Instruction stringlengths 362 7.83k | output_code stringlengths 1 945 |
|---|---|
Given the following code snippet before the placeholder: <|code_start|>
def refresh_info(self):
self.info = self.fetch_info()
return self.info
def commit_info(self):
if self.info:
self.cache.upload_single(
self.meta.join(self.mesh_path, 'info'),
jsonify(self.info),
conten... | return self.info['@type'] == 'neuroglancer_multilod_draco' |
Predict the next line for this snippet: <|code_start|>CredentialType = Dict[str,Union[str,int]]
CredentialCacheType = Dict[str,CredentialType]
PROJECT_NAME = default_google_project_name()
GOOGLE_CREDENTIALS_CACHE:CredentialCacheType = {}
google_credentials_path = secretpath('secrets/google-secret.json')
def google_cr... | break |
Continue the code snippet: <|code_start|> secretpath('project_name')
]
def default_google_project_name():
if 'GOOGLE_PROJECT_NAME' in os.environ:
return os.environ['GOOGLE_PROJECT_NAME']
else:
for path in project_name_paths:
if os.path.exists(path):
with open(path, 'r') as f:
ret... | if bucket in GOOGLE_CREDENTIALS_CACHE.keys(): |
Given snippet: <|code_start|>
# NOTE: Plugins are registered in __init__.py
# Set the interpreter bool
try:
INTERACTIVE = bool(sys.ps1)
except AttributeError:
INTERACTIVE = bool(sys.flags.interactive)
REGISTERED_PLUGINS = {}
def register_plugin(key, creation_function):
REGISTERED_PLUGINS[key.lower()] = creati... | CacheType = Union[bool,str] |
Next line prediction: <|code_start|>
# NOTE: Plugins are registered in __init__.py
# Set the interpreter bool
try:
INTERACTIVE = bool(sys.ps1)
except AttributeError:
<|code_end|>
. Use current file imports:
(import sys
import time
import multiprocessing as mp
import numpy as np
from typing import Optional, Union
... | INTERACTIVE = bool(sys.flags.interactive) |
Predict the next line for this snippet: <|code_start|>
# NOTE: Plugins are registered in __init__.py
# Set the interpreter bool
try:
INTERACTIVE = bool(sys.ps1)
except AttributeError:
INTERACTIVE = bool(sys.flags.interactive)
<|code_end|>
with the help of current file imports:
import sys
import time
import mu... | REGISTERED_PLUGINS = {} |
Continue the code snippet: <|code_start|> return os.path.join(
self._path.basepath, self._path.layer, file_path
)
def put_file(
self, file_path, content,
content_type, compress,
cache_control=None
):
path = self.get_path_to_file(file_path)
mkdir(os.path.dirname(path))
# keep... | f.write(content) |
Given the following code snippet before the placeholder: <|code_start|> with open(path, 'wb') as f:
f.write(content)
def get_file(self, file_path, start=None, end=None):
path = self.get_path_to_file(file_path)
if os.path.exists(path + '.gz'):
encoding = "gzip"
path += '.gz'
elif... | path = self.get_path_to_file(file_path) |
Using the snippet: <|code_start|> def __exit__(self, exception_type, exception_value, traceback):
self.release_connection()
class FileInterface(StorageInterface):
def __init__(self, path):
super(StorageInterface, self).__init__()
self._path = path
def get_path_to_file(self, file_path):
return os.... | and type(content) is str: |
Continue the code snippet: <|code_start|>
if sys.version_info < (3,):
integer_types = (int, long, np.integer)
string_types = (str, basestring, unicode)
else:
integer_types = (int, np.integer)
string_types = (str,)
floating_types = (float, np.floating)
COLORS = {
'RESET': "\033[m",
'YELLOW': "\033[1;93m"... | 'RED': '\033[1;91m', |
Here is a snippet: <|code_start|>
ExtractedPath = namedtuple('ExtractedPath',
('format', 'protocol', 'bucket', 'basepath', 'no_bucket_basepath', 'dataset', 'layer')
)
ALLOWED_PROTOCOLS = cloudfiles.paths.ALLOWED_PROTOCOLS
ALLOWED_FORMATS = [ 'graphene', 'precomputed', 'boss' ]
<|code_end|>
. Write the next line... | def cloudpath_error(cloudpath): |
Predict the next line for this snippet: <|code_start|>
retry = tenacity.retry(
reraise=True,
stop=tenacity.stop_after_attempt(7),
wait=tenacity.wait_random_exponential(0.5, 60.0),
<|code_end|>
with the help of current file imports:
from six.moves import queue as Queue
from functools import partial
from goog... | ) |
Continue the code snippet: <|code_start|>
NOTICE = {
'vertices': 0,
'num_vertices': 0,
'faces': 0,
}
def deprecation_notice(key):
<|code_end|>
. Use current file imports:
import copy
import re
import struct
import numpy as np
import DracoPy
import vtk
from .exceptions import MeshDecodeError
from .li... | if NOTICE[key] < 1: |
Next line prediction: <|code_start|> # normal_vector_map = np.vectorize(lambda idx: normals[idx])
# eff_normals = normal_vector_map(uniq_idx)
return Mesh(eff_verts, eff_faces, None,
segid=self.segid,
encoding_type=copy.deepcopy(self.encoding_type),
encoding_options=copy.deepcopy(self.enco... | Actual Bytes: {} |
Given the following code snippet before the placeholder: <|code_start|> # normal_vector_map = np.vectorize(lambda idx: normals[idx])
# eff_normals = normal_vector_map(uniq_idx)
return Mesh(eff_verts, eff_faces, None,
segid=self.segid,
encoding_type=copy.deepcopy(self.encoding_type),
encod... | Actual Bytes: {} |
Next line prediction: <|code_start|> assert a.chunks == a2.chunks
@pytest.mark.skipif(sys.version_info[0] < 3, reason="Python 2 not supported.")
def test_roundtrip_4d_channel_rechunked():
da = pytest.importorskip('dask.array')
du = pytest.importorskip('dask.utils')
a = da.random.randint(100, size=(3, 3, 3, 3)... | du = pytest.importorskip('dask.utils') |
Given snippet: <|code_start|> lru[i] = i
assert 0 < lru.nbytes <= small_int_bytes * base_size
for i in range(100):
lru[i] = i
assert 0 < lru.nbytes <= small_int_bytes * base_size
assert len(lru) == 5
lru.resize(size * 2)
for i in range(5):
lru[i] = i
assert 0 < lru.nbytes <= small_int_bytes ... | def test_lru_chaos(): |
Given snippet: <|code_start|> self.info = self.default_info()
@property
def spatial_index(self):
if 'spatial_index' in self.info:
return self.info['spatial_index']
return None
@property
def skeleton_path(self):
if 'skeletons' in self.meta.info:
return self.meta.info['skeletons']... | return self.meta.join(*paths) |
Given the following code snippet before the placeholder: <|code_start|>
def test_create_campaign():
campaign = models.Campaign('test')
campaign.put()
<|code_end|>
, predict the next line using imports from the current file:
import time
from mothership import models
and context including class names, funct... | assert campaign.id > 0
|
Given the code snippet: <|code_start|>
class CampaignForm(Form):
name = StringField('Name', validators=[validators.required()])
executable_name = StringField('Executable Name', validators=[validators.required()], default='executable')
executable_args = StringField('Executable Args', default='@@')
afl_args = Strin... | check_validate = super().validate() |
Predict the next line after this snippet: <|code_start|> return 'Campaign already has a master', 400
instance = models.FuzzerInstance.create(hostname=hostname, master=True)
instance.start_time = time.time()
campaign.fuzzers.append(instance)
campaign.commit()
# avoid all hosts uploading at the same time from... | instance.commit() |
Here is a snippet: <|code_start|> copy.desired_fuzzers = size
copy.has_dictionary = original.has_dictionary
copy.executable_name = original.executable_name
copy.executable_args = original.executable_args
copy.afl_args = original.afl_args
copy.parent_id = original.id
copy.put()
dir = os.path.join(... | return redirect(url_for('campaigns.delete', campaign_id=campaign_id)) |
Predict the next line for this snippet: <|code_start|>
def get_ldd(campaign_model):
env = dict(os.environ)
if 'LD_LIBRARY_PATH' in env:
env['LD_LIBRARY_PATH'] = ':' + env['LD_LIBRARY_PATH']
else:
env['LD_LIBRARY_PATH'] = ''
env['LD_LIBRARY_PATH'] = os.path.join(current_app.config['DATA_DIRECTORY'], secure_file... | ldd_row = (parts[0], 'danger', 'Not Found') |
Next line prediction: <|code_start|> return redirect(url_for('campaigns.campaign', campaign_id=original.id))
else:
return render_template('make-tests.html', campaign=original, form=form)
@campaigns.route('/campaigns/<int:campaign_id>', methods=['GET', 'POST'])
def campaign(campaign_id):
campaign_model = models.Ca... | child.put() |
Given snippet: <|code_start|> if form.executable.has_file():
form.executable.data.save(os.path.join(dir, 'executable'))
elif other:
shutil.copy(os.path.join(other, 'executable'), os.path.join(dir, 'executable'))
for config_files in ['libraries', 'testcases', 'ld_preload']:
dest = os.path.join(dir, config... | return redirect(request.args.get('next') or url_for('campaigns.campaign', campaign_id=model.id)) |
Predict the next line after this snippet: <|code_start|> child.put()
if 'deactivate_children' in request.form:
for child in campaign_model.children:
child.active = False
child.put()
if 'delete_children' in request.form:
for child in campaign_model.children:
delete_campaign(child)
if 'reset_ch... | 'PROBABLY_NOT_EXPLOITABLE': 3}, |
Given the code snippet: <|code_start|>
def test_davidson():
np.random.seed(0)
dim = 1000
A = np.diag(np.arange(dim,dtype=np.float64))
A[1:3,1:3] = 0
<|code_end|>
, generate the next line using the imports in this file:
import numpy as np
from mmd.utils.davidson import davidson
and context (functions... | M = np.random.randn(dim,dim) |
Based on the snippet: <|code_start|>
x, y = reshape_data(x, y)
data_scaler = StandardScaler()
x = data_scaler.fit_transform(x)
lda = LDA()
lda.fit(x, y)
coef = lda.scalings_ * lda.coef_[:1].T
channels = []
fbins = []
for c in range(n_channels):
fbins.extend(range(n_fbins)) ... | plt.bar(range(0, n_fbins), abs(coef[i * n_fbins:i * n_fbins + n_fbins])) |
Given the code snippet: <|code_start|> channels = []
fbins = []
for c in range(n_channels):
fbins.extend(range(n_fbins)) # 0- delta, 1- theta ...
channels.extend([c] * n_fbins)
if plot:
fig = plt.figure()
for i in range(n_channels):
if n_channels == 24:
... | def predict(subject, model, data_scaler, data_path, submission_path, test_labels, opt_threshold_train): |
Based on the snippet: <|code_start|> def __init__(self, rng, input, nkerns, recept_width, pool_width, stride, training_mode, dropout_prob, activation,
weights_variance, n_channels, n_timesteps, n_fbins, global_pooling):
self.layer0 = ConvPoolLayer(rng, input=input,
... | training_mode=training_mode, |
Given the code snippet: <|code_start|>
class FeatureExtractor(object):
def __init__(self, rng, input, nkerns, recept_width, pool_width, stride, training_mode, dropout_prob, activation,
weights_variance, n_channels, n_timesteps, n_fbins, global_pooling):
self.layer0 = ConvPoolLayer(rng, inp... | self.glob_pool = GlobalPoolLayer(self.layer1.output) |
Using the snippet: <|code_start|> x_train = np.concatenate(x_train, axis=3)
x_train = np.rollaxis(x_train, axis=3)
y_train = np.array(y_train)
x_valid = [x[..., np.newaxis] for x in x_valid]
x_valid = np.concatenate(x_valid, axis=3)
x_valid = np.rollaxis(x_valid, axis=3)
... | def run_trainer(): |
Continue the code snippet: <|code_start|>
def predict(model, x_test, n_test_examples, n_timesteps):
pred_1m = model.predict_proba(x_test)[:, 1]
pred_10m = np.reshape(pred_1m, (n_test_examples, n_timesteps))
pred_10m = np.mean(pred_10m, axis=1)
return pred_10m
def cross_validate(subject, data_path, re... | for i in train_indexes: |
Continue the code snippet: <|code_start|>
def curve_per_subject(subject, data_path, test_labels):
d = load_train_data(data_path, subject)
x, y_10m = d['x'], d['y']
n_train_examples = x.shape[0]
n_timesteps = x.shape[-1]
print 'n_preictal', np.sum(y_10m)
print 'n_inetrictal', np.sum(y_10m - 1)... | data_scaler = StandardScaler() |
Predict the next line after this snippet: <|code_start|>
def curve_per_subject(subject, data_path, test_labels):
d = load_train_data(data_path, subject)
x, y_10m = d['x'], d['y']
<|code_end|>
using the current file's imports:
import numpy as np
import json
import os
import matplotlib.pyplot as plt
import p... | n_train_examples = x.shape[0] |
Next line prediction: <|code_start|> d = load_test_data(data_path, subject)
x_test, id = d['x'], d['id']
n_test_examples = x_test.shape[0]
n_timesteps = x_test.shape[3]
x_test = reshape_data(x_test)
x_test = data_scaler.transform(x_test)
pred_1m = model.predict_proba(x_test)[:, 1]
pred... | if not os.path.exists(data_path): |
Given the code snippet: <|code_start|>
def train(subject, data_path, reg_C=None):
d = load_train_data(data_path, subject)
x, y = d['x'], d['y']
x, y = reshape_data(x, y)
data_scaler = StandardScaler()
x = data_scaler.fit_transform(x)
lda = LogisticRegression(C=reg_C)
lda.fit(x, y)
retur... | return pred_10m |
Continue the code snippet: <|code_start|>
def merge_csv_files(submission_path, subjects, submission_name):
print subjects
with open(submission_path + '/' + submission_name + '.csv', 'wb') as f:
writer = csv.writer(f)
writer.writerow(['clip', 'preictal'])
<|code_end|>
. Use current file imports... | for subject in subjects: |
Given snippet: <|code_start|> if 'test' in raw_file_path or 'holdout' in raw_file_path:
sequence = np.Inf
else:
sequence = d[sample][0][0][4][0][0]
new_sampling_frequency = 400
new_x = filter(x, new_sampling_frequency, data_length_sec, lowcut, highcut)
data_dict = {'data': new_x, 'd... | for subject in subjects: |
Given snippet: <|code_start|>"""Abstract Handler with helper methods."""
log = logging.getLogger('handler')
class CursorKindException(TypeError):
"""When a child node of a VAR_DECL is parsed as an initialization value,
when its not actually part of that initiwlization value."""
<|code_end|>
, continue by ... | pass |
Predict the next line after this snippet: <|code_start|> elif literal_kind == CursorKind.STRING_LITERAL:
return [TypeKind.CHAR16, TypeKind.CHAR32, TypeKind.CHAR_S,
TypeKind.SCHAR, TypeKind.WCHAR] # DEBUG
elif literal_kind == CursorKind.CHARACTER_LITERAL:
retur... | return True |
Predict the next line after this snippet: <|code_start|>
# logging.basicConfig(level=logging.DEBUG)
class StringConstantsTest(ClangTest):
"""Tests some string variations.
"""
def test_char(self):
self.convert("""
char x = 'x';
<|code_end|>
using the current file's imports:
import loggi... | char zero = 0; |
Next line prediction: <|code_start|> # include source file location in comments
generate_locations: bool = False
# do not include declaration defined outside of the source files
filter_location: bool = True
# dll to be loaded before all others (to resolve symbols)
preloaded_dlls: list = []
# ... | self.filter_location = not options.generate_includes |
Here is a snippet: <|code_start|>
class CodegenConfig:
# symbol to include, if empty, everything will be included
symbols: list = []
# regular expression for symbols to include
expressions: list = []
# verbose output
verbose: bool = False
# include source doxygen-style comments
generat... | types: list = [] |
Predict the next line after this snippet: <|code_start|> int first;
int last;
};
struct example {
int argsz;
int flags;
int count;
struct example_detail details[2];
};
''')
self.assertIn("i", py_namespace)
self.assertIn("c2", py_namespace)
self.assertIn("s... | int argsz; |
Based on the snippet: <|code_start|>
def run(args):
if hasattr(subprocess, 'run'):
p = subprocess.run(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
output, stderr = p.stdout.decode(), p.stderr.decode()
return p, output, stderr
else:
p = subprocess... | output, stderr = p.communicate() |
Using the snippet: <|code_start|> for _ in range(3):
for i in range(size*multiplier, size*(multiplier+1)):
self.assertEqual(time, func(i))
def test_on_purge(self):
test_index = 1
purges = []
@lru_cache(on_purge=lambda index: purges... | self.assertEqual(size, len(func._cache)) |
Predict the next line for this snippet: <|code_start|>########
# Copyright (c) 2016 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | 'level': 'INFO', |
Given the following code snippet before the placeholder: <|code_start|>########
# Copyright (c) 2013 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Lice... | def setUpClass(cls): |
Next line prediction: <|code_start|> self.keeper = gate_keeper.GateKeeper(
with_gate_keeper=True,
gate_keeper_bucket_size=self.bucket_size,
worker=mock.Mock())
def tearDown(self):
for q in self.keeper._current.values():
self.assertTrue(q.empty())
... | self.requests.append(request) |
Based on the snippet: <|code_start|>
def test_put_new_property_twice(self):
node = NodeInstance('instance_id', 'node_id')
node.put('key', 'value')
node.put('key', 'v')
self.assertEqual('v', node.get('key'))
props = node.runtime_properties
self.assertEqual(1, len(props... | runtime_properties={'preexisting-key': 'val'}) |
Given the code snippet: <|code_start|> node = NodeInstance('instance_id', 'node_id')
node.put('key', 'value')
node.put('key', 'v')
self.assertEqual('v', node.get('key'))
props = node.runtime_properties
self.assertEqual(1, len(props))
self.assertEqual('v', props['ke... | del(node['preexisting-key']) |
Based on the snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache... | super(TestLoggingServer, self).setUp() |
Using the snippet: <|code_start|> def test_disabled(self):
server = self._start_server(enable=False)
self.assertIsNone(server.logging_server)
self.assertIsNone(server.socket_url)
def test_handler_cache_size(self):
num_loggers = 7
cache_size = 3
server = self._star... | self.assertIsNotNone(server_handler.stream) |
Predict the next line after this snippet: <|code_start|> raise NotImplementedError()
def get_resource(self, resource_path):
with open(os.path.join(self.resources_root, resource_path)) as f:
return f.read()
def download_resource(self, resource_path, target_path=None):
if not ... | instance['version'] += 1 |
Next line prediction: <|code_start|> workflow, workflow_name, parameters, allow_custom_parameters)
return dispatch.dispatch(__cloudify_context=ctx, **merged_parameters)
def init_env(blueprint_path,
name='local',
inputs=None,
storage=None,
ignored... | resolver=resolver) |
Predict the next line after this snippet: <|code_start|> if not self.closed:
logger.warning('Error raised during record processing',
exc_info=True)
def close(self):
if not self.closed:
self.closed = True
self.sock... | @staticmethod |
Continue the code snippet: <|code_start|> if not self.closed:
logger.warning('Error raised during record processing',
exc_info=True)
def close(self):
if not self.closed:
self.closed = True
self.socket.close()
... | @staticmethod |
Predict the next line for this snippet: <|code_start|># you may not 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
# distributed under the License... | return None |
Given snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/li... | with open(conf_file_path) as conf_handle: |
Using the snippet: <|code_start|> options = ''
# BROKER_URL is held in the config to avoid the password appearing
# in ps listings
URL_TEMPLATE = \
'amqp://{username}:{password}@{hostname}:{port}/{vhost}{options}'
if config.get('cluster'):
BROKER_URL = ';'.join(URL_TEMPLATE.format(username=broker_username,
... | BROKER_URL += ';' |
Predict the next line after this snippet: <|code_start|> self.sock.bind(self.socket_url)
self.poller = zmq.Poller()
self.poller.register(self.sock, zmq.POLLIN)
def poll_and_process(self, timeout=1):
state = dict(self.poller.poll(1000 * timeout)).get(self.sock)
if not state ==... | port = port or get_unused_port() |
Given the following code snippet before the placeholder: <|code_start|>
class PathDictAccess(object):
pattern = re.compile("(.+)\[(\d+)\]")
def __init__(self, obj):
self.obj = obj
def set(self, prop_path, value):
obj, prop_name = self._get_parent_obj_prop_name_by_path(prop_path)
o... | current = current[property_name][index] |
Continue the code snippet: <|code_start|> test_event = _event('cloudify_log', level='DEBUG')
self.assertFalse(test_event.has_output)
test_event = _event('cloudify_log', level='DEBUG',
verbosity_level=event.MEDIUM_VERBOSE)
self.assertTrue(test_event.has_output)
... | message=message, |
Given the code snippet: <|code_start|> self.assertEqual(test_event.text, message)
causes = []
test_event = _event('cloudify_event',
event_type='task_failed',
message=message,
causes=causes)
self.assertEqua... | causes=causes, |
Continue the code snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.a... | target=None): |
Predict the next line for this snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | tenant=None, |
Next line prediction: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache... | max_retries=3, |
Based on the snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache... | tenant=None, |
Predict the next line after this snippet: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | max_retries=3, |
Given the following code snippet before the placeholder: <|code_start|>########
# Copyright (c) 2015 GigaSpaces Technologies Ltd. All rights reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Lice... | tenant=None, |
Predict the next line for this snippet: <|code_start|>
# from slugify import slugify_url
TOPIC_ID = "topic"
LINK_ID = "link"
class Topic(Object, RenderedTextMixin):
__mapper_args__ = {
'polymorphic_identity': TOPIC_ID
<|code_end|>
with the help of current file imports:
from beavy.models.object import O... | } |
Given the following code snippet before the placeholder: <|code_start|>
# from slugify import slugify_url
TOPIC_ID = "topic"
LINK_ID = "link"
class Topic(Object, RenderedTextMixin):
__mapper_args__ = {
<|code_end|>
, predict the next line using imports from the current file:
from beavy.models.object import Obje... | 'polymorphic_identity': TOPIC_ID |
Using the snippet: <|code_start|>
# from slugify import slugify_url
TOPIC_ID = "topic"
LINK_ID = "link"
class Topic(Object, RenderedTextMixin):
__mapper_args__ = {
'polymorphic_identity': TOPIC_ID
}
title = PayloadProperty('title')
text = PayloadProperty('text')
CAPABILITIES = [Object.C... | __mapper_args__ = { |
Next line prediction: <|code_start|>
def before_scenario(context, scenario):
benv.before_scenario(context, scenario)
context.personas = ensure_personas()
def after_scenario(context, scenario):
if getattr(context, "browser", None):
has_warnings = False
for entry in context.browser.driver.... | has_warnings = True |
Predict the next line after this snippet: <|code_start|># import os
log = logging.Logger(__name__)
BEHAVE_DEBUG_ON_ERROR = not os.getenv("CI", False)
BEHAVE_ERROR_ON_BROWSER_WARNINGS = os.getenv("BEHAVE_ERROR_ON_BROWSER_WARNINGS", not BEHAVE_DEBUG_ON_ERROR) # noqa
def before_all(context):
context.default_bro... | context.default_browser_size = (1280, 1024) |
Here is a snippet: <|code_start|># import os
log = logging.Logger(__name__)
BEHAVE_DEBUG_ON_ERROR = not os.getenv("CI", False)
BEHAVE_ERROR_ON_BROWSER_WARNINGS = os.getenv("BEHAVE_ERROR_ON_BROWSER_WARNINGS", not BEHAVE_DEBUG_ON_ERROR) # noqa
def before_all(context):
context.default_browser = os.getenv("BEHAV... | def after_all(context): |
Using the snippet: <|code_start|># , Schema, fields
class PrivateMessageSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
<|code_end|>
, determine the next line of code. You have imports:
from beavy.common.paging_schema import makePaginationSchema
from beavy.schemas.object import ObjectFi... | title = fields.String() |
Using the snippet: <|code_start|># , Schema, fields
class PrivateMessageSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
title = fields.String()
type = fields.String(attribute="discriminator")
<|code_end|>
, determine the next line of code. You have imports:
from beavy.common.pa... | class Meta: |
Given snippet: <|code_start|>
COMMENT_ID = "comment"
class CommentObject(Object, RenderedTextMixin):
__mapper_args__ = {
'polymorphic_identity': COMMENT_ID
}
CAPABILITIES = [Object.Capabilities.listed_for_activity]
in_reply_to_id = db.Column(db.Integer, db.ForeignKey("objects.id"),
... | return |
Given the code snippet: <|code_start|>
COMMENT_ID = "comment"
class CommentObject(Object, RenderedTextMixin):
__mapper_args__ = {
'polymorphic_identity': COMMENT_ID
}
CAPABILITIES = [Object.Capabilities.listed_for_activity]
in_reply_to_id = db.Column(db.Integer, db.ForeignKey("objects.id"),
... | nullable=True) |
Using the snippet: <|code_start|>
COMMENT_ID = "comment"
class CommentObject(Object, RenderedTextMixin):
__mapper_args__ = {
'polymorphic_identity': COMMENT_ID
}
CAPABILITIES = [Object.Capabilities.listed_for_activity]
in_reply_to_id = db.Column(db.Integer, db.ForeignKey("objects.id"),
... | cls.owner_id == current_user.id) |
Predict the next line for this snippet: <|code_start|># from marshmallow import Schema, fields
# class BaseLike(Schema):
# subject = fields.Nested(BaseUser)
# created_at = fields.DateTime()
# ActivityField.registry['like'] = BaseLike
class UserLike(Schema):
id = fields.Integer()
created_at = field... | return item |
Predict the next line for this snippet: <|code_start|># from marshmallow import Schema, fields
# class BaseLike(Schema):
# subject = fields.Nested(BaseUser)
# created_at = fields.DateTime()
# ActivityField.registry['like'] = BaseLike
class UserLike(Schema):
id = fields.Integer()
created_at = field... | for key in self.REMAP_TUPLE_KEYS: |
Given the code snippet: <|code_start|># , Schema, fields
class CommentSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
text = fields.String(attribute='cooked')
belongs_to_id = fields.Integer()
... | url_kwargs={'user_id': '<owner_id>'}, |
Here is a snippet: <|code_start|># , Schema, fields
class CommentSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
text = fields.String(attribute='cooked')
belongs_to_id = fields.Integer()
in_re... | comment = CommentSchema() |
Given snippet: <|code_start|># , Schema, fields
class CommentSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
text = fields.String(attribute='cooked')
belongs_to_id = fields.Integer()
<|code_end|>
... | in_reply_to_id = fields.Integer() |
Given snippet: <|code_start|># , Schema, fields
class CommentSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
<|code_end|>
, continue by predicting the next line. Consider current file imports:
from beavy... | text = fields.String(attribute='cooked') |
Using the snippet: <|code_start|>
class TopicSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
title = fields.String(attribute='title')
slug = fields.String(attribute='slug')
text = fields.String(... | type = fields.String(attribute="discriminator") |
Predict the next line for this snippet: <|code_start|># , Schema, fields
class TopicSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
title = fields.String(attribute='title')
slug = fields.String(at... | class Meta: |
Based on the snippet: <|code_start|># , Schema, fields
class TopicSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
title = fields.String(attribute='title')
slug = fields.String(attribute='slug')
... | type_='user') |
Using the snippet: <|code_start|>class TopicSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
title = fields.String(attribute='title')
slug = fields.String(attribute='slug')
text = fields.String(at... | slug = fields.String(attribute='slug') |
Given the code snippet: <|code_start|># , Schema, fields
class TopicSchema(Schema):
id = fields.Integer()
created_at = fields.DateTime()
owner_id = fields.Integer()
type = fields.String(attribute="discriminator")
title = fields.String(attribute='title')
slug = fields.String(attribute='slug')
... | class Meta: |
Based on the snippet: <|code_start|>
# Define models
roles_users = db.Table('roles_users',
db.Column('user_id',
db.Integer(),
db.ForeignKey('user.id'),
<|code_end|>
, predict the immediate next line with the help of imports:
from ... | nullable=False), |
Given the code snippet: <|code_start|>
class ObjectQuery(AccessQuery):
def by_capability(self, aborting=True, abort_code=404, *caps):
caps = set(chain.from_iterable(map(lambda c:
getattr(Object.TypesForCapability,
... | my_activities = aliased(Activity.query.filter( |
Given the following code snippet before the placeholder: <|code_start|>
class ObjectQuery(AccessQuery):
def by_capability(self, aborting=True, abort_code=404, *caps):
caps = set(chain.from_iterable(map(lambda c:
getattr(Object.TypesForCapability,
... | if aborting: |
Given snippet: <|code_start|>
PM_ID = "private_message"
# Define models
PMParticipants = db.Table('{}_participants'.format(PM_ID),
db.Column('user_id',
db.Integer(),
db.ForeignKey(User.id),
<|code_end|>
, continue by pr... | nullable=False), |
Predict the next line for this snippet: <|code_start|>
PM_ID = "private_message"
# Define models
PMParticipants = db.Table('{}_participants'.format(PM_ID),
db.Column('user_id',
db.Integer(),
db.ForeignKey(User.id),
... | lazy='dynamic')) |
Next line prediction: <|code_start|>
PM_ID = "private_message"
# Define models
PMParticipants = db.Table('{}_participants'.format(PM_ID),
db.Column('user_id',
db.Integer(),
db.ForeignKey(User.id),
... | nullable=False)) |
Based on the snippet: <|code_start|>
PM_ID = "private_message"
# Define models
PMParticipants = db.Table('{}_participants'.format(PM_ID),
db.Column('user_id',
db.Integer(),
db.ForeignKey(User.id),
<|code_end|>
, predict... | nullable=False), |
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