code[4:5] \
+ [(LOAD_FAST, 'b'),(BINARY_ADD, None)] \
+ ca.code[5:]
print "before",
a()
ca.code = cc
a.func_code = ca.to_code()
print "after",
a()<|fim_prefix|># repo: evandri... | code_fim | medium | {
"lang": "python",
"repo": "evandrix/Splat",
"path": "/doc/pycodeutils_using_byteplay.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: evandrix/Splat path: /doc/pycodeutils_using_byteplay.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from byteplay import *
from pprint import pprint
from simple import a, b
ca = Code.from_code<|fim_suffix|>
print
cc = ca.code[:1] \
+ [(LOAD_CONST, 4)] \
+ ca.code[2:4] \
+ [(LOAD_CONST, 2),(S... | code_fim | medium | {
"lang": "python",
"repo": "evandrix/Splat",
"path": "/doc/pycodeutils_using_byteplay.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> \
+ [(LOAD_FAST, 'b'),(BINARY_ADD, None)] \
+ ca.code[5:]
print "before",
a()
ca.code = cc
a.func_code = ca.to_code()
print "after",
a()<|fim_prefix|># repo: evandrix/Splat path: /doc/pycodeutils_using_byteplay.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from byteplay import *
from pprint import ... | code_fim | hard | {
"lang": "python",
"repo": "evandrix/Splat",
"path": "/doc/pycodeutils_using_byteplay.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open(args.checkpoint, 'rb') as f:
if args.cuda:
model = torch.load(f)
else:
model = torch.load(f, map_location='cpu')
model.eval()
if args.model == 'QRNN':
model.reset()
if args.cuda:
model.cuda()
else:
model.cpu()
corpus = data.Corpus(args.data)
ntokens = len(co... | code_fim | hard | {
"lang": "python",
"repo": "zzsfornlp/misc",
"path": "/ark/lmeval/lm_eval2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zzsfornlp/misc path: /ark/lmeval/lm_eval2.py
#
import argparse
import torch
from torch.autograd import Variable
import data
parser = argparse.ArgumentParser(description='PyTorch PTB Language Model')
# Model parameters.
parser.add_argument('--data', type=str, default='./data/penn',
... | code_fim | hard | {
"lang": "python",
"repo": "zzsfornlp/misc",
"path": "/ark/lmeval/lm_eval2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> txt.append(
"{name:20} = {date:{DATE_FMT_DEFAULT}} {value:{value_fmt}}".format(
name=name,
date=m.date,
DATE_FMT_DEFAULT=DATE_FMT_DEFAULT,
value=value,
value_fmt=value_fmt,
... | code_fim | hard | {
"lang": "python",
"repo": "galactics/beyond",
"path": "/beyond/io/ccsds/tdm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return header + "\n" + text
def _dumps_xml(data, **kwargs):
filtered = ((path, data.filter(path=path)) for path in data.paths)
top = dump_xml_header(data, "TDM", version="1.0", **kwargs)
body = ET.SubElement(top, "body")
for path, measure_set in filtered:
segment = ET.SubE... | code_fim | hard | {
"lang": "python",
"repo": "galactics/beyond",
"path": "/beyond/io/ccsds/tdm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: galactics/beyond path: /beyond/io/ccsds/tdm.py
import numpy as np
import lxml.etree as ET
from ...constants import c
from ...utils import units
from ...utils.measures import MeasureSet, Range, Azimut, Elevation, Doppler
from .commons import (
CcsdsError,
parse_date,
dump_kvn_header,... | code_fim | hard | {
"lang": "python",
"repo": "galactics/beyond",
"path": "/beyond/io/ccsds/tdm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RidhimaKohli/hostel-web-app path: /hostel_project/hostel_webapp/migrations/0007_auto_20201126_1135.py
# Generated by Django 3.0.8 on 2020-11-26 11:35
<|fim_suffix|>class Migration(migrations.Migration):
dependencies = [
('hostel_webapp', '0006_remove_complaint_complaint_pic'),
]... | code_fim | easy | {
"lang": "python",
"repo": "RidhimaKohli/hostel-web-app",
"path": "/hostel_project/hostel_webapp/migrations/0007_auto_20201126_1135.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.RenameField(
model_name='complaint',
old_name='author',
new_name='student',
),
]<|fim_prefix|># repo: RidhimaKohli/hostel-web-app path: /hostel_project/hostel_webapp/migrations/0007_auto_20201126_1135.py
# Generated by ... | code_fim | medium | {
"lang": "python",
"repo": "RidhimaKohli/hostel-web-app",
"path": "/hostel_project/hostel_webapp/migrations/0007_auto_20201126_1135.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mrdegerholm/tracerobot path: /tracerobot/utils.py
#pylint: disable=no-else-return
from contextlib import contextmanager
from datetime import datetime
import traceback
import os.path
@contextmanager
def catch_exc():
<|fim_suffix|> return datetime.now().strftime('%Y%m%d %H:%M:%S.%f')[0:-3]
... | code_fim | hard | {
"lang": "python",
"repo": "mrdegerholm/tracerobot",
