text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> x, y = point
x = x * inverseClipperScale
if int(x) == x:
x = int(x)
y = y * inverseClipperScale
if int(y) == y:
y = int(y)
return x, y
# ----------
# Attributes
# ----------
def _get_final(self):
# XXX this c... | code_fim | hard | {
"lang": "python",
"repo": "typemytype/booleanOperations",
"path": "/Lib/booleanOperations/flatten.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sat_images, pos, neg, alt, slp = dataset.make_small_dataset("data/")
gen = dataset.patch_generator(sat_images, pos, neg, alt, slp, area, batch_size, 0.4)
X, y = next(gen)
assert X.shape == (batch_size, area, area, 14)<|fim_prefix|># repo: MVPTylerE/landslide path: /test/test_dataset.... | code_fim | medium | {
"lang": "python",
"repo": "MVPTylerE/landslide",
"path": "/test/test_dataset.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MVPTylerE/landslide path: /test/test_dataset.py
import dataset
def test_call_patch_generator():
sat_images, pos, neg, alt, slp = dataset.make_small_dataset("data/")
gen = dataset.patch_generator(sat_images, pos, neg, alt, slp, 25, 512, 0.4)
next(gen)
<|fim_suffix|> sat_images, p... | code_fim | medium | {
"lang": "python",
"repo": "MVPTylerE/landslide",
"path": "/test/test_dataset.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JeffreyUrban/count-sequences path: /iterate_and_count.py
# Naive approach as point of truth and performance benchmark.
# Single dictionary: Iterate through items. Count sequences of all lengths ending at that item.
from collections import Counter
<|fim_suffix|> sequences = Counter()
for... | code_fim | medium | {
"lang": "python",
"repo": "JeffreyUrban/count-sequences",
"path": "/iterate_and_count.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for sequence in sequences.most_common():
if sequence[1] < 2:
# Keep only repeated sequences
del sequences[sequence[0]]
return sequences<|fim_prefix|># repo: JeffreyUrban/count-sequences path: /iterate_and_count.py
# Naive approach as point of truth and performance... | code_fim | hard | {
"lang": "python",
"repo": "JeffreyUrban/count-sequences",
"path": "/iterate_and_count.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_mnist_model_register_using_non_existent_handler_with_nonzero_workers():
'''
Validates that a model cannot be registered with a non existent handler if
the initial number of workers is greater than zero.
'''
response = requests.post(
'http://127.0.0.1:8081/models?handl... | code_fim | hard | {
"lang": "python",
"repo": "AbishekIdeas/serve",
"path": "/test/pytest/test_handler.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AbishekIdeas/serve path: /test/pytest/test_handler.py
import subprocess
import time
import os
import glob
import requests
import json
from os import path
ROOT_DIR = "/workspace/"
MODEL_STORE = ROOT_DIR + "model_store/"
# CHANGE THIS TO CORRECT PYTORCH CODE REPOSITORY
CODEBUILD_WD = path.abspath(... | code_fim | hard | {
"lang": "python",
"repo": "AbishekIdeas/serve",
"path": "/test/pytest/test_handler.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for k in old_values:
if k in new_values:
if old_values[k] != new_values[k]:
audit_values.append({"key": k, "action": "updated", "value": new_values[k]})
else:
audit_values.append({"key": k, "action": "removed", "value": old_values[k]})
new_keys = set(new_valu... | code_fim | hard | {
"lang": "python",
"repo": "HeqetLabs/dynaconfig",
"path": "/dynaconfig/endpoints.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> current_config = list(r.table("config").get_all(config_id(user_id, config_name), index="name").run(db.conn))
if current_config:
current_config = current_config[0]
if 0 <= version <= current_config["highest_version"]:
current_version = current_config["version"]
audit_tr... | code_fim | hard | {
"lang": "python",
"repo": "HeqetLabs/dynaconfig",
"path": "/dynaconfig/endpoints.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HeqetLabs/dynaconfig path: /dynaconfig/endpoints.py
import datetime
import rethinkdb as r
from flask import request
from flask.ext.restful import Resource, abort
from dynaconfig import db
from time import time
def config_id(user_id, config_name):
return "{}-{}".format(user_id, config_name)
... | code_fim | hard | {
"lang": "python",
"repo": "HeqetLabs/dynaconfig",
"path": "/dynaconfig/endpoints.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: log2timeline/plaso path: /tests/parsers/text_plugins/gdrive_synclog.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for the Google Drive Sync log log text parser plugin."""
import unittest
from dfvfs.helpers import fake_file_system_builder
from plaso.parsers import text_parser
from ... | code_fim | hard | {
"lang": "python",
"repo": "log2timeline/plaso",
"path": "/tests/parsers/text_plugins/gdrive_synclog.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> number_of_warnings = storage_writer.GetNumberOfAttributeContainers(
'recovery_warning')
self.assertEqual(number_of_warnings, 0)
expected_event_values = {
'added_time': '2018-03-01T12:48:14.224-08:00',
'data_type': 'google_drive_sync_log:entry',
'level': 'INFO',... | code_fim | hard | {
"lang": "python",
"repo": "log2timeline/plaso",
"path": "/tests/parsers/text_plugins/gdrive_synclog.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liyanting0403/tongjierban path: /5.2.py
#猜数字:第一关总共10轮,每一个100分.
