text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: sagarnikam123/learnNPractice path: /hackerRank/tracks/languages/python/4_sets/9_set.symmetricDifferenceOperation.py
# Set .symmetric_difference() Operation
#######################################################################################################################
#
# .symmetric_dif... | code_fim | hard | {
"lang": "python",
"repo": "sagarnikam123/learnNPractice",
"path": "/hackerRank/tracks/languages/python/4_sets/9_set.symmetricDifferenceOperation.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> p.cast(DrawBotPen).draw_with_filters(rect, filters)
return p
return _draw_call
def page_rect() -> Rect:
return Rect(db.width(), db.height())
@contextlib.contextmanager
def new_page(r:Rect=Rect(1000, 1000)):
_r = Rect(r)
db.newPage(*_r.wh())
yield _r
@contextlib.conte... | code_fim | hard | {
"lang": "python",
"repo": "econchick/coldtype",
"path": "/coldtype/drawbot.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: econchick/coldtype path: /coldtype/drawbot.py
import contextlib
import drawBot as db
from coldtype.geometry import Point, Line, Rect
from coldtype.pens.drawbotpen import DrawBotPen
from coldtype.pens.draftingpen import DraftingPen
from coldtype.pens.draftingpens import DraftingPens
from coldtype.... | code_fim | hard | {
"lang": "python",
"repo": "econchick/coldtype",
"path": "/coldtype/drawbot.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _draw_call(p:DraftingPen):
p.cast(DrawBotPen).draw_with_filters(rect, filters)
return p
return _draw_call
def page_rect() -> Rect:
return Rect(db.width(), db.height())
@contextlib.contextmanager
def new_page(r:Rect=Rect(1000, 1000)):
_r = Rect(r)
db.newPage(*_r.wh... | code_fim | hard | {
"lang": "python",
"repo": "econchick/coldtype",
"path": "/coldtype/drawbot.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return _p.createFunction( function,_p.PLATFORM.GLES2,'GLES2_EXT_texture_norm16',error_checker=_errors._error_checker)
GL_R16_EXT=_C('GL_R16_EXT',0x822A)
GL_R16_SNORM_EXT=_C('GL_R16_SNORM_EXT',0x8F98)
GL_RG16_EXT=_C('GL_RG16_EXT',0x822C)
GL_RG16_SNORM_EXT=_C('GL_RG16_SNORM_EXT',0x8F99)
GL_RGB16_EXT=_C(... | code_fim | medium | {
"lang": "python",
"repo": "juso40/bl2sdk_Mods",
"path": "/blimgui/dist/OpenGL/raw/GLES2/EXT/texture_norm16.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juso40/bl2sdk_Mods path: /blimgui/dist/OpenGL/raw/GLES2/EXT/texture_norm16.py
'''Autogenerated by xml_generate script, do not edit!'''
from OpenGL import platform as _p, arrays
# Code generation uses this
from OpenGL.raw.GLES2 import _types as _cs
# End users want this...
from OpenGL.raw.GLES2._t... | code_fim | medium | {
"lang": "python",
"repo": "juso40/bl2sdk_Mods",
"path": "/blimgui/dist/OpenGL/raw/GLES2/EXT/texture_norm16.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: emjelde/pytiles path: /components.py
#!/usr/bin/python
# Copyright (C) 2014 - Evan Mjelde
#
# 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/lic... | code_fim | hard | {
"lang": "python",
"repo": "emjelde/pytiles",
"path": "/components.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, name, items=None, inherit=True, **kwargs):
"""Keyword arguments:
items -- Array of initial items.
inherit -- Lets you know if it should inherit items on merge. (Default: True)
"""
self.items = items if items is not None else []
... | code_fim | hard | {
"lang": "python",
"repo": "emjelde/pytiles",
"path": "/components.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lecklis/python_auto_office path: /B站/Python自动化办公 · 一课通（适合小白）/Chapter1/S1-1-1/LessonCode/1.1read.py
import xlrd
xlsx = xlrd.open_workbook('d:/7月下旬入库表.xlsx')
<|fim_suffix|># table.cell_value(1, 2)
# print(table.cell(1, 2).value)
# print(table.row(1)[2].value)
for i in range(0, xlsx.nsheets):
... | code_fim | medium | {
"lang": "python",
"repo": "lecklis/python_auto_office",
"path": "/B站/Python自动化办公 · 一课通（适合小白）/Chapter1/S1-1-1/LessonCode/1.1read.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in xlsx.sheet_names():
table = xlsx.sheet_by_name(i)
print(table.cell_value(3, 3))<|fim_prefix|># repo: lecklis/python_auto_office path: /B站/Python自动化办公 · 一课通（适合小白）/Chapter1/S1-1-1/LessonCode/1.1read.py
import xlrd
xlsx = xlrd.open_workbook('d:/7月下旬入库表.xlsx')
table = xlsx.sheet_by_index(0... | code_fim | medium | {
"lang": "python",
"repo": "lecklis/python_auto_office",
"path": "/B站/Python自动化办公 · 一课通（适合小白）/Chapter1/S1-1-1/LessonCode/1.1read.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: claudemp/iem path: /scripts/climodat/check_database.py
"""
Check over the database and make sure we have what we need there to
make the climodat reports happy...
