text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> def update_pipette_config(self, axis, data):
'''
Updates the following configs for a given pipette mount based on
the detected pipette type:
- homing positions M365.0
- Max Travel M365.1
- endstop debounce M365.2 (NOT for zprobe debounce)
- retra... | code_fim | hard | {
"lang": "python",
"repo": "fakela/opentrons",
"path": "/api/src/opentrons/drivers/smoothie_drivers/__init__.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fakela/opentrons path: /api/src/opentrons/drivers/smoothie_drivers/__init__.py
class SmoothieDriver(object):
def __init__(self):
pass
class VirtualSmoothie(object):
def __init__(self):
pass
class SimulatingDriver:
def __init__(self):
self._steps_per_mm = ... | code_fim | hard | {
"lang": "python",
"repo": "fakela/opentrons",
"path": "/api/src/opentrons/drivers/smoothie_drivers/__init__.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Hovden/tomviz path: /tomviz/python/MisalignImgs_Uniform.py
#Misalign (Random-Uniform) a tomography tilt series
#for testing and reconsruction development
#
#developed as part of the tomviz project (www.tomviz.com)
def transform_scalars(dataset):
from tomviz import utils
import n... | code_fim | medium | {
"lang": "python",
"repo": "Hovden/tomviz",
"path": "/tomviz/python/MisalignImgs_Uniform.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if data_py is None: #Check if data exists
raise RuntimeError("No data array found!")
if TILT_AXIS == []: #If tilt axis is not given, find it
#Find smallest array dimension, assume it is the tilt angle axis
if data_py.ndim == 3:
TILT_AXIS = np.argmin( data_p... | code_fim | hard | {
"lang": "python",
"repo": "Hovden/tomviz",
"path": "/tomviz/python/MisalignImgs_Uniform.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if TILT_AXIS == []: #If tilt axis is not given, find it
#Find smallest array dimension, assume it is the tilt angle axis
if data_py.ndim == 3:
TILT_AXIS = np.argmin( data_py.shape )
elif data_py.ndim == 2:
raise RuntimeError("Data Array is 2 dimensions, it s... | code_fim | hard | {
"lang": "python",
"repo": "Hovden/tomviz",
"path": "/tomviz/python/MisalignImgs_Uniform.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>gen.add("color_mode",
int_t,
0,
"Video mode for color camera",
68,
1,
74,
edit_method=output_mode_enum)
gen.add("depth_mode",
int_t,
0,
"Video mode for depth camera",
69,
1,
74,
edit_method=outp... | code_fim | hard | {
"lang": "python",
"repo": "orbbec/ros_astra_camera",
"path": "/cfg/Astra.cfg",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: orbbec/ros_astra_camera path: /cfg/Astra.cfg
#!/usr/bin/env python
PACKAGE = 'astra_camera'
from dynamic_reconfigure.parameter_generator_catkin import *
gen = ParameterGenerator()
# TODO Only offer modes supported by known hardware
output_mode_enum = gen.enum([
gen.const("1024_768_5", int... | code_fim | hard | {
"lang": "python",
"repo": "orbbec/ros_astra_camera",
"path": "/cfg/Astra.cfg",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>gen.add("ir_time_offset", double_t, 0, "ir image time offset in seconds",
-0.033, -1.0, 1.0)
gen.add("color_time_offset", double_t, 0, "color image time offset in seconds",
-0.033, -1.0, 1.0)
gen.add("depth_time_offset", double_t, 0, "depth image time offset in seconds",
-0.033, -1... | code_fim | hard | {
"lang": "python",
"repo": "orbbec/ros_astra_camera",
"path": "/cfg/Astra.cfg",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>plt.tight_layout()
#Exercise 3 - Save figures
plt.savefig("plot_and_scatter.png")<|fim_prefix|># repo: cce-bigdataintro-1160/spring2019 path: /class6-notebook/exercises/matplotlib_1-3.py
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv('../data/boston/housing.data',
... | code_fim | hard | {
"lang": "python",
"repo": "cce-bigdataintro-1160/spring2019",
"path": "/class6-notebook/exercises/matplotlib_1-3.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cce-bigdataintro-1160/spring2019 path: /class6-notebook/exercises/matplotlib_1-3.py
import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv('../data/boston/housing.data',
sep='\s+',
header=None)
df.columns = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', '... | code_fim | medium | {
"lang": "python",
"repo": "cce-bigdataintro-1160/spring2019",
"path": "/class6-notebook/exercises/matplotlib_1-3.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> < #count{Z : n(Z) }. %#int(X), X < #count{Z : n(Z) }.
c(X1) :- X1 < #count{Z : n(Z) }, X=1+X1. %#int(X), X1 < #count{Z : n(Z) }, +(X, 1, X1).
