text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> @hidden.setter
def hidden(self, value):
return
def get_help_record(self, ctx):
"""
Has "None" as its help record. All that is needed.
"""
return
class DocumentableArgument(click.Argument):
def __init__(self, *args, **kwargs):
doc_help = kw... | code_fim | hard | {
"lang": "python",
"repo": "mobiusklein/glycresoft",
"path": "/src/glycan_profiling/cli/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewDoing/chess_ai path: /Joueur.py/games/chess/search.py
Location (RANK, FILE)
- Capture? 1 otherwise 0
- Castling? 1 character following FEN, otherwise -
- Promotion? Indicates which piece the pawn becomes, otherwise -
"""
action_list = []
if state.active... | code_fim | hard | {
"lang": "python",
"repo": "andrewDoing/chess_ai",
"path": "/Joueur.py/games/chess/search.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewDoing/chess_ai path: /Joueur.py/games/chess/search.py
ry[idx]:
return False
return True
def is_checkmate(state):
"""Returns a boolean as to whether the active color's king is in checkmate.
"""
in_check = check.space_under_attack(state, state.active_king,... | code_fim | hard | {
"lang": "python",
"repo": "andrewDoing/chess_ai",
"path": "/Joueur.py/games/chess/search.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #Change priority queue back to a list of moves
for entry in q.queue:
sorted_moves.append(entry[2])
return sorted_moves
def tl_ht_qs_ab_id_dl_minimax(node, qs_depth, history_table, percentage, time_remaining):
"""Time Limited, Alpha Beta Pruning, Iterative Deepening,
Depth Limi... | code_fim | hard | {
"lang": "python",
"repo": "andrewDoing/chess_ai",
"path": "/Joueur.py/games/chess/search.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Brothers-Coins/BrothersCoinsDataCollector path: /src/model/transaction/transaction.py
from abc import ABCMeta
from src.model.date.date import Date
from src.model.transaction.type_transaction import TypeTransaction
class Transaction:
__metaclass__ = ABCMeta # define transaction abstract
... | code_fim | medium | {
"lang": "python",
"repo": "Brothers-Coins/BrothersCoinsDataCollector",
"path": "/src/model/transaction/transaction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def type_transaction(self):
return TypeTransaction.BUY_TRANSACTION if self.__value > 0 else TypeTransaction.SELL_TRANSACTION
@property
def value(self):
return self.__value
@property
def abs_value(self):
return abs(self.__value)
@property
... | code_fim | hard | {
"lang": "python",
"repo": "Brothers-Coins/BrothersCoinsDataCollector",
"path": "/src/model/transaction/transaction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if speed <= 10:
print(f'slow')
elif 10 < speed <= 50:
print(f'average')
elif 50 < speed <= 150:
print(f'fast')
elif 150 < speed <= 1000:
print(f'ultra fast')
elif speed > 1000:
print(f'extremely fast')<|fim_prefix|># repo: karolinanikolova/SoftUni-Software-Engineering path: /1-Python-... | code_fim | medium | {
"lang": "python",
"repo": "karolinanikolova/SoftUni-Software-Engineering",
"path": "/1-Python-Programming-Basics (Sep 2020)/Course-Exercises-and-Exams/02_Conditional-Statements/02.Exercise-03-Speed-Info.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gorilik324/yabc path: /src/yabc/taxdoc.py
from sqlalchemy import Column
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import String
<|fim_suffix|>
class TaxDoc(yabc.Base):
"""
TODO: If we need to store these, do so in an encrypted object storage, not a... | code_fim | medium | {
"lang": "python",
"repo": "gorilik324/yabc",
"path": "/src/yabc/taxdoc.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
TODO: If we need to store these, do so in an encrypted object storage, not as rows in a databse.
"""
__tablename__ = "taxdoc"
id = Column(Integer, primary_key=True)
user_id = Column(Integer, ForeignKey("user.id"))
file_name = Column(String)
file_hash = Column(String)
... | code_fim | medium | {
"lang": "python",
"repo": "gorilik324/yabc",
"path": "/src/yabc/taxdoc.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daspiker/fakie path: /app/models.py
from app import db
class SyslogSettings(db.Model):
id = db.Column(db.Integer, primary_key=True)
serverIP = db.Column(db.String(64), index=True, unique=True)
comment = db.Column(db.String(128))
<|fim_suffix|> id = db.Column(db.Integer, primary_k... | code_fim | easy | {
"lang": "python",
"repo": "daspiker/fakie",
