text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> See `wrap.base.Scatter` for a description of how matplotlib is wrapped to make this plot.
"""<|fim_prefix|># repo: Jammy2211/PyAutoArray path: /autoarray/plot/wrap/two_d/parallel_overscan_plot.py
from autoarray.plot.wrap.two_d.grid_plot import GridPlot
<|fim_middle|>
class ParallelOverscanPl... | code_fim | medium | {
"lang": "python",
"repo": "Jammy2211/PyAutoArray",
"path": "/autoarray/plot/wrap/two_d/parallel_overscan_plot.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def construct_capture_obj(captureds):
captures = []
for location, piece in captureds.items():
captures.append({'location': location, 'name': piece.kind, 'color': piece.color, 'moves': piece.moves})
return captures
@staticmethod
def constru... | code_fim | hard | {
"lang": "python",
"repo": "theovoss/Chess",
"path": "/chess/board/history.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> captures = []
for location, piece in captureds.items():
captures.append({'location': location, 'name': piece.kind, 'color': piece.color, 'moves': piece.moves})
return captures
@staticmethod
def construct_side_effect(method, **kwargs):
start = kwargs['st... | code_fim | hard | {
"lang": "python",
"repo": "theovoss/Chess",
"path": "/chess/board/history.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: theovoss/Chess path: /chess/board/history.py
import copy
class History():
def __init__(self, json=None):
self._index = -1
self._history = []
self._initial_board = {}
if json:
if 'history' in json:
self._history = json['history']
... | code_fim | hard | {
"lang": "python",
"repo": "theovoss/Chess",
"path": "/chess/board/history.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iampakos/moai-0.1.0a2 path: /moai/data/datasets/human_pose/HUMAN4D/importers/image.py
import cv2
import torch
import numpy
import io
#NOTE: extract these to common loading funcs
def load_image(filename: str, data_type=torch.float32):
color_img = numpy.array(cv2.imread(filename, cv2.IMREAD_A... | code_fim | hard | {
"lang": "python",
"repo": "iampakos/moai-0.1.0a2",
"path": "/moai/data/datasets/human_pose/HUMAN4D/importers/image.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def load_depth_pgm(filename: str, data_type=torch.float32, scale = 1):
depth_img = readpgm(filename)
depth_img = depth_img.astype(numpy.float32) * scale
h, w = depth_img.shape
depth_data = depth_img.astype(numpy.float32)
return torch.from_numpy(
depth_data.reshape(1, 1, h, w) ... | code_fim | hard | {
"lang": "python",
"repo": "iampakos/moai-0.1.0a2",
"path": "/moai/data/datasets/human_pose/HUMAN4D/importers/image.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return QPushButton("PyQt5 button")<|fim_prefix|># repo: sweersr/pandas-profiling-1 path: /src/pandas_profiling/report/presentation/flavours/qt/dataset.py
from PyQt5.QtWidgets import QPushButton
from pandas_profiling.report.presentation.core import Dataset
<|fim_middle|>
class QtDataset(Dataset)... | code_fim | easy | {
"lang": "python",
"repo": "sweersr/pandas-profiling-1",
"path": "/src/pandas_profiling/report/presentation/flavours/qt/dataset.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sweersr/pandas-profiling-1 path: /src/pandas_profiling/report/presentation/flavours/qt/dataset.py
from PyQt5.QtWidgets import QPushButton
from pandas_profiling.report.presentation.core import Dataset
<|fim_suffix|> def render(self):
return QPushButton("PyQt5 button")<|fim_middle|>cl... | code_fim | easy | {
"lang": "python",
"repo": "sweersr/pandas-profiling-1",
"path": "/src/pandas_profiling/report/presentation/flavours/qt/dataset.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thorsteinson/board-vector-proto path: /lib/cmdlet.py
import argparse
import sys
from typing import Callable, List, Dict, Any
ArgsType = Dict[str, Any]
class Cmdlet:
def __init__(self, name: str, helpmsg: str, runner: Callable):
self.name = name
self.helpmsg = helpmsg
... | code_fim | hard | {
"lang": "python",
"repo": "thorsteinson/board-vector-proto",
"path": "/lib/cmdlet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for cmd in self.cmdlets:
cmd.add_command(subparsers)
args = main_parser.parse_args()
command = sys.argv[1]
for cmd in self.cmdlets:
if command == cmd.name:
cmd.runner(args)<|fim_prefix|># repo: thorsteinson/board-vector-proto path:... | code_fim | hard | {
"lang": "python",
"repo": "thorsteinson/board-vector-proto",
"path": "/lib/cmdlet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dr-guangtou/asap path: /asap/scripts/um_precompute_pairs.py
#!/usr/bin/env python
"""
Precompute lensing pairs using UniverseMachine SMDPL catalog.
