text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: vgrem/Office365-REST-Python-Client path: /examples/sharepoint/folders/folder_exists.py
"""
How to determine whether folder exist?
"""
from office365.sharepoint.client_context import ClientContext
from tests import te<|fim_suffix|>r_path = "SitePages"
folder = ctx.web.get_folder_by_server_relativ... | code_fim | medium | {
"lang": "python",
"repo": "vgrem/Office365-REST-Python-Client",
"path": "/examples/sharepoint/folders/folder_exists.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: greendwin/puzzles path: /ProjectEuler/Task018_067_MaximumPathSum.py
from collections import Counter
def iterRows(path):
with open(path) as f:
for line in f:
yield map(int, line.strip().split())
def process(path):
prev = Counter()
next = Counter()
<|fim_suffix|... | code_fim | medium | {
"lang": "python",
"repo": "greendwin/puzzles",
"path": "/ProjectEuler/Task018_067_MaximumPathSum.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
print process('task018_example.txt')
print process('task018_input.txt')
print process('task018_067_input.txt')<|fim_prefix|># repo: greendwin/puzzles path: /ProjectEuler/Task018_067_MaximumPathSum.py
from collections import Counter
def iterRows(path):
with ope... | code_fim | medium | {
"lang": "python",
"repo": "greendwin/puzzles",
"path": "/ProjectEuler/Task018_067_MaximumPathSum.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: blocus/naturalSim path: /pixie.py
from utils import *
import random
import numpy as np
class Pixie:
def __init__(self, canvas, x, y):
self.x = x
self.y = y
self.r = 3
self.speed = int(random.random() * 5) + 1
xS = self.x - self.r
xE = self.x + ... | code_fim | hard | {
"lang": "python",
"repo": "blocus/naturalSim",
"path": "/pixie.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> record = np.inf
index = 0
i = 0
if(len(foods) == 0):
return False
for food in foods:
d = dist(self.x, self.y, food.x, food.y)
if d < record:
record = d
index = i
i += 1
food = ... | code_fim | hard | {
"lang": "python",
"repo": "blocus/naturalSim",
"path": "/pixie.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rl-institut/smooth path: /smooth/components/external_component_h2_dispenser.py
"""
This external component class is created to represent the dispenser unit
of a hydrogen refuelling station.
*****
Scope
*****
The dispenser unit of a hydrogen refuelling station does not need to be
included in the ... | code_fim | hard | {
"lang": "python",
"repo": "rl-institut/smooth",
"path": "/smooth/components/external_component_h2_dispenser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ------------------- PARAMETERS -------------------
self.name = 'Test_additional/external_costs_default_name'
self.life_time = 20
self.vehicle_tank_size = 40
self.number_of_hoses = 2
self.refuelling_time = 15
self.nominal_value = 1
self.csv... | code_fim | hard | {
"lang": "python",
"repo": "rl-institut/smooth",
"path": "/smooth/components/external_component_h2_dispenser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> KBList = []
for R in RList:
node = Formula(None)
for symbol in R:
node = parseToTree(symbol, node)
node = findRoot(node)
KBList.append(node)
return KBList
def toCNF(node, step):
if not node: return None
if step == 0:
if node.symbol =... | code_fim | hard | {
"lang": "python",
"repo": "rickxu0423/Automatic-Reasoning",
"path": "/parser.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rickxu0423/Automatic-Reasoning path: /parser.py
from formula import Formula, Atom, Negation, Conjunction, Disjunction, Implication, Biconditional
import copy
operatorList = ['^', 'v', '~', '=>', '<=>']
afterList = ['(', '>']
beforeList = [')', '=', '<']
def splitString(logic):
RList = []
... | code_fim | hard | {
"lang": "python",
"repo": "rickxu0423/Automatic-Reasoning",
"path": "/parser.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liuzhaomax/pyGUI-BakeShop path: /src/view/login/Login_Failed_Dialog.py
#!/usr/bin/python3
# coding=utf-8
'''''''''''''''''''''''''''''''''''''''''''''''''''
@FileName Login_Failed_Dialog.py
@Author Zhao Liu
@StudId 30822750
@StartDate 24-09-2020
@LastModified 24-09-20... | code_fim | medium | {
"lang": "python",
"repo": "liuzhaomax/pyGUI-BakeShop",
"path": "/src/view/login/Login_Failed_Dialog.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def on_click_btn_ok(self):
'''
Callback when the OK button is clicked
@return:
'''
self.dialog.frame.close()<|fim_prefix|># repo: liuzhaomax/pyGUI-BakeShop path: /src/view/login/Login_Failed_Dialog.py
#!/usr/bin/python3
# coding=utf-8
''''''''''''''''''''''''''... | code_fim | hard | {
"lang": "python",
"repo": "liuzhaomax/pyGUI-BakeShop",
"path": "/src/view/login/Login_Failed_Dialog.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tianhm/stock path: /fund/fund_holding_person.py
import datetime
import time
import akshare as ak
import pandas as pd
symbol_dict = {"股票型", "混合型", "指数型", "QDII", "LOF",}
import sys
sys.path.append('..')