%% end %%
"""<|fim_prefix|># repo: dave90/Dlv_safe2 path: /Dlv2_safe2/tests/parser/bug.76.test.py
input = """
%% start file count.dl %%
%#maxint = 5.
n(1).
n(2... | code_fim | hard | {
"lang": "python",
"repo": "dave90/Dlv_safe2",
"path": "/Dlv2_safe2/tests/parser/bug.76.test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dave90/Dlv_safe2 path: /Dlv2_safe2/tests/parser/bug.76.test.py
input = """
%% start file count.dl %%
%#maxint = 5.
n(1).
n(2).
n(3).
a(X) :- X > 0, X < #count{Z : n(Z) }. %#int(X), X > 0, X < #count{Z : n(Z) }.
b(X) :- X <|fim_suffix|>output = """
%% start file count.dl %%
%#maxint = 5.
n(1).
n(2... | code_fim | medium | {
"lang": "python",
"repo": "dave90/Dlv_safe2",
"path": "/Dlv2_safe2/tests/parser/bug.76.test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Initializing Databases
accessdb = AccessModule()
acc_peodb = AccPeoModule()
peopledb = PeopleModule()
peo_curdb = PeoCurModule()
curriculumdb = CurriculumModule()
# Importing views
from views import *
# Running the app
if __name__ == '__main__':
app.run()<|fim_prefix|># repo: GuilhermeVieira/mac03... | code_fim | medium | {
"lang": "python",
"repo": "GuilhermeVieira/mac0350-database",
"path": "/src/api/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GuilhermeVieira/mac0350-database path: /src/api/app.py
from flask import Flask
from access_module import AccessModule
from acc_peo_module import AccPeoModule
from people_module import PeopleModule
from peo_cur_module import PeoCurModule
from curriculum_module import CurriculumModule
# Project Co... | code_fim | medium | {
"lang": "python",
"repo": "GuilhermeVieira/mac0350-database",
"path": "/src/api/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> CW.put_metric_data(
Namespace="Turbine",
MetricData=[
{
"MetricName": "ClusterLoad",
"Dimensions": [{"Name": "StackName", "Value": os.environ["StackName"]}],
"Timestamp": time,
"Value": value,
"... | code_fim | hard | {
"lang": "python",
"repo": "amizzo87/bernstein-stack",
"path": "/functions/load_metric.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: amizzo87/bernstein-stack path: /functions/load_metric.py
import datetime
import logging
import os
import boto3
CW = boto3.client("cloudwatch")
logging.getLogger().setLevel(os.environ.get("LOGLEVEL", logging.INFO))
def handler(_event, _context):
logging.debug("environment variables:\n %s",... | code_fim | hard | {
"lang": "python",
"repo": "amizzo87/bernstein-stack",
"path": "/functions/load_metric.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if robot.model_type == "MJCF":
MJCF_SCALING = robot.mjcf_scaling
scaling = [1.0/MJCF_SCALING, 1.0/MJCF_SCALING, 0.6/MJCF_SCALING]
else:
scaling = [1, 1, 1]
magnified = [2, 2, 2]
collisionId = p.createCollisionShape(p.GEOM_MESH, fileName... | code_fim | hard | {
"lang": "python",
"repo": "sacadena/midlevel-reps",
"path": "/gibson/gibson/core/physics/scene_building.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sacadena/midlevel-reps path: /gibson/gibson/core/physics/scene_building.py
import os, inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir)
os.sys.path.insert(0,parentdir)
import pybullet_data
from gibson.data.data... | code_fim | hard | {
"lang": "python",
"repo": "sacadena/midlevel-reps",
"path": "/gibson/gibson/core/physics/scene_building.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hung4564/MMNN path: /markov/M_M_C.py
import math
class M_M_C(object):
def __init__(self, lamda, muy, C):
self.lamda = float(lamda)
self.muy = float(muy)
self.C = int(C)
def r(self):
return self.lamda/self.muy
def Rho(self):
return self.r()/s... | code_fim | hard | {
"lang": "python",
"repo": "hung4564/MMNN",
"path": "/markov/M_M_C.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Thoi gian doi trung binh"""
if not self.isVaild():
pass
return self.Lq()/self.lamda
def diplay(self):
if self.isVaild():
print("Mo hinh M/M/"+str(self.C))
print("rho: " + str(self.Rho()))
print("Xac suat tat ca kenh ph... | code_fim | hard | {
"lang": "python",
"repo": "hung4564/MMNN",
"path": "/markov/M_M_C.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """test getting all authors"""
self.register_user()
token = self.login_user()
response = self.client.get(self.user_author, format='json', HTTP_AUTHORIZATION='Token ' +token)
self.assertEqual(response.status_code, status.HTTP_200_OK)
def test_get_specific_autho... | code_fim | medium | {
"lang": "python",
"repo": "andela/ah-technocrats",
"path": "/authors/apps/profiles/tests/test_view_all_profiles.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_get_specific_authors_profile(self):
"""test viewing a specific author's profile"""
self.register_user()
token = self.login_user()
response = self.client.get(reverse("profiles:profile", kwargs={
'username':self.register_data['user']['username'],
... | code_fim | hard | {
"lang": "python",
"repo": "andela/ah-technocrats",
"path": "/authors/apps/profiles/tests/test_view_all_profiles.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andela/ah-technocrats path: /authors/apps/profiles/tests/test_view_all_profiles.py
from authors.base_file import BaseTestCase
from django.urls import reverse
from rest_framework import status
from ..models import Profile
class TestProfile(BaseTestCase):
"""test the user profile"""
def l... | code_fim | medium | {
