text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: CodeReclaimers/neat-python path: /tests/test_xor_example.py
import os
import neat
def test_xor_example_uniform_weights():
test_xor_example(uniform_weights=True)
def test_xor_example(uniform_weights=False):
# 2-input XOR inputs and expected outputs.
xor_inputs = [(0.0, 0.0), (0.0,... | code_fim | hard | {
"lang": "python",
"repo": "CodeReclaimers/neat-python",
"path": "/tests/test_xor_example.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Add a stdout reporter to show progress in the terminal.
p.add_reporter(neat.StdOutReporter(True))
stats = neat.StatisticsReporter()
p.add_reporter(stats)
checkpointer = neat.Checkpointer(25, 10, filename_prefix)
p.add_reporter(checkpointer)
# Run for up to 100 generations, a... | code_fim | hard | {
"lang": "python",
"repo": "CodeReclaimers/neat-python",
"path": "/tests/test_xor_example.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Pandinosaurus/pytorch path: /test/fx2trt/converters/acc_op/test_split.py
# Owner(s): ["oncall: fx"]
import torch
import torch.fx.experimental.fx_acc.acc_ops as acc_ops
import torch.nn as nn
from caffe2.torch.fb.fx2trt.tests.test_utils import AccTestCase
from parameterized import parameterized
... | code_fim | medium | {
"lang": "python",
"repo": "Pandinosaurus/pytorch",
"path": "/test/fx2trt/converters/acc_op/test_split.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return x.split(split_size_or_sections, dim)[0]
inputs = [torch.randn(1, 10)]
self.run_test(
Split(),
inputs,
expected_ops={
acc_ops.split
if isinstance(split_size_or_sections, int)
else acc... | code_fim | medium | {
"lang": "python",
"repo": "Pandinosaurus/pytorch",
"path": "/test/fx2trt/converters/acc_op/test_split.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> inputs = [torch.randn(1, 10)]
self.run_test(
Split(),
inputs,
expected_ops={
acc_ops.split
if isinstance(split_size_or_sections, int)
else acc_ops.slice_tensor
},
test_explicit_batch... | code_fim | hard | {
"lang": "python",
"repo": "Pandinosaurus/pytorch",
"path": "/test/fx2trt/converters/acc_op/test_split.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def hello(event, context):
r = requests.get(url=POE_URL)
body = json.loads(r.text)
matches = filter(lambda x: x["accountName"] == event["account"], body["stashes"])
count = sum(1 for _ in matches)
return "Found " + str(count) + " matches for account name " + event["account"]<|fim_p... | code_fim | hard | {
"lang": "python",
"repo": "ammarv23/poe-account-currency-scraper",
"path": "/handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>POE_URL = "http://api.pathofexile.com/public-stash-tabs"
def hello(event, context):
r = requests.get(url=POE_URL)
body = json.loads(r.text)
matches = filter(lambda x: x["accountName"] == event["account"], body["stashes"])
count = sum(1 for _ in matches)
return "Found " + str(count... | code_fim | medium | {
"lang": "python",
"repo": "ammarv23/poe-account-currency-scraper",
"path": "/handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ammarv23/poe-account-currency-scraper path: /handler.py
"""
Given an account name and a shard_id, make a request to the bulk stash tab API of Path of Exile
http://api.pathofexile.com/public-stash-tabs
<|fim_suffix|>def hello(event, context):
r = requests.get(url=POE_URL)
body = json.loa... | code_fim | hard | {
"lang": "python",
"repo": "ammarv23/poe-account-currency-scraper",
"path": "/handler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> db = r.db("logcentral")
if 'cursor_state' not in db.table_list().run():
r.db("logcentral").table_create("cursor_state").run()
if 'log' not in db.table_list().run():
r.db("logcentral").table_create("log").run()
cursor_table = r.db("logcentral").table('cursor_state')
l... | code_fim | hard | {
"lang": "python",
"repo": "teh/logcentral",
"path": "/logshipper/logshipper-daemon.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: teh/logcentral path: /logshipper/logshipper-daemon.py
#!/usr/bin/python
import rethinkdb as r
import argparse
import json
import subprocess
import socket
def yield_log_lines(cursor=None):
cursor_args = [] if cursor is None else ['--after-cursor', cursor]
p = subprocess.Popen(['journalct... | code_fim | medium | {
"lang": "python",
"repo": "teh/logcentral",
"path": "/logshipper/logshipper-daemon.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TOsborn/TrackML path: /helper_functions/.ipynb_checkpoints/file_utilities-checkpoint.py
"""Utilities for interacting with files.
These methods are specific to our team's SageMaker environment.
"""
__authors__ = ['Trenton Osborn']
def file_url(category, event_id=None, train_or_test="train"):
<|... | code_fim | medium | {
"lang": "python",
"repo": "TOsborn/TrackML",
"path": "/helper_functions/.ipynb_checkpoints/file_utilities-checkpoint.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Arguments:
category -- one of "cells", "hits", "particles", "truth", "detectors",
"sample_submission" or "hit_orders".
event_id -- the integer id of an event. Should be included unless
category is "detectors" or "sample submission". Ensure that event_id
and train_or_tes... | code_fim | medium | {
"lang": "python",
"repo": "TOsborn/TrackML",
"path": "/helper_functions/.ipynb_checkpoints/file_utilities-checkpoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return '/home/ec2-user/SageMaker/efs/{0}/event{1:09d}-{2}.csv'.format(
folder, event_id, category)<|fim_prefix|># repo: TOsborn/TrackML path: /helper_functions/.ipynb_checkpoints/file_utilities-checkpoint.py
"""Utilities for interacting with files.