"path": "/app/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> id = db.Column(db.Integer, primary_key=True)
workspaceId = db.Column(db.String(64), index=True, unique=True)
workspaceKey = db.Column(db.String(128))
comment = db.Column(db.String(128))
db.create_all()<|fim_prefix|># repo: daspiker/fakie path: /app/models.py
from app import db
class Sys... | code_fim | easy | {
"lang": "python",
"repo": "daspiker/fakie",
"path": "/app/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zqbxx/mytools path: /dnscache/dnscache.py
import ctypes
import datetime
import json
import logging
import logging.config
import os
import sys
import time
import traceback
from pathlib import Path
from random import shuffle
from shutil import copyfile
from typing import List
from appdirs import A... | code_fim | hard | {
"lang": "python",
"repo": "zqbxx/mytools",
"path": "/dnscache/dnscache.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> with open(file_path, 'w', newline=os.linesep) as f:
for line in lines:
f.write(line + '\n')
class DnsCache:
dns_cache_record_begin = '----------------------------------------'
dns_cache_record_name = '记录名称'
dns_cache_a_record = 'A (主机)记录'
def __init__(self):
... | code_fim | hard | {
"lang": "python",
"repo": "zqbxx/mytools",
"path": "/dnscache/dnscache.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def is_admin():
try:
return ctypes.windll.shell32.IsUserAnAdmin()
except:
return False
def get_admin():
if sys.version_info[0] == 3:
ctypes.windll.shell32.ShellExecuteW(None, "runas", sys.executable, " ".join(sys.argv), None, 1)
else:#in python2.x
ctypes.wind... | code_fim | hard | {
"lang": "python",
"repo": "zqbxx/mytools",
"path": "/dnscache/dnscache.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rwl/PYPOWER path: /pypower/t/t_loadcase.py
)
t_is(baseMVA1, baseMVA, 12, [t, 'baseMVA'])
t_is(bus1, bus, 12, [t, 'bus'])
t_is(gen1, gen, 12, [t, 'gen'])
t_is(branch1, branch, 12, [t, 'branch'])
t_is(areas1, areas, 12, [t, 'areas'])
... | code_fim | hard | {
"lang": "python",
"repo": "rwl/PYPOWER",
"path": "/pypower/t/t_loadcase.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
## read version 1 PF data matrices
baseMVA, bus, gen, branch = t_case9_pf()
savemat(pfmatfile + '.mat',
{'baseMVA': baseMVA, 'bus': bus, 'gen': gen, 'branch': branch},
oned_as='column')
## read version 2 PF data matrices
ppc = t_case9_pfv2()
tmp = (ppc['baseMVA'],... | code_fim | hard | {
"lang": "python",
"repo": "rwl/PYPOWER",
"path": "/pypower/t/t_loadcase.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rwl/PYPOWER path: /pypower/t/t_loadcase.py
## read version 2 OPF data matrices
ppc = t_case9_opfv2()
## save as .mat file
savemat(matfilev2 + '.mat', {'ppc': ppc}, oned_as='column')
## prepare expected matrices for v1 load
## (missing gen cap curve & branch ang diff lims... | code_fim | hard | {
"lang": "python",
"repo": "rwl/PYPOWER",
"path": "/pypower/t/t_loadcase.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Informatica-EIC/REST-API-Samples path: /python/similarityReport.py
"""
Created on Jul 11, 2018
@author: dwrigley
similarityReport - get information about all similar relationships for an object
Note: this is 10.2.1+ only - the method is different starting with 10.2.1
& uses v1 (undocum... | code_fim | hard | {
"lang": "python",
"repo": "Informatica-EIC/REST-API-Samples",
"path": "/python/similarityReport.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # print("\t\t" + scoreSim +":" + patternSim +":" + nameSim +":" +
# valSim +":" + frqSim +":")
simLinks += 1
colWriter.writerow(
[itemId, dstId, scoreSim, valSim, frqSim, patternSim, nameSim]
... | code_fim | hard | {
"lang": "python",
"repo": "Informatica-EIC/REST-API-Samples",
"path": "/python/similarityReport.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print("url=" + objectsurl)
print("user=" + uid)
print("query=" + query)
print("")
itemCount = 0
itemsWithSim = 0
simLinks = 0
while offset < total:
page += 1
parameters = {"q": query, "offset": offset, "pageSize": pageSize}
# execute catalog rest call, for a page of results
resp = reques... | code_fim | hard | {
"lang": "python",
"repo": "Informatica-EIC/REST-API-Samples",
"path": "/python/similarityReport.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lodemo/CATANA path: /src/face_recognition/trimFeatures.py
# -*- coding: utf-8 -*-
'''
Due to memory usage problems, if features array is present as file on-disk,
its loaded here and used for computing sparse distance matrix.