from configure.settings import DBSelector
import pymongo
def get_mongo_doc():
client = ... | code_fim | hard | {
"lang": "python",
"repo": "tianhm/stock",
"path": "/fund/fund_holding_person.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> doc = get_mongo_doc()
for item in symbol_dict:
fund_open_fund_rank_em_df = ak.fund_open_fund_rank_em(symbol=item)
print(fund_open_fund_rank_em_df.head())
print(item,len(fund_open_fund_rank_em_df))
obj_list = fund_open_fund_rank_em_df.to_dict('records')
for ... | code_fim | hard | {
"lang": "python",
"repo": "tianhm/stock",
"path": "/fund/fund_holding_person.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @Cog.listener()
async def on_member_leave(self, member: Member) -> None:
config = await self.get_config(member.guild.id)
await self.log(
"MEMBER_LEAVE",
config,
member_mention=member.mention,
member_name=member.name,
memb... | code_fim | hard | {
"lang": "python",
"repo": "vcokltfre/Raptor",
"path": "/bot/cogs/logging/guilds.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vcokltfre/Raptor path: /bot/cogs/logging/guilds.py
from datetime import datetime
from typing import Optional
from discord import Member
from discord.abc import GuildChannel
from discord.ext.commands import Cog
from loguru import logger
from bot.components.bot import Raptor
from common.schemas.l... | code_fim | hard | {
"lang": "python",
"repo": "vcokltfre/Raptor",
"path": "/bot/cogs/logging/guilds.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if isinstance(v, datetime):
ts_format = config.formats.timestamp or "%Y-%m-%d %H:%M:%S"
v = f"{v.strftime(ts_format)}"
fmt = fmt.replace(repl, v)
return fmt
async def log(
self, event: str, config: LoggingModel, in_channel: Opt... | code_fim | hard | {
"lang": "python",
"repo": "vcokltfre/Raptor",
"path": "/bot/cogs/logging/guilds.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def supported_deploy_interfaces(self):
"""List of classes of supported deploy interfaces."""
return [fake.FakeDeploy] + super().supported_deploy_interfaces
@property
def supported_inspect_interfaces(self):
"""List of classes of supported inspect interface... | code_fim | hard | {
"lang": "python",
"repo": "openstack/ironic",
"path": "/ironic/drivers/fake_hardware.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: openstack/ironic path: /ironic/drivers/fake_hardware.py
# Copyright 2016 Red Hat, 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
#
# http://www.apache.org/li... | code_fim | hard | {
"lang": "python",
"repo": "openstack/ironic",
"path": "/ironic/drivers/fake_hardware.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> convertTrajectoryToStateDf = ConvertTrajectoryToStateDf(getAllLevelValuesRange, conditionDfFromParametersDict,
extractColumnValues)
df = convertTrajectoryToStateDf(trajectory)
print(df)
saveToPickle(df, 'df.pickle')
if __name__ ... | code_fim | hard | {
"lang": "python",
"repo": "Enmin/ModellingJointInferenceOfPhysicsAndMind",
"path": "/exec/createTrajectoryDf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Enmin/ModellingJointInferenceOfPhysicsAndMind path: /exec/createTrajectoryDf.py
import os
import sys
DIRNAME = os.path.dirname(__file__)
sys.path.append(os.path.join(DIRNAME, '..'))
import numpy as np
from exec.trajectoriesSaveLoad import ConvertTrajectoryToStateDf, GetAgentCoordinateFromTrajec... | code_fim | hard | {
"lang": "python",
"repo": "Enmin/ModellingJointInferenceOfPhysicsAndMind",
"path": "/exec/createTrajectoryDf.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for h in handle:
h.remove()
gradAmpmap = gradabsdata.permute([1, 2, 0]).abs().mean(dim=2).cpu() / cnt
if show:
plt.figure(figsize=[6, 6.5])
plt.pcolor(gradAmpmap)
plt.gca().invert_yaxis()
plt.axis("image")
plt.title("L %s Unit %s"%(target_layer, ... | code_fim | hard | {
"lang": "python",
"repo": "Animadversio/Visual_Neuro_InSilico_Exp",
"path": "/grad_RF_estim.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Animadversio/Visual_Neuro_InSilico_Exp path: /grad_RF_estim.py
"""
Small lib to calculate RF by back prop towards the image.
It has functions that calculate population RF based on a tensor of weights recombining.
"""
import numpy as np
import torch, torchvision
import matplotlib.pylab as plt
impo... | code_fim | hard | {
"lang": "python",
"repo": "Animadversio/Visual_Neuro_InSilico_Exp",
"path": "/grad_RF_estim.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> device="cuda", show=True, reps=200, batch=1, label="", figdir=None):
# (slice(None), 7, 7)
handle, module_names, module_types = register_hook_by_module_names(target_layer,
get_activation("record", unit=None, ingraph=True), model,
input_size, device=device, )
... | code_fim | hard | {
"lang": "python",
"repo": "Animadversio/Visual_Neuro_InSilico_Exp",
"path": "/grad_RF_estim.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guoxuesong/deepstacks path: /deepstacks/framework/macros.py
#!/usr/bin/env python
# coding:utf-8
# vi:tabstop=4:shiftwidth=4:expandtab:sts=4
<|fim_suffix|> return (
(0,0,0,0,0,0,{
'equal':[target,'classify',lambda x,y:r*lasagne.objectives.categorical_crossentropy(x... | code_fim | medium | {
"lang": "python",
"repo": "guoxuesong/deepstacks",
"path": "/deepstacks/framework/macros.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (
(0,0,0,0,0,0,{
'equal':[target,'classify',lambda x,y:r*lasagne.objectives.categorical_crossentropy(x,y),],
}),
(0,0,0,0,0,0,{
'nonlinearity':lambda x:T.argmax(x, axis=1),'shape':(curr_batchsize,),
'watch':... | code_fim | medium | {
"lang": "python",
"repo": "guoxuesong/deepstacks",
"path": "/deepstacks/framework/macros.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: herohenu/logmon path: /logmon/config.py
'''
logmon.config
-------------
Flask configuration.
