text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
class WordTokenizer(BaseTokenizer):
def __init__(self, vocab_file, ignored_tokens=[]):
super().__init__(vocab_file, ignored_tokens)
def token2idx(self, text):
words = text.split(' ')
return [
self._token2idx.get(w, self._token2idx['<unk>']) for w in words
... | code_fim | hard | {
"lang": "python",
"repo": "lfelipesv/speech2text",
"path": "/asr/lm/tokenizer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ecds/readux path: /apps/iiif/manifests/views.py
"""Django views for manifests"""
import json
import logging
from datetime import datetime
from django.contrib import messages
from django.http import JsonResponse
from django.views import View
from django.views.generic.base import TemplateView
from ... | code_fim | hard | {
"lang": "python",
"repo": "ecds/readux",
"path": "/apps/iiif/manifests/views.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class ManifestRis(TemplateView):
"""Manifest Ris"""
content_type = 'application/x-research-info-systems; charset=UTF-8'
template_name = "citation.ris"
def get_context_data(self, **kwargs):
"""Context data for view
:return: [description]
:rtype: [type]
"""
... | code_fim | hard | {
"lang": "python",
"repo": "ecds/readux",
"path": "/apps/iiif/manifests/views.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: markokr/cc path: /cc/daemon/infosender.py
#! /usr/bin/env python
"""Read infofiles.
"""
import glob
import os, os.path
import sys
import threading
import time
import skytools
import cc.util
from cc import json
from cc.daemon import CCDaemon
from cc.message import is_msg_req_valid
from cc.reqs... | code_fim | hard | {
"lang": "python",
"repo": "markokr/cc",
"path": "/cc/daemon/infosender.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def work (self):
t = time.time()
while self.looping and self.stats_period > time.time() - t:
self._work()
self.sleep(1)
return 1
def stop (self):
""" Called from signal handler """
super(InfofileCollector, self).stop()
self.l... | code_fim | hard | {
"lang": "python",
"repo": "markokr/cc",
"path": "/cc/daemon/infosender.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Maxiimeeb/avionix path: /avionix/chart/__init__.py
# flake8: noqa
from avionix.chart.chart_builder import ChartBuilder
fr<|fim_suffix|>hart.chart_info import ChartInfo
from avionix.chart.chart_maintainer import ChartMaintainer
from avionix.chart.values_yaml import Value, Values<|fim_middle|>om a... | code_fim | medium | {
"lang": "python",
"repo": "Maxiimeeb/avionix",
"path": "/avionix/chart/__init__.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>hart.chart_info import ChartInfo
from avionix.chart.chart_maintainer import ChartMaintainer
from avionix.chart.values_yaml import Value, Values<|fim_prefix|># repo: Maxiimeeb/avionix path: /avionix/chart/__init__.py
# flake8: noqa
from avionix.chart.chart_builder import ChartBuilder
fr<|fim_middle|>om a... | code_fim | medium | {
"lang": "python",
"repo": "Maxiimeeb/avionix",
"path": "/avionix/chart/__init__.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>e.astype(np.uint16),disk(3))
slicing(contr,'gray')<|fim_prefix|># repo: CameraIA/dipmicroct path: /partII/solutions/ex04.py
from skimage.filters.rank import enhance_contrast<|fim_middle|>
contr = np.empty_like(img)
for i, aslice in enumerate(img):
contr[i]= enhance_contrast(aslic | code_fim | medium | {
"lang": "python",
"repo": "CameraIA/dipmicroct",
"path": "/partII/solutions/ex04.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: CameraIA/dipmicroct path: /partII/solutions/ex04.py
from skimage.filters.rank import enhance_contrast<|fim_suffix|>merate(img):
contr[i]= enhance_contrast(aslice.astype(np.uint16),disk(3))
slicing(contr,'gray')<|fim_middle|>
contr = np.empty_like(img)
for i, aslice in enu | code_fim | easy | {
"lang": "python",
"repo": "CameraIA/dipmicroct",
"path": "/partII/solutions/ex04.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alejandro-ariza/scikit-fda path: /tests/test_elastic.py
from skfda import FDataGrid
from skfda.datasets import make_multimodal_samples, make_random_warping
from skfda.misc.metrics import (fisher_rao_distance, amplitude_distance,
phase_distance, pairwise_distance, l... | code_fim | hard | {
"lang": "python",
"repo": "alejandro-ariza/scikit-fda",
"path": "/tests/test_elastic.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> t = np.linspace(0, np.pi, 1000)
id = FDataGrid([t], t)
cos = np.cos(id)
sin = np.sin(id)
gamma = normalize_warping(np.sqrt(id), (0, np.pi))
gamma2 = normalize_warping(np.square(id), (0, np.pi))
distance_original = fisher_rao_distance(cos, sin)
... | code_fim | hard | {
"lang": "python",
"repo": "alejandro-ariza/scikit-fda",
"path": "/tests/test_elastic.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>"""
Normal 10-fold
------- HybridModel
=== Part full
rmse: 0.8908 ± 0.0044 prec@5: 0.8756 ± 0.0035
------- HybridModel_SVDpp
=== Part full
rmse: 0.8953 ± 0.0048 prec@5: 0.8747 ± 0.0031
------- HybridModel_AttributeBiasExperimental
=== Part full
rmse: 0.9235 ± 0.0041 prec@5: 0.8633 ± 0.0043
"""<|fim_p... | code_fim | medium | {
"lang": "python",
"repo": "sbremer/hybrid_rs",
"path": "/scripts/test_10fold.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sbremer/hybrid_rs path: /scripts/test_10fold.py
import script_chdir
from evaluation.eval_script import evaluate_models_xval, print_results, EvalModel
from hybrid_model.dataset import get_dataset
# Get dataset
dataset = get_dataset('ml100k')
# dataset = get_dataset('ml1m')
<|fim_suffix|>"""
Norm... | code_fim | hard | {
"lang": "python",
"repo": "sbremer/hybrid_rs",
"path": "/scripts/test_10fold.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>model_type = HybridModel
config = hybrid_config
models.append(EvalModel(model_type.__name__, model_type, config))
results = evaluate_models_xval(dataset, models, coldstart=False, n_fold=10)
print('Normal 10-fold')
print_results(results)
"""
Normal 10-fold
------- HybridModel
=== Part full
rmse: 0.8908 ±... | code_fim | medium | {
"lang": "python",
"repo": "sbremer/hybrid_rs",