Features array cant be loaded as numpy memmap, as its not a "perfect"... | code_fim | hard | {
"lang": "python",
"repo": "lodemo/CATANA",
"path": "/src/face_recognition/trimFeatures.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import networkx as nx
fileDir = os.path.dirname(os.path.realpath(__file__))
# Load features array from disk
features = np.load(os.path.join(fileDir,'features_3MONTH.npy'))
print 'Loaded feature:', features.shape
np.save('features_3MONTH_15.npy', np.asarray([f[:15] for f in features]))<|fim_prefix|># r... | code_fim | hard | {
"lang": "python",
"repo": "lodemo/CATANA",
"path": "/src/face_recognition/trimFeatures.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import hdbscan
from sklearn.cluster import DBSCAN
from sklearn.cluster import AgglomerativeClustering
import facedist32
import networkx as nx
fileDir = os.path.dirname(os.path.realpath(__file__))
# Load features array from disk
features = np.load(os.path.join(fileDir,'features_3MONTH.npy'))
print 'Lo... | code_fim | medium | {
"lang": "python",
"repo": "lodemo/CATANA",
"path": "/src/face_recognition/trimFeatures.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> {
'scan': 'scan',
'track': 'track',
'acq_date': 'acq_date',
'acq_time': 'acq_time',
'satellite': 'satellite',
'point': 'POINT'
}<|fim_prefix|># repo: pjdufour/ex2 path: /ex2/enumerations.py
COUNTRY_MAPPING = {
'name': 'name',
'iso2': 'iso2',
'iso3': 'iso<|fim_middle|>... | code_fim | medium | {
"lang": "python",
"repo": "pjdufour/ex2",
"path": "/ex2/enumerations.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pjdufour/ex2 path: /ex2/enumerations.py
COUNTRY_MAPPING = {
'name': 'name',
'iso2': 'iso2',
'iso3': 'iso<|fim_suffix|> 'acq_time': 'acq_time',
'satellite': 'satellite',
'point': 'POINT'
}<|fim_middle|>3',
'pop2005': 'pop2005',
'mpoly': 'MULTIPOLYGON'
}
HOTSPOT_MAPPING ... | code_fim | medium | {
"lang": "python",
"repo": "pjdufour/ex2",
"path": "/ex2/enumerations.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>Max AC Charger Current", "int", "A", {"device-class": "current"}],
[26, "PV1 Input Current", "int", "A", {"icon": "mdi:solar-power", "device-class": "power"}],
[
27,
"Battery Discharge Current",
"int",
"A",
... | code_fim | hard | {
"lang": "python",
"repo": "jblance/mpp-solar",
"path": "/mppsolar/protocols/pi30m045.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jblance/mpp-solar path: /mppsolar/protocols/pi30m045.py
import logging
from .pi30max import pi30max
log = logging.getLogger("pi30m045")
QUERY_COMMANDS = {
"QDI": {
"name": "QDI",
"description": "Default Settings inquiry",
"type": "QUERY",
"response": [
... | code_fim | hard | {
"lang": "python",
"repo": "jblance/mpp-solar",
"path": "/mppsolar/protocols/pi30m045.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Inserts a dimension of length one at a given index of the
dimension array.
Args:
module: Module object corresponding to the arrays.
array: The array whose dimension to expand.
dimension: The index at which to insert the new
dimension.
Returns:
... | code_fim | hard | {
"lang": "python",
"repo": "simonpf/quantnn",
"path": "/quantnn/generic/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simonpf/quantnn path: /quantnn/generic/__init__.py
)
elif module == tf:
return module.convert_to_tensor(array)
raise UnknownModuleException(f"Module {module.__name__} not supported.")
def sample_uniform(module, shape, like=None):
"""
Create a tensor with random values sa... | code_fim | hard | {
"lang": "python",
"repo": "simonpf/quantnn",
"path": "/quantnn/generic/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def expand_dims(module, array, dimension):
"""
Expand tensor dimension along given axis.
Inserts a dimension of length one at a given index of the
dimension array.
Args:
module: Module object corresponding to the arrays.
array: The array whose dimension to expand.
... | code_fim | hard | {
"lang": "python",
"repo": "simonpf/quantnn",
"path": "/quantnn/generic/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MickaelRigault/pysedm path: /bin/extractstar.py
#################################
#
# MAIN
#
#################################
if __name__ == "__main__":
import argparse
import numpy as np
from pysedm import get_sedmcube, io
# ================= #
# Options ... | code_fim | hard | {
"lang": "python",
"repo": "MickaelRigault/pysedm",
"path": "/bin/extractstar.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MickaelRigault/pysedm path: /bin/extractstar.py
Parser(
description=""" run the interactive plotting of a given cube""",
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('infile', type=str, default="None",
help='cube filepath')
#... | code_fim | hard | {
"lang": "python",
"repo": "MickaelRigault/pysedm",
"path": "/bin/extractstar.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser.add_argument('--byecr_showcube', action="store_true", default=False,
help="Show a cube with detected cosmic rays.")
# Centroid
parser.add_argument('--centroid', type=str, default="auto", nargs="+",
help='Where is the point source expec... | code_fim | hard | {
"lang": "python",
"repo": "MickaelRigault/pysedm",
"path": "/bin/extractstar.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: camoz/snakecube path: /vector.py
#!/usr/bin/env python3
def multiply(matrix, vector):
"""Return the matrix product of a matrix and a vector.
Args:
matrix (list(list(int))): A matrix of size m*n.
vector (list(int)): A vector of size n.