'''
<|fim_suffix|> # indicates the file to watch
#LOG_FILE = '/var/log/nginx/access.log'
# For your Rails app, feel free change it to your production.log or development.log
#L... | code_fim | medium | {
"lang": "python",
"repo": "herohenu/logmon",
"path": "/logmon/config.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> SITE_NAME = 'Logmon'
SITE_DOMAIN = 'localhost'
# indicates the file to watch
#LOG_FILE = '/var/log/nginx/access.log'
# For your Rails app, feel free change it to your production.log or development.log
#LOG_FILE = '/www/fosun/log/development.log'
LOG_FILE = '/var/rails/fosu... | code_fim | easy | {
"lang": "python",
"repo": "herohenu/logmon",
"path": "/logmon/config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(execute(test_func, "Tanya", 22)) # "I am Tanya and I am 22 years old"<|fim_prefix|># repo: Andrey-V-Georgiev/PythonOOP path: /_06_PolymorphismLab/_01_Execute.py
def execute(f, *args):
return f(*args)
def test_func(name, age):
<|fim_middle|> return f"I am {name} and I am {age} years old"
... | code_fim | easy | {
"lang": "python",
"repo": "Andrey-V-Georgiev/PythonOOP",
"path": "/_06_PolymorphismLab/_01_Execute.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Andrey-V-Georgiev/PythonOOP path: /_06_PolymorphismLab/_01_Execute.py
def execute(f, *args):
<|fim_suffix|> return f"I am {name} and I am {age} years old"
print(execute(test_func, "Tanya", 22)) # "I am Tanya and I am 22 years old"<|fim_middle|> return f(*args)
def test_func(name, age):... | code_fim | easy | {
"lang": "python",
"repo": "Andrey-V-Georgiev/PythonOOP",
"path": "/_06_PolymorphismLab/_01_Execute.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: letcsv/python-csvorm path: /csvorm/relations.py
class RelationType(object):
ONE_TO_MANY = "one_to_many"
ONE_TO_ONE = "one_to_one"
class Relation(object):
def __init__(self, cls):
self.cls = cls
class HasOne(Relation):
def get(self, id):
return self.cls.get(id=i... | code_fim | easy | {
"lang": "python",
"repo": "letcsv/python-csvorm",
"path": "/csvorm/relations.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class HasOne(Relation):
def get(self, id):
return self.cls.get(id=id)
class HasMany(Relation):
def get(self, id):
value = []
tokens = id.split(",")
for token in tokens:
value += (self.cls.get(id=token.strip()))
return value<|fim_prefix|># rep... | code_fim | easy | {
"lang": "python",
"repo": "letcsv/python-csvorm",
"path": "/csvorm/relations.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tsuru/rpaas path: /rpaas/api.py
est
from raven.contrib.flask import Sentry
import hm.log
from rpaas import (admin_api, router_api, admin_plugin, auth, get_manager, manager,
plugin, storage, tasks)
from rpaas.misc import (validate_name, validate_content, ValidationError, requir... | code_fim | hard | {
"lang": "python",
"repo": "tsuru/rpaas",
"path": "/rpaas/api.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tsuru/rpaas path: /rpaas/api.py
= check_option_enable(os.environ.get("API_DEBUG"))
handler = logging.StreamHandler()
if api.debug:
logging.basicConfig(level=logging.DEBUG)
handler.setLevel(logging.DEBUG)
else:
handler.setLevel(logging.WARN)
api.logger.addHandler(handler)
hm.log.set_h... | code_fim | hard | {
"lang": "python",
"repo": "tsuru/rpaas",
"path": "/rpaas/api.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@api.route("/resources/<name>/block/<block_name>", methods=["DELETE"])
@auth.required
def delete_block(name, block_name):
try:
get_manager().delete_block(name, block_name)
except tasks.NotReadyError as e:
return "Instance not ready: {}".format(e), 412
return "", 200
@api.rou... | code_fim | hard | {
"lang": "python",
"repo": "tsuru/rpaas",
"path": "/rpaas/api.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>SerializerType = enum_type_wrapper.EnumTypeWrapper(_SERIALIZERTYPE)
DEFAULT = 0
STRING = 1
NUMPY = 2
_FUNCTION = _descriptor.Descriptor(
name='Function',
full_name='Function',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='name', ... | code_fim | hard | {
"lang": "python",
"repo": "jssmith/fluent",
"path": "/functions/include/functions_pb2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jssmith/fluent path: /functions/include/functions_pb2.py
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: functions.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf.internal import enum_type_wrapper
from google.p... | code_fim | hard | {
"lang": "python",
"repo": "jssmith/fluent",
"path": "/functions/include/functions_pb2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
_VALUE = _descriptor.Descriptor(
name='Value',
full_name='Value',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='body', full_name='Value.body', index=0,
number=1, type=12, cpp_type=9, label=2,
has_default_value=False, de... | code_fim | hard | {
"lang": "python",
"repo": "jssmith/fluent",
"path": "/functions/include/functions_pb2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (i,j) in visited:
continue
# visited.add((i,j))
if mat[i][j] == 1:
res.append(explore_islands_using_dfs(mat, i, j, visited))
print("Number of islands present is ", mat, len(res))<|fim_prefix|># repo: iamlmn/PyDS path: /algos/pat... | code_fim | medium | {
"lang": "python",
"repo": "iamlmn/PyDS",
"path": "/algos/patterns/dfs/numberOfIslands.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iamlmn/PyDS path: /algos/patterns/dfs/numberOfIslands.py
'''
Calculate the area of an island
'''
def validate(matrix, i, j,visited):
if j < 0 or i < 0 or i >= len(matrix) or j >= len(matrix[0]) or (i,j) in visited or matrix[i][j] != 1:
return False
return True
def explore_islands... | code_fim | hard | {
"lang": "python",
"repo": "iamlmn/PyDS",
