text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: home-assistant/core path: /tests/components/mqtt/test_select.py
ntry: MqttMockHAClientGenerator
) -> None:
"""Test that it fetches the given payload with a template."""
await mqtt_mock_entry()
async_fire_mqtt_message(hass, "test/select_stat", '{"val":"milk"}')
await hass.async_b... | code_fim | hard | {
"lang": "python",
"repo": "home-assistant/core",
"path": "/tests/components/mqtt/test_select.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kwasnydam/coding_challanges path: /coursera/array_inversions_count/test_array_inversion_count.py
import unittest
import array_inversions_count
class TestCountInversions(unittest.TestCase):
def setUp(self):
self.object_under_test = array_inversions_count.count_inversions
... | code_fim | medium | {
"lang": "python",
"repo": "kwasnydam/coding_challanges",
"path": "/coursera/array_inversions_count/test_array_inversion_count.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> test_data = [1]
expected_value = 0
self._test_inversions_count(test_data, expected_value)
def test_should_return_15_on_654321_input(self):
test_data = [6, 5, 4, 3, 2, 1]
expected_value = 15
self._test_inversions_count(test_data, expected_value)
... | code_fim | hard | {
"lang": "python",
"repo": "kwasnydam/coding_challanges",
"path": "/coursera/array_inversions_count/test_array_inversion_count.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_should_return_0_on_1_element_input(self):
test_data = [1]
expected_value = 0
self._test_inversions_count(test_data, expected_value)
def test_should_return_15_on_654321_input(self):
test_data = [6, 5, 4, 3, 2, 1]
expected_value = 15
... | code_fim | hard | {
"lang": "python",
"repo": "kwasnydam/coding_challanges",
"path": "/coursera/array_inversions_count/test_array_inversion_count.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def train(self, data, labels, C, scale=True, weights = True,
mem_size=512):
'''
Train the ELM Classifier
-----------------------
Input:
------
data - (numpy array) - shape n x p
n - number of observatio... | code_fim | hard | {
"lang": "python",
"repo": "neurophysics/meet",
"path": "/meet/elm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: neurophysics/meet path: /meet/elm.py
tives and negatives and is
generally regarded as a balanced measure which can be used even if
the classes are of very different sizes. The MCC is in essence a
correlation coefficient between the observed and predicted binary
classifications; it... | code_fim | hard | {
"lang": "python",
"repo": "neurophysics/meet",
"path": "/meet/elm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: neurophysics/meet path: /meet/elm.py
(TP + FP)/float(N)
try: MCC = (TP/float(N) - S*P) / _np.sqrt(S*P*(1 - S)*(1 - P))
except: MCC = 0
return MCC
def PPV2DR1(conf_matrix):
"""
Calculate the weighted average (WA) of Positive Preditive Value (PPV)
and Detection Rate (DR):
... | code_fim | hard | {
"lang": "python",
"repo": "neurophysics/meet",
"path": "/meet/elm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(response.status_code, 201) # Created
self.assertEqual(Measurement.objects.count(), 1)
self.assertEqual(Alarm.objects.count(), 1)
data = {
"Measurements": [
{
"date": measurement_time + 500,
... | code_fim | hard | {
"lang": "python",
"repo": "sigurdsa/angelika-api",
"path": "/measurement/tests.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sigurdsa/angelika-api path: /measurement/tests.py
from test.testcase import AngelikaAPITestCase
from patient.models import Patient
from measurement.models import Measurement
from threshold_value.models import ThresholdValue
from alarm.models import Alarm
import time
class PostMeasurementTests(A... | code_fim | hard | {
"lang": "python",
"repo": "sigurdsa/angelika-api",
"path": "/measurement/tests.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def create_observation(self, loc):
cur = {}
cur['poses'] = []
cur['poses_in_arm'] = []
cur['last_seen'] = []
cur['labels'] = []
cur['counter'] = 0
cur['type'] = []
cur['blacklisted'] = False
self.objects_at_location[loc].append(cu... | code_fim | hard | {
"lang": "python",
"repo": "smARTLab-liv/smartlabatwork-release",
"path": "/slaw_manipulation/src/object_manager.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: smARTLab-liv/smartlabatwork-release path: /slaw_manipulation/src/object_manager.py
aw_srvs.srv import SwitchOnForLocation, SwitchOnForLocationResponse, GetObjectAtLocation, \
GetObjectAtLocationResponse, RemoveObjectAtLocation, RemoveObjectAtLocationResponse
from collections import Counter
M... | code_fim | hard | {
"lang": "python",
"repo": "smARTLab-liv/smartlabatwork-release",
"path": "/slaw_manipulation/src/object_manager.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: smARTLab-liv/smartlabatwork-release path: /slaw_manipulation/src/object_manager.py
= 1.
BETTER_COLOR = ['M20_h', 'RV20_h']
merged_map = {'RV20': ['RV20_v', 'RV20_h'],
'F20_20': ['F20_20_v'],
'S40_40': ['S40_40_v']
}
objects_map = {'R20': ['RV20_h', 'RV20_v'],
... | code_fim | hard | {
"lang": "python",
"repo": "smARTLab-liv/smartlabatwork-release",
"path": "/slaw_manipulation/src/object_manager.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert actual == expected<|fim_prefix|># repo: bmoretz/Daily-Coding-Problem path: /py/tests/leetcode/arr_tests/find_pivot_test.py
import unittest
from dcp.leetcode.arr import find_pivot
<|fim_middle|>class Test_FindPivot(unittest.TestCase):
def setUp(self):
pass
def test_c... | code_fim | medium | {
"lang": "python",
"repo": "bmoretz/Daily-Coding-Problem",
"path": "/py/tests/leetcode/arr_tests/find_pivot_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bmoretz/Daily-Coding-Problem path: /py/tests/leetcode/arr_tests/find_pivot_test.py
import unittest
from dcp.leetcode.arr import find_pivot
class Test_FindPivot(unittest.TestCase):
def setUp(self):
pass
<|fim_suffix|> assert actual == expected<|fim_middle|> def test_c... | code_fim | medium | {
"lang": "python",
"repo": "bmoretz/Daily-Coding-Problem",
"path": "/py/tests/leetcode/arr_tests/find_pivot_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> train_order = list(range(len(instance_triple)))
save_epoch = FLAGS.save_epoch
if FLAGS.restore_epoch > 0:
saver.restore(sess, FLAGS.model_dir + FLAGS.model + "-" + str(1832 * FLAGS.restore_epoch))
print('restored model from epoch {}'.format(FLAGS.restore_epoch))
for one_... | code_fim | hard | {
"lang": "python",
"repo": "YangLi1221/CoRA",
"path": "/script/train.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YangLi1221/CoRA path: /script/train.py
import tensorflow as tf
import numpy as np
import datetime, os, sys, json, pickle
from model.model_CoRA import CoRA
config = json.loads(open("./data/config", 'r').read())
FLAGS = tf.app.flags.FLAGS
# overall
tf.app.flags.DEFINE_string('model', 'CoRA', 'n... | code_fim | hard | {
"lang": "python",
"repo": "YangLi1221/CoRA",
"path": "/script/train.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OCR-D/ocrd_tesserocr path: /test/test_cli.py
from click.testing import CliRunner
from test.base import main
from pathlib import Path
runner = CliRunner()
def test_show_resource(tmpdir, monkeypatch):
<|fim_suffix|>def test_list_all_resources(tmpdir, monkeypatch):
samplefile = Path(tmpdir, '... | code_fim | hard | {
"lang": "python",
"repo": "OCR-D/ocrd_tesserocr",
"path": "/test/test_cli.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_list_all_resources(tmpdir, monkeypatch):
samplefile = Path(tmpdir, 'foo.traineddata')
samplefile.write_text('foo')
# simulate a Tesseract compiled with custom tessdata dir
monkeypatch.setenv('TESSDATA_PREFIX', str(tmpdir))
# envvars influence tesserocr's module initialization
... | code_fim | hard | {
"lang": "python",
"repo": "OCR-D/ocrd_tesserocr",
"path": "/test/test_cli.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Read all pins again
await websocket.send(json.dumps(READ_ALL))
print(f"Sent > {READ_ALL}")
response = await websocket.recv()
print(f"Received < {response}")
# Parse JSON response
data = json.loads(response)
p... | code_fim | hard | {
"lang": "python",
"repo": "logimic/iqrfboard",
"path": "/examples/digital-input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: logimic/iqrfboard path: /examples/digital-input.py
#
# Copyright Logimic,s.r.o., www.logimic.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apa... | code_fim | hard | {
"lang": "python",
"repo": "logimic/iqrfboard",
"path": "/examples/digital-input.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Wait 2 sec
time.sleep(3)
# Read all pins again
await websocket.send(json.dumps(READ_ALL))
print(f"Sent > {READ_ALL}")
response = await websocket.recv()
print(f"Received < {response}")
# Parse JSON ... | code_fim | hard | {
"lang": "python",
"repo": "logimic/iqrfboard",
"path": "/examples/digital-input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> match.solve()
match.reviewers[0].matching.append(Player(name="foo", pref_names=[]))
with pytest.raises(Exception):
match._check_reviewer_matching()
@HOSPITAL_RESIDENT
def test_reviewer_capacity(resident_names, hospital_names, capacities, seed):
""" Test that HospitalResident rec... | code_fim | hard | {
"lang": "python",
"repo": "Nikoleta-v3/matching",
"path": "/tests/hospital_resident/test_solver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Nikoleta-v3/matching path: /tests/hospital_resident/test_solver.py
""" Unit tests for the HR solver. """
import numpy as np
import pytest
from matching import HospitalResident, Matching, Player
from .params import HOSPITAL_RESIDENT, _make_match
@HOSPITAL_RESIDENT
def test_init(resident_names... | code_fim | hard | {
"lang": "python",
"repo": "Nikoleta-v3/matching",
"path": "/tests/hospital_resident/test_solver.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hussainmustafa2190/Karl path: /features/bot1.py
import pandas as pd
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.decomposition import TruncatedSVD
from sklearn.neighbors import BallTree
from sklearn.base import BaseEstimator
from sklearn.pipeli... | code_fim | hard | {
"lang": "python",
"repo": "hussainmustafa2190/Karl",
"path": "/features/bot1.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.tree_ = BallTree(X)
self.y_ = np.array(y)
def predict(self, X, random_state = None):
distances, indeces = self.tree_.query(X, return_distance = True, k = self.k)
result = []
for distance, index in zip(distances, indeces):
result.... | code_fim | hard | {
"lang": "python",
"repo": "hussainmustafa2190/Karl",
"path": "/features/bot1.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> def parse(self, conf):
"""
Parse the BOUNDARIES section of the config into the bcs list.
Args:
conf (configparser section or dict):
The full BOUNDARIES section from the config.
"""
boundaries = process_args(conf,
... | code_fim | hard | {
"lang": "python",
"repo": "AndrewLister-STFC/TTiP",
"path": "/TTiP/parsers/boundary_conds_parser.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AndrewLister-STFC/TTiP path: /TTiP/parsers/boundary_conds_parser.py
"""
This contains the parser for parsing the BOUNDARIES section of the config.
"""
from TTiP.parsers.parse_args import process_args
from TTiP.parsers.parser import FunctionSectionParser
class BoundaryCondsParser(FunctionSection... | code_fim | hard | {
"lang": "python",
"repo": "AndrewLister-STFC/TTiP",
"path": "/TTiP/parsers/boundary_conds_parser.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: lung21/caliper-min path: /benchmark/custom/fabric_log_script/process_occ-standard_orderer.py
import sys
import math
def main():
if len(sys.argv) < 2:
print "python process_occ-standard_orderer.py <order/log/path>"
return 1
total_schedule_count = 0
total_drop_count = ... | code_fim | hard | {
"lang": "python",
"repo": "lung21/caliper-min",
"path": "/benchmark/custom/fabric_log_script/process_occ-standard_orderer.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> total_drop_count = middle_drop_count + rw_drop_count + anti_drop_count + cww_drop_count
print "total # of scheduled txns: \t", total_schedule_count
print "total # of dropped txns: \t", total_drop_count
print "\t# of dropped txns due to cww: \t", cww_drop_count
print "\t# of dropped txn... | code_fim | hard | {
"lang": "python",
"repo": "lung21/caliper-min",
"path": "/benchmark/custom/fabric_log_script/process_occ-standard_orderer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> parser = get_parser(
description=(
'initialises an aiida environment via yaml config file')
)
parser.add_argument('--version', action='version', version=__version__)
parser.add_argument("filepath", type=str, nargs='?',
help="path to config file",... | code_fim | hard | {
"lang": "python",
"repo": "ezpzbz/activate_aiida",
"path": "/activate_aiida/parse_args.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return CustomParser(
formatter_class=CustomFormatter,
**kwargs
)
def run(sys_args=None):
if sys_args is None:
sys_args = sys.argv[1:]
parser = get_parser(
description=(
'initialises an aiida environment via yaml config file')
)
parser... | code_fim | hard | {
"lang": "python",
"repo": "ezpzbz/activate_aiida",
"path": "/activate_aiida/parse_args.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ezpzbz/activate_aiida path: /activate_aiida/parse_args.py
import argparse
import sys
from activate_aiida import __version__
class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter,
argparse.RawDescriptionHelpFormatter,
):
pass
class Custom... | code_fim | hard | {
"lang": "python",
"repo": "ezpzbz/activate_aiida",
"path": "/activate_aiida/parse_args.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert len(patch.get_atomics('LineReplacement')) == 2
assert len(patch.get_atomics('LineInsertion')) == 1
atomics = patch.get_atomics()
count = 0
for edit in patch.edit_list:
for atomic in edit.atomic_operators:
assert atomic in ... | code_fim | hard | {
"lang": "python",
"repo": "yrko1/CS454",
"path": "/pyggi_hj/test/test_patch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yrko1/CS454 path: /pyggi_hj/test/test_patch.py
import pytest
from pyggi import Program, Patch, GranularityLevel
from pyggi.custom_operator import LineDeletion, LineMoving
@pytest.fixture(scope='session')
def setup():
program = Program('./resource/Triangle_bug', GranularityLevel.LINE)
as... | code_fim | hard | {
"lang": "python",
"repo": "yrko1/CS454",
"path": "/pyggi_hj/test/test_patch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>PROJECTIONS = {
'none': NoProjection,
'linesearch': BisectionPerceptualProjection,
'bisection': BisectionPerceptualProjection,
'gradient': NewtonsPerceptualProjection,
'newtons': NewtonsPerceptualProjection,
}
class FirstOrderStepPerceptualAttack(nn.Module):
def __init__(self, mo... | code_fim | hard | {
"lang": "python",
"repo": "samyakjain0112/OAAT",
"path": "/perceptual_advex/perceptual_attacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: samyakjain0112/OAAT path: /perceptual_advex/perceptual_attacks.py
uts.device)
lam_max = torch.ones(batch_size, device=inputs.device)
lam = 0.5 * torch.ones(batch_size, device=inputs.device)
for _ in range(self.num_steps):
projected_adv_inputs = (
... | code_fim | hard | {
"lang": "python",
"repo": "samyakjain0112/OAAT",
"path": "/perceptual_advex/perceptual_attacks.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> max_iterations=10):
super().__init__()
self.bound = bound
self.lpips_model = lpips_model
self.projection_overshoot = projection_overshoot
self.max_iterations = max_iterations
self.bisection_projection = BisectionPerceptualProjection(
... | code_fim | hard | {
"lang": "python",
"repo": "samyakjain0112/OAAT",
"path": "/perceptual_advex/perceptual_attacks.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # then
_assert_with_static_payload(
checkout, data, amount, webhook, expected_data, response, mock_request
)
@freeze_time()
@mock.patch("saleor.plugins.webhook.tasks.send_webhook_request_sync")
def test_gateway_initialize_checkout_without_request_data(
mock_request, webhook_plugi... | code_fim | hard | {
"lang": "python",
"repo": "vineetb/saleor",
"path": "/saleor/plugins/webhook/tests/test_payment_gateway_initialize_session_webhook.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # then
_assert_with_subscription(
checkout, None, amount, webhook, expected_data, response, mock_request
)
@freeze_time()
@mock.patch("saleor.plugins.webhook.tasks.send_webhook_request_sync")
def test_gateway_initialize_checkout_with_request_data(
mock_request, webhook_plugin, we... | code_fim | hard | {
"lang": "python",
"repo": "vineetb/saleor",
"path": "/saleor/plugins/webhook/tests/test_payment_gateway_initialize_session_webhook.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vineetb/saleor path: /saleor/plugins/webhook/tests/test_payment_gateway_initialize_session_webhook.py
import json
from decimal import Decimal
from unittest import mock
import graphene
from freezegun import freeze_time
from ....core import EventDeliveryStatus
from ....core.models import EventDel... | code_fim | hard | {
"lang": "python",
"repo": "vineetb/saleor",
"path": "/saleor/plugins/webhook/tests/test_payment_gateway_initialize_session_webhook.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: robotenique/mlAlgorithms path: /supervised/modelEvaluation/learningCurve.py
import numpy as np
from trainLinearReg import trainLinearReg
from linearRegCostFunction import linearRegCostFunction
<|fim_suffix|> In this function, you will compute the train and test errors for
dataset sizes f... | code_fim | hard | {
"lang": "python",
"repo": "robotenique/mlAlgorithms",
"path": "/supervised/modelEvaluation/learningCurve.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(m):
theta = trainLinearReg(X[:i + 1], y[:i + 1], Lambda)
error_train[i], _ = linearRegCostFunction(X[:i + 1], y[:i + 1], theta, 0)
error_val[i], _ = linearRegCostFunction(Xval, yval, theta, 0)
return error_train, error_val<|fim_prefix|># repo: roboteniq... | code_fim | medium | {
"lang": "python",
"repo": "robotenique/mlAlgorithms",
"path": "/supervised/modelEvaluation/learningCurve.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Number of training examples
m, _ = X.shape
# You need to return these values correctly
error_train = np.zeros(m)
error_val = np.zeros(m)
for i in range(m):
theta = trainLinearReg(X[:i + 1], y[:i + 1], Lambda)
error_train[i], _ = linearRegCostFunction(X[:i + 1], ... | code_fim | hard | {
"lang": "python",
"repo": "robotenique/mlAlgorithms",
"path": "/supervised/modelEvaluation/learningCurve.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|># @app.get('/users')
# async def list_users():
# users = []
# for user in db.users.find():
# users.append(User(**user))
# return {'users': users}<|fim_prefix|># repo: shuxiaokai/favv path: /fastapi/app/api/routes/test.py
# either in one file or put in folder...
from fastapi import API... | code_fim | hard | {
"lang": "python",
"repo": "shuxiaokai/favv",
"path": "/fastapi/app/api/routes/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shuxiaokai/favv path: /fastapi/app/api/routes/test.py
# either in one file or put in folder...
from fastapi import APIRouter, Depends, Query
from typing import Optional
import subprocess
from services.db import get_db
from services.redis import get_redis
from services.mongodb import get_mongodb,... | code_fim | hard | {
"lang": "python",
"repo": "shuxiaokai/favv",
"path": "/fastapi/app/api/routes/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_fail(self):
self.assertEqual(add(2,2), 5)
if __name__ == '__main__':
unittest.main(argv=[''], exit=False)<|fim_prefix|># repo: AMoazeni/PyOffice path: /PyOffice/test.py
import unittest
def add(a,b):
return a+b
class TestDemo(unittest.TestCase):
<|fim_middle|> """Example o... | code_fim | medium | {
"lang": "python",
"repo": "AMoazeni/PyOffice",
"path": "/PyOffice/test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AMoazeni/PyOffice path: /PyOffice/test.py
import unittest
def add(a,b):
return a+b
class TestDemo(unittest.TestCase):
"""Example of how to use unittest in Jupyter. Functions must contain the word 'test'."""
def test_pass(self):
<|fim_suffix|>if __name__ == '__main__':
unittes... | code_fim | medium | {
"lang": "python",
"repo": "AMoazeni/PyOffice",
"path": "/PyOffice/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AMoazeni/PyOffice path: /PyOffice/test.py
import unittest
def add(a,b):
return a+b
<|fim_suffix|> self.assertEqual(add(2,2), 5)
if __name__ == '__main__':
unittest.main(argv=[''], exit=False)<|fim_middle|>class TestDemo(unittest.TestCase):
"""Example of how to use unittest in ... | code_fim | hard | {
"lang": "python",
"repo": "AMoazeni/PyOffice",
"path": "/PyOffice/test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.assertEqual(switch_it_up(8), 'Eight')
def test_equal_10(self):
self.assertEqual(switch_it_up(9), 'Nine')<|fim_prefix|># repo: mveselov/CodeWars path: /tests/kyu_8_tests/test_switch_it_up.py
import unittest
from katas.kyu_8.switch_it_up import switch_it_up
class SwitchItUpTest... | code_fim | hard | {
"lang": "python",
"repo": "mveselov/CodeWars",
"path": "/tests/kyu_8_tests/test_switch_it_up.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mveselov/CodeWars path: /tests/kyu_8_tests/test_switch_it_up.py
import unittest
from katas.kyu_8.switch_it_up import switch_it_up
class SwitchItUpTestCase(unittest.TestCase):
<|fim_suffix|> def test_equal_8(self):
self.assertEqual(switch_it_up(7), 'Seven')
def test_equal_9(self... | code_fim | hard | {
"lang": "python",
"repo": "mveselov/CodeWars",
"path": "/tests/kyu_8_tests/test_switch_it_up.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return LaunchDescription([
Node(package='rm_task',
node_executable='task_show_image',
parameters=[
{'cam_topic_name': 'sim_cam/image_raw'}
],
output='screen')
])<|fim_prefix|># repo: Hqz971016/rmoss_core path: /rm_task/launch... | code_fim | easy | {
"lang": "python",
"repo": "Hqz971016/rmoss_core",
"path": "/rm_task/launch/task_show_image.launch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Hqz971016/rmoss_core path: /rm_task/launch/task_show_image.launch.py
import os
from ament_index_python.packages import get_package_share_directory
from launch import LaunchDescription
from launch_ros.actions import Node
<|fim_suffix|> return LaunchDescription([
Node(package='rm_task',... | code_fim | easy | {
"lang": "python",
"repo": "Hqz971016/rmoss_core",
"path": "/rm_task/launch/task_show_image.launch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Reference:
1. S. Bravyi, D. Maslov, *Hadamard-free circuits expose the
structure of the Clifford group*,
`arXiv:2003.09412 [quant-ph] <https://arxiv.org/abs/2003.09412>`_
"""
if not isinstance(stab, StabilizerState):
raise QiskitError("The input is not a ... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/synthesis/stabilizer/stabilizer_decompose.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 1ucian0/qiskit-terra path: /qiskit/synthesis/stabilizer/stabilizer_decompose.py
# This code is part of Qiskit.
#
# (C) Copyright IBM 2023.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of th... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/synthesis/stabilizer/stabilizer_decompose.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> phase = []
phase.extend(phase_destab)
phase.extend(phase_stab)
phase = np.array(phase, dtype=int)
A = cliff.symplectic_matrix.astype(int)
Ainv = calc_inverse_matrix(A)
# By carefully writing how X, Y, Z gates affect each qubit, all we need to compute
# is A^{-1} * (phase)... | code_fim | hard | {
"lang": "python",
"repo": "1ucian0/qiskit-terra",
"path": "/qiskit/synthesis/stabilizer/stabilizer_decompose.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Build all submodels for DeepLook """
self.backbone = Backbone(
self.configs['backbone'],
freeze_backbone=self.configs['freeze_backbone'],
freeze_batchnorm=True
)
backbone_channel_sizes = get_backbone_channel_sizes(self.backbone)
... | code_fim | hard | {
"lang": "python",
"repo": "mingruimingrui/DeepLook",
"path": "/deep_look/modules/deep_look.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def build_modules(self):
""" Build all submodels for DeepLook """
self.backbone = Backbone(
self.configs['backbone'],
freeze_backbone=self.configs['freeze_backbone'],
freeze_batchnorm=True
)
backbone_channel_sizes = get_backbone_chan... | code_fim | hard | {
"lang": "python",
"repo": "mingruimingrui/DeepLook",
"path": "/deep_look/modules/deep_look.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mingruimingrui/DeepLook path: /deep_look/modules/deep_look.py
""" DeepLook implementation in pytorch """
import torch
# Default configs
from ._deep_look_configs import make_configs
# Other modules
from ._backbone import (
Backbone,
get_backbone_channel_sizes
)
from ._feature_pyramid_n... | code_fim | hard | {
"lang": "python",
"repo": "mingruimingrui/DeepLook",
"path": "/deep_look/modules/deep_look.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dm_data = pd.read_csv('AUS_vt_test_sentences.csv')
df = pd.DataFrame(dm_data, columns=['VideoID', 'Text', 'Top5%',
'Emoji_1', 'Emoji_2', 'Emoji_3', 'Emoji_4', 'Emoji_5',
'Pct_1', 'Pct_2', 'Pct_3', 'Pct_4', 'Pct_5'])
kmeans = KMeans(n_clusters=8... | code_fim | medium | {
"lang": "python",
"repo": "dmougouei/ValueTube",
"path": "/backend/scripts/torchMoji3/examples/kmeans_emojized.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dmougouei/ValueTube path: /backend/scripts/torchMoji3/examples/kmeans_emojized.py
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.datasets import make_blobs
from sklearn.cluster import KMeans
<|fim_suffix|> dm_data = pd.read_csv('AUS_vt_test_sentences.... | code_fim | medium | {
"lang": "python",
"repo": "dmougouei/ValueTube",
"path": "/backend/scripts/torchMoji3/examples/kmeans_emojized.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: topix-hackademy/contact-tools path: /contacts/models.py
from __future__ import unicode_literals
from django.db import models
from django.utils.encoding import python_2_unicode_compatible
from django.core.exceptions import ValidationError
import datetime
from imagekit.models import ImageSpecFiel... | code_fim | hard | {
"lang": "python",
"repo": "topix-hackademy/contact-tools",
"path": "/contacts/models.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
@python_2_unicode_compatible
class Contact(models.Model):
# this is needed to sync with the old CS
contact_centralservices_id = models.IntegerField('Old Centralservices ID', null=True, blank=True, help_text="ID of this contact in the old CS")
contact_username = models.CharField('Contact ... | code_fim | hard | {
"lang": "python",
"repo": "topix-hackademy/contact-tools",
"path": "/contacts/models.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_sum, numpy_values_nansum, pandas_sum, numpy_sum],
"title": "Pandas Sum vs Numpy Sum",
"largest_df_single_test": False,
}
benchmark = Benchmar... | code_fim | medium | {
"lang": "python",
"repo": "EduardoRubioM/mat281_portfolio",
"path": "/m02_data_analysis/m02_c06_development/fast_pandas/benchmark_sum.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return np.sum(df["A"].values)
def numpy_values_nansum(df):
return np.nansum(df["A"].values)
params = {
"df_generator": 'pd.DataFrame(np.random.randint(1, df_size, (df_size, 2)), columns=list("AB"))',
"functions_to_evaluate": [numpy_values_sum, numpy_values_nansum, pandas_sum, numpy_sum],... | code_fim | medium | {
"lang": "python",
"repo": "EduardoRubioM/mat281_portfolio",
"path": "/m02_data_analysis/m02_c06_development/fast_pandas/benchmark_sum.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EduardoRubioM/mat281_portfolio path: /m02_data_analysis/m02_c06_development/fast_pandas/benchmark_sum.py
from Benchmarker import Benchmarker
import numpy as np
def pandas_sum(df):
return df["A"].sum()
def numpy_sum(df):
return np.sum(df["A"])
def numpy_values_sum(df):
return np.su... | code_fim | hard | {
"lang": "python",
"repo": "EduardoRubioM/mat281_portfolio",
"path": "/m02_data_analysis/m02_c06_development/fast_pandas/benchmark_sum.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: parashardhapola/bartide path: /bartide/utils.py
from typing import Generator, Tuple
from .config import logger
import os
import glob
__all__ = ["glob_files"]
def glob_files(
directory: str,
read1_pattern: str = "R1",
read2_pattern: str = "R2",
file_extension: str = "fastq.gz",
... | code_fim | hard | {
"lang": "python",
"repo": "parashardhapola/bartide",
"path": "/bartide/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ension are correct. "
"Also that `read1_pattern` and `read2_pattern` parameter are correct. "
"For example, for miSeq runs `read1_pattern` and `read2_pattern` could "
"look like: 'R1_001' and 'R2_001' respectively."
)
return None
... | code_fim | hard | {
"lang": "python",
"repo": "parashardhapola/bartide",
"path": "/bartide/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brucelevis/cherrysoda-engine path: /Tools/create_project.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import lib.cherrysoda as cherry
import argparse
import sys
<|fim_suffix|> template_path = cherry.join_path(cherry.tool_path, 'res/CherrySoda/ProjectTemplate')
project_path = cherry... | code_fim | medium | {
"lang": "python",
"repo": "brucelevis/cherrysoda-engine",
"path": "/Tools/create_project.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def main():
parser = argparse.ArgumentParser()
parser.add_argument('project_name')
args = parser.parse_args(sys.argv[1:])
create_project('.', args.project_name)
if __name__ == '__main__':
main()<|fim_prefix|># repo: brucelevis/cherrysoda-engine path: /Tools/create_project.py
#!/usr... | code_fim | hard | {
"lang": "python",
"repo": "brucelevis/cherrysoda-engine",
"path": "/Tools/create_project.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# def test_put_task_to_retry_table(self):
# _ = self.scavenger.get_db_field_name
#
# raise NotImplementedError<|fim_prefix|># repo: sosw/sosw path: /sosw/test/integration/test_scavenger_i.py
import os
import unittest
from copy import deepcopy
from unittest.mock import Mock
from... | code_fim | medium | {
"lang": "python",
"repo": "sosw/sosw",
"path": "/sosw/test/integration/test_scavenger_i.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sosw/sosw path: /sosw/test/integration/test_scavenger_i.py
import os
import unittest
from copy import deepcopy
from unittest.mock import Mock
from sosw.scavenger import Scavenger
from sosw.test.variables import TEST_SCAVENGER_CONFIG
from sosw.components.dynamo_db import DynamoDbClient
<|fim_su... | code_fim | medium | {
"lang": "python",
"repo": "sosw/sosw",
"path": "/sosw/test/integration/test_scavenger_i.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: IamWangYunKai/CapsuleNet path: /utils.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import numpy as np
import torch.nn as nn
import matplotlib
if os.environ.get('DISPLAY','') == '':
print('no display found. Using non-interactive Agg backend')
matplotlib.use('Agg')
import ma... | code_fim | hard | {
"lang": "python",
"repo": "IamWangYunKai/CapsuleNet",
"path": "/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> big_image = np.ones((3, imsize*4, imsize*6+1))
images = denormalize(images).view(-1, 3, imsize, imsize)
reconstructions = denormalize(reconstructions).view(-1, 3, imsize, imsize)
images = images.data.cpu().numpy()
reconstructions = reconstructions.data.cpu().numpy()
for i in range(... | code_fim | hard | {
"lang": "python",
"repo": "IamWangYunKai/CapsuleNet",
"path": "/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vinu76jsr/django_profiler path: /fabfile.py
from fabric.operations import local
def rst_generate():
local('pandoc --from=markdown --to=rst README.md -o README.rst')
<|fim_suffix|> # local('rm -f README.rst')
# rst_generate()
local('python setup.py sdist upload')<|fim_middle|>
de... | code_fim | easy | {
"lang": "python",
"repo": "vinu76jsr/django_profiler",
"path": "/fabfile.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vinu76jsr/django_profiler path: /fabfile.py
from fabric.operations import local
<|fim_suffix|> local('pandoc --from=markdown --to=rst README.md -o README.rst')
def publish():
# local('rm -f README.rst')
# rst_generate()
local('python setup.py sdist upload')<|fim_middle|>def rst... | code_fim | easy | {
"lang": "python",
"repo": "vinu76jsr/django_profiler",
"path": "/fabfile.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def publish():
# local('rm -f README.rst')
# rst_generate()
local('python setup.py sdist upload')<|fim_prefix|># repo: vinu76jsr/django_profiler path: /fabfile.py
from fabric.operations import local
<|fim_middle|>
def rst_generate():
local('pandoc --from=markdown --to=rst README.md -o RE... | code_fim | medium | {
"lang": "python",
"repo": "vinu76jsr/django_profiler",
"path": "/fabfile.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: luanphantiki/vault-kv-backup path: /vmb/transit.py
import base64
import logging
from hvac import Client
logger = logging.LoggerAdapter(logging.getLogger(__name__),
{'STAGE': 'Transit encryption'})
class Transit:
<|fim_suffix|> def backup_key(self):
se... | code_fim | hard | {
"lang": "python",
"repo": "luanphantiki/vault-kv-backup",
"path": "/vmb/transit.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.client.secrets.transit.update_key_configuration(
name=self.encryption_key,
exportable=True,
allow_plaintext_backup=True,
)
backup_key_response = self.client.secrets.transit.backup_key(
name=self.encryption_key,
)
... | code_fim | hard | {
"lang": "python",
"repo": "luanphantiki/vault-kv-backup",
"path": "/vmb/transit.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> list_display = ('user', 'check_code', 'add_time')
class UserRelationshipAdmin(admin.ModelAdmin):
list_display = ('from_user', 'to_user', 'add_time')
admin.site.register(User, UserAdmin)
admin.site.register(CheckCode, CheckCodeAdmin)
admin.site.register(UserRelationship, UserRelationshipAdmin)<... | code_fim | medium | {
"lang": "python",
"repo": "guojy1314/stw1209",
"path": "/user/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guojy1314/stw1209 path: /user/admin.py
from django.contrib import admin
from .models import User, CheckCode, UserRelationship
<|fim_suffix|>
admin.site.register(User, UserAdmin)
admin.site.register(CheckCode, CheckCodeAdmin)
admin.site.register(UserRelationship, UserRelationshipAdmin)<|fim_mid... | code_fim | hard | {
"lang": "python",
"repo": "guojy1314/stw1209",
"path": "/user/admin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class UserRelationshipAdmin(admin.ModelAdmin):
list_display = ('from_user', 'to_user', 'add_time')
admin.site.register(User, UserAdmin)
admin.site.register(CheckCode, CheckCodeAdmin)
admin.site.register(UserRelationship, UserRelationshipAdmin)<|fim_prefix|># repo: guojy1314/stw1209 path: /user/admi... | code_fim | medium | {
"lang": "python",
"repo": "guojy1314/stw1209",
"path": "/user/admin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Set parameters for LJ
m = 1
sigma = 1.0e-10
eps = 30.0
lambda_a = 6.0
lambda_r = 12.0
svrm.init("Ar")
svrm.set_tmin(temp=2.0)
svrm.set_pure_fluid_param(1, m, sigma, eps, lambda_a, lambda_r)
svrm.redefine_critical_parameters(False)
# Plot phase envelope
z = np.array([1.0])
T, P, v = svrm.get_envelope_tw... | code_fim | hard | {
"lang": "python",
"repo": "ibell/thermopack",
"path": "/addon/pyExamples/saft_vr_mie.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ibell/thermopack path: /addon/pyExamples/saft_vr_mie.py
#!/usr/bin/python
# Support for python2
from __future__ import print_function
#Modify system path
import sys
sys.path.append('../pycThermopack/')
# Importing pyThermopack
from pyctp import saftvrmie
# Importing Numpy (math, arrays, etc...)
i... | code_fim | hard | {
"lang": "python",
"repo": "ibell/thermopack",
"path": "/addon/pyExamples/saft_vr_mie.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ Calculate reduced density
"""
rhoStar = np.zeros_like(rhoa)
rhoStar = sigma**3*NA*rhoa
return rhoStar
# Instanciate and init SAFT-VR Mie object
svrm = saftvrmie.saftvrmie()
svrm.init("H2")
svrm.set_tmin(temp=2.0)
# Get parameters for H2
m, sigma, eps, lambda_a, lambda_r = svrm.ge... | code_fim | medium | {
"lang": "python",
"repo": "ibell/thermopack",
"path": "/addon/pyExamples/saft_vr_mie.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(
self, method: str, has_data: Optional[bool] = None
) -> None: ...
class ResolutionQuery(SimpleQuery):
def __init__(self, min: float, max: float) -> None: ...
class BFactorQuery(SimpleQuery):
def __init__(self, min: float, max: float) -> None: ...
class MolecularWei... | code_fim | hard | {
"lang": "python",
"repo": "Dr-Moreb/biotite",
"path": "/src/biotite/database/rcsb/search.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Dr-Moreb/biotite path: /src/biotite/database/rcsb/search.pyi
# This source code is part of the Biotite package and is distributed
# under the 3-Clause BSD License. Please see 'LICENSE.rst' for further
# information.
from typing import Iterable, List, Union, Optional
from abc import abstractmetho... | code_fim | medium | {
"lang": "python",
"repo": "Dr-Moreb/biotite",
"path": "/src/biotite/database/rcsb/search.pyi",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>class SimpleQuery(Query):
def __init__(self, query_type: str, parameter_class: str = "") -> None: ...
def add_param(self, param: str, content: str) -> None: ...
class MethodQuery(SimpleQuery):
def __init__(
self, method: str, has_data: Optional[bool] = None
) -> None: ...
class R... | code_fim | hard | {
"lang": "python",
"repo": "Dr-Moreb/biotite",
"path": "/src/biotite/database/rcsb/search.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def list_installed_depends_by_extra(
installed_dists: InstalledDistributions,
project_name: NormalizedName,
) -> Dict[Optional[NormalizedName], Set[NormalizedName]]:
"""Get installed dependencies of a project, grouped by extra."""
res = {} # type: Dict[Optional[NormalizedName], Set[Normal... | code_fim | hard | {
"lang": "python",
"repo": "ThomasBinsfeld/pip-deepfreeze",
"path": "/src/pip_deepfreeze/list_installed_depends.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ThomasBinsfeld/pip-deepfreeze path: /src/pip_deepfreeze/list_installed_depends.py
from typing import Dict, Optional, Sequence, Set
from packaging.requirements import Requirement
from packaging.utils import canonicalize_name
from .compat import NormalizedName
from .installed_dist import Installe... | code_fim | hard | {
"lang": "python",
"repo": "ThomasBinsfeld/pip-deepfreeze",
"path": "/src/pip_deepfreeze/list_installed_depends.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def list_installed_depends_by_extra(
installed_dists: InstalledDistributions,
project_name: NormalizedName,
) -> Dict[Optional[NormalizedName], Set[NormalizedName]]:
"""Get installed dependencies of a project, grouped by extra."""
res = {} # type: Dict[Optional[NormalizedName], Set[Norma... | code_fim | medium | {
"lang": "python",
"repo": "ThomasBinsfeld/pip-deepfreeze",
"path": "/src/pip_deepfreeze/list_installed_depends.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> license_plate = db.Column(db.String(16), primary_key=True)
user_id = db.Column(db.String(64), unique=True)
brand = db.Column(db.String(64))
color = db.Column(db.String(64))
type = db.Column(db.String(64))
horsepower = db.Column(db.Integer)
build_year = db.Column(db.Integer)
fuel_type = db.Column(d... | code_fim | medium | {
"lang": "python",
"repo": "Deedss/Vroomrr",
"path": "/vroomrr-api/flask/model/car.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Deedss/Vroomrr path: /vroomrr-api/flask/model/car.py
from ext import db
from dataclasses import dataclass
from dataclasses_json import dataclass_json
<|fim_suffix|> license_plate = db.Column(db.String(16), primary_key=True)
user_id = db.Column(db.String(64), unique=True)
brand = db.Column(db.S... | code_fim | hard | {
"lang": "python",
"repo": "Deedss/Vroomrr",
"path": "/vroomrr-api/flask/model/car.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def vote(solid):
#TODO: validate oauth
pass
if __name__ == '__main__':
app.run(debug=True, port=31415)<|fim_prefix|># repo: xxranagazooxx/alaalametcys-sol-finder path: /api.py
#!flask/bin/python
from flask import Flask, jsonify
from models import get_solution
app = Flask(__name__)
SECMAP = ... | code_fim | hard | {
"lang": "python",
"repo": "xxranagazooxx/alaalametcys-sol-finder",
"path": "/api.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xxranagazooxx/alaalametcys-sol-finder path: /api.py
#!flask/bin/python
from flask import Flask, jsonify
from models import get_solution
app = Flask(__name__)
SECMAP = {
# translate uri to db namespace
"CP": "C/P",
"SB": "S/B",
"BB" : "B/B",
"CARS" : "CARS"}
@app.route('/')
d... | code_fim | medium | {
"lang": "python",
"repo": "xxranagazooxx/alaalametcys-sol-finder",
"path": "/api.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return jsonify(get_solution(mod, rsec, num))
def vote(solid):
#TODO: validate oauth
pass
if __name__ == '__main__':
app.run(debug=True, port=31415)<|fim_prefix|># repo: xxranagazooxx/alaalametcys-sol-finder path: /api.py
#!flask/bin/python
from flask import Flask, jsonify
from models im... | code_fim | hard | {
"lang": "python",
"repo": "xxranagazooxx/alaalametcys-sol-finder",
"path": "/api.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> template_fields: Any
template_ext: Any
ui_color: str
source_project_dataset_tables: Any
destination_project_dataset_table: Any
write_disposition: Any
create_disposition: Any
bigquery_conn_id: Any
delegate_to: Any
labels: Any
encryption_configuration: Any
def... | code_fim | medium | {
"lang": "python",
"repo": "viewthespace/mypy-stubs",
"path": "/src/airflow-stubs/contrib/operators/bigquery_to_bigquery.pyi",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: viewthespace/mypy-stubs path: /src/airflow-stubs/contrib/operators/bigquery_to_bigquery.pyi
from airflow.contrib.hooks.bigquery_hook import BigQueryHook as BigQueryHook
from airflow.models import BaseOperator as BaseOperator
from airflow.utils.decorators import apply_defaults as apply_defaults
fr... | code_fim | medium | {
"lang": "python",
"repo": "viewthespace/mypy-stubs",
"path": "/src/airflow-stubs/contrib/operators/bigquery_to_bigquery.pyi",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def fit_plane(points):
'''Fit a plane to the 3D beads surface'''
import scipy.optimize
import functools
fun = functools.partial(squared_error, points=points)
params0 = [0.0, 0.0, 0.0]
return scipy.optimize.minimize(fun, params0)
def interpolate_surface(coords, output_shape, met... | code_fim | hard | {
"lang": "python",
"repo": "scottberry/JtModules",
"path": "/src/python/jtmodules/generate_volume_image.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: scottberry/JtModules path: /src/python/jtmodules/generate_volume_image.py
use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dis... | code_fim | hard | {
"lang": "python",
"repo": "scottberry/JtModules",
"path": "/src/python/jtmodules/generate_volume_image.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return filtered_coords_global
def main(image, mask, threshold=25,
mean_size=6, min_size=10,
filter_type='log_2d',
minimum_bead_intensity=150,
z_step=0.333, pixel_size=0.1625,
alpha=0, plot=False):
'''Converts an image stack with labelled cell surface ... | code_fim | hard | {
"lang": "python",
"repo": "scottberry/JtModules",
"path": "/src/python/jtmodules/generate_volume_image.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.