Returns:
Vector3D: A v... | code_fim | hard | {
"lang": "python",
"repo": "camoz/snakecube",
"path": "/vector.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __next__(self):
if self._pos >= self.__len__():
raise StopIteration
pos = self._pos
self._pos += 1
return self[pos]
def __add__(self, other):
return Vector3D(self.x + other.x, self.y + other.y, self.z + other.z)
def __sub__(self, other)... | code_fim | hard | {
"lang": "python",
"repo": "camoz/snakecube",
"path": "/vector.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return res
print Solution().findDiagonalOrder(
[
[ 1, 2, 3 ],
[ 4, 5, 6 ],
[ 7, 8, 9 ]
]
)<|fim_prefix|># repo: xiaonanln/myleetcode-python path: /src/498. Diagonal Traverse.py
class Solution(object):
def findDiagonalOrder(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: List[int]
... | code_fim | hard | {
"lang": "python",
"repo": "xiaonanln/myleetcode-python",
"path": "/src/498. Diagonal Traverse.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print Solution().findDiagonalOrder(
[
[ 1, 2, 3 ],
[ 4, 5, 6 ],
[ 7, 8, 9 ]
]
)<|fim_prefix|># repo: xiaonanln/myleetcode-python path: /src/498. Diagonal Traverse.py
class Solution(object):
def findDiagonalOrder(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: List[int]
"""
R = len(... | code_fim | hard | {
"lang": "python",
"repo": "xiaonanln/myleetcode-python",
"path": "/src/498. Diagonal Traverse.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xiaonanln/myleetcode-python path: /src/498. Diagonal Traverse.py
class Solution(object):
def findDiagonalOrder(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: List[int]
"""
R = len(matrix)
if not R:
return []
C = len(matrix[0])
r, c = 0, 0
dir = 1 # dir can be (-1... | code_fim | medium | {
"lang": "python",
"repo": "xiaonanln/myleetcode-python",
"path": "/src/498. Diagonal Traverse.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: babybunny/rebuildingtogethercaptain path: /dev_server.py
import subprocess
import sys
import time
import os
import dev_utilities
my_path = os.path.realpath(__file__)
app_yaml = os.path.join(os.path.dirname(my_path), 'gae', 'app.yaml')
<|fim_suffix|> print("check out the local server at http://... | code_fim | hard | {
"lang": "python",
"repo": "babybunny/rebuildingtogethercaptain",
"path": "/dev_server.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("check out the local server at http://localhost:8080")
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
print("Received KeyboardInterrupt")
sys.exit(0)<|fim_prefix|># repo: babybunny/rebuildingtogethercaptain path: /dev_server.py
import subprocess
import sys
import ... | code_fim | hard | {
"lang": "python",
"repo": "babybunny/rebuildingtogethercaptain",
"path": "/dev_server.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JetBrains/intellij-community path: /python/helpers/third_party/thriftpy/_shaded_thriftpy/protocol/binary.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import struct
from ..thrift import TType
from .exc import TProtocolException
from .base import TProtocolBase
# VERSION_MA... | code_fim | hard | {
"lang": "python",
"repo": "JetBrains/intellij-community",
"path": "/python/helpers/third_party/thriftpy/_shaded_thriftpy/protocol/binary.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def read_val(inbuf, ttype, spec=None, decode_response=True):
if ttype == TType.BOOL:
return bool(unpack_i8(inbuf.read(1)))
elif ttype == TType.BYTE:
return unpack_i8(inbuf.read(1))
elif ttype == TType.I16:
return unpack_i16(inbuf.read(2))
elif ttype == TType.I32:... | code_fim | hard | {
"lang": "python",
"repo": "JetBrains/intellij-community",
"path": "/python/helpers/third_party/thriftpy/_shaded_thriftpy/protocol/binary.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Remmeauth/block-producers-directory-back path: /directory/block_producer/migrations/0007_add_status_description_field.py
# Generated by Django 2.2.5 on 2019-09-27 15:12
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
mig... | code_fim | medium | {
"lang": "python",
"repo": "Remmeauth/block-producers-directory-back",
"path": "/directory/block_producer/migrations/0007_add_status_description_field.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('block_producer', '0006_add_created_at'),
]
operations = [
migrations.AddField(
model_name='blockproducer',
name='status_description',
field=models.TextField(blank=True, max_length=1000),
),
migrations.Alter... | code_fim | medium | {
"lang": "python",
"repo": "Remmeauth/block-producers-directory-back",
"path": "/directory/block_producer/migrations/0007_add_status_description_field.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='blockproducer',
name='status_description',
field=models.TextField(blank=True, max_length=1000),
),
migrations.AlterField(
model_name='blockproducer',
name='full_descripti... | code_fim | medium | {
"lang": "python",
"repo": "Remmeauth/block-producers-directory-back",
"path": "/directory/block_producer/migrations/0007_add_status_description_field.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
This function transfers data from local file system to remote S3
storage
:param input_path:
:param bucket_name:
:param file_ext:
:return:
"""
client = boto3.client('s3', aws_access_key_id=self.access_key,
... | code_fim | hard | {
"lang": "python",
"repo": "SwiftDerek/USImmigrationETL",
"path": "/load/aws_load.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SwiftDerek/USImmigrationETL path: /load/aws_load.py
import os
from boto3.s3.transfer import S3Transfer
import boto3
import logging
class AWSLoad:
def __init__(self, access_key, secret_key):
<|fim_suffix|> """
This function transfers data from local file system to remote S3
... | code_fim | hard | {
"lang": "python",
"repo": "SwiftDerek/USImmigrationETL",
"path": "/load/aws_load.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: materialsproject/MPContribs path: /mpcontribs-api/mpcontribs/api/core.py
)
description = f"List of fields to include in response ({fields_avail})."
description += " Use dot-notation for nested subfields."