These methods are specific to our team's Sa... | code_fim | hard | {
"lang": "python",
"repo": "TOsborn/TrackML",
"path": "/helper_functions/.ipynb_checkpoints/file_utilities-checkpoint.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yanaiela/num_fh path: /num_fh/identification/data/utils.py
import io
import json
import nltk
from nltk.tree import Tree
def read_data(in_f):
"""
reading the imdb (parsed) corpus
:param in_f: input file
:return: yielding a tuple of (text, show-index, scene-index and text-sentence... | code_fim | hard | {
"lang": "python",
"repo": "yanaiela/num_fh",
"path": "/num_fh/identification/data/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
find boundaries of a number
:param s: the nlp'ed sentence
:param w: the nlp'ed word (number) of the sentence
:return: start and end indices of the complete number
"""
ind = w.i
# handling height
if ind + 2 < len(s) and s[ind + 1].text == "'" and s[ind + 2].like_num:... | code_fim | hard | {
"lang": "python",
"repo": "yanaiela/num_fh",
"path": "/num_fh/identification/data/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self._i
def find_boundaries(s, w):
"""
find boundaries of a number
:param s: the nlp'ed sentence
:param w: the nlp'ed word (number) of the sentence
:return: start and end indices of the complete number
"""
ind = w.i
# handling height
if ind + 2 < len(s)... | code_fim | hard | {
"lang": "python",
"repo": "yanaiela/num_fh",
"path": "/num_fh/identification/data/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>* ")
print(" *o****o ")
print(" ***o**$** ")
print(" o*$*****o** ")
print(" **o***o**o**o ")
print(" o********o***$* ")
print(" ** ")
print(" AAA ** SsS ")
p... | code_fim | medium | {
"lang": "python",
"repo": "yamadathamine/300ideiasparaprogramarPython",
"path": "/001 Saída Simples/pinheiro2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> o********o***$* ")
print(" ** ")
print(" AAA ** SsS ")
print(" AAA****** sss ")
print(" DDDD AAA****** SsS ")<|fim_prefix|># repo: yamadathamine/300ideiasparaprogramarPython path: /001 Saída Simples/pinheiro2.py
# encodi... | code_fim | medium | {
"lang": "python",
"repo": "yamadathamine/300ideiasparaprogramarPython",
"path": "/001 Saída Simples/pinheiro2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yamadathamine/300ideiasparaprogramarPython path: /001 Saída Simples/pinheiro2.py
# encoding: utf-8
# Pinheiro 2 -Elabore uma versão 2 do programa do item anterior
# que desenhe o pinheiro com asteriscos (*).
# [Dica: use o recurso de localização/substituição do editor para fazer a substitui... | code_fim | medium | {
"lang": "python",
"repo": "yamadathamine/300ideiasparaprogramarPython",
"path": "/001 Saída Simples/pinheiro2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ardydedase/couchbasekit path: /couchbasekit/viewsync.py
#! /usr/bin/env python
"""
couchbasekit.viewsync
~~~~~~~~~~~~~~~~~~~~~
:website: http://github.com/kirpit/couchbasekit
:copyright: Copyright 2013, Roy Enjoy <kirpit *at* gmail.com>, see AUTHORS.txt.
:license: MIT, see LICENSE.txt for detail... | code_fim | hard | {
"lang": "python",
"repo": "ardydedase/couchbasekit",
"path": "/couchbasekit/viewsync.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @classmethod
def upload(cls):
"""Uploads all the local views from :attr:`VIEW_PATHS` directory
to CouchBase server
This method **over-writes** all the server-side views with the same
named ones coming from :attr:`VIEW_PATHS` folder.
"""
cls._check_f... | code_fim | hard | {
"lang": "python",
"repo": "ardydedase/couchbasekit",
"path": "/couchbasekit/viewsync.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: avikde/controlutils path: /py/kinematics.py
'''
Helpful utilities
'''
import autograd.numpy as np
from scipy.spatial.transform import Rotation
Skew2 = np.array([[0, -1], [1, 0]])
def skew(a=[0,0]):
# Skew of a vector
if len(a) == 3:
return np.array([
[0, -a[2], a[1]... | code_fim | hard | {
"lang": "python",
"repo": "avikde/controlutils",
"path": "/py/kinematics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def rot(phi, euler=False):
'''Either planar, or rotation vector for 3D'''
if len(phi) == 1:
return rot2(phi[0])
else:
if euler:
return Rotation.from_euler('xyz',phi).as_dcm()
else:
return Rotation.from_rotvec(phi).as_dcm()
def affineKinematics(q... | code_fim | medium | {
"lang": "python",
"repo": "avikde/controlutils",
"path": "/py/kinematics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''Linearization of rotation (small angle)'''
return np.eye(2) + phiz * Skew2
def rot(phi, euler=False):
'''Either planar, or rotation vector for 3D'''
if len(phi) == 1:
return rot2(phi[0])
else:
if euler:
return Rotation.from_euler('xyz',phi).as_dcm()
... | code_fim | medium | {
"lang": "python",
"repo": "avikde/controlutils",
"path": "/py/kinematics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>Mats(cat=default) \
.sent(es="En mi patio tengo animales salvajes.",
en="In my yard I have wild animals.",
zh="在我的院子里，我有野生动物。",
ja="私の庭には野生動物がいます。",
v0="Watashi no niwa ni wa yasei dōbutsu ga imasu.",
) \<|fim_prefix|># repo: samlet/stack path: /mats/... | code_fim | easy | {
"lang": "python",
"repo": "samlet/stack",