"""
from __future__ import print_function
import sys
import mx.DateTime
from pyiem.network import Table as NetworkTable
from pyiem.u... | code_fim | hard | {
"lang": "python",
"repo": "claudemp/iem",
"path": "/scripts/climodat/check_database.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
"""Go Main"""
for station in nt.sts:
sts = mx.DateTime.DateTime(constants.startyear(station), 1, 1)
ets = constants._ENDTS
# Check for obs total
now = sts
interval = mx.DateTime.RelativeDateTime(years=1)
while now < (ets - interval):
... | code_fim | hard | {
"lang": "python",
"repo": "claudemp/iem",
"path": "/scripts/climodat/check_database.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Check records database...
sts = mx.DateTime.DateTime(2000, 1, 1)
ets = mx.DateTime.DateTime(2001, 1, 1)
interval = mx.DateTime.RelativeDateTime(days=1)
for table in ['climate', 'climate51', 'climate71', 'climate81']:
ccursor.execute("""SELECT count(*) ... | code_fim | hard | {
"lang": "python",
"repo": "claudemp/iem",
"path": "/scripts/climodat/check_database.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: saeeddhqan/natural-language-processing-for-osint path: /m3/document similarity/ds.py
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfVectorizer
import nltk
from nltk.corpus import stopwords
import re
def rstopwords(... | code_fim | hard | {
"lang": "python",
"repo": "saeeddhqan/natural-language-processing-for-osint",
"path": "/m3/document similarity/ds.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def punc(doc):
replace = re.sub(r"[\W]+", " ", doc)
return " ".join(replace.split())
def euclidean_distance(x, y):
return np.sqrt(np.sum((x - y) ** 2))
def cosine_similarity(x,y):
return np.dot(x, y) / (np.sqrt(np.dot(x, x)) * np.sqrt(np.dot(y, y)))
doc1 = open('ML.txt').read()
doc2 = open('DL.txt'... | code_fim | hard | {
"lang": "python",
"repo": "saeeddhqan/natural-language-processing-for-osint",
"path": "/m3/document similarity/ds.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>data = np.array(data)
print('ML - DL', cosine_similarity(data[0], data[1]))
print('ML - MJ', cosine_similarity(data[0], data[2]))
print('ML - AI', cosine_similarity(data[0], data[3]))
print('DL - MJ', cosine_similarity(data[1], data[2]))
print('DL - AI', cosine_similarity(data[1], data[3]))
print('AI - ... | code_fim | hard | {
"lang": "python",
"repo": "saeeddhqan/natural-language-processing-for-osint",
"path": "/m3/document similarity/ds.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MarlonIC/demo-clean-architecture-projects-tasks path: /tests/test_main.py
import os
import sys
import taskit.__main__
from subprocess import run
from pytest import fixture
from unittest.mock import Mock, patch
from taskit.__main__ import main, build_state
@fixture(scope='module')
def taskit_dir... | code_fim | medium | {
"lang": "python",
"repo": "MarlonIC/demo-clean-architecture-projects-tasks",
"path": "/tests/test_main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_main_db_file_not_empty(taskit_dir) -> None:
sandbox = patch.dict(os.environ, {'TASKIT_DIR': taskit_dir})
sandbox.start()
db_path = os.sep.join([taskit_dir, 'db.json'])
with open(db_path, 'w+') as f:
f.write('{"projects": {}}')
python_bin = sys.executable
result = r... | code_fim | hard | {
"lang": "python",
"repo": "MarlonIC/demo-clean-architecture-projects-tasks",
"path": "/tests/test_main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jschultz/Gooey path: /gooey/gui/windows/base_window.py
'''
Created on Jan 19, 2014
@author: Chris
'''
import sys
import wx
from gooey.gui import image_repository, events
from gooey.gui.lang.i18n import _
from gooey.gui.pubsub import pub
from gooey.gui.util import wx_util
from gooe... | code_fim | hard | {
"lang": "python",
"repo": "jschultz/Gooey",
"path": "/gooey/gui/windows/base_window.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def onResize(self, evt):
evt.Skip()
def onClose(self, evt):
if evt.CanVeto():
evt.Veto()
pub.send_message(str(events.WINDOW_CLOSE))
def UpdateProgressBar(self, value, disable_animation=False):
pb = self.foot_panel.progress_bar
if value < 0:
pb.Pulse()
... | code_fim | hard | {
"lang": "python",
"repo": "jschultz/Gooey",
"path": "/gooey/gui/windows/base_window.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>assert number_of_keys_with_foo_in_name(test_2) == 0
print("it works, congrats!")<|fim_prefix|># repo: toumorokoshi/python-code-challenges path: /07/23.py
def number_of_keys_with_foo_in_name(my_dict):
""" return an integer, with the number of keys with the string "foo" in them. """
z = []
for... | code_fim | hard | {
"lang": "python",
"repo": "toumorokoshi/python-code-challenges",
"path": "/07/23.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: toumorokoshi/python-code-challenges path: /07/23.py
def number_of_keys_with_foo_in_name(my_dict):
""" return an integer, with the number of keys with the string "foo" in them. """
z = []
for x in my_dict:
b = x.find("foo", 0)
if b is not -1:
z.append(b)
... | code_fim | medium | {
"lang": "python",
"repo": "toumorokoshi/python-code-challenges",
"path": "/07/23.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>bytes = s.send(msg)
begin = time.time()
print "Bytes sent %d" % bytes
c = s.recv(5000)
end = time.time()
print "RECEIVE: '%s'" % c
print "TIMEOUT PERIOD: %d" % (end - begin)<|fim_prefix|># repo: kongyew/gpdb path: /gpMgmt/test/behave_utils/gpfdist_utils/gpfdist_client.py
#!/usr/bin/env python
import ... | code_fim | medium | {
"lang": "python",
"repo": "kongyew/gpdb",
"path": "/gpMgmt/test/behave_utils/gpfdist_utils/gpfdist_client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kongyew/gpdb path: /gpMgmt/test/behave_utils/gpfdist_utils/gpfdist_client.py
#!/usr/bin/env python
import socket, time