# 由电脑随机产生两个数字,让用户输入这两个数字的和.
# 最后看是进入第二关还是’Game Over’
import random
def youxi():
<|fim_suffix|> if count == 1000:
print('开始第二关')
else:
print('Game Over.')
def start():
youxi()
start()<|fim... | code_fim | hard | {
"lang": "python",
"repo": "liyanting0403/tongjierban",
"path": "/5.2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> count = 0
for i in range(5):
num1 = random.randint(0,5)
num2 = random.randint(0,5)
print(num1,num2)
num3 = int(input("请输入num1+num2 == "))
if num3 == num1+num2:
print("please continue")
count+=200
else:
pr... | code_fim | medium | {
"lang": "python",
"repo": "liyanting0403/tongjierban",
"path": "/5.2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return tuple(result), code
def rebuild(self, conversion, tail_code, cf_cap=None):
"""
Recreates the voltage from a conversion
:param conversion: Tuples of references of convesion,
shape = base_shape + (n_caps-1, n_diff,)
:type conversion: :class:`t... | code_fim | hard | {
"lang": "python",
"repo": "jabozzo/delta_sigma_pipe_lascas_2020",
"path": "/calib/calib/gen.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Represents a number of configuration and inputs pairs.
"""
@classmethod
def Stack(cls, conf_set0, *conf_sets):
assert all(conf_set0.ds_samples == conf_set.ds_samples for conf_set in conf_sets)
conf_sets = (conf_set0,) + conf_sets
inputs = tuple(e for conf_... | code_fim | hard | {
"lang": "python",
"repo": "jabozzo/delta_sigma_pipe_lascas_2020",
"path": "/calib/calib/gen.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jabozzo/delta_sigma_pipe_lascas_2020 path: /calib/calib/gen.py
les, self.n_cs, n_diff,)
crop_idx = (slice(start_sample, start_sample+n_samples), slice(None), slice(None),)
ins = np.broadcast_to(np.reshape([-1] * self.n_cs * n_diff, shape), full_shape)
ins = ins[crop_idx]
... | code_fim | hard | {
"lang": "python",
"repo": "jabozzo/delta_sigma_pipe_lascas_2020",
"path": "/calib/calib/gen.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fvigo/content path: /Packs/mnemonicMDR/Integrations/ArgusManagedDefence/ArgusManagedDefence.py
mit=args.get("limit", None),
sortBy=sort_by,
)
return CommandResults(
readable_output=pretty_print_comments(
result["data"], f"# #{case_id}: Comments\n"
),
... | code_fim | hard | {
"lang": "python",
"repo": "fvigo/content",
"path": "/Packs/mnemonicMDR/Integrations/ArgusManagedDefence/ArgusManagedDefence.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> result = get_case_metadata_by_id(
id=case_id, skipRedirect=args.get("skip_redirect", None)
)
return CommandResults(
readable_output=pretty_print_case_metadata(result),
outputs_prefix="Argus.Case",
outputs=result,
raw_response=result,
)
def list_ca... | code_fim | hard | {
"lang": "python",
"repo": "fvigo/content",
"path": "/Packs/mnemonicMDR/Integrations/ArgusManagedDefence/ArgusManagedDefence.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def remove_case_tag_by_key_value_command(args: Dict[str, Any]) -> CommandResults:
case_id = args.get("case_id", None)
key = args.get("key", None)
value = args.get("value", None)
if not case_id:
raise ValueError("case id not specified")
if not key:
raise ValueError("key... | code_fim | hard | {
"lang": "python",
"repo": "fvigo/content",
"path": "/Packs/mnemonicMDR/Integrations/ArgusManagedDefence/ArgusManagedDefence.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: girder/dkc-next path: /dkc/core/models/quota.py
from typing import Type
from django.conf import settings
from django.contrib.auth.models import User
from django.db import IntegrityError, models, transaction
from django.db.models.signals import post_save
from django.dispatch import receiver
from... | code_fim | hard | {
"lang": "python",
"repo": "girder/dkc-next",
"path": "/dkc/core/models/quota.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
# Use an .update query instead of a .save, to avoid assigning an F-expression on the
# local instance, which might need to be rolled back on a failure
Quota.objects.filter(pk=self.pk).update(used=(models.F('used') + amount))
except IntegrityError as... | code_fim | hard | {
"lang": "python",
"repo": "girder/dkc-next",
"path": "/dkc/core/models/quota.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: odchavez/CausalDART path: /bartpy/examples/ols.py
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from bartpy.extensions.baseestimator import ResidualBART
from bartpy.sklearnmodel import SklearnModel
def run(alpha, beta, n_trees, n_regressors, n_burn=50, n_samples=2... | code_fim | hard | {
"lang": "python",
"repo": "odchavez/CausalDART",
"path": "/bartpy/examples/ols.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == "__main__":
import cProfile
from datetime import datetime as dt
print(dt.now())
# model, x, y = run(0.95, 2., 200, 50, n_obsv=100000)
cProfile.run("run(0.95, 2., 200, 40)", "restats")
print(dt.now())<|fim_prefix|># repo: odchavez/CausalDART path: /bartpy/examples/o... | code_fim | hard | {
"lang": "python",
"repo": "odchavez/CausalDART",
"path": "/bartpy/examples/ols.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
import cProfile
from datetime import datetime as dt
print(dt.now())
# model, x, y = run(0.95, 2., 200, 50, n_obsv=100000)
cProfile.run("run(0.95, 2., 200, 40)", "restats")
print(dt.now())<|fim_prefix|># repo: odchavez/CausalDART path: /bartpy/examples/... | code_fim | hard | {
"lang": "python",
"repo": "odchavez/CausalDART",
"path": "/bartpy/examples/ols.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: clawnchair/svexdb path: /svexdb/settings.py
"""
Django settings for svexdb project.
Generated by 'django-admin startproject' using Django 2.0.
