blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c12917949c5cb349cdd7d91554b4297b4bb23946 | [
"if not date == None:\n date = '%sT%sZ' % (date, time)\nreturn date",
"if not datetime == None and 'T' in datetime:\n datetime = datetime.split('T')[0]\nreturn datetime"
] | <|body_start_0|>
if not date == None:
date = '%sT%sZ' % (date, time)
return date
<|end_body_0|>
<|body_start_1|>
if not datetime == None and 'T' in datetime:
datetime = datetime.split('T')[0]
return datetime
<|end_body_1|>
| StringExtensions | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringExtensions:
def convertDateStrToDateTimeStr(date, time='00:00:00'):
"""Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Args: date: the date as a string to be converted time: the time as a string to be added to the date Returns... | stack_v2_sparse_classes_75kplus_train_006500 | 1,907 | permissive | [
{
"docstring": "Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Args: date: the date as a string to be converted time: the time as a string to be added to the date Returns: A string representation of a datetime in the following format YYYY-MM-DDTHH:mm:SSZ"... | 2 | stack_v2_sparse_classes_30k_train_031100 | Implement the Python class `StringExtensions` described below.
Class description:
Implement the StringExtensions class.
Method signatures and docstrings:
- def convertDateStrToDateTimeStr(date, time='00:00:00'): Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Ar... | Implement the Python class `StringExtensions` described below.
Class description:
Implement the StringExtensions class.
Method signatures and docstrings:
- def convertDateStrToDateTimeStr(date, time='00:00:00'): Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Ar... | b596df09c52511e2e0c0987f6245aa4607190dd0 | <|skeleton|>
class StringExtensions:
def convertDateStrToDateTimeStr(date, time='00:00:00'):
"""Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Args: date: the date as a string to be converted time: the time as a string to be added to the date Returns... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StringExtensions:
def convertDateStrToDateTimeStr(date, time='00:00:00'):
"""Convert Date string (YYYY-MM-DD) to a datetime string by adding the desired time (YYYY-MM-DDTHH:mm:SSZ) Args: date: the date as a string to be converted time: the time as a string to be added to the date Returns: A string rep... | the_stack_v2_python_sparse | starthinker/task/traffic/class_extensions.py | google/starthinker | train | 167 | |
cd56e733ef5b7c29119fd0b11d7a53d602a2a9df | [
"print()\n_cred = {'username': input('Username: '), 'password': getpass.getpass('Password: '), 'cred_type': input('Credential Type: ')}\nmanage.add_device_cred(_cred)",
"if len(manage.get_device_creds()) == 0:\n print('No device credentials stored.')\nelse:\n print()\n DeleteDeviceCred().cmdloop()\n p... | <|body_start_0|>
print()
_cred = {'username': input('Username: '), 'password': getpass.getpass('Password: '), 'cred_type': input('Credential Type: ')}
manage.add_device_cred(_cred)
<|end_body_0|>
<|body_start_1|>
if len(manage.get_device_creds()) == 0:
print('No device crede... | ModifyDevice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifyDevice:
def do_1(self, args):
"""Add a device credential to secure storage"""
<|body_0|>
def do_2(self, args):
"""Delete a credential"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print()
_cred = {'username': input('Username: '), 'pa... | stack_v2_sparse_classes_75kplus_train_006501 | 3,458 | no_license | [
{
"docstring": "Add a device credential to secure storage",
"name": "do_1",
"signature": "def do_1(self, args)"
},
{
"docstring": "Delete a credential",
"name": "do_2",
"signature": "def do_2(self, args)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019579 | Implement the Python class `ModifyDevice` described below.
Class description:
Implement the ModifyDevice class.
Method signatures and docstrings:
- def do_1(self, args): Add a device credential to secure storage
- def do_2(self, args): Delete a credential | Implement the Python class `ModifyDevice` described below.
Class description:
Implement the ModifyDevice class.
Method signatures and docstrings:
- def do_1(self, args): Add a device credential to secure storage
- def do_2(self, args): Delete a credential
<|skeleton|>
class ModifyDevice:
def do_1(self, args):
... | a26ed281f72ea6f2f5e197684f540f65102024ee | <|skeleton|>
class ModifyDevice:
def do_1(self, args):
"""Add a device credential to secure storage"""
<|body_0|>
def do_2(self, args):
"""Delete a credential"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModifyDevice:
def do_1(self, args):
"""Add a device credential to secure storage"""
print()
_cred = {'username': input('Username: '), 'password': getpass.getpass('Password: '), 'cred_type': input('Credential Type: ')}
manage.add_device_cred(_cred)
def do_2(self, args):
... | the_stack_v2_python_sparse | netcrawl/credentials/menu.py | jhinckley/netcrawl | train | 0 | |
686077756fe8211cb66acc1786fae01a1d389c00 | [
"self.graph = tf.Graph()\ngraph_def = None\nwith tf.gfile.GFile(FROZEN_GRAPH_NAME, 'rb') as f:\n print(FROZEN_GRAPH_NAME)\n graph_def = tf.GraphDef().FromString(f.read())\nif graph_def is None:\n raise RuntimeError('Cannot find inference graph in tar archive.')\nwith self.graph.as_default():\n tf.import... | <|body_start_0|>
self.graph = tf.Graph()
graph_def = None
with tf.gfile.GFile(FROZEN_GRAPH_NAME, 'rb') as f:
print(FROZEN_GRAPH_NAME)
graph_def = tf.GraphDef().FromString(f.read())
if graph_def is None:
raise RuntimeError('Cannot find inference graph i... | Class to load deeplab model and run inference. | SgmtModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SgmtModel:
"""Class to load deeplab model and run inference."""
def __init__(self):
"""Creates and loads pretrained deeplab model."""
<|body_0|>
def run(self, image):
"""Runs inference on a single image. Args: image: A PIL.Image object, raw input image. Returns: ... | stack_v2_sparse_classes_75kplus_train_006502 | 2,761 | permissive | [
{
"docstring": "Creates and loads pretrained deeplab model.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Runs inference on a single image. Args: image: A PIL.Image object, raw input image. Returns: resized_image: RGB image resized from original input image. seg_map:... | 2 | null | Implement the Python class `SgmtModel` described below.
Class description:
Class to load deeplab model and run inference.
Method signatures and docstrings:
- def __init__(self): Creates and loads pretrained deeplab model.
- def run(self, image): Runs inference on a single image. Args: image: A PIL.Image object, raw i... | Implement the Python class `SgmtModel` described below.
Class description:
Class to load deeplab model and run inference.
Method signatures and docstrings:
- def __init__(self): Creates and loads pretrained deeplab model.
- def run(self, image): Runs inference on a single image. Args: image: A PIL.Image object, raw i... | fba29e142e3ef628c6b9b09cbb3b49cbc0828c8a | <|skeleton|>
class SgmtModel:
"""Class to load deeplab model and run inference."""
def __init__(self):
"""Creates and loads pretrained deeplab model."""
<|body_0|>
def run(self, image):
"""Runs inference on a single image. Args: image: A PIL.Image object, raw input image. Returns: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SgmtModel:
"""Class to load deeplab model and run inference."""
def __init__(self):
"""Creates and loads pretrained deeplab model."""
self.graph = tf.Graph()
graph_def = None
with tf.gfile.GFile(FROZEN_GRAPH_NAME, 'rb') as f:
print(FROZEN_GRAPH_NAME)
... | the_stack_v2_python_sparse | workspace/seg/infer_utils/inference_gpu.py | huangxf14/models | train | 0 |
3d70a69127c57de607b4d136373576ac5ddf0e2f | [
"bounds = {}\nfor c in self.chunks:\n bounds[c.chunk_idx[-1]] = c.chunk_size[-1]\nreturn bounds",
"offsets = {}\no = 0\nfor c in self.chunks:\n for i, s in zip(c.chunk_idx, c.chunk_size):\n offsets[i] = o\n o += s\nreturn offsets"
] | <|body_start_0|>
bounds = {}
for c in self.chunks:
bounds[c.chunk_idx[-1]] = c.chunk_size[-1]
return bounds
<|end_body_0|>
<|body_start_1|>
offsets = {}
o = 0
for c in self.chunks:
for i, s in zip(c.chunk_idx, c.chunk_size):
offset... | ChunkInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChunkInfo:
def get_contig_chunk_boundary(self):
"""Get index in last chunk for each contig keyed by chunk index"""
<|body_0|>
def get_chunk_offset(self):
"""Get global offset for first row index in each chunk keyed by chunk index"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_75kplus_train_006503 | 10,548 | permissive | [
{
"docstring": "Get index in last chunk for each contig keyed by chunk index",
"name": "get_contig_chunk_boundary",
"signature": "def get_contig_chunk_boundary(self)"
},
{
"docstring": "Get global offset for first row index in each chunk keyed by chunk index",
"name": "get_chunk_offset",
... | 2 | stack_v2_sparse_classes_30k_train_041294 | Implement the Python class `ChunkInfo` described below.
Class description:
Implement the ChunkInfo class.
Method signatures and docstrings:
- def get_contig_chunk_boundary(self): Get index in last chunk for each contig keyed by chunk index
- def get_chunk_offset(self): Get global offset for first row index in each ch... | Implement the Python class `ChunkInfo` described below.
Class description:
Implement the ChunkInfo class.
Method signatures and docstrings:
- def get_contig_chunk_boundary(self): Get index in last chunk for each contig keyed by chunk index
- def get_chunk_offset(self): Get global offset for first row index in each ch... | c3e8fbc3dff1d25109b01a62fc372555306ecbb3 | <|skeleton|>
class ChunkInfo:
def get_contig_chunk_boundary(self):
"""Get index in last chunk for each contig keyed by chunk index"""
<|body_0|>
def get_chunk_offset(self):
"""Get global offset for first row index in each chunk keyed by chunk index"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChunkInfo:
def get_contig_chunk_boundary(self):
"""Get index in last chunk for each contig keyed by chunk index"""
bounds = {}
for c in self.chunks:
bounds[c.chunk_idx[-1]] = c.chunk_size[-1]
return bounds
def get_chunk_offset(self):
"""Get global offse... | the_stack_v2_python_sparse | src/python/gwas_analysis/method/pruning.py | related-sciences/gwas-analysis | train | 23 | |
8fec4badf95c2f7b4425935763445afdab6cfb5e | [
"if lazy_numer is None:\n self.lazy_numer = int(np.sqrt(points_number))\nelse:\n self.lazy_numer = lazy_numer\nsuper().__init__(points_number, neighborhood_radius, 1, dist_func_points, net_dist_to_lr, points_to_aprox, self.lazy_numer)\nself.lr = lr",
"def dist_from_point(p):\n return self.dist_points(poi... | <|body_start_0|>
if lazy_numer is None:
self.lazy_numer = int(np.sqrt(points_number))
else:
self.lazy_numer = lazy_numer
super().__init__(points_number, neighborhood_radius, 1, dist_func_points, net_dist_to_lr, points_to_aprox, self.lazy_numer)
self.lr = lr
<|end_... | Implementation neuron gas | Neuron_gas | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Neuron_gas:
"""Implementation neuron gas"""
def __init__(self, points_number, points_to_aprox, neighborhood_radius=2, net_dist_to_lr=GNF, dist_func_points=E_dist, lazy_numer=None, lr=0.2):
"""Args: points_number: number of points to approximate dinm_network: number of dimensions of n... | stack_v2_sparse_classes_75kplus_train_006504 | 2,811 | no_license | [
{
"docstring": "Args: points_number: number of points to approximate dinm_network: number of dimensions of network organization dist_func: callable object that takes two points of from points_to_aprox and returns distance between them net_dist_to_lr: callable object that takes poison of two neurons and returns ... | 2 | null | Implement the Python class `Neuron_gas` described below.
Class description:
Implementation neuron gas
Method signatures and docstrings:
- def __init__(self, points_number, points_to_aprox, neighborhood_radius=2, net_dist_to_lr=GNF, dist_func_points=E_dist, lazy_numer=None, lr=0.2): Args: points_number: number of poin... | Implement the Python class `Neuron_gas` described below.
Class description:
Implementation neuron gas
Method signatures and docstrings:
- def __init__(self, points_number, points_to_aprox, neighborhood_radius=2, net_dist_to_lr=GNF, dist_func_points=E_dist, lazy_numer=None, lr=0.2): Args: points_number: number of poin... | 2609bf83e00e1d8773f127e10d9c140341397554 | <|skeleton|>
class Neuron_gas:
"""Implementation neuron gas"""
def __init__(self, points_number, points_to_aprox, neighborhood_radius=2, net_dist_to_lr=GNF, dist_func_points=E_dist, lazy_numer=None, lr=0.2):
"""Args: points_number: number of points to approximate dinm_network: number of dimensions of n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Neuron_gas:
"""Implementation neuron gas"""
def __init__(self, points_number, points_to_aprox, neighborhood_radius=2, net_dist_to_lr=GNF, dist_func_points=E_dist, lazy_numer=None, lr=0.2):
"""Args: points_number: number of points to approximate dinm_network: number of dimensions of network organi... | the_stack_v2_python_sparse | Zadanie2/SOM/Neuron_gas.py | PatrykLisik/iad | train | 0 |
7bc512d873d6e52dd5e690bb4b66510bbe69286a | [
"log.debug('setting up')\ncls.extractors = LyricsExtractor.extractors\nlog.info('loaded {} extractors'.format(len(cls.extractors)))",
"log.info('extracting lyrics from url \"{}\"'.format(url))\nurl_data = UrlData(url)\nfor extractor in cls.extractors:\n if not extractor.can_handle(url_data):\n continue\... | <|body_start_0|>
log.debug('setting up')
cls.extractors = LyricsExtractor.extractors
log.info('loaded {} extractors'.format(len(cls.extractors)))
<|end_body_0|>
<|body_start_1|>
log.info('extracting lyrics from url "{}"'.format(url))
url_data = UrlData(url)
for extractor... | Manage stuff. | LyricsManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LyricsManager:
"""Manage stuff."""
def setup(cls):
"""Initialize class."""
<|body_0|>
def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyrics:
"""Extract lyrics from url."""
<|body_1|>
def search_lyrics(cls, song: str, album: str, artist:... | stack_v2_sparse_classes_75kplus_train_006505 | 3,433 | permissive | [
{
"docstring": "Initialize class.",
"name": "setup",
"signature": "def setup(cls)"
},
{
"docstring": "Extract lyrics from url.",
"name": "extract_lyrics",
"signature": "def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyrics"
},
{
"docstring": "Search the net for lyri... | 3 | stack_v2_sparse_classes_30k_train_039524 | Implement the Python class `LyricsManager` described below.
Class description:
Manage stuff.
Method signatures and docstrings:
- def setup(cls): Initialize class.
- def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyrics: Extract lyrics from url.
- def search_lyrics(cls, song: str, album: str, artist: str... | Implement the Python class `LyricsManager` described below.
Class description:
Manage stuff.
Method signatures and docstrings:
- def setup(cls): Initialize class.
- def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyrics: Extract lyrics from url.
- def search_lyrics(cls, song: str, album: str, artist: str... | e8836c23b7b7e43661b59afd1bfc18d381b95d4a | <|skeleton|>
class LyricsManager:
"""Manage stuff."""
def setup(cls):
"""Initialize class."""
<|body_0|>
def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyrics:
"""Extract lyrics from url."""
<|body_1|>
def search_lyrics(cls, song: str, album: str, artist:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LyricsManager:
"""Manage stuff."""
def setup(cls):
"""Initialize class."""
log.debug('setting up')
cls.extractors = LyricsExtractor.extractors
log.info('loaded {} extractors'.format(len(cls.extractors)))
def extract_lyrics(cls, url: str, song: str, artist: str) -> Lyr... | the_stack_v2_python_sparse | wiki_music/external_libraries/lyricsfinder/lyrics.py | marian-code/wikipedia-music-tags | train | 13 |
7e211fd2c0414dcfea889002ba45d2d8c6c78b07 | [
"ret_data = []\nfunction_query = FunctionGenerator.extend()\nname = self.get_argument('name', None)\nif name is not None:\n function_query = function_query.filter(FunctionGenerator.name == name)\nfunction_query = function_query.order_by(FunctionGenerator.add_time.desc())\nfunctions = await self.application.objec... | <|body_start_0|>
ret_data = []
function_query = FunctionGenerator.extend()
name = self.get_argument('name', None)
if name is not None:
function_query = function_query.filter(FunctionGenerator.name == name)
function_query = function_query.order_by(FunctionGenerator.add... | FunctionHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionHandler:
async def get(self, *args, **kwargs):
"""获取内置函数列表"""
<|body_0|>
async def post(self, *args, **kwargs):
"""增加内置函数数据"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret_data = []
function_query = FunctionGenerator.extend()
... | stack_v2_sparse_classes_75kplus_train_006506 | 17,374 | permissive | [
{
"docstring": "获取内置函数列表",
"name": "get",
"signature": "async def get(self, *args, **kwargs)"
},
{
"docstring": "增加内置函数数据",
"name": "post",
"signature": "async def post(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025241 | Implement the Python class `FunctionHandler` described below.
Class description:
Implement the FunctionHandler class.
Method signatures and docstrings:
- async def get(self, *args, **kwargs): 获取内置函数列表
- async def post(self, *args, **kwargs): 增加内置函数数据 | Implement the Python class `FunctionHandler` described below.
Class description:
Implement the FunctionHandler class.
Method signatures and docstrings:
- async def get(self, *args, **kwargs): 获取内置函数列表
- async def post(self, *args, **kwargs): 增加内置函数数据
<|skeleton|>
class FunctionHandler:
async def get(self, *args... | dc9b4c55f0b3ace180c30b7f080eb5d88bb38fdb | <|skeleton|>
class FunctionHandler:
async def get(self, *args, **kwargs):
"""获取内置函数列表"""
<|body_0|>
async def post(self, *args, **kwargs):
"""增加内置函数数据"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FunctionHandler:
async def get(self, *args, **kwargs):
"""获取内置函数列表"""
ret_data = []
function_query = FunctionGenerator.extend()
name = self.get_argument('name', None)
if name is not None:
function_query = function_query.filter(FunctionGenerator.name == name)... | the_stack_v2_python_sparse | apps/project/handlers.py | xiaoxiaolulu/MagicTestPlatform | train | 5 | |
8df120006538e72e8e7e248f5befec826cb4d276 | [
"self.application_parameters = application_parameters\nself.excluded_disks = excluded_disks\nself.vm_credentials = vm_credentials",
"if dictionary is None:\n return None\napplication_parameters = cohesity_management_sdk.models.application_parameters.ApplicationParameters.from_dictionary(dictionary.get('applica... | <|body_start_0|>
self.application_parameters = application_parameters
self.excluded_disks = excluded_disks
self.vm_credentials = vm_credentials
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
application_parameters = cohesity_management_sdk.models.... | Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Specifies parameters that are related to applications running on the Protection Source. exclu... | VmwareSpecialParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VmwareSpecialParameters:
"""Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Specifies parameters that are related to a... | stack_v2_sparse_classes_75kplus_train_006507 | 3,395 | permissive | [
{
"docstring": "Constructor for the VmwareSpecialParameters class",
"name": "__init__",
"signature": "def __init__(self, application_parameters=None, excluded_disks=None, vm_credentials=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A... | 2 | stack_v2_sparse_classes_30k_train_035191 | Implement the Python class `VmwareSpecialParameters` described below.
Class description:
Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Spe... | Implement the Python class `VmwareSpecialParameters` described below.