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
if not s:
raise Exception("socket not created")
s.connect(("localhost", 8088))
print "connected"
msg = """GET /data... | code_fim | easy | {
"lang": "python",
"repo": "kongyew/gpdb",
"path": "/gpMgmt/test/behave_utils/gpfdist_utils/gpfdist_client.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>msg = """GET /data.txt HTTP/1.1
Host: localhost"""
bytes = s.send(msg)
begin = time.time()
print "Bytes sent %d" % bytes
c = s.recv(5000)
end = time.time()
print "RECEIVE: '%s'" % c
print "TIMEOUT PERIOD: %d" % (end - begin)<|fim_prefix|># repo: kongyew/gpdb path: /gpMgmt/test/behave_utils/gpfdist_ut... | code_fim | medium | {
"lang": "python",
"repo": "kongyew/gpdb",
"path": "/gpMgmt/test/behave_utils/gpfdist_utils/gpfdist_client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('course', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='coursesmodel',
name='duration',
field=models.CharField(max_length=255),
),
]<|fim_prefix|># repo: dewale005/whitefieldcoursesite p... | code_fim | easy | {
"lang": "python",
"repo": "dewale005/whitefieldcoursesite",
"path": "/course/migrations/0002_alter_coursesmodel_duration.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dewale005/whitefieldcoursesite path: /course/migrations/0002_alter_coursesmodel_duration.py
# Generated by Django 3.2.6 on 2021-08-25 14:57
from django.db import migrations, models
<|fim_suffix|> dependencies = [
('course', '0001_initial'),
]
operations = [
migration... | code_fim | easy | {
"lang": "python",
"repo": "dewale005/whitefieldcoursesite",
"path": "/course/migrations/0002_alter_coursesmodel_duration.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='coursesmodel',
name='duration',
field=models.CharField(max_length=255),
),
]<|fim_prefix|># repo: dewale005/whitefieldcoursesite path: /course/migrations/0002_alter_coursesmodel_duration.py
# Gen... | code_fim | medium | {
"lang": "python",
"repo": "dewale005/whitefieldcoursesite",
"path": "/course/migrations/0002_alter_coursesmodel_duration.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ccsValidator('Cold-Measurement')<|fim_prefix|># repo: lsst-camera-dh/harnessed-jobs path: /BNL_T05/Cold_Measurement/v0/validator_Cold-Measurement.py
#!/usr/bin/env python
from ccsTools import ccsValidator
import glob
import os
<|fim_middle|>datfile = glob.glob("*.csv")[0]
os.system("grep \"^#\" %s > tem... | code_fim | medium | {
"lang": "python",
"repo": "lsst-camera-dh/harnessed-jobs",
"path": "/BNL_T05/Cold_Measurement/v0/validator_Cold-Measurement.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lsst-camera-dh/harnessed-jobs path: /BNL_T05/Cold_Measurement/v0/validator_Cold-Measurement.py
#!/usr/bin/env python
from ccsTools import ccsValidator
import glob
import os
<|fim_suffix|>ccsValidator('Cold-Measurement')<|fim_middle|>datfile = glob.glob("*.csv")[0]
os.system("grep \"^#\" %s > tem... | code_fim | medium | {
"lang": "python",
"repo": "lsst-camera-dh/harnessed-jobs",
"path": "/BNL_T05/Cold_Measurement/v0/validator_Cold-Measurement.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Runs the API and gets the statis
def get_max_core_usage(self, sdate, edate, limit):
metrics_api = "/analytics/metrics/controller"
params = {
'metric_id': 'controller_stats.max_num_se_cores',
'step': 86400,
'start': sdate,
'stop': ed... | code_fim | hard | {
"lang": "python",
"repo": "sjafferali/devops",
"path": "/python/core_useage.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sjafferali/devops path: /python/core_useage.py
#####################################################################################
# Script to get max CPU usage by Avi SEs over given time period
# usage: python core_useage.py [-h] [-v AVI_VERSION] [-s STARTDATE] [-e ENDDATE]
# ... | code_fim | hard | {
"lang": "python",
"repo": "sjafferali/devops",
"path": "/python/core_useage.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # add list item
# find out which list was asked
for lists,contents in rmds.items():
if lists in self.query:
# add list item
data = {}
data["name"] = ' '.join( self.query[ self.query.index("add")+1:self.query.index("to") ] )
rmds[lists].app... | code_fim | hard | {
"lang": "python",
"repo": "1egoman/qlists",
"path": "/rmd.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 1egoman/qlists path: /rmd.py
from base import *
import os
import datetime
import json
# to-do list words
todo_words = ["todo", "to do", "to-do", "reminder", "remind", "list"]
remove_words = ["check", "remove", "cross", "crossout", "checkoff", "delete"]
remove_preps = ["on", "from", "at"]
"""
M... | code_fim | hard | {
"lang": "python",
"repo": "1egoman/qlists",
"path": "/rmd.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: albertmas/Image-Filters path: /Exercises/MorphologicalFilters.py
import numpy as np
import cv2
def ErosionFilter(img, times=1):
rows, cols = img.shape
paddedimg = np.ones((rows + 2, cols + 2))
paddedimg[:, :] = 255
paddedimg[1:-1, 1:-1] = img.copy()
newimg = img.copy()
f... | code_fim | hard | {
"lang": "python",
"repo": "albertmas/Image-Filters",
"path": "/Exercises/MorphologicalFilters.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
image = cv2.imread("binary.png", cv2.IMREAD_GRAYSCALE)
filteredImg = DilationFilter(image, 1)
filteredImg = ErosionFilter(filteredImg, 6)
# cv2.imshow('Image', np.hstack((image, filteredImg)))
cv2.imshow('Original', image)
cv2.imshow('Filtered', filtered... | code_fim | hard | {
"lang": "python",
"repo": "albertmas/Image-Filters",
"path": "/Exercises/MorphologicalFilters.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Finds the flow table entry that matches the given packet.
Returns the highest priority flow table entry that matches the given packet
on the given in_port, or None if no matching entry is found.