For more information on this file, see
https://docs.djangoproject.com/en/2.0/topics/settings/
For the full list of settings and their values, see
https... | code_fim | hard | {
"lang": "python",
"repo": "clawnchair/svexdb",
"path": "/svexdb/settings.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@pytest.mark.parametrize("missing_attr", ["result_paths", "cross_experiment_key"])
def test_invalid_environment(monkeypatch, env_fixture_0, missing_attr):
monkeypatch.delattr(settings.G.Env, missing_attr)
with pytest.raises(EnvironmentInvalidError):
CrossExperimentKeyMaker(dict(a="foo", b... | code_fim | hard | {
"lang": "python",
"repo": "mdjabc/hyperparameter_hunter",
"path": "/tests/test_keys.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert make_hash_sha256(obj) == expected
@pytest.mark.parametrize(["obj", "expected"], **args_ids_for(scenarios_lambda))
def test_make_hash_sha256_lambda(obj, expected):
assert make_hash_sha256(obj) == expected
@pytest.mark.parametrize(["obj", "expected"], **args_ids_for(scenarios_partial))
de... | code_fim | hard | {
"lang": "python",
"repo": "mdjabc/hyperparameter_hunter",
"path": "/tests/test_keys.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mdjabc/hyperparameter_hunter path: /tests/test_keys.py
"LjjneyLDFKRJ6R-v7ZKkOCasaqQDrmqKy2z1gjn7r10="], # Same as empty list, dict
[("foo", "bar"), "nLa17RepW5vZ-h-Tmoj56p_xIznyxOK7HXJX-Y4XieE="],
[("bar", "foo"), "5UmXFMC8LmyZJLnaImLH108nXTNQE4Ei4ZzmLsqxzCE="],
]
scenarios_list = [
... | code_fim | hard | {
"lang": "python",
"repo": "mdjabc/hyperparameter_hunter",
"path": "/tests/test_keys.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>benchmark = Benchmarker(**params)
benchmark.benchmark_all()
benchmark.print_results()
benchmark.plot_results()<|fim_prefix|># repo: EduardoRubioM/mat281_portfolio path: /m02_data_analysis/m02_c06_development/fast_pandas/benchmark_prod.py
from Benchmarker import Benchmarker
import numpy as np
def pandas... | code_fim | hard | {
"lang": "python",
"repo": "EduardoRubioM/mat281_portfolio",
"path": "/m02_data_analysis/m02_c06_development/fast_pandas/benchmark_prod.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
params = {
"df_generator": 'pd.DataFrame(np.random.randint(1, df_size, (df_size, 2)), columns=list("AB"))',
"functions_to_evaluate": [numpy_values_prod, numpy_values_nanprod, pandas_prod, numpy_prod],
"title": "Pandas Prod vs Numpy Prod",
}
benchmark = Benchmarker(**params)
benchmark.benchma... | code_fim | hard | {
"lang": "python",
"repo": "EduardoRubioM/mat281_portfolio",
"path": "/m02_data_analysis/m02_c06_development/fast_pandas/benchmark_prod.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: prometheusresearch/baseline-codebase path: /src/rex.widget/demo/src/rex/widget_demo.py
"""
rex.widget_demo
===============
:copyright: 2015, Prometheus Research, LLC
"""
from rex.core import Setting, SeqVal, RecordVal, StrVal, get_settings
from rex.widget import computed_field, Wi... | code_fim | hard | {
"lang": "python",
"repo": "prometheusresearch/baseline-codebase",
"path": "/src/rex.widget/demo/src/rex/widget_demo.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class DemoPageHome(Widget):
name = 'DemoPageHome'
js_type = 'rex-widget-demo', 'Home'
class DemoPageLayout(Widget):
name = 'DemoPageLayout'
js_type = 'rex-widget-demo', 'Layout'
class DemoPageUI(Widget):
name = 'DemoPageUI'
js_type = 'rex-widget-demo', 'UI'
class DemoPageFor... | code_fim | hard | {
"lang": "python",
"repo": "prometheusresearch/baseline-codebase",
"path": "/src/rex.widget/demo/src/rex/widget_demo.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ibaiGorordo/lanedet path: /configs/condlane/resnet101_culane.py
net = dict(
type='Detector',
)
backbone = dict(
type='ResNetWrapper',
resnet='resnet101',
pretrained=True,
replace_stride_with_dilation=[False, False, False],
out_conv=False,
in_channels=[64, 128, 256, 51... | code_fim | hard | {
"lang": "python",
"repo": "ibaiGorordo/lanedet",
"path": "/configs/condlane/resnet101_culane.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ),
dict(type='CollectLane',
down_scale=mask_down_scale,
hm_down_scale=hm_down_scale,
max_mask_sample=5,
line_width=line_width,
radius=radius,
keys=['img', 'gt_hm'],
meta_keys=[
'gt_masks', 'mask_shape', 'hm_shape',
'do... | code_fim | hard | {
"lang": "python",
"repo": "ibaiGorordo/lanedet",
"path": "/configs/condlane/resnet101_culane.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>bbox = np.array([[[-100,-100,0], [-5, -100, 0], [-5,-5,0], [-100,-5,0], [-100,-100,100], [-5, -100, 100], [-5,-5,100], [-100,-5,100]]])
image_size = (2000, 2000)
rays,rgbs = ray_sampling(Ks,Ts,image_size)
# print(bbox)
bbox = torch.from_numpy(bbox).reshape((1, 8, 3))
sample_t = rsp.forward(rays[:5000].re... | code_fim | hard | {
"lang": "python",
"repo": "suoxinkey/PlenOctrees_NeRF-SH",
"path": "/tests/test_ray_samplepoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suoxinkey/PlenOctrees_NeRF-SH path: /tests/test_ray_samplepoint.py
import sys
sys.path.append('..')