"lang": "python",
"repo": "andela/ah-technocrats",
"path": "/authors/apps/profiles/tests/test_view_all_profiles.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: flowroute/flowroute-sdk-v3-python path: /flowroutenumbersandmessaging/models/attributes_28.py
# -*- coding: utf-8 -*-
"""
flowroutenumbersandmessaging.models.attributes_28
This file was automatically generated by APIMATIC v2.0 ( https://apimatic.io )
"""
class Attributes28(ob... | code_fim | hard | {
"lang": "python",
"repo": "flowroute/flowroute-sdk-v3-python",
"path": "/flowroutenumbersandmessaging/models/attributes_28.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def from_dictionary(cls,
dictionary):
"""Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the ser... | code_fim | hard | {
"lang": "python",
"repo": "flowroute/flowroute-sdk-v3-python",
"path": "/flowroutenumbersandmessaging/models/attributes_28.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aashishogale/DataStructurePrograms-Python- path: /com/bridgelabz/utility/linkedlist.py
class LinkedList:
def __init__(self):
self.head = None
def addatEnd(self, item):
node = Node(item)
if (self.isempty()):
self.head = node
else:
... | code_fim | hard | {
"lang": "python",
"repo": "aashishogale/DataStructurePrograms-Python-",
"path": "/com/bridgelabz/utility/linkedlist.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return False
def display(self):
temp = self.head
while (temp != None):
print(temp.data)
temp=temp.getNext()
return
def writeToFile(self,filename):
with open(filename,"w") as file:
temp=self.head
while(temp!=... | code_fim | hard | {
"lang": "python",
"repo": "aashishogale/DataStructurePrograms-Python-",
"path": "/com/bridgelabz/utility/linkedlist.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@app.route('/oauth2callback')
def oauth2callback():
"""
The 'flow' has this one place to call back to. We'll enter here
more than once as steps in the flow are completed, and need to keep
track of how far we've gotten. The first time we'll do the first
step, the second time we'll skip the first... | code_fim | hard | {
"lang": "python",
"repo": "jeffbayes/399se",
"path": "/proj6-Gcal/meetingmaker/oauth.py",
"mode": "spm",
"license": "Artistic-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeffbayes/399se path: /proj6-Gcal/meetingmaker/oauth.py
import flask
from meetingmaker import app
# OAuth2 - Google library implementation for convenience
from oauth2client import client
import httplib2 # used in oauth2 flow
# Google API for services
from apiclient import discovery
import C... | code_fim | hard | {
"lang": "python",
"repo": "jeffbayes/399se",
"path": "/proj6-Gcal/meetingmaker/oauth.py",
"mode": "psm",
"license": "Artistic-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zxzl/dike path: /dike/webdike/migrations/0011_auto_20171124_0641.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2017-11-24 06:41
from __future__ import unicode_literals
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('webdike', '0010_step_result')... | code_fim | medium | {
"lang": "python",
"repo": "zxzl/dike",
"path": "/dike/webdike/migrations/0011_auto_20171124_0641.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
('webdike', '0010_step_result'),
]
operations = [
migrations.AlterField(
model_name='step',
name='parent_step',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.... | code_fim | medium | {
"lang": "python",
"repo": "zxzl/dike",
"path": "/dike/webdike/migrations/0011_auto_20171124_0641.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == 'POST':
form = UserRegisterForm(request.POST)
if form.is_valid():
try:
form.save()
username = form.cleaned_data.get('username')
auth_user = AuthUser.objects.filter(username=username).first()
... | code_fim | hard | {
"lang": "python",
"repo": "Abhis33/Fridge-9000---Software-Engg-Project",
"path": "/application/Django_refrigerator_project/users/views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Abhis33/Fridge-9000---Software-Engg-Project path: /application/Django_refrigerator_project/users/views.py
from django.shortcuts import render, redirect
from django.contrib import messages
from django.contrib.auth.decorators import login_required
from .forms import UserRegisterForm
from .models im... | code_fim | hard | {
"lang": "python",
"repo": "Abhis33/Fridge-9000---Software-Engg-Project",
"path": "/application/Django_refrigerator_project/users/views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: doribugi/BOJ path: /14709/14709.py
"""
문제: https://www.acmicpc.net/problem/14709
풀이: (1, 3), (4, 3), (1, 4) 가 들어오면 여우 사인 (입력 순서, 쌍의 순서 바뀔 수 있음)
그 외 다른 모든 입력은 여우 사인 아님
"""
def check_fox_sign(input_list):
if not [1, 3] in input_list and not [3, 1] in input_list:
return False
... | code_fim | medium | {
"lang": "python",
"repo": "doribugi/BOJ",
"path": "/14709/14709.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not [1, 3] in input_list and not [3, 1] in input_list:
return False
elif not [4, 3] in input_list and not [3, 4] in input_list:
return False
elif not [1, 4] in input_list and not [4, 1] in input_list:
return False
else:
return True
nmrLine = int(input()... | code_fim | medium | {
"lang": "python",
"repo": "doribugi/BOJ",
"path": "/14709/14709.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jhson989/jhML path: /playground/step3/jhML/core.py