"path": "/scripts/test_10fold.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class TestMetricLogger(unittest.TestCase):
def test_update(self):
meter = MetricLogger()
for i in range(10):
meter.update(metric=float(i))
m = meter.meters["metric"]
self.assertEqual(m.count, 10)
self.assertEqual(m.total, 45)
self.as... | code_fim | medium | {
"lang": "python",
"repo": "KaihuaTang/Scene-Graph-Benchmark.pytorch",
"path": "/tests/test_metric_logger.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> _ = meter.not_existent
self.assertRaises(AttributeError, broken)
if __name__ == "__main__":
unittest.main()<|fim_prefix|># repo: KaihuaTang/Scene-Graph-Benchmark.pytorch path: /tests/test_metric_logger.py
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
imp... | code_fim | hard | {
"lang": "python",
"repo": "KaihuaTang/Scene-Graph-Benchmark.pytorch",
"path": "/tests/test_metric_logger.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KaihuaTang/Scene-Graph-Benchmark.pytorch path: /tests/test_metric_logger.py
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import unittest
from maskrcnn_benchmark.utils.metric_logger import MetricLogger
<|fim_suffix|> def test_no_attr(self):
meter = MetricLog... | code_fim | hard | {
"lang": "python",
"repo": "KaihuaTang/Scene-Graph-Benchmark.pytorch",
"path": "/tests/test_metric_logger.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>##CREATE RIVER IMPUT FILE
file_name = "compartmentsGenericRiverSec_prop.txt"
out_file = open(file_name, "w")
out_file.write("riverSection,nameRS,compartment,compType,depth_m,length_m,volume_m3,width_m,G,T_K,vFlow_m_s,SPM_mgL\n")
for rs in range(numRS):
for comp in range(len(compartments)):
#... | code_fim | hard | {
"lang": "python",
"repo": "PradoDomercq/JupiterNotebook_sample_FullMulti",
"path": "/Inputs/GenerateGenericRiverImputFile.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PradoDomercq/JupiterNotebook_sample_FullMulti path: /Inputs/GenerateGenericRiverImputFile.py
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 13 19:05:39 2021
@author: PradoDomercq
"""
#Script to generate the Generic River imput file including
#river sections and compartments of constant dimensio... | code_fim | hard | {
"lang": "python",
"repo": "PradoDomercq/JupiterNotebook_sample_FullMulti",
"path": "/Inputs/GenerateGenericRiverImputFile.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
##CREATE RIVER IMPUT FILE
file_name = "compartmentsGenericRiverSec_prop.txt"
out_file = open(file_name, "w")
out_file.write("riverSection,nameRS,compartment,compType,depth_m,length_m,volume_m3,width_m,G,T_K,vFlow_m_s,SPM_mgL\n")
for rs in range(numRS):
for comp in range(len(compartments)):
... | code_fim | medium | {
"lang": "python",
"repo": "PradoDomercq/JupiterNotebook_sample_FullMulti",
"path": "/Inputs/GenerateGenericRiverImputFile.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Hanyu-Li/neurokernel path: /neurokernel/LPU/synapses/AlphaSynapse.py
from basesynapse import BaseSynapse
import numpy as np
import pycuda.gpuarray as garray
from pycuda.tools import dtype_to_ctype
import pycuda.driver as cuda
from pycuda.compiler import SourceModule
cuda_src = """
__global__ v... | code_fim | hard | {
"lang": "python",
"repo": "Hanyu-Li/neurokernel",
"path": "/neurokernel/LPU/synapses/AlphaSynapse.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.gpu_block = (128,1,1)
self.gpu_grid = (min( 6*cuda.Context.get_device().MULTIPROCESSOR_COUNT,\
(self.num-1)/self.gpu_block[0] + 1), 1)
# cuda_src = open('./alpha_synapse.cu','r')
mod = SourceModule( \
cuda_src % {"type": dt... | code_fim | hard | {
"lang": "python",
"repo": "Hanyu-Li/neurokernel",
"path": "/neurokernel/LPU/synapses/AlphaSynapse.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> arr[i], arr[k] = arr[k], arr[i]
print(arr)<|fim_prefix|># repo: vanigupta20024/Programming-Challenges path: /SelectionSort.py
def selection_sort(arr):
for i in range(len(arr))<|fim_middle|>:
k = i
for j in range(i, len(arr)):
if arr[j] < arr[k]:
... | code_fim | medium | {
"lang": "python",
"repo": "vanigupta20024/Programming-Challenges",
"path": "/SelectionSort.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vanigupta20024/Programming-Challenges path: /SelectionSort.py
def selection_sort(arr):
for i in range(len(arr))<|fim_suffix|> if arr[j] < arr[k]:
k = j
arr[i], arr[k] = arr[k], arr[i]
print(arr)<|fim_middle|>:
k = i
for j in range(i, len(a... | code_fim | easy | {
"lang": "python",
"repo": "vanigupta20024/Programming-Challenges",
"path": "/SelectionSort.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class PywebsocketServer(local_server.LocalServer):
def __init__(self):
super(PywebsocketServer, self).__init__(PywebsocketServerBackend)
def GetBackendStartupArgs(self):
return {}<|fim_prefix|># repo: metux/chromium-suckless path: /tools/perf/benchmarks/pywebsocket_server.py
# Copyright 201... | code_fim | hard | {
"lang": "python",
"repo": "metux/chromium-suckless",
"path": "/tools/perf/benchmarks/pywebsocket_server.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: metux/chromium-suckless path: /tools/perf/benchmarks/pywebsocket_server.py
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import os
import sys
<|fim_suffix|> def __init__(self):
... | code_fim | hard | {
"lang": "python",
"repo": "metux/chromium-suckless",
"path": "/tools/perf/benchmarks/pywebsocket_server.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlexKent3141/PicASCII path: /picascii.py
import os
import sys
import argparse
import itertools
import irc.client
from ascii_converter import *
from pixabay_finder import *
from google_finder import *
''' Picascii is an IRC bot which displays pixel art for the specified search terms. '''
image_... | code_fim | hard | {
"lang": "python",
"repo": "AlexKent3141/PicASCII",
"path": "/picascii.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> online = True
reactor = irc.client.Reactor()
try:
c = reactor.server().connect(args.server, args.port, bot_nick)
except irc.client.ServerConnectionError:
print "Unable to connect: "
print sys.exc_info()[1]
print "Running offline..."