from layers.RaySamplePoint import RaySamplePoint
import torch
import numpy as np
from utils.ray_sampling import ray_sampling
from mpl_toolkits.mplot3d.axes3d import Axes3D
import matplotlib.pyplot ... | code_fim | hard | {
"lang": "python",
"repo": "suoxinkey/PlenOctrees_NeRF-SH",
"path": "/tests/test_ray_samplepoint.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>image_size = (2000, 2000)
rays,rgbs = ray_sampling(Ks,Ts,image_size)
# print(bbox)
bbox = torch.from_numpy(bbox).reshape((1, 8, 3))
sample_t = rsp.forward(rays[:5000].reshape(-1,6), bbox, method=None)<|fim_prefix|># repo: suoxinkey/PlenOctrees_NeRF-SH path: /tests/test_ray_samplepoint.py
import sys
sys.p... | code_fim | medium | {
"lang": "python",
"repo": "suoxinkey/PlenOctrees_NeRF-SH",
"path": "/tests/test_ray_samplepoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def lista_wektorow(self, typ):
"""
Metoda obliczająca iloczyn kartezjański dla dwóch wygenerowanych list metodą 'wspolrzedna_wektora'.
:param typ: Określa, z jakiego zakresu mają być wybierane wektory sieci odwrotnej. Wartość min oznacza, że
z podstawowego tzn. dla tych... | code_fim | hard | {
"lang": "python",
"repo": "szymag/ZFN",
"path": "/src/eig_problem/WektorySieciOdwrotnej.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: szymag/ZFN path: /src/eig_problem/WektorySieciOdwrotnej.py
from math import sqrt
import numpy as np
class WektorySieciOdwrotnej:
"""
Klasa, której zadaniem jest wygenerowanie wektorow sieci odwrotnej, służących dalej do definiowania
macierzy zagadnienia własnego. W tym przypadku wy... | code_fim | hard | {
"lang": "python",
"repo": "szymag/ZFN",
"path": "/src/eig_problem/WektorySieciOdwrotnej.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param k: Określa, którą współrzędną metoda ma obliczyć. Dla k=1 igrekową, dla k=2 zetową.
:param typ: Określa, z jakiego zakresu mają być wybierane wektory sieci odwrotnej. Wartość min oznacza, że
z podstawowego tzn. dla tych wektorów generuje się zagadnienie własne. Wartość max o... | code_fim | hard | {
"lang": "python",
"repo": "szymag/ZFN",
"path": "/src/eig_problem/WektorySieciOdwrotnej.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pedrohenriquebraga/Curso-Python path: /Mundo 3/Exercícios/ex_106.py
# Mini-Menu para Interactive Help
from time import sleep
cores = {"limpa":"\033[m",
"azul":"\033[7;36m",
"roxo":"\033[7;35m",
"negrito":"\033[1m",
"branco":"\033[7m",
"verde":"\033[7;32m",
"amarelo":"\033[33m",
"vermelho":"\... | code_fim | hard | {
"lang": "python",
"repo": "pedrohenriquebraga/Curso-Python",
"path": "/Mundo 3/Exercícios/ex_106.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> funcao = str(input(f"{cores['negrito']}QUAL COMANDO VOCÊ QUER PESQUISAR?[FIM para] = "))
if funcao.upper() == "FIM":
break
print()
print(f"{cores['azul']}=" * 50)
print(f"{f'ACESSANDO PYHELP PARA {funcao.upper()}':^50}")
print("=" * 50)
sleep(1)
print(f"{c... | code_fim | medium | {
"lang": "python",
"repo": "pedrohenriquebraga/Curso-Python",
"path": "/Mundo 3/Exercícios/ex_106.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, *args, always_show_modifiers=False, **kwargs):
super().__init__(*args, **kwargs)
self.time_total = None
self.run_state = None
self.always_show_modifiers = always_show_modifiers
def initialize(self):
self.time_total = 0
self.run_st... | code_fim | hard | {
"lang": "python",
"repo": "RacconAppend/modlunky2",
"path": "/src/modlunky2/ui/trackers/category.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RacconAppend/modlunky2 path: /src/modlunky2/ui/trackers/category.py
from enum import Enum
import logging
from logging import CRITICAL, WARNING
import tkinter as tk
from tkinter import ttk
from queue import Empty
from PIL import Image, ImageTk
from modlunky2.config import Config
from modlunky2.c... | code_fim | hard | {
"lang": "python",
"repo": "RacconAppend/modlunky2",
"path": "/src/modlunky2/ui/trackers/category.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self, *args, always_show_modifiers=False, **kwargs):
super().__init__(file_name="category.txt", *args, **kwargs)
self.watcher_thread = CategoryWatcherThread(
self.queue,
always_show_modifiers=always_show_modifiers,
)
self.watcher_th... | code_fim | hard | {
"lang": "python",
"repo": "RacconAppend/modlunky2",
"path": "/src/modlunky2/ui/trackers/category.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MouseHu/emdqn path: /baselines/ecbp/agents/buffer/ps_learning_process.py
import numpy as np
from sklearn.neighbors import BallTree, KDTree
import os
from baselines.ecbp.agents.buffer.lru_knn_gpu_ps import LRU_KNN_GPU_PS
from baselines.ecbp.agents.buffer.lru_knn_gpu_ps_density import LRU_KNN_GPU_P... | code_fim | hard | {
"lang": "python",
"repo": "MouseHu/emdqn",
"path": "/baselines/ecbp/agents/buffer/ps_learning_process.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # recursive backup
# self.log("begin backup", self.run_sweep)
self.num_iters += 1
# self.log("bk pqueue len", len(self.pqueue))
if len(self.pqueue) > 0:
if self.iters_per_step < self.min_iter:
self.iters_per_step += 1
# self.l... | code_fim | hard | {
"lang": "python",
"repo": "MouseHu/emdqn",
"path": "/baselines/ecbp/agents/buffer/ps_learning_process.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while self.run_sweep:
self.backup()
if self.update_enough:
self.recv_msg()
# self.update_enough = 0
def retrieve_q_value(self, obj):
z, h, knn = obj
extrinsic_qs, intrinsic_qs, find, neighbour_ind,neighbour_dist = self.e... | code_fim | hard | {
"lang": "python",
"repo": "MouseHu/emdqn",
"path": "/baselines/ecbp/agents/buffer/ps_learning_process.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def add(self, what, **attributes):
if type(what) in [C, Y, X]:
child = what
else:
child = X(what, **attributes)
self.children.append(child)
return child
def to_xml_lines(self, margin=0, indent=2):
output = []
spaces = ' ' * m... | code_fim | hard | {
"lang": "python",
"repo": "guitarmanvt/cson2lang",
"path": "/xmlish.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guitarmanvt/cson2lang path: /xmlish.py
"""Dirt-simple XML structure building, without the nasties.