import numpy as np
import contextlib
class Config:
enable_backprop = True
#contextlib.contextmanager
def using_config(name, value):
old_value = getattr(Config, name)
setattr(Config, name, value)
try:
yield
finally... | code_fim | hard | {
"lang": "python",
"repo": "jhson989/jhML",
"path": "/playground/step3/jhML/core.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> gx = np.ones_like(self.data)
if self.required_grad and retain_grad:
self.grad = self.grad + gx
if self.creator is None:
return
funcs = []
seen_set = set()
def add_func(f, gy):
if f not in seen_set:
s... | code_fim | hard | {
"lang": "python",
"repo": "jhson989/jhML",
"path": "/playground/step3/jhML/core.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: flashlin/pycore path: /video_processing/flac_file.py
import librosa
def convert_flac_to_wav(flac_filepath, wav_filepath,<|fim_suffix|>epath)
waveform = librosa.resample(waveform, sample_rate, resample_rate)
librosa.output.write_wav(wav_filepath, waveform, resample_rate)<|fim_middle... | code_fim | medium | {
"lang": "python",
"repo": "flashlin/pycore",
"path": "/video_processing/flac_file.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ate)
librosa.output.write_wav(wav_filepath, waveform, resample_rate)<|fim_prefix|># repo: flashlin/pycore path: /video_processing/flac_file.py
import librosa
def convert_flac_to_wav(flac_filepath, wav_filepath, resample_rate=16000):
waveform, sample_rate = librosa.load(flac_fil<|fim_middle... | code_fim | medium | {
"lang": "python",
"repo": "flashlin/pycore",
"path": "/video_processing/flac_file.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>epath)
waveform = librosa.resample(waveform, sample_rate, resample_rate)
librosa.output.write_wav(wav_filepath, waveform, resample_rate)<|fim_prefix|># repo: flashlin/pycore path: /video_processing/flac_file.py
import librosa
def convert_flac_to_wav(flac_filepath, wav_filepath,<|fim_middle... | code_fim | medium | {
"lang": "python",
"repo": "flashlin/pycore",
"path": "/video_processing/flac_file.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(found_words,
["ab", "ac", "bd", "ca", "db"])
def test_find_words_long(self):
found_words = self.sol.findWords(board_1, words_1)
self.assertEqual(found_words,
['aaaaaaaaaaaaaaaa',
'aaa... | code_fim | hard | {
"lang": "python",
"repo": "brigitteunger/katas",
"path": "/test_word_search_II.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brigitteunger/katas path: /test_word_search_II.py
import unittest
from data_word_search import board_1, words_1
from typing import List, Dict
from copy import deepcopy
class Trie:
def __init__(self) -> None:
"""
Initialize your data structure here.
"""
self.c... | code_fim | hard | {
"lang": "python",
"repo": "brigitteunger/katas",
"path": "/test_word_search_II.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TTdeveloping/text_classification path: /model/Cnn.py
from model.Initialize import *
import torch.nn as nn
import torch.nn.functional as F
class CNN(nn.Module):
"""
CNN
"""
def __init__(self, **kwargs):
super(CNN, self).__init__()
for k in kwargs:
... | code_fim | hard | {
"lang": "python",
"repo": "TTdeveloping/text_classification",
"path": "/model/Cnn.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.pretrained_embed:
self.embed.weight.data.copy_(self.pretrained_weight)
else:
init_embedding(self.embed.weight)
self.dropout_embed = nn.Dropout(self.dropout_emb)
self.dropout = nn.Dropout(self.dropout)
# cnn
if self.wide_conv:... | code_fim | hard | {
"lang": "python",
"repo": "TTdeveloping/text_classification",
"path": "/model/Cnn.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for conv in self.conv:
if self.use_cuda:
conv.cuda()
in_fea = len(kernel_sizes) * kernel_nums
self.linear = nn.Linear(in_features=in_fea, out_features=C, bias=True)
init_linear(self.linear)
def forward(self, word, sentence_length):
"... | code_fim | hard | {
"lang": "python",
"repo": "TTdeveloping/text_classification",
"path": "/model/Cnn.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pektin/jam path: /compiler/interpreter/state.py
from contextlib import contextmanager
class State:
self = None
stdout = None
@classmethod
@contextmanager
def print(cls, value):
<|fim_suffix|> @classmethod
@contextmanager
def selfScope(cls, self):
previous_... | code_fim | medium | {
"lang": "python",
"repo": "pektin/jam",
"path": "/compiler/interpreter/state.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> yield
cls.self = previous_self<|fim_prefix|># repo: pektin/jam path: /compiler/interpreter/state.py
from contextlib import contextmanager
class State:
<|fim_middle|> self = None
stdout = None
@classmethod
@contextmanager
def print(cls, value):
if cls.stdout i... | code_fim | hard | {
"lang": "python",
"repo": "pektin/jam",
"path": "/compiler/interpreter/state.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pombredanne/awspider path: /awspider/resources/admin.py
from twisted.python.failure import Failure
from twisted.web import server
from .base import BaseResource
class AdminResource(BaseResource):
<|fim_suffix|> def render(self, request):
request.setHeader('Content-type', 'text/javasc... | code_fim | medium | {
"lang": "python",
"repo": "pombredanne/awspider",