fields_param = {
"name": "_fields",
"in": "q... | code_fim | hard | {
"lang": "python",
"repo": "materialsproject/MPContribs",
"path": "/mpcontribs-api/mpcontribs/api/core.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: materialsproject/MPContribs path: /mpcontribs-api/mpcontribs/api/core.py
if hasattr(op, "fmt"):
filter_params[-1]["format"] = op.fmt
if op.allow_negation:
suffix = "not__"
suffix += op.suf if hasattr(op, "suf") else op.op
name = f"{l... | code_fim | hard | {
"lang": "python",
"repo": "materialsproject/MPContribs",
"path": "/mpcontribs-api/mpcontribs/api/core.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return spec
class SwaggerView(OriginalSwaggerView, ResourceView):
"""A class-based view defining additional methods"""
def __init_subclass__(cls, **kwargs):
"""initialize Schema, decorators, definitions, and tags"""
super().__init_subclass__(**kwargs)
if not __name_... | code_fim | hard | {
"lang": "python",
"repo": "materialsproject/MPContribs",
"path": "/mpcontribs-api/mpcontribs/api/core.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
x_train, y_train = shuffle(x_train, y_train, random_state=0)
model = bd_lstm(embedding_matrix)
batch_size = 64
epochs = 20
PATIENCE=4
_, tmpfn = tempfile.mkstemp()
callbacks = [EarlyStopping(patience=PATIENCE), ModelCheckpoint(
tmpfn, save_best_only=True, save_weight... | code_fim | hard | {
"lang": "python",
"repo": "thunlp/SememePSO-Attack",
"path": "/SST/train_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
test_x = pad_sequences(dataset.test_seqs2, maxlen=250, padding='post')
test_y = np.array(dataset.test_y)
train_y=np.array([[0,1] if t==1 else [1,0] for t in train_y])
#valid_y = np.array([[0, 1] if t == 1 else [1, 0] for t in valid_y])
test_y = np.array([[0, 1] if t == 1 else [1, 0] ... | code_fim | hard | {
"lang": "python",
"repo": "thunlp/SememePSO-Attack",
"path": "/SST/train_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thunlp/SememePSO-Attack path: /SST/train_model.py
from __future__ import print_function
from keras.callbacks import EarlyStopping, ModelCheckpoint
import tempfile
from keras.models import Sequential
from keras.layers import *
from keras.layers import Dense, Dropout, Activation
from keras.layers i... | code_fim | hard | {
"lang": "python",
"repo": "thunlp/SememePSO-Attack",
"path": "/SST/train_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amwelch/a10sdk-python path: /a10sdk/core/cgnv6/cgnv6_one_to_one_global.py
from a10sdk.common.A10BaseClass import A10BaseClass
class Global(A10BaseClass):
""" :param mapping_timeout: {"description": "Configure timeout for the one-to-one NAT mapping (Timeout in minutes (default: 10 mi... | code_fim | medium | {
"lang": "python",
"repo": "amwelch/a10sdk-python",
"path": "/a10sdk/core/cgnv6/cgnv6_one_to_one_global.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
"""
def __init__(self, **kwargs):
self.ERROR_MSG = ""
self.required=[]
self.b_key = "global"
self.a10_url="/axapi/v3/cgnv6/one-to-one/global"
self.DeviceProxy = ""
self.mapping_timeout = ""
self.uuid = ""
for keys, value in kwa... | code_fim | hard | {
"lang": "python",
"repo": "amwelch/a10sdk-python",
"path": "/a10sdk/core/cgnv6/cgnv6_one_to_one_global.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def on_event(self, event, extension):
if event.id == "todoist_kw":
extension.keyword = event.new_value
elif event.id == "todoist_api_token":
extension.api_token = event.new_value<|fim_prefix|># repo: cmuench/ulauncher-todoist path: /todoistext/PreferencesEventL... | code_fim | hard | {
"lang": "python",
"repo": "cmuench/ulauncher-todoist",
"path": "/todoistext/PreferencesEventListener.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cmuench/ulauncher-todoist path: /todoistext/PreferencesEventListener.py
from ulauncher.api.client.EventListener import EventListener
<|fim_suffix|> if event.id == "todoist_kw":
extension.keyword = event.new_value
elif event.id == "todoist_api_token":
extens... | code_fim | hard | {
"lang": "python",
"repo": "cmuench/ulauncher-todoist",
"path": "/todoistext/PreferencesEventListener.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shawnkx/multiDDS path: /util_scripts/word_freq.py
import sys
filename = sys.argv[1]
words = {}
with open(filename, 'r') as myfile:
for line in myfile:
toks = line.split()
for w in toks:
if w in words:
words[w] += 1
else:
... | code_fim | easy | {
"lang": "python",
"repo": "shawnkx/multiDDS",
"path": "/util_scripts/word_freq.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sorted_words = sorted(words.items(), key=lambda kv:kv[1])[::-1]
with open(out_filename, 'w') as myfile:
for w, count in sorted_words:
myfile.write("{} {}\n".format(count, w))<|fim_prefix|># repo: shawnkx/multiDDS path: /util_scripts/word_freq.py
import sys
filename = sys.argv[1]
words = {}... | code_fim | easy | {
"lang": "python",
"repo": "shawnkx/multiDDS",
"path": "/util_scripts/word_freq.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> await setup_platform(hass, [SENSOR_DOMAIN], usage=MOCK_VOIP_USAGE)
assert hass.states.get("sensor.mobile_national_calls").state == "1"
assert hass.states.get("sensor.mobile_sms_sent").state == STATE_UNKNOWN
assert hass.states.get("sensor.mobile_data_used").state == STATE_UNKNOWN<|fim_pref... | code_fim | medium | {
"lang": "python",
"repo": "JeffLIrion/home-assistant",
"path": "/tests/components/aussie_broadband/test_sensor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JeffLIrion/home-assistant path: /tests/components/aussie_broadband/test_sensor.py
"""Aussie Broadband sensor platform tests."""