online = False
... | code_fim | hard | {
"lang": "python",
"repo": "AlexKent3141/PicASCII",
"path": "/picascii.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> fig = plt.gcf()
fig.set_size_inches(10, 5)
plt.tight_layout()
fig.savefig(save_to, dpi=200)
fig.clf()<|fim_prefix|># repo: sdss/astra path: /python/astra/contrib/zetapayne/fit_common.py
import matplotlib.pyplot as plt
<|fim_middle|>def save_figure(save_to):
| code_fim | easy | {
"lang": "python",
"repo": "sdss/astra",
"path": "/python/astra/contrib/zetapayne/fit_common.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sdss/astra path: /python/astra/contrib/zetapayne/fit_common.py
import matplotlib.pyplot as plt
<|fim_suffix|> fig = plt.gcf()
fig.set_size_inches(10, 5)
plt.tight_layout()
fig.savefig(save_to, dpi=200)
fig.clf()<|fim_middle|>def save_figure(save_to):
| code_fim | easy | {
"lang": "python",
"repo": "sdss/astra",
"path": "/python/astra/contrib/zetapayne/fit_common.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: david-c-stein/Python-Multiprocessing path: /Logger.py
#!/usr/bin/env python
import logging
import logging.config
import logging.handlers
import traceback
import time
import os
class SizedTimedRotatingFileHandler(logging.handlers.TimedRotatingFileHandler):
def __init__(self, filename, mode=... | code_fim | hard | {
"lang": "python",
"repo": "david-c-stein/Python-Multiprocessing",
"path": "/Logger.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
logconfig = {
'version': 1,
'formatters': {
'detailed': {
'class': 'logging.Formatter',
'format': '[%(levelname)-4s][%(asctime)-15s][%(processName)-10s][%(filename)-10s][%(funcName)-8s][%(lineno)-3s] : %(message)s'
},
'simple': {
'class'... | code_fim | hard | {
"lang": "python",
"repo": "david-c-stein/Python-Multiprocessing",
"path": "/Logger.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # check rollover by size
if self.maxBytes > 0:
msg = "%s\n" % self.format(record)
self.stream.seek(0, 2)
if self.stream.tell() + len(msg) >= self.maxBytes:
return 1
# check rollover by time
t = int(time.time())
if... | code_fim | hard | {
"lang": "python",
"repo": "david-c-stein/Python-Multiprocessing",
"path": "/Logger.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # test loading from database
dynamic_agent = DynamicAgent(owner=config["owner"],
name=config["name"],
game_type=config["game_type"],
class_name=config["class_name"],
... | code_fim | hard | {
"lang": "python",
"repo": "arenarium/battleground_core",
"path": "/unit_tests/test_dynamic_agent.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: arenarium/battleground_core path: /unit_tests/test_dynamic_agent.py
from battleground.dynamic_agent import DynamicAgent
from battleground.games.basic_game.basic_agent import BasicAgent
from battleground.persistence import agent_data
from battleground.agent import Agent
def test_dynamic_agent_lo... | code_fim | hard | {
"lang": "python",
"repo": "arenarium/battleground_core",
"path": "/unit_tests/test_dynamic_agent.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> config = {
"owner": "test_owner",
"name": "test_agent",
"game_type": "test_game",
"class_name": "BasicAgent",
"local_path": "battleground.games.basic_game.basic_agent",
"remote_path": None
}
# create an agent ID
agent_id = agent_data.get_agen... | code_fim | hard | {
"lang": "python",
"repo": "arenarium/battleground_core",
"path": "/unit_tests/test_dynamic_agent.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gudiandian/ElasticFlow path: /ElasticFlow/chronus-scheduler/client/users.py
from abc import ABCMeta, abstractmethod
import os, sys
import math
class UserManager(object):
def __init__(self, **kwargs):
self.user_list = list()
def __getitem__(self, idx):
return self.us... | code_fim | hard | {
"lang": "python",
"repo": "gudiandian/ElasticFlow",
"path": "/ElasticFlow/chronus-scheduler/client/users.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return len(self.user_list)
class BaseUser(metaclass=ABCMeta):
def __init__(self, JOBS, CLUSTER, name, logger, **kwargs):
self.job_manager = JOBS
self.cluster_manager = CLUSTER
self.name = name
self.logger = logger
self.with_job_list = list()
... | code_fim | hard | {
"lang": "python",
"repo": "gudiandian/ElasticFlow",
"path": "/ElasticFlow/chronus-scheduler/client/users.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def finish_job(self, job):
self.with_job_list.remove(job)
class TimeAwareUser(BaseUser):
def __init__(self, JOBS, CLUSTER, name, logger, **kwargs):