"path": "/tracerobot/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def timestamp():
return datetime.now().strftime('%Y%m%d %H:%M:%S.%f')[0:-3]
def format_args(*args, **kwargs):
return ([repr(a) for a in args] +
['{!r}={!r}'.format(k, v) for k, v in kwargs.items()])
def format_exc(exc, value, tb):
stack_summary = traceback.extract_tb(tb)
fr... | code_fim | hard | {
"lang": "python",
"repo": "mrdegerholm/tracerobot",
"path": "/tracerobot/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: skbansal5642/Web-CLI path: /web-cli.py
#!/usr/bin/python3
print("content-type:text/html \n")
print("""
<html>
<head>
<title>Don't look at title</title>
</head>
<|fim_suffix|>opt = sp.getoutput("sudo " + cmd)
if cmd == "date":
full_date = list(opt.split())
print("<h1> Date </h1>")
pri... | code_fim | hard | {
"lang": "python",
"repo": "skbansal5642/Web-CLI",
"path": "/web-cli.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("<h1> Date </h1>")
print(f"""
<h3><xmp>
Day: {full_date[0]}
Date: {full_date[2]}
Month: {full_date[1]}
Year: {full_date[5]}
Time: {full_date[3]}
Timezome: {full_date[4]}
</xmp></h3>
""")
else:
print(f"<h1> {cmd}: </h1>")
print(f"""
<h3><xmp>
{op... | code_fim | medium | {
"lang": "python",
"repo": "skbansal5642/Web-CLI",
"path": "/web-cli.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>opt = sp.getoutput("sudo " + cmd)
if cmd == "date":
full_date = list(opt.split())
print("<h1> Date </h1>")
print(f"""
<h3><xmp>
Day: {full_date[0]}
Date: {full_date[2]}
Month: {full_date[1]}
Year: {full_date[5]}
Time: {full_date[3]}
Timezome: {full_date[4]}
</xmp></h3>
""... | code_fim | hard | {
"lang": "python",
"repo": "skbansal5642/Web-CLI",
"path": "/web-cli.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NicolasMRSN/final_project_BC path: /frontend/views.py
from django.shortcuts import render
from blockchain_func.blockchain import Blockchain
from authentication.models import FaceAuthUser
from frontend.forms.transaction import Transaction
from authentication.views import facial_auth
<|fim_suffix... | code_fim | medium | {
"lang": "python",
"repo": "NicolasMRSN/final_project_BC",
"path": "/frontend/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Show all information stored about a single user.
Args:
pk (str): [description]
Returns:
render: show_user.html
"""
user = facial_auth.get_user()
if user is None:
return redirect('login_password')
#user = FaceAuthUser.objects.get(pk=1)
global cur... | code_fim | medium | {
"lang": "python",
"repo": "NicolasMRSN/final_project_BC",
"path": "/frontend/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 0rbytal/pappy-proxy path: /pappyproxy/config.py
import imp
import json
import os
import shutil
PAPPY_DIR = os.path.dirname(os.path.realpath(__file__))
DATA_DIR = os.path.join(os.path.expanduser('~'), '.pappy')
CERT_DIR = os.path.join(DATA_DIR, 'certs')
DATAFILE = 'data.db'
DEBUG_DIR = None
DEBU... | code_fim | hard | {
"lang": "python",
"repo": "0rbytal/pappy-proxy",
"path": "/pappyproxy/config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Make sure we have a config file
if not os.path.isfile(fname):
print "Copying default config to %s" % fname
default_config_file = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'default_user_config.json')
shutil.copyfile(d... | code_fim | hard | {
"lang": "python",
"repo": "0rbytal/pappy-proxy",
"path": "/pappyproxy/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: naturalGAYms/TheGame path: /menu.py
# coding=utf-8
"""
EXAMPLE 2
Game menu with 3 difficulty options.
Copyright (C) 2017-2018 Pablo Pizarro @ppizarror
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Fr... | code_fim | hard | {
"lang": "python",
"repo": "naturalGAYms/TheGame",
"path": "/menu.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>for m in HELP:
help_menu.add_line(m)
help_menu.add_line(PYGAMEMENU_TEXT_NEWLINE)
help_menu.add_option('Return to menu', PYGAME_MENU_BACK)
main_menu = pygameMenu.Menu(surface,
bgfun=main_background,
color_selected=COLOR_WHITE,
... | code_fim | hard | {
"lang": "python",
"repo": "naturalGAYms/TheGame",
"path": "/menu.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 6e726d/monmob path: /tools/trxunpack.py
#!/usr/bin/python
from __future__ import with_statement
import sys
from struct import pack, unpack
from zlib import crc32, adler32
<|fim_suffix|> if calcedcrc < 0: # crc32 should be unsigned...
calcedcrc = (calcedcrc + 1) * (-1)
if pack("<... | code_fim | hard | {
"lang": "python",
"repo": "6e726d/monmob",
"path": "/tools/trxunpack.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if calcedcrc < 0: # crc32 should be unsigned...