"""
import os
import argparse
import numpy as np
from astropy.table import Table
from asap import vagc
def main(um_file, ptl_file, wl_min_r=0.0... | code_fim | hard | {
"lang": "python",
"repo": "dr-guangtou/asap",
"path": "/asap/scripts/um_precompute_pairs.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument(
'ptl_file', type=str,
help=('Simulation particle table in .npy format'))
parser.add_argument(
'-l', '--r_low', dest='wl_min_r',
help='Lower limit of the radial bin',
type=float, default=0.08)
parser.add_argument(
'-u', '--r... | code_fim | hard | {
"lang": "python",
"repo": "dr-guangtou/asap",
"path": "/asap/scripts/um_precompute_pairs.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument(
'-n', '--n_bins', dest='wl_n_bins',
help='Number of the radial bin',
type=int, default=22)
args = parser.parse_args()
main(args.um_file, args.ptl_file,
wl_min_r=args.wl_min_r, wl_max_r=args.wl_max_r,
wl_n_bins=args.wl_n_bins)<|fi... | code_fim | hard | {
"lang": "python",
"repo": "dr-guangtou/asap",
"path": "/asap/scripts/um_precompute_pairs.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frankygtd/connector-x path: /connectorx-python/connectorx/tests/test_oracle.py
import os
import pandas as pd
import pytest
from pandas.testing import assert_frame_equal
from .. import read_sql
@pytest.fixture(scope="module") # type: ignore
def oracle_url() -> str:
conn = os.environ["ORAC... | code_fim | hard | {
"lang": "python",
"repo": "frankygtd/connector-x",
"path": "/connectorx-python/connectorx/tests/test_oracle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.skipif(not os.environ.get("ORACLE_URL"), reason="Test oracle until we deploy oracle database")
def test_empty_result(oracle_url: str) -> None:
query = "select * from test_partition where TEST_INT < -100"
df = read_sql(
oracle_url,
query
)
expected = pd.DataFram... | code_fim | hard | {
"lang": "python",
"repo": "frankygtd/connector-x",
"path": "/connectorx-python/connectorx/tests/test_oracle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CFGIndia20/team-25 path: /API/app.py
import json
from googletrans import Translator
from classification.categorize import pred
from flask import Flask, render_template,request, redirect, url_for
app = Flask(__name__)
translator = Translator()
@app.route('/complaints', methods=['POST'])
def get_... | code_fim | hard | {
"lang": "python",
"repo": "CFGIndia20/team-25",
"path": "/API/app.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@app.errorhandler(404)
def not_found(e):
"""Simple error handler if there are calls to any other endpoint"""
return json.dumps({"error": "Endpoint not found"})
if __name__ == '__main__':
app.run(debug=True, port=5000)<|fim_prefix|># repo: CFGIndia20/team-25 path: /API/app.py
import json... | code_fim | hard | {
"lang": "python",
"repo": "CFGIndia20/team-25",
"path": "/API/app.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""Simple error handler if there are calls to any other endpoint"""
return json.dumps({"error": "Endpoint not found"})
if __name__ == '__main__':
app.run(debug=True, port=5000)<|fim_prefix|># repo: CFGIndia20/team-25 path: /API/app.py
import json
from googletrans import Translator
from cla... | code_fim | hard | {
"lang": "python",
"repo": "CFGIndia20/team-25",
"path": "/API/app.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Computational-Chemistry-Research/nanome-lib path: /nanome/_internal/_network/_commands/_serialization/_stream/_create_stream.py
from nanome._internal._util._serializers import _ArraySerializer, _LongSerializer
from nanome._internal._util._serializers import _TypeSerializer
from nanome.util.enums ... | code_fim | medium | {
"lang": "python",
"repo": "Computational-Chemistry-Research/nanome-lib",
"path": "/nanome/_internal/_network/_commands/_serialization/_stream/_create_stream.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def name(self):
return "StreamCreation"
def serialize(self, version, value, context):
stream_type = value[0]
if version > 0:
context.write_byte(stream_type)
if version >= 2:
context.write_byte(value[2])
if stream_type == SType.shape... | code_fim | medium | {
"lang": "python",
"repo": "Computational-Chemistry-Research/nanome-lib",
"path": "/nanome/_internal/_network/_commands/_serialization/_stream/_create_stream.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class MessageRecvError(Exception):
pass
class RoutineStop(Exception):
pass<|fim_prefix|># repo: pmdz/smite path: /smite/exceptions.py
class ConnectionError(Exception):
pass
class ClientTimeout(Exception):
pass
class ServantBindError(Exception):
pass
<|fim_middle|>
class ProxyB... | code_fim | hard | {
"lang": "python",
"repo": "pmdz/smite",
"path": "/smite/exceptions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pmdz/smite path: /smite/exceptions.py
class ConnectionError(Exception):
pass
class ClientTimeout(Exception):
pass
<|fim_suffix|> super(MessageException, self).__init__(message)
self.traceback = traceback
class MessageRecvError(Exception):
pass
class RoutineStop(E... | code_fim | medium | {
"lang": "python",
"repo": "pmdz/smite",
"path": "/smite/exceptions.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class ProxyBindError(Exception):
pass
class MessageException(Exception):
def __init__(self, message, traceback):
super(MessageException, self).__init__(message)
self.traceback = traceback
class MessageRecvError(Exception):
pass
class RoutineStop(Exception):
pass<|fim... | code_fim | medium | {
"lang": "python",
"repo": "pmdz/smite",
"path": "/smite/exceptions.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thanhtu19392/SmileML path: /src/smileml/pipeline.py
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn import clone
import pandas as pd
import numpy as np
from scipy import stats
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection import cross_val_predic... | code_fim | hard | {
"lang": "python",
"repo": "thanhtu19392/SmileML",
"path": "/src/smileml/pipeline.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class CountFrequencyEncoder(BaseEstimator, TransformerMixin):