"path": "/awspider/resources/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def render(self, request):
request.setHeader('Content-type', 'text/javascript; charset=UTF-8')
if len(request.postpath) > 0:
if request.postpath[0] == "clear_http_cache":
d = self.adminserver.clearHTTPCache()
d.addCallback(self._successRespon... | code_fim | medium | {
"lang": "python",
"repo": "pombredanne/awspider",
"path": "/awspider/resources/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.adminserver = adminserver
BaseResource.__init__(self)
def render(self, request):
request.setHeader('Content-type', 'text/javascript; charset=UTF-8')
if len(request.postpath) > 0:
if request.postpath[0] == "clear_http_cache":
d =... | code_fim | medium | {
"lang": "python",
"repo": "pombredanne/awspider",
"path": "/awspider/resources/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertTrue(isinstance(self.new_news,News))
if __name__ == '__main__':
unittest.main()<|fim_prefix|># repo: BridgitKirika/News-Highlights path: /app/tests/news_test.py
import unittest
from app.models import News
# News = news.News
class NewsTest(unittest.TestCase):
'''
Test Cl... | code_fim | hard | {
"lang": "python",
"repo": "BridgitKirika/News-Highlights",
"path": "/app/tests/news_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BridgitKirika/News-Highlights path: /app/tests/news_test.py
import unittest
from app.models import News
# News = news.News
class NewsTest(unittest.TestCase):
<|fim_suffix|> def test_instance(self):
self.assertTrue(isinstance(self.new_news,News))
if __name__ == '__main__':
unitt... | code_fim | hard | {
"lang": "python",
"repo": "BridgitKirika/News-Highlights",
"path": "/app/tests/news_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
Set up method that will run before every Test
'''
self.new_news= News('Ex Radio Presenter: We suffered after Rose Kamotho sold Kameme fm' ,'Nairobi Traders in fear over planned evictions','11/28/2020','https://www.kenyans.co.ke/news/index.html','https://www.kenyans.co.k... | code_fim | medium | {
"lang": "python",
"repo": "BridgitKirika/News-Highlights",
"path": "/app/tests/news_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: praneet-away/FarmAID path: /app.py
pickle.load(open('UP_Wheat/january.pkl','rb'))
february = pickle.load(open('UP_Wheat/february.pkl','rb'))
UP_Rice = load_model('UP_Rice')
june = pickle.load(open('UP_Rice/june.pkl','rb'))
july = pickle.load(open('UP_Rice/july.pkl','rb'))
august = pickle.load(... | code_fim | hard | {
"lang": "python",
"repo": "praneet-away/FarmAID",
"path": "/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@app.route('/hr/rice/', methods=['POST'])
def predict_9():
# get data
data = request.get_json(force=True)
# convert data into dataframe
data.update((x, [y]) for x, y in data.items())
data_df = pd.DataFrame.from_dict(data)
# predictions
result1 = june.predict(data_df)
result2 =... | code_fim | hard | {
"lang": "python",
"repo": "praneet-away/FarmAID",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # return data
return jsonify(prediction)
@app.route('/hr/wheat/', methods=['POST'])
def predict_8():
# get data
data = request.get_json(force=True)
# convert data into dataframe
data.update((x, [y]) for x, y in data.items())
data_df = pd.DataFrame.from_dict(data)
# predictions
... | code_fim | hard | {
"lang": "python",
"repo": "praneet-away/FarmAID",
"path": "/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tws0002/pype path: /pype/aport/__init__.py
import os
import sys
from avalon import api as avalon
from pyblish import api as pyblish
from app import api as app
from .. import api
t = app.Templates()
log = api.Logger.getLogger(__name__, "aport")
AVALON_CONFIG = os.getenv("AVALON_CONFIG", "pype"... | code_fim | hard | {
"lang": "python",
"repo": "tws0002/pype",
"path": "/pype/aport/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> os.chdir(path)
print(os.getcwd())
print(os.listdir(path))
try:
args = [sys.executable, "-m", "pico.server",
# "pipeline",
"api"
]
app.forward(
args,
cwd=path
)
except Exception as e:
... | code_fim | hard | {
"lang": "python",
"repo": "tws0002/pype",
"path": "/pype/aport/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Chia-Network/clvm_tools path: /tests/curry_test.py
from clvm.operators import KEYWORD_TO_ATOM
from clvm_tools.binutils import assemble, disassemble
from clvm_tools.curry import curry, uncurry
<|fim_suffix|>
def test_curry_uncurry():
PLUS = KEYWORD_TO_ATOM["+"][0]
f = assemble("(+ 2 5)")... | code_fim | hard | {
"lang": "python",
"repo": "Chia-Network/clvm_tools",
"path": "/tests/curry_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> PLUS = KEYWORD_TO_ATOM["+"][0]
f = assemble("(+ 2 5)")
args = assemble("(200 30)")
actual_disassembly = check_idempotency(f, args)
assert actual_disassembly == f"(a (q {PLUS} 2 5) (c (q . 200) (c (q . 30) 1)))"
f = assemble("(+ 2 5)")
args = assemble("((+ (q . 50) (q . 60)))")... | code_fim | hard | {
"lang": "python",
"repo": "Chia-Network/clvm_tools",
"path": "/tests/curry_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> f = assemble("(+ 2 5)")
args = assemble("((+ (q . 50) (q . 60)))")
actual_disassembly = check_idempotency(f, args)
assert actual_disassembly == f"(a (q {PLUS} 2 5) (c (q {PLUS} (q . 50) (q . 60)) 1))"<|fim_prefix|># repo: Chia-Network/clvm_tools path: /tests/curry_test.py