"path": "/algos/patterns/dfs/numberOfIslands.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RemDelaporteMathurin/FESTIM path: /test/unit/test_sources.py
import festim
import fenics as f
import sympy as sp
import numpy as np
def test_implantation_flux_attributes():
"""
Checks all attributes of the ImplantationFlux class
"""
flux = 1
imp_depth = 5e-9
width = 5e-9... | code_fim | hard | {
"lang": "python",
"repo": "RemDelaporteMathurin/FESTIM",
"path": "/test/unit/test_sources.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert my_source.value._cppcode == expected_value
def test_source_with_float_value():
"""
Tests that Source can be created with a float value and that the .value
attribute is Constant
"""
source = festim.Source(2.0, volume=1, field="solute")
assert isinstance(source.value, f.... | code_fim | hard | {
"lang": "python",
"repo": "RemDelaporteMathurin/FESTIM",
"path": "/test/unit/test_sources.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # input
inputs = Input(shape=(height,), dtype='int32')
embed = Embedding(input_set_size, width, input_length=height)(inputs)
sentence_model = Bidirectional(LSTM(64, return_sequences=True))(embed)
pool = GlobalMaxPooling1D()(sentence_model)
# output
out = [Dense(mul_nb_classes[i], activation='sigmoi... | code_fim | medium | {
"lang": "python",
"repo": "susht3/Text_Mutil_Classification_keras",
"path": "/model/para_lstm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: susht3/Text_Mutil_Classification_keras path: /model/para_lstm.py
from keras.layers import Input, Dense, Dropout, Flatten, merge, Reshape, Activation, Permute
from keras.layers.convolutional import Convolution1D, Convolution2D
from keras.layers.pooling import GlobalMaxPooling1D, MaxPooling1D
from ... | code_fim | medium | {
"lang": "python",
"repo": "susht3/Text_Mutil_Classification_keras",
"path": "/model/para_lstm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mesmith/ModelClarity path: /air_force_shared.py
# Shared functions and variables used in both training and in production.
#
import numpy as np
import math
import pandas as pd
import io
import torch
import torch.nn as nn
import torch.nn.functional as F
# For reusing the same categorical encoder f... | code_fim | hard | {
"lang": "python",
"repo": "mesmith/ModelClarity",
"path": "/air_force_shared.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return (x - mean) / std
s = pd.Series(data[field])
numerics = pd.to_numeric(s, errors='coerce')
mapped = numerics.map(lambda x: 0 if math.isnan(x) else norm(x, mean, std))
norm_field = norm_prefix + '_' + field
out = pd.DataFrame({norm_field: mapped})
return out
# Apply ... | code_fim | hard | {
"lang": "python",
"repo": "mesmith/ModelClarity",
"path": "/air_force_shared.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mesonbuild/meson path: /mesonbuild/templates/objctemplates.py
# Copyright 2019 The Meson development team
# 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://w... | code_fim | hard | {
"lang": "python",
"repo": "mesonbuild/meson",
"path": "/mesonbuild/templates/objctemplates.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>hello_objc_meson_template = '''project('{project_name}', 'objc',
version : '{version}',
default_options : ['warning_level=3'])
exe = executable('{exe_name}', '{source_name}',
install : true)
test('basic', exe)
'''
class ObjCProject(FileHeaderImpl):
source_ext = 'm'
header_ext = 'h'
... | code_fim | hard | {
"lang": "python",
"repo": "mesonbuild/meson",
"path": "/mesonbuild/templates/objctemplates.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def convert2ace_js(completions):
"""
转换completions为ace.js所需要的补全列表格式[{"caption":,"meta":,"name":,"value":,"score":]
caption ：字幕，也就是展示在列表中的内容
meta ：展示类型
name ：名称
value ：值
score ：分数，越大的排在越上面
:return:
"""
ace... | code_fim | hard | {
"lang": "python",
"repo": "lgq9220/archery",
"path": "/sql/completer/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lgq9220/archery path: /sql/completer/__init__.py
# -*- coding: UTF-8 -*-
"""
@author: hhyo
@license: Apache Licence
@file: completion_engines.py
@time: 2019/03/09
"""
__author__ = 'hhyo'
class Completer:
@property
def name(self):
"""返回engine名称"""
return 'Completer engi... | code_fim | hard | {
"lang": "python",
"repo": "lgq9220/archery",
"path": "/sql/completer/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
刷新completer对象元数据
:param reset:
:return:
"""
def _on_completions_refreshed(self, new_completer):
"""
刷新completer对象回调函数，替换对象
:param new_completer:
:return:
"""
def get_completions(self, text, cursor_position):
... | code_fim | medium | {
"lang": "python",
"repo": "lgq9220/archery",
"path": "/sql/completer/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: baverman/cachel path: /cachel/__init__.py
from .base import (SERIALIZERS, make_key_func, NullCache, BaseCache,
<|fim_suffix|>e_cache
from .offload import make_offload_cache
from . import compat
if compat.ASYNC_AWAIT: # pragma: no cover
from .base import AsyncBaseCache<|fim_middle|> ... | code_fim | medium | {
"lang": "python",
"repo": "baverman/cachel",
"path": "/cachel/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ompat.ASYNC_AWAIT: # pragma: no cover
from .base import AsyncBaseCache<|fim_prefix|># repo: baverman/cachel path: /cachel/__init__.py
from .base import (SERIALIZERS, make_key_func, NullCache, BaseCache,
<|fim_middle|> wrap_in, wrap_dict_value_in, expire)
from .simple import make_ca... | code_fim | medium | {
"lang": "python",
"repo": "baverman/cachel",
"path": "/cachel/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class CompanyProfileUpdateForm(forms.ModelForm):
"""
CustomerProfile update form.