"path": "/mats/4_es/Basics.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samlet/stack path: /mats/4_es/Basics.py
from sagas.nlu.mats import Cats, Mats
<|fim_suffix|>Mats(cat=default) \
.sent(es="En mi patio tengo animales salvajes.",
en="In my yard I have wild animals.",
zh="在我的院子里，我有野生动物。",
ja="私の庭には野生動物がいます。",
v0="Watashi... | code_fim | easy | {
"lang": "python",
"repo": "samlet/stack",
"path": "/mats/4_es/Basics.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PacktPublishing/Apache-Spark-in-7-Days path: /Section 2/2.5_code_SharedVariables.py
# shared variables
# broadcast variable is read-only on the worker nodes
# broadcast example
<|fim_suffix|># example of large configuration dictionary or lookup table
config = sc.broadcast({"transformation": 1... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/Apache-Spark-in-7-Days",
"path": "/Section 2/2.5_code_SharedVariables.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># foreach is a transformation and it does not return a value, it only executes the function on each element
sc.parallelize([1, 2, 3, 4]).foreach(lambda x: accum.add(x))
accum.value<|fim_prefix|># repo: PacktPublishing/Apache-Spark-in-7-Days path: /Section 2/2.5_code_SharedVariables.py
# shared variables... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/Apache-Spark-in-7-Days",
"path": "/Section 2/2.5_code_SharedVariables.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# accumulator variable is write-only on the worker nodes
# accumulator example
accum = sc.accumulator(0)
accum
def test_accum(x):
accum.add(x)
# foreach is a transformation and it does not return a value, it only executes the function on each element
sc.parallelize([1, 2, 3, 4]).foreach(lambda x: accu... | code_fim | hard | {
"lang": "python",
"repo": "PacktPublishing/Apache-Spark-in-7-Days",
"path": "/Section 2/2.5_code_SharedVariables.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShoueneKun/Machine-Learning-driven-analysis-of-Gaze-Error path: /ML/DeepModels/models.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 7 11:57:48 2019
@author: rakshit
"""
import torch
import torch.nn.functional as F
import numpy as np
from ModelHelpers import linStack, ... | code_fim | hard | {
"lang": "python",
"repo": "ShoueneKun/Machine-Learning-driven-analysis-of-Gaze-Error",
"path": "/ML/DeepModels/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert not (torch.isnan(x).any() or torch.isinf(x).any()), "NaN or Inf found in input"
assert not (torch.isnan(target).any() or torch.isinf(target).any()), "NaN or Inf found in target"
assert not (torch.isnan(weight).any() or torch.isinf(weight).any()), "NaN or Inf found in weight"... | code_fim | hard | {
"lang": "python",
"repo": "ShoueneKun/Machine-Learning-driven-analysis-of-Gaze-Error",
"path": "/ML/DeepModels/models.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: somiyagawa/camphr path: /subpackages/camphr_core/tests/test_factories.py
from pathlib import Path
from camphr_test.utils import check_lang
import pytest
import spacy
import toml
with (Path(__file__).parent / "../pyproject.toml") as f:
conf = toml.load(f)
<|fim_suffix|>
@pytest.fixture(para... | code_fim | medium | {
"lang": "python",
"repo": "somiyagawa/camphr",
"path": "/subpackages/camphr_core/tests/test_factories.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> name = request.param
if not check_lang(name):
pytest.skip(f"{name} is required")
return name
def test_blank(lang):
spacy.blank(lang)<|fim_prefix|># repo: somiyagawa/camphr path: /subpackages/camphr_core/tests/test_factories.py
from pathlib import Path
from camphr_test.utils imp... | code_fim | medium | {
"lang": "python",
"repo": "somiyagawa/camphr",
"path": "/subpackages/camphr_core/tests/test_factories.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.fixture(params=LANGS)
def lang(request):
name = request.param
if not check_lang(name):
pytest.skip(f"{name} is required")
return name
def test_blank(lang):
spacy.blank(lang)<|fim_prefix|># repo: somiyagawa/camphr path: /subpackages/camphr_core/tests/test_factories.py
fro... | code_fim | medium | {
"lang": "python",
"repo": "somiyagawa/camphr",
"path": "/subpackages/camphr_core/tests/test_factories.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anuparna/Gaussian_Process path: /plot_data.py
from pylab import *
def plot_marker(marker_id, frames, x_coordinates, coordinate='x'):
plot(frames, x_coordinates)
xlabel('Frames')
ylabel(coordinate+'-coordinate of marker - '+marker_id)
title(coordinate+' coordinate movement of mar... | code_fim | medium | {
"lang": "python",
"repo": "anuparna/Gaussian_Process",
"path": "/plot_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def plot_marker_test(frames, x_coordinates, mse, markers, labels, markersize=1):
plot(frames, x_coordinates, markers,markersize=markersize, label=labels)
if mse is not None:
fill(np.concatenate([frames, frames[::-1]]),
np.concatenate([x_coordinates - 1.9600 * mse,
... | code_fim | hard | {
"lang": "python",
"repo": "anuparna/Gaussian_Process",
"path": "/plot_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(time.asctime(), f'Load experimental results from {exp_dir}')