"""
Encode the value by their frequency observed in the training set
"""
def __init__(self, min_card=5, count_na=False):
self.min_card = min_card
self.count_na = count_na
self.vc = None
def fit(sel... | code_fim | hard | {
"lang": "python",
"repo": "thanhtu19392/SmileML",
"path": "/src/smileml/pipeline.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.conn.execute("SELECT * FROM avc where class='Taboo' and attribute='name' and value='test_Taboo'")
result = self.conn.fetchall()
self.assertTrue(result > 0, "successful in adding Taboo")
self.assertTrue(result[0][1] == "test_Taboo", "value didnot match for the added Tab... | code_fim | hard | {
"lang": "python",
"repo": "mrlesmithjr/acitoolkit",
"path": "/applications/search/aciSearch_update_local_database_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mrlesmithjr/acitoolkit path: /applications/search/aciSearch_update_local_database_test.py
from acitoolkit.acisession import Session
import unittest
import sys
import time
import sqlite3
from acitoolkit.acitoolkit import *
from acitoolkit.aciphysobject import *
class TestTenantUpdateInDatabase(... | code_fim | hard | {
"lang": "python",
"repo": "mrlesmithjr/acitoolkit",
"path": "/applications/search/aciSearch_update_local_database_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.parametrize(
'exc,type_',
(
(TypeError(), 'type_error'),
(ValueError(), 'value_error'),
(AssertionError(), 'assertion_error'),
(errors.DecimalIsNotFiniteError(), 'value_error.decimal.not_finite'),
),
)
def test_get_exc_type(exc, type_):
if isins... | code_fim | hard | {
"lang": "python",
"repo": "collerek/pydantic",
"path": "/tests/test_errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: collerek/pydantic path: /tests/test_errors.py
import pickle
import sys
from typing import Dict, List, Optional, Union
from uuid import UUID, uuid4
import pytest
from pydantic import UUID1, BaseConfig, BaseModel, PydanticTypeError, ValidationError, conint, errors, validator
from pydantic.error_w... | code_fim | hard | {
"lang": "python",
"repo": "collerek/pydantic",
"path": "/tests/test_errors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_single_error():
class Model(BaseModel):
x: int
with pytest.raises(ValidationError) as exc_info:
Model(x='x')
expected = """\
1 validation error for Model
x
value is not a valid integer (type=type_error.integer)"""
assert str(exc_info.value) == expected
asse... | code_fim | hard | {
"lang": "python",
"repo": "collerek/pydantic",
"path": "/tests/test_errors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Concatenation model."""
def __init__(self, opt, texts):
super(Concat, self).__init__(opt, texts)
embed_dim = opt.embed_dim
class Composer(torch.nn.Module):
"""Inner composer class."""
def __init__(self, opt):
super(Composer, sel... | code_fim | hard | {
"lang": "python",
"repo": "huynhtruc0309/maaf",
"path": "/models/third_party/tirg.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> dots = torch.mm(mod_img1, img2.transpose(0, 1))
labels = torch.tensor(range(dots.shape[0])).long()
labels = torch.autograd.Variable(labels).cuda()
losses = F.cross_entropy(dots, labels, reduction='none')
if self.opt.drop_worst_flag:
losses, idx = torch.t... | code_fim | hard | {
"lang": "python",
"repo": "huynhtruc0309/maaf",
"path": "/models/third_party/tirg.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: huynhtruc0309/maaf path: /models/third_party/tirg.py
# Copyright 2019 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.ap... | code_fim | hard | {
"lang": "python",
"repo": "huynhtruc0309/maaf",
"path": "/models/third_party/tirg.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 50183816/lineregression path: /HMM/whiteblackball.py
# _*_ codig utf8 _*_
import numpy as np
# HMM前向算法
#
def hmm_forward(pi, A, B, s):
'''
:param pi:
:param A:
:param B:
:param s:
:return:
'''
alpha = pi * B[:, s[0]]
print(alpha)
for index in np.arange(... | code_fim | hard | {
"lang": "python",
"repo": "50183816/lineregression",
"path": "/HMM/whiteblackball.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
pi = np.array([0.2, 0.5, 0.3])
A = np.array([
[0.5, 0.4, 0.1],
[0.2, 0.2, 0.6],
[0.2, 0.5, 0.3]
])
B = np.array([
[0.4, 0.6],
[0.8, 0.2],
[0.5, 0.5]
])
s = [0, 1, 0, 0, 1]
final, p = hmm_viterbi(pi, A, ... | code_fim | hard | {
"lang": "python",
"repo": "50183816/lineregression",
"path": "/HMM/whiteblackball.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>0\x00\x00\x00\x00J\x00\x13\x00\x01\x00L\x00e\x00g\x00a\x00l\x00C\x00o\x00p\x00y\x00r\x00i\x00g\x00h\x00t\x00\x00\x00C\x00o\x00p\x00y\x00r\x00i\x00g\x00h\x00t\x00 \x00\xa9\x00 \x00.\x00 \x002\x000\x002\x000\x00\x00\x00\x00\x00*\x00\x01\x00\x01\x00L\x00e\x00g\x00a\x00l\x00T\x00r\x00a\x00d\x00e\x00m\x00a\x00... | code_fim | hard | {
"lang": "python",
"repo": "target/strelka",
"path": "/src/python/strelka/tests/test_scan_png_eof.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: target/strelka path: /src/python/strelka/tests/test_scan_png_eof.py
from pathlib import Path
from unittest import TestCase, mock
from strelka.scanners.scan_png_eof import ScanPngEof as ScanUnderTest
from strelka.tests import run_test_scan
def test_scan_png_eof(mocker):
"""
Pass: Sample... | code_fim | hard | {
"lang": "python",
"repo": "target/strelka",
"path": "/src/python/strelka/tests/test_scan_png_eof.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: haowu666/pytext path: /pytext/data/tokenizers/tokenizer.py
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import re
from typing import List, NamedTuple
from pytext.config.component import Component, ComponentType
class Token(NamedTuple):
valu... | code_fim | hard | {
"lang": "python",
"repo": "haowu666/pytext",
"path": "/pytext/data/tokenizers/tokenizer.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def from_config(cls, config: Config):
return cls()
def __init__(self):
super().__init__(None)
def tokenize(self, input: List[str]) -> List[Token]:
tokens = [Token(token_text, -1, -1) for token_text in input if token_text]