super(TimeAwareUser, self).__init__(JOBS=JOBS, CLUSTER=CLUSTER, name=name, logger=logger)
self.quota = kwargs.get('quota')... | code_fim | hard | {
"lang": "python",
"repo": "gudiandian/ElasticFlow",
"path": "/ElasticFlow/chronus-scheduler/client/users.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Gruschwick/ECG_PLATFORM path: /Framework/Sketch/Procedures/QRS/Ecgpuwave.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 22 03:59:01 2020
@author: mateusz
"""
from ..Abstract.ProcedureBase import Base
from biosppy.signals import ecg
from .Resume.Results import *
import w... | code_fim | medium | {
"lang": "python",
"repo": "Gruschwick/ECG_PLATFORM",
"path": "/Framework/Sketch/Procedures/QRS/Ecgpuwave.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return results(ecgpu_detector.xqrs_detect(sig=data.signal, fs=data.freq), data,"Ecgpuwave")<|fim_prefix|># repo: Gruschwick/ECG_PLATFORM path: /Framework/Sketch/Procedures/QRS/Ecgpuwave.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 22 03:59:01 2020
@author: mateusz
"""
from ... | code_fim | medium | {
"lang": "python",
"repo": "Gruschwick/ECG_PLATFORM",
"path": "/Framework/Sketch/Procedures/QRS/Ecgpuwave.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>import skimage
from skimage import img_as_ubyte, img_as_float32
from sklearn.model_selection import StratifiedShuffleSplit
from glob import glob
# import albumentations
#import nibabel as nib
#import pandas as pd<|fim_prefix|># repo: virtualgraham/fgraph path: /src/sc_patch/sc_patch.py
import torch
i... | code_fim | hard | {
"lang": "python",
"repo": "virtualgraham/fgraph",
"path": "/src/sc_patch/sc_patch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: virtualgraham/fgraph path: /src/sc_patch/sc_patch.py
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
from torchvision import models, datasets
import torchvision
from torchvision import transforms... | code_fim | medium | {
"lang": "python",
"repo": "virtualgraham/fgraph",
"path": "/src/sc_patch/sc_patch.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: evancohen/home-assistant path: /homeassistant/components/ifttt.py
"""
homeassistant.components.ifttt
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This component enable you to trigger Maker IFTTT recipes.
For more details about this component, please refer to the documentation at
https://home-assistant.io/comp... | code_fim | medium | {
"lang": "python",
"repo": "evancohen/home-assistant",
"path": "/homeassistant/components/ifttt.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>_LOGGER = logging.getLogger(__name__)
DOMAIN = "ifttt"
SERVICE_TRIGGER = 'trigger'
ATTR_EVENT = 'event'
ATTR_VALUE1 = 'value1'
ATTR_VALUE2 = 'value2'
ATTR_VALUE3 = 'value3'
DEPENDENCIES = []
REQUIREMENTS = ['pyfttt==0.3']
def trigger(hass, event, value1=None, value2=None, value3=None):
""" Trig... | code_fim | medium | {
"lang": "python",
"repo": "evancohen/home-assistant",
"path": "/homeassistant/components/ifttt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def trigger_service(call):
""" Handle ifttt trigger service calls. """
event = call.data.get(ATTR_EVENT)
value1 = call.data.get(ATTR_VALUE1)
value2 = call.data.get(ATTR_VALUE2)
value3 = call.data.get(ATTR_VALUE3)
if event is None:
return
... | code_fim | hard | {
"lang": "python",
"repo": "evancohen/home-assistant",
"path": "/homeassistant/components/ifttt.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if numba < 2:
return False
else:
for k in range(2,numba-1):
if numba % k == 0:
return False
else:
return True
#gen_primes generates a list of primes between 2 and n using a recursive method
def gen_primes(n):
primes = []
for... | code_fim | medium | {
"lang": "python",
"repo": "bugo99iot/mathematics",
"path": "/goldbach/goldbach.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bugo99iot/mathematics path: /goldbach/goldbach.py
#this programs asks the user to input an even integer greater than 2 and expresses it as the sum of two primes
#the program gives all possible combinations of primes
#if you like to know how you can go from working in Subway aged 40 to solving one... | code_fim | hard | {
"lang": "python",
"repo": "bugo99iot/mathematics",
"path": "/goldbach/goldbach.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>print "This code takes an even integer n greater than 2 and expresses all even numbers between 2 and n as a sum of two primes."
n = int(input("Enter n: "))
while n % 2 != 0 or n<2:
print "You must enter an even number greater than 2."