from homeassistant.components.sensor import DOMAIN as SENSOR_DOMAIN
from homeassistant.const import STATE_UNKNOWN
from .common import setup_platform
MOCK_NBN_USAGE = {... | code_fim | hard | {
"lang": "python",
"repo": "JeffLIrion/home-assistant",
"path": "/tests/components/aussie_broadband/test_sensor.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Accepts a string containing a location and formats it properly."""
prompt = ConversionPrompt(
'I', 'O',
("lenox ma", "Lenox, MA"),
("london", "London, U.K."),
("chicago", "Chicago, IL"),
("dallas, tx", "Dallas, TX"),
engine='babbage'
)
ret... | code_fim | easy | {
"lang": "python",
"repo": "nelsonlove/gpt-utils",
"path": "/src/gpt_utils/location.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nelsonlove/gpt-utils path: /src/gpt_utils/location.py
from . import GPT
from .prompt import ConversionPrompt
<|fim_suffix|> """Accepts a string containing a location and formats it properly."""
prompt = ConversionPrompt(
'I', 'O',
("lenox ma", "Lenox, MA"),
("londo... | code_fim | easy | {
"lang": "python",
"repo": "nelsonlove/gpt-utils",
"path": "/src/gpt_utils/location.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def _get_model_instance(name, tensor_dim):
return {
'unet':{'2D': unet_2D, '3D': unet_3D},
'unet_nonlocal':{'2D': unet_nonlocal_2D, '3D': unet_nonlocal_3D},
'unet_grid_gating': {'3D': unet_grid_attention_3D},
'unet_ct_dsv': {'3D': unet_CT_dsv_3D},
'unet_ct_sing... | code_fim | hard | {
"lang": "python",
"repo": "Lorna-Liu/Attention-Gated-Networks",
"path": "/models/networks/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lorna-Liu/Attention-Gated-Networks path: /models/networks/__init__.py
from .unet_2D import *
from .unet_3D import *
from .unet_nonlocal_2D import *
from .unet_nonlocal_3D import *
from .unet_grid_attention_3D import *
from .unet_CT_dsv_3D import *
from .unet_CT_single_att_dsv_3D import *
from .un... | code_fim | hard | {
"lang": "python",
"repo": "Lorna-Liu/Attention-Gated-Networks",
"path": "/models/networks/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if name in ['unet', 'unet_ct_dsv']:
model = model(n_classes=n_classes,
is_batchnorm=True,
in_channels=in_channels,
feature_scale=feature_scale,
is_deconv=False)
elif name in ['unet_nonlocal']:
m... | code_fim | hard | {
"lang": "python",
"repo": "Lorna-Liu/Attention-Gated-Networks",
"path": "/models/networks/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chreman/embedbot path: /workflow/workflow.py
from os import path
import time
import logging
import argparse
from pyspark import SparkContext, SparkConf
from pyspark.sql import SparkSession
from pyspark.ml import Pipeline
from pyspark.ml.feature import RegexTokenizer, Word2Vec
from transformers im... | code_fim | hard | {
"lang": "python",
"repo": "chreman/embedbot",
"path": "/workflow/workflow.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> w2vpipeline = Pipeline(stages=[stringconcat,
tokenizer,
word2Vec])
logger.info('Fitting feature pipeline.')
w2vpipeline_model = w2vpipeline.fit(fulltexts)
w2vmodel = w2vpipeline_model.stages[-1]
vectors = w2vmodel.ge... | code_fim | hard | {
"lang": "python",
"repo": "chreman/embedbot",
"path": "/workflow/workflow.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='do stuff')
parser.add_argument('--input', dest='input', help='relative or absolute '
'path of the input folder')
parser.add_argument('--output', dest='output', help='relative or absolute '
... | code_fim | hard | {
"lang": "python",
"repo": "chreman/embedbot",
"path": "/workflow/workflow.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> files = []
for root, dirnames, filenames in os.walk(directory_name):
for filename in fnmatch.filter(filenames, pattern):
files.append(os.path.join(root, filename))
return files<|fim_prefix|># repo: Laymer/renode path: /src/Renode/RobotFrameworkEngine/helper.py
import netif... | code_fim | hard | {
"lang": "python",
"repo": "Laymer/renode",
"path": "/src/Renode/RobotFrameworkEngine/helper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> proc = subprocess.Popen(['ip', 'addr', 'show', name, 'up'], stdout=subprocess.PIPE)
(output, err) = proc.communicate()
exit_code = proc.wait()
if exit_code != 0 or len(output) == 0:
raise Exception('Network interface {} is not up.'.format(name))
def network_interface_should_have_a... | code_fim | medium | {
"lang": "python",
"repo": "Laymer/renode",
"path": "/src/Renode/RobotFrameworkEngine/helper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Laymer/renode path: /src/Renode/RobotFrameworkEngine/helper.py
import netifaces
import subprocess
import fnmatch
import os
def network_interface_should_exist(name):
if name not in netifaces.interfaces():
raise Exception('Network interface {} not found.'.format(name))
<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "Laymer/renode",
"path": "/src/Renode/RobotFrameworkEngine/helper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LuizArmesto/mootiro-maps path: /mootiro_komoo/apps/search/utils.py
# -*- coding=utf-8 -*-
import requests
import simplejson as json
from django.conf import settings
ES = settings.ELASTICSEARCH_URL