"""
packet_match = ofp_match.from_packet(packet, in_port, spec_frags = True)
... | code_fim | hard | {
"lang": "python",
"repo": "noxrepo/pox",
"path": "/pox/openflow/flow_table.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._table
def __len__ (self):
return len(self._table)
def add_entry (self, entry):
assert isinstance(entry, TableEntry)
#self._table.append(entry)
#self._table.sort(key=lambda e: e.effective_priority, reverse=True)
# Use binary search to insert at correct place
... | code_fim | hard | {
"lang": "python",
"repo": "noxrepo/pox",
"path": "/pox/openflow/flow_table.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: noxrepo/pox path: /pox/openflow/flow_table.py
# Copyright 2011,2012,2013 Colin Scott
#
# 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/lice... | code_fim | hard | {
"lang": "python",
"repo": "noxrepo/pox",
"path": "/pox/openflow/flow_table.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: easyopsapis/easyops-api-python path: /scheduler_sdk/model/cmdb_extend/subsystem_dependency_pb2.py
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: subsystem_dependency.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('la... | code_fim | hard | {
"lang": "python",
"repo": "easyopsapis/easyops-api-python",
"path": "/scheduler_sdk/model/cmdb_extend/subsystem_dependency_pb2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>_SUBSYSTEMDEPENDENCY_CONNECTSUBSYSTEMS.containing_type = _SUBSYSTEMDEPENDENCY
_SUBSYSTEMDEPENDENCY.fields_by_name['components'].message_type = scheduler__sdk_dot_model_dot_cmdb__extend_dot_app__dependency__pb2._APPDEPENDENCY
_SUBSYSTEMDEPENDENCY.fields_by_name['connect_subsystems'].message_type = _SUBSYST... | code_fim | hard | {
"lang": "python",
"repo": "easyopsapis/easyops-api-python",
"path": "/scheduler_sdk/model/cmdb_extend/subsystem_dependency_pb2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.scale = facette_to_json(GRAPH_GROUP_SCALE, js, self.group)
def set(self, name=None, type=None, stack_id=None, series=None, scale=None):
self.name = facette_set(name, GRAPH_GROUP_NAME, self.group)
self.type = facette_set(type, GRAPH_GROUP_TYPE, ... | code_fim | hard | {
"lang": "python",
"repo": "OpenTouch/python-facette",
"path": "/src/facette/v1/graphgroup.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OpenTouch/python-facette path: /src/facette/v1/graphgroup.py
from facette.utils import *
from facette.v1.graphgroupserie import GraphGroupSerie
import json
GRAPH_GROUP_NAME = "name"
GRAPH_GROUP_TYPE = "type"
GRAPH_GROUP_STACK_ID = "stack_id"
GRAPH_GROUP_SERIES = "series"
GRAPH_GROUP_SC... | code_fim | hard | {
"lang": "python",
"repo": "OpenTouch/python-facette",
"path": "/src/facette/v1/graphgroup.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(not ())
print(not (1,))
print(not [])
print(not [1,])
print(not {})
print(not {1:1})<|fim_prefix|># repo: jiapei100/Stereo path: /micropython/tests/basics/unary_op.py
print(not None)
print(not False)
print(not Tr<|fim_middle|>ue)
print(not 0)
print(not 1)
print(not -1)
| code_fim | easy | {
"lang": "python",
"repo": "jiapei100/Stereo",
"path": "/micropython/tests/basics/unary_op.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jiapei100/Stereo path: /micropython/tests/basics/unary_op.py
print(not None)
print(not False)
print(not True)
print(not 0)
print(not 1)
print(not -1)
<|fim_suffix|>print(not [1,])
print(not {})
print(not {1:1})<|fim_middle|>print(not ())
print(not (1,))
print(not [])
| code_fim | easy | {
"lang": "python",
"repo": "jiapei100/Stereo",
"path": "/micropython/tests/basics/unary_op.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def val_loss():
net.eval()
result = []
for item in data['val']:
item = {key: value.to(_device) for key, value in item.items()}
result.append(net.cost(item).item())
net.train()
return torch.tensor(result).mean()
net.to(_device)
... | code_fim | hard | {
"lang": "python",
"repo": "gchrupala/platalea",
"path": "/platalea/basic.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> stepsize = n_batches * 4
logging.info("Setting stepsize of {}".format(stepsize))
lr_lambda = lambda iteration: (max_lr - min_lr)*(0.5 * (np.cos(np.pi * (1 + (3 - 1) / stepsize * iteration)) + 1))+min_lr
scheduler = lr_scheduler.LambdaLR(optimizer, lr_lambda, last_epoch=-1)
# lambda fun... | code_fim | hard | {
"lang": "python",
"repo": "gchrupala/platalea",
"path": "/platalea/basic.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gchrupala/platalea path: /platalea/basic.py
from collections import Counter
import logging
import json
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
from platalea.encoders import SpeechEncoder, ImageEncoder
import platalea.... | code_fim | hard | {
"lang": "python",
"repo": "gchrupala/platalea",
"path": "/platalea/basic.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> async def test_pre_refresh_token_callback__raises_key_error(self):
authorizer = DummyAuthorizer(None)
with pytest.raises(KeyError):
await self.manager.pre_refresh_callback(authorizer)
await self.manager.close()
async def test_register(self):
assert awa... | code_fim | hard | {
"lang": "python",
"repo": "LilSpazJoekp/asyncpraw",
"path": "/tests/unit/util/test_token_manager.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LilSpazJoekp/asyncpraw path: /tests/unit/util/test_token_manager.py
"""Test asyncpraw.util.refresh_token_manager."""
import sys
from tempfile import NamedTemporaryFile
import aiofiles
import pytest
from asynctest import mock
from asyncpraw.util.token_manager import (
BaseTokenManager,
F... | code_fim | hard | {
"lang": "python",
"repo": "LilSpazJoekp/asyncpraw",
"path": "/tests/unit/util/test_token_manager.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> await self.manager.post_refresh_callback(authorizer)
assert authorizer.refresh_token is None
assert await self.manager._get() == "dummy_value_updated"
await self.manager.close()
async def test_pre_refresh_token_callback(self):
authorizer = DummyAuthorizer(None)... | code_fim | hard | {
"lang": "python",
"repo": "LilSpazJoekp/asyncpraw",
"path": "/tests/unit/util/test_token_manager.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> test_preds += preds.numpy()
score = calculate_overall_lwlrap_sklearn(oof_preds, transformed_y).numpy()[0]
print("Saving out-of-fold predictions...")