n = int(input("Enter n: "))
else:
print "OK, ", n, "is a ... | code_fim | hard | {
"lang": "python",
"repo": "bugo99iot/mathematics",
"path": "/goldbach/goldbach.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not word: return True
i, n = 0, len(word)
for ch in s:
if ch == word[i]:
i += 1
if i == n:
return True
return False
d.append("")
return next((word for word in ... | code_fim | hard | {
"lang": "python",
"repo": "wyaadarsh/LeetCode-Solutions",
"path": "/Python3/0524-Longest-Word-in-Dictionary-Through-Deleting/soln-1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wyaadarsh/LeetCode-Solutions path: /Python3/0524-Longest-Word-in-Dictionary-Through-Deleting/soln-1.py
class Solution(object):
def findLongestWord(self, s, d):
<|fim_suffix|> if not word: return True
i, n = 0, len(word)
for ch in s:
if ch == ... | code_fim | hard | {
"lang": "python",
"repo": "wyaadarsh/LeetCode-Solutions",
"path": "/Python3/0524-Longest-Word-in-Dictionary-Through-Deleting/soln-1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nnethercote/symbolic path: /py/tests/test_debug.py
import os
from symbolic import ObjectLookup, Archive, id_from_breakpad, normalize_code_id, normalize_debug_id
def test_object_features_mac(res_path):
binary_path = os.path.join(res_path, 'minidump', 'crash_macos')
archive = Archive.ope... | code_fim | hard | {
"lang": "python",
"repo": "nnethercote/symbolic",
"path": "/py/tests/test_debug.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> lookup = ObjectLookup([{
'code_id': 'DFB8E43A-F242-3D73-A453-AEB6A777EF75',
'code_file': 'CoreFoundation',
'debug_id': 'dfb8e43a-f242-3d73-a453-aeb6a777ef75',
'debug_file': 'CoreFoundation.dSYM',
'image_addr': '0x1000',
'image_size': 1024,
}])
f... | code_fim | hard | {
"lang": "python",
"repo": "nnethercote/symbolic",
"path": "/py/tests/test_debug.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Plusers/ASLServerDjango path: /ASLServerDjango/mysite/polls/migrations/0008_books_options.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11.9 on 2019-01-31 09:10
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_s... | code_fim | medium | {
"lang": "python",
"repo": "Plusers/ASLServerDjango",
"path": "/ASLServerDjango/mysite/polls/migrations/0008_books_options.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class Migration(migrations.Migration):
dependencies = [
('polls', '0007_auto_20190123_1923'),
]
operations = [
migrations.AddField(
model_name='books',
name='options',
field=models.CharField(blank=True, choices=[(1, 'Учебник'), (2, 'Художес... | code_fim | medium | {
"lang": "python",
"repo": "Plusers/ASLServerDjango",
"path": "/ASLServerDjango/mysite/polls/migrations/0008_books_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('polls', '0007_auto_20190123_1923'),
]
operations = [
migrations.AddField(
model_name='books',
name='options',
field=models.CharField(blank=True, choices=[(1, 'Учебник'), (2, 'Художественная литература')], max_length=100),... | code_fim | medium | {
"lang": "python",
"repo": "Plusers/ASLServerDjango",
"path": "/ASLServerDjango/mysite/polls/migrations/0008_books_options.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return upload_time < taken_time
def upload_image(file_path):
Notify.Notification.new("Uploading image...").show()
p = subprocess.Popen(["curl", "-F", "token=@/home/bunogi/.monshot_token", "-F", "image=@{}".format(file_path), upload_target], stdout=subprocess.PIPE)
out, err = ... | code_fim | hard | {
"lang": "python",
"repo": "Bunogi/dotfiles",
"path": "/bin/screentool.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
Notify.init("screentool.py")
if len(sys.argv) == 1: # Capture
p = subprocess.run(["maim", "-s", "-k", "-c", "1,0.68,0", "-b", "1", ss_file])
if p.returncode != 0:
exit()
os.system("xclip -sel clipboard -t image/png < " + ss_file)
... | code_fim | hard | {
"lang": "python",
"repo": "Bunogi/dotfiles",
"path": "/bin/screentool.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bunogi/dotfiles path: /bin/screentool.py
#!/usr/bin/env python
import sys
import os
import time
import subprocess
import gi
import base64
import hashlib
import json
ss_file = "/tmp/screenshot.png"
taken_file = "/tmp/screentool-taken"
upload_file = "/tmp/screentool-uploaded"
link_file = "/tmp/sc... | code_fim | hard | {
"lang": "python",
"repo": "Bunogi/dotfiles",
"path": "/bin/screentool.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: feitianyiren/eums path: /eums/api/supply_efficiency_report/supply_efficiency_report_endpoint.py
import logging
from rest_framework.response import Response
from rest_framework.status import HTTP_200_OK, HTTP_503_SERVICE_UNAVAILABLE
from rest_framework.views import APIView
<|fim_suffix|> t... | code_fim | hard | {
"lang": "python",
"repo": "feitianyiren/eums",
"path": "/eums/api/supply_efficiency_report/supply_efficiency_report_endpoint.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def post(self, request):
try:
report_items = SupplyEfficiencyReportService.search_reports(request.data)
return Response(report_items, status=HTTP_200_OK)
except Exception as e:
logger.exception("Try to get response from elasticsearch service failed: ... | code_fim | medium | {
"lang": "python",
"repo": "feitianyiren/eums",
"path": "/eums/api/supply_efficiency_report/supply_efficiency_report_endpoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: APS-XSD-OPT-Group/wavepytools path: /wavepytools/imaging/integration/fourier_integration.py
# -*- coding: utf-8 -*- #
"""
Created on Mon Sep 12 16:40:44 2016
@author: grizolli
"""
import numpy as np
from numpy.fft import fft, ifft
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.p... | code_fim | hard | {
"lang": "python",
"repo": "APS-XSD-OPT-Group/wavepytools",
"path": "/wavepytools/imaging/integration/fourier_integration.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> bigGprime = fft(del_f_del_x*phaseShift)
bigG = bigGprime*mult_factor
func_g = ifft(bigG) /phaseShift