return tokens<|fim_pr... | code_fim | hard | {
"lang": "python",
"repo": "haowu666/pytext",
"path": "/pytext/data/tokenizers/tokenizer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def from_config(cls, config: Config):
return cls(config.split_regex, config.lowercase)
def __init__(self, split_regex=r"\s+", lowercase=True):
super().__init__(None)
self.split_regex = split_regex
self.lowercase = lowercase
def tokenize(self, ... | code_fim | hard | {
"lang": "python",
"repo": "haowu666/pytext",
"path": "/pytext/data/tokenizers/tokenizer.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: torfinnnome-test/usegalaxy-no-tools-1 path: /scripts/write_report_from_log.py
import csv
import sys
import argparse
default_tool_shed = 'toolshed.g2.bx.psu.edu'
log_file = 'automated_tool_installation_log.tsv'
"""
Generate a report of weekly installations and updates on usegalaxy.no
Because thi... | code_fim | hard | {
"lang": "python",
"repo": "torfinnnome-test/usegalaxy-no-tools-1",
"path": "/scripts/write_report_from_log.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> rows = [
row_num for (row_num, row) in enumerate(table) if row['Category'] == build_category.title() and row['Build Num.'] == str(build_number)
]
return (rows[0], rows[-1])
def tool_table(tool_dict):
content = '| Section | Tool |\n|---------|-----|\n'
for section in sorted(to... | code_fim | hard | {
"lang": "python",
"repo": "torfinnnome-test/usegalaxy-no-tools-1",
"path": "/scripts/write_report_from_log.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return line_y, line_x
def plotting_tip(diff_min_x, diff_min_y):
tip_x = int(round(diff_min_x/rescale_factor))
tip_y = int(round(diff_min_y/rescale_factor))
circle_y, circle_x = disk([tip_y, tip_x], 12)
frame_raw[circle_y, circle_x] = 1
return
#def plot_lines():<|f... | code_fim | hard | {
"lang": "python",
"repo": "janwolzenburg/us-detection-biopsy-needle",
"path": "/needle_detection/plotting.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: janwolzenburg/us-detection-biopsy-needle path: /needle_detection/plotting.py
import numpy as np
import astropy.convolution as ascon
from scipy import ndimage, signal
from skimage import draw
"""
description
gets the x- and y-values representing the line to be drawn in the raw frame
... | code_fim | hard | {
"lang": "python",
"repo": "janwolzenburg/us-detection-biopsy-needle",
"path": "/needle_detection/plotting.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def plotting_tip(diff_min_x, diff_min_y):
tip_x = int(round(diff_min_x/rescale_factor))
tip_y = int(round(diff_min_y/rescale_factor))
circle_y, circle_x = disk([tip_y, tip_x], 12)
frame_raw[circle_y, circle_x] = 1
return
#def plot_lines():<|fim_prefix|># repo: janwolzenbur... | code_fim | hard | {
"lang": "python",
"repo": "janwolzenburg/us-detection-biopsy-needle",
"path": "/needle_detection/plotting.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: g0e/ccd3 path: /dist/server/echo_csv.py
#!/usr/bin/python3
# coding:utf-8
<|fim_suffix|>params = cgi.FieldStorage()
print("Content-Disposition: attachment; filename=" + params.getfirst("file_name","data.csv"))
print("Content-Type: text/csv;\n")
print(params.getfirst("file_contents",""))<|fim_mid... | code_fim | easy | {
"lang": "python",
"repo": "g0e/ccd3",
"path": "/dist/server/echo_csv.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>params = cgi.FieldStorage()
print("Content-Disposition: attachment; filename=" + params.getfirst("file_name","data.csv"))
print("Content-Type: text/csv;\n")
print(params.getfirst("file_contents",""))<|fim_prefix|># repo: g0e/ccd3 path: /dist/server/echo_csv.py
#!/usr/bin/python3
# coding:utf-8
<|fim_mid... | code_fim | easy | {
"lang": "python",
"repo": "g0e/ccd3",
"path": "/dist/server/echo_csv.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> serializer_class = webSerializers.PracticeAttackDefenseTaskSerializer
queryset = PracticeAttackDefenseTask.objects.filter(is_copy=False, event__public=True).order_by('lock', '-id', )
cms_serializer = cmsSerializers.PracticeAttackDefenseTaskSerializer
web_serializer = webSerializers.Practic... | code_fim | medium | {
"lang": "python",
"repo": "g842995907/guops-know",
"path": "/test-xooj/practice_attack_defense/api.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: g842995907/guops-know path: /test-xooj/practice_attack_defense/api.py
# -*- coding: utf-8 -*-
from practice.api import Practice
from practice_attack_defense.cms import serializers as cmsSerializers
from practice_attack_defense.models import PracticeAttackDefenseTask, PracticeAttackDefenseCategor... | code_fim | medium | {
"lang": "python",
"repo": "g842995907/guops-know",
"path": "/test-xooj/practice_attack_defense/api.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> backend_uri = None
tmp_path = None
try:
if example_utils.SQLALCHEMY_AVAILABLE:
tmp_path = tempfile.mktemp(prefix='tf-resume-example')
backend_uri = "sqlite:///%s" % (tmp_path)
else:
tmp_path = tempfile.mkdtemp(prefix='tf-resume-example')
... | code_fim | hard | {
"lang": "python",
"repo": "openstack/taskflow",
"path": "/taskflow/examples/resume_many_flows.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openstack/taskflow path: /taskflow/examples/resume_many_flows.py
# -*- coding: utf-8 -*-
# Copyright (C) 2013 Yahoo! Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may o... | code_fim | hard | {
"lang": "python",
"repo": "openstack/taskflow",
"path": "/taskflow/examples/resume_many_flows.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> stdout, _stderr = proc.communicate()
rc = proc.returncode
if rc != 0:
raise RuntimeError("Could not run %s [%s]", cmd, rc)
print(stdout.decode())
def _path_to(name):
return os.path.abspath(os.path.join(os.path.dirname(__file__),
'resume... | code_fim | hard | {
"lang": "python",
"repo": "openstack/taskflow",
"path": "/taskflow/examples/resume_many_flows.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CloudVE/galaxycloudrunner path: /galaxycloudrunner/__init__.py
"""GalaxyCloudRunner library setup."""