all_oof_preds = pd.DataFrame(np.hstack((filenames, oof_preds)), columns = test.columns)
all_oof_preds.to_csv('../kfolds/{}__{}.csv'.format(MODEL_NAME, ... | code_fim | hard | {
"lang": "python",
"repo": "JoshVarty/AudioTagging",
"path": "/src/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>mskf = MultilabelStratifiedKFold(n_splits=5, random_state=4, shuffle=True)
for train_index, val_index in mskf.split(X, transformed_y):
#Our clasifier stuff
src = (ImageList.from_csv('../'/WORK/'image', Path('../../')/CSV_TRN_CURATED, folder='trn_curated', suffix='.jpg')
.split_by_idx(v... | code_fim | hard | {
"lang": "python",
"repo": "JoshVarty/AudioTagging",
"path": "/src/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JoshVarty/AudioTagging path: /src/main.py
import os
import shutil
import pandas as pd
import numpy as np
from sklearn.preprocessing import MultiLabelBinarizer
from iterstrat.ml_stratifiers import MultilabelStratifiedKFold
from fastai.vision import *
import sklearn.metrics
# Make required folders... | code_fim | hard | {
"lang": "python",
"repo": "JoshVarty/AudioTagging",
"path": "/src/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pgjones/quart path: /src/quart/debug.py
from __future__ import annotations
import inspect
import sys
from jinja2 import Template
from .wrappers import Response
TEMPLATE = """
<style>
pre {
margin: 0;
}
.traceback, .locals {
display: table;
width: 100%;
margin: 5px;
}
.traceback>div,... | code_fim | hard | {
"lang": "python",
"repo": "pgjones/quart",
"path": "/src/quart/debug.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|><h1>{{ name }} <span>{{ value }}</span></h1>
<ul>
{% for frame in frames %}
<li>
<div class="header">
File <span class="info">{{ frame.file }}</span>,
line <span class="info">{{ frame.line }}</span>, in
</div>
<div class="traceback">
{% for line in frame.cod... | code_fim | hard | {
"lang": "python",
"repo": "pgjones/quart",
"path": "/src/quart/debug.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jatin69/du-result-fetcher path: /development/2018/merge-restructured/config.py
VIEWSTATE = '/wEPDwUKMTU1ODI4OTc2Mw8WAh4JSXBBZGRyZXNzBQwxMDMuNzguMTQ4LjgWAgIDD2QWCgIBD2QWAgIFDw8WAh4EVGV4dAU0UmVzdWx0cyAoMy1ZZWFyIFNlbWVzdGVyIEV4YW1pbmF0aW9uIE1heS1KdW5lIDIwMTggKWRkAgcPDxYCHwEFECAoTWF5LUp1bmUgMjAxOClkZ... | code_fim | hard | {
"lang": "python",
"repo": "jatin69/du-result-fetcher",
"path": "/development/2018/merge-restructured/config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>yMzMDMjM3AzIyMwMwMTkDMDEwAzMxNAMwMjEDMDIyAzEwOQMwMjQDMDI1AzAyNgMwMjkDMDI4AzAzMAMwMzEDMDMyAzMwNgMwMzMDMDM0AzAzNQMwMzYDMDM4AzAzOQMwNDADMzEwAzMxMQMwNDEDMzE1AzA0MwMwNDQDMDQ3AzA0OAMwNDkDMDUzAzA1NAMwNTUDMDU4AzAyMAMwNTYDMDY4AzA2MgMwNjMDU09MAzA2NAMwNjUDMDY2AzA2NwMwNzEDMDczAzA3NAMwNzUEU09MUwMwNzYDMDc3AzA3OAMwNjkDM... | code_fim | hard | {
"lang": "python",
"repo": "jatin69/du-result-fetcher",
"path": "/development/2018/merge-restructured/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vicb1/python-reference path: /code/algorithms/bst-master/tests/test_bst_base.py
import unittest
from bst import BST, Node
class TestBSTBase(unittest.TestCase):
def setUp(self):
<|fim_suffix|> self.subject.root = Node(25)
self.subject.root.left = Node(15)
self.subject.... | code_fim | medium | {
"lang": "python",
"repo": "vicb1/python-reference",
"path": "/code/algorithms/bst-master/tests/test_bst_base.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.subject.root = Node(25)
self.subject.root.left = Node(15)
self.subject.root.right = Node(50)
self.subject.root.left.left = Node(10)
self.subject.root.left.right = Node(22)
self.subject.root.left.left.left = Node(4)
self.subject.root.left.left.ri... | code_fim | medium | {
"lang": "python",
"repo": "vicb1/python-reference",
"path": "/code/algorithms/bst-master/tests/test_bst_base.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: beneduzi/METEO path: /ecmwf_inmet/py/ecmwf_csv.py
#!/usr/bin/python
# coding: utf-8
import numpy as np
import netCDF4
import math
import sys
import time
import calendar
import datetime
from math import pi
from numpy import cos, sin, arccos, power, sqrt, exp,arctan2
## Entrada
filename = (sys.ar... | code_fim | hard | {
"lang": "python",
"repo": "beneduzi/METEO",
"path": "/ecmwf_inmet/py/ecmwf_csv.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> d1 = date0 + datetime.timedelta(hours = i*12 + utc0)
hora = d1.strftime('%Y%m%d %H:%M')
tempc = tempk[i,ix,iy] - 273.15
# tempc_min = tempk_min[i,ix,iy] - 273.15
# tempc_max = tempk_max[i,ix,iy] - 273.15
# chuva_co = chuva_c[i,ix,iy] * 1000
chuva_to = chuva_t[i,ix,iy] * 1000
# if chuva_co < 0:
# chuv... | code_fim | hard | {
"lang": "python",
"repo": "beneduzi/METEO",
"path": "/ecmwf_inmet/py/ecmwf_csv.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>##########################################################################################
#indices das coordenandas
#iz,ix,iy = tunnel_fast(latvar, lonvar, lat0, lon0)
ix,iy = tunnel_fast(latvar, lonvar, lat0, lon0)
max_i = len(time)
####################################################################... | code_fim | hard | {
"lang": "python",
"repo": "beneduzi/METEO",
"path": "/ecmwf_inmet/py/ecmwf_csv.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from pylightnix import PYLIGHTNIX_ROOT, PYLIGHTNIX_STORE, PYLIGHTNIX_TMP
if not isdir(PYLIGHTNIX_ROOT):
print(
f"Warning: PYLIGHTNIX_ROOT directory ('{PYLIGHTNIX_ROOT}') doesn`t exist. "
f"Please create either direcotry or a symlink with this name.")