calcedcrc = (calcedcrc + 1) * (-1)
if pack("<l", calcedcrc) != headercrc:
raise Exception("Checksum mismatch!")
else:
print "checksum ok"
with open(dstfname, "wb") as f:
f.write(firmdata[0x1c:])
if __name__ ... | code_fim | medium | {
"lang": "python",
"repo": "6e726d/monmob",
"path": "/tools/trxunpack.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KRHS-GameProgramming-2014/the-temple-of-the-lobsterman-2 path: /Player.py
import pygame
from Bullet import Bullet
class Player(pygame.sprite.Sprite):
def __init__(self, pos):
pygame.sprite.Sprite.__init__(self, self.containers)
self.upImages = [pygame.image.load("Resour... | code_fim | hard | {
"lang": "python",
"repo": "KRHS-GameProgramming-2014/the-temple-of-the-lobsterman-2",
"path": "/Player.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if direction == "attack":
self.changed = True
self.speedx = 0
self.speedy = 0
self.attacking = True
self.frame = 0
self.waitCount = 0
Bullet(self.rect.center, self.facing)
if direction == "up":
... | code_fim | hard | {
"lang": "python",
"repo": "KRHS-GameProgramming-2014/the-temple-of-the-lobsterman-2",
"path": "/Player.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not self.is_new_parent:
if len(self.slate_obj['document']['nodes']):
last_node = self.slate_obj['document']['nodes'].pop()
if last_node['type'] in ['paragraph', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6']:
last_node['nodes'].append(elem)
... | code_fim | hard | {
"lang": "python",
"repo": "YosefMac/html-slate-parser",
"path": "/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YosefMac/html-slate-parser path: /__init__.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals, print_function
from html.parser import HTMLParser
__all__ = ['slate_parser_loads', 'slate_parser_load']
class MyHTMLParser(HTMLParser, object):... | code_fim | hard | {
"lang": "python",
"repo": "YosefMac/html-slate-parser",
"path": "/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.RemoveField(
model_name='logic',
name='concs',
),
migrations.RemoveField(
model_name='logic',
name='hyps',
),
]<|fim_prefix|># repo: rschwiebert/RingApp path: /ringapp/migrations/0062_remove_... | code_fim | medium | {
"lang": "python",
"repo": "rschwiebert/RingApp",
"path": "/ringapp/migrations/0062_remove_hyps_concs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rschwiebert/RingApp path: /ringapp/migrations/0062_remove_hyps_concs.py
# Generated by Django 3.2.14 on 2022-08-12 15:46
<|fim_suffix|> dependencies = [
('ringapp', '0061_migrate_to_souffle'),
]
operations = [
migrations.RemoveField(
model_name='logic',
... | code_fim | medium | {
"lang": "python",
"repo": "rschwiebert/RingApp",
"path": "/ringapp/migrations/0062_remove_hyps_concs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('ringapp', '0061_migrate_to_souffle'),
]
operations = [
migrations.RemoveField(
model_name='logic',
name='concs',
),
migrations.RemoveField(
model_name='logic',
... | code_fim | easy | {
"lang": "python",
"repo": "rschwiebert/RingApp",
"path": "/ringapp/migrations/0062_remove_hyps_concs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: adobe/lagrange path: /modules/core/python/tests/test_combine_meshes.py
#
# Copyright 2022 Adobe. All rights reserved.
# This file is licensed to you under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. You may obtain a copy
# of... | code_fim | hard | {
"lang": "python",
"repo": "adobe/lagrange",
"path": "/modules/core/python/tests/test_combine_meshes.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> mesh = cube
opt = lagrange.NormalOptions()
lagrange.compute_normal(mesh)
out = lagrange.combine_meshes([mesh, mesh], True)
assert out.has_attribute(opt.output_attribute_name)
assert out.is_attribute_indexed(opt.output_attribute_name)<|fim_prefix|># repo: ad... | code_fim | hard | {
"lang": "python",
"repo": "adobe/lagrange",
"path": "/modules/core/python/tests/test_combine_meshes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> out = lagrange.combine_meshes([mesh1, mesh2], True)
assert np.all(out.vertices[:8] == mesh1.vertices)
assert np.all(out.vertices[8:] == mesh2.vertices)
assert np.all(out.facets[:6] == mesh1.facets)
assert np.all(out.facets[6:] == mesh2.facets + mesh1.num_vertices)
... | code_fim | hard | {
"lang": "python",
"repo": "adobe/lagrange",
"path": "/modules/core/python/tests/test_combine_meshes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: druedaplata/app_gnss path: /utils/planet.py
from PIL import Image
import os
import tempfile
import numpy as np
import cv2
from skimage.transform import warp
def get_planet_image(image_path):
""" Gets a panorama image path and returns
a stereographic projection aka plante projection
... | code_fim | hard | {
"lang": "python",
"repo": "druedaplata/app_gnss",
"path": "/utils/planet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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