func_g -= func_g[0] # since the integral have and undefined constant,
# here it is applied an arbritary offset
return func_g
# %%
result = fourier_integra... | code_fim | hard | {
"lang": "python",
"repo": "APS-XSD-OPT-Group/wavepytools",
"path": "/wavepytools/imaging/integration/fourier_integration.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: louietsai/python-xbee path: /examples/Receiver.py
#import config
import serial
import time
from xbee import ZigBee
def toHex(s):
lst = []
for ch in s:
hv = hex(ord(ch)).replace('0x', '')
if len(hv) == 1:
hv = '0'+hv
hv = '0x' + hv
lst.append(hv... | code_fim | medium | {
"lang": "python",
"repo": "louietsai/python-xbee",
"path": "/examples/Receiver.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>PORT = '/dev/ttyUSB1'
BAUD_RATE = 9600
# Open serial port
ser = serial.Serial(PORT, BAUD_RATE)
zb = ZigBee(ser, escaped = True)
while True:
data = zb.wait_read_frame()
decodedData = decodeReceivedFrame(data)
print decodedData<|fim_prefix|># repo: louietsai/python-xbee path: /examples/Receive... | code_fim | hard | {
"lang": "python",
"repo": "louietsai/python-xbee",
"path": "/examples/Receiver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>zb = ZigBee(ser, escaped = True)
while True:
data = zb.wait_read_frame()
decodedData = decodeReceivedFrame(data)
print decodedData<|fim_prefix|># repo: louietsai/python-xbee path: /examples/Receiver.py
#import config
import serial
import time
from xbee import ZigBee
def toHex(s):
lst = []... | code_fim | hard | {
"lang": "python",
"repo": "louietsai/python-xbee",
"path": "/examples/Receiver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>], 1, 1e8)
ndvi = (((b2-b1)/(b2+b1)+1)/2*255+0.5).astype(np.uint8)
return (ndvi, raster1[1], raster1[2])<|fim_prefix|># repo: Image-Py/geonumpy path: /geonumpy/indicate/geo_indicate.py
import numpy as np
def ndvi(raster1, raster2):
b1 <|fim_middle|>= np.clip(raster1[0], 1, 1e8)
b2 = np.c... | code_fim | easy | {
"lang": "python",
"repo": "Image-Py/geonumpy",
"path": "/geonumpy/indicate/geo_indicate.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Image-Py/geonumpy path: /geonumpy/indicate/geo_indicate.py
import numpy as np
def ndvi(raster1, raster2):
b1 <|fim_suffix|>type(np.uint8)
return (ndvi, raster1[1], raster1[2])<|fim_middle|>= np.clip(raster1[0], 1, 1e8)
b2 = np.clip(raster2[0], 1, 1e8)
ndvi = (((b2-b1)/(b2+b1)+1)/... | code_fim | medium | {
"lang": "python",
"repo": "Image-Py/geonumpy",
"path": "/geonumpy/indicate/geo_indicate.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> "2": ["3", "4", "5"],
"3": ["4", "5", "6"],
},
{"0": "2", "1": "4", "2": "3", "3": "4"},
[1, 2, 3],
{1: 0.5, 2: 0.75, 3: 1.0},
),
],
)
def test_hits(nn_ind, gold, k, expected):
res = hits(nn_ind, gold, k)
assert res... | code_fim | hard | {
"lang": "python",
"repo": "cthoyt/kiez",
"path": "/tests/evaluate/test_eval_metrics.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cthoyt/kiez path: /tests/evaluate/test_eval_metrics.py
import pytest
from kiez.evaluate import hits
@pytest.mark.parametrize(
"nn_ind, gold, k, expected",
[
(
[[1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 6]],
{0: 2, 1: 4, 2: 3, 3: 4},
[1, 2, 3],
... | code_fim | hard | {
"lang": "python",
"repo": "cthoyt/kiez",
"path": "/tests/evaluate/test_eval_metrics.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='temporaryuploadchunked',
name='offset',
field=models.BigIntegerField(default=0),
),
migrations.AlterField(
model_name='temporaryuploadchunked',
name='total_size',
... | code_fim | medium | {
"lang": "python",
"repo": "ImperialCollegeLondon/django-drf-filepond",
"path": "/django_drf_filepond/migrations/0010_temp_chunked_biginteger.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ImperialCollegeLondon/django-drf-filepond path: /django_drf_filepond/migrations/0010_temp_chunked_biginteger.py
# Generated by Django 3.0.5 on 2021-06-25 16:33
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.A... | code_fim | medium | {
"lang": "python",
"repo": "ImperialCollegeLondon/django-drf-filepond",
"path": "/django_drf_filepond/migrations/0010_temp_chunked_biginteger.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: walnutgeek/D2UX path: /d2ux/model.py
'''
'''
from enum import Enum
import os
class FileType(Enum):
DIR=(0,None,)
CSV=(1,'.csv')
JSON=(2,'.json')
MD=(3,'.md')
class ContentType(Enum):
<|fim_suffix|> os.path.join(self.parts.join('/'),root)<|fim_middle|> DATA_FRAME=(1,)... | code_fim | medium | {
"lang": "python",
"repo": "walnutgeek/D2UX",
"path": "/d2ux/model.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> os.path.join(self.parts.join('/'),root)<|fim_prefix|># repo: walnutgeek/D2UX path: /d2ux/model.py
'''
'''
from enum import Enum
import os
class FileType(Enum):
DIR=(0,None,)
CSV=(1,'.csv')
JSON=(2,'.json')
MD=(3,'.md')
class ContentType(Enum):
DATA_FRAME=(1,)
OBJECT=(2... | code_fim | medium | {
"lang": "python",
"repo": "walnutgeek/D2UX",
"path": "/d2ux/model.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BC-SECURITY/Empire path: /empire/server/core/host_service.py
from sqlalchemy.orm import Session
from empire.server.core.db import models
class HostService(object):
<|fim_suffix|> return db.query(models.Host).all()
@staticmethod
def get_by_id(db: Session, uid: int):
retu... | code_fim | medium | {
"lang": "python",
"repo": "BC-SECURITY/Empire",
"path": "/empire/server/core/host_service.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, main_menu):
self.main_menu = main_menu
@staticmethod
def get_all(db: Session):
return db.query(models.Host).all()
@staticmethod
def get_by_id(db: Session, uid: int):
return db.query(models.Host).filter(models.Host.id == uid).first()<|fim_pre... | code_fim | easy | {
"lang": "python",
"repo": "BC-SECURITY/Empire",
"path": "/empire/server/core/host_service.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> STOPPED = "<stopped>"
RUNNING = "<running>"
COMPLETE = "<complete>"
status = StatusFlag()<|fim_prefix|># repo: cedadev/mistamover path: /lib/StatusFlag.py