Simplifications/limitations:
- XML comments are only allowed as siblings to other tags and strictly formatted.
- Internal Text is allowed, but cannot be intermixed with children or comments.
- Attr... | code_fim | hard | {
"lang": "python",
"repo": "guitarmanvt/cson2lang",
"path": "/xmlish.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def detach_template(self, api, template_index, filter_fn):
"""
:param api: Instance of Rest API
:param template_index: Instance of DeviceTemplateIndex
:param filter_fn: Function used to filter elements to be returned
:return: List of worker actions to monitor [(... | code_fim | hard | {
"lang": "python",
"repo": "jeremypng/sastre",
"path": "/cisco_sdwan/tasks/common.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeremypng/sastre path: /cisco_sdwan/tasks/common.py
s):
self._log('warning', *args)
def log_error(self, *args):
self._log('error', *args)
def log_critical(self, *args):
self._log('critical', *args)
def _log(self, level, *args):
getattr(logging.getLog... | code_fim | hard | {
"lang": "python",
"repo": "jeremypng/sastre",
"path": "/cisco_sdwan/tasks/common.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._rows.extend(self._row_class(*row_values) for row_values in row_values_iter)
def __iter__(self):
return iter(self._rows)
def __len__(self):
total_len = len(self._rows) - self._rows.count(None)
return total_len if total_len > 0 else 0
def _column_max_widt... | code_fim | hard | {
"lang": "python",
"repo": "jeremypng/sastre",
"path": "/cisco_sdwan/tasks/common.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Apkawa/django-querybuilder-rules path: /querybuilder_rules/variables/simple.py
from collections import namedtuple
from django.utils.encoding import smart_text
<|fim_suffix|>class IntegerVariable(SimpleTypeVariable):
type = int
class FloatVariable(SimpleTypeVariable):
type = float
cl... | code_fim | hard | {
"lang": "python",
"repo": "Apkawa/django-querybuilder-rules",
"path": "/querybuilder_rules/variables/simple.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return {
'value': TypeVariableField(self.title, self.help_text, None, self.get_context)
}
class IntegerVariable(SimpleTypeVariable):
type = int
class FloatVariable(SimpleTypeVariable):
type = float
class TextVariable(SimpleTypeVariable):
type = str
class Boo... | code_fim | medium | {
"lang": "python",
"repo": "Apkawa/django-querybuilder-rules",
"path": "/querybuilder_rules/variables/simple.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kajweb/myj_crawler path: /main.py
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from function import *
from globalvar import *
from util import *
import json
# 初始化全局变量
globalvar_init();
# 初始化mysql库
connectMysql();
#初始化Urllib
# curl = initUrllib();
<|fim_suffix|>categoryResponse = getCategory(auth... | code_fim | medium | {
"lang": "python",
"repo": "kajweb/myj_crawler",
"path": "/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>mysql = get_value("mysql");
mysql.execute("select * from myj_category where deal = 0");
data = mysql.fetchall()
for i in data:
id = i[0];
name = i[1];
title = i[2];
#datetime = i[4];
# getBook( id, name, title )
getBook( id, authorization );<|fim_prefix|># repo: kajweb/myj_crawler path: /main.py
#!... | code_fim | medium | {
"lang": "python",
"repo": "kajweb/myj_crawler",
"path": "/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def init_fcm_config(config_file):
if not os.path.exists(config_file):
with open(config_file, 'w') as config:
json.dump(INITIAL_CONFIG, config)<|fim_prefix|># repo: jphacks/SD_1806 path: /server/fcmconfig.py
import json, os
INITIAL_CONFIG = {
'id': ''
}
def set_fcm_config(co... | code_fim | medium | {
"lang": "python",
"repo": "jphacks/SD_1806",
"path": "/server/fcmconfig.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not os.path.exists(config_file):
with open(config_file, 'w') as config:
json.dump(INITIAL_CONFIG, config)<|fim_prefix|># repo: jphacks/SD_1806 path: /server/fcmconfig.py
import json, os
INITIAL_CONFIG = {
'id': ''
}
<|fim_middle|>def set_fcm_config(config, form):
if '... | code_fim | medium | {
"lang": "python",
"repo": "jphacks/SD_1806",
"path": "/server/fcmconfig.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jphacks/SD_1806 path: /server/fcmconfig.py
import json, os
INITIAL_CONFIG = {
'id': ''
}
def set_fcm_config(config, form):
if 'id' in form:
json.dump({"id": form['id']}, config)
return config
<|fim_suffix|> if not os.path.exists(config_file):
with open(config_fil... | code_fim | easy | {
"lang": "python",
"repo": "jphacks/SD_1806",
"path": "/server/fcmconfig.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: steev/etest path: /etest_test/fixtures_test/scripts_test/ed59fae4f26745cda3050c9d60077a2a.py
"""Unadorned curly braces."""