# Current version of the library
__version__ = "0.3.0+dev"
<|fim_suffix|> :rtype: ``string``
:return: Library version (e.g., "0.1.0").
"""
return __version__<|fim_middle|>def g... | code_fim | medium | {
"lang": "python",
"repo": "CloudVE/galaxycloudrunner",
"path": "/galaxycloudrunner/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Return a string with the current version of the library.
:rtype: ``string``
:return: Library version (e.g., "0.1.0").
"""
return __version__<|fim_prefix|># repo: CloudVE/galaxycloudrunner path: /galaxycloudrunner/__init__.py
"""GalaxyCloudRunner library setup."""
<|fim_midd... | code_fim | medium | {
"lang": "python",
"repo": "CloudVE/galaxycloudrunner",
"path": "/galaxycloudrunner/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_version():
"""
Return a string with the current version of the library.
:rtype: ``string``
:return: Library version (e.g., "0.1.0").
"""
return __version__<|fim_prefix|># repo: CloudVE/galaxycloudrunner path: /galaxycloudrunner/__init__.py
"""GalaxyCloudRunner library se... | code_fim | medium | {
"lang": "python",
"repo": "CloudVE/galaxycloudrunner",
"path": "/galaxycloudrunner/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: F5Networks/f5-common-python path: /f5/bigip/tm/sys/sflow.py
# coding=utf-8
#
# Copyright 2017 F5 Networks Inc.
#
# 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
#
# ht... | code_fim | hard | {
"lang": "python",
"repo": "F5Networks/f5-common-python",
"path": "/f5/bigip/tm/sys/sflow.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> super(Receivers, self).__init__(sflow)
self._meta_data['allowed_lazy_attributes'] = [Receiver]
self._meta_data['attribute_registry'] =\
{'tm:sys:sflow:receiver:receiverstate': Receiver}
class Receiver(Resource):
def __init__(self, receivers):
super(Receive... | code_fim | hard | {
"lang": "python",
"repo": "F5Networks/f5-common-python",
"path": "/f5/bigip/tm/sys/sflow.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_unique(self):
# A job can not be created without a jobtype, create one first
jobtype = JobType()
jobtype.name = "foo"
jobtype.description = "this is a job type"
jobtype.classname = "Foobar"
jobtype.code = dedent("""
class Foobar(JobType)... | code_fim | hard | {
"lang": "python",
"repo": "pyfarm/pyfarm-master",
"path": "/tests/test_models/test_model_job.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pyfarm/pyfarm-master path: /tests/test_models/test_model_job.py
# No shebang line, this module is meant to be imported
#
# Copyright 2013 Oliver Palmer
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may ... | code_fim | hard | {
"lang": "python",
"repo": "pyfarm/pyfarm-master",
"path": "/tests/test_models/test_model_job.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pitzer42/opbk-br-quickstart path: /validate.py
from opbk_br_quickstart.client_factory import create_client, ApiFamily, AdminApiFamily,CommonApiFamily, ChannelsApiFamily, ProductsServicesApiFamily
from participant_endpoints import get_endpoints
<|fim_suffix|>def validate_client(client):
for m... | code_fim | hard | {
"lang": "python",
"repo": "pitzer42/opbk-br-quickstart",
"path": "/validate.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return methods
def validate_participant(participant, host):
print(header)
print(participant)
print(header)
validate_client(create_client(
host,
ApiFamily.ADMIN,
AdminApiFamily.METRICS))
validate_client(create_client(
host,
ApiFamily.... | code_fim | hard | {
"lang": "python",
"repo": "pitzer42/opbk-br-quickstart",
"path": "/validate.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lpieri/api_slack path: /clean_channel.py
import requests
from error import *
def clean_channel(channel2clean, token):
print ('Your token is: {token}'.format(token=token))
chan_to_find = channel2clean
response = requests.get('https://slack.com/api/channels.list?limit=100&token={token}'.format(... | code_fim | hard | {
"lang": "python",
"repo": "lpieri/api_slack",
"path": "/clean_channel.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> doesn\'t exist !')
confirmation = input('Really want to delete all messages from this channel ? [y/n]')
if confirmation == 'y':
response = requests.get('https://slack.com/api/channels.history?count=1000&channel={id}&token={token}'.format(id=chan_id, token=token)).json()
if response['ok'] == False:
... | code_fim | hard | {
"lang": "python",
"repo": "lpieri/api_slack",
"path": "/clean_channel.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """"Takes in a list of images and returns the activation dictionary."""
if auto_resize:
images_ = [imresize(im, (224, 224)) for im in images]
else:
images_ = images
feed_dict = {self.input_images: images_}
return sess.run(vgg.activations, fee... | code_fim | hard | {
"lang": "python",
"repo": "HangJie720/Classifiers2LearnWith",
"path": "/experiments/vgg16_pre-trained/vgg16_pre-trained-alt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HangJie720/Classifiers2LearnWith path: /experiments/vgg16_pre-trained/vgg16_pre-trained-alt.py
"""A pre-trained implimentation of VGG16 with weights trained on ImageNet.