# BSD Licence
# Copyright (c) 2012, Science & Technology Facilities Council (STFC)
# All rights reserved.
#
# See the LICENSE file in the sourc... | code_fim | easy | {
"lang": "python",
"repo": "cedadev/mistamover",
"path": "/lib/StatusFlag.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cedadev/mistamover path: /lib/StatusFlag.py
# BSD Licence
# Copyright (c) 2012, Science & Technology Facilities Council (STFC)
# All rights reserved.
#
# See the LICENSE file in the source distribution of this software for
# the full license text.
<|fim_suffix|> STOPPED = "<stopped>"
RUNNING ... | code_fim | easy | {
"lang": "python",
"repo": "cedadev/mistamover",
"path": "/lib/StatusFlag.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: filipknapik/gcp_functions_library path: /aws_s3_to_gcp_gcs/source/main.py
import boto3
import json
import os
from flask import jsonify
from google.cloud import storage
def execute(request):
request_json = request.get_json()
access_key_id = request_json['aws_access_key_id']
secre... | code_fim | hard | {
"lang": "python",
"repo": "filipknapik/gcp_functions_library",
"path": "/aws_s3_to_gcp_gcs/source/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> fileSize = os.path.getsize(tempFileName)
print("filesize="+str(os.path.getsize('/tmp/filedump')))
return fileSize
def writeGCS(gcsbucket, path, tempFileName):
storage_client = storage.Client()
bucket = storage_client.get_bucket(gcsbucket)
blob = bucket.blob(path)
blob.upload_... | code_fim | hard | {
"lang": "python",
"repo": "filipknapik/gcp_functions_library",
"path": "/aws_s3_to_gcp_gcs/source/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def readS3(access_key_id, secret_access_key, s3bucket, region_input, path, tempFileName):
session = boto3.Session(aws_access_key_id=access_key_id,aws_secret_access_key=secret_access_key)
s3 = session.resource('s3',region_name=region_input)
s3.meta.client.download_file(s3bucket, path, tempFile... | code_fim | hard | {
"lang": "python",
"repo": "filipknapik/gcp_functions_library",
"path": "/aws_s3_to_gcp_gcs/source/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # RecId 查出乘客行程，根据乘客行程，改变乘客行程跟车主行程。
# 乘客行程
try:
rec_detail_obj = CarPoolingRecDetail.objects.get(c_id=RecId)
if rec_detail_obj.c_userid != request.session[WOPENID]:
return HttpResponse(RtnDefault(RtnCode.STATUS_PARAM, "非本人不能退订该行程"),
... | code_fim | hard | {
"lang": "python",
"repo": "yangtao4389/pinche",
"path": "/carPooling/api_userrec.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yangtao4389/pinche path: /carPooling/api_userrec.py
rt json
import requests
import traceback
from datetime import datetime,timedelta
from django.shortcuts import render,HttpResponse,HttpResponseRedirect
from django.conf import settings
from common import client,uuid_maker,checkparam
from common.j... | code_fim | hard | {
"lang": "python",
"repo": "yangtao4389/pinche",
"path": "/carPooling/api_userrec.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # "CurrentPageIndex": 1, "PageSize": 20, "RowCount": 66, "PageCount": 4, "IsFirstPage": true, "IsLastPage": false, "CurrentRowCount": 20, "CurrentStartIndex": 1, "CurrentEndIndex": 20
resultDict = dict(
CurrentPageIndex=pageNum,
PageSize=numPerPage,
RowC... | code_fim | hard | {
"lang": "python",
"repo": "yangtao4389/pinche",
"path": "/carPooling/api_userrec.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> class Meta:
model = Function
fields = ('uuid','movie','group')
class ShowtimesSerializer(serializers.ModelSerializer):
"""
Serializer for Function Model
"""
uuid = serializers.UUIDField(source='movie.uuid', format='hex')
movie = ShowtimeMovieSerializer(many=False,... | code_fim | hard | {
"lang": "python",
"repo": "juliancantillo/royal-films",
"path": "/royalfilms/cinemas/serializers.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Serializer for Cinema Model
"""
uuid = serializers.UUIDField(format='hex')
functions = FunctionSerializer(source='function_set', read_only=True, many=True)
class Meta:
model = Cinema
fields = ('uuid','name','functions','address','lat','lng',)<|fim_prefix|># rep... | code_fim | hard | {
"lang": "python",
"repo": "juliancantillo/royal-films",
"path": "/royalfilms/cinemas/serializers.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juliancantillo/royal-films path: /royalfilms/cinemas/serializers.py
from rest_framework import serializers
from .models import Cinema, Function, Show, FunctionType, Auditorium
from royalfilms.movies.models import Movie
from royalfilms.movies.serializers import MovieSerializer,\
ShowtimeMovie... | code_fim | hard | {
"lang": "python",
"repo": "juliancantillo/royal-films",
"path": "/royalfilms/cinemas/serializers.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Testing with Hong Kong/68"""
nuc = "ATGAAGACCATCATTGCTTTGAGCTACATTTTCTGTCTGGCTCTCGGCCAAGACCTTCCAGGAAATGACAACAGCACAGCAACGCTGTGCCTGGGACATCATGCGGTGCCAAACGGAACACTAGTGAAAACAATCACAGATGATCAGATTGAAGTGACTAATGCTACTGAGCTAGTTCAGAGCTCCTCAACGGGGAAAATATGCAACAATCCTCATCGAATCCTTGATGGAATAGACTGCACACTGATAGATGCTCTATTGGGGG... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/treetool",
"path": "/augur/src/seq_util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 5l1v3r1/treetool path: /augur/src/seq_util.py
from itertools import izip
import numpy as np
def hamming_distance(seq1, seq2):