import textwrap
from etest_test.fixtures_test.scripts_test import SCRIPTS
<|fim_suffix|>SCRIPTS.setdefault("all", []).append(_)
SCRIPTS.setdefault("bash", []).append(_)<|f... | code_fim | hard | {
"lang": "python",
"repo": "steev/etest",
"path": "/etest_test/fixtures_test/scripts_test/ed59fae4f26745cda3050c9d60077a2a.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xxxxHolic/pypcl path: /pcl/pointcloud.py
else:
shape = dtype.subdtype[1][0] if len(dtype.subdtype[1]) == 1 else dtype.subdtype[1]
return str(shape) + _numpy_to_txt(dtype.subdtype[0])
def _cast_fields_to_tuples(dtype):
# Cast point fields into specific tuples that can be ... | code_fim | hard | {
"lang": "python",
"repo": "xxxxHolic/pypcl",
"path": "/pcl/pointcloud.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xxxxHolic/pypcl path: /pcl/pointcloud.py
p.array([])
self.__width = abs(width)
self.__height = abs(height)
# adjust points with width and height automatically
if width is 0:
if _safe_len(self.__points) > 0:
widt... | code_fim | hard | {
"lang": "python",
"repo": "xxxxHolic/pypcl",
"path": "/pcl/pointcloud.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __len__(self):
return _safe_len(self.__points)
def __iter__(self):
return iter(self.__points)
def __contains__(self, item):
# for the field names, use 'names' property for instead.
return item in self.__points
def __reduce__(self):
# Pickle su... | code_fim | hard | {
"lang": "python",
"repo": "xxxxHolic/pypcl",
"path": "/pcl/pointcloud.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>treefarmcfg = configparser.ConfigParser()
treefarmcfg.read(os.path.join(CONFIG_DIR, "treefarmrc"))
if not treefarmcfg.has_section("treefarm"):
treefarmcfg.add_section("treefarm")<|fim_prefix|># repo: ytree-project/treefarm path: /treefarm/config.py
"""
ytree config
"""
#--------------------------... | code_fim | medium | {
"lang": "python",
"repo": "ytree-project/treefarm",
"path": "/treefarm/config.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ytree-project/treefarm path: /treefarm/config.py
"""
ytree config
"""
#-----------------------------------------------------------------------------
# Copyright (c) ytree development team. All rights reserved.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license i... | code_fim | medium | {
"lang": "python",
"repo": "ytree-project/treefarm",
"path": "/treefarm/config.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dkp-1024/my_machine_learning path: /pandas_practice/a2_basic.py
import pandas as pd
#Let's create another data frame.
data = pd.DataFrame({'group':['a', 'a', 'a', 'b','b', 'b', 'c', 'c','c'],'ounces':[4, 3, 12, 6, 7.5, 8, 3, 5, 6]})
print(data)
<|fim_suffix|># sorting by multiple columns
data.s... | code_fim | medium | {
"lang": "python",
"repo": "dkp-1024/my_machine_learning",
"path": "/pandas_practice/a2_basic.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># sorting by multiple columns
data.sort_values(by=['group','ounces'],ascending=[True,False],inplace=False)
print(data)<|fim_prefix|># repo: dkp-1024/my_machine_learning path: /pandas_practice/a2_basic.py
import pandas as pd
#Let's create another data frame.
data = pd.DataFrame({'group':['a', 'a', 'a', '... | code_fim | medium | {
"lang": "python",
"repo": "dkp-1024/my_machine_learning",
"path": "/pandas_practice/a2_basic.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># 2. Draw the 'Vertical Wall' outlines. They will go to the
# Left/Right of the 'base' outline, interlocking with it.
# 'Left' wall:
# (Flat line across the top.)
svg.write((" <path d=\"M0,%.2f h%.2f v%.2f h%.2f "
%(base_y, cell_h, cren_l, gaps_t)))
# Top-Right -> Bottom-Right.
c_sign = "... | code_fim | hard | {
"lang": "python",
"repo": "WRansohoff/grid_box_pattern_gen",
"path": "/gen_grid_box.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WRansohoff/grid_box_pattern_gen path: /gen_grid_box.py
import sys
import math
# Check that the right number of arguments were passed in.
if len(sys.argv) != 7:
print(("Usage: 'python gen_grid_box.py [W] [L] [H] [C] [R] [T]'\n"
" [W] = Interior width (x-axis) of one cell, in mm\n"
... | code_fim | hard | {
"lang": "python",
"repo": "WRansohoff/grid_box_pattern_gen",
"path": "/gen_grid_box.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Draw the 'Grid Box' pattern.
# 1. Draw the 'Base' outline, and its notches for the
# horizontal/vertical divider columns.
# Draw a path to outline the base of the box.
base_x = cell_h
base_y = (svg_h - (box_l + (cell_h)))
svg.write(" <path d=\"M%.2f,%.2f "%(base_x, base_y))
# Top-Left -> Top-Right... | code_fim | hard | {
"lang": "python",
"repo": "WRansohoff/grid_box_pattern_gen",
"path": "/gen_grid_box.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if log is not None:
log.progress_update(minibatch_num)
self._on_minibatch_end(epoch_num, minibatch_num)
if log is not None:
log.progress_end()
val_score = self._get_val_score(epoch_num)
return val_score
####################... | code_fim | hard | {
"lang": "python",
"repo": "werywjw/mBERT-FineTuning",
"path": "/mufins-project/mufins/common/model/training_process_adversarial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: werywjw/mBERT-FineTuning path: /mufins-project/mufins/common/model/training_process_adversarial.py
'''
Adversarial abstract training process class.