Field enhancements:
* time uses forms.TimeField with format '%H:%M'
* serviceproviderType uses forms.TypedChoiceField choices from CompanyProfile.SERVICEPROVIDER_TYPE_CHOICES
* invoiceRefType uses for... | code_fim | hard | {
"lang": "python",
"repo": "lususnaturae/terapialaskutus",
"path": "/therapyinvoicing/customers/forms.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lususnaturae/terapialaskutus path: /therapyinvoicing/customers/forms.py
from django import forms
from django.utils.translation import ugettext_lazy as _
from .models import Customer, Session, CompanyProfile
class CustomerUpdateForm(forms.ModelForm):
"""
Update Customer form
Field en... | code_fim | hard | {
"lang": "python",
"repo": "lususnaturae/terapialaskutus",
"path": "/therapyinvoicing/customers/forms.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
CustomerProfile update form.
Field enhancements:
* time uses forms.TimeField with format '%H:%M'
* serviceproviderType uses forms.TypedChoiceField choices from CompanyProfile.SERVICEPROVIDER_TYPE_CHOICES
* invoiceRefType uses forms.TypedChoiceField choices from CompanyProfile.I... | code_fim | hard | {
"lang": "python",
"repo": "lususnaturae/terapialaskutus",
"path": "/therapyinvoicing/customers/forms.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Polling of the client until the job is complete
while True:
message = yield from client.socket.recv()
if message is None or message.strip().lower()=="terminate":
# Kill thread if running
if job.status==Job.RUNNING or job.status==Job.WAITING:
client.log("Terminate request \"%s\""%ha... | code_fim | hard | {
"lang": "python",
"repo": "sebMathieu/dsima",
"path": "/server/iginterface.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Agree to receive the instance parameters and waits
yield from client.socket.send("ok instance generation request")
xmlParameters=yield from client.socket.recv()
if xmlParameters is None:
return
yield from client.socket.send("ok instance received")
client.log("\n"+xmlParameters)
# Star... | code_fim | hard | {
"lang": "python",
"repo": "sebMathieu/dsima",
"path": "/server/iginterface.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sebMathieu/dsima path: /server/iginterface.py
##@package iginterface
# Instance generator interface.
#@author Sebastien MATHIEU
import time, sys, threading, queue, subprocess,traceback,os
import asyncio,websockets
import xml.etree.ElementTree as ElementTree
from .job import Job
from .l... | code_fim | hard | {
"lang": "python",
"repo": "sebMathieu/dsima",
"path": "/server/iginterface.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Pulecz/convert_currency path: /tests_long.py
#!/usr/bin/env python
import convert_currency
import unittest
from CONST import supported_currencies
class Args_for_convert_currency:
'simulate Namespace class for argsparse with all arguments convert_currency takes'
def __init__(self, amount,... | code_fim | hard | {
"lang": "python",
"repo": "Pulecz/convert_currency",
"path": "/tests_long.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
go over each currency_code and print output for all
since input is always different, request from API is needed in each run
therefore we can just run the main with different input parameter for each country_code
and test that it returns 0
'''
pri... | code_fim | hard | {
"lang": "python",
"repo": "Pulecz/convert_currency",
"path": "/tests_long.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return np.concatenate((warmup_lr_schedule, cosine_lr_schedule))
def length_to_mask(length, stride=1, max_len=None, dtype=None):
"""length: B.
return B x max_len.
If max_len is None, then max of length will be used.