ES_INDEX = settings.ELASTICSEARCH_INDEX_NAME
ES_TYPE = 'komoo_objects'
MAPPINGS_DICT = {
ES_TY... | code_fim | hard | {
"lang": "python",
"repo": "LuizArmesto/mootiro-maps",
"path": "/mootiro_komoo/apps/search/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> requests.post(es_url('{ES}/{INDEX}]_refresh'))
def es_index_dict(obj):
return {
'object_id': obj.id,
'table_ref': '{}.{}'.format(
obj._meta.app_label, obj.__class__.__name__),
'name': obj.name,
'description': getattr(obj, 'description', ''),
'e... | code_fim | hard | {
"lang": "python",
"repo": "LuizArmesto/mootiro-maps",
"path": "/mootiro_komoo/apps/search/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> GET /databases
"""
r = self.__get_response(settings.LST_DBS)
if r["status"] == 200:
return r["result"]
raise Exception(r["result"]["message"])
def list_collections(self, database):
"""Returns a list of collections name of database selecte... | code_fim | hard | {
"lang": "python",
"repo": "puentesarrin/pymongolab",
"path": "/mongolabclient/client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: puentesarrin/pymongolab path: /mongolabclient/client.py
# -*- coding: utf-8 *-*
try:
import simplejson as json
except ImportError:
import json
import requests
from bson import json_util
from mongolabclient import settings, validators, errors
class MongoLabClient(object):
"""Instanc... | code_fim | hard | {
"lang": "python",
"repo": "puentesarrin/pymongolab",
"path": "/mongolabclient/client.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leafvmaple/pyluadec path: /pyluadec/utility.py
import sys
import json
import struct
BYTE_ORDER = {
'*': sys.byteorder,
'+': 'big',
'-': 'little',
}
def get_null_string(data, offset):
idx = data.find(b'\0', offset)
return bytes.decode(data[offset: idx])
def fread(file, size)... | code_fim | hard | {
"lang": "python",
"repo": "leafvmaple/pyluadec",
"path": "/pyluadec/utility.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._form[key] = form
setattr(self, key, read(file, form, initvars))
def tojson(self, indent='\t'):
return json.dumps(self.format(), indent=indent)
def to_bytes(self):
return to_bytes(self, self._export)
class Version:
def __init__(self, file, export):
... | code_fim | hard | {
"lang": "python",
"repo": "leafvmaple/pyluadec",
"path": "/pyluadec/utility.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jyurkiw/py_cyberpunk_2020_rest_api path: /util/__init__.py
from pymongo import MongoClient
from pyconst import loadConstantsFile
from random import choices
import os
if os.path.exists(".dbConstants"):
_db_consts = loadConstantsFile("DatabaseConstants", ".dbConstants")
db = MongoCl... | code_fim | hard | {
"lang": "python",
"repo": "jyurkiw/py_cyberpunk_2020_rest_api",
"path": "/util/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # We're distributing based on an index list because weighting requires using
# random.choices
indexList = [i for i in range(0, len(valueList))]
while points > 0:
points -= (
1
if incrementAtIndex(
valueList, choices(indexList, weight... | code_fim | hard | {
"lang": "python",
"repo": "jyurkiw/py_cyberpunk_2020_rest_api",
"path": "/util/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def convertValueNameListToDict(valueList):
"""Returns a dictionary formed from a list of name/value pairs. Not recursive."""
return {k["name"]: k["value"] for k in valueList}
def distributePoints(valueList, **args):
"""Returns a list of random numbers that line up with a valueIndexMap.... | code_fim | hard | {
"lang": "python",
"repo": "jyurkiw/py_cyberpunk_2020_rest_api",
"path": "/util/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: home-assistant/core path: /homeassistant/components/esphome/camera.py
"""Support for ESPHome cameras."""
from __future__ import annotations
import asyncio
from collections.abc import Callable, Coroutine
from functools import partial
from typing import Any
from aioesphomeapi import CameraInfo, C... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/homeassistant/components/esphome/camera.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Notify listeners of new image when update arrives."""
super()._on_state_update()
self._set_futures(True)
async def async_camera_image(
self, width: int | None = None, height: int | None = None
) -> bytes | None:
"""Return single camera image bytes."""
... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/homeassistant/components/esphome/camera.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_true():
return True<|fim_prefix|># repo: AbdallahCoptan/presence path: /tests/test_presence.py
"""Tests for presence"""
import json
import os
import sys
<|fim_middle|>sys.path.insert(0, os.path.abspath('.'))
#from tests.resources import *
| code_fim | medium | {
"lang": "python",
"repo": "AbdallahCoptan/presence",
"path": "/tests/test_presence.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AbdallahCoptan/presence path: /tests/test_presence.py
"""Tests for presence"""
import json
import os
import sys
<|fim_suffix|>#from tests.resources import *
def test_true():
return True<|fim_middle|>sys.path.insert(0, os.path.abspath('.'))