NOTE: It's not a great idea to use tf.constant to take in large arrays that will
not change, better to use a non-trainable var... | code_fim | hard | {
"lang": "python",
"repo": "HangJie720/Classifiers2LearnWith",
"path": "/experiments/vgg16_pre-trained/vgg16_pre-trained-alt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
parameters = [] # storage for trainable parameters
# pooling arguments
_ksize = [1, 2, 2, 1]
_strides = [1, 2, 2, 1]
# center the input images
with tf.name_scope('preprocess_centering'):
mean = tf.constant([123.68, 116.779, 103.939], dtype=tf... | code_fim | hard | {
"lang": "python",
"repo": "HangJie720/Classifiers2LearnWith",
"path": "/experiments/vgg16_pre-trained/vgg16_pre-trained-alt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def generate_credential(s):
'''basic_auth_header will return a base64 encoded header object to
:param username: the username
'''
if sys.version_info[0] >= 3:
s = bytes(s, 'utf-8')
credentials = base64.b64encode(s).decode('utf-8')
else:
credentials = base64.b64en... | code_fim | hard | {
"lang": "python",
"repo": "mconcas/singularity-python",
"path": "/singularity/registry/auth.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # If token file not provided, check environment
if secrets is None:
secrets = os.environ.get("SREGISTRY_CLIENT_SECRETS")
# Fall back to default
if secrets is None:
userhome = pwd.getpwuid(os.getuid())[5]
secrets = "%s/.sregistry" % (userhome)
if secrets is not... | code_fim | hard | {
"lang": "python",
"repo": "mconcas/singularity-python",
"path": "/singularity/registry/auth.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mconcas/singularity-python path: /singularity/registry/auth.py
'''
auth.py: authentication functions for singularity hub api
currently no token / auth for private collections
The MIT License (MIT)
Copyright (c) 2016-2017 Vanessa Sochat
Permission is hereby granted, free of charge, to ... | code_fim | hard | {
"lang": "python",
"repo": "mconcas/singularity-python",
"path": "/singularity/registry/auth.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: molejar/project_generator path: /tests/test_commands/test_import.py
# Copyright 2015 0xc0170
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.o... | code_fim | medium | {
"lang": "python",
"repo": "molejar/project_generator",
"path": "/tests/test_commands/test_import.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""test import command"""
def setUp(self):
if not os.path.exists('test_workspace'):
os.makedirs('test_workspace')
# write project file
with open(os.path.join(os.getcwd(), 'test_workspace/template_file'), 'wt') as f:
f.write(yaml.dump('Hello', defau... | code_fim | medium | {
"lang": "python",
"repo": "molejar/project_generator",
"path": "/tests/test_commands/test_import.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CheetahTemplate3/cheetah3 path: /Cheetah/Tests/Test.py
#!/usr/bin/env python
"""
Core module of Cheetah's Unit-testing framework
TODO
================================================================================
# combo tests
# negative test cases for expected exceptions
# black-box vs clear-... | code_fim | hard | {
"lang": "python",
"repo": "CheetahTemplate3/cheetah3",
"path": "/Cheetah/Tests/Test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from Cheetah.Tests import Analyzer # noqa: E402
from Cheetah.Tests import CheetahWrapper # noqa: E402
from Cheetah.Tests import Filters # noqa: E402
from Cheetah.Tests import ImportHooks # noqa: E402
from Cheetah.Tests import LoadTemplate # noqa: E402
from Cheetah.Tests import Misc # noqa: E402
from... | code_fim | hard | {
"lang": "python",
"repo": "CheetahTemplate3/cheetah3",
"path": "/Cheetah/Tests/Test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Args:
x(torch.Tensor):
Input tensor.
"""
b, _, _ = x.shape
if self.has_cls:
cls_tokens = self.cls_token.expand(b, -1, -1)
x = torch.cat((cls_tokens, x), dim=1)
if self.sep_pos_embed:
pos_em... | code_fim | hard | {
"lang": "python",
"repo": "NbnbZero/towhee",
"path": "/towhee/models/layers/spatial_temporal_cls_positional_encoding.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NbnbZero/towhee path: /towhee/models/layers/spatial_temporal_cls_positional_encoding.py
# Copyright 2021 Zilliz and Facebook. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtai... | code_fim | hard | {
"lang": "python",
"repo": "NbnbZero/towhee",
"path": "/towhee/models/layers/spatial_temporal_cls_positional_encoding.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Add a cls token and apply a spatial-temporal encoding to a tensor.