Class description:
Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Spe... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VmwareSpecialParameters:
"""Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Specifies parameters that are related to a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VmwareSpecialParameters:
"""Implementation of the 'VmwareSpecialParameters' model. Specifies additional special settings applicable for a Protection Source of 'kVMware' type in a Protection Job. Attributes: application_parameters (ApplicationParameters): Specifies parameters that are related to applications r... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vmware_special_parameters.py | cohesity/management-sdk-python | train | 24 |
271a9b156211331a53efbf7d15818f3d1f9835e2 | [
"Reference.__init__(self, reference_tokens)\nself.n = n\nself._reference_length = len(self._reference_tokens)\nself._reference_ngrams = self._get_ngrams(self._reference_tokens, self.n)",
"n_grams = []\nfor n in range(1, max_n + 1):\n n_grams.append(defaultdict(int))\n for n_gram in zip(*[tokens[i:] for i in... | <|body_start_0|>
Reference.__init__(self, reference_tokens)
self.n = n
self._reference_length = len(self._reference_tokens)
self._reference_ngrams = self._get_ngrams(self._reference_tokens, self.n)
<|end_body_0|>
<|body_start_1|>
n_grams = []
for n in range(1, max_n + 1)... | Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014). | SentenceBleuReference | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must ... | stack_v2_sparse_classes_75kplus_train_006508 | 3,952 | permissive | [
{
"docstring": "@param reference the reference translation that hypotheses shall be scored against. Must be an iterable of tokens (any type). @param n maximum n-gram order to consider.",
"name": "__init__",
"signature": "def __init__(self, reference_tokens, n=4)"
},
{
"docstring": "Extracts all ... | 3 | stack_v2_sparse_classes_30k_train_032069 | Implement the Python class `SentenceBleuReference` described below.
Class description:
Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014).
Method signatures and docstrings:
- def __init__(self, reference_tokens, n=4): @param reference the reference t... | Implement the Python class `SentenceBleuReference` described below.
Class description:
Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014).
Method signatures and docstrings:
- def __init__(self, reference_tokens, n=4): @param reference the reference t... | 49d050863bc9644b8c0a9d9ab6e54ccd30f927dd | <|skeleton|>
class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SentenceBleuReference:
"""Smoothed sentence-level BLEU as as proposed by Lin and Och (2004). Implemented as described in (Chen and Cherry, 2014)."""
def __init__(self, reference_tokens, n=4):
"""@param reference the reference translation that hypotheses shall be scored against. Must be an iterabl... | the_stack_v2_python_sparse | nematus/metrics/sentence_bleu.py | EdinburghNLP/nematus | train | 598 |
99f68a678806e1e4b77a8e876c5ff2e7165a1ac3 | [
"if not data:\n return ''\nreturn data[0].upper() + data[1:]",
"if not data:\n return ''\nreturn data[0].lower() + data[1:]",
"isContains = False\nfor data in dataList:\n if data in srcStr:\n isContains = True\n break\nreturn isContains"
] | <|body_start_0|>
if not data:
return ''
return data[0].upper() + data[1:]
<|end_body_0|>
<|body_start_1|>
if not data:
return ''
return data[0].lower() + data[1:]
<|end_body_1|>
<|body_start_2|>
isContains = False
for data in dataList:
... | StrUtil | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StrUtil:
def capitalize(data: str):
"""将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value"""
<|body_0|>
def decapitalize(data: str):
"""将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value"""
<|body_1|>
def containsStr(srcStr: str, dataList: []):
... | stack_v2_sparse_classes_75kplus_train_006509 | 1,488 | permissive | [
{
"docstring": "将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value",
"name": "capitalize",
"signature": "def capitalize(data: str)"
},
{
"docstring": "将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value",
"name": "decapitalize",
"signature": "def decapitalize(data: str)"
},
{
... | 3 | stack_v2_sparse_classes_30k_test_001368 | Implement the Python class `StrUtil` described below.
Class description:
Implement the StrUtil class.
Method signatures and docstrings:
- def capitalize(data: str): 将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value
- def decapitalize(data: str): 将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value
- def contains... | Implement the Python class `StrUtil` described below.
Class description:
Implement the StrUtil class.
Method signatures and docstrings:
- def capitalize(data: str): 将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value
- def decapitalize(data: str): 将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value
- def contains... | 24cca5e9aaa56392200da48a1692201e2dfa25c8 | <|skeleton|>
class StrUtil:
def capitalize(data: str):
"""将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value"""
<|body_0|>
def decapitalize(data: str):
"""将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value"""
<|body_1|>
def containsStr(srcStr: str, dataList: []):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StrUtil:
def capitalize(data: str):
"""将字符串的首字母大写，其余字母大小写不变 :param data: data :return: value"""
if not data:
return ''
return data[0].upper() + data[1:]
def decapitalize(data: str):
"""将字符串的首字母小写，其余字母大小写不变 :param data: data :return: value"""
if not data... | the_stack_v2_python_sparse | util/StrUtil.py | lkl22/CommonTools | train | 2 | |
55a8d31018ec74d8722fc0afe894a7a192e2d665 | [
"audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)\nif audit['submitted'] == True:\n abort(400, 'Already submitted')\nif audit['approved'] == True:\n abort(400, 'Already approved by administrator(s)')\nschema = AuditUpdateSchema(only=['submitted', 'rejected_reason'])\... | <|body_start_0|>
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == True:
abort(400, 'Already approved by administrator(s)')
schema = Au... | AuditSubmission | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
audit = AuditResou... | stack_v2_sparse_classes_75kplus_train_006510 | 18,857 | no_license | [
{
"docstring": "Submit the specified audit result",
"name": "post",
"signature": "def post(self, audit_uuid)"
},
{
"docstring": "Withdraw the submission of the specified audit result",
"name": "delete",
"signature": "def delete(self, audit_uuid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025930 | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result
<|skeleton|>
cl... | 7b67aa682d73c8a8d7f0f19b2a90e69c40761c58 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == Tr... | the_stack_v2_python_sparse | rem/apis/audit.py | recruit-tech/casval | train | 6 | |
44214eb762ef6d852b2e1ceef7aa03f16498991e | [
"update = np.random.random(size=(size,))\nshp = update[update <= heading_update_chance].shape\npersons[:, idx.x_dir][update <= heading_update_chance] = np.random.normal(loc=0, scale=1 / 3, size=shp)\nupdate = np.random.random(size=(size,))\nshp = update[update <= heading_update_chance].shape\npersons[:, idx.y_dir][... | <|body_start_0|>
update = np.random.random(size=(size,))
shp = update[update <= heading_update_chance].shape
persons[:, idx.x_dir][update <= heading_update_chance] = np.random.normal(loc=0, scale=1 / 3, size=shp)
update = np.random.random(size=(size,))
shp = update[update <= head... | Class providing abstraction into each movement of the population | Movement | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Movement:
"""Class providing abstraction into each movement of the population"""
def update_persons(self, persons: np.ndarray, size: int, speed: float=0.1, heading_update_chance: float=0.02) -> np.ndarray:
"""Randomly updates/initializes the destination each person is headed to and c... | stack_v2_sparse_classes_75kplus_train_006511 | 6,071 | permissive | [
{
"docstring": "Randomly updates/initializes the destination each person is headed to and corresponding speed randomly. Parameters ---------- person : np.ndarray The NumPy array containing the details of the persons to be updated. size : int The size of the array of the persons to be updated to. speed : float, ... | 3 | null | Implement the Python class `Movement` described below.
Class description:
Class providing abstraction into each movement of the population
Method signatures and docstrings:
- def update_persons(self, persons: np.ndarray, size: int, speed: float=0.1, heading_update_chance: float=0.02) -> np.ndarray: Randomly updates/i... | Implement the Python class `Movement` described below.
Class description:
Class providing abstraction into each movement of the population
Method signatures and docstrings:
- def update_persons(self, persons: np.ndarray, size: int, speed: float=0.1, heading_update_chance: float=0.02) -> np.ndarray: Randomly updates/i... | d07994136163918858773afc10c6651a03418adc | <|skeleton|>
class Movement:
"""Class providing abstraction into each movement of the population"""
def update_persons(self, persons: np.ndarray, size: int, speed: float=0.1, heading_update_chance: float=0.02) -> np.ndarray:
"""Randomly updates/initializes the destination each person is headed to and c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Movement:
"""Class providing abstraction into each movement of the population"""
def update_persons(self, persons: np.ndarray, size: int, speed: float=0.1, heading_update_chance: float=0.02) -> np.ndarray:
"""Randomly updates/initializes the destination each person is headed to and corresponding ... | the_stack_v2_python_sparse | src/movements.py | mnk400/viral-diseases-simulator | train | 1 |
5ab8cb16aebe6f89bbcb22ab72f9a1e6c967bda0 | [
"self.trie = Trie()\nfor sentence, time in zip(sentences, times):\n self.trie.update_sentence(sentence, time)\nself.cur_trie_node = self.trie.root\nself.prefix = []",
"if c == '#':\n self.trie.update_sentence(self.prefix, 1)\n self.cur_trie_node = self.trie.root\n self.prefix = []\n return []\nelse... | <|body_start_0|>
self.trie = Trie()
for sentence, time in zip(sentences, times):
self.trie.update_sentence(sentence, time)
self.cur_trie_node = self.trie.root
self.prefix = []
<|end_body_0|>
<|body_start_1|>
if c == '#':
self.trie.update_sentence(self.pre... | AutocompleteSystem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.trie = Trie()
... | stack_v2_sparse_classes_75kplus_train_006512 | 2,164 | permissive | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | null | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | ba84c192fb9995dd48ddc6d81c3153488dd3c698 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.trie = Trie()
for sentence, time in zip(sentences, times):
self.trie.update_sentence(sentence, time)
self.cur_trie_node = self.trie.root
se... | the_stack_v2_python_sparse | Python/design-search-autocomplete-system.py | phucle2411/LeetCode | train | 0 | |
777924f2d7a53dedcb1d6ba16df62fb98e77ae7a | [
"super().__init__(pred_name, target_name, filter_func=filter_func, use_sample_weights=use_sample_weights, sample_weight_name=sample_weight_name)\nself._class_names = class_names\nself.metric_func = metric_func",
"results = {}\naucs_per_class = []\nif self._class_names is None:\n num_classes = self.collected_da... | <|body_start_0|>
super().__init__(pred_name, target_name, filter_func=filter_func, use_sample_weights=use_sample_weights, sample_weight_name=sample_weight_name)
self._class_names = class_names
self.metric_func = metric_func
<|end_body_0|>
<|body_start_1|>
results = {}
aucs_per_c... | Applying a given metric function | FuseMetricDefault | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FuseMetricDefault:
"""Applying a given metric function"""
def __init__(self, metric_func: Callable, pred_name: str, target_name: str, class_names: Optional[str]=None, filter_func: Optional[Callable]=None, use_sample_weights: Optional[bool]=False, sample_weight_name: Optional[str]=None) -> No... | stack_v2_sparse_classes_75kplus_train_006513 | 6,058 | permissive | [
{
"docstring": ":param metric_func: metric function. Will be applied for each class in a one-vs-rest manner. Gets as an input y_true (a boolean np.ndarray), y_score and sample_weight. :param pred_name: batch_dict key for predicted output (e.g., class probabilities after softmax) :param target_name: batch_dict k... | 2 | null | Implement the Python class `FuseMetricDefault` described below.
Class description:
Applying a given metric function
Method signatures and docstrings:
- def __init__(self, metric_func: Callable, pred_name: str, target_name: str, class_names: Optional[str]=None, filter_func: Optional[Callable]=None, use_sample_weights:... | Implement the Python class `FuseMetricDefault` described below.
Class description:
Applying a given metric function
Method signatures and docstrings:
- def __init__(self, metric_func: Callable, pred_name: str, target_name: str, class_names: Optional[str]=None, filter_func: Optional[Callable]=None, use_sample_weights:... | acbfd4975f18cd4361d31697faf2f82036399865 | <|skeleton|>
class FuseMetricDefault:
"""Applying a given metric function"""
def __init__(self, metric_func: Callable, pred_name: str, target_name: str, class_names: Optional[str]=None, filter_func: Optional[Callable]=None, use_sample_weights: Optional[bool]=False, sample_weight_name: Optional[str]=None) -> No... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FuseMetricDefault:
"""Applying a given metric function"""
def __init__(self, metric_func: Callable, pred_name: str, target_name: str, class_names: Optional[str]=None, filter_func: Optional[Callable]=None, use_sample_weights: Optional[bool]=False, sample_weight_name: Optional[str]=None) -> None:
"... | the_stack_v2_python_sparse | fuse/metrics/classification/metric_default.py | rosenzvi/fuse-med-ml | train | 0 |
278a2ac80920a9e32fd77b3c254e2bfe70710849 | [
"assert type(n_bins) is int\nassert n_bins > 0\nassert isinstance(bin_boundaries_policy, BinBoundariesPolicy)\nsuper().__init__(n_bins=n_bins, bin_boundaries_policy=bin_boundaries_policy)",
"if specific_scores is None:\n assert hasattr(model, 'predict_proba'), 'Model must implement the predict_proba method.'\n... | <|body_start_0|>
assert type(n_bins) is int
assert n_bins > 0
assert isinstance(bin_boundaries_policy, BinBoundariesPolicy)
super().__init__(n_bins=n_bins, bin_boundaries_policy=bin_boundaries_policy)
<|end_body_0|>
<|body_start_1|>
if specific_scores is None:
assert... | SpecificClassBinningPolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecificClassBinningPolicy:
def __init__(self, n_bins, bin_boundaries_policy):
"""Initializes a specific class binning policy, which sends samples into the n_bins bins created by the bin_boundaries_policy, based on the score the model gives for the class provided at runtime. Args: n_bins... | stack_v2_sparse_classes_75kplus_train_006514 | 6,913 | permissive | [
{
"docstring": "Initializes a specific class binning policy, which sends samples into the n_bins bins created by the bin_boundaries_policy, based on the score the model gives for the class provided at runtime. Args: n_bins: int, number of bins used to divide the interval. bin_boundaries_policy: BinBoundariesPol... | 2 | stack_v2_sparse_classes_30k_train_019090 | Implement the Python class `SpecificClassBinningPolicy` described below.
Class description:
Implement the SpecificClassBinningPolicy class.
Method signatures and docstrings:
- def __init__(self, n_bins, bin_boundaries_policy): Initializes a specific class binning policy, which sends samples into the n_bins bins creat... | Implement the Python class `SpecificClassBinningPolicy` described below.
Class description:
Implement the SpecificClassBinningPolicy class.
Method signatures and docstrings:
- def __init__(self, n_bins, bin_boundaries_policy): Initializes a specific class binning policy, which sends samples into the n_bins bins creat... | 9bfa81dd7a39ebe069c5b11b8e7a9bf9017e9350 | <|skeleton|>
class SpecificClassBinningPolicy:
def __init__(self, n_bins, bin_boundaries_policy):
"""Initializes a specific class binning policy, which sends samples into the n_bins bins created by the bin_boundaries_policy, based on the score the model gives for the class provided at runtime. Args: n_bins... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpecificClassBinningPolicy:
def __init__(self, n_bins, bin_boundaries_policy):
"""Initializes a specific class binning policy, which sends samples into the n_bins bins created by the bin_boundaries_policy, based on the score the model gives for the class provided at runtime. Args: n_bins: int, number ... | the_stack_v2_python_sparse | explicalib/calibration/evaluation/prototype/binning/legacy.py | euranova/estimating_eces | train | 4 | |
f477fc0823af961884e87f5a90b3f8a698e20024 | [
"super(RtuQuery, self).__init__()\nself._request_address = 0\nself._response_address = 0",
"self._request_address = slave\nif self._request_address < 0 or self._request_address > 255:\n raise InvalidArgumentError('Invalid address {0}'.format(self._request_address))\ndata = struct.pack('>B', self._request_addre... | <|body_start_0|>
super(RtuQuery, self).__init__()
self._request_address = 0
self._response_address = 0
<|end_body_0|>
<|body_start_1|>
self._request_address = slave
if self._request_address < 0 or self._request_address > 255:
raise InvalidArgumentError('Invalid addre... | Subclass of a Query. Adds the Modbus RTU specific part of the protocol | RtuQuery | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
<|body_0|>
def build_request(self, pdu, slave):
"""Add the Modbus RTU part to the request"""
<|body_1|>
def parse_response(se... | stack_v2_sparse_classes_75kplus_train_006515 | 9,056 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Add the Modbus RTU part to the request",
"name": "build_request",
"signature": "def build_request(self, pdu, slave)"
},
{
"docstring": "Extract the pdu from the Modbus RTU respo... | 5 | stack_v2_sparse_classes_30k_train_024789 | Implement the Python class `RtuQuery` described below.
Class description:
Subclass of a Query. Adds the Modbus RTU specific part of the protocol
Method signatures and docstrings:
- def __init__(self): Constructor
- def build_request(self, pdu, slave): Add the Modbus RTU part to the request
- def parse_response(self, ... | Implement the Python class `RtuQuery` described below.
Class description:
Subclass of a Query. Adds the Modbus RTU specific part of the protocol
Method signatures and docstrings:
- def __init__(self): Constructor
- def build_request(self, pdu, slave): Add the Modbus RTU part to the request
- def parse_response(self, ... | a5aeb1238b26c1af55cf3a82787ed347dff1fb86 | <|skeleton|>
class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
<|body_0|>
def build_request(self, pdu, slave):
"""Add the Modbus RTU part to the request"""
<|body_1|>
def parse_response(se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RtuQuery:
"""Subclass of a Query. Adds the Modbus RTU specific part of the protocol"""
def __init__(self):
"""Constructor"""
super(RtuQuery, self).__init__()
self._request_address = 0
self._response_address = 0
def build_request(self, pdu, slave):
"""Add the M... | the_stack_v2_python_sparse | external/modbus_tk/modbus_tk/modbus_rtu.py | intel/intel-device-resource-mgt-lib | train | 2 |
fdda61069f20db9251ada9d4cef33f36a90ca8a5 | [
"super(Segmentation, self).__init__()\nself.word_segmentation = WordSegmentation(stop_words_file)\nself.sentence_segmentation = SentenceSegmentation(delimiters)",
"sentences = self.sentence_segmentation.segment_text(text)\nwords_no_filter = self.word_segmentation.segment_sentences(sentences=sentences, lower=lower... | <|body_start_0|>
super(Segmentation, self).__init__()
self.word_segmentation = WordSegmentation(stop_words_file)
self.sentence_segmentation = SentenceSegmentation(delimiters)
<|end_body_0|>
<|body_start_1|>
sentences = self.sentence_segmentation.segment_text(text)
words_no_filte... | 分割器 | Segmentation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Segmentation:
"""分割器"""
def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\n'):
"""函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合"""
<|body_0|>
def segment_text(self, text, lower=False, speech_tag_filter=True):
"""函数功能： 对text进行分割处理（分词／分句） text: ... | stack_v2_sparse_classes_75kplus_train_006516 | 6,042 | no_license | [
{
"docstring": "函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合",
"name": "__init__",
"signature": "def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\\n')"
},
{
"docstring": "函数功能： 对text进行分割处理（分词／分句） text: 待处理文本 lower: 是否将英语单词转化为小写 speech_tag_filter: 词性过滤器",
"name": "segmen... | 2 | stack_v2_sparse_classes_30k_train_041249 | Implement the Python class `Segmentation` described below.
Class description:
分割器
Method signatures and docstrings:
- def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\n'): 函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合
- def segment_text(self, text, lower=False, speech_tag_filter=True): 函数功能： 对tex... | Implement the Python class `Segmentation` described below.