aseq1, aseq2 = np.array(seq1), np.array(seq2)
non_gap = (aseq1!='-')*(aseq2!='-')
return np.mean(aseq1[non_gap]!=aseq2[non_gap])
def translate(nuc):
<|fim_suffix|>def... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/treetool",
"path": "/augur/src/seq_util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
"""Testing with Hong Kong/68"""
nuc = "ATGAAGACCATCATTGCTTTGAGCTACATTTTCTGTCTGGCTCTCGGCCAAGACCTTCCAGGAAATGACAACAGCACAGCAACGCTGTGCCTGGGACATCATGCGGTGCCAAACGGAACACTAGTGAAAACAATCACAGATGATCAGATTGAAGTGACTAATGCTACTGAGCTAGTTCAGAGCTCCTCAACGGGGAAAATATGCAACAATCCTCATCGAATCCTTGATGGAATAGACTGCACACTGATAGATG... | code_fim | hard | {
"lang": "python",
"repo": "5l1v3r1/treetool",
"path": "/augur/src/seq_util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> day = (prn-1)//37
prn = prn - 37*day
start += chip_rate*86400*day
start = start%code_length
p_x1 = x1(prn,start,len)
p_x2 = x2(prn,start-prn,len)
p_last_x2 = last_x2(prn,(start-prn)%code_length,len)
idx_x2 = (start - prn + np.arange(len)) % code_length
idx_last_x2 = idx_x2>=(code_lengt... | code_fim | hard | {
"lang": "python",
"repo": "mfkiwl/GNSS-DSP-tools",
"path": "/gnsstools/gps/p.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def chips2hex(c):
n = c.shape[0]//4
r = c.shape[0]%4
if r!=0:
s = octal_digit(c[0:r])
else:
s = ""
for i in range(n):
s += hex_digit(c[r+4*i:r+4*(i+1)])
return s
def first_256_chips_hex(prn):
start = 0
len = 256
c = p_code(prn,start,len)
return chips2hex(c)
def last_1024_... | code_fim | hard | {
"lang": "python",
"repo": "mfkiwl/GNSS-DSP-tools",
"path": "/gnsstools/gps/p.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mfkiwl/GNSS-DSP-tools path: /gnsstools/gps/p.py
# GPS P code construction
#
# Copyright 2014 Peter Monta
import numpy as np
chip_rate = 10230000
code_length = chip_rate*86400*7
def x1a_shift(x):
return [x[11]^x[10]^x[7]^x[5]] + x[0:11]
def x1b_shift(x):
return [x[11]^x[10]^x[9]^x[8]^x[7]^... | code_fim | hard | {
"lang": "python",
"repo": "mfkiwl/GNSS-DSP-tools",
"path": "/gnsstools/gps/p.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Junlin-Yin/Data-Mining-Homework path: /hw3/hw3_code/neural_networks/feedforward_backprop.py
from fullyconnect_feedforward import fullyconnect_feedforward
from fullyconnect_backprop import fullyconnect_backprop
from relu_feedforward import relu_feedforward
from relu_backprop import relu_backprop
f... | code_fim | medium | {
"lang": "python",
"repo": "Junlin-Yin/Data-Mining-Homework",
"path": "/hw3/hw3_code/neural_networks/feedforward_backprop.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# feedforward hidden layer and relu
fully1_out = fullyconnect_feedforward(data, weights['fully1_weight'], weights['fully1_bias'])
#print('fully1_out', fully1_out)
relu1_out = relu_feedforward(fully1_out)
#print("relu1_out", relu1_out)
# softmax loss (probs = e^(w*x+b) / sum(e^(w*... | code_fim | medium | {
"lang": "python",
"repo": "Junlin-Yin/Data-Mining-Homework",
"path": "/hw3/hw3_code/neural_networks/feedforward_backprop.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# feedforward hidden layer and relu
fully1_out = fullyconnect_feedforward(data, weights['fully1_weight'], weights['fully1_bias'])
#print('fully1_out', fully1_out)
relu1_out = relu_feedforward(fully1_out)
#print("relu1_out", relu1_out)
# softmax loss (probs = e^(w*x+b) / sum(e^(w... | code_fim | medium | {
"lang": "python",
"repo": "Junlin-Yin/Data-Mining-Homework",
"path": "/hw3/hw3_code/neural_networks/feedforward_backprop.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>iff//max_diff + 1)
if total_diffs*diff_base+len(dense_array_of_diffs)*correction_precision < min_total_diff_cost:
min_total_diff_cost = total_diffs*diff_base+len(dense_array_of_diffs)*correction_precision
return min_total_diff_cost<|fim_prefix|># repo: pandey-shruti/LC-model-compr... | code_fim | hard | {
"lang": "python",
"repo": "pandey-shruti/LC-model-compression",
"path": "/lc/compression_types/utils.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pandey-shruti/LC-model-compression path: /lc/compression_types/utils.py
import numpy as np
"""
TODO: This file is poorly documented for now, will fix in future version.
"""
def diff_based_coding(dense_array_of_diffs, correction_precision=16, diff_bases=range(3, 20)):
min_total_diff_cost ... | code_fim | hard | {
"lang": "python",
"repo": "pandey-shruti/LC-model-compression",
"path": "/lc/compression_types/utils.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class NamesClassifier(Model):
def __init__(self,
word_embeddings: TextFieldEmbedder,
encoder: Seq2SeqEncoder,
vocab: Vocabulary) -> None:
super().__init__(vocab)
self.word_embeddings = word_embeddings
self.encoder = encoder
... | code_fim | hard | {
"lang": "python",
"repo": "Murfin/allennlp_lab4",
"path": "/modules/homework_4.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Murfin/allennlp_lab4 path: /modules/homework_4.py
from typing import Iterator, List, Dict
import torch
import torch.optim as optim
import numpy as np
from allennlp.common.params import Params
from allennlp.data import Instance
from allennlp.data.fields import TextField, SequenceLabelField
fro... | code_fim | hard | {
"lang": "python",
"repo": "Murfin/allennlp_lab4",
"path": "/modules/homework_4.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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