assert isdir(PYLIGHTNIX_STORE), \
(f"PYL... | code_fim | hard | {
"lang": "python",
"repo": "stagedml/stagedml",
"path": "/src/stagedml/devenv.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert isfile(join(STAGEDML_ROOT,'3rdparty','tensorflow_models','README.md')), \
(f"Git submodule {join(STAGEDML_ROOT,'3rdparty','tensorflow_models')} looks uninitialized. "
f"Did you run `git submodule update --init`?")
else:
print(f"STAGEDML_ROOT env var is not set. We assume that you d... | code_fim | hard | {
"lang": "python",
"repo": "stagedml/stagedml",
"path": "/src/stagedml/devenv.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stagedml/stagedml path: /src/stagedml/devenv.py
from os import environ
from os.path import join, islink, isdir, isfile
from stagedml.utils.files import assert_link
import tensorflow as tf
assert tf.version.VERSION.startswith('2.1') or \
tf.version.VERSION.startswith('2.2'), \
(f"Stage... | code_fim | hard | {
"lang": "python",
"repo": "stagedml/stagedml",
"path": "/src/stagedml/devenv.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SentientHome/SentientHome path: /feed/feed.home.nest.py
#!/usr/local/bin/python3 -u
"""
Author: Oliver Ratzesberger <https://github.com/fxstein>
Copyright: Copyright (C) 2016 Oliver Ratzesberger
License: Apache License, Version 2.0
"""
# Make sure we have access to SentientHo... | code_fim | hard | {
"lang": "python",
"repo": "SentientHome/SentientHome",
"path": "/feed/feed.home.nest.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> while True:
retries = 0
# app.log.info(json.dumps(nest._status, sort_keys=True))
# exit(1)
# Retry loop for Nest communications
while True:
try:
# Loop through Nest structures aka homes
for structure in nest.structur... | code_fim | hard | {
"lang": "python",
"repo": "SentientHome/SentientHome",
"path": "/feed/feed.home.nest.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tms1337/crypto-trader path: /bot/strategy/deciders/simple/offer/tests/test_percentbased.py
import unittest
from bot.strategy.deciders.simple.offer.percentbased import PercentBasedOfferDecider
from bot.strategy.decision import OfferType
from bot.strategy.pipeline.data.statsmatrix import StatsMatr... | code_fim | hard | {
"lang": "python",
"repo": "tms1337/crypto-trader",
"path": "/bot/strategy/deciders/simple/offer/tests/test_percentbased.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.decider = PercentBasedOfferDecider(buy_threshold=0,
sell_threshold=0.1,
currencies=self.currencies,
trading_currency="BTC",
... | code_fim | hard | {
"lang": "python",
"repo": "tms1337/crypto-trader",
"path": "/bot/strategy/deciders/simple/offer/tests/test_percentbased.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.informer = InformerMock([1, 1, 1, 1.11, 1.11],
self.exchanges,
self.currencies)
self._assert_buy()
self._assert_none()
self._assert_none()
self._assert_sell()
self._assert_buy()
... | code_fim | hard | {
"lang": "python",
"repo": "tms1337/crypto-trader",
"path": "/bot/strategy/deciders/simple/offer/tests/test_percentbased.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Trainer(BaseTrainer):
def data(self):
(x_train, y_train), (x_eval, y_eval) = datasets.boston_housing.load_data()
x_train, x_eval = preprocess.standardize(x_train, x_eval)
train_data, eval_data = (x_train, y_train), (x_eval, y_eval)
return train_data, eval_dat... | code_fim | medium | {
"lang": "python",
"repo": "daodaoliang/ModelZoo",
"path": "/examples/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: daodaoliang/ModelZoo path: /examples/train.py
from model_zoo import flags, datasets, preprocess
from model_zoo.trainer import BaseTrainer
<|fim_suffix|>class Trainer(BaseTrainer):
def data(self):
(x_train, y_train), (x_eval, y_eval) = datasets.boston_housing.load_data()
... | code_fim | medium | {
"lang": "python",
"repo": "daodaoliang/ModelZoo",
"path": "/examples/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return len(s1) == len(s2)
str2lower_if_samelength = \
FunctionTool.funcs_cond2compiled([cls.str2lower], f_cond)
def str2lower_eachchar(s):
return "".join(lmap(str2lower_if_samelength, s))
funcs = [cls.str2lower,
str2lower_each... | code_fim | hard | {
"lang": "python",
"repo": "yerihyo/foxylib",
"path": "/foxylib/tools/string/string_tool.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yerihyo/foxylib path: /foxylib/tools/string/string_tool.py
import ast
import random
import re
from functools import reduce
from operator import itemgetter as ig
from typing import List
from future.utils import lmap, lfilter
from nose.tools import assert_false
from foxylib.tools.collections.iter... | code_fim | hard | {
"lang": "python",
"repo": "yerihyo/foxylib",
"path": "/foxylib/tools/string/string_tool.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GabriellBP/mlclass path: /03_Validation/mlp.py
# testing attributes for MLP
import pandas as pd
from sklearn.neural_network import MLPClassifier
from sklearn.preprocessing import MinMaxScaler
# different learning rate schedules and momentum parameters
params = [{'solver': 'sgd', 'learning_rate':... | code_fim | hard | {
"lang": "python",
"repo": "GabriellBP/mlclass",
"path": "/03_Validation/mlp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def transform_sex_column(df):
for idx, cell in enumerate(df['sex']):
if cell == 'I':
df.at[idx, 'sex'] = 0
elif cell == 'M':
df.at[idx, 'sex'] = 1
else:
df.at[idx, 'sex'] = -1
# load dataset
data = pd.read_csv('abalone_dataset.csv')
featur... | code_fim | hard | {
"lang": "python",
"repo": "GabriellBP/mlclass",