exp_res = load_exp_res(exp_dir)
print(time.asctime(), 'Merge last cumulative truths')
exp_res = merge_last_cum_truth(exp_res, forecast_date)
sel_exp_res = exp_res
# transform to the cdc format per model and seed
... | code_fim | hard | {
"lang": "python",
"repo": "Frankfanwei/HierST",
"path": "/src/run_ensemble.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> raw_pred = raw_pred[(raw_pred['target'] == target) & (raw_pred['target_end_date'] == pd.to_datetime(target_end_date))]
if level == 'county':
raw_pred = raw_pred[raw_pred['location'].map(lambda x: len(x) == 5)]
else:
raw_pred = raw_pred[raw_pred['location'].map(lambda x: len(x) ... | code_fim | hard | {
"lang": "python",
"repo": "Frankfanwei/HierST",
"path": "/src/run_ensemble.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Frankfanwei/HierST path: /src/run_ensemble.py
on)
if len(task_items) == 4:
seed = int(seed.lstrip('seed'))
else:
seed = '_'.join([seed.lstrip('seed')] + task_items[4:])
if model == 'gbm':
gbm_out = pd.read_csv(os.path.join(exp_dir, task... | code_fim | hard | {
"lang": "python",
"repo": "Frankfanwei/HierST",
"path": "/src/run_ensemble.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Get the high and low bounds on AK135
AK135_innercore['rho max'] = AK135_innercore['rho']*(1+rho_sigma)
AK135_innercore['Ks max'] = AK135_innercore['Ks']*(1+Ks_sigma)
AK135_innercore['vphi max'] = AK135_innercore['vphi']*(1+vphi_sigma)
AK135_innercore['rho min'] = AK135_innercore['rho']*(1-rho_sigma)... | code_fim | hard | {
"lang": "python",
"repo": "r-a-morrison/fe_alloy_sound_velocities",
"path": "/150_HighTEOS/HighT_Compare_Fe.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: r-a-morrison/fe_alloy_sound_velocities path: /150_HighTEOS/HighT_Compare_Fe.py
# Front matter
import datetime
import pandas as pd
import numpy as np
from scipy.interpolate import interp1d
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLocator
from matplot... | code_fim | hard | {
"lang": "python",
"repo": "r-a-morrison/fe_alloy_sound_velocities",
"path": "/150_HighTEOS/HighT_Compare_Fe.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> ax1.plot(EOS_df['P'],EOS_df['Ks'],'-',
label=labelchoice[study],color=colorchoice[study],lw=1,
linestyle=linestylechoice[study])
# ax1.fill_between(EOS_df['P'], EOS_df['Ks']+17,
# EOS_df['Ks']-17, facecolor=colorchoice[study], alpha=0.3)
ax1.set_ylabel(r'$... | code_fim | hard | {
"lang": "python",
"repo": "r-a-morrison/fe_alloy_sound_velocities",
"path": "/150_HighTEOS/HighT_Compare_Fe.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> cls,
*args: typing.Union[dict, frozendict, str, date, datetime, int, float, decimal.Decimal, None, list, tuple, bytes],
_configuration: typing.Optional[schemas.Configuration] = None,
**kwargs: typing.Type[schemas.Schema],
) -> 'PropertyNamedRefThatIsNotAReference':
... | code_fim | hard | {
"lang": "python",
"repo": "InfoSec812/openapi-generator",
"path": "/samples/openapi3/client/3_0_3_unit_test/python-experimental/unit_test_api/model/property_named_ref_that_is_not_a_reference.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: InfoSec812/openapi-generator path: /samples/openapi3/client/3_0_3_unit_test/python-experimental/unit_test_api/model/property_named_ref_that_is_not_a_reference.py
# coding: utf-8
"""
openapi 3.0.3 sample spec
sample spec for testing openapi functionality, built from json schema tests for... | code_fim | hard | {
"lang": "python",
"repo": "InfoSec812/openapi-generator",
"path": "/samples/openapi3/client/3_0_3_unit_test/python-experimental/unit_test_api/model/property_named_ref_that_is_not_a_reference.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Do not edit the class manually.
"""
ref = schemas.StrSchema
locals()["$ref"] = ref
del locals()['ref']
"""
NOTE:
openapi/json-schema allows properties to have invalid python names
The above local assignment allows the code to keep those invalid python names
This all... | code_fim | medium | {
"lang": "python",
"repo": "InfoSec812/openapi-generator",
"path": "/samples/openapi3/client/3_0_3_unit_test/python-experimental/unit_test_api/model/property_named_ref_that_is_not_a_reference.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: scitao/machin path: /machin/model/nets/__init__.py
from .base import NeuralNetworkModule, dynamic_module_wrapper, static_module_wrapper
from .resnet import ResNet
<|fim_suffix|>__all__ = [
"NeuralNetworkModule",
"dynamic_module_wrapper",
"static_module_wrapper",
"ResNet",
"b... | code_fim | easy | {
"lang": "python",
"repo": "scitao/machin",
"path": "/machin/model/nets/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>__all__ = [
"NeuralNetworkModule",
"dynamic_module_wrapper",
"static_module_wrapper",
"ResNet",
"base",
"resnet",
]<|fim_prefix|># repo: scitao/machin path: /machin/model/nets/__init__.py
from .base import NeuralNetworkModule, dynamic_module_wrapper, static_module_wrapper
<|fim_m... | code_fim | medium | {
"lang": "python",
"repo": "scitao/machin",
"path": "/machin/model/nets/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fslds/fpf path: /tests/test_fpf.py
#!/usr/bin/env python
"""Tests for `fpf` filter function."""