Args:
embed_dim(int):
Embedding dimension for input sequence.
patch_embed_shape(Tuple):
The number of patches in each dimension (T, H, W) after patch embedding.
sep_pos_embed(... | code_fim | hard | {
"lang": "python",
"repo": "NbnbZero/towhee",
"path": "/towhee/models/layers/spatial_temporal_cls_positional_encoding.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kilbyjmichael/pi_temp path: /led_temp.py
from w1thermsensor import W1ThermSensor
import RPi.GPIO as GPIO
from datetime import datetime
import time
import sqlite3
GPIO.setmode(GPIO.BCM)
blue_led = 16
orange_led = 20
red_led = 21
GPIO.setup(blue_led,GPIO.OUT)
GPIO.setup(orange_led,GPIO.OUT)
GPIO.s... | code_fim | hard | {
"lang": "python",
"repo": "kilbyjmichael/pi_temp",
"path": "/led_temp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> GPIO.output(chosen_light,GPIO.HIGH)
time.sleep(0.25)
GPIO.output(chosen_light,GPIO.LOW)
time.sleep(0.25)
GPIO.output(chosen_light,GPIO.HIGH)
time.sleep(0.25)
GPIO.output(chosen_light,GPIO.LOW)
time.sleep(0.25)
GPIO.output(chosen_light,GPIO.HIGH)
time.sleep(0.25)
... | code_fim | hard | {
"lang": "python",
"repo": "kilbyjmichael/pi_temp",
"path": "/led_temp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aimanow/sft path: /src/backend/app/api/public/aspects/aspect/aspect_favorite.py
import datetime
from http import HTTPStatus
from flask_login import current_user
from flask_restplus import Resource, abort
from app.api.models import AspectModel
from app.api.namespaces import aspects
from database... | code_fim | medium | {
"lang": "python",
"repo": "aimanow/sft",
"path": "/src/backend/app/api/public/aspects/aspect/aspect_favorite.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not current_user.favorite_aspects_backref.filter_by(favorite_id=aspect_id).delete():
current_user.favorite_aspects_backref.append(FavoriteAspect(
favorite_id=aspect_id,
created_at=datetime.datetime.now()
))
db.session.commit()
... | code_fim | hard | {
"lang": "python",
"repo": "aimanow/sft",
"path": "/src/backend/app/api/public/aspects/aspect/aspect_favorite.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GabrielRojas74/CajeroEAN path: /CajeroEANFinal.py
uiere retirar", font=("Bahnschrift SemiBold Condensed",25, BOLD), bg="purple", fg="#271F26", width="40", height=2, bd=8, relief=RAISED)
reti.pack(pady=25)
clavecd= tk.Label(bancop, text="Monto:", font=("Bahnschrift SemiBol... | code_fim | hard | {
"lang": "python",
"repo": "GabrielRojas74/CajeroEAN",
"path": "/CajeroEANFinal.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> bancop=tk.Toplevel()
bancop.geometry("300x300")
bancop.title("Transferencia exitosa")
bancop.configure(bd=40, bg="Magenta")
dinerocaja = Label(bancop, text="Su nuevo saldo es de: ", font=("Bahnschri... | code_fim | hard | {
"lang": "python",
"repo": "GabrielRojas74/CajeroEAN",
"path": "/CajeroEANFinal.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GabrielRojas74/CajeroEAN path: /CajeroEANFinal.py
tillium", 15, BOLD))
entradanud.pack(pady=7)
#
enti = tk.Label(win, text="Entidad", font=("titillium", 16), bg="#3bac53", fg="black")
enti.pack(pady=3, side=tk.TOP)
entradant = tk.Entry(win, font=("titillium", 15, BOLD))
en... | code_fim | hard | {
"lang": "python",
"repo": "GabrielRojas74/CajeroEAN",
"path": "/CajeroEANFinal.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openprocurement/openprocurement.auctions.core path: /openprocurement/auctions/core/tests/plugins/awarding/v3/tests/blanks/migration_blanks.py
from uuid import uuid4
from copy import deepcopy
from isodate import parse_datetime
from openprocurement.api.utils import get_now, set_specific_hour
fro... | code_fim | hard | {
"lang": "python",
"repo": "openprocurement/openprocurement.auctions.core",
"path": "/openprocurement/auctions/core/tests/plugins/awarding/v3/tests/blanks/migration_blanks.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> auction.update(auction)
self.db.save(auction)
self.migrate_data(self.app.app.registry)
response = self.app.get('/auctions/{}'.format(self.auction_id))
auction = response.json['data']
self.assertEqual(auction['status'], u'active.qualification')
self.assertEqual(auction['awards'... | code_fim | hard | {
"lang": "python",
"repo": "openprocurement/openprocurement.auctions.core",
"path": "/openprocurement/auctions/core/tests/plugins/awarding/v3/tests/blanks/migration_blanks.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HiroIshida/RobotOS.jl path: /src/ros_callbacks.py
#Python 2/3 compatibility with 3 style code
from __future__ import absolute_import, division, print_function, unicode_literals
__metaclass__ = type
import sys
import ctypes
import threading
try:
import queue
except ImportError:
import Que... | code_fim | hard | {
"lang": "python",
"repo": "HiroIshida/RobotOS.jl",
"path": "/src/ros_callbacks.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._queue.put(msg)
self._cb_notify(self._notify_handle)
def size(self):
return self._queue.qsize()
def get(self):
return self._queue.get()
class ServiceCallback:
def __init__(self, cbptr, notify_handle):
CBType = ctypes.CFUNCTYPE(ctypes.c_int, ctype... | code_fim | medium | {
"lang": "python",
"repo": "HiroIshida/RobotOS.jl",
"path": "/src/ros_callbacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> CBType = ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p)
self._cb_notify = CBType(cbptr.value)
self._notify_handle = notify_handle