Class description:
分割器
Method signatures and docstrings:
- def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\n'): 函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合
- def segment_text(self, text, lower=False, speech_tag_filter=True): 函数功能： 对tex... | 9855d6e69598f9cbf1652c3bcea27133a755c03c | <|skeleton|>
class Segmentation:
"""分割器"""
def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\n'):
"""函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合"""
<|body_0|>
def segment_text(self, text, lower=False, speech_tag_filter=True):
"""函数功能： 对text进行分割处理（分词／分句） text: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Segmentation:
"""分割器"""
def __init__(self, stop_words_file=None, delimiters='?!;？！。；…\n'):
"""函数功能： 默认构造函数 stop_words_file: 停止词文件 delimiters: 分隔符集合"""
super(Segmentation, self).__init__()
self.word_segmentation = WordSegmentation(stop_words_file)
self.sentence_segmentation... | the_stack_v2_python_sparse | TextRank/Segmentation.py | xc15071347094/ASExtractor | train | 0 |
0cf4d6fac4082cf456afc78b9cb480aa948d7f9b | [
"args = self.args\nif len(args.rsplit()) != 2:\n self.statname = None\n self.statvalue = None\n return\nstatname = args.rsplit()[0]\nstatvalue = args.rsplit()[1]\nself.statname = statname\nself.statvalue = statvalue",
"allowed_statnames = self.caller.db.stats.keys()\nerrmsg1 = 'You must supply a stat ( %... | <|body_start_0|>
args = self.args
if len(args.rsplit()) != 2:
self.statname = None
self.statvalue = None
return
statname = args.rsplit()[0]
statvalue = args.rsplit()[1]
self.statname = statname
self.statvalue = statvalue
<|end_body_0|>
... | set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation. | CmdSetStat | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CmdSetStat:
"""set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation."""
def parse(self):
"""This parses the arguments"""
<|body_0|>
def func(self):
"""This perform... | stack_v2_sparse_classes_75kplus_train_006517 | 19,545 | no_license | [
{
"docstring": "This parses the arguments",
"name": "parse",
"signature": "def parse(self)"
},
{
"docstring": "This performs the actual command",
"name": "func",
"signature": "def func(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_030549 | Implement the Python class `CmdSetStat` described below.
Class description:
set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation.
Method signatures and docstrings:
- def parse(self): This parses the arguments
- def fun... | Implement the Python class `CmdSetStat` described below.
Class description:
set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation.
Method signatures and docstrings:
- def parse(self): This parses the arguments
- def fun... | 66e9c2ab1570bc8f439cf6ccde872534eecb0d62 | <|skeleton|>
class CmdSetStat:
"""set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation."""
def parse(self):
"""This parses the arguments"""
<|body_0|>
def func(self):
"""This perform... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CmdSetStat:
"""set a stat of a character Usage: +setstat (stat) (1-200) This sets the power of the current character. This can only be used during character generation."""
def parse(self):
"""This parses the arguments"""
args = self.args
if len(args.rsplit()) != 2:
sel... | the_stack_v2_python_sparse | commands/command.py | Cidusii/Kyatsu | train | 0 |
6bb7b3ccbb8cea0dce1ed9533acb3f40220d1b9e | [
"self._config = {}\nfor key, value in kwargs.items():\n if key not in self.__dict__:\n self._config[key] = value\n else:\n raise ConfigException('Can\\'t store \"{0}\" in configuration because the key conflicts with an existing property.'.format(key))\nif 'path' not in self._config:\n self._c... | <|body_start_0|>
self._config = {}
for key, value in kwargs.items():
if key not in self.__dict__:
self._config[key] = value
else:
raise ConfigException('Can\'t store "{0}" in configuration because the key conflicts with an existing property.'.forma... | The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located. | Config | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located."""
def __init__(self, **kwargs):
"""Store all parameters."""
<|body_0|>
def __getattr__(self, key):
... | stack_v2_sparse_classes_75kplus_train_006518 | 1,717 | permissive | [
{
"docstring": "Store all parameters.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Grab the value from the class properties, then check the configuration, and raise an exception if nothing works.",
"name": "__getattr__",
"signature": "def __getattr... | 2 | stack_v2_sparse_classes_30k_train_042123 | Implement the Python class `Config` described below.
Class description:
The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located.
Method signatures and docstrings:
- def __init__(self, **kwargs): Store all parameters.... | Implement the Python class `Config` described below.
Class description:
The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located.
Method signatures and docstrings:
- def __init__(self, **kwargs): Store all parameters.... | fc39e58b79e7805480e5b92bda2ad33e937423ff | <|skeleton|>
class Config:
"""The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located."""
def __init__(self, **kwargs):
"""Store all parameters."""
<|body_0|>
def __getattr__(self, key):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Config:
"""The Config class handles all configuration for pokemontools. Other classes and functions use a Config object to determine where expected files can be located."""
def __init__(self, **kwargs):
"""Store all parameters."""
self._config = {}
for key, value in kwargs.items()... | the_stack_v2_python_sparse | extras/pokemontools/configuration.py | longlostsoul/EvoYellow | train | 24 |
bb1b5efe7a199508d1ebd7dc4a7495686ec7bd0d | [
"self.key = []\nself.val = []\nself.capacity = capacity",
"if key in self.key:\n idx = self.key.index(key)\n self.key.pop(idx)\n val = self.val.pop(idx)\n self.key.append(key)\n self.val.append(val)\n return val\nelse:\n return -1",
"if key in self.key:\n idx = self.key.index(key)\n s... | <|body_start_0|>
self.key = []
self.val = []
self.capacity = capacity
<|end_body_0|>
<|body_start_1|>
if key in self.key:
idx = self.key.index(key)
self.key.pop(idx)
val = self.val.pop(idx)
self.key.append(key)
self.val.append(... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus_train_006519 | 1,281 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_003413 | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | d253f2bdc90348ad6ff0ea8f391fe3839f279879 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.key = []
self.val = []
self.capacity = capacity
def get(self, key):
""":type key: int :rtype: int"""
if key in self.key:
idx = self.key.index(key)
self.key.pop(id... | the_stack_v2_python_sparse | 字节跳动/5数据结构/2LRU缓存机制.py | eumeniders/LeetCode | train | 1 | |
afb7b9a422d5837e16624228215318bd8cf1cb83 | [
"n = len(nums)\ni = 0\nj = 0\nwhile i < n:\n if nums[i] != 0:\n nums[i], nums[j] = (nums[j], nums[i])\n j += 1\n i += 1\nprint(nums)",
"n = len(nums)\ncount = 0\nfor i in range(n):\n if nums[i] != 0:\n nums[count] = nums[i]\n count += 1\nfor j in range(count, n):\n nums[j] ... | <|body_start_0|>
n = len(nums)
i = 0
j = 0
while i < n:
if nums[i] != 0:
nums[i], nums[j] = (nums[j], nums[i])
j += 1
i += 1
print(nums)
<|end_body_0|>
<|body_start_1|>
n = len(nums)
count = 0
for i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def move_zeroes2(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."... | stack_v2_sparse_classes_75kplus_train_006520 | 1,304 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "move_zeroes",
"signature": "def move_zeroes(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.",
"name": "... | 2 | stack_v2_sparse_classes_30k_train_015050 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def move_zeroes(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def move_zeroes2(self, nums): :type nums: List[int] :rtype... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def move_zeroes(self, nums): :type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead.
- def move_zeroes2(self, nums): :type nums: List[int] :rtype... | 3b13b36f37eb364410b3b5b4f10a1808d8b1111e | <|skeleton|>
class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
<|body_0|>
def move_zeroes2(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def move_zeroes(self, nums):
""":type nums: List[int] :rtype: None Do not return anything, modify nums in-place instead."""
n = len(nums)
i = 0
j = 0
while i < n:
if nums[i] != 0:
nums[i], nums[j] = (nums[j], nums[i])
... | the_stack_v2_python_sparse | leetcode/283.py | yanggelinux/algorithm-data-structure | train | 0 | |
dac925a2145fa34e8bd7ef71b271c2d78bc05f2c | [
"samples = len(y_pred)\ny_pred_clipped = np.clip(y_pred, 1e-07, 1 - 1e-07)\nif len(y_true.shape) == 1:\n correct_confidences = y_pred_clipped[range(samples), y_true]\nelif len(y_true.shape) == 2:\n correct_confidences = np.sum(y_pred_clipped * y_true, axis=1)\nnegative_log_likelihoods = -np.log(correct_confid... | <|body_start_0|>
samples = len(y_pred)
y_pred_clipped = np.clip(y_pred, 1e-07, 1 - 1e-07)
if len(y_true.shape) == 1:
correct_confidences = y_pred_clipped[range(samples), y_true]
elif len(y_true.shape) == 2:
correct_confidences = np.sum(y_pred_clipped * y_true, axi... | The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116] | CategoricalCrossentropy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CategoricalCrossentropy:
"""The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]"""
def forward(self, y_pred, y_true):
"""Performs the forward p... | stack_v2_sparse_classes_75kplus_train_006521 | 2,192 | no_license | [
{
"docstring": "Performs the forward pass. Args : y_pred(np.array): Model predictions y_true(np.array): Actual values Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]",
"name": "forward",
"signature": "def forward(self, y_pred, y_true)"
},
{
"docstring": "... | 2 | stack_v2_sparse_classes_30k_train_028957 | Implement the Python class `CategoricalCrossentropy` described below.
Class description:
The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]
Method signatures and docstrings:
- ... | Implement the Python class `CategoricalCrossentropy` described below.
Class description:
The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]
Method signatures and docstrings:
- ... | 8ffd24971d8808e7c9caa722a7ff4df306b75b90 | <|skeleton|>
class CategoricalCrossentropy:
"""The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]"""
def forward(self, y_pred, y_true):
"""Performs the forward p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CategoricalCrossentropy:
"""The class computes the categorical crossentropy by applying the formula: -sum(y_{i,j}*log(y_hat_{i,j})) Sources: * Neural Networks from Scratch - Harrison Kinsley & Daniel Kukieła [pg.112-116]"""
def forward(self, y_pred, y_true):
"""Performs the forward pass. Args : y... | the_stack_v2_python_sparse | Music Recognizer/Metrics/CategoricalCrossentropy.py | andutzu7/Lucrare-Licenta-MusicRecognizer | train | 0 |
dc9242ee420a6691b8c50ddae8286278cdeb2eab | [
"query = None\nif '-' in accession:\n accession = accession.split('-')[0]\ntry:\n service = Service('http://www.mousemine.org/mousemine/service')\n query = service.new_query('Gene')\n query.add_view('primaryIdentifier', 'ncbiGeneNumber', 'proteins.primaryAccession', 'symbol', 'proteins.synonyms.value', ... | <|body_start_0|>
query = None
if '-' in accession:
accession = accession.split('-')[0]
try:
service = Service('http://www.mousemine.org/mousemine/service')
query = service.new_query('Gene')
query.add_view('primaryIdentifier', 'ncbiGeneNumber', 'pro... | IntermineTools | [
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntermineTools:
def mousemine_accession_lookup(accession, verbose=False):
"""Return an intermine query object for a given protien accession number. The query is design to find Entrez gene IDs for proetiens of a given accession number. It only considers the cannonical isoform of whole mou... | stack_v2_sparse_classes_75kplus_train_006522 | 9,507 | permissive | [
{
"docstring": "Return an intermine query object for a given protien accession number. The query is design to find Entrez gene IDs for proetiens of a given accession number. It only considers the cannonical isoform of whole mouse proteins(not fragments) presnt in the Swiss-Prot or TrEMBL databases. Parameters -... | 5 | stack_v2_sparse_classes_30k_train_018715 | Implement the Python class `IntermineTools` described below.
Class description:
Implement the IntermineTools class.
Method signatures and docstrings:
- def mousemine_accession_lookup(accession, verbose=False): Return an intermine query object for a given protien accession number. The query is design to find Entrez ge... | Implement the Python class `IntermineTools` described below.
Class description:
Implement the IntermineTools class.
Method signatures and docstrings:
- def mousemine_accession_lookup(accession, verbose=False): Return an intermine query object for a given protien accession number. The query is design to find Entrez ge... | bedb36eafe681401c11d562f8d7117aad3d758d7 | <|skeleton|>
class IntermineTools:
def mousemine_accession_lookup(accession, verbose=False):
"""Return an intermine query object for a given protien accession number. The query is design to find Entrez gene IDs for proetiens of a given accession number. It only considers the cannonical isoform of whole mou... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IntermineTools:
def mousemine_accession_lookup(accession, verbose=False):
"""Return an intermine query object for a given protien accession number. The query is design to find Entrez gene IDs for proetiens of a given accession number. It only considers the cannonical isoform of whole mouse proteins(no... | the_stack_v2_python_sparse | omin/utils/network_tools.py | dmpio/omin | train | 0 | |
81cad55ae8195c696abe8e02a66ee833df38cfde | [
"rev = 0\nwhile x:\n pop = x % 10\n rev = rev * 10 + pop\n x //= 10\n if rev > 2147483647:\n return 0\nreturn rev",
"if x >= 0:\n return self.reversed_positive(x)\nelse:\n return -self.reversed_positive(-x)",
"x_l = list(str(x))\nx_l_r = []\nlead_string = x_l[0]\nwhile x_l:\n x_l_r.a... | <|body_start_0|>
rev = 0
while x:
pop = x % 10
rev = rev * 10 + pop
x //= 10
if rev > 2147483647:
return 0
return rev
<|end_body_0|>
<|body_start_1|>
if x >= 0:
return self.reversed_positive(x)
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reversed_positive(self, x):
"""方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:"""
<|body_0|>
def reversed_all(self, x):
"""所有整数反转 :param x: :return:"""
<|body_1|>
def reverse(self, x):
"""方式2：借助列表进行末尾弹出，列表拼接、类型转换等方式反转数字 :type x: int ... | stack_v2_sparse_classes_75kplus_train_006523 | 1,527 | no_license | [
{
"docstring": "方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:",
"name": "reversed_positive",
"signature": "def reversed_positive(self, x)"
},
{
"docstring": "所有整数反转 :param x: :return:",
"name": "reversed_all",
"signature": "def reversed_all(self, x)"
},
{
"docstring": "方式2：借助列表进... | 3 | stack_v2_sparse_classes_30k_train_010925 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reversed_positive(self, x): 方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:
- def reversed_all(self, x): 所有整数反转 :param x: :return:
- def reverse(self, x): 方式2：借助列表进行末尾弹出，列表拼接、... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reversed_positive(self, x): 方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:
- def reversed_all(self, x): 所有整数反转 :param x: :return:
- def reverse(self, x): 方式2：借助列表进行末尾弹出，列表拼接、... | 9b55b49b468ff412c5d78773a03279bdc77a3874 | <|skeleton|>
class Solution:
def reversed_positive(self, x):
"""方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:"""
<|body_0|>
def reversed_all(self, x):
"""所有整数反转 :param x: :return:"""
<|body_1|>
def reverse(self, x):
"""方式2：借助列表进行末尾弹出，列表拼接、类型转换等方式反转数字 :type x: int ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reversed_positive(self, x):
"""方法1：用数学的方式解决，余数 及整除 的定义 :param x: 正整数 :return:"""
rev = 0
while x:
pop = x % 10
rev = rev * 10 + pop
x //= 10
if rev > 2147483647:
return 0
return rev
def reversed_... | the_stack_v2_python_sparse | online_programming/letecode_reverse.py | rowlingz/Deepen-learning-Python | train | 0 | |
c34b715f78860bf9fc9345651bfba7a221a13f65 | [
"queryset = models.Book.objects.all().select_related()\nser_obj = BookSerializer(queryset, many=True)\nreturn Response(ser_obj.data)",
"obj = request.data\nser_obj = BookSerializer(data=obj)\nprint(ser_obj)\nif not ser_obj.is_valid():\n return Response({'code': 1000, 'error_mes': ser_obj.errors})\nser_obj.save... | <|body_start_0|>
queryset = models.Book.objects.all().select_related()
ser_obj = BookSerializer(queryset, many=True)
return Response(ser_obj.data)
<|end_body_0|>
<|body_start_1|>
obj = request.data
ser_obj = BookSerializer(data=obj)
print(ser_obj)
if not ser_obj.... | BookView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookView:
def get(self, request):
"""获取所有"""
<|body_0|>
def post(self, request):
"""增加数据:反序列化"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
queryset = models.Book.objects.all().select_related()
ser_obj = BookSerializer(queryset, many=True)... | stack_v2_sparse_classes_75kplus_train_006524 | 3,287 | no_license | [
{
"docstring": "获取所有",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "增加数据:反序列化",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020328 | Implement the Python class `BookView` described below.
Class description:
Implement the BookView class.
Method signatures and docstrings:
- def get(self, request): 获取所有
- def post(self, request): 增加数据:反序列化 | Implement the Python class `BookView` described below.
Class description:
Implement the BookView class.
Method signatures and docstrings:
- def get(self, request): 获取所有
- def post(self, request): 增加数据:反序列化
<|skeleton|>
class BookView:
def get(self, request):
"""获取所有"""
<|body_0|>
def post(s... | 2d966d3e0ec0eebfb7882d807b806071aa1906f8 | <|skeleton|>
class BookView:
def get(self, request):
"""获取所有"""
<|body_0|>
def post(self, request):
"""增加数据:反序列化"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BookView:
def get(self, request):
"""获取所有"""
queryset = models.Book.objects.all().select_related()
ser_obj = BookSerializer(queryset, many=True)
return Response(ser_obj.data)
def post(self, request):
"""增加数据:反序列化"""
obj = request.data
ser_obj = Book... | the_stack_v2_python_sparse | django_pro_demo/demo_ModelSerializers/book_supermarket/views/books.py | MrHou999/study_django | train | 0 | |
b87107a2d5c8b0419c81300374fc8c8b4e8b8ab7 | [
"self._login = login\nself._password = password\nself._cookie_jar = cookielib.CookieJar()\nself._url_opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(self._cookie_jar))",
"data = {'login_username': self._login, 'login_password': self._password, 'login': '%C2%F5%EE%E4'}\nresp = self._url_opener.open('http... | <|body_start_0|>
self._login = login
self._password = password
self._cookie_jar = cookielib.CookieJar()
self._url_opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(self._cookie_jar))
<|end_body_0|>
<|body_start_1|>
data = {'login_username': self._login, 'login_password':... | Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org. | RutrackerBrowser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RutrackerBrowser:
"""Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org."""
def __init__(self, login, password):
"""Initialises browser, stores RuTracker.Org's login and password. login - RuTracker.org login; ... | stack_v2_sparse_classes_75kplus_train_006525 | 3,694 | permissive | [
{
"docstring": "Initialises browser, stores RuTracker.Org's login and password. login - RuTracker.org login; password - RuTracker.org password.",
"name": "__init__",
"signature": "def __init__(self, login, password)"
},
{
"docstring": "Logs in RuTracker.Org. This method should be called before a... | 5 | stack_v2_sparse_classes_30k_train_025869 | Implement the Python class `RutrackerBrowser` described below.
Class description:
Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org.
Method signatures and docstrings:
- def __init__(self, login, password): Initialises browser, stores RuTracke... | Implement the Python class `RutrackerBrowser` described below.
Class description:
Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org.