"""
assert len(length.shape) == 1, 'Length shape should be 1 dime... | code_fim | hard | {
"lang": "python",
"repo": "SABER-labs/SABERv2",
"path": "/utils/training_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SABER-labs/SABERv2 path: /utils/training_utils.py
import math
from utils.config import config
import numpy as np
import torch
import torch.distributed as dist
class GatherLayer(torch.autograd.Function):
@staticmethod
def forward(ctx, tensor):
ctx.batch_size = tensor.shape[0]
... | code_fim | medium | {
"lang": "python",
"repo": "SABER-labs/SABERv2",
"path": "/utils/training_utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> start_lr = config.trainer.start_lr
final_lr = config.trainer.final_lr
learning_rate = config.trainer.learning_rate
warmup_epochs = config.trainer.warmup_epochs
max_epochs = config.trainer.max_epochs
warmup_lr_schedule = np.linspace(
start_lr, learning_rate, int(train_iters... | code_fim | hard | {
"lang": "python",
"repo": "SABER-labs/SABERv2",
"path": "/utils/training_utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class SituacaoUpdate(UpdateView):
model = Situacao
template_name = 'situacao.html'
form_class = SituacaoForm
def produto_json(request, pk):
''' Retorna o produto, id e estoque. '''
produto = Produto.objects.filter(pk=pk)
data = [item.to_dict_json() for item in produto]
return... | code_fim | hard | {
"lang": "python",
"repo": "CSAAtibaia/Listas",
"path": "/ERP/core/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CSAAtibaia/Listas path: /ERP/core/views.py
from django.shortcuts import render
from django.http import JsonResponse, HttpResponseRedirect
from django.urls import reverse
from django.views.generic import CreateView, UpdateView, ListView
from .models import Item as Produto, Situacao
from .forms imp... | code_fim | hard | {
"lang": "python",
"repo": "CSAAtibaia/Listas",
"path": "/ERP/core/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> ''' Retorna o produto, id e estoque. '''
produto = Produto.objects.filter(pk=pk)
data = [item.to_dict_json() for item in produto]
return JsonResponse({'data': data})
def save_data(data):
'''
Salva os dados no banco.
'''
aux = []
for item in data:
produto = ite... | code_fim | hard | {
"lang": "python",
"repo": "CSAAtibaia/Listas",
"path": "/ERP/core/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.cnn = nn.Sequential(
nn.Conv1d(self.embed_size, 128, 4, 2),
nn.BatchNorm1d(128),
nn.ELU(),
nn.Conv1d(128, 256, 4, 2),
nn.BatchNorm1d(256),
nn.ELU(),
nn.Conv1d(256, 256, 4, 2),
nn.BatchNorm1d(256)... | code_fim | hard | {
"lang": "python",
"repo": "asiddhant/hybrid_rvae",
"path": "/model/encoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
:param input: An float tensor with shape of [batch_size, seq_len, embed_size]
:return: An float tensor with shape of [batch_size, latent_variable_size]
"""
'''
Transpose input to the shape of [batch_size, embed_size, seq_len]
'''
input =... | code_fim | hard | {
"lang": "python",
"repo": "asiddhant/hybrid_rvae",
"path": "/model/encoder.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asiddhant/hybrid_rvae path: /model/encoder.py
import torch as t
import torch.nn as nn
import torch.nn.functional as F
class Encoder(nn.Module):
def __init__(self, embed_size, latent_size):
super(Encoder, self).__init__()
<|fim_suffix|> """
:param input: An float tens... | code_fim | hard | {
"lang": "python",
"repo": "asiddhant/hybrid_rvae",
"path": "/model/encoder.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Set up coords
x = x[:,np.newaxis]
y = y[np.newaxis,:]
# Integrate over vortex
M00 = np.sum(np.abs(vtx_field-edge)*(x**0)*(y**0))
M10 = np.sum(np.abs(vtx_field-edge)*(x**1)*(y**0))
M01 = np.sum(np.abs(vtx_field-edge)*(x**0)*(y**1))
Marea = np.sum(np.abs(vtx_field-edge)*(x*... | code_fim | hard | {
"lang": "python",
"repo": "BrisClimate/How-well-are-Sudden-Stratospheric-Warming-surface-impacts-captured-in-CMIP6-climate-models-",
"path": "/vor_fast.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> *field*
A :py:class:`numpy.ndarray` or :py:class:`numpy.ma.core.MasekdArray`
with two dimensions. The 0th dimension should represent latitude, and
the 1st dimension longitude.
*lats*
A one dimensional array or list with the latitude grid values for field
... | code_fim | hard | {
"lang": "python",
"repo": "BrisClimate/How-well-are-Sudden-Stratospheric-Warming-surface-impacts-captured-in-CMIP6-climate-models-",
"path": "/vor_fast.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BrisClimate/How-well-are-Sudden-Stratospheric-Warming-surface-impacts-captured-in-CMIP6-climate-models- path: /vor_fast.py
'''
This file is part of vortex-moments on William Sevour's Github page.
Please see README.md for more information, including citations.
vortex-moments is free software:... | code_fim | hard | {
"lang": "python",
"repo": "BrisClimate/How-well-are-Sudden-Stratospheric-Warming-surface-impacts-captured-in-CMIP6-climate-models-",
"path": "/vor_fast.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Standard methods for instantiation, printing, and type
information.
"""
...
def SetArrayComponent(self, p_int):
"""
V.SetArrayComponent(int)
C++: virtual void SetArrayComponent(int _arg)
Set/get which component of a multi-co... | code_fim | hard | {
"lang": "python",
"repo": "gen4438/vtk-python-stubs",
"path": "/typings/vtkmodules/vtkFiltersGeneral/vtkDiscreteFlyingEdgesClipper2D.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
V.SetComputeScalars(int)
C++: virtual void SetComputeScalars(int _arg)
Option to set the cell scalars of the output. The scalars will be
the contour values. By default this flag is on.
"""
...
def SetNumberOfContours(self, p_int... | code_fim | hard | {
"lang": "python",
"repo": "gen4438/vtk-python-stubs",
"path": "/typings/vtkmodules/vtkFiltersGeneral/vtkDiscreteFlyingEdgesClipper2D.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gen4438/vtk-python-stubs path: /typings/vtkmodules/vtkFiltersGeneral/vtkDiscreteFlyingEdgesClipper2D.pyi
"""
This type stub file was generated by pyright.