Like normal training process, but each epoch consists of training the model once on data set
and once on another data set, with the aim being to cre... | code_fim | hard | {
"lang": "python",
"repo": "werywjw/mBERT-FineTuning",
"path": "/mufins-project/mufins/common/model/training_process_adversarial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if log is not None:
log.progress_update(minibatch_num)
self._on_minibatch_end_disc(epoch_num, minibatch_num)
if log is not None:
log.progress_end()
self._on_discriminator_trained(epoch_num)
model.set... | code_fim | hard | {
"lang": "python",
"repo": "werywjw/mBERT-FineTuning",
"path": "/mufins-project/mufins/common/model/training_process_adversarial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simplextech/udi-poly-withings path: /nodes/withings_activity_tracker_node.py
try:
import polyinterface
except ImportError:
import pgc_interface as polyinterface
import utils
LOGGER = polyinterface.LOGGER
class WithingsActivityTrackerNode(polyinterface.Node):
def __init__(self, co... | code_fim | hard | {
"lang": "python",
"repo": "simplextech/udi-poly-withings",
"path": "/nodes/withings_activity_tracker_node.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class WithingsActivityTrackerSleepNode(polyinterface.Node):
def __init__(self, controller, primary, address, name, devices, sleep):
super(WithingsActivityTrackerSleepNode, self).__init__(controller, primary, address, name)
self.devices = devices
self.sleep = sleep
self... | code_fim | hard | {
"lang": "python",
"repo": "simplextech/udi-poly-withings",
"path": "/nodes/withings_activity_tracker_node.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>'''
Sample Input/Output:
Example 1:
Input: n = 27
Output: true
Example 2:
Input: n = 0
Output: false
'''<|fim_prefix|># repo: UG-SEP/Data-Structure-and-Algorithms path: /Leetcode/Power of Three/Power of Three.py
'''
A python program to implement Power of Three
Given an integer n, return true if it ... | code_fim | medium | {
"lang": "python",
"repo": "UG-SEP/Data-Structure-and-Algorithms",
"path": "/Leetcode/Power of Three/Power of Three.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: UG-SEP/Data-Structure-and-Algorithms path: /Leetcode/Power of Three/Power of Three.py
'''
A python program to implement Power of Three
Given an integer n, return true if it is a power of three. Otherwise, return false.
'''
class Solution:
def isPowerOfThree(self, n: int) -> bool:
<|fim_suffix... | code_fim | medium | {
"lang": "python",
"repo": "UG-SEP/Data-Structure-and-Algorithms",
"path": "/Leetcode/Power of Three/Power of Three.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>Example 1:
Input: n = 27
Output: true
Example 2:
Input: n = 0
Output: false
'''<|fim_prefix|># repo: UG-SEP/Data-Structure-and-Algorithms path: /Leetcode/Power of Three/Power of Three.py
'''
A python program to implement Power of Three
Given an integer n, return true if it is a power of three. Otherwise... | code_fim | hard | {
"lang": "python",
"repo": "UG-SEP/Data-Structure-and-Algorithms",
"path": "/Leetcode/Power of Three/Power of Three.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def initFromOwner(self, rid):
# There are four possibilities here:
#
# 1: this instance is the instance for the master component
#
# 2: this instance is an expanded instance derived directly from the
# master component
#
# 3: This instan... | code_fim | hard | {
"lang": "python",
"repo": "eventable/PyCalendar",
"path": "/src/pycalendar/icalendar/componentexpanded.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eventable/PyCalendar path: /src/pycalendar/icalendar/componentexpanded.py
##
# Copyright (c) 2007-2013 Cyrus Daboo. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... | code_fim | hard | {
"lang": "python",
"repo": "eventable/PyCalendar",
"path": "/src/pycalendar/icalendar/componentexpanded.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class VlanId(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ValueRangeConstraint(1, 4094)
wwpGenIgmpSnoopMIBObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 6141, 2, 19, 1))
wwpGenIgmpSnoop = MibIdentifier((1, 3, 6, 1, 4, 1, 6141, 2, 19, 1, 1))
wwpGenIgmpSnoopMI... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/WWP-GENERIC-IGMP-SNOOP-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> status = 'current'
subtypeSpec = Integer32.subtypeSpec + ValueRangeConstraint(1, 4094)
wwpGenIgmpSnoopMIBObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 6141, 2, 19, 1))
wwpGenIgmpSnoop = MibIdentifier((1, 3, 6, 1, 4, 1, 6141, 2, 19, 1, 1))
wwpGenIgmpSnoopMIBNotificationPrefix = MibIdentifier((1, 3, 6... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/WWP-GENERIC-IGMP-SNOOP-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp/WWP-GENERIC-IGMP-SNOOP-MIB.py
#
# PySNMP MIB module WWP-GENERIC-IGMP-SNOOP-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/WWP-GENERIC-IGMP-SNOOP-MIB
# Produced by pysmi-0.3.4 at Mon Apr 29 21:30:50 2019... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp/WWP-GENERIC-IGMP-SNOOP-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># Create pysqlite connection from APSW connection
con = sqlite3.connect(apsw_con)
result = con.execute("select times_two(15)").fetchone()[0]
assert result == 30
con.close()<|fim_prefix|># repo: oyorooms/hue path: /desktop/core/ext-py/pysqlite/doc/includes/sqlite3/apsw_example.py
from pysqlite2 import dba... | code_fim | medium | {
"lang": "python",
"repo": "oyorooms/hue",
"path": "/desktop/core/ext-py/pysqlite/doc/includes/sqlite3/apsw_example.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: oyorooms/hue path: /desktop/core/ext-py/pysqlite/doc/includes/sqlite3/apsw_example.py
from pysqlite2 import dbapi2 as sqlite3
import apsw
<|fim_suffix|># Create pysqlite connection from APSW connection