Method signatures and docstrings:
- def __init__(self, login, password): Initialises browser, stores RuTracke... | daff74bf96b2a7a13f94f6762305ac82c33edfe6 | <|skeleton|>
class RutrackerBrowser:
"""Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org."""
def __init__(self, login, password):
"""Initialises browser, stores RuTracker.Org's login and password. login - RuTracker.org login; ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RutrackerBrowser:
"""Class RutrackerBrowser presents browser for RuTracker.Org. It allows logging in and getting .torrent files from RuTracker.Org."""
def __init__(self, login, password):
"""Initialises browser, stores RuTracker.Org's login and password. login - RuTracker.org login; password - Ru... | the_stack_v2_python_sparse | rt_browser.py | serejkus/rt_download_server | train | 0 |
887722c706fc27b57dd15f1d1f4e5e8b05de78e4 | [
"if not UpgradeCommand.check_mlf_core_latest():\n if mlf_core_questionary_or_dot_mlf_core(function='confirm', question='Do you want to upgrade?', default='y'):\n UpgradeCommand.upgrade_mlf_core()",
"latest_local_version = mlf_core.__version__\nsliced_local_version = latest_local_version[:-9] if latest_l... | <|body_start_0|>
if not UpgradeCommand.check_mlf_core_latest():
if mlf_core_questionary_or_dot_mlf_core(function='confirm', question='Do you want to upgrade?', default='y'):
UpgradeCommand.upgrade_mlf_core()
<|end_body_0|>
<|body_start_1|>
latest_local_version = mlf_core.__v... | Responsible for checking for newer versions mlf-core and upgrading it if required. | UpgradeCommand | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpgradeCommand:
"""Responsible for checking for newer versions mlf-core and upgrading it if required."""
def check_upgrade_mlf_core() -> None:
"""Checks whether the locally installed version of mlf-core is the latest. If not it prompts whether to upgrade and runs the upgrade command ... | stack_v2_sparse_classes_75kplus_train_006526 | 4,119 | permissive | [
{
"docstring": "Checks whether the locally installed version of mlf-core is the latest. If not it prompts whether to upgrade and runs the upgrade command if desired.",
"name": "check_upgrade_mlf_core",
"signature": "def check_upgrade_mlf_core() -> None"
},
{
"docstring": "Checks whether the loca... | 4 | stack_v2_sparse_classes_30k_train_013693 | Implement the Python class `UpgradeCommand` described below.
Class description:
Responsible for checking for newer versions mlf-core and upgrading it if required.
Method signatures and docstrings:
- def check_upgrade_mlf_core() -> None: Checks whether the locally installed version of mlf-core is the latest. If not it... | Implement the Python class `UpgradeCommand` described below.
Class description:
Responsible for checking for newer versions mlf-core and upgrading it if required.
Method signatures and docstrings:
- def check_upgrade_mlf_core() -> None: Checks whether the locally installed version of mlf-core is the latest. If not it... | c997a20419b075b2860119b3a4cd06dc132ec704 | <|skeleton|>
class UpgradeCommand:
"""Responsible for checking for newer versions mlf-core and upgrading it if required."""
def check_upgrade_mlf_core() -> None:
"""Checks whether the locally installed version of mlf-core is the latest. If not it prompts whether to upgrade and runs the upgrade command ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpgradeCommand:
"""Responsible for checking for newer versions mlf-core and upgrading it if required."""
def check_upgrade_mlf_core() -> None:
"""Checks whether the locally installed version of mlf-core is the latest. If not it prompts whether to upgrade and runs the upgrade command if desired.""... | the_stack_v2_python_sparse | mlf_core/upgrade/upgrade.py | ggabernet/mlf-core | train | 0 |
1760b37375bb9216d067904813741986241a6d0f | [
"access_token = (yield self._token_cache.get_access_cache(self._token_cache.KEY_ACCESS_TOKEN))\nunion_id_url = WxConfig.get_union_id_url.format(ACCESS_TOKEN=access_token, OPENID=open_id)\nrequest_union_id = requests.get(union_id_url)\nres_info = json.loads(request_union_id.text, encoding='utf-8')\nunion_id = res_in... | <|body_start_0|>
access_token = (yield self._token_cache.get_access_cache(self._token_cache.KEY_ACCESS_TOKEN))
union_id_url = WxConfig.get_union_id_url.format(ACCESS_TOKEN=access_token, OPENID=open_id)
request_union_id = requests.get(union_id_url)
res_info = json.loads(request_union_id.t... | 分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串 | AnalysisChance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnalysisChance:
"""分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串"""
def get_union_id(self, open_id):
"""根据open_id获取union_id :param open_id: :return:"""
<|body_0|>
def get_draw_status(self, open_id):
"""根据open_id返回需要返回的字符串 :param open_id: :retur... | stack_v2_sparse_classes_75kplus_train_006527 | 2,171 | no_license | [
{
"docstring": "根据open_id获取union_id :param open_id: :return:",
"name": "get_union_id",
"signature": "def get_union_id(self, open_id)"
},
{
"docstring": "根据open_id返回需要返回的字符串 :param open_id: :return:",
"name": "get_draw_status",
"signature": "def get_draw_status(self, open_id)"
}
] | 2 | null | Implement the Python class `AnalysisChance` described below.
Class description:
分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串
Method signatures and docstrings:
- def get_union_id(self, open_id): 根据open_id获取union_id :param open_id: :return:
- def get_draw_status(self, open_id): 根据open_id返回需要返回的字符串 :... | Implement the Python class `AnalysisChance` described below.
Class description:
分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串
Method signatures and docstrings:
- def get_union_id(self, open_id): 根据open_id获取union_id :param open_id: :return:
- def get_draw_status(self, open_id): 根据open_id返回需要返回的字符串 :... | b4b60a33028ae1c638b8051304576f2b9e4630aa | <|skeleton|>
class AnalysisChance:
"""分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串"""
def get_union_id(self, open_id):
"""根据open_id获取union_id :param open_id: :return:"""
<|body_0|>
def get_draw_status(self, open_id):
"""根据open_id返回需要返回的字符串 :param open_id: :retur... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnalysisChance:
"""分析该用户是否有机会领取奖励 0、是否有下载游戏注册账号 1、有机会就返回领取成功的字符串 2、没有机会的话返回没有机会的字符串"""
def get_union_id(self, open_id):
"""根据open_id获取union_id :param open_id: :return:"""
access_token = (yield self._token_cache.get_access_cache(self._token_cache.KEY_ACCESS_TOKEN))
union_id_url = W... | the_stack_v2_python_sparse | prize_server/weixinback/core/server/analysis_chance.py | XTAYJGDUFVF/prize_server | train | 0 |
61c14109b4ea67de36be535b4f96e9dfb61f50df | [
"if not email:\n raise ValueError('Введите e-mail')\nuser = self.model(email=self.normalize_email(email), username=username, first_name=first_name, last_name=last_name, confirm_email=False, is_active=True)\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email=sel... | <|body_start_0|>
if not email:
raise ValueError('Введите e-mail')
user = self.model(email=self.normalize_email(email), username=username, first_name=first_name, last_name=last_name, confirm_email=False, is_active=True)
user.set_password(password)
user.save(using=self._db)
... | Account manager. | MyAccountManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyAccountManager:
"""Account manager."""
def create_user(self, first_name, last_name, email, username, password=None):
"""Creates and saves a new user."""
<|body_0|>
def create_superuser(self, first_name, last_name, email, username, password):
"""Creates and save... | stack_v2_sparse_classes_75kplus_train_006528 | 3,931 | permissive | [
{
"docstring": "Creates and saves a new user.",
"name": "create_user",
"signature": "def create_user(self, first_name, last_name, email, username, password=None)"
},
{
"docstring": "Creates and saves a new super user.",
"name": "create_superuser",
"signature": "def create_superuser(self,... | 2 | stack_v2_sparse_classes_30k_test_000098 | Implement the Python class `MyAccountManager` described below.
Class description:
Account manager.
Method signatures and docstrings:
- def create_user(self, first_name, last_name, email, username, password=None): Creates and saves a new user.
- def create_superuser(self, first_name, last_name, email, username, passwo... | Implement the Python class `MyAccountManager` described below.
Class description:
Account manager.
Method signatures and docstrings:
- def create_user(self, first_name, last_name, email, username, password=None): Creates and saves a new user.
- def create_superuser(self, first_name, last_name, email, username, passwo... | cbb16fc9ab2b85232e4c05446697fc82b78bc8e4 | <|skeleton|>
class MyAccountManager:
"""Account manager."""
def create_user(self, first_name, last_name, email, username, password=None):
"""Creates and saves a new user."""
<|body_0|>
def create_superuser(self, first_name, last_name, email, username, password):
"""Creates and save... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyAccountManager:
"""Account manager."""
def create_user(self, first_name, last_name, email, username, password=None):
"""Creates and saves a new user."""
if not email:
raise ValueError('Введите e-mail')
user = self.model(email=self.normalize_email(email), username=use... | the_stack_v2_python_sparse | shop/accounts/models.py | Anych/mila-iris | train | 0 |
9f7b4254b82c1a94563110e2219e74d3feea60fc | [
"with self.OutputCapturer() as output:\n try:\n mps.main(['--help'])\n except exceptions.SystemExit as e:\n self.assertEquals(e.args[0], 0)\nstdout = output.GetStdout()\nself.assertTrue(stdout.startswith('usage: '), msg='Expected output starting with \"usage: \" but got:\\n%s' % stdout)",
"wit... | <|body_start_0|>
with self.OutputCapturer() as output:
try:
mps.main(['--help'])
except exceptions.SystemExit as e:
self.assertEquals(e.args[0], 0)
stdout = output.GetStdout()
self.assertTrue(stdout.startswith('usage: '), msg='Expected outp... | Test argument handling at the main method level. | MainTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-public-domain",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
<|body_0|>
def testMissingOut(self):
"""Test that running without --out exits with an error."""
<|body_1|>
def testMissingPacka... | stack_v2_sparse_classes_75kplus_train_006529 | 10,044 | permissive | [
{
"docstring": "Test that --help is functioning",
"name": "testHelp",
"signature": "def testHelp(self)"
},
{
"docstring": "Test that running without --out exits with an error.",
"name": "testMissingOut",
"signature": "def testMissingOut(self)"
},
{
"docstring": "Test that running... | 4 | stack_v2_sparse_classes_30k_train_019550 | Implement the Python class `MainTest` described below.
Class description:
Test argument handling at the main method level.
Method signatures and docstrings:
- def testHelp(self): Test that --help is functioning
- def testMissingOut(self): Test that running without --out exits with an error.
- def testMissingPackage(s... | Implement the Python class `MainTest` described below.
Class description:
Test argument handling at the main method level.
Method signatures and docstrings:
- def testHelp(self): Test that --help is functioning
- def testMissingOut(self): Test that running without --out exits with an error.
- def testMissingPackage(s... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
<|body_0|>
def testMissingOut(self):
"""Test that running without --out exits with an error."""
<|body_1|>
def testMissingPacka... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MainTest:
"""Test argument handling at the main method level."""
def testHelp(self):
"""Test that --help is functioning"""
with self.OutputCapturer() as output:
try:
mps.main(['--help'])
except exceptions.SystemExit as e:
self.assert... | the_stack_v2_python_sparse | third_party/chromite/scripts/merge_package_status_unittest.py | metux/chromium-suckless | train | 5 |
a9e701612e5995fd00dc97402f11a91f807cb47f | [
"with open(relation_file, 'r') as f:\n self.tweet_relations = f.read().split('\\n\\n')\nself.get_patterns()",
"for idx, tweet in enumerate(self.tweet_relations):\n tweet_info = tweet.split('\\n')\n self.tweets.append(tweet_info[0])\n for relation in tweet_info[1:]:\n triple = relation.split(' '... | <|body_start_0|>
with open(relation_file, 'r') as f:
self.tweet_relations = f.read().split('\n\n')
self.get_patterns()
<|end_body_0|>
<|body_start_1|>
for idx, tweet in enumerate(self.tweet_relations):
tweet_info = tweet.split('\n')
self.tweets.append(tweet_i... | Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values | TweetLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TweetLoader:
"""Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values"""
def __init__(self, relation_file):
"""Initialize the class by splitting the OpenIE fi... | stack_v2_sparse_classes_75kplus_train_006530 | 1,443 | no_license | [
{
"docstring": "Initialize the class by splitting the OpenIE file into tweet descriptor sections :param relation_file: the OpenIE output file with relations extracted from tweets",
"name": "__init__",
"signature": "def __init__(self, relation_file)"
},
{
"docstring": "Filter the output relations... | 2 | stack_v2_sparse_classes_30k_train_035462 | Implement the Python class `TweetLoader` described below.
Class description:
Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values
Method signatures and docstrings:
- def __init__(self, relati... | Implement the Python class `TweetLoader` described below.
Class description:
Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values
Method signatures and docstrings:
- def __init__(self, relati... | 1da8f7fb76cb9f193d3c262b07434f32caeefc09 | <|skeleton|>
class TweetLoader:
"""Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values"""
def __init__(self, relation_file):
"""Initialize the class by splitting the OpenIE fi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TweetLoader:
"""Processes OpenIE outputs - Converts triples to format that can be matched to predefined emotion-cause patterns - Includes preprocessing steps of adding POS tags and emotion values"""
def __init__(self, relation_file):
"""Initialize the class by splitting the OpenIE file into tweet... | the_stack_v2_python_sparse | src/baseline/openie_tweet_loader.py | jmcanal/BECR | train | 2 |
c06338d6b6a14da71922a2d8cee026b5113044b7 | [
"if cosmo_type is None:\n self._Ddt_sampling = False\nelif cosmo_type == 'D_dt':\n self._Ddt_sampling = True\nelse:\n raise ValueError('cosmo_type %s is not supported!' % cosmo_type)\nself._cosmo_type = cosmo_type\nself._mass_scaling = mass_scaling\nself._num_scale_factor = num_scale_factor\nself._kwargs_f... | <|body_start_0|>
if cosmo_type is None:
self._Ddt_sampling = False
elif cosmo_type == 'D_dt':
self._Ddt_sampling = True
else:
raise ValueError('cosmo_type %s is not supported!' % cosmo_type)
self._cosmo_type = cosmo_type
self._mass_scaling = ma... | class that handles the cosmology relevant parameters | CosmoParam | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CosmoParam:
"""class that handles the cosmology relevant parameters"""
def __init__(self, cosmo_type=None, mass_scaling=False, kwargs_fixed={}, num_scale_factor=1, kwargs_lower=None, kwargs_upper=None):
""":param sampling: bool, if True, activates time-delay parameters :param D_dt_in... | stack_v2_sparse_classes_75kplus_train_006531 | 3,602 | permissive | [
{
"docstring": ":param sampling: bool, if True, activates time-delay parameters :param D_dt_init: initial guess of time-delay distance (Mpc) :param D_dt_sigma: initial uncertainty :param D_dt_lower: lower bound :param D_dt_upper: upper bound",
"name": "__init__",
"signature": "def __init__(self, cosmo_t... | 4 | stack_v2_sparse_classes_30k_train_008255 | Implement the Python class `CosmoParam` described below.
Class description:
class that handles the cosmology relevant parameters
Method signatures and docstrings:
- def __init__(self, cosmo_type=None, mass_scaling=False, kwargs_fixed={}, num_scale_factor=1, kwargs_lower=None, kwargs_upper=None): :param sampling: bool... | Implement the Python class `CosmoParam` described below.
Class description:
class that handles the cosmology relevant parameters
Method signatures and docstrings:
- def __init__(self, cosmo_type=None, mass_scaling=False, kwargs_fixed={}, num_scale_factor=1, kwargs_lower=None, kwargs_upper=None): :param sampling: bool... | dcdfc61ce5351ac94565228c822f1c94392c1ad6 | <|skeleton|>
class CosmoParam:
"""class that handles the cosmology relevant parameters"""
def __init__(self, cosmo_type=None, mass_scaling=False, kwargs_fixed={}, num_scale_factor=1, kwargs_lower=None, kwargs_upper=None):
""":param sampling: bool, if True, activates time-delay parameters :param D_dt_in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CosmoParam:
"""class that handles the cosmology relevant parameters"""
def __init__(self, cosmo_type=None, mass_scaling=False, kwargs_fixed={}, num_scale_factor=1, kwargs_lower=None, kwargs_upper=None):
""":param sampling: bool, if True, activates time-delay parameters :param D_dt_init: initial g... | the_stack_v2_python_sparse | lenstronomy/Cosmo/cosmo_param.py | guoxiaowhu/lenstronomy | train | 1 |
1fd59927edeb1148d8581c6963d53c9ff3fed20a | [
"apply_patch(self.request, save=False, src=self.request.validated['tender_src'])\nif all([i.auctionPeriod and i.auctionPeriod.endDate for i in self.request.validated['tender'].lots if i.numberOfBids > 1 and i.status == 'active']):\n add_next_award(self.request)\nif save_tender(self.request):\n self.LOGGER.inf... | <|body_start_0|>
apply_patch(self.request, save=False, src=self.request.validated['tender_src'])
if all([i.auctionPeriod and i.auctionPeriod.endDate for i in self.request.validated['tender'].lots if i.numberOfBids > 1 and i.status == 'active']):
add_next_award(self.request)
if save_t... | TenderUaAuctionResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenderUaAuctionResource:
def collection_post(self):
"""Report auction results."""
<|body_0|>
def post(self):
"""Report auction results for lot."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
apply_patch(self.request, save=False, src=self.request.va... | stack_v2_sparse_classes_75kplus_train_006532 | 2,504 | permissive | [
{
"docstring": "Report auction results.",
"name": "collection_post",
"signature": "def collection_post(self)"
},
{
"docstring": "Report auction results for lot.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_045776 | Implement the Python class `TenderUaAuctionResource` described below.
Class description:
Implement the TenderUaAuctionResource class.
Method signatures and docstrings:
- def collection_post(self): Report auction results.
- def post(self): Report auction results for lot. | Implement the Python class `TenderUaAuctionResource` described below.
Class description:
Implement the TenderUaAuctionResource class.
Method signatures and docstrings:
- def collection_post(self): Report auction results.
- def post(self): Report auction results for lot.
<|skeleton|>
class TenderUaAuctionResource:
... | 5afdd3a62a8e562cf77e2d963d88f1a26613d16a | <|skeleton|>
class TenderUaAuctionResource:
def collection_post(self):
"""Report auction results."""
<|body_0|>
def post(self):
"""Report auction results for lot."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TenderUaAuctionResource:
def collection_post(self):
"""Report auction results."""
apply_patch(self.request, save=False, src=self.request.validated['tender_src'])
if all([i.auctionPeriod and i.auctionPeriod.endDate for i in self.request.validated['tender'].lots if i.numberOfBids > 1 and... | the_stack_v2_python_sparse | src/openprocurement/tender/openuadefense/views/auction.py | pontostroy/api | train | 0 | |
916717d3f914b851dbae07a840fffb8989f31084 | [
"result = super(StockPicking, self)._action_done()\nfor picking in self:\n if picking.sale_id.invoice_status == 'invoiced':\n continue\n order = picking.sale_id\n work_flow_process_record = order and order.auto_workflow_process_id\n delivery_lines = picking.move_line_ids.filtered(lambda l: l.prod... | <|body_start_0|>
result = super(StockPicking, self)._action_done()
for picking in self:
if picking.sale_id.invoice_status == 'invoiced':
continue
order = picking.sale_id
work_flow_process_record = order and order.auto_workflow_process_id
de... | StockPicking | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StockPicking:
def _action_done(self):
"""Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'."""
<|body_0|>
def send_to_shipper(self):
"""usage: If auto_processed_orders_ept = True passed in Context... | stack_v2_sparse_classes_75kplus_train_006533 | 1,518 | no_license | [
{
"docstring": "Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'.",
"name": "_action_done",
"signature": "def _action_done(self)"
},
{
"docstring": "usage: If auto_processed_orders_ept = True passed in Context then we can no... | 2 | null | Implement the Python class `StockPicking` described below.
Class description:
Implement the StockPicking class.
Method signatures and docstrings:
- def _action_done(self): Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'.
- def send_to_shipper(se... | Implement the Python class `StockPicking` described below.
Class description:
Implement the StockPicking class.
Method signatures and docstrings:
- def _action_done(self): Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'.
- def send_to_shipper(se... | 6b64f0dfbeae0610605de9321d736f6f09768bb3 | <|skeleton|>
class StockPicking:
def _action_done(self):
"""Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'."""