self._queue = queue.Queue()
def storemsg(self, msg):
self._queue.put(msg)
self._cb_notify(self._notify_handle)
def s... | code_fim | medium | {
"lang": "python",
"repo": "HiroIshida/RobotOS.jl",
"path": "/src/ros_callbacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jpiv/RocketLeagueRL path: /bot-1/src/bot.py
import logging, os
import math
logging.disable(logging.INFO)
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
from rlbot.agents.base_agent import BaseAgent, SimpleControllerState
from rlbot.messages.flat.QuickChatSelection import QuickChatSelection
from rlbot.... | code_fim | hard | {
"lang": "python",
"repo": "jpiv/RocketLeagueRL",
"path": "/bot-1/src/bot.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.set_controls_from_model(packet, controls)
self.last_state = controls
return controls
def set_controls_from_model(self, tick, controls):
actions = self.get_actions(tick)
if (len(actions) > 1):
controls.throttle = actions[OutputOptions.THROTTL... | code_fim | hard | {
"lang": "python",
"repo": "jpiv/RocketLeagueRL",
"path": "/bot-1/src/bot.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: proh4cktive/phk-logger path: /phk_logger/phkLogger.py
# -*- coding: utf-8 -*-
import logging
from .stdLogger import STDLogger
class PHKLogger(STDLogger):
"""ProHacktive Logging class
Set user-friendly methods to log event with specific log level
"""
def __init__(
self,
... | code_fim | hard | {
"lang": "python",
"repo": "proh4cktive/phk-logger",
"path": "/phk_logger/phkLogger.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
None
"""
# Clean message
message = str(message).rstrip()
# Only log if there is a message (not just a new line)
if message == "":
return None
# Autoset level if necessary
if level is None:
level... | code_fim | hard | {
"lang": "python",
"repo": "proh4cktive/phk-logger",
"path": "/phk_logger/phkLogger.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def generate_pretty_key(*args, **kwargs):
"""Same as generate_str_key(), except the key is formated to
make debugging easier
"""
return '\n'.join((
"",
"\tindex: {}".format(str(kwargs.get('index'))),
"\tdoc_type: {}".format(str(kwargs.get('doc_type'))),
"\tb... | code_fim | hard | {
"lang": "python",
"repo": "fjbsantiago/elasticmock",
"path": "/elasticmock/utilities/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if isinstance(item, dict):
self.sort_dict_recursively(item)
elif not isinstance(item, str) and isinstance(item, collections.Iterable):
self.sort_items_recursively(item)
def generate_str_key(*args, **kwargs):
"""Converts elastic search kwargs in... | code_fim | hard | {
"lang": "python",
"repo": "fjbsantiago/elasticmock",
"path": "/elasticmock/utilities/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fjbsantiago/elasticmock path: /elasticmock/utilities/__init__.py
# -*- coding: utf-8 -*-
import random
import string
import hashlib
import collections
from sortedcontainers import SortedDict
DEFAULT_ELASTICSEARCH_ID_SIZE = 20
CHARSET_FOR_ELASTICSEARCH_ID = string.ascii_letters + string.digits
... | code_fim | hard | {
"lang": "python",
"repo": "fjbsantiago/elasticmock",
"path": "/elasticmock/utilities/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: michaelhabeck/isdhic path: /tests/test_nblist.py
"""
Testing neighbor list
"""
import isdhic
import numpy as np
from scipy.spatial import cKDTree
from scipy.spatial.distance import squareform
from csb.bio.utils import distance_matrix
<|fim_suffix|> c = np.zeros((n_particles,n_particles),'i'... | code_fim | hard | {
"lang": "python",
"repo": "michaelhabeck/isdhic",
"path": "/tests/test_nblist.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def nblist_contacts(nblist, universe):
nblist.update(universe)
return nblist.ctype.contacts
def nblist_pairs(nblist, universe):
contacts = nblist_contacts(nblist, universe)
contacts = [contacts[i,:l] for i, l in enumerate(nblist.ctype.n_contacts.tolist())]
return [(i,j) for i in ra... | code_fim | medium | {
"lang": "python",
"repo": "michaelhabeck/isdhic",
"path": "/tests/test_nblist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def nblist_pairs(nblist, universe):
contacts = nblist_contacts(nblist, universe)
contacts = [contacts[i,:l] for i, l in enumerate(nblist.ctype.n_contacts.tolist())]
return [(i,j) for i in range(len(contacts)) for j in contacts[i]]
def pairs_to_matrix(pairs, n_particles):
c = np.zeros((... | code_fim | medium | {
"lang": "python",
"repo": "michaelhabeck/isdhic",
"path": "/tests/test_nblist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def insert_data(sql, params):
#Insert crypto currencies data to database.
try:
con = connect_to_db()
logging.info('Connected to database.')
stmt = ibm_db.prepare(con, sql)
o = ibm_db.execute_many(stmt, tuple(params))
logging.info(f'{o} records inserte... | code_fim | hard | {
"lang": "python",
"repo": "rmayherr/crypto_app",
"path": "/crypto_app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rmayherr/crypto_app path: /crypto_app.py
"""
Application download current stock prices of 5 top crypto currency.
Data are inserted to db2 database.
"""
import os.path
import json
import configparser
import logging
import sys
import requests
import ibm_db
coins = {'BTC': 'Bitcoin', ... | code_fim | hard | {
"lang": "python",
"repo": "rmayherr/crypto_app",
"path": "/crypto_app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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