con = sqlite3.connect(apsw_con)
result = con.execute("select times_two(15)").fetchone()[0]
ass... | code_fim | medium | {
"lang": "python",
"repo": "oyorooms/hue",
"path": "/desktop/core/ext-py/pysqlite/doc/includes/sqlite3/apsw_example.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: contractshark/dispatch path: /src/dispatch/individual/models.py
from datetime import datetime
from typing import List, Optional
from sqlalchemy import Column, ForeignKey, Integer, PrimaryKeyConstraint, String, Table
from sqlalchemy.orm import relationship
from sqlalchemy_utils import TSVectorTyp... | code_fim | hard | {
"lang": "python",
"repo": "contractshark/dispatch",
"path": "/src/dispatch/individual/models.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class IndividualContactCreate(IndividualContactBase):
terms: Optional[List[TermCreate]] = []
incident_priorities: Optional[List[IncidentPriorityCreate]] = []
incident_types: Optional[List[IncidentTypeCreate]] = []
class IndividualContactUpdate(IndividualContactBase):
terms: Optional[List... | code_fim | hard | {
"lang": "python",
"repo": "contractshark/dispatch",
"path": "/src/dispatch/individual/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class IndividualContactBase(ContactBase):
weblink: Optional[str]
mobile_phone: Optional[str]
office_phone: Optional[str]
title: Optional[str]
class IndividualContactCreate(IndividualContactBase):
terms: Optional[List[TermCreate]] = []
incident_priorities: Optional[List[IncidentP... | code_fim | hard | {
"lang": "python",
"repo": "contractshark/dispatch",
"path": "/src/dispatch/individual/models.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tskkst51/lplTrade path: /PTP/multi_tasking/timer_task.py
import datetime
from typing import Optional, Any
from multi_tasking.job_server import JobServer
from multi_tasking.task import Task
from trade_interface import current_time
#
#
#
class TimerTask(Task):
#
#
#
... | code_fim | hard | {
"lang": "python",
"repo": "tskkst51/lplTrade",
"path": "/PTP/multi_tasking/timer_task.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> #
#
#
def f(self, parent: JobServer, data: Any) -> (bool, tuple, Optional[str],
Optional[datetime.datetime]):
"""Executes the job task at specific time.
Args:
parent: JobServer object.
... | code_fim | hard | {
"lang": "python",
"repo": "tskkst51/lplTrade",
"path": "/PTP/multi_tasking/timer_task.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mtn/advent16 path: /day03/part2.py
#!/usr/bin/env python3
from itertools import combinations
count = 0
with open('input.txt') as f:
for line1 in f:
line2 = f.next()
line3 = f.next()
<|fim_suffix|> for (p1, p2) in combinations(triangle, 2):
if p1 +... | code_fim | hard | {
"lang": "python",
"repo": "mtn/advent16",
"path": "/day03/part2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for (p1, p2) in combinations(triangle, 2):
if p1 + p2 <= total - (p1 + p2):
break
else:
count += 1
print(count)<|fim_prefix|># repo: mtn/advent16 path: /day03/part2.py
#!/usr/bin/env python3
from itertools import combinations
... | code_fim | hard | {
"lang": "python",
"repo": "mtn/advent16",
"path": "/day03/part2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i, _ in enumerate(line1):
triangle = [line1[i], line2[i], line3[i]]
total = sum(triangle)
for (p1, p2) in combinations(triangle, 2):
if p1 + p2 <= total - (p1 + p2):
break
else:
count += 1
pri... | code_fim | medium | {
"lang": "python",
"repo": "mtn/advent16",
"path": "/day03/part2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: slack333/Python path: /sentencia if.py
if True: #Se ejectua
print ("se cumple la condicion")
if False: #No se ejecuta
print ("se cumple la condicion")
a = 5
if a == 2: #no detecta ya que a = 5
print ("a vale 2")
if a == 5: #se cumple la funcion
print ("a vale 5")
a = 5
b = 10
... | code_fim | medium | {
"lang": "python",
"repo": "slack333/Python",
"path": "/sentencia if.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>nota = float(input("Introduce una nota: "))
if nota >= 9:
print ("Sobresaliente")
elif nota >= 7:
print ("Notable")
elif nota >= 6:
print ("Bien")
elif nota >= 5:
print ("Suficiente")
else:
print ("Insuficiente")
if True:
pass<|fim_prefix|># repo: slack333/Python path: /sentenci... | code_fim | hard | {
"lang": "python",
"repo": "slack333/Python",
"path": "/sentencia if.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: joaocarlos1994/tekton path: /backend/appengine/routes/login_rh/form.py
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from google.appengine.ext import ndb
from config.template_middleware import TemplateResponse
from gaecookie.decorator import no_csrf
from gaeperm... | code_fim | hard | {
"lang": "python",
"repo": "joaocarlos1994/tekton",
"path": "/backend/appengine/routes/login_rh/form.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@no_csrf
@login_not_required
def verifica_registro(**propriedades):
query = User.query(User.email == propriedades['email']).get()
result = query
if result.email == propriedades['email'] and result.password == propriedades['password']:
return TemplateResponse(template_path="/candidato/... | code_fim | medium | {
"lang": "python",
"repo": "joaocarlos1994/tekton",
"path": "/backend/appengine/routes/login_rh/form.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: m0re4u/machine path: /machine/models/seq2seq.py
import torch.nn.functional as F
from .baseSeqModel import BaseSeqModel
class Seq2seq(BaseSeqModel):
""" Standard sequence-to-sequence architecture with configurable encoder
and decoder.
"""
def __init__(self, encoder, decoder, de... | code_fim | hard | {
"lang": "python",
"repo": "m0re4u/machine",
"path": "/machine/models/seq2seq.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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