"path": "/03_Validation/mlp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # for each dataset, plot learning for each learning strategy
print("\nlearning on dataset %s" % name)
# Normalizing
X = MinMaxScaler().fit_transform(X)
for label, param in zip(labels, params):
print("training: %s" % label)
mlp = MLPClassifier(verbose=0, random_state=0,... | code_fim | hard | {
"lang": "python",
"repo": "GabriellBP/mlclass",
"path": "/03_Validation/mlp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> test_df = test_df[:7]
return CausalManager(train_df, test_df, target_feature,
ModelTask.REGRESSION, ['CHAS'])
class TestCausalManagerTreatmentCosts:
def test_zero_cost(self, cost_manager):
with patch.object(cost_manager, '_create_policy', return_value=None)\
... | code_fim | hard | {
"lang": "python",
"repo": "ShabadVaswani/responsible-ai-widgets",
"path": "/responsibleai/tests/test_causal/test_causal_manager.py",
"mode": "spm",
"license": "LGPL-3.0-only",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class TestCausalManagerTreatmentCosts:
def test_zero_cost(self, cost_manager):
with patch.object(cost_manager, '_create_policy', return_value=None)\
as mock_create:
cost_manager.add(['ZN', 'RM', 'B'], treatment_cost=0)
mock_create.assert_any_call(ANY, A... | code_fim | hard | {
"lang": "python",
"repo": "ShabadVaswani/responsible-ai-widgets",
"path": "/responsibleai/tests/test_causal/test_causal_manager.py",
"mode": "spm",
"license": "LGPL-3.0-only",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShabadVaswani/responsible-ai-widgets path: /responsibleai/tests/test_causal/test_causal_manager.py
# Copyright (c) Microsoft Corporation
# Licensed under the MIT License.
import numpy as np
import pytest
from unittest.mock import patch, ANY
from responsibleai import ModelAnalysis, ModelTask
fro... | code_fim | hard | {
"lang": "python",
"repo": "ShabadVaswani/responsible-ai-widgets",
"path": "/responsibleai/tests/test_causal/test_causal_manager.py",
"mode": "psm",
"license": "LGPL-3.0-only",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vegitron/spotseeker-server path: /spotseeker_server/test/hours/put.py
from django.test import TestCase
from django.conf import settings
from django.test.client import Client
from spotseeker_server.models import Spot, SpotAvailableHours
import simplejson as json
<|fim_suffix|>
def test_hours... | code_fim | hard | {
"lang": "python",
"repo": "vegitron/spotseeker-server",
"path": "/spotseeker_server/test/hours/put.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> with self.settings(SPOTSEEKER_AUTH_MODULE='spotseeker_server.auth.all_ok',
SPOTSEEKER_SPOT_FORM='spotseeker_server.default_forms.spot.DefaultSpotForm'):
spot = Spot.objects.create(name="This spot has available hours")
etag = spot.etag
put... | code_fim | hard | {
"lang": "python",
"repo": "vegitron/spotseeker-server",
"path": "/spotseeker_server/test/hours/put.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.maxDiff = None
self.assertEquals(spot_dict["available_hours"], put_obj["available_hours"], "Data from the web service matches the data for the spot")<|fim_prefix|># repo: vegitron/spotseeker-server path: /spotseeker_server/test/hours/put.py
from django.test import TestCase
fr... | code_fim | hard | {
"lang": "python",
"repo": "vegitron/spotseeker-server",
"path": "/spotseeker_server/test/hours/put.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def setReminder(reminder):
global DONE_reminder
reminderList = ["-PT10M", "-PT30M", "-PT1H", "-PT2H", "-P1D"]
if (reminder == "1"):
DONE_reminder = reminderList[0]
elif (reminder == "2"):
DONE_reminder = reminderList[1]
elif (reminder == "3"):
DONE_reminder = re... | code_fim | hard | {
"lang": "python",
"repo": "NagaruZ/CCZU-iCal",
"path": "/script_zh.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def save(string):
f = open("class.ics", 'wb')
f.write(string.encode("utf-8"))
f.close()
def icsCreateAndSave():
icsString = "BEGIN:VCALENDAR\nMETHOD:PUBLISH\nVERSION:2.0\nX-WR-CALNAME:课程表\nPRODID:-//Apple Inc.//Mac OS X 10.12//EN\nX-APPLE-CALENDAR-COLOR:#FC4208\nX-WR-TIMEZONE:Asia/Shang... | code_fim | hard | {
"lang": "python",
"repo": "NagaruZ/CCZU-iCal",
"path": "/script_zh.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NagaruZ/CCZU-iCal path: /script_zh.py
import requests
import json
import sys
import copy
import datetime
import time
from random import Random
from lxml import etree
def LoginCookie(user: str, passwd: str) -> dict:
session = requests.session()
url = "http://jwcas.cczu.edu.cn/login"
... | code_fim | hard | {
"lang": "python",
"repo": "NagaruZ/CCZU-iCal",
"path": "/script_zh.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cloudlet001/repo1 path: /try/dict.py
# -*- coding:utf8 -*-
'''
Created on 2018年4月11日
@author: bhlin
'''
#Python函数 dict()
#https://www.cnblogs.com/guyuyuan/p/6952442.html
d1=dict() # 创建空字典 {}
d2=dict(a='1', b='2', t='t') # 传入关键字 {'a': '1', 'b': '2', 't': 't'}
d3 = dict(zip(['one', 'two',... | code_fim | medium | {
"lang": "python",
"repo": "cloudlet001/repo1",
"path": "/try/dict.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #list of keys
keys=[k for k in d4]
print "keys = %s" % (keys)
# check if key k existed
print "# check if key k existed"
k="one"
if k in d4: print "Has key : %s" % (k)
if d4.has_key(k): print "Has key : %s" % (k)
else: print "Has no key : %s" % (k)
#li... | code_fim | hard | {
"lang": "python",
"repo": "cloudlet001/repo1",
"path": "/try/dict.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RT-Thread/rt-thread path: /bsp/stm32/libraries/STM32L4xx_HAL/SConscript
import rtconfig
from building import *
# get current directory
cwd = GetCurrentDir()