from clvm.operat... | code_fim | hard | {
"lang": "python",
"repo": "Chia-Network/clvm_tools",
"path": "/tests/curry_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: biocore/gneiss path: /gneiss/plot/_regression_plot.py
# ----------------------------------------------------------------------------
# Copyright (c) 2016--, gneiss development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distr... | code_fim | hard | {
"lang": "python",
"repo": "biocore/gneiss",
"path": "/gneiss/plot/_regression_plot.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Explained sum of squares
ess = model.ess
# Summary object
_k, _l = model.kfold(), model.lovo()
smry = model.summary(_k, _l)
_deposit_results(model, output_dir)
t = _decorate_tree(tree, ess)
p1 = radialplot(t, figsize=(800, 800))
p1.title.text = 'Explained Sum of Squa... | code_fim | hard | {
"lang": "python",
"repo": "biocore/gneiss",
"path": "/gneiss/plot/_regression_plot.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: githubBingoChen/D4Net path: /resnext/config.py
import os
pytorch_pretrained_root = '/home/b3-542/Packages/Models/PyT<|fim_suffix|>.path.join(pytorch_pretrained_root, 'ResNet', 'resnet18-5c106cde.pth')<|fim_middle|>orch Pretrained'
resnext101_32_path = os.path.join(pytorch_pretrained_root, 'ResNeX... | code_fim | medium | {
"lang": "python",
"repo": "githubBingoChen/D4Net",
"path": "/resnext/config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>_root, 'ResNeXt', 'resnext_101_32x4d.pth')
pretrained_res18_path = os.path.join(pytorch_pretrained_root, 'ResNet', 'resnet18-5c106cde.pth')<|fim_prefix|># repo: githubBingoChen/D4Net path: /resnext/config.py
import os
pytorch_pretrained_root = '/home/b3-542/Packages/Models/PyT<|fim_middle|>orch Pretraine... | code_fim | medium | {
"lang": "python",
"repo": "githubBingoChen/D4Net",
"path": "/resnext/config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: theambidextrous/Access-approval-management- path: /app/requesttypes/routes.py
from flask import Blueprint, jsonify, request,current_app, make_response
from app.models import RequestType
from app import db
import uuid
from app.utils import AuthUtil
requesttypes = Blueprint('requesttypes', __name_... | code_fim | hard | {
"lang": "python",
"repo": "theambidextrous/Access-approval-management-",
"path": "/app/requesttypes/routes.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
data = request.get_json()
gen_id = str(uuid.uuid4())
type = RequestType(type_id=gen_id,type_name=data['type_name'])
db.session.add(type)
db.session.commit()
return jsonify({'status':0, 'created_id':gen_id, 'message':'Created!'})
except Exception... | code_fim | hard | {
"lang": "python",
"repo": "theambidextrous/Access-approval-management-",
"path": "/app/requesttypes/routes.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('wildlifecompliance', '0407_briefofevidenceotherstatements_legal_case'),
]
operations = [
migrations.AlterField(
model_name='briefofevidenceotherstatements',
name='legal_case',
field=models.ForeignKey(on_delete=django.db.mo... | code_fim | medium | {
"lang": "python",
"repo": "dbca-wa/wildlifecompliance",
"path": "/wildlifecompliance/migrations/0408_auto_20200131_1451.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dbca-wa/wildlifecompliance path: /wildlifecompliance/migrations/0408_auto_20200131_1451.py
# -*- coding: utf-8 -*-
# Generated by Django 1.10.8 on 2020-01-31 06:51
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(... | code_fim | medium | {
"lang": "python",
"repo": "dbca-wa/wildlifecompliance",
"path": "/wildlifecompliance/migrations/0408_auto_20200131_1451.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# ===============================================================================
# Keras Pattern Classifier, fits Binary Classes to MORGAN2048 fingerprints
# ===============================================================================
class KlassBinaryMorgan(with_metaclass(ModelMetaClass, KlassSeque... | code_fim | hard | {
"lang": "python",
"repo": "kellerberrin/OSM-QSAR",
"path": "/OSMKerasFingerprint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def model_name(self):
return "MORGAN > Binary Class (EC50) Classifier"
def model_postfix(self): # Must be unique for each model.
return "bin_m"
def model_description(self):
return ("A KERAS (TensorFlow) multi-layer Neural Network class classification model. \n"
... | code_fim | hard | {
"lang": "python",
"repo": "kellerberrin/OSM-QSAR",
"path": "/OSMKerasFingerprint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kellerberrin/OSM-QSAR path: /OSMKerasFingerprint.py
# MIT License
#
# Copyright (c) 2017
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, includi... | code_fim | hard | {
"lang": "python",
"repo": "kellerberrin/OSM-QSAR",
"path": "/OSMKerasFingerprint.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>n fruits:
print('Saya suka ' + fruit)<|fim_prefix|># repo: myarist/Progate path: /Languages/Python/python_study_2/page4/script.py
fruits = ['apel', 'pisang', 'jeruk']
# Dapatkan element fruits menggunakan loop f<|fim_middle|>or, dan cetak 'Saya suka ___'
for fruit i | code_fim | easy | {
"lang": "python",
"repo": "myarist/Progate",