| code_fim | easy | {
"lang": "python",
"repo": "AbdallahCoptan/presence",
"path": "/tests/test_presence.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alliefitter/boto3_type_annotations path: /boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py
from typing import Dict
from botocore.paginate import Paginator
class ListCertificateAuthorities(Paginator):
def paginate(self, PaginationConfig: Dict = None) -> Dict:
<|fim_suffix|>... | code_fim | medium | {
"lang": "python",
"repo": "alliefitter/boto3_type_annotations",
"path": "/boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class ListTags(Paginator):
def paginate(self, CertificateAuthorityArn: str, PaginationConfig: Dict = None) -> Dict:
pass<|fim_prefix|># repo: alliefitter/boto3_type_annotations path: /boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py
from typing import Dict
from botocore.pagi... | code_fim | medium | {
"lang": "python",
"repo": "alliefitter/boto3_type_annotations",
"path": "/boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pass
class ListTags(Paginator):
def paginate(self, CertificateAuthorityArn: str, PaginationConfig: Dict = None) -> Dict:
pass<|fim_prefix|># repo: alliefitter/boto3_type_annotations path: /boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py
from typing import Dict
fro... | code_fim | medium | {
"lang": "python",
"repo": "alliefitter/boto3_type_annotations",
"path": "/boto3_type_annotations/boto3_type_annotations/acm_pca/paginator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: biogui/simple-image-editor-with-opencv path: /blur.py
from cv2 import blur as blurCV
from validChoice import validChoice
<|fim_suffix|> i = validChoice(input(">> "), 5)
kernels = [1, 3, 5, 9, 11]
k = kernels[i]
print("Creating the new image...")
newImage = blurCV(image, (k, k))
... | code_fim | medium | {
"lang": "python",
"repo": "biogui/simple-image-editor-with-opencv",
"path": "/blur.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("Creating the new image...")
newImage = blurCV(image, (k, k))
return newImage<|fim_prefix|># repo: biogui/simple-image-editor-with-opencv path: /blur.py
from cv2 import blur as blurCV
from validChoice import validChoice
def blur(image):
<|fim_middle|> print("Choice the blur intensity")
... | code_fim | hard | {
"lang": "python",
"repo": "biogui/simple-image-editor-with-opencv",
"path": "/blur.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
A list of references to all virtual machines in the Dedicated Host.
"""
return pulumi.get(self, "virtual_machines")
class AwaitableGetDedicatedHostResult(GetDedicatedHostResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/compute/v20230701/get_dedicated_host.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> host_group_name: Optional[str] = None,
host_name: Optional[str] = None,
resource_group_name: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetDedicatedHostResult:
"""
Retrie... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/compute/v20230701/get_dedicated_host.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/pulumi-azure-native path: /sdk/python/pulumi_azure_native/compute/v20230701/get_dedicated_host.py
# coding=utf-8
# *** WARNING: this file was generated by pulumi. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import copy
import warnings
import pulumi... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/compute/v20230701/get_dedicated_host.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ashesh-0/kaggle_competitions path: /sales_prediction/tests/test_train_test_similarity.py
import pandas as pd
import numpy as np
from train_test_similarity import make_train_have_similar_zeroed_entries_as_test, get_monthly_sales
def dummy_sales():
columns = ['date', 'date_block_num', 'shop_i... | code_fim | hard | {
"lang": "python",
"repo": "ashesh-0/kaggle_competitions",
"path": "/sales_prediction/tests/test_train_test_similarity.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert output_df[output_df.date_block_num == 11].shape[0] == 6
assert all(output_df[output_df.date_block_num == 11].groupby('item_id')['shop_id'].count().unique() == [2])
assert all(output_df[output_df.date_block_num == 11].groupby('shop_id')['item_id'].count().unique() == [3])
# original... | code_fim | hard | {
"lang": "python",
"repo": "ashesh-0/kaggle_competitions",
"path": "/sales_prediction/tests/test_train_test_similarity.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Test Simple """
tests = [
{"name": "foo", "gtest": True},
{"name": "test_bar"},
{"name": "test_baz", "pytest": True}
]
qitest_json = tmpdir.join("qitest.json")
qitest_json.write(json.dumps(tests))
qitest_action("list", cwd=tmpdir.strpath)
assert reco... | code_fim | medium | {
"lang": "python",
"repo": "aldebaran/qibuild",
"path": "/python/qitest/test/test_qitest_list.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aldebaran/qibuild path: /python/qitest/test/test_qitest_list.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2012-2021 SoftBank Robotics. All rights reserved.
# Use of this source code is governed by a BSD-style license (see the COPYING file).
""" Test QiTest List """
from __futu... | code_fim | medium | {
"lang": "python",
"repo": "aldebaran/qibuild",
"path": "/python/qitest/test/test_qitest_list.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: modichirag/galference path: /code/clean_rim/dm_multi_single.py
""" Implementation of Cosmic RIM estimator"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
physical_devices = tf.config.experimental.list_physica... | code_fim | hard | {
"lang": "python",
"repo": "modichirag/galference",
"path": "/code/clean_rim/dm_multi_single.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
###########################################
####Train
###
#Training
losses = []
for epoch in range(args.epochs):
print("\nFor epoch %d\n"%epoch)
#TRAIN LOOP
total_loss = 0.0
num_batches = 0
starte = time.time()
for x in train_dist_dataset:
startb = time.time()
... | code_fim | hard | {
"lang": "python",
"repo": "modichirag/galference",
"path": "/code/clean_rim/dm_multi_single.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> per_replica_losses = strategy.run(train_step, args=(dataset_inputs,))
return strategy.reduce(tf.distribute.ReduceOp.SUM, per_replica_losses,
axis=None)
@tf.function
def distributed_test_step(dataset_inputs):
return strategy.run(test_step, args=(dataset_inputs,))
#######... | code_fim | hard | {
"lang": "python",
"repo": "modichirag/galference",
"path": "/code/clean_rim/dm_multi_single.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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