<|fim_suffix|>def test_filter_file_paths_import_simple():
test_fnc = filter_file_paths
assert test_fnc
assert hasattr(fpf, '__call__')<|fim_middle|>from fpf import fpf, file_path_filter, ... | code_fim | hard | {
"lang": "python",
"repo": "fslds/fpf",
"path": "/tests/test_fpf.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> test_fnc = fpf
assert test_fnc
assert hasattr(fpf, '__call__')
def test_file_path_filter_import_simple():
test_fnc = file_path_filter
assert test_fnc
assert hasattr(fpf, '__call__')
def test_filter_file_paths_import_simple():
test_fnc = filter_file_paths
assert test_fnc... | code_fim | medium | {
"lang": "python",
"repo": "fslds/fpf",
"path": "/tests/test_fpf.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JayjeetAtGithub/spack path: /var/spack/repos/builtin/packages/py-pyparsing/package.py
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.pa... | code_fim | hard | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/py-pyparsing/package.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> version("3.0.9", sha256="2b020ecf7d21b687f219b71ecad3631f644a47f01403fa1d1036b0c6416d70fb")
version("3.0.6", sha256="d9bdec0013ef1eb5a84ab39a3b3868911598afa494f5faa038647101504e2b81")
version("2.4.7", sha256="c203ec8783bf771a155b207279b9bccb8dea02d8f0c9e5f8ead507bc3246ecc1")
version("2.4.2... | code_fim | medium | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/py-pyparsing/package.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> file_name = file_name if file_name is not None else f"{text}.mp3"
voice = __voice_config(voice_language, voice_gender)
return __text_to_speech(text, file_name, voice)<|fim_prefix|># repo: gthoma17/anki-assistant path: /anki_assistant/google_cloud_speech_client.py
import os
from google.cloud i... | code_fim | hard | {
"lang": "python",
"repo": "gthoma17/anki-assistant",
"path": "/anki_assistant/google_cloud_speech_client.py",
"mode": "spm",
"license": "0BSD",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gthoma17/anki-assistant path: /anki_assistant/google_cloud_speech_client.py
import os
from google.cloud import texttospeech
def __set_credentials():
creds_folder = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
creds_file = os.path.join(creds_folder, "google_creds.secret.j... | code_fim | medium | {
"lang": "python",
"repo": "gthoma17/anki-assistant",
"path": "/anki_assistant/google_cloud_speech_client.py",
"mode": "psm",
"license": "0BSD",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JiajunRen33/N-queens path: /run.py
#################################
#
# NOTE: Do not edit this file.
#
import sys
from nqueens import solve
<|fim_suffix|>with open(in_file) as f:
problems = map(int, f.readlines())
for p in problems:
print(solve(p))<|fim_middle|>if len(sys.argv) != ... | code_fim | medium | {
"lang": "python",
"repo": "JiajunRen33/N-queens",
"path": "/run.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>problems = []
with open(in_file) as f:
problems = map(int, f.readlines())
for p in problems:
print(solve(p))<|fim_prefix|># repo: JiajunRen33/N-queens path: /run.py
#################################
#
# NOTE: Do not edit this file.
#
<|fim_middle|>import sys
from nqueens import solve
if le... | code_fim | medium | {
"lang": "python",
"repo": "JiajunRen33/N-queens",
"path": "/run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='ticketcategory',
name='allowed_users',
field=models.ManyToManyField(to=settings.AUTH_USER_MODEL),
),
]<|fim_prefix|># repo: claudiobat/uniTicket path: /uni_ticket/migrations/0129_ticketcategory_all... | code_fim | medium | {
"lang": "python",
"repo": "claudiobat/uniTicket",
"path": "/uni_ticket/migrations/0129_ticketcategory_allowed_users.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: claudiobat/uniTicket path: /uni_ticket/migrations/0129_ticketcategory_allowed_users.py
# Generated by Django 3.0.7 on 2020-06-23 07:01
from django.conf import settings
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
migrations.swappable_dependency(settings.A... | code_fim | medium | {
"lang": "python",
"repo": "claudiobat/uniTicket",
"path": "/uni_ticket/migrations/0129_ticketcategory_allowed_users.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paulhtremblay/big-data path: /big_data/python_tools/big_data_tools/bokeh_tools/make_graph_instance.py
from bokeh.plotting import figure
def make_p(widt<|fim_suffix|>ght=height, x_axis_type=x_axis_type, title=title)<|fim_middle|>h = 400, height = 400, x_axis_type = None, title=""):
return figu... | code_fim | medium | {
"lang": "python",
"repo": "paulhtremblay/big-data",
"path": "/big_data/python_tools/big_data_tools/bokeh_tools/make_graph_instance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ght=height, x_axis_type=x_axis_type, title=title)<|fim_prefix|># repo: paulhtremblay/big-data path: /big_data/python_tools/big_data_tools/bokeh_tools/make_graph_instance.py
from bokeh.plotting import figure
def make_p(widt<|fim_middle|>h = 400, height = 400, x_axis_type = None, title=""):
return figu... | code_fim | medium | {
"lang": "python",
"repo": "paulhtremblay/big-data",
"path": "/big_data/python_tools/big_data_tools/bokeh_tools/make_graph_instance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andreylrr/HHAnalyticsDjango path: /hhmain/admin.py
from django.contrib import admin
from .models import Contacts
<|fim_suffix|> list_display = ('id','name', 'email', 'content')<|fim_middle|># Register your models here.
@admin.register(Contacts)
class ContactsAdmin(admin.ModelAdmin):
| code_fim | medium | {
"lang": "python",
"repo": "andreylrr/HHAnalyticsDjango",
"path": "/hhmain/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_display = ('id','name', 'email', 'content')<|fim_prefix|># repo: andreylrr/HHAnalyticsDjango path: /hhmain/admin.py
from django.contrib import admin
from .models import Contacts
<|fim_middle|># Register your models here.
@admin.register(Contacts)
class ContactsAdmin(admin.ModelAdmin):
| code_fim | medium | {
"lang": "python",
"repo": "andreylrr/HHAnalyticsDjango",
"path": "/hhmain/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Kozea/WeasyPrint path: /weasyprint/formatting_structure/boxes.py
t.element_tag, style, parent.element, *args, **kwargs)
def copy(self):
"""Return shallow copy of the box."""