"path": "/Languages/Python/python_study_2/page4/script.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: myarist/Progate path: /Languages/Python/python_study_2/page4/script.py
fruits = ['apel', 'pisang', 'jeruk']
# D<|fim_suffix|>n fruits:
print('Saya suka ' + fruit)<|fim_middle|>apatkan element fruits menggunakan loop for, dan cetak 'Saya suka ___'
for fruit i | code_fim | medium | {
"lang": "python",
"repo": "myarist/Progate",
"path": "/Languages/Python/python_study_2/page4/script.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> team = StringField(required = True)
first_name = StringField(required = True)
last_name = StringField(required = True)
img_slug = StringField(required = True)
silly_img_slug = StringField(required = True)
description = StringField(default = "", required = False)
order = IntFiel... | code_fim | medium | {
"lang": "python",
"repo": "hackBCA/hackbcathree",
"path": "/application/mod_web/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> date = StringField(required = True)
time = DateTimeField(required = True)
event = StringField(required = True)
location = StringField()<|fim_prefix|># repo: hackBCA/hackbcathree path: /application/mod_web/models.py
from mongoengine import *
class MailingListEntry(Document):
email = Stri... | code_fim | hard | {
"lang": "python",
"repo": "hackBCA/hackbcathree",
"path": "/application/mod_web/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hackBCA/hackbcathree path: /application/mod_web/models.py
from mongoengine import *
class MailingListEntry(Document):
email = StringField(max_length = 50, required = True)
verified = BooleanField(required = False, default = False)
<|fim_suffix|> date = StringField(required = True)
time... | code_fim | hard | {
"lang": "python",
"repo": "hackBCA/hackbcathree",
"path": "/application/mod_web/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suyanzhou626/video_decaptioning path: /models/discriminator.py
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
import pdb
class Discriminator(nn.Module):
def __init__(self, opt=None):
super(Discriminator, self).__init... | code_fim | hard | {
"lang": "python",
"repo": "suyanzhou626/video_decaptioning",
"path": "/models/discriminator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Discriminator2D(nn.Module):
def __init__(self, opt=None):
super(Discriminator2D, self).__init__()
self.main = nn.Sequential(
# (3+3)x1x128x128
nn.Conv3d(6, 64, kernel_size=(1,4,4), stride=(1,2,2), padding=(0,2,2)),
nn.LeakyReLU(0.2, inplace=... | code_fim | hard | {
"lang": "python",
"repo": "suyanzhou626/video_decaptioning",
"path": "/models/discriminator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> output = self.main(x)
return output.view(-1, 1)
class Discriminator2D(nn.Module):
def __init__(self, opt=None):
super(Discriminator2D, self).__init__()
self.main = nn.Sequential(
# (3+3)x1x128x128
nn.Conv3d(6, 64, kernel_size=(1,4,4), strid... | code_fim | hard | {
"lang": "python",
"repo": "suyanzhou626/video_decaptioning",
"path": "/models/discriminator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fazlikeles/RACLAB path: /Goruntu Isleme/Examples/ornek22.py
#-*-coding: utf-8-*-
###Object Detection And Classification - Paralel Proglamlama###
import numpy as np
import cv2
from multiprocessing import Process
from multiprocessing import Queue
def classify_frame(net,inputqueue, outputqueue):
... | code_fim | hard | {
"lang": "python",
"repo": "fazlikeles/RACLAB",
"path": "/Goruntu Isleme/Examples/ornek22.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cv2.rectangle(frame,(startx,starty),(endx,endy),colors[idx],2)
y=starty - 15 if starty -15 > 15 else starty + 15
cv2.putText(frame,label,(startx, y),cv2.FONT_HERSHEY_SIMPLEX,0.5,colors[idx],2)
cv2.imshow("frame",frame)
if cv2.waitKey(1) & 0xff == 27:
break
cam.release()
cv2.dest... | code_fim | hard | {
"lang": "python",
"repo": "fazlikeles/RACLAB",
"path": "/Goruntu Isleme/Examples/ornek22.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#parelel işlem processi tanımlandı.
p=Process(target=classify_frame, args=(net,inputqueue,outputqueue,))
p.daemon=True
p.start()
cam=cv2.VideoCapture(0)
while(1):
ret,frame=cam.read()
if ret:
#frame=cv2.resize(frame,(500,400))
h,w=frame.shape[:2]
if inputqueue.empty():
inputqueue.put(frame)... | code_fim | hard | {
"lang": "python",
"repo": "fazlikeles/RACLAB",
"path": "/Goruntu Isleme/Examples/ornek22.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>'''
class Solution(object):
def hIndex(self, citations):
"""
:type citations: List[int]
:rtype: int
"""
count = [0 for i in xrange(len(citations) + 1)]
for c in citations:
if c >= len(citations):
count[-1] += 1
el... | code_fim | medium | {
"lang": "python",
"repo": "sugia/leetcode",
"path": "/H-Index II.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
'''
class Solution(object):
def hIndex(self, citations):
"""
:type citations: List[int]
:rtype: int
"""
count = [0 for i in xrange(len(citations) + 1)]
for c in citations:
if c >= len(citations):
count[-1] += 1
e... | code_fim | hard | {
"lang": "python",
"repo": "sugia/leetcode",
"path": "/H-Index II.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sugia/leetcode path: /H-Index II.py
'''
Given an array of citations sorted in ascending order (each citation is a non-negative integer) of a researcher, write a function to compute the researcher's h-index.