<|body_0|>
def send_to_shipper(self):
"""usage: If auto_processed_orders_ept = True passed in Context... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StockPicking:
def _action_done(self):
"""Added comment by Udit create and paid invoice on the basis of auto invoice work flow when invoicing policy is 'delivery'."""
result = super(StockPicking, self)._action_done()
for picking in self:
if picking.sale_id.invoice_status == ... | the_stack_v2_python_sparse | common_connector_library/models/stock_picking.py | marandagroup/sh_v14_addons | train | 0 | |
4a457293ce1f4ac991c3af30f11fa96b5b5c56d1 | [
"bundle = sorted(((val, i) for i, val in enumerate(nums)))\nfor i in xrange(len(bundle)):\n j = i + 1\n while j < len(bundle) and bundle[j][0] - bundle[i][0] <= t:\n if abs(bundle[i][1] - bundle[j][1]) <= k:\n return True\n j += 1\nreturn False",
"if t < 0:\n return False\nbucket... | <|body_start_0|>
bundle = sorted(((val, i) for i, val in enumerate(nums)))
for i in xrange(len(bundle)):
j = i + 1
while j < len(bundle) and bundle[j][0] - bundle[i][0] <= t:
if abs(bundle[i][1] - bundle[j][1]) <= k:
return True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def containsNearbyAlmostDuplicate(self, nums, k, t):
"""Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together to preserve information. Then the loop will stop when value diff is larger than t. Sorting will ... | stack_v2_sparse_classes_75kplus_train_006534 | 2,672 | no_license | [
{
"docstring": "Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together to preserve information. Then the loop will stop when value diff is larger than t. Sorting will help in terms of reducing time complexity but the big O is same as without... | 2 | stack_v2_sparse_classes_30k_train_017680 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyAlmostDuplicate(self, nums, k, t): Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def containsNearbyAlmostDuplicate(self, nums, k, t): Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together... | 33c623f226981942780751554f0593f2c71cf458 | <|skeleton|>
class Solution:
def containsNearbyAlmostDuplicate(self, nums, k, t):
"""Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together to preserve information. Then the loop will stop when value diff is larger than t. Sorting will ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def containsNearbyAlmostDuplicate(self, nums, k, t):
"""Bacially the solution is brutal force. The array can be sorted by the value, using tuple to bind the value and index together to preserve information. Then the loop will stop when value diff is larger than t. Sorting will help in terms ... | the_stack_v2_python_sparse | arr/leetcode_Contains_Duplicate_III.py | monkeylyf/interviewjam | train | 59 | |
ca5b86fc5ad32d750086aaac8187f3b9f12bc8a3 | [
"if len(args) >= 2 and isinstance(args[0], str):\n value = args[1]\n for key in reversed(args[0].split('.')):\n value = {key: value}\n self.data = value\nelse:\n super().__init__(*args, **kwargs)",
"for k, v in other.items():\n if isinstance(v, collections.abc.Mapping):\n self[k] = WD... | <|body_start_0|>
if len(args) >= 2 and isinstance(args[0], str):
value = args[1]
for key in reversed(args[0].split('.')):
value = {key: value}
self.data = value
else:
super().__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
... | WDict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WDict:
def __init__(self, *args, **kwargs):
"""permet d'initialiser un dict sous forme nested WDict("aaa.bbb.ccc", 2) => {"aaa":{"bbb":{"ccc":2}}}"""
<|body_0|>
def update(self, other):
"""Recursively update nested dict :param other: some Mapping :return: self, updat... | stack_v2_sparse_classes_75kplus_train_006535 | 6,173 | no_license | [
{
"docstring": "permet d'initialiser un dict sous forme nested WDict(\"aaa.bbb.ccc\", 2) => {\"aaa\":{\"bbb\":{\"ccc\":2}}}",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Recursively update nested dict :param other: some Mapping :return: self, updated... | 2 | stack_v2_sparse_classes_30k_train_011964 | Implement the Python class `WDict` described below.
Class description:
Implement the WDict class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): permet d'initialiser un dict sous forme nested WDict("aaa.bbb.ccc", 2) => {"aaa":{"bbb":{"ccc":2}}}
- def update(self, other): Recursively update n... | Implement the Python class `WDict` described below.
Class description:
Implement the WDict class.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): permet d'initialiser un dict sous forme nested WDict("aaa.bbb.ccc", 2) => {"aaa":{"bbb":{"ccc":2}}}
- def update(self, other): Recursively update n... | 8bd37e89cff02cf0366ef66d30d7ebab38205759 | <|skeleton|>
class WDict:
def __init__(self, *args, **kwargs):
"""permet d'initialiser un dict sous forme nested WDict("aaa.bbb.ccc", 2) => {"aaa":{"bbb":{"ccc":2}}}"""
<|body_0|>
def update(self, other):
"""Recursively update nested dict :param other: some Mapping :return: self, updat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WDict:
def __init__(self, *args, **kwargs):
"""permet d'initialiser un dict sous forme nested WDict("aaa.bbb.ccc", 2) => {"aaa":{"bbb":{"ccc":2}}}"""
if len(args) >= 2 and isinstance(args[0], str):
value = args[1]
for key in reversed(args[0].split('.')):
... | the_stack_v2_python_sparse | src/mycartable/utils.py | jgirardet/MyCartable | train | 3 | |
e9ee9f9afcb5ec4266e57963e3065a2b9d2cf24e | [
"self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')\nself.n_win = hyper_parameters['model'].get('n_win', 3)\nsuper().__init__(hyper_parameters)",
"super().create_model(hyper_parameters)\nembedding = self.word_embedding.output\n\ndef win_mean(x):\n res_list = []\n for i in range(self.len_... | <|body_start_0|>
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
<|end_body_0|>
<|body_start_1|>
super().create_model(hyper_parameters)
embedding = self.word_embeddin... | SWEMGraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus_train_006536 | 2,341 | permissive | [
{
"docstring": "初始化 :param hyper_parameters: json，超参",
"name": "__init__",
"signature": "def __init__(self, hyper_parameters)"
},
{
"docstring": "构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl",
"name": "create_model",
"signature": "def create_mod... | 2 | stack_v2_sparse_classes_30k_train_046572 | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | Implement the Python class `SWEMGraph` described below.
Class description:
Implement the SWEMGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper parameters of ... | 640e3f44f90d9d8046546f7e1a93a29ebe5c8d30 | <|skeleton|>
class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SWEMGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
self.encode_type = hyper_parameters['model'].get('encode_type', 'MAX')
self.n_win = hyper_parameters['model'].get('n_win', 3)
super().__init__(hyper_parameters)
def create_model(sel... | the_stack_v2_python_sparse | keras_textclassification/m15_SWEM/graph.py | wzjames/Keras-TextClassification | train | 1 | |
7264f7018531a0b39d2eefdcc4aec3aa42e1b040 | [
"super(AttentionEncoder, self).__init__()\nself.lookup = nn.Embedding(vocab_size, emb_size)\nif pretrained_emb is None:\n xavier_uniform(self.lookup.weight.data)\nelse:\n assert pretrained_emb.size() == (vocab_size, emb_size), 'Word embedding matrix has incorrect size: {} instead of {}'.format(w_emb.size(), (... | <|body_start_0|>
super(AttentionEncoder, self).__init__()
self.lookup = nn.Embedding(vocab_size, emb_size)
if pretrained_emb is None:
xavier_uniform(self.lookup.weight.data)
else:
assert pretrained_emb.size() == (vocab_size, emb_size), 'Word embedding matrix has i... | Segment encoder that produces segment vectors as the weighted average of word embeddings. | AttentionEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttentionEncoder:
"""Segment encoder that produces segment vectors as the weighted average of word embeddings."""
def __init__(self, vocab_size, emb_size, bias=True, M=None, b=None, pretrained_emb=None, fix_w_emb=False):
"""Initializes the encoder using a [vocab_size x emb_size] embe... | stack_v2_sparse_classes_75kplus_train_006537 | 22,149 | permissive | [
{
"docstring": "Initializes the encoder using a [vocab_size x emb_size] embedding matrix. The encoder learns a matrix M, which may be initialized explicitely or randomly. Parameters: vocab_size (int): the vocabulary size emb_size (int): dimensionality of embeddings bias (bool): whether or not to use a bias vect... | 2 | stack_v2_sparse_classes_30k_train_008363 | Implement the Python class `AttentionEncoder` described below.
Class description:
Segment encoder that produces segment vectors as the weighted average of word embeddings.
Method signatures and docstrings:
- def __init__(self, vocab_size, emb_size, bias=True, M=None, b=None, pretrained_emb=None, fix_w_emb=False): Ini... | Implement the Python class `AttentionEncoder` described below.
Class description:
Segment encoder that produces segment vectors as the weighted average of word embeddings.
Method signatures and docstrings:
- def __init__(self, vocab_size, emb_size, bias=True, M=None, b=None, pretrained_emb=None, fix_w_emb=False): Ini... | 41452f447284491cf8ade8e09f3bc4e314ec64f7 | <|skeleton|>
class AttentionEncoder:
"""Segment encoder that produces segment vectors as the weighted average of word embeddings."""
def __init__(self, vocab_size, emb_size, bias=True, M=None, b=None, pretrained_emb=None, fix_w_emb=False):
"""Initializes the encoder using a [vocab_size x emb_size] embe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AttentionEncoder:
"""Segment encoder that produces segment vectors as the weighted average of word embeddings."""
def __init__(self, vocab_size, emb_size, bias=True, M=None, b=None, pretrained_emb=None, fix_w_emb=False):
"""Initializes the encoder using a [vocab_size x emb_size] embedding matrix.... | the_stack_v2_python_sparse | iswd/model_library.py | gkaramanolakis/ISWD | train | 7 |
5bda1b4c9a27b594cc3de26783741ed119dd7412 | [
"log_info(prm)\nself.default_solver = default_solver\nN_IW = sb_qmc.N_IW\niw_points = matsubara_frequencies(np.arange(N_IW), prm.beta)\ndata = get_initial_condition(prm, kind=starting_point, iw_points=iw_points, output_dir=output_dir)\ndata_T = data.temperature\niw_points = matsubara_frequencies(np.arange(N_IW), 1.... | <|body_start_0|>
log_info(prm)
self.default_solver = default_solver
N_IW = sb_qmc.N_IW
iw_points = matsubara_frequencies(np.arange(N_IW), prm.beta)
data = get_initial_condition(prm, kind=starting_point, iw_points=iw_points, output_dir=output_dir)
data_T = data.temperature... | Run r-DMFT loop using `Runner.iteration`. | Runner | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Runner:
"""Run r-DMFT loop using `Runner.iteration`."""
def __init__(self, prm: Hubbard_Parameters, starting_point='auto', output_dir=None, default_solver=sb_qmc.solve) -> None:
"""Create runner for the model `prm`. Parameters ---------- prm : Hubbard_Parameters Parameters of the Ham... | stack_v2_sparse_classes_75kplus_train_006538 | 24,309 | no_license | [
{
"docstring": "Create runner for the model `prm`. Parameters ---------- prm : Hubbard_Parameters Parameters of the Hamiltonian. starting_point : {'auto', 'resume', 'Hartree', 'Hubbard-I'}, optional What kind of starting point is used. 'resume' loads previous iteration (layer data with largest iteration number)... | 3 | stack_v2_sparse_classes_30k_train_004302 | Implement the Python class `Runner` described below.
Class description:
Run r-DMFT loop using `Runner.iteration`.
Method signatures and docstrings:
- def __init__(self, prm: Hubbard_Parameters, starting_point='auto', output_dir=None, default_solver=sb_qmc.solve) -> None: Create runner for the model `prm`. Parameters ... | Implement the Python class `Runner` described below.
Class description:
Run r-DMFT loop using `Runner.iteration`.
Method signatures and docstrings:
- def __init__(self, prm: Hubbard_Parameters, starting_point='auto', output_dir=None, default_solver=sb_qmc.solve) -> None: Create runner for the model `prm`. Parameters ... | 18dba6f322f27733307b4d0679e7629d69689415 | <|skeleton|>
class Runner:
"""Run r-DMFT loop using `Runner.iteration`."""
def __init__(self, prm: Hubbard_Parameters, starting_point='auto', output_dir=None, default_solver=sb_qmc.solve) -> None:
"""Create runner for the model `prm`. Parameters ---------- prm : Hubbard_Parameters Parameters of the Ham... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Runner:
"""Run r-DMFT loop using `Runner.iteration`."""
def __init__(self, prm: Hubbard_Parameters, starting_point='auto', output_dir=None, default_solver=sb_qmc.solve) -> None:
"""Create runner for the model `prm`. Parameters ---------- prm : Hubbard_Parameters Parameters of the Hamiltonian. sta... | the_stack_v2_python_sparse | layer_dmft/layer_dmft.py | DerWeh/layer_dmft | train | 0 |
83d10a260d7fbb82f3a2307cc5fc2da1e3e7ea06 | [
"is_valid = True\ntry:\n fips = item[0]\n name = item[2]\n geoid = int(item[3])\nexcept:\n is_valid = False\nif is_valid and fips and name:\n return is_valid\nlogger.warning('Invalid Record: ({item})'.format(item=item))\nreturn False",
"division = self._get_division_cache(data['division_fips'])\nif... | <|body_start_0|>
is_valid = True
try:
fips = item[0]
name = item[2]
geoid = int(item[3])
except:
is_valid = False
if is_valid and fips and name:
return is_valid
logger.warning('Invalid Record: ({item})'.format(item=item)... | Command | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
def is_entry_valid(self, item):
"""Checks for minimum subdivision requirements."""
<|body_0|>
def get_query_fields(self, data):
"""Fields to identify a subdivision record."""
<|body_1|>
def record_to_dict(self, item):
"""Given a division... | stack_v2_sparse_classes_75kplus_train_006539 | 2,957 | permissive | [
{
"docstring": "Checks for minimum subdivision requirements.",
"name": "is_entry_valid",
"signature": "def is_entry_valid(self, item)"
},
{
"docstring": "Fields to identify a subdivision record.",
"name": "get_query_fields",
"signature": "def get_query_fields(self, data)"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_050244 | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def is_entry_valid(self, item): Checks for minimum subdivision requirements.
- def get_query_fields(self, data): Fields to identify a subdivision record.
- def record_to_dict(self,... | Implement the Python class `Command` described below.
Class description:
Implement the Command class.
Method signatures and docstrings:
- def is_entry_valid(self, item): Checks for minimum subdivision requirements.
- def get_query_fields(self, data): Fields to identify a subdivision record.
- def record_to_dict(self,... | cd7c51e358e5b2d2c3ca92626edbdd7e4f573ab8 | <|skeleton|>
class Command:
def is_entry_valid(self, item):
"""Checks for minimum subdivision requirements."""
<|body_0|>
def get_query_fields(self, data):
"""Fields to identify a subdivision record."""
<|body_1|>
def record_to_dict(self, item):
"""Given a division... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Command:
def is_entry_valid(self, item):
"""Checks for minimum subdivision requirements."""
is_valid = True
try:
fips = item[0]
name = item[2]
geoid = int(item[3])
except:
is_valid = False
if is_valid and fips and name:
... | the_stack_v2_python_sparse | geoware/management/commands/subdivision.py | un33k/django-geoware | train | 4 | |
f2574cdff829c35b966d5a960426aaf591d565ff | [
"if files is None:\n files = ['meta.yaml', 'build.sh']\nchanged = set()\nfor path in self.list_changed_files(ref, other):\n if not path.startswith(self.recipes_folder):\n continue\n for fname in files:\n if os.path.basename(path) == fname:\n changed.add(os.path.dirname(path))\nretu... | <|body_start_0|>
if files is None:
files = ['meta.yaml', 'build.sh']
changed = set()
for path in self.list_changed_files(ref, other):
if not path.startswith(self.recipes_folder):
continue
for fname in files:
if os.path.basename(... | Githandler with logic specific to Bioconda Repo | BiocondaRepoMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiocondaRepoMixin:
"""Githandler with logic specific to Bioconda Repo"""
def get_changed_recipes(self, ref=None, other=None, files=None):
"""Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD other: See `get_merge_base`. Defaults to origin/master files... | stack_v2_sparse_classes_75kplus_train_006540 | 25,216 | permissive | [
{
"docstring": "Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD other: See `get_merge_base`. Defaults to origin/master files: List of files to consider. Defaults to ``meta.yaml`` and ``build.sh`` Result: List of unique recipe folders with changes. Path is from repo root (e.g. ... | 4 | stack_v2_sparse_classes_30k_train_046241 | Implement the Python class `BiocondaRepoMixin` described below.
Class description:
Githandler with logic specific to Bioconda Repo
Method signatures and docstrings:
- def get_changed_recipes(self, ref=None, other=None, files=None): Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD oth... | Implement the Python class `BiocondaRepoMixin` described below.
Class description:
Githandler with logic specific to Bioconda Repo
Method signatures and docstrings:
- def get_changed_recipes(self, ref=None, other=None, files=None): Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD oth... | 9a85115ae306f58c8b4e65e5f92f6cbdb5b68f04 | <|skeleton|>
class BiocondaRepoMixin:
"""Githandler with logic specific to Bioconda Repo"""
def get_changed_recipes(self, ref=None, other=None, files=None):
"""Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD other: See `get_merge_base`. Defaults to origin/master files... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BiocondaRepoMixin:
"""Githandler with logic specific to Bioconda Repo"""
def get_changed_recipes(self, ref=None, other=None, files=None):
"""Returns list of modified recipes Args: ref: See `get_merge_base`. Defaults to HEAD other: See `get_merge_base`. Defaults to origin/master files: List of fil... | the_stack_v2_python_sparse | bioconda_utils/githandler.py | bioconda/bioconda-utils | train | 106 |
6e496121999f5a37a17d3e184866cc98b9a7d96e | [
"if not matrix:\n return\nn = matrix.__len__()\nrotate = [[0 for _ in range(n)] for _ in range(n)]\nfor i in range(n):\n for j in range(n):\n rotate[j][n - 1 - i] = matrix[i][j]\nmatrix[:] = rotate[:]",
"if not matrix:\n return\nn = matrix.__len__()\nmatrix.reverse()\nfor i in range(n):\n for j... | <|body_start_0|>
if not matrix:
return
n = matrix.__len__()
rotate = [[0 for _ in range(n)] for _ in range(n)]
for i in range(n):
for j in range(n):
rotate[j][n - 1 - i] = matrix[i][j]
matrix[:] = rotate[:]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_75kplus_train_006541 | 1,454 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "rotate",
"signature": "def rotate(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
... | 2 | stack_v2_sparse_classes_30k_train_038497 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix): :type matrix: List[List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate1(self, matrix): :type matrix: List[List[... | 472f780c3214aab5c713612812d834ccbe589434 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate1(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
if not matrix:
return
n = matrix.__len__()
rotate = [[0 for _ in range(n)] for _ in range(n)]
for i in range(n):
... | the_stack_v2_python_sparse | 2/48-Rotate_Image.py | ChangXiaodong/Leetcode-solutions | train | 4 | |
74287659e00de320b5cca17a048fd0f1914775ec | [
"chans = self._get_chans(spec_data.metadata.chans)\nlogger.info(f'Calibrating channels {chans}')\nmessages = [f'Calibrating channels {chans}']\ndata = {x: np.array(y) for x, y in spec_data.data.items()}\nfor chan in chans:\n logger.info(f'Looking for sensor calibration data for channel {chan}')\n cal_data = s... | <|body_start_0|>
chans = self._get_chans(spec_data.metadata.chans)
logger.info(f'Calibrating channels {chans}')
messages = [f'Calibrating channels {chans}']
data = {x: np.array(y) for x, y in spec_data.data.items()}
for chan in chans:
logger.info(f'Looking for sensor ... | SensorCalibrator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensorCalibrator:
def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData:
"""Calibrate Spectra data"""
<|body_0|>
def _get_cal_data(self, dir_path: Path, metadata: SpectraMetadata, chan: str) -> Union[CalibrationData, None]:
"""Get the calibration data"... | stack_v2_sparse_classes_75kplus_train_006542 | 18,607 | permissive | [
{
"docstring": "Calibrate Spectra data",
"name": "run",
"signature": "def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData"
},
{
"docstring": "Get the calibration data",
"name": "_get_cal_data",
"signature": "def _get_cal_data(self, dir_path: Path, metadata: SpectraMetada... | 2 | stack_v2_sparse_classes_30k_train_012236 | Implement the Python class `SensorCalibrator` described below.
