text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Set item category and item name')
parser.parse_args()
if len(sys.argv) == 1:
item_category()<|fim_prefix|># repo: Findspire/workflow path: /scripts/item_category.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
i... | code_fim | hard | {
"lang": "python",
"repo": "Findspire/workflow",
"path": "/scripts/item_category.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Findspire/workflow path: /scripts/item_category.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import os
import django
import argparse
<|fim_suffix|>from workflow.apps.workflow.models import Item, ItemCategory, Workflow
def item_category():
for item in Item.objects.all():
... | code_fim | medium | {
"lang": "python",
"repo": "Findspire/workflow",
"path": "/scripts/item_category.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jimmy-INL/google-research path: /jaxraytrace/main.py
# coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# 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
#
# ... | code_fim | hard | {
"lang": "python",
"repo": "Jimmy-INL/google-research",
"path": "/jaxraytrace/main.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> rendering_config = configuration.get_config()
rendering_config = ml_collections.FrozenConfigDict(rendering_config)
aspect_ratio = rendering_config.aspect_ratio
height = rendering_config.height
width = int(aspect_ratio * height)
scene_camera = build_camera(rendering_config, aspect_ratio)
wor... | code_fim | hard | {
"lang": "python",
"repo": "Jimmy-INL/google-research",
"path": "/jaxraytrace/main.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: debuggerpk/django-stubs path: /django-stubs/views/generic/list.pyi
from typing import Any, Dict, List, Optional, Tuple, Union
from django.core.handlers.wsgi import WSGIRequest
from django.core.paginator import Page, Paginator
from django.db.models.query import QuerySet
from django.template.respo... | code_fim | hard | {
"lang": "python",
"repo": "debuggerpk/django-stubs",
"path": "/django-stubs/views/generic/list.pyi",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> allow_empty: bool = ...
queryset: Any = ...
model: Any = ...
paginate_by: Any = ...
paginate_orphans: int = ...
context_object_name: Any = ...
paginator_class: Any = ...
page_kwarg: str = ...
ordering: Any = ...
def get_queryset(self) -> Union[List[Dict[str, str]], ... | code_fim | medium | {
"lang": "python",
"repo": "debuggerpk/django-stubs",
"path": "/django-stubs/views/generic/list.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self, *, object_list: Optional[Any] = ..., **kwargs: Any
) -> Dict[str, Any]: ...
class BaseListView(MultipleObjectMixin, View):
object_list: Any = ...
def get(
self, request: WSGIRequest, *args: Any, **kwargs: Any
) -> TemplateResponse: ...
class MultipleObjectTemplateRe... | code_fim | hard | {
"lang": "python",
"repo": "debuggerpk/django-stubs",
"path": "/django-stubs/views/generic/list.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MercerBinaryBears/Slides path: /2016/slides/GraphTheory/graph.py
class Graph:
def __init__(self):
self.adjacency = {}
def connect(self, vertex1, vertex2, weight=None):
if vertex1 not in self.adjacency:
self.adjacency[vertex1] = {}
self.adjacency[verte... | code_fim | medium | {
"lang": "python",
"repo": "MercerBinaryBears/Slides",
"path": "/2016/slides/GraphTheory/graph.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def are_connected(self, vertex1, vertex2):
return self.is_vertex(vertex1) and vertex2 in self.adjacency[vertex1]
def weight(self, vertex1, vertex2):
return self.adjacency[vertex1][vertex2]
def neighbors(self, vertex1):
return self.adjacency[vertex1].keys()
# Test Cod... | code_fim | medium | {
"lang": "python",
"repo": "MercerBinaryBears/Slides",
"path": "/2016/slides/GraphTheory/graph.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> generate_out['fake_image'] = self.net['netG'](input_semantics, warp_out=CBN_in)
generate_out = {**generate_out, **coor_out}
return generate_out
def inference(self, input_semantics, ref_semantics=None, ref_image=None, self_ref=None):
generate_out = {}
coor_out ... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/CoCosNet",
"path": "/models/pix2pix_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not self.opt.no_ganFeat_loss:
num_D = len(pred_fake)
GAN_Feat_loss = self.FloatTensor(1).fill_(0)
for i in range(num_D): # for each discriminator
# last output is the final prediction, so we exclude it
num_intermediate_outputs... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/CoCosNet",
"path": "/models/pix2pix_model.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/CoCosNet path: /models/pix2pix_model.py
n generated_out else generated_out['warp_mask']
out['adaptive_feature_seg'] = None if 'adaptive_feature_seg' not in generated_out else generated_out['adaptive_feature_seg']
out['adaptive_feature_img'] = None if 'adaptive_fe... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/CoCosNet",
"path": "/models/pix2pix_model.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kemitche/indextank-service path: /gen-py/flaptor/indextank/rpc/Indexer-remote
#!/usr/bin/env python
#
# Autogenerated by Thrift
#
# DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING
#
import sys
import pprint
from urlparse import urlparse
from thrift.transport import TTransport
fr... | code_fim | hard | {
"lang": "python",
"repo": "kemitche/indextank-service",
"path": "/gen-py/flaptor/indextank/rpc/Indexer-remote",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>elif cmd == 'removeScoreFunction':
if len(args) != 1:
print 'removeScoreFunction requires 1 args'
sys.exit(1)
pp.pprint(client.removeScoreFunction(eval(args[0]),))
elif cmd == 'listScoreFunctions':
if len(args) != 0:
print 'listScoreFunctions requires 0 args'
sys.exit(1)
pp.pprint... | code_fim | hard | {
"lang": "python",
"repo": "kemitche/indextank-service",
"path": "/gen-py/flaptor/indextank/rpc/Indexer-remote",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if sys.argv[argi] == '-u':
url = urlparse(sys.argv[argi+1])
parts = url[1].split(':')
host = parts[0]
if len(parts) > 1:
port = int(parts[1])
else:
port = 80
uri = url[2]
if url[4]:
uri += '?%s' % url[4]
http = True
argi += 2
if sys.argv[argi] == '-f' or sys.argv[argi] == '-... | code_fim | hard | {
"lang": "python",
"repo": "kemitche/indextank-service",
"path": "/gen-py/flaptor/indextank/rpc/Indexer-remote",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: siddharthSharma102/HandCricket-OpenCV path: /test.py
from keras.models import load_model
import cv2
import numpy as np
import sys
<|fim_suffix|># PREDICTION
pred = model.predict(np.array([img]))
move_code = np.argmax(pred[0])
move_name = mapper(move_code)
print("\n\nPridcted: {}".form... | code_fim | hard | {
"lang": "python",
"repo": "siddharthSharma102/HandCricket-OpenCV",
"path": "/test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return rev_class_map[val]
# LOADNG TRAINED MODEL
model = load_model("Hand-Cricket-model.h5")
# PREPARING IMAGE
img = cv2.imread(filepath)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = cv2.resize(img, (227, 227))
# PREDICTION
pred = model.predict(np.array([img]))
move_code = np.argmax... | code_fim | medium | {
"lang": "python",
"repo": "siddharthSharma102/HandCricket-OpenCV",
"path": "/test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #todo get the result below using pandas
def df_sessions_registered_participants(self):
results = {}
for key, value in self.hugo.df_participants().to_dict(orient='index').items():
title = value.get('title')
sessions = value.get('sessions')
for ses... | code_fim | hard | {
"lang": "python",
"repo": "OpenSecuritySummit/jp-2020",
"path": "/notebooks/api/oss_hugo/OSS_Schedule.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OpenSecuritySummit/jp-2020 path: /notebooks/api/oss_hugo/OSS_Schedule.py
import pandas as pd
from oss_hugo.API_Hugo_OSS import API_Hugo_OSS
class OSS_Schedule:
def __init__(self):
self.hugo = API_Hugo_OSS()
def sessions_mapped_by_size(self):
mapping = []
for pat... | code_fim | hard | {
"lang": "python",
"repo": "OpenSecuritySummit/jp-2020",
"path": "/notebooks/api/oss_hugo/OSS_Schedule.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> results = {}
for key, value in self.hugo.df_participants().to_dict(orient='index').items():
title = value.get('title')
sessions = value.get('sessions')
for session in sessions:
if results.get(session) is None: results[session] = []
... | code_fim | hard | {
"lang": "python",
"repo": "OpenSecuritySummit/jp-2020",
"path": "/notebooks/api/oss_hugo/OSS_Schedule.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ipavlopoulos/lm path: /run_mlm.py
"""
import unittest
class MyTestCase(unittest.TestCase):
def test_something(self):
self.assertEqual(True, False)
if __name__ == '__main__':
unittest.main()
"""
import pandas as pd
from sklearn.model_selection import train_test_split
from marko... | code_fim | hard | {
"lang": "python",
"repo": "ipavlopoulos/lm",
"path": "/run_mlm.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for K in kappas:
print(f"Micro Accuracy({K}-GLM) & {100 * np.mean(accs[K]):.2f} ± {100*sem(accs[K]):.2f} \\\\")
print(f"Keystrokes({K}-GLM) & {100 * np.mean(keys[K]):.2f} ± {100*sem(keys[K]):.2f} \\\\")
print()
if FLAGS.method in {"lstm", "gru"}:
pr... | code_fim | hard | {
"lang": "python",
"repo": "ipavlopoulos/lm",
"path": "/run_mlm.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_register_should_set_request_handler_for_service_actions(self):
self._service_provider.server.set_request_handler.assert_called()
def test_update_cell_with_no_active_session(self):
update_cell_request = UpdateCellRequest()
update_cell_request.owner_uri = 'test_own... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/pgtoolsservice",
"path": "/tests/edit_data/test_edit_data_service.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/pgtoolsservice path: /tests/edit_data/test_edit_data_service.py
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project roo... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/pgtoolsservice",
"path": "/tests/edit_data/test_edit_data_service.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> request = RevertRowRequest()
request.owner_uri = 'test_owner_uri'
request.row_id = 1
self._validate_row_operations(self._service_under_test._revert_row, 'revert_row', request, request.row_id)
def test_revert_cell_operation(self):
request = RevertCellRequest()... | code_fim | hard | {
"lang": "python",
"repo": "microsoft/pgtoolsservice",
"path": "/tests/edit_data/test_edit_data_service.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wmww/wayland-debug path: /core/persistent_ui_state.py
from interfaces import UIState
class PersistentUIState(UIState.Listener):
'''Keeps track of a UI state
UIState.Listener methods can be called directly to set the state without other listeners being notified'''
<|fim_suffix|> '... | code_fim | hard | {
"lang": "python",
"repo": "wmww/wayland-debug",
"path": "/core/persistent_ui_state.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def quit_requested(self) -> None:
'''Overrides a method in UIState.Listener'''
self._should_quit = True<|fim_prefix|># repo: wmww/wayland-debug path: /core/persistent_ui_state.py
from interfaces import UIState
class PersistentUIState(UIState.Listener):
'''Keeps track of a UI stat... | code_fim | hard | {
"lang": "python",
"repo": "wmww/wayland-debug",
"path": "/core/persistent_ui_state.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''Overrides a method in UIState.Listener'''
self._paused = False
def quit_requested(self) -> None:
'''Overrides a method in UIState.Listener'''
self._should_quit = True<|fim_prefix|># repo: wmww/wayland-debug path: /core/persistent_ui_state.py
from interfaces import ... | code_fim | hard | {
"lang": "python",
"repo": "wmww/wayland-debug",
"path": "/core/persistent_ui_state.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NAIST-SD-PBL-PAL/Teddy-plus path: /evaluation/nor-manim_10.py
def get_stroke_rgbas(self, vmobject, background=False):
return self.modi<|fim_suffix|>ct.get_stroke_rgbas(background)
)<|fim_middle|>fied_rgbas(
vmobject, vmobje | code_fim | easy | {
"lang": "python",
"repo": "NAIST-SD-PBL-PAL/Teddy-plus",
"path": "/evaluation/nor-manim_10.py",
"mode": "psm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|>ct.get_stroke_rgbas(background)
)<|fim_prefix|># repo: NAIST-SD-PBL-PAL/Teddy-plus path: /evaluation/nor-manim_10.py
def get_stroke_rgbas(self, vmobject, bac<|fim_middle|>kground=False):
return self.modified_rgbas(
vmobject, vmobje | code_fim | medium | {
"lang": "python",
"repo": "NAIST-SD-PBL-PAL/Teddy-plus",
"path": "/evaluation/nor-manim_10.py",
"mode": "spm",
"license": "ISC",
"source": "the-stack-v2"
} |
<|fim_suffix|> nonlocal num_fails
func_name = func.__name__
try:
return func(*args, **kwargs)
except Exception as e:
num_fails += 1
if num_fails == 1:
print(('Something went wrong in `{}`. ' +
'The process will con... | code_fim | hard | {
"lang": "python",
"repo": "DavitAbgaryan/aim",
"path": "/aim/sdk/session/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DavitAbgaryan/aim path: /aim/sdk/session/utils.py
import os
from functools import wraps
from aim.engine.configs import (
AIM_BRANCH_ENV_VAR,
AIM_COMMIT_ENV_VAR,
AIM_AUTOMATED_EXEC_ENV_VAR,
)
<|fim_suffix|> nonlocal num_fails
func_name = func.__name__
try:
... | code_fim | hard | {
"lang": "python",
"repo": "DavitAbgaryan/aim",
"path": "/aim/sdk/session/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: RomeoV/pyomo-MINLP-benchmarking path: /models/tls2.py
# MINLP written by GAMS Convert at 05/15/20 00:51:26
#
# Equation counts
# Total E G L N X C B
# 25 7 0 18 0 0 0 0
#
# Variabl... | code_fim | hard | {
"lang": "python",
"repo": "RomeoV/pyomo-MINLP-benchmarking",
"path": "/models/tls2.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>m.c19 = Constraint(expr= m.x8 - 3*m.b35 - 8*m.b36 - 15*m.b37 == 1)
m.c20 = Constraint(expr= m.b24 + m.b25 + m.b26 + m.b27 <= 1)
m.c21 = Constraint(expr= m.b28 + m.b29 + m.b30 + m.b31 <= 1)
m.c22 = Constraint(expr= m.b32 + m.b33 + m.b34 <= 1)
m.c23 = Constraint(expr= m.b35 + m.b36 + m.b37 <= ... | code_fim | hard | {
"lang": "python",
"repo": "RomeoV/pyomo-MINLP-benchmarking",
"path": "/models/tls2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>m.c24 = Constraint(expr=-(sqrt(m.i3*m.x5) + sqrt(m.i4*m.x6)) + m.b9 + 2*m.b10 + 3*m.b11 + 4*m.b12 + 5*m.b13 + 6*m.b14
+ 7*m.b15 + 8*m.b16 + m.b17 + 2*m.b18 + 3*m.b19 + 4*m.b20 + 5*m.b21 + 6*m.b22 + 7*m.b23 + m.b24
+ 2*m.b25 + 3*m.b26 + 4*m.b27 + m.b28 + 2*... | code_fim | hard | {
"lang": "python",
"repo": "RomeoV/pyomo-MINLP-benchmarking",
"path": "/models/tls2.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: atakan-tr/fmeca-1 path: /app/api/components.py
from flask import jsonify, request
from . import api
from .. import db
from ..models import Area, Component
from ..decorators import json, paginate
@api.route("/areas/<int:id>/components/", methods=['GET'])
@json
@paginate('components')
def get_are... | code_fim | hard | {
"lang": "python",
"repo": "atakan-tr/fmeca-1",
"path": "/app/api/components.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@api.route("/components/<int:id>", methods=["DELETE"])
@json
def component_delete(id):
component = Component.query.get_or_404(id)
db.session.delete(component)
db.session.commit()
return {}<|fim_prefix|># repo: atakan-tr/fmeca-1 path: /app/api/components.py
from flask import jsonify, reque... | code_fim | hard | {
"lang": "python",
"repo": "atakan-tr/fmeca-1",
"path": "/app/api/components.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> candidate_samples = []
for i in range(1, len(existing_samples)):
candidate_sample = 0.5 * (existing_samples[i] - existing_samples[i-1])
gradient = gradients[i-1]
if i > 2:
score +=
# Sort the candidate... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/metadata/parameter.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jskinn/robot-vision-experiment-framework path: /metadata/parameter.py
# Copyright (c) 2017, John Skinner
import operator
import database.entity
class ContinuousParameter(database.entity.Entity):
def __init__(self, name, min_ = None, max_ = None, id_ = None, **kwargs):
super().__ini... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/metadata/parameter.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param existing_results: A map of existing sample values to a numeric score which we're sampling against.
:param num_samples: The upper limit on the desired samples/
:return:
"""
new_samples = set()
existing_samples = list(existing_results.keys())
... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/metadata/parameter.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>items():
d1[value]=d1.get(value,0)+1
for x in d1.items():
print(x)<|fim_prefix|># repo: inwk6312fall2017/programming-task-2-gansiva path: /code.py
import string
import csv
d=dict()
d1=dict()
with open("Crime.csv", 'r') as myfile:
reader = csv.reader(myfile)
for row in reader:
d[row[2<|fim_middle... | code_fim | medium | {
"lang": "python",
"repo": "inwk6312fall2017/programming-task-2-gansiva",
"path": "/code.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: inwk6312fall2017/programming-task-2-gansiva path: /code.py
import string
import csv
d=dict()
d1=dict()
with open("Crime.csv", 'r'<|fim_suffix|>items():
d1[value]=d1.get(value,0)+1
for x in d1.items():
print(x)<|fim_middle|>) as myfile:
reader = csv.reader(myfile)
for row in reader:
d[row... | code_fim | medium | {
"lang": "python",
"repo": "inwk6312fall2017/programming-task-2-gansiva",
"path": "/code.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: helena-network/gnosisdb path: /gnosisdb/restapi/tests/test_views.py
n/json')
self.assertEqual(market_response_data.status_code, status.HTTP_200_OK)
self.assertEqual(len(json.loads(market_response_data.content).get('results')), len(markets))
market_search_response = self.c... | code_fim | hard | {
"lang": "python",
"repo": "helena-network/gnosisdb",
"path": "/gnosisdb/restapi/tests/test_views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: helena-network/gnosisdb path: /gnosisdb/restapi/tests/test_views.py
json.loads(events_response.content).get('results')[0].get('contract').get('address'), add_0x_prefix(event.address))
def test_markets(self):
# test empty events response
empty_markets_response = self.client.ge... | code_fim | hard | {
"lang": "python",
"repo": "helena-network/gnosisdb",
"path": "/gnosisdb/restapi/tests/test_views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> trades_response = self.client.get(url, content_type='application/json')
trades_data = json.loads(trades_response.content)
self.assertEqual(trades_response.status_code, status.HTTP_200_OK)
self.assertEqual(len(trades_data.get('results')), 1)
self.assertEqual(trades_d... | code_fim | hard | {
"lang": "python",
"repo": "helena-network/gnosisdb",
"path": "/gnosisdb/restapi/tests/test_views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: slalom/slaloms-and-dragons path: /game/animations.py
import emoji
import sys
import time
import pyfiglet
from colorama import Fore, Back, Style
title = "slaloms & dragons"
subtitle = "Let's play SLALOMS & DRAGONS :dragon:"
<|fim_suffix|> color = Fore.MAGENTA
font_bold = Style.BRIGHT
... | code_fim | medium | {
"lang": "python",
"repo": "slalom/slaloms-and-dragons",
"path": "/game/animations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> color = Fore.MAGENTA
font_bold = Style.BRIGHT
result = pyfiglet.figlet_format(" ".join(list(title.upper())), font="mini")
print(color + font_bold + result)
animation = emoji.emojize(color + font_bold + subtitle)
for i in animation:
time.sleep(0.03)
sys.stdout.writ... | code_fim | medium | {
"lang": "python",
"repo": "slalom/slaloms-and-dragons",
"path": "/game/animations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> os.system("./conflictAnalyzer.sh test/example3.c > /dev/null 2> /dev/null")
with open('result.txt') as rf:
data = rf.readlines()
correctStr = "[E_orange, E_orange, E_orange, E_purple, E_purple, E_purple, E_orange, E_orange, E_purple, E_orange, E_orange, E_purple, E_purple, E_purple... | code_fim | hard | {
"lang": "python",
"repo": "gaps-closure/capo",
"path": "/C/formal/ontology/deprecated/regressionTest.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gaps-closure/capo path: /C/formal/ontology/deprecated/regressionTest.py
#!/usr/bin/python3
import os
if __name__ == '__main__':
os.system("./conflictAnalyzer.sh test/example1.c > /dev/null 2> /dev/null")
with open('result.txt') as rf:
data = rf.readlines()
correctStr = "... | code_fim | hard | {
"lang": "python",
"repo": "gaps-closure/capo",
"path": "/C/formal/ontology/deprecated/regressionTest.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jart/cosmopolitan path: /third_party/python/Tools/scripts/which.py
#! /usr/bin/env python3
# Variant of "which".
# On stderr, near and total misses are reported.
# '-l<flags>' argument adds ls -l<flags> of each file found.
import sys
if sys.path[0] in (".", ""): del sys.path[0]
<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "jart/cosmopolitan",
"path": "/third_party/python/Tools/scripts/which.py",
"mode": "psm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> pathlist = os.environ['PATH'].split(os.pathsep)
sts = 0
longlist = ''
if sys.argv[1:] and sys.argv[1][:2] == '-l':
longlist = sys.argv[1]
del sys.argv[1]
for prog in sys.argv[1:]:
ident = ()
for dir in pathlist:
filename = os.path.join(dir... | code_fim | hard | {
"lang": "python",
"repo": "jart/cosmopolitan",
"path": "/third_party/python/Tools/scripts/which.py",
"mode": "spm",
"license": "Python-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.drivers[side].sendCalibrate()
self.storedCommand[side] = None
def dropClicked(self):
if self.widget.handSelect.leftButton.checked:
side = 'left'
else:
side = 'right'
self.drivers[side].sendDrop()
self.storedCommand[side] = ... | code_fim | hard | {
"lang": "python",
"repo": "mlab-upenn/arch-apex",
"path": "/APEX-S/Libraries/drake-v0.9.11-mac/build/lib/python2.7/dist-packages/ddapp/handcontrolpanel.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mlab-upenn/arch-apex path: /APEX-S/Libraries/drake-v0.9.11-mac/build/lib/python2.7/dist-packages/ddapp/handcontrolpanel.py
import PythonQt
from PythonQt import QtCore, QtGui, QtUiTools
from ddapp import lcmUtils
from ddapp import applogic as app
from ddapp.utime import getUtime
from ddapp.timerca... | code_fim | hard | {
"lang": "python",
"repo": "mlab-upenn/arch-apex",
"path": "/APEX-S/Libraries/drake-v0.9.11-mac/build/lib/python2.7/dist-packages/ddapp/handcontrolpanel.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Wajdi-Mabroukeh/CvStudio path: /view/widgets/image_viewer/image_viewer.py
,value):
self._curr_channel=value
def build_toolbox(self):
icon_size=QSize(28,28)
self._toolbox = [
ImageButton(icon=GUIUtilities.get_icon("polygon.png"),size=icon_size, tag="polygon... | code_fim | hard | {
"lang": "python",
"repo": "Wajdi-Mabroukeh/CvStudio",
"path": "/view/widgets/image_viewer/image_viewer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @dask.delayed
def load_image_label(self):
return self._ann_dao.get_label(self.tag.id)
@dask.delayed
def load_image_annotations(self):
return self._ann_dao.fetch_all(self.tag.id)
def load_image(self):
@work_exception
def do_work():
return da... | code_fim | hard | {
"lang": "python",
"repo": "Wajdi-Mabroukeh/CvStudio",
"path": "/view/widgets/image_viewer/image_viewer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @dask.delayed
def load_labels(self):
dataset_id=self.tag.dataset
return self._labels_dao.fetch_all(dataset_id)
@gui_exception
def image_list_sel_changed_slot(self,curr: CustomListWidgetItem,prev: CustomListWidgetItem):
self.image, self.tag = cv2.imread(curr.tag.fi... | code_fim | hard | {
"lang": "python",
"repo": "Wajdi-Mabroukeh/CvStudio",
"path": "/view/widgets/image_viewer/image_viewer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LeoneBacciu/django-email-verification path: /django_email_verification/urls.py
from django.urls import path
from django.views.decorators.csrf import csrf_exempt
<|fim_suffix|>urlpatterns = [
path('email/<str:token>', csrf_exempt(verify_email_page)),
path('password/<str:token>', csrf_exem... | code_fim | medium | {
"lang": "python",
"repo": "LeoneBacciu/django-email-verification",
"path": "/django_email_verification/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = [
path('email/<str:token>', csrf_exempt(verify_email_page)),
path('password/<str:token>', csrf_exempt(verify_password_page)),
]<|fim_prefix|># repo: LeoneBacciu/django-email-verification path: /django_email_verification/urls.py
from django.urls import path
from django.views.decorato... | code_fim | medium | {
"lang": "python",
"repo": "LeoneBacciu/django-email-verification",
"path": "/django_email_verification/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: muraria/graviton2-workshop path: /scripts/elasticsearch-generate-data.py
#!/usr/bin/env python
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. SPDX-License-Identifier: MIT-0
#
# This script inserts random data into an index named "people" within an Amazon
# Elasticsearch clu... | code_fim | hard | {
"lang": "python",
"repo": "muraria/graviton2-workshop",
"path": "/scripts/elasticsearch-generate-data.py",
"mode": "psm",
"license": "MIT-0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
result = es.index(index="people", doc_type="_doc", body=document)
print("Indexed with ID '%s'" % result['_id'])
time.sleep(0.25)
except ConnectionTimeout as e:
print("Connection to the ES cluster timed out: %s" % str(e))
tim... | code_fim | hard | {
"lang": "python",
"repo": "muraria/graviton2-workshop",
"path": "/scripts/elasticsearch-generate-data.py",
"mode": "spm",
"license": "MIT-0",
"source": "the-stack-v2"
} |
<|fim_suffix|> region = os.environ['AWS_REGION']
service = 'es'
credentials = boto3.Session().get_credentials()
awsauth = AWS4Auth(credentials.access_key, credentials.secret_key, region, service, session_token=credentials.token)
fake = Faker()
es = Elasticsearch(
hosts = [{... | code_fim | hard | {
"lang": "python",
"repo": "muraria/graviton2-workshop",
"path": "/scripts/elasticsearch-generate-data.py",
"mode": "spm",
"license": "MIT-0",
"source": "the-stack-v2"
} |
<|fim_suffix|> length = int(data.strip(), 16)
if length == 0:
resp = self.current_response
if resp._decompressor:
resp.body += resp._decompressor.flush()
del resp._decompressor
self._stream.on_read = self._read_additional_headers
... | code_fim | hard | {
"lang": "python",
"repo": "ixokai/pants",
"path": "/pants/contrib/http/client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if headers is None:
headers = {}
if headers.get('Content-Type', '') == 'application/x-www-form-urlencoded' and files:
raise ValueError("Cannot send files with Content-Type "
"'application/x-www-form-urlencoded'.")
if files:
... | code_fim | hard | {
"lang": "python",
"repo": "ixokai/pants",
"path": "/pants/contrib/http/client.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ixokai/pants path: /pants/contrib/http/client.py
if response_handler is not None:
if not callable(response_handler):
raise ValueError("response handler must be callable.")
self.on_response = response_handler
# Internal State
self._s... | code_fim | hard | {
"lang": "python",
"repo": "ixokai/pants",
"path": "/pants/contrib/http/client.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Camiloasc1/AlgorithmsUNAL path: /SPOJ/TSORT.py
import sys
n = input()
data = sys.stdin.read().splitlines()
sortedList = []
for i in data:
sortedList.append(int(i))
sortedList.sort()
for i in sortedList:
print i
# V2
<|fim_suffix|>import sys
raw_input()
print ... | code_fim | hard | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/SPOJ/TSORT.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sortedList.sort()
for i in sortedList:
print i
# V2
import sys
m = int(1E6 + 1)
count = [0] * m
n = int(raw_input())
for _ in xrange(n):
count[int(sys.stdin.readline())] += 1
for i in xrange(m):
# if(count[i]>0):
# print "\n".join(map(str, [i] * count[i]))
f... | code_fim | medium | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/SPOJ/TSORT.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>for i in xrange(m):
# if(count[i]>0):
# print "\n".join(map(str, [i] * count[i]))
for _ in xrange(count[i]):
print i
# V3
import sys
raw_input()
print "\n".join(map(str, sorted(map(int, sys.stdin.read().splitlines()))))<|fim_prefix|># repo: Camiloasc1/AlgorithmsUNAL pat... | code_fim | medium | {
"lang": "python",
"repo": "Camiloasc1/AlgorithmsUNAL",
"path": "/SPOJ/TSORT.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarvex/composer path: /composer/callbacks/checkpoint_saver.py
"Callback to save checkpoints.
.. note::
If the ``folder`` argument is specified when constructing the :class:`.Trainer`, then the :class:`.CheckpointSaver`
callback need not be constructed manually. However, for ... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/composer",
"path": "/composer/callbacks/checkpoint_saver.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarvex/composer path: /composer/callbacks/checkpoint_saver.py
ck): # noqa: D101
__doc__ = f"""Callback to save checkpoints.
.. note::
If the ``folder`` argument is specified when constructing the :class:`.Trainer`, then the :class:`.CheckpointSaver`
callback need not be... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/composer",
"path": "/composer/callbacks/checkpoint_saver.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> When DeepSpeed is not being used, the rank zero process will save the checkpoint to
``'awesome-training-run/checkpoints/ep1-ba42-rank0'``,
and a symlink will be created at
``'awesome-training-run/checkpoints/latest-rank0' -> 'awesome-training-run/checkpoints... | code_fim | hard | {
"lang": "python",
"repo": "sarvex/composer",
"path": "/composer/callbacks/checkpoint_saver.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>se: 2**(49-1).",
),
pytest.param(
2 ** (53 + 1),
True,
id="True case: 2**(53+1).",
),
],
)
def test_power_of_2(value: int, expected_result: bool):
"""
Passes test if `check_power_of_2`(`value`)
is equal to `expected_result`.
"... | code_fim | hard | {
"lang": "python",
"repo": "mag-id/epam_python_autumn_2020",
"path": "/homework_1/sample_project/tests/test_calculator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mag-id/epam_python_autumn_2020 path: /homework_1/sample_project/tests/test_calculator.py
"""
Unit tests for `calculator` module.
"""
import pytest
from homework_1.sample_project.calculator.calc import check_power_of_2
@pytest.mark.parametrize(
["value", "expected_result"],
[
p... | code_fim | hard | {
"lang": "python",
"repo": "mag-id/epam_python_autumn_2020",
"path": "/homework_1/sample_project/tests/test_calculator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> time_delta = 0.1
distance = calc_distance(start_point, end_point)
return distance / time_delta
def calc_distance(start_point, end_point):
distance = math.sqrt(
(start_point[0] - end_point[0]) ** 2 +
(start_point[1] - end_point[1]) ** 2 +
(start_point[2] - end_poin... | code_fim | hard | {
"lang": "python",
"repo": "goldarte/blender-csv-animation",
"path": "/addon.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for second_drone_obj in drone_objects:
if second_drone_obj is not drone_obj:
x2, y2, z2 = second_drone_obj.matrix_world.to_translation()
distance = calc_distance((x, y, z), (x2, y2, z2))
... | code_fim | hard | {
"lang": "python",
"repo": "goldarte/blender-csv-animation",
"path": "/addon.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: goldarte/blender-csv-animation path: /addon.py
import os
import csv
import math
import bpy
from bpy_extras.io_utils import ExportHelper
from bpy.types import Operator
from bpy.props import StringProperty, BoolProperty, FloatProperty, IntProperty
bl_info = {
"name": "Export > CSV Drone Swarm... | code_fim | hard | {
"lang": "python",
"repo": "goldarte/blender-csv-animation",
"path": "/addon.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mmuldo/palette-cleanser path: /tests/test_template.py
from palettecleanser import template
from palettecleanser import theme
from palettecleanser import palette
from palettecleanser import config
import yaml
import os
import jinja2 as j2
class TestTemplateFile:
def test_generate_signature_hs... | code_fim | hard | {
"lang": "python",
"repo": "mmuldo/palette-cleanser",
"path": "/tests/test_template.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> monkeypatch.setattr(os, 'environ', os.environ | {'HOME': os.path.join(os.path.dirname(__file__), 'test_data', 'fake_home')})
assert template.TemplateFile('test_template_template1').is_templated()
def test_is_templated_shebang(self, monkeypatch):
monkeypatch.setattr(os, 'enviro... | code_fim | hard | {
"lang": "python",
"repo": "mmuldo/palette-cleanser",
"path": "/tests/test_template.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ToolSvc.L1TriggerTowerTool.BaselineCorrection = _doPC
from TrigBunchCrossingTool.BunchCrossingTool import BunchCrossingTool
bct = BunchCrossingTool()
if not hasattr(ToolSvc, bct.getName()):
ToolSvc += bct
else:
bct = getattr(ToolSvc, bct.getName())
if _doPC and not hasattr(ToolSvc, 'L1Dynami... | code_fim | hard | {
"lang": "python",
"repo": "strigazi/athena",
"path": "/Trigger/TrigT1/TrigT1CaloSim/share/TrigT1CaloSimJobOptions_Run2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: strigazi/athena path: /Trigger/TrigT1/TrigT1CaloSim/share/TrigT1CaloSimJobOptions_Run2.py
# Import the configurable algorithms for TrigT1Calo
from AthenaCommon.GlobalFlags import globalflags
from AthenaCommon.Logging import logging # loads logger
log = logging.getLogger( "TrigT1CaloSimJobOption... | code_fim | hard | {
"lang": "python",
"repo": "strigazi/athena",
"path": "/Trigger/TrigT1/TrigT1CaloSim/share/TrigT1CaloSimJobOptions_Run2.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># autoconfigure pedestal correction based on the input file
if _doPC and _bunchSpacing not in (25,50):
log.warning('Only 25ns intra train bunch spacing currently supported. Dynamic pedestal correction is disabled!')
_doPC = False
ToolSvc.L1TriggerTowerTool.BaselineCorrection = _doPC
from TrigBun... | code_fim | hard | {
"lang": "python",
"repo": "strigazi/athena",
"path": "/Trigger/TrigT1/TrigT1CaloSim/share/TrigT1CaloSimJobOptions_Run2.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alanag13/adventofcode2020 path: /9_encoding_error/solution.py
from os import path
this_dir = path.dirname(path.realpath(__file__))
input_file = path.join(this_dir, "input.txt")
rolling_sum = 0
contiguous_nums = []
PART_ONE_SOLUTION = 70639851
def has_sum_pair_in_range(input_list, value, start,... | code_fim | hard | {
"lang": "python",
"repo": "alanag13/adventofcode2020",
"path": "/9_encoding_error/solution.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>with open(input_file) as f:
input_list = [int(entry.strip()) for entry in f]
for i in range(len(input_list)):
num = input_list[i]
if i > 24 and not has_sum_pair_in_range(input_list, num, i - 25, i):
print(f"Part one: {num}")
if len(contiguous_nums) > 1 ... | code_fim | hard | {
"lang": "python",
"repo": "alanag13/adventofcode2020",
"path": "/9_encoding_error/solution.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> checked = set()
for i in range(start, end):
item = input_list[i]
diff = value - item
if diff in checked:
return True
checked.add(item)
with open(input_file) as f:
input_list = [int(entry.strip()) for entry in f]
for i in range(len(input_list)):
... | code_fim | medium | {
"lang": "python",
"repo": "alanag13/adventofcode2020",
"path": "/9_encoding_error/solution.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cfalguiere/morse-challenge path: /version-9/test_node.py
import pytest
from node import NodeState, Node
@pytest.fixture
def sentence1():
sentence = '..-.--.'
return sentence
@pytest.fixture
def sentence2():
sentence = '..--'
return sentence
def test_root_node(sentence1):
... | code_fim | hard | {
"lang": "python",
"repo": "cfalguiere/morse-challenge",
"path": "/version-9/test_node.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_next_done_completed(sentence2):
# node_0 = Node('', 0, sentence2, state=NodeState.ROOT)
node_0 = Node('', 0, len(sentence2), state=NodeState.ROOT)
node_1 = Node('..', 0, len('--'), parent=node_0)
node_2 = Node('--', 2, len(''), parent=node_1)
assert node_2.is_done is True
d... | code_fim | hard | {
"lang": "python",
"repo": "cfalguiere/morse-challenge",
"path": "/version-9/test_node.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mcmero/SVclone path: /SVclone/SVprocess/svp_dtypes.py
import numpy as np
#####################################################################
# Data dtypes
#####################################################################
bp_dtype = [('chrom','<U20'),('start', int), ('end', int), ('dir', '... | code_fim | hard | {
"lang": "python",
"repo": "mcmero/SVclone",
"path": "/SVclone/SVprocess/svp_dtypes.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|># Output from count step
sv_out_dtype = [('ID', 'int64'),
('chr1', '<U20'),
('pos1', 'int64'),
('dir1', '<U1'),
('chr2', '<U20'),
('pos2', 'int64'),
('dir2', '<U1'),
('classification', '<U100'),
('split_norm1',... | code_fim | hard | {
"lang": "python",
"repo": "mcmero/SVclone",
"path": "/SVclone/SVprocess/svp_dtypes.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: romadm/LibRecommender path: /examples/pure_rating_example.py
import time
import numpy as np
import pandas as pd
from libreco.data import split_by_ratio_chrono, DatasetPure
from libreco.algorithms import SVD, SVDpp, NCF, ALS, UserCF, ItemCF, RNN4Rec
# remove unnecessary tensorflow logging
import ... | code_fim | hard | {
"lang": "python",
"repo": "romadm/LibRecommender",
"path": "/examples/pure_rating_example.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> reset_state("ALS")
als = ALS(task="rating", data_info=data_info, embed_size=16, n_epochs=2,
reg=5.0, alpha=10, seed=42)
als.fit(train_data, verbose=2, use_cg=False, n_threads=1,
eval_data=eval_data, metrics=["rmse", "mae", "r2"])
print("prediction: ", als.predict(... | code_fim | hard | {
"lang": "python",
"repo": "romadm/LibRecommender",
"path": "/examples/pure_rating_example.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: angr/rex path: /rex/utils/curl2rexaction.py
import argparse
import os
import time
import signal
import psutil
import nclib
from rex.exploit.actions import RexWaitAction, RexOpenChannelAction, RexSendAction, RexCloseChannelAction
def timeout(seconds_before_timeout):
def decorate(f):
... | code_fim | hard | {
"lang": "python",
"repo": "angr/rex",
"path": "/rex/utils/curl2rexaction.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> data = b''
while True:
try:
data += recv_once(r)
except Exception: #pylint:disable=broad-except
return data
def force_kill(r):
r.close()
proc = psutil.Process(r.pid)
for child in proc.children():
os.system("kill -9 %d" % child.pid)
o... | code_fim | hard | {
"lang": "python",
"repo": "angr/rex",
"path": "/rex/utils/curl2rexaction.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: StevenTagawa/treehouse-python-project-3 path: /logentry.py
"""
Contains the specification of a LogEntry object.
This object containing information on a single task within the
WorkLog object.
Class Definitions:
- LogEntry -- the log entry object.
Private Functi... | code_fim | hard | {
"lang": "python",
"repo": "StevenTagawa/treehouse-python-project-3",
"path": "/logentry.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def _validate_dict_entry(self, dict_entry):
"""
Validates the types of a dictionary's items.
Arguments:
- dict_entry -- the dictionary to validate.
Returns: True if the types are valid, else False.
--------------------------... | code_fim | hard | {
"lang": "python",
"repo": "StevenTagawa/treehouse-python-project-3",
"path": "/logentry.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Returns a pre-defined model by name.
Parameters
----------
name : str
Name of the model.
dataset_name : str or None, default None
The dataset name on which the pre-trained model is trained.
For language model, options are 'wikitext-2'.
For ELMo, Opti... | code_fim | hard | {
"lang": "python",
"repo": "MoisesHer/gluon-nlp",
"path": "/src/gluonnlp/model/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MoisesHer/gluon-nlp path: /src/gluonnlp/model/__init__.py
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this fil... | code_fim | hard | {
"lang": "python",
"repo": "MoisesHer/gluon-nlp",
"path": "/src/gluonnlp/model/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_model(name, **kwargs):
"""Returns a pre-defined model by name.
Parameters
----------
name : str
Name of the model.
dataset_name : str or None, default None
The dataset name on which the pre-trained model is trained.
For language model, options are 'wiki... | code_fim | hard | {
"lang": "python",
"repo": "MoisesHer/gluon-nlp",
"path": "/src/gluonnlp/model/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_initialize_post_save_double_import_error_caught(monkeypatch, caplog, capsys, jupyter_app):
"""Test that both missing nbautoexport error and missing jupyer_core are caught and properly
logged."""
real_import = __builtins__["__import__"]
def mock_import(name, globals=None, locals... | code_fim | hard | {
"lang": "python",
"repo": "Jimmy-INL/nbautoexport",
"path": "/tests/test_jupyter_config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Jimmy-INL/nbautoexport path: /tests/test_jupyter_config.py
import builtins
import logging
from pkg_resources import parse_version
from pkg_resources.extern.packaging.version import Version
import sys
import textwrap
from notebook.services.contents.filemanager import FileContentsManager
from trai... | code_fim | hard | {
"lang": "python",
"repo": "Jimmy-INL/nbautoexport",
"path": "/tests/test_jupyter_config.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def mock_import(name, globals=None, locals=None, fromlist=(), level=0):
if name == "nbautoexport":
raise ModuleNotFoundError("No module named 'nbautoexport'")
if name == "jupyter_core.application":
raise ModuleNotFoundError("No module named 'jupyter_core.applica... | code_fim | hard | {
"lang": "python",
"repo": "Jimmy-INL/nbautoexport",
"path": "/tests/test_jupyter_config.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zzerain/ppSCAN path: /paper/deprecated/scalability/scalability_figure_paper.py
import matplotlib.pyplot as plt
thread_str_lst = ['1', '4', '8', '16', '24', '32', '40']
pscan_runtime_lst = [164.248, 63.705, 2487.317, 3726.302]
def accumulate_for_bar_char(breakdown_time_lst):
for idx in xran... | code_fim | hard | {
"lang": "python",
"repo": "zzerain/ppSCAN",
"path": "/paper/deprecated/scalability/scalability_figure_paper.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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