"""
import vtkmodules.vtkCommonExecutionModel as __vtkmodules_vtkCommonExecutionModel
class vtkDiscreteFlyingEdgesClipper2D(__vtkmodules_vtk... | code_fim | hard | {
"lang": "python",
"repo": "gen4438/vtk-python-stubs",
"path": "/typings/vtkmodules/vtkFiltersGeneral/vtkDiscreteFlyingEdgesClipper2D.pyi",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> Args:
channels: The channel that the barrier applies to.
name: Name of the directive for display purposes.
"""
super().__init__(operands=tuple(channels), name=name)
@property
def channels(self) -> Tuple[chans.Channel]:
"""Returns the channel... | code_fim | hard | {
"lang": "python",
"repo": "CoolProgrammerX/qiskit-terra",
"path": "/qiskit/pulse/instructions/directives.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def duration(self) -> int:
"""Duration of this instruction."""
return 0
class RelativeBarrier(Directive):
"""Pulse ``RelativeBarrier`` directive."""
def __init__(self, *channels: chans.Channel, name: Optional[str] = None):
"""Create a relative barrier d... | code_fim | hard | {
"lang": "python",
"repo": "CoolProgrammerX/qiskit-terra",
"path": "/qiskit/pulse/instructions/directives.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CoolProgrammerX/qiskit-terra path: /qiskit/pulse/instructions/directives.py
# This code is part of Qiskit.
#
# (C) Copyright IBM 2020.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this s... | code_fim | hard | {
"lang": "python",
"repo": "CoolProgrammerX/qiskit-terra",
"path": "/qiskit/pulse/instructions/directives.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
# top
# get y
y = 0
# get x
b_right_part = True
if angle > angle_top_left:
angle = np.abs(360 - angle)
b_right_part = False
if angle == 0:
x = 0
... | code_fim | hard | {
"lang": "python",
"repo": "neutronimaging/python_notebooks",
"path": "/notebooks/__code/radial_profile/event_handler.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: neutronimaging/python_notebooks path: /notebooks/__code/radial_profile/event_handler.py
import numpy as np
import pyqtgraph as pg
from qtpy import QtGui
from __code._utilities.parent import Parent
from __code.radial_profile.display import Display
class EventHandler(Parent):
def file_index... | code_fim | hard | {
"lang": "python",
"repo": "neutronimaging/python_notebooks",
"path": "/notebooks/__code/radial_profile/event_handler.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.parent.angle_0:
self.parent.ui.image_view.removeItem(self.parent.angle_0)
if self.parent.angle_90:
self.parent.ui.image_view.removeItem(self.parent.angle_90)
if self.parent.angle_180:
self.parent.ui.image_view.removeItem(self.parent.ang... | code_fim | hard | {
"lang": "python",
"repo": "neutronimaging/python_notebooks",
"path": "/notebooks/__code/radial_profile/event_handler.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> job = self.registry[task.job]
retries = getattr(job, 'retries', self.retries)
backoff = getattr(job, 'backoff', self.backoff)
try:
await asyncio.wait_for(job(task), timeout=task.timeout)
await self.queue.remove(task)
except Exception:
... | code_fim | hard | {
"lang": "python",
"repo": "knowark/schedulark",
"path": "/schedulark/worker/worker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: knowark/schedulark path: /schedulark/worker/worker.py
import time
import asyncio
import logging
from typing import Type, Tuple, Dict, Callable
from ..base import Job
from ..queue import Queue
Registry = Dict[str, Job]
class Worker:
def __init__(self, registry: Registry, queue: Queue) -> N... | code_fim | hard | {
"lang": "python",
"repo": "knowark/schedulark",
"path": "/schedulark/worker/worker.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.iterations = 0
async def _process(self, task) -> None:
if not task:
return await asyncio.sleep(self.sleep)
job = self.registry[task.job]
retries = getattr(job, 'retries', self.retries)
backoff = getattr(job, 'backoff', self.backoff)
tr... | code_fim | hard | {
"lang": "python",
"repo": "knowark/schedulark",
"path": "/schedulark/worker/worker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> strides = list(data.strides)
strides[axis] *= stepsize
strides.append(data.strides[axis])
strided = np.lib.stride_tricks.as_strided(
data, shape=shape, strides=strides
)
return strided
@staticmethod
def get_MFCC(path, window=10, step=1... | code_fim | hard | {
"lang": "python",
"repo": "gundamMC/animius",
"path": "/animius/SpeakerVerification/MFCC.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gundamMC/animius path: /animius/SpeakerVerification/MFCC.py
import numpy as np
import scipy.io.wavfile as wav
import speechpy
class MFCC:
@staticmethod
def sliding_window(data, size, stepsize=1, axis=0):
"""
Calculate a sliding window over a signal
Parameters
... | code_fim | hard | {
"lang": "python",
"repo": "gundamMC/animius",
"path": "/animius/SpeakerVerification/MFCC.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def send(self, worker: int, msg: Any) -> bool:
try:
self.pipes[worker].send(msg)
return True
except BrokenPipeError:
self._on_error(worker)
return False
def broadcast(self, obj: Any) -> List[bool]:
ret = []
for pipe i... | code_fim | hard | {
"lang": "python",
"repo": "i404788/distributed-worker",
"path": "/distributed_worker/manager.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return [(x, self.pipes[x]) for x in self.get_active_workers()]
def get_active_workers(self):
ret = []
for i, pipe in enumerate(self.pipes):
last_msg = self.last_message_time.get(i, 0)
if last_msg + self.ttl > time.time():
ret.append(i)
... | code_fim | hard | {
"lang": "python",
"repo": "i404788/distributed-worker",
"path": "/distributed_worker/manager.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: i404788/distributed-worker path: /distributed_worker/manager.py
from typing import Tuple, Mapping, List, Any
import multiprocessing
from multiprocessing.connection import Listener, Client, Pipe
import select
import time
from .worker import create_worker
default_address = 'localhost'
default_po... | code_fim | hard | {
"lang": "python",
"repo": "i404788/distributed-worker",
"path": "/distributed_worker/manager.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># return it mohamed
#uriMementos.txt
mementosFile = open("memento.txt","w")
i = 0
for s in links:
p = subprocess.Popen(['curl',"http://web.archive.org/web/timemap/link/"+s], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = p.communicate()
i = i + 1
sys.stdout.flush()
sys.stdout.write("calc... | code_fim | medium | {
"lang": "python",
"repo": "maturban/cs595-f13",
"path": "/Assignment2/CDXaggregator/getMementos.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: maturban/cs595-f13 path: /Assignment2/CDXaggregator/getMementos.py
# -*- encoding: utf-8 -*-
import os
import sys
from datetime import datetime,date
import subprocess
import simplejson
<|fim_suffix|>i = 0
for s in links:
p = subprocess.Popen(['curl',"http://web.archive.org/web/timemap/link/"+s... | code_fim | medium | {
"lang": "python",
"repo": "maturban/cs595-f13",
"path": "/Assignment2/CDXaggregator/getMementos.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return 'soft'
elif obj[0] == 'pre-presbyopic':
return 'soft'
elif obj[2] == 'yes':
return 'none'<|fim_prefix|># repo: rajes95/intro_to_artificial_intelligence path: /4_ID3_classifier/outputs/rules/rules.py
def findDecision(obj): #obj[0]: age, obj[1]: spectacle... | code_fim | hard | {
"lang": "python",
"repo": "rajes95/intro_to_artificial_intelligence",
"path": "/4_ID3_classifier/outputs/rules/rules.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rajes95/intro_to_artificial_intelligence path: /4_ID3_classifier/outputs/rules/rules.py
def findDecision(obj): #obj[0]: age, obj[1]: spectacle-prescription, obj[2]: astigmatism, obj[3]: tear-prod-rate
if obj[3] == 'reduced':
<|fim_suffix|>':
return 'none'
elif obj[1]... | code_fim | hard | {
"lang": "python",
"repo": "rajes95/intro_to_artificial_intelligence",
"path": "/4_ID3_classifier/outputs/rules/rules.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amcardie/discord-bot path: /cogs/moderation.py
import discord
from discord.ext import commands
import re
import asyncio
time_regex = re.compile("(?:(\d{1,5})(h|s|m|d))+?")
time_dict = {"h":3600, "s":1, "m":60, "d":86400}
class TimeConverter(commands.Converter):
async def convert(se... | code_fim | hard | {
"lang": "python",
"repo": "amcardie/discord-bot",
"path": "/cogs/moderation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if time:
await asyncio.sleep(time)
await member.remove_roles(role)
@commands.command()
@commands.has_permissions(manage_roles=True)
async def unmute(self, ctx, member: discord.Member = None):
if not member:
return await ctx.reply... | code_fim | hard | {
"lang": "python",
"repo": "amcardie/discord-bot",
"path": "/cogs/moderation.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: feer56/Kitsune1 path: /kitsune/questions/migrations/0005_auto__add_field_answer_is_spam__add_field_answer_marked_as_spam__add_f.py
# -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
... | code_fim | hard | {
"lang": "python",
"repo": "feer56/Kitsune1",
"path": "/kitsune/questions/migrations/0005_auto__add_field_answer_is_spam__add_field_answer_marked_as_spam__add_f.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> models = {
u'auth.group': {
'Meta': {'object_name': 'Group'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('d... | code_fim | hard | {
"lang": "python",
"repo": "feer56/Kitsune1",
"path": "/kitsune/questions/migrations/0005_auto__add_field_answer_is_spam__add_field_answer_marked_as_spam__add_f.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
models = {
u'auth.group': {
'Meta': {'object_name': 'Group'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('... | code_fim | hard | {
"lang": "python",
"repo": "feer56/Kitsune1",
"path": "/kitsune/questions/migrations/0005_auto__add_field_answer_is_spam__add_field_answer_marked_as_spam__add_f.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gcandal/ripe-api path: /src/ripe/order.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
import json
class OrderAPI(object):
@classmethod
def load_order(cls, order):
structure = order.get("structure", None)
if structure: order["details"] = json.loads(structure)
... | code_fim | hard | {
"lang": "python",
"repo": "gcandal/ripe-api",
"path": "/src/ripe/order.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> url = self.base_url + "orders"
contents = self.post(url, data_j = order)
return contents
def get_order(self, number):
url = self.base_url + "orders/%d" % number
contents = self.get(url)
return contents
def price_order(self, number, currenc... | code_fim | hard | {
"lang": "python",
"repo": "gcandal/ripe-api",
"path": "/src/ripe/order.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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