cls = type(self)
# Create a new instance without calling __init__: parameters are
# di... | code_fim | hard | {
"lang": "python",
"repo": "Kozea/WeasyPrint",
"path": "/weasyprint/formatting_structure/boxes.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Kozea/WeasyPrint path: /weasyprint/formatting_structure/boxes.py
io, brry * ratio),
(blrx * ratio, blry * ratio))
def rounded_box_ratio(self, ratio):
return self.rounded_box(
self.border_top_width * ratio,
self.border_right_width * ratio,
... | code_fim | hard | {
"lang": "python",
"repo": "Kozea/WeasyPrint",
"path": "/weasyprint/formatting_structure/boxes.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.children:
return len(self.children)
else:
try:
return max(int(self.element.get('span', '').strip()), 1)
except ValueError:
return 1
# Not really a parent box, but pretending to be removes some corner cases.
class... | code_fim | hard | {
"lang": "python",
"repo": "Kozea/WeasyPrint",
"path": "/weasyprint/formatting_structure/boxes.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
ax = plt.gca()
plt.scatter(X,Y,s=5, lw=0, alpha=0.8)
ax.set_xscale('log')
ax.set_yscale('log')
plt.xlabel('|V|+|E|')
plt.ylabel('Time')
#plt.ylim(1.0,3.0)
#plt.xlim(1.0,1000.0)
plt.savefig(filename, format='eps', dpi=1000)
# plt.show()
def main(argv):
X, Y =... | code_fim | hard | {
"lang": "python",
"repo": "ShoYamanishi/wailea",
"path": "/jgaa/plot_performance.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ShoYamanishi/wailea path: /jgaa/plot_performance.py
import sys
import fileinput
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
<|fim_suffix|>
def draw(X, Y, filename):
ax = plt.gca()
plt.scatter(X,Y,s=5, lw=0, alpha=0.8)
... | code_fim | hard | {
"lang": "python",
"repo": "ShoYamanishi/wailea",
"path": "/jgaa/plot_performance.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>elist=os.listdir('C:\Users\Gianmarco\Desktop\obj')
#for file in filelist[:]: # filelist[:] makes a copy of filelist.
im = Image.open('tiger.jpg')
im = add_corners(im, 50)
im.save('tiger.png')<|fim_prefix|># repo: Bshowg/MemoryCardGame path: /Client/Assets/Sprites/round.py
import Image, ImageDraw
imp... | code_fim | hard | {
"lang": "python",
"repo": "Bshowg/MemoryCardGame",
"path": "/Client/Assets/Sprites/round.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>))
alpha.paste(circle.crop((rad, 0, rad * 2, rad)), (w - rad, 0))
alpha.paste(circle.crop((rad, rad, rad * 2, rad * 2)), (w - rad, h - rad))
im.putalpha(alpha)
return im
#filelist=os.listdir('C:\Users\Gianmarco\Desktop\obj')
#for file in filelist[:]: # filelist[:] makes a copy of fil... | code_fim | medium | {
"lang": "python",
"repo": "Bshowg/MemoryCardGame",
"path": "/Client/Assets/Sprites/round.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Bshowg/MemoryCardGame path: /Client/Assets/Sprites/round.py
import Image, ImageDraw
import os
def add_corners(im, rad):
circle = Image.new('L', (rad * 2, rad * 2), 0)
draw = ImageDraw.Draw(circle)
draw.ellipse((0, 0, rad * 2, rad * 2)<|fim_suffix|>elist=os.listdir('C:\Users\G... | code_fim | hard | {
"lang": "python",
"repo": "Bshowg/MemoryCardGame",
"path": "/Client/Assets/Sprites/round.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/ref/settings/
"""
# import install-specific settings from a separate file
# that is easy to replace as part of the deployment process
from SiteMain.settings_base import * # noqa
# end of file<|fim_p... | code_fim | medium | {
"lang": "python",
"repo": "RamonvdW/nhb-apps",
"path": "/SiteMain/settings.py",
"mode": "spm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RamonvdW/nhb-apps path: /SiteMain/settings.py
# -*- coding: utf-8 -*-
# Copyright (c) 2019-2023 Ramon van der Winkel.
# All rights reserved.
# Licensed under BSD-3-Clause-Clear. See LICENSE file for details.
<|fim_suffix|># import install-specific settings from a separate file
# that is easy... | code_fim | hard | {
"lang": "python",
"repo": "RamonvdW/nhb-apps",
"path": "/SiteMain/settings.py",
"mode": "psm",
"license": "BSD-3-Clause-Clear",
"source": "the-stack-v2"
} |
<|fim_suffix|> raise NotImplementedError("This is an Interface class")
class Polygon(Obstacle):
def __init__(self):
super().__init__(ObstacleType.POLYGON)
self.points = [] # expected [(x0, y0), (x1, y1), ...]
def to_qobject(self, x_offset, y_offset, width, height, inflate_radius=None):... | code_fim | hard | {
"lang": "python",
"repo": "ENACRobotique/pygargue",
"path": "/obstacle.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ENACRobotique/pygargue path: /obstacle.py
from enum import Enum
import pyclipper
from PyQt5.QtCore import QPointF, QRectF
from PyQt5.QtGui import QPolygonF
TABLE_WIDTH = 3000 # obstacles coordinates will usually be 0<= x <= TABLE_WIDTH
TABLE_HEIGHT = 2000 # obstacles coordinates will usually ... | code_fim | hard | {
"lang": "python",
"repo": "ENACRobotique/pygargue",
"path": "/obstacle.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GaoJiah/slippy path: /slippy/core/abcs.py
"""
Minimal abstract base classes please don't add any code to these, they are strictly to avoid circular imports,
this module should be as minimal as possible as it will be imported every time any sub package is imported
"""
import abc
__all__ = ['_Sur... | code_fim | hard | {
"lang": "python",
"repo": "GaoJiah/slippy",
"path": "/slippy/core/abcs.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @abc.abstractmethod
def dimensionalise_gap(self, nd_gap, un_dimensionalise: bool = False):
pass
@abc.abstractmethod
def dimensionalise_length(self, nd_length, un_dimensionalise: bool = False):
pass
class _SubModelABC(abc.ABC):
name: str
requires: set
provides... | code_fim | hard | {
"lang": "python",
"repo": "GaoJiah/slippy",
"path": "/slippy/core/abcs.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def merge(
self, streams: Dict[str, Generator[None, None, None]]
) -> Generator[None, None, None]:
"""Merge multiple streams in one stream_data.