# The set of source files associated with this SConscript file.
src = Split('''
CMSIS/Device/ST/STM32L4xx/Source/Templates/system_stm32l4... | code_fim | hard | {
"lang": "python",
"repo": "RT-Thread/rt-thread",
"path": "/bsp/stm32/libraries/STM32L4xx_HAL/SConscript",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if GetDepend(['BSP_USING_FMC']):
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_ll_fmc.c']
if GetDepend(['BSP_USING_GFXMMU']):
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_hal_gfxmmu.c']
if GetDepend(['BSP_USING_DSI']):
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_hal_dsi.c']
src += ['STM32L4... | code_fim | hard | {
"lang": "python",
"repo": "RT-Thread/rt-thread",
"path": "/bsp/stm32/libraries/STM32L4xx_HAL/SConscript",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if GetDepend(['RT_USING_PM']):
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_hal_lptim.c']
if GetDepend(['BSP_USING_ON_CHIP_FLASH']):
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_hal_flash.c']
src += ['STM32L4xx_HAL_Driver/Src/stm32l4xx_hal_flash_ex.c']
src += ['STM32L4xx_HAL_Driver/Src/stm3... | code_fim | hard | {
"lang": "python",
"repo": "RT-Thread/rt-thread",
"path": "/bsp/stm32/libraries/STM32L4xx_HAL/SConscript",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>img = img[125:157, 10:img.shape[1] - 70]
for i in range(4):
image = img[:,i*int(img.shape[1]/4):(i+1)*int(img.shape[1]/4)]
image = image.astype('uint8')
image = Image.fromarray(image)
image.show()
image.save('type1_train_1_code_{}.jpg'.format(i))<|fim_prefix|># repo: lvyufeng/Captcha_r... | code_fim | hard | {
"lang": "python",
"repo": "lvyufeng/Captcha_recognition",
"path": "/type1_split.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lvyufeng/Captcha_recognition path: /type1_split.py
import numpy as np
from PIL import Image
path = '/Users/lvyufeng/Documents/captcha_train_set/type1_train/type1_train_1.jpg'
img = np.array(Image.open(path).convert('L'), 'f')
img[img >= 200] = 255
img[img < 200] = 0
<|fim_suffix|>img = img[125:1... | code_fim | hard | {
"lang": "python",
"repo": "lvyufeng/Captcha_recognition",
"path": "/type1_split.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>eplace=False))
print(arr)
DF = pd.DataFrame(arr)
DF.to_csv("temp.csv")<|fim_prefix|># repo: sriharikapu/RandomSequenceGenerator path: /rand.py
import sys;
import numpy as np;
import pandas as pd;
np.set_printopti<|fim_middle|>ons(threshold=sys.maxsize)
# replace the range, sample size with your custom ... | code_fim | medium | {
"lang": "python",
"repo": "sriharikapu/RandomSequenceGenerator",
"path": "/rand.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>custom numbers
arr = np.array(np.random.choice(range(10000), 10000, replace=False))
print(arr)
DF = pd.DataFrame(arr)
DF.to_csv("temp.csv")<|fim_prefix|># repo: sriharikapu/RandomSequenceGenerator path: /rand.py
import sys;
import numpy as np;
import pandas as pd;
np.set_printopti<|fim_middle|>ons(thr... | code_fim | medium | {
"lang": "python",
"repo": "sriharikapu/RandomSequenceGenerator",
"path": "/rand.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sriharikapu/RandomSequenceGenerator path: /rand.py
import sys;
import numpy as np;
import pandas as pd;
np.set_printopti<|fim_suffix|>eplace=False))
print(arr)
DF = pd.DataFrame(arr)
DF.to_csv("temp.csv")<|fim_middle|>ons(threshold=sys.maxsize)
# replace the range, sample size with your custom ... | code_fim | medium | {
"lang": "python",
"repo": "sriharikapu/RandomSequenceGenerator",
"path": "/rand.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def count_tokens(self, request: Request, completions: List[Sequence]) -> int:
"""
Counts the number of generated tokens.
TODO: Cohere simply counts the number of generations, but we currently only support counting tokens.
"""
return sum(len(sequence.tokens) for ... | code_fim | easy | {
"lang": "python",
"repo": "closerforever/helm",
"path": "/src/helm/proxy/token_counters/cohere_token_counter.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: closerforever/helm path: /src/helm/proxy/token_counters/cohere_token_counter.py
from typing import List
from helm.common.request import Request, Sequence
from .token_counter import TokenCounter
class CohereTokenCounter(TokenCounter):
<|fim_suffix|> """
Counts the number of gener... | code_fim | medium | {
"lang": "python",
"repo": "closerforever/helm",
"path": "/src/helm/proxy/token_counters/cohere_token_counter.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> plt.imshow(
self, *args, cmap=plt.get_cmap(cmap_name),
extent=self.extent, **kwargs
)
if if_show:
plt.colorbar(orientation='horizontal')
plt.show()
def show(self, *args, **kwargs):
"""A shortcut of :meth:`self.plot`. Jus... | code_fim | hard | {
"lang": "python",
"repo": "TitorX/gkit",
"path": "/gkit/core/raster.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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