According to the definition of h-index on Wikipedia: "A scientist has index h if h of his... | code_fim | hard | {
"lang": "python",
"repo": "sugia/leetcode",
"path": "/H-Index II.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> cols = ['session_id', 'impressions', 'impr_rank', 'ts_sub_prev', 'abs_impr_rank_sub_lastest_item-impr_rank', 'impr_rank_sub_lastest_item-impr_rank', 'nearest_step_delta', 'prices_div_active_items-session_id_by_prices_median-v2', 'price_rank', 'act_pre1', 'lastest_item-impr_rank', 'impr_rank_sub_impres... | code_fim | hard | {
"lang": "python",
"repo": "tuantx7110/pvz_recsys2019",
"path": "/src/m2/src/extract_topk_features.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tuantx7110/pvz_recsys2019 path: /src/m2/src/extract_topk_features.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 基础模块
import os
import sys
import gc
import json
import time
import functools
from datetime import datetime
# 数据处理
import numpy as np
import pandas as pd
# 自定义工具包
sys.path.append... | code_fim | hard | {
"lang": "python",
"repo": "tuantx7110/pvz_recsys2019",
"path": "/src/m2/src/extract_topk_features.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> print('start time: %s' % datetime.now())
# tr = loader.load_df('../feature/tr_s0_106.ftr')
# te = loader.load_df('../feature/te_s0_106.ftr')
tr = loader.load_df('../../../feat/m2_tr_s0_106.ftr')
te = loader.load_df('../../../feat/m2_te_s0_106.ftr')
cols = ['session_id', 'impressio... | code_fim | medium | {
"lang": "python",
"repo": "tuantx7110/pvz_recsys2019",
"path": "/src/m2/src/extract_topk_features.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # The block above the current one is the one with the higher id
child_above = current + grid.cols
# the top row of blocks starts with this id
topmost = len(grid.children) - grid.cols
if child_above > topmost:
# We are in the top row, generate new colou... | code_fim | hard | {
"lang": "python",
"repo": "ohaz/Colours",
"path": "/screens/ingamescreen.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ohaz/Colours path: /screens/ingamescreen.py
from kivy.uix.screenmanager import Screen
from kivy.uix.togglebutton import ToggleButton
from kivy.uix.popup import Popup
from kivy.lang import Builder
from kivy.utils import get_color_from_hex
from kivy.properties import NumericProperty
from screens im... | code_fim | hard | {
"lang": "python",
"repo": "ohaz/Colours",
"path": "/screens/ingamescreen.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Recursively check the blocks for groups
:param current: the block currently visited
:return: a list of blocks
"""
grid = self.ids.grid
children = grid.children
own_color = children[current].background_color
children[current].visit... | code_fim | hard | {
"lang": "python",
"repo": "ohaz/Colours",
"path": "/screens/ingamescreen.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
查询某段时间的所有论文，用于每周报告。
:param start_timestamp: 开始的时间戳
:param end_timestamp: 结束的时间戳，可选
:return: .Paper 的生成器
"""
SQL = "SELECT user_id,title,authors,description,link FROM paper WHERE user_id LIKE '%%{}%%'".format(
u_id)
cur.execu... | code_fim | hard | {
"lang": "python",
"repo": "LibRec-Practical/ideaman-offline",
"path": "/ideaman_analyzer/model/paper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LibRec-Practical/ideaman-offline path: /ideaman_analyzer/model/paper.py
import datetime
from ideaman_util.db import *
import sys, os
sys.path.append("../../")
sys.path.extend([os.path.join(root, name) for root, dirs, _ in os.walk("../") for name in dirs])
class Paper:
def __init__(self, u... | code_fim | hard | {
"lang": "python",
"repo": "LibRec-Practical/ideaman-offline",
"path": "/ideaman_analyzer/model/paper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> SQL = "UPDATE paper SET %s = '%s' WHERE user_id = %s" % (col_name, col_value, user_id)
try:
cur.execute(SQL)
conn.commit()
except:
conn.rollback()
@staticmethod
def get_classifier_dataset():
sql = """SELECT
ti... | code_fim | hard | {
"lang": "python",
"repo": "LibRec-Practical/ideaman-offline",
"path": "/ideaman_analyzer/model/paper.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from .rivalregions import Item, WorkProduction, Building, ConstructionCosts<|fim_prefix|># repo: jan-makarek/rival_regions_calc path: /rival_regions_calc/__init__.py
"""
# Rival Regions Calc
<|fim_middle|>Unofficial calculator for Rival Regions. Easily calculate common known
formulas from the game.
"""... | code_fim | medium | {
"lang": "python",
"repo": "jan-makarek/rival_regions_calc",
"path": "/rival_regions_calc/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jan-makarek/rival_regions_calc path: /rival_regions_calc/__init__.py
"""
# Rival Regions Calc
<|fim_suffix|>from .rivalregions import Item, WorkProduction, Building, ConstructionCosts<|fim_middle|>Unofficial calculator for Rival Regions. Easily calculate common known
formulas from the game.
"""... | code_fim | medium | {
"lang": "python",
"repo": "jan-makarek/rival_regions_calc",
"path": "/rival_regions_calc/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mostafaFechfouch/Data-Reading path: /datareading.py
import serial
import time
import csv
import numpy as np
import pandas as pd
import datetime
ser = serial.Serial('COM3',19200)
ser.flushInput()
i=0
ts = time.gmtime()
hours=time.strftime("%H", ts)
minutes=time.strftime("%M", ts)
seconds=time.st... | code_fim | hard | {
"lang": "python",
"repo": "mostafaFechfouch/Data-Reading",
"path": "/datareading.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> break
i=i+1
with open('data.csv', 'a',newline='') as csvfile:
fieldnames = ['time', 'ECG','EMG','HR','RESP']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writerow({'time': currenttime, 'ECG': data[0],'EMG':data[1],'HR':data[2],'RESP':data[3]}... | code_fim | hard | {
"lang": "python",
"repo": "mostafaFechfouch/Data-Reading",
"path": "/datareading.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eliahrebstock/ansible-role-netatalk path: /molecule/default/tests/test_default.py
import os
import testinfra.utils.ansible_runner
testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner(
os.environ['MOLECULE_INVENTORY_FILE']
).get_hosts('all')
<|fim_suffix|>
def test_line_in_config(... | code_fim | medium | {
"lang": "python",
"repo": "eliahrebstock/ansible-role-netatalk",
"path": "/molecule/default/tests/test_default.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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