Args:
streams: mapping of streams (generators)
"""
buffer_dtype_init_values = self.buffer_dtype_ini... | code_fim | hard | {
"lang": "python",
"repo": "zggl/wax-ml",
"path": "/wax/stream.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zggl/wax-ml path: /wax/stream.py
e(verbose, time_dim):
if isinstance(verbose, bool):
return verbose
if isinstance(verbose, (list, tuple)):
if time_dim in verbose:
return True
return False
class GeneratorState(NamedTuple):
output_values: Any
strea... | code_fim | hard | {
"lang": "python",
"repo": "zggl/wax-ml",
"path": "/wax/stream.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zggl/wax-ml path: /wax/stream.py
ype is onp.datetime64
}
assert len(time_coords) == 1
return time_coords.pop()
def get_dataset_time_coords(dataset):
time_coords = {
dim for dim, vals in dataset.coords.items() if vals.dtype.type is onp.datetime64
}
assert len(time... | code_fim | hard | {
"lang": "python",
"repo": "zggl/wax-ml",
"path": "/wax/stream.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert(len(array) == len(helper_array))
if start < end:
middle = (end - start) // 2 + start
if start < middle:
sort_helper(array, helper_array, start, middle)
if (middle + 1) < end:
sort_helper(array, helper_array, middle + 1, end)
merge_help... | code_fim | medium | {
"lang": "python",
"repo": "isayapin/cracking-the-coding-interview",
"path": "/python_solutions/chapter_10_sorting_and_searching/merge_sort.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: isayapin/cracking-the-coding-interview path: /python_solutions/chapter_10_sorting_and_searching/merge_sort.py
import copy
def merge_helper(array, helper_array, start, middle, end):
assert(len(array) == len(helper_array))
left_idx = start
right_idx = middle + 1
helper_idx = start... | code_fim | medium | {
"lang": "python",
"repo": "isayapin/cracking-the-coding-interview",
"path": "/python_solutions/chapter_10_sorting_and_searching/merge_sort.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def xpath_findall(xpath, xml_content):
"""
Search xml by xpath
Returns:
List of Element [Element...]
"""
if LXML:
# print(xml_content)
root = etree.fromstring(xml_content.encode('utf-8'))
for node in root.xpath("//node"):
node.tag = safe_xm... | code_fim | medium | {
"lang": "python",
"repo": "xxhdxh/uiautomator2",
"path": "/uiautomator2/simplexml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
List of Element [Element...]
"""
if LXML:
# print(xml_content)
root = etree.fromstring(xml_content.encode('utf-8'))
for node in root.xpath("//node"):
node.tag = safe_xmlstr(node.attrib.pop("class"))
return root.xpath(
xpa... | code_fim | medium | {
"lang": "python",
"repo": "xxhdxh/uiautomator2",
"path": "/uiautomator2/simplexml.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xxhdxh/uiautomator2 path: /uiautomator2/simplexml.py
# coding: utf-8
#
try:
from lxml import etree
LXML = True
except:
import xml.etree.ElementTree as ET
LXML = False
def safe_xmlstr(s):
<|fim_suffix|>def xpath_findall(xpath, xml_content):
"""
Search xml by xpath
R... | code_fim | medium | {
"lang": "python",
"repo": "xxhdxh/uiautomator2",
"path": "/uiautomator2/simplexml.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def run(self):
self.get_filenames()
fnames = self.get_filenames()
df = self.load_multiple_files_to_df(fnames)
self.store_as_pickle(df)
return True<|fim_prefix|># repo: morganpare/ecx_analytics path: /ecx_analytics/data_processor/raw_to_bronze.py
import pandas a... | code_fim | hard | {
"lang": "python",
"repo": "morganpare/ecx_analytics",
"path": "/ecx_analytics/data_processor/raw_to_bronze.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def store_as_pickle(self, df, filename='ecx_bronze.pkl'):
file_path = pathlib.Path.joinpath(self.bronze_path, filename)
df.to_pickle(file_path)
def get_filenames(self):
file_list = os.listdir(self.raw_path)
return file_list
def run(self):
self.get_file... | code_fim | hard | {
"lang": "python",
"repo": "morganpare/ecx_analytics",
"path": "/ecx_analytics/data_processor/raw_to_bronze.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: morganpare/ecx_analytics path: /ecx_analytics/data_processor/raw_to_bronze.py
import pandas as pd
import pathlib
import os
class RawToBronze:
def __init__(self, data_path):
self.data_path = data_path
try:
self.raw_path = pathlib.Path.joinpath(self.data_path, "raw"... | code_fim | medium | {
"lang": "python",
"repo": "morganpare/ecx_analytics",
"path": "/ecx_analytics/data_processor/raw_to_bronze.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def split_data(num_samples, num_splits):
""" Yields a split of data into train and test indices.
"""
kf = sklearn.model_selection.KFold(n_splits=num_splits, random_state=0);
return kf.split(range(num_samples))
def make_bar_plot(x, y, title):
""" Makes a bar chart with a title.
"... | code_fim | hard | {
"lang": "python",
"repo": "andy-sweet/planet-amazon",
"path": "/planet/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Resizes 2D image to new 2D size over all channels.
"""
return skimage.transform.resize(image, size, mode='reflect', preserve_range=True).astype(image.dtype)
def resize_images(images, size):
""" Resizes 2D images to new 2D size over all channels.
"""
num_images = images.shape[... | code_fim | hard | {
"lang": "python",
"repo": "andy-sweet/planet-amazon",
"path": "/planet/util.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andy-sweet/planet-amazon path: /planet/util.py
""" Some utility functions for loading and exploring the data.
Nomenclature
------------
tag : The name of a label to predict. E.g. "haze".
label : The non-negative integer value associated with a tag. E.g. 3.
sample : The name associated with a sam... | code_fim | hard | {
"lang": "python",
"repo": "andy-sweet/planet-amazon",
"path": "/planet/util.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NunoXu/UnbabelChallenge2016 path: /Feature/NGramFeature/ProbabilityFeature.py
import kenlm
import numpy
import math
from .NGramFeature import NGramFeature
class Probability(NGramFeature):
<|fim_suffix|> super(Probability, self).__init__(model_path)
def evaluate(self, sentence):
... | code_fim | easy | {
"lang": "python",
"repo": "NunoXu/UnbabelChallenge2016",
"path": "/Feature/NGramFeature/ProbabilityFeature.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> super(Probability, self).__init__(model_path)
def evaluate(self, sentence):
return math.pow(10, self._model.score(sentence))<|fim_prefix|># repo: NunoXu/UnbabelChallenge2016 path: /Feature/NGramFeature/ProbabilityFeature.py
import kenlm
import numpy
import math
from .NGramFeature imp... | code_fim | medium | {
"lang": "python",
"repo": "NunoXu/UnbabelChallenge2016",
"path": "/Feature/NGramFeature/ProbabilityFeature.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shinenazeer/automating_excel_with_python path: /07_chart_types/area_chart_3d.py
# area_chart_3d.py
from openpyxl import Workbook
from openpyxl.chart import AreaChart3D, Reference
def main(filename):
<|fim_suffix|> cats = Reference(sheet, min_col=1, min_row=1, max_row=7)
data = Reference(... | code_fim | hard | {
"lang": "python",
"repo": "shinenazeer/automating_excel_with_python",
"path": "/07_chart_types/area_chart_3d.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> sheet.add_chart(chart, "E2")
wb.save(filename)
if __name__ == "__main__":
main("area_chart_3d.xlsx")<|fim_prefix|># repo: shinenazeer/automating_excel_with_python path: /07_chart_types/area_chart_3d.py
# area_chart_3d.py
from openpyxl import Workbook
from openpyxl.chart import AreaChart3D,... | code_fim | hard | {
"lang": "python",
"repo": "shinenazeer/automating_excel_with_python",
"path": "/07_chart_types/area_chart_3d.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gwli/pyESN path: /Lorenz.py
import numpy as np
def lorenz(dt,sigma=10.0,beta=2.66667,ro=28.):
def l(x,y,z):
xn = y*dt*sigma + x*(1 - dt*sigma)
yn = x*dt*(ro-z) + y*(1-dt)
zn = x*y*dt + z*(1 - dt*beta)
return (xn,yn,zn)
return l
<|fim_suffix|>def plot(trajectory):
fig = plt.figure()
a... | code_fim | hard | {
"lang": "python",
"repo": "gwli/pyESN",
"path": "/Lorenz.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_suffix|>frequency_control = (frequency_control- frequency_control.min())/(frequency_control.max()-frequency_control.min())
frequency_output = (frequency_output- frequency_output.min())/(frequency_output.max()-frequency_output.min())<|fim_prefix|># repo: gwli/pyESN path: /Lorenz.py
import numpy as np
def lorenz(d... | code_fim | hard | {
"lang": "python",
"repo": "gwli/pyESN",
"path": "/Lorenz.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lukasHD/adventOfCode2020 path: /day20/test_yield.py
def rotflip():
yield "rot1"
yield "rot2"
yield "rot3"
yield "rot4"
<|fim_suffix|>ile True:
a = a_gen.__next__()
print(a)
i += 1
if i == 6:
break<|fim_middle|> yield "flip"
yield "rot1"
yield "ro... | code_fim | medium | {
"lang": "python",
"repo": "lukasHD/adventOfCode2020",
"path": "/day20/test_yield.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>aise ValueError("aaaaa")
i = 0
#for i,a in enumerate(rotflip()):
a_gen = rotflip()
while True:
a = a_gen.__next__()
print(a)
i += 1
if i == 6:
break<|fim_prefix|># repo: lukasHD/adventOfCode2020 path: /day20/test_yield.py
def rotflip():
yield "rot1"
yield "rot2"
yield... | code_fim | medium | {
"lang": "python",
"repo": "lukasHD/adventOfCode2020",
"path": "/day20/test_yield.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tfinnm/HotWired-Bot path: /cogs/urbandict_utils/urbandictpages.py
import re
import typing as t
import discord
from discord.ext.commands import Context
from cogs.utils.paginator import Pages
class UrbanDictionaryPages(Pages):
BRACKETED = re.compile(r"(\[(.+?)\])")
def __init__(self, c... | code_fim | hard | {
"lang": "python",
"repo": "tfinnm/HotWired-Bot",
"path": "/cogs/urbandict_utils/urbandictpages.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Prepare embeds for the paginator."""
if self.maximum_pages > 1:
title = f'{entry["word"]}: {page} out of {self.maximum_pages}'
else:
title = entry["word"]
self.embed = e = discord.Embed(colour=0xE86222, title=title, url=entry["permalink"])
... | code_fim | hard | {
"lang": "python",
"repo": "tfinnm/HotWired-Bot",
"path": "/cogs/urbandict_utils/urbandictpages.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tongxindao/shiyanlou path: /shiyanlou_cs642-966a5463b4/ibot.py
# _*_ coding: utf-8 _*_
# six
# 导入模块
from distutils.log import warn as printf
import sys
from bosonnlp import BosonNLP
from os.path import expanduser
import os
import collections
import subprocess
import datetime
# 配置 API 密钥
bosonnl... | code_fim | hard | {
"lang": "python",
"repo": "tongxindao/shiyanlou",
"path": "/shiyanlou_cs642-966a5463b4/ibot.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
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