Class description:
Implement the SensorCalibrator class.
Method signatures and docstrings:
- def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData: Calibrate Spectra data
- def _get_cal_data(self, dir_path: Path, metadata: SpectraMetadata, ... | Implement the Python class `SensorCalibrator` described below.
Class description:
Implement the SensorCalibrator class.
Method signatures and docstrings:
- def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData: Calibrate Spectra data
- def _get_cal_data(self, dir_path: Path, metadata: SpectraMetadata, ... | cba60747803b6c582eaaf1a670a7f455f5724ebd | <|skeleton|>
class SensorCalibrator:
def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData:
"""Calibrate Spectra data"""
<|body_0|>
def _get_cal_data(self, dir_path: Path, metadata: SpectraMetadata, chan: str) -> Union[CalibrationData, None]:
"""Get the calibration data"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SensorCalibrator:
def run(self, dir_path: Path, spec_data: SpectraData) -> SpectraData:
"""Calibrate Spectra data"""
chans = self._get_chans(spec_data.metadata.chans)
logger.info(f'Calibrating channels {chans}')
messages = [f'Calibrating channels {chans}']
data = {x: np... | the_stack_v2_python_sparse | resistics/calibrate.py | resistics/resistics | train | 47 | |
90c3fe5de5e014f36260d94e850e5cf3a5b679c5 | [
"producer = Producer()\nrecord_metadata = producer.send_message(TOPIC, URL, REGEX, TEST_DATA).get(timeout=5)\nassert record_metadata.topic == TOPIC, 'Stats should be sent properly to topic {}.'.format(TOPIC)",
"producer = Producer()\nwith pytest.raises(KafkaTimeoutError):\n producer.send_message('topic_not_exi... | <|body_start_0|>
producer = Producer()
record_metadata = producer.send_message(TOPIC, URL, REGEX, TEST_DATA).get(timeout=5)
assert record_metadata.topic == TOPIC, 'Stats should be sent properly to topic {}.'.format(TOPIC)
<|end_body_0|>
<|body_start_1|>
producer = Producer()
wit... | This is to Producer. | TestProducer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestProducer:
"""This is to Producer."""
def test_send_message(self):
"""Verify producer should send message properly."""
<|body_0|>
def test_send_message_to_non_existing_topic(self):
"""Verify exception should occur is producer tries to send message to non exist... | stack_v2_sparse_classes_75kplus_train_006543 | 2,132 | no_license | [
{
"docstring": "Verify producer should send message properly.",
"name": "test_send_message",
"signature": "def test_send_message(self)"
},
{
"docstring": "Verify exception should occur is producer tries to send message to non existing topic.",
"name": "test_send_message_to_non_existing_topic... | 3 | stack_v2_sparse_classes_30k_train_001176 | Implement the Python class `TestProducer` described below.
Class description:
This is to Producer.
Method signatures and docstrings:
- def test_send_message(self): Verify producer should send message properly.
- def test_send_message_to_non_existing_topic(self): Verify exception should occur is producer tries to send... | Implement the Python class `TestProducer` described below.
Class description:
This is to Producer.
Method signatures and docstrings:
- def test_send_message(self): Verify producer should send message properly.
- def test_send_message_to_non_existing_topic(self): Verify exception should occur is producer tries to send... | 4f86f5695b853d4a7871e7b90acf36f5bc6dd21f | <|skeleton|>
class TestProducer:
"""This is to Producer."""
def test_send_message(self):
"""Verify producer should send message properly."""
<|body_0|>
def test_send_message_to_non_existing_topic(self):
"""Verify exception should occur is producer tries to send message to non exist... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestProducer:
"""This is to Producer."""
def test_send_message(self):
"""Verify producer should send message properly."""
producer = Producer()
record_metadata = producer.send_message(TOPIC, URL, REGEX, TEST_DATA).get(timeout=5)
assert record_metadata.topic == TOPIC, 'Stat... | the_stack_v2_python_sparse | testcases/test_producer.py | anujkumar21/monitoring | train | 0 |
159419af10996331a0a880ef0493a1d4d3129850 | [
"super().__init__(ordered_dict)\nself.__verify(required_keys)\nself.__fill(optional_keys)",
"keys = set(self.keys())\nrequired_keys = set(required_keys)\nif not required_keys <= keys:\n missing_keys = required_keys - keys\n raise KeyError('Missing required keys: ' + str(missing_keys))",
"for optional_key ... | <|body_start_0|>
super().__init__(ordered_dict)
self.__verify(required_keys)
self.__fill(optional_keys)
<|end_body_0|>
<|body_start_1|>
keys = set(self.keys())
required_keys = set(required_keys)
if not required_keys <= keys:
missing_keys = required_keys - key... | MagicDict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicDict:
def __init__(self, ordered_dict, required_keys, optional_keys):
"""Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies all keys we expect in the data are there and adds any optional ones into the data as None. :param o... | stack_v2_sparse_classes_75kplus_train_006544 | 3,535 | no_license | [
{
"docstring": "Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies all keys we expect in the data are there and adds any optional ones into the data as None. :param ordered_dict: The ordered dictionary we'd like to format :param required_keys: The keys... | 6 | stack_v2_sparse_classes_30k_train_036164 | Implement the Python class `MagicDict` described below.
Class description:
Implement the MagicDict class.
Method signatures and docstrings:
- def __init__(self, ordered_dict, required_keys, optional_keys): Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies a... | Implement the Python class `MagicDict` described below.
Class description:
Implement the MagicDict class.
Method signatures and docstrings:
- def __init__(self, ordered_dict, required_keys, optional_keys): Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies a... | 1cfbdc0f4967b809bda5c0406d9baf344990f481 | <|skeleton|>
class MagicDict:
def __init__(self, ordered_dict, required_keys, optional_keys):
"""Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies all keys we expect in the data are there and adds any optional ones into the data as None. :param o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MagicDict:
def __init__(self, ordered_dict, required_keys, optional_keys):
"""Initializes a magic dict instance. This method is similar to the OrderedDict constructor, but it also verifies all keys we expect in the data are there and adds any optional ones into the data as None. :param ordered_dict: T... | the_stack_v2_python_sparse | billserve/api/networking/models/MagicDict.py | BtLutz/billserve-container | train | 0 | |
61c0b19cb779d608ca7ddd34b11481d5992f78fb | [
"with catch(self):\n if not self.params['code']:\n self.error('缺少code')\n return\n info = (yield self.company_service.fetch_with_code(self.params['code']))\n self.success(info)",
"with catch(self):\n self.guarantee('mobile')\n validate_mobile(self.params['mobile'])\n info = (yield ... | <|body_start_0|>
with catch(self):
if not self.params['code']:
self.error('缺少code')
return
info = (yield self.company_service.fetch_with_code(self.params['code']))
self.success(info)
<|end_body_0|>
<|body_start_1|>
with catch(self):
... | CompanyApplicationHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompanyApplicationHandler:
def get(self):
"""@api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @apiSuccessExample {json} Success-Response: HTTP/1.1 200 OK { "status": 0, "msg": "success", "data": { "cid": 1, "c... | stack_v2_sparse_classes_75kplus_train_006545 | 27,125 | no_license | [
{
"docstring": "@api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @apiSuccessExample {json} Success-Response: HTTP/1.1 200 OK { \"status\": 0, \"msg\": \"success\", \"data\": { \"cid\": 1, \"company_name\": \"十全\", \"contact\": \"1390... | 2 | stack_v2_sparse_classes_30k_train_025822 | Implement the Python class `CompanyApplicationHandler` described below.
Class description:
Implement the CompanyApplicationHandler class.
Method signatures and docstrings:
- def get(self): @api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @... | Implement the Python class `CompanyApplicationHandler` described below.
Class description:
Implement the CompanyApplicationHandler class.
Method signatures and docstrings:
- def get(self): @api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @... | 0b09280afe5b764a485b3bf6e760aaf9a68bc4d5 | <|skeleton|>
class CompanyApplicationHandler:
def get(self):
"""@api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @apiSuccessExample {json} Success-Response: HTTP/1.1 200 OK { "status": 0, "msg": "success", "data": { "cid": 1, "c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CompanyApplicationHandler:
def get(self):
"""@api {get} /api/company/application 员工申请加入的初始条件 @apiName CompanyApplicationGetHandler @apiGroup Company @apiParam {String} code @apiSuccessExample {json} Success-Response: HTTP/1.1 200 OK { "status": 0, "msg": "success", "data": { "cid": 1, "company_name": ... | the_stack_v2_python_sparse | handler/company/company.py | pickCloud/TenCloud_Backend | train | 0 | |
f65cfbcebe6877a956f8814b8f9cd80e0b528cc0 | [
"self.userTweetlistDict = {}\nself.graphAdjDict = {}\nself.timeStamp = 0",
"self.timeStamp = self.timeStamp + 1\nif userId not in self.userTweetlistDict:\n temp = []\n temp.append((tweetId, self.timeStamp))\n self.userTweetlistDict[userId] = temp\nelse:\n temp = self.userTweetlistDict[userId]\n tem... | <|body_start_0|>
self.userTweetlistDict = {}
self.graphAdjDict = {}
self.timeStamp = 0
<|end_body_0|>
<|body_start_1|>
self.timeStamp = self.timeStamp + 1
if userId not in self.userTweetlistDict:
temp = []
temp.append((tweetId, self.timeStamp))
... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_75kplus_train_006546 | 3,785 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet. :type userId: int :type tweetId: int :rtype: void",
"name": "postTweet",
"signature": "def postTweet(self, userId, tweetId)"
},
{
"... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | 0a2e0e4a5176c02910d7718c42903d10a6c47a5f | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.userTweetlistDict = {}
self.graphAdjDict = {}
self.timeStamp = 0
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
... | the_stack_v2_python_sparse | design_twitter.py | baichuan/Leetcode | train | 0 | |
e4200a907d477d8145c14bd32f2bc7e5a2df4fb3 | [
"asserts.type_of(account_dto, AccountDto)\naccount_ndb = Account()\nmap_props(account_ndb, account_dto, cls._props)\nreturn account_ndb",
"asserts.type_of(account_ndb, Account)\naccount_dto = AccountDto()\nmap_props(account_dto, account_ndb, cls._props)\nreturn account_dto"
] | <|body_start_0|>
asserts.type_of(account_dto, AccountDto)
account_ndb = Account()
map_props(account_ndb, account_dto, cls._props)
return account_ndb
<|end_body_0|>
<|body_start_1|>
asserts.type_of(account_ndb, Account)
account_dto = AccountDto()
map_props(account... | AccountDto | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountDto:
def to_account_ndb(cls, account_dto):
"""Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)"""
<|body_0|>
def from_account_ndb(cls, account_ndb):
"""Translates the given Ac... | stack_v2_sparse_classes_75kplus_train_006547 | 4,124 | no_license | [
{
"docstring": "Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)",
"name": "to_account_ndb",
"signature": "def to_account_ndb(cls, account_dto)"
},
{
"docstring": "Translates the given Account NDB to AccountDto.... | 2 | stack_v2_sparse_classes_30k_train_021838 | Implement the Python class `AccountDto` described below.
Class description:
Implement the AccountDto class.
Method signatures and docstrings:
- def to_account_ndb(cls, account_dto): Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)
- ... | Implement the Python class `AccountDto` described below.
Class description:
Implement the AccountDto class.
Method signatures and docstrings:
- def to_account_ndb(cls, account_dto): Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)
- ... | 1d6522069da3e5a6de41ce948b04872d0a994cca | <|skeleton|>
class AccountDto:
def to_account_ndb(cls, account_dto):
"""Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)"""
<|body_0|>
def from_account_ndb(cls, account_ndb):
"""Translates the given Ac... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AccountDto:
def to_account_ndb(cls, account_dto):
"""Translates the given AccountDto to Account NDB model. :param account_dto: (dto.accounts.AccountDto) :return: (kinds.accounts.Account)"""
asserts.type_of(account_dto, AccountDto)
account_ndb = Account()
map_props(account_ndb, ... | the_stack_v2_python_sparse | models/dto/accounts.py | venvadlamani/HumanLink | train | 0 | |
48f1522337e0c96dcfa1ce7627c658e4ff7c7d66 | [
"user = User.from_db(username)\nif not user:\n api.abort(404, 'No such user')\nreturn (user, 200)",
"user = User.from_db(username)\nif not user:\n api.abort(404, 'No such user')\nargs = user_modify_parser.parse_args()\ntry:\n user.modify(args.changes)\nexcept json.decoder.JSONDecodeError:\n api.abort(... | <|body_start_0|>
user = User.from_db(username)
if not user:
api.abort(404, 'No such user')
return (user, 200)
<|end_body_0|>
<|body_start_1|>
user = User.from_db(username)
if not user:
api.abort(404, 'No such user')
args = user_modify_parser.parse... | SpecificUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecificUser:
def get(self, username):
"""Get a specific user"""
<|body_0|>
def patch(self, username):
"""Modify a specific user"""
<|body_1|>
def delete(self, username):
"""Delete a specific user"""
<|body_2|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_75kplus_train_006548 | 12,864 | no_license | [
{
"docstring": "Get a specific user",
"name": "get",
"signature": "def get(self, username)"
},
{
"docstring": "Modify a specific user",
"name": "patch",
"signature": "def patch(self, username)"
},
{
"docstring": "Delete a specific user",
"name": "delete",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_031983 | Implement the Python class `SpecificUser` described below.
Class description:
Implement the SpecificUser class.
Method signatures and docstrings:
- def get(self, username): Get a specific user
- def patch(self, username): Modify a specific user
- def delete(self, username): Delete a specific user | Implement the Python class `SpecificUser` described below.
Class description:
Implement the SpecificUser class.
Method signatures and docstrings:
- def get(self, username): Get a specific user
- def patch(self, username): Modify a specific user
- def delete(self, username): Delete a specific user
<|skeleton|>
class ... | ab8c722673d5c43e5bd40c4747c374a73ea56ccc | <|skeleton|>
class SpecificUser:
def get(self, username):
"""Get a specific user"""
<|body_0|>
def patch(self, username):
"""Modify a specific user"""
<|body_1|>
def delete(self, username):
"""Delete a specific user"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SpecificUser:
def get(self, username):
"""Get a specific user"""
user = User.from_db(username)
if not user:
api.abort(404, 'No such user')
return (user, 200)
def patch(self, username):
"""Modify a specific user"""
user = User.from_db(username)
... | the_stack_v2_python_sparse | kovaak_stats_back/kovaak_stats/api/users.py | ftsn/kovaak-stats-viewer | train | 0 | |
b331b82d4ea7ac8cc3d7ca4d257317286937b6fe | [
"if isinstance(type, str):\n type = getattr(DiskType, type)\nvolume = Volume()\nvolume.size = size\nvolume.type = type\nvolume.info.node_id = node_id\nvolume.info.pool_id = pool_id\nvolume.info.workload_type = WorkloadType.Volume\nreturn volume",
"if isinstance(volume_id, Volume):\n if not volume_id.id:\n ... | <|body_start_0|>
if isinstance(type, str):
type = getattr(DiskType, type)
volume = Volume()
volume.size = size
volume.type = type
volume.info.node_id = node_id
volume.info.pool_id = pool_id
volume.info.workload_type = WorkloadType.Volume
return... | VolumesGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumesGenerator:
def create(self, node_id: str, pool_id: int, size: int=5, type: Union[str, DiskType]=DiskType.HDD) -> Volume:
"""add a volume to the reservation Args: node_id(str): id of the node where to reserve the volume pool_id(int) the capacity pool ID size(int, optional): size in... | stack_v2_sparse_classes_75kplus_train_006549 | 1,932 | permissive | [
{
"docstring": "add a volume to the reservation Args: node_id(str): id of the node where to reserve the volume pool_id(int) the capacity pool ID size(int, optional): size in GiB. Defaults to 5. type(Union[str,DiskType], optional): type of disk to use. Can be SSD or HDD. Defaults to \"HDD\". Returns: Volume: the... | 2 | stack_v2_sparse_classes_30k_train_027155 | Implement the Python class `VolumesGenerator` described below.
Class description:
Implement the VolumesGenerator class.
Method signatures and docstrings:
- def create(self, node_id: str, pool_id: int, size: int=5, type: Union[str, DiskType]=DiskType.HDD) -> Volume: add a volume to the reservation Args: node_id(str): ... | Implement the Python class `VolumesGenerator` described below.
Class description:
Implement the VolumesGenerator class.
Method signatures and docstrings:
- def create(self, node_id: str, pool_id: int, size: int=5, type: Union[str, DiskType]=DiskType.HDD) -> Volume: add a volume to the reservation Args: node_id(str): ... | e44e950daeced3a6713b39f0d6dae1fa681e1d11 | <|skeleton|>
class VolumesGenerator:
def create(self, node_id: str, pool_id: int, size: int=5, type: Union[str, DiskType]=DiskType.HDD) -> Volume:
"""add a volume to the reservation Args: node_id(str): id of the node where to reserve the volume pool_id(int) the capacity pool ID size(int, optional): size in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VolumesGenerator:
def create(self, node_id: str, pool_id: int, size: int=5, type: Union[str, DiskType]=DiskType.HDD) -> Volume:
"""add a volume to the reservation Args: node_id(str): id of the node where to reserve the volume pool_id(int) the capacity pool ID size(int, optional): size in GiB. Defaults... | the_stack_v2_python_sparse | jumpscale/sals/zos/volumes.py | xmonader/js-sdk | train | 0 | |
3a57da770d749e5f44098e7398b089517e2d9395 | [
"assert gamma >= 1, 'gamma must be >= 1 (E^(-gamma))'\nassert 0 <= e_min <= e_max, 'energy limits must be 0 <= e_min <= e_max'\nmsg = 'direction must be None or direction in [0, 2pi)'\nassert direction is None or 0 <= direction < 2 * np.pi, msg\nself.name = name\nself.e_min = e_min\nself.e_max = e_max\nself.gamma =... | <|body_start_0|>
assert gamma >= 1, 'gamma must be >= 1 (E^(-gamma))'
assert 0 <= e_min <= e_max, 'energy limits must be 0 <= e_min <= e_max'
msg = 'direction must be None or direction in [0, 2pi)'
assert direction is None or 0 <= direction < 2 * np.pi, msg
self.name = name
... | Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived class must implement: __init__ generate(num, random_seed) Attributes ---------- direction... | BaseParticleGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseParticleGenerator:
"""Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived class must implement: __init__ generate(... | stack_v2_sparse_classes_75kplus_train_006550 | 7,692 | no_license | [
{
"docstring": "Initialize base particle generator. Parameters ---------- e_min : float The minimium particle energy to generate. This must be greater equal zero and not greater than e_max. e_max : float The maximum particle energy to generate. This must be greater equal zero and not less than e_min. gamma : fl... | 5 | stack_v2_sparse_classes_30k_train_035824 | Implement the Python class `BaseParticleGenerator` described below.
Class description:
Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived c... | Implement the Python class `BaseParticleGenerator` described below.
Class description:
Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived c... | 0d7442bd78f9899536a109e87a4c4639ade82a58 | <|skeleton|>
class BaseParticleGenerator:
"""Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived class must implement: __init__ generate(... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseParticleGenerator:
"""Base particle generator class. This class is intended as a base class for particle generators. Each particle type must create their own generator class if the particle has new parameters other than the ones sampled here. A derived class must implement: __init__ generate(num, random_s... | the_stack_v2_python_sparse | project_a5/simulation/generator/base_generator.py | yungsalami/linuxtest | train | 0 |
8d5f2e5f279a28e46143e65199a4b1ba6a5068fd | [
"s3 = chrono.perf_counter()\nitems = list(data.keys())\nn = len(data.columns)\ninit = 0\ne = pd.DataFrame(dtype=float)\ne = self._around_event_recur_(n, data, e, reward, items, init)\nself.around_event = e\ns4 = chrono.perf_counter()\nlogging.debug(f'Fin Event, durée all via map: {s4 - s3}')\nreturn self.around_eve... | <|body_start_0|>
s3 = chrono.perf_counter()
items = list(data.keys())
n = len(data.columns)
init = 0
e = pd.DataFrame(dtype=float)
e = self._around_event_recur_(n, data, e, reward, items, init)
self.around_event = e
s4 = chrono.perf_counter()
loggi... | PreFormatData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreFormatData:
def make_event_around(self, data: DataFrame, reward: Series):
"""Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour en extraire les valeurs correctement calcul pour toutes les colonnes d'un dataframe :param data: :par... | stack_v2_sparse_classes_75kplus_train_006551 | 2,213 | no_license | [
{
"docstring": "Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour en extraire les valeurs correctement calcul pour toutes les colonnes d'un dataframe :param data: :param reward: c'est les temps des event en ms sur lesquel on ce calle :return:",
"name"... | 2 | stack_v2_sparse_classes_30k_test_002399 | Implement the Python class `PreFormatData` described below.
Class description:
Implement the PreFormatData class.
Method signatures and docstrings:
- def make_event_around(self, data: DataFrame, reward: Series): Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour... | Implement the Python class `PreFormatData` described below.
Class description:
Implement the PreFormatData class.
Method signatures and docstrings:
- def make_event_around(self, data: DataFrame, reward: Series): Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour... | 82f9c78828a1e1fb6c3d60d91777638720129e1a | <|skeleton|>
class PreFormatData:
def make_event_around(self, data: DataFrame, reward: Series):
"""Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour en extraire les valeurs correctement calcul pour toutes les colonnes d'un dataframe :param data: :par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreFormatData:
def make_event_around(self, data: DataFrame, reward: Series):
"""Pour utiliser cette methode il faut que la series des event soit indexé sur la base de temps des data pour en extraire les valeurs correctement calcul pour toutes les colonnes d'un dataframe :param data: :param reward: c'e... | the_stack_v2_python_sparse | build/lib/py_NPClab_Package/utilitaire_traitement/PreFormatData.py | NPC-lab-python/py_NPC-Lab_Packages | train | 0 | |
db4cc6e0b0b73a8322049990eed24a3f0439f549 | [
"usuario_actual = LoginControlador.token_requerido_grpc(token)\nif usuario_actual is None:\n error = ManejadorDeArchivos_pb2.Error.TOKEN_INVALIDO\n ValidacionServiciosGrpc.logger.info(ip + ' -- Error autenticacion: TOKEN_INVALIDO')\n return error",
"if token is None or token == '':\n error = Manejador... | <|body_start_0|>
usuario_actual = LoginControlador.token_requerido_grpc(token)
if usuario_actual is None:
error = ManejadorDeArchivos_pb2.Error.TOKEN_INVALIDO
ValidacionServiciosGrpc.logger.info(ip + ' -- Error autenticacion: TOKEN_INVALIDO')
return error
<|end_body_0... | ValidacionServiciosGrpc | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidacionServiciosGrpc:
def validar_token_valido(token, ip):
"""Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual se le realizara la validación de su solicitud :return: None si el token es valido o un ManejadorDeArchivos_pb2.Er... | stack_v2_sparse_classes_75kplus_train_006552 | 3,065 | no_license | [
{
"docstring": "Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual se le realizara la validación de su solicitud :return: None si el token es valido o un ManejadorDeArchivos_pb2.Error.TOKEN_INVALIDO",
"name": "validar_token_valido",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_030736 | Implement the Python class `ValidacionServiciosGrpc` described below.
Class description:
Implement the ValidacionServiciosGrpc class.
Method signatures and docstrings:
- def validar_token_valido(token, ip): Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual s... | Implement the Python class `ValidacionServiciosGrpc` described below.
Class description:
Implement the ValidacionServiciosGrpc class.
Method signatures and docstrings:
- def validar_token_valido(token, ip): Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual s... | 49bbaaf0bd4d1bec2d81eb35882e5f073b1c149f | <|skeleton|>
class ValidacionServiciosGrpc:
def validar_token_valido(token, ip):
"""Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual se le realizara la validación de su solicitud :return: None si el token es valido o un ManejadorDeArchivos_pb2.Er... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ValidacionServiciosGrpc:
def validar_token_valido(token, ip):
"""Valida que el token es un token valido :param token: El token a validar :param ip: El ip del cliente del cual se le realizara la validación de su solicitud :return: None si el token es valido o un ManejadorDeArchivos_pb2.Error.TOKEN_INVA... | the_stack_v2_python_sparse | app/util/validaciones/servicios_grpc/ValidacionServiciosGrpc.py | codeChinoUV/EspotifeiAPI | train | 0 | |
98c13f6904e9569bae18bb2f8cd49abdf5f98cc2 | [
"count = 0\nwhile n:\n if n & 1 == 1:\n count += 1\n n = n >> 1\n if count > 1:\n return False\nif count == 0:\n return False\nreturn True",
"if n == 0:\n return False\ncount = 0\nfor i in range(2):\n count += 1\n n = n & n - 1\n if n == 0:\n break\nif count != 1:\n ... | <|body_start_0|>
count = 0
while n:
if n & 1 == 1:
count += 1
n = n >> 1
if count > 1:
return False
if count == 0:
return False
return True
<|end_body_0|>
<|body_start_1|>
if n == 0:
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfTwo3(self, n: int) -> bool:
"""位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1"""
<|body_0|>
def isPowerOfTwo2(self, n: int) -> bool:
"""位运算(推荐) 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1。 计算1的个数是否为1"""
<|body_1... | stack_v2_sparse_classes_75kplus_train_006553 | 1,448 | no_license | [
{
"docstring": "位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1",
"name": "isPowerOfTwo3",
"signature": "def isPowerOfTwo3(self, n: int) -> bool"
},
{
"docstring": "位运算(推荐) 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1。 计算1的个数是否为1",
"name": "isPowerOfTwo2",
"signatu... | 3 | stack_v2_sparse_classes_30k_train_040887 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo3(self, n: int) -> bool: 位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1
- def isPowerOfTwo2(self, n: int) -> bool: 位运算(推荐) 1 2 10 2 100 4 1000 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo3(self, n: int) -> bool: 位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1
- def isPowerOfTwo2(self, n: int) -> bool: 位运算(推荐) 1 2 10 2 100 4 1000 ... | c0dd577481b46129d950354d567d332a4d091137 | <|skeleton|>
class Solution:
def isPowerOfTwo3(self, n: int) -> bool:
"""位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1"""
<|body_0|>
def isPowerOfTwo2(self, n: int) -> bool:
"""位运算(推荐) 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1。 计算1的个数是否为1"""
<|body_1... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def isPowerOfTwo3(self, n: int) -> bool:
"""位运算 1 2 10 2 100 4 1000 8 10000 16 如上所述，2的幂的二进制仅包含一个1. 计算1的个数是否为1"""
count = 0
while n:
if n & 1 == 1:
count += 1
n = n >> 1
if count > 1:
return False
if c... | the_stack_v2_python_sparse | leetcode/231_2的幂.py | tenqaz/crazy_arithmetic | train | 0 | |
f2d8bce1b2e6f5f4b03aa36fc9250c3a3ea68e63 | [
"if request.user.is_authenticated:\n user_object = get_object_or_404(UserSet.queryset, pk=request.user.pk)\n return JsonResponse(UserSerializer(user_object).data, status=status.HTTP_200_OK)\nreturn JsonResponse(data={'error': 'forbidden'}, status=status.HTTP_403_FORBIDDEN)",
"if not request.user.is_authenti... | <|body_start_0|>
if request.user.is_authenticated:
user_object = get_object_or_404(UserSet.queryset, pk=request.user.pk)
return JsonResponse(UserSerializer(user_object).data, status=status.HTTP_200_OK)
return JsonResponse(data={'error': 'forbidden'}, status=status.HTTP_403_FORBID... | UserSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSet:
def list(self, request, *args, **kwargs):
"""Function display only current user, not full list, like a retrieve, but without "pk" argument. :return JSON: string with object or error message"""
<|body_0|>
def retrieve(self, request, pk):
"""Function display o... | stack_v2_sparse_classes_75kplus_train_006554 | 13,687 | no_license | [
{
"docstring": "Function display only current user, not full list, like a retrieve, but without \"pk\" argument. :return JSON: string with object or error message",
"name": "list",
"signature": "def list(self, request, *args, **kwargs)"
},
{
"docstring": "Function display only current user, if y... | 5 | stack_v2_sparse_classes_30k_train_048122 | Implement the Python class `UserSet` described below.
Class description:
Implement the UserSet class.
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Function display only current user, not full list, like a retrieve, but without "pk" argument. :return JSON: string with object or error m... | Implement the Python class `UserSet` described below.
Class description:
Implement the UserSet class.
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Function display only current user, not full list, like a retrieve, but without "pk" argument. :return JSON: string with object or error m... | e4f7aab834c01de6f20d8bac85ede83fbca3a846 | <|skeleton|>
class UserSet:
def list(self, request, *args, **kwargs):
"""Function display only current user, not full list, like a retrieve, but without "pk" argument. :return JSON: string with object or error message"""
<|body_0|>
def retrieve(self, request, pk):
"""Function display o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserSet:
def list(self, request, *args, **kwargs):
"""Function display only current user, not full list, like a retrieve, but without "pk" argument. :return JSON: string with object or error message"""
if request.user.is_authenticated:
user_object = get_object_or_404(UserSet.querys... | the_stack_v2_python_sparse | executor/api/views.py | pywebexecutorgb/main | train | 0 | |
6664ed44dceba73c1b378f4a7d9931d6710bcbe0 | [
"self.Slack = namedtuple('Slack', ['api_token', 'channel', 'user', 'mecab'])\nself.config_file = 'enviroment_slack.yml'\nself.slack_channel = ''\nself.chan = ''\nself.user = ''\nself.mecab_dict = ''\nself.parameter_dict = {}\ntrain_path = '../data/'\nself.parameter_dict['source'] = train_path + 'player_1_wakati'\ns... | <|body_start_0|>
self.Slack = namedtuple('Slack', ['api_token', 'channel', 'user', 'mecab'])
self.config_file = 'enviroment_slack.yml'
self.slack_channel = ''
self.chan = ''
self.user = ''
self.mecab_dict = ''
self.parameter_dict = {}
train_path = '../data... | SlackModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlackModel:
def __init__(self):
"""setting paramater Slack model :return:"""
<|body_0|>
def read_config(self):
"""read config file for slack"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.Slack = namedtuple('Slack', ['api_token', 'channel', 'u... | stack_v2_sparse_classes_75kplus_train_006555 | 1,799 | permissive | [
{
"docstring": "setting paramater Slack model :return:",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "read config file for slack",
"name": "read_config",
"signature": "def read_config(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_029367 | Implement the Python class `SlackModel` described below.
Class description:
Implement the SlackModel class.
Method signatures and docstrings:
- def __init__(self): setting paramater Slack model :return:
- def read_config(self): read config file for slack | Implement the Python class `SlackModel` described below.
Class description:
Implement the SlackModel class.
Method signatures and docstrings:
- def __init__(self): setting paramater Slack model :return:
- def read_config(self): read config file for slack
<|skeleton|>
class SlackModel:
def __init__(self):
... | 2ea8bf0168ea53c804412b40fdb4d9b70b043073 | <|skeleton|>
class SlackModel:
def __init__(self):
"""setting paramater Slack model :return:"""
<|body_0|>
def read_config(self):
"""read config file for slack"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SlackModel:
def __init__(self):
"""setting paramater Slack model :return:"""
self.Slack = namedtuple('Slack', ['api_token', 'channel', 'user', 'mecab'])
self.config_file = 'enviroment_slack.yml'
self.slack_channel = ''
self.chan = ''
self.user = ''
self.... | the_stack_v2_python_sparse | slack/slack_model.py | SnowMasaya/Chainer-Slack-Twitter-Dialogue | train | 56 | |
4109b0a3748f7d5d98c91fd5f9cadfed173c5270 | [
"self.BATT_SIZE = 50\nself.FULL_CHAR = '+'\nself.EMPTY_CHAR = '.'\nself.empty = empty\nself.full = full\nself.charge = None",
"if self.charge is None:\n return None\nreturn saturate(self.charge, self.empty, self.full, 0, 100)",
"level = self.get_level()\nif level is None:\n return 'Awaiting data...'\nasse... | <|body_start_0|>
self.BATT_SIZE = 50
self.FULL_CHAR = '+'
self.EMPTY_CHAR = '.'
self.empty = empty
self.full = full
self.charge = None
<|end_body_0|>
<|body_start_1|>
if self.charge is None:
return None
return saturate(self.charge, self.empty,... | Represents a battery and defines its analog port and charge limits (eg, full, empty). | Battery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"... | stack_v2_sparse_classes_75kplus_train_006556 | 5,209 | no_license | [
{
"docstring": "Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery",
"name": "__init__",
"signature": "def __init__(self, empty=120, full=150)"
},
{
"docstring": "@return: the current charge of the battery as... | 3 | stack_v2_sparse_classes_30k_train_011618 | Implement the Python class `Battery` described below.
Class description:
Represents a battery and defines its analog port and charge limits (eg, full, empty).
Method signatures and docstrings:
- def __init__(self, empty=120, full=150): Constructor. @param empty: the raw signal value that indicates empty battery @para... | Implement the Python class `Battery` described below.
Class description:
Represents a battery and defines its analog port and charge limits (eg, full, empty).
Method signatures and docstrings:
- def __init__(self, empty=120, full=150): Constructor. @param empty: the raw signal value that indicates empty battery @para... | 52bacd9f58524090e0ab421a47714629249ca273 | <|skeleton|>
class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Battery:
"""Represents a battery and defines its analog port and charge limits (eg, full, empty)."""
def __init__(self, empty=120, full=150):
"""Constructor. @param empty: the raw signal value that indicates empty battery @param full: the raw signal value that indicates full battery"""
se... | the_stack_v2_python_sparse | src/09-10/ubc-tbird-ros-pkg/sb_util/scripts/battery_monitor.py | jpearkes/snowbots | train | 0 |
53b2dfd733cf264e13684fe707facabe6a5eeaa7 | [
"super().__init__(r_cut, **kwargs)\nself.grid_eam = grid_eam\nself.alpha = alpha\nself.r0 = r0",
"super().calculate(atoms, properties, system_changes)\nforces = np.zeros((len(self.atoms), 3))\npotential_energies = np.zeros((len(self.atoms), 1))\nfor i in range(len(self.atoms)):\n inds, pos, dists2 = self.nl.ge... | <|body_start_0|>
super().__init__(r_cut, **kwargs)
self.grid_eam = grid_eam
self.alpha = alpha
self.r0 = r0
<|end_body_0|>
<|body_start_1|>
super().calculate(atoms, properties, system_changes)
forces = np.zeros((len(self.atoms), 3))
potential_energies = np.zeros(... | A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object | EamSingleSpecies | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EamSingleSpecies:
"""A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object"""
def __init__(self, r_cut, grid_eam, alpha, r0, **kwargs):
"""Args: grid_eam (object): ... | stack_v2_sparse_classes_75kplus_train_006557 | 25,108 | permissive | [
{
"docstring": "Args: grid_eam (object): 1D Spline interpolator for the eam mapped grid r_cut (float): cutoff radius alpha (float): Exponential prefactor of the eam Descriptor r0 (float): Radius in the exponent of the eam Descriptor",
"name": "__init__",
"signature": "def __init__(self, r_cut, grid_eam,... | 2 | null | Implement the Python class `EamSingleSpecies` described below.
Class description:
A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object
Method signatures and docstrings:
- def __init__(self, r_cut, ... | Implement the Python class `EamSingleSpecies` described below.
Class description:
A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object
Method signatures and docstrings:
- def __init__(self, r_cut, ... | cd1b22b606dfd64d91dc94fece72ad6a707212af | <|skeleton|>
class EamSingleSpecies:
"""A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object"""
def __init__(self, r_cut, grid_eam, alpha, r0, **kwargs):
"""Args: grid_eam (object): ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EamSingleSpecies:
"""A mapped Eam calculator for ase Attributes: grid_eam (object): 1D Spline interpolator for the eam mapped grid results(dict): energy and forces calculated on the atoms object"""
def __init__(self, r_cut, grid_eam, alpha, r0, **kwargs):
"""Args: grid_eam (object): 1D Spline int... | the_stack_v2_python_sparse | mff/calculators.py | kcl-tscm/mff | train | 16 |
ce19eec972183543148b9ab60222eb0a5357d071 | [
"if Question.objects.filter(pk=kwargs['pk']).exists():\n qu = Question.objects.get(pk=kwargs['pk'])\n if qu.user != self.request.user:\n return HttpResponseForbidden('Access Denied')\nelse:\n return HttpResponseForbidden('Access Denied')\nreturn super(EditQuestionView, self).get(*args, **kwargs)",
... | <|body_start_0|>
if Question.objects.filter(pk=kwargs['pk']).exists():
qu = Question.objects.get(pk=kwargs['pk'])
if qu.user != self.request.user:
return HttpResponseForbidden('Access Denied')
else:
return HttpResponseForbidden('Access Denied')
... | Edit Question View | EditQuestionView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditQuestionView:
"""Edit Question View"""
def get(self, *args, **kwargs):
"""user can't edit the other users question"""
<|body_0|>
def form_valid(self, form):
"""Edit the update date of question"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_006558 | 7,882 | no_license | [
{
"docstring": "user can't edit the other users question",
"name": "get",
"signature": "def get(self, *args, **kwargs)"
},
{
"docstring": "Edit the update date of question",
"name": "form_valid",
"signature": "def form_valid(self, form)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020577 | Implement the Python class `EditQuestionView` described below.
Class description:
Edit Question View
Method signatures and docstrings:
- def get(self, *args, **kwargs): user can't edit the other users question
- def form_valid(self, form): Edit the update date of question | Implement the Python class `EditQuestionView` described below.
Class description:
Edit Question View
Method signatures and docstrings:
- def get(self, *args, **kwargs): user can't edit the other users question
- def form_valid(self, form): Edit the update date of question
<|skeleton|>
class EditQuestionView:
"""... | d89a811c5c928921a6ffac9120fd1d8d14dd4ac6 | <|skeleton|>
class EditQuestionView:
"""Edit Question View"""
def get(self, *args, **kwargs):
"""user can't edit the other users question"""
<|body_0|>
def form_valid(self, form):
"""Edit the update date of question"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EditQuestionView:
"""Edit Question View"""
def get(self, *args, **kwargs):
"""user can't edit the other users question"""
if Question.objects.filter(pk=kwargs['pk']).exists():
qu = Question.objects.get(pk=kwargs['pk'])
if qu.user != self.request.user:
... | the_stack_v2_python_sparse | forum/views.py | suman1oct/stack_overflow | train | 0 |
038f6697ae97aee0be2915251e6f5c966ad62680 | [
"arg_parser.add_argument('-i', '--input_file', type=Path, metavar='<input.hyper>', required=True, help='Input .hyper file')\narg_parser.add_argument('-o', '--output_file', type=Path, metavar='<output.hyper>', required=True, help='Output .hyper file')\narg_parser.add_argument('-m', '--mode', type=AdjustVertexOrderMo... | <|body_start_0|>
arg_parser.add_argument('-i', '--input_file', type=Path, metavar='<input.hyper>', required=True, help='Input .hyper file')
arg_parser.add_argument('-o', '--output_file', type=Path, metavar='<output.hyper>', required=True, help='Output .hyper file')
arg_parser.add_argument('-m', ... | Command to adjust vertex order of all polygons in a .hyper file | AdjustVertexOrder | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdjustVertexOrder:
"""Command to adjust vertex order of all polygons in a .hyper file"""
def define_args(self, arg_parser):
"""Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to"""
<|body_0|>
def run(self, args):
"""... | stack_v2_sparse_classes_75kplus_train_006559 | 8,875 | permissive | [
{
"docstring": "Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to",
"name": "define_args",
"signature": "def define_args(self, arg_parser)"
},
{
"docstring": "Runs the command :param args: Arguments from argparse.Namespace",
"name": "run",
... | 2 | null | Implement the Python class `AdjustVertexOrder` described below.
Class description:
Command to adjust vertex order of all polygons in a .hyper file
Method signatures and docstrings:
- def define_args(self, arg_parser): Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to
- ... | Implement the Python class `AdjustVertexOrder` described below.
Class description:
Command to adjust vertex order of all polygons in a .hyper file
Method signatures and docstrings:
- def define_args(self, arg_parser): Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to
- ... | 382e66481ec8339407cf9cfa5d41fcdcf3f6a0fb | <|skeleton|>
class AdjustVertexOrder:
"""Command to adjust vertex order of all polygons in a .hyper file"""
def define_args(self, arg_parser):
"""Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to"""
<|body_0|>
def run(self, args):
"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdjustVertexOrder:
"""Command to adjust vertex order of all polygons in a .hyper file"""
def define_args(self, arg_parser):
"""Adds arguments for the command :param arg_parser: The argparse.ArgumentParser to add arguments to"""
arg_parser.add_argument('-i', '--input_file', type=Path, meta... | the_stack_v2_python_sparse | Community-Supported/adjust-vertex-order/adjust_vertex_order.py | turner-anderson/hyper-api-samples | train | 0 |
e6d205a790c772bd68e34c76e9d4efd28dc9666e | [
"input_file = self.open_input_file(args)\nrequired_total_fuel = 0\nfor line in input_file:\n mass_of_module = int(line.rstrip())\n required_total_fuel += _calculate_fuel(mass_of_module)\nprint('What is the sum of the fuel requirements for all of the modules on your spacecraft?\\n{}'.format(required_total_fuel... | <|body_start_0|>
input_file = self.open_input_file(args)
required_total_fuel = 0
for line in input_file:
mass_of_module = int(line.rstrip())
required_total_fuel += _calculate_fuel(mass_of_module)
print('What is the sum of the fuel requirements for all of the modul... | The class to solve this level (both parts) | Level01 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Level01:
"""The class to solve this level (both parts)"""
def solve_part1(self, args):
"""Override to solve part 1 of the puzzle"""
<|body_0|>
def solve_part2(self, args):
"""Override to solve part 2 of the puzzle"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_75kplus_train_006560 | 1,926 | no_license | [
{
"docstring": "Override to solve part 1 of the puzzle",
"name": "solve_part1",
"signature": "def solve_part1(self, args)"
},
{
"docstring": "Override to solve part 2 of the puzzle",
"name": "solve_part2",
"signature": "def solve_part2(self, args)"
}
] | 2 | stack_v2_sparse_classes_30k_train_025282 | Implement the Python class `Level01` described below.
Class description:
The class to solve this level (both parts)
Method signatures and docstrings:
- def solve_part1(self, args): Override to solve part 1 of the puzzle
- def solve_part2(self, args): Override to solve part 2 of the puzzle | Implement the Python class `Level01` described below.
Class description:
The class to solve this level (both parts)
Method signatures and docstrings:
- def solve_part1(self, args): Override to solve part 1 of the puzzle
- def solve_part2(self, args): Override to solve part 2 of the puzzle
<|skeleton|>
class Level01:... | 56bf8831fe936271e415c68ac8d2cf6ab9adfe11 | <|skeleton|>
class Level01:
"""The class to solve this level (both parts)"""
def solve_part1(self, args):
"""Override to solve part 1 of the puzzle"""
<|body_0|>
def solve_part2(self, args):
"""Override to solve part 2 of the puzzle"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Level01:
"""The class to solve this level (both parts)"""
def solve_part1(self, args):
"""Override to solve part 1 of the puzzle"""
input_file = self.open_input_file(args)
required_total_fuel = 0
for line in input_file:
mass_of_module = int(line.rstrip())
... | the_stack_v2_python_sparse | 2019/python/level01.py | istvans/AdventOfCode | train | 0 |
7c9b922bed58fed469de68f1637c1fe99df4a27e | [
"subject = self.cleaned_data['subject']\nif not subject:\n raise forms.ValidationError('This is required')\nreturn subject",
"text = self.cleaned_data['text']\nif not text:\n raise forms.ValidationError('This is required')\nreturn text"
] | <|body_start_0|>
subject = self.cleaned_data['subject']
if not subject:
raise forms.ValidationError('This is required')
return subject
<|end_body_0|>
<|body_start_1|>
text = self.cleaned_data['text']
if not text:
raise forms.ValidationError('This is requi... | invoice form for send email | InvoiceEmailForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvoiceEmailForm:
"""invoice form for send email"""
def clean_subject(self):
"""subject validation"""
<|body_0|>
def clean_text(self):
"""text validation"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
subject = self.cleaned_data['subject']
... | stack_v2_sparse_classes_75kplus_train_006561 | 3,109 | no_license | [
{
"docstring": "subject validation",
"name": "clean_subject",
"signature": "def clean_subject(self)"
},
{
"docstring": "text validation",
"name": "clean_text",
"signature": "def clean_text(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_039786 | Implement the Python class `InvoiceEmailForm` described below.
Class description:
invoice form for send email
Method signatures and docstrings:
- def clean_subject(self): subject validation
- def clean_text(self): text validation | Implement the Python class `InvoiceEmailForm` described below.
Class description:
invoice form for send email
Method signatures and docstrings:
- def clean_subject(self): subject validation
- def clean_text(self): text validation
<|skeleton|>
class InvoiceEmailForm:
"""invoice form for send email"""
def cle... | 17615ea9bfb1edebe41d60dbf2e977f0018d5339 | <|skeleton|>
class InvoiceEmailForm:
"""invoice form for send email"""
def clean_subject(self):
"""subject validation"""
<|body_0|>
def clean_text(self):
"""text validation"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InvoiceEmailForm:
"""invoice form for send email"""
def clean_subject(self):
"""subject validation"""
subject = self.cleaned_data['subject']
if not subject:
raise forms.ValidationError('This is required')
return subject
def clean_text(self):
"""tex... | the_stack_v2_python_sparse | invoices/forms.py | Swiftkind/invoice | train | 0 |
ff32188867c6b3d36233a6712447587976c47349 | [
"payload = {'email': user.email}\npayload.update(kwargs)\ntoken = jwt.encode(payload, cls.secret, algorithm=algorithm_used)\nreturn token",
"try:\n return jwt.decode(token, cls.secret, algorithms=algorithms_used, **kwargs)\nexcept:\n return None"
] | <|body_start_0|>
payload = {'email': user.email}
payload.update(kwargs)
token = jwt.encode(payload, cls.secret, algorithm=algorithm_used)
return token
<|end_body_0|>
<|body_start_1|>
try:
return jwt.decode(token, cls.secret, algorithms=algorithms_used, **kwargs)
... | Class for Generating JWT token and decode them. | TokenGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TokenGenerator:
"""Class for Generating JWT token and decode them."""
def generate_token(cls, user, algorithm_used='HS256', **kwargs):
"""Method for generating token."""
<|body_0|>
def decode_token(cls, token, algorithms_used=['HS256'], **kwargs):
"""Method for d... | stack_v2_sparse_classes_75kplus_train_006562 | 2,861 | no_license | [
{
"docstring": "Method for generating token.",
"name": "generate_token",
"signature": "def generate_token(cls, user, algorithm_used='HS256', **kwargs)"
},
{
"docstring": "Method for decoding token.",
"name": "decode_token",
"signature": "def decode_token(cls, token, algorithms_used=['HS2... | 2 | null | Implement the Python class `TokenGenerator` described below.
Class description:
Class for Generating JWT token and decode them.
Method signatures and docstrings:
- def generate_token(cls, user, algorithm_used='HS256', **kwargs): Method for generating token.
- def decode_token(cls, token, algorithms_used=['HS256'], **... | Implement the Python class `TokenGenerator` described below.
Class description:
Class for Generating JWT token and decode them.
Method signatures and docstrings:
- def generate_token(cls, user, algorithm_used='HS256', **kwargs): Method for generating token.
- def decode_token(cls, token, algorithms_used=['HS256'], **... | 6bcf64c03f0e47f2c11e5dbbf36c87a0ba8a36e6 | <|skeleton|>
class TokenGenerator:
"""Class for Generating JWT token and decode them."""
def generate_token(cls, user, algorithm_used='HS256', **kwargs):
"""Method for generating token."""
<|body_0|>
def decode_token(cls, token, algorithms_used=['HS256'], **kwargs):
"""Method for d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TokenGenerator:
"""Class for Generating JWT token and decode them."""
def generate_token(cls, user, algorithm_used='HS256', **kwargs):
"""Method for generating token."""
payload = {'email': user.email}
payload.update(kwargs)
token = jwt.encode(payload, cls.secret, algorith... | the_stack_v2_python_sparse | backend/backend/apps/accounts/utils.py | faizalsha/symptom-checker | train | 0 |
312f87f2fde251181b6f6e7c0f3fb42655c6f018 | [
"def backtrack(i, tmp_num, tmp):\n if tmp_num == target:\n tmp = sorted(tmp)\n if tmp not in res:\n res.append(tmp)\n return\n return\n if i == n or tmp_num > target:\n return\n backtrack(i + 1, tmp_num + candidates[i], tmp + [candidates[i]])\n backtrack... | <|body_start_0|>
def backtrack(i, tmp_num, tmp):
if tmp_num == target:
tmp = sorted(tmp)
if tmp not in res:
res.append(tmp)
return
return
if i == n or tmp_num > target:
return
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def combinationSum21(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def combinationSum2(self, candidates, target):
""":param candidates: :param target: :return:"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_006563 | 1,580 | no_license | [
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]]",
"name": "combinationSum21",
"signature": "def combinationSum21(self, candidates, target)"
},
{
"docstring": ":param candidates: :param target: :return:",
"name": "combinationSum2",
"signature": "def c... | 2 | stack_v2_sparse_classes_30k_train_013270 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum21(self, candidates, target): :type candidates: List[int] :type target: int :rtype: List[List[int]]
- def combinationSum2(self, candidates, target): :param cand... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def combinationSum21(self, candidates, target): :type candidates: List[int] :type target: int :rtype: List[List[int]]
- def combinationSum2(self, candidates, target): :param cand... | a91a758ab52d8615366a46b168181c04a92a793b | <|skeleton|>
class Solution:
def combinationSum21(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
<|body_0|>
def combinationSum2(self, candidates, target):
""":param candidates: :param target: :return:"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def combinationSum21(self, candidates, target):
""":type candidates: List[int] :type target: int :rtype: List[List[int]]"""
def backtrack(i, tmp_num, tmp):
if tmp_num == target:
tmp = sorted(tmp)
if tmp not in res:
res.a... | the_stack_v2_python_sparse | 算法/40. 组合总和 II.py | Confucius-hui/LeetCode | train | 0 | |
5cfd1037c434e94fb43c99cbe696634bbc5ed8c6 | [
"self.method = method\nself.M = M\nself.snr = snr\nself.dt = dt\nself.z = z\nself.mirror = mirror\nself.p = p\nself.like = 0.0\nA = fstat.snr_f_to_a(self.z, event.get_fsig(mirror))\nself.D, self.cosi, _, _ = fstat.a_to_params(A)\nif method is not 'time' and method is not 'marg':\n self.approx_like(event, Dmax)\n... | <|body_start_0|>
self.method = method
self.M = M
self.snr = snr
self.dt = dt
self.z = z
self.mirror = mirror
self.p = p
self.like = 0.0
A = fstat.snr_f_to_a(self.z, event.get_fsig(mirror))
self.D, self.cosi, _, _ = fstat.a_to_params(A)
... | class to hold the details of a localization method | localization | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class localization:
"""class to hold the details of a localization method"""
def __init__(self, method, M, snr, dt, z, event, mirror=False, p=0.9, Dmax=1000, area=0):
"""Initialization :param method: how we do localization, one of "time", "coh", "left, "right", "marg" :param M: localizatio... | stack_v2_sparse_classes_75kplus_train_006564 | 29,171 | no_license | [
{
"docstring": "Initialization :param method: how we do localization, one of \"time\", \"coh\", \"left, \"right\", \"marg\" :param M: localization matrix :param snr: snr of event :param dt: time offset :param z: complex snr :param event: details of event :param mirror: are we looking in the mirror location :par... | 4 | stack_v2_sparse_classes_30k_train_027044 | Implement the Python class `localization` described below.
Class description:
class to hold the details of a localization method
Method signatures and docstrings:
- def __init__(self, method, M, snr, dt, z, event, mirror=False, p=0.9, Dmax=1000, area=0): Initialization :param method: how we do localization, one of "t... | Implement the Python class `localization` described below.
Class description:
class to hold the details of a localization method
Method signatures and docstrings:
- def __init__(self, method, M, snr, dt, z, event, mirror=False, p=0.9, Dmax=1000, area=0): Initialization :param method: how we do localization, one of "t... | 22342a3bc81e4a12ff506c76f24167d5d29b26d1 | <|skeleton|>
class localization:
"""class to hold the details of a localization method"""
def __init__(self, method, M, snr, dt, z, event, mirror=False, p=0.9, Dmax=1000, area=0):
"""Initialization :param method: how we do localization, one of "time", "coh", "left, "right", "marg" :param M: localizatio... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class localization:
"""class to hold the details of a localization method"""
def __init__(self, method, M, snr, dt, z, event, mirror=False, p=0.9, Dmax=1000, area=0):
"""Initialization :param method: how we do localization, one of "time", "coh", "left, "right", "marg" :param M: localization matrix :par... | the_stack_v2_python_sparse | simple_pe/localize.py | grferna/GW150914_phase | train | 0 |
d2478bf7780aa015a8d60e209b9e6684fa6a9346 | [
"self.glacier_retrieval_type = glacier_retrieval_type\nself.restore_objects = restore_objects\nself.search_job_uid = search_job_uid\nself.task_name = task_name\nself.vault_id = vault_id",
"if dictionary is None:\n return None\nglacier_retrieval_type = dictionary.get('glacierRetrievalType')\nrestore_objects = N... | <|body_start_0|>
self.glacier_retrieval_type = glacier_retrieval_type
self.restore_objects = restore_objects
self.search_job_uid = search_job_uid
self.task_name = task_name
self.vault_id = vault_id
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return... | Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current Cluster. Attributes: glacier_retrieval_type (GlacierRetrievalTypeEnum): Specifies the way data needs to b... | CreateRemoteVaultRestoreTaskParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateRemoteVaultRestoreTaskParameters:
"""Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current Cluster. Attributes: glacier_retrieval_... | stack_v2_sparse_classes_75kplus_train_006565 | 4,811 | permissive | [
{
"docstring": "Constructor for the CreateRemoteVaultRestoreTaskParameters class",
"name": "__init__",
"signature": "def __init__(self, glacier_retrieval_type=None, restore_objects=None, search_job_uid=None, task_name=None, vault_id=None)"
},
{
"docstring": "Creates an instance of this model fro... | 2 | stack_v2_sparse_classes_30k_train_004226 | Implement the Python class `CreateRemoteVaultRestoreTaskParameters` described below.
Class description:
Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current ... | Implement the Python class `CreateRemoteVaultRestoreTaskParameters` described below.
Class description:
Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CreateRemoteVaultRestoreTaskParameters:
"""Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current Cluster. Attributes: glacier_retrieval_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CreateRemoteVaultRestoreTaskParameters:
"""Implementation of the 'CreateRemoteVaultRestoreTaskParameters' model. Specifies settings required to create a task that restores the index and/or the Snapshots of a Protection Job from a remote Vault to the current Cluster. Attributes: glacier_retrieval_type (Glacier... | the_stack_v2_python_sparse | cohesity_management_sdk/models/create_remote_vault_restore_task_parameters.py | cohesity/management-sdk-python | train | 24 |
997cb47e5216f9d14f0ebc265fc1730636cdf7d2 | [
"paths = files_conf.get('paths')\nfields = {f.name: f for f in dataclasses.fields(cls)}\ninclude = files_conf.get('include', fields['include'].default_factory())\nexclude = files_conf.get('exclude', fields['exclude'].default_factory())\nif not paths:\n raise ValueError('You must define the paths when using scrip... | <|body_start_0|>
paths = files_conf.get('paths')
fields = {f.name: f for f in dataclasses.fields(cls)}
include = files_conf.get('include', fields['include'].default_factory())
exclude = files_conf.get('exclude', fields['exclude'].default_factory())
if not paths:
raise... | Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* of interest and further refining the list by *include* and *exclude* which act as ... | FilesCollection | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilesCollection:
"""Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* of interest and further refining the li... | stack_v2_sparse_classes_75kplus_train_006566 | 3,452 | permissive | [
{
"docstring": "Load from config dict",
"name": "from_config",
"signature": "def from_config(cls: Type['FilesCollection'], files_conf: YamlConf) -> 'FilesCollection'"
},
{
"docstring": "Return a full whitelist for use with `fs.filtered_walk()`",
"name": "whitelist",
"signature": "def whi... | 3 | stack_v2_sparse_classes_30k_train_046534 | Implement the Python class `FilesCollection` described below.
Class description:
Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* ... | Implement the Python class `FilesCollection` described below.
Class description:
Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* ... | 3b4242ace18e73eb0298b4a7a677425f5eac6a68 | <|skeleton|>
class FilesCollection:
"""Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* of interest and further refining the li... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FilesCollection:
"""Configure files passed to the script. This section allows you to inject a set of files into the script as the ``{{ files }}`` expression. This configuration allows you to flexibly define what files are collected by specifying the *paths* of interest and further refining the list by *includ... | the_stack_v2_python_sparse | src/peltak/core/types.py | novopl/peltak | train | 7 |
14f4f745de1a0f5b90ab3b87677839c01b1150bf | [
"Instruction.__init__(self, input)\nself.device = input[self.start]\nself.device_name = input[self.start + 1]\nself.device_info = input[self.start + 1:]",
"if self.device == 'host':\n new_device = Host(self.device_info)\nelif self.device == 'hub':\n new_device = Hub(self.device_info)\nelif self.device == 's... | <|body_start_0|>
Instruction.__init__(self, input)
self.device = input[self.start]
self.device_name = input[self.start + 1]
self.device_info = input[self.start + 1:]
<|end_body_0|>
<|body_start_1|>
if self.device == 'host':
new_device = Host(self.device_info)
... | Create | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Create:
def __init__(self, input):
"""Init create instruction information"""
<|body_0|>
def execute(self, net_stat: Status):
"""Execute create Instruction"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Instruction.__init__(self, input)
self... | stack_v2_sparse_classes_75kplus_train_006567 | 1,193 | no_license | [
{
"docstring": "Init create instruction information",
"name": "__init__",
"signature": "def __init__(self, input)"
},
{
"docstring": "Execute create Instruction",
"name": "execute",
"signature": "def execute(self, net_stat: Status)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001111 | Implement the Python class `Create` described below.
Class description:
Implement the Create class.
Method signatures and docstrings:
- def __init__(self, input): Init create instruction information
- def execute(self, net_stat: Status): Execute create Instruction | Implement the Python class `Create` described below.
Class description:
Implement the Create class.
Method signatures and docstrings:
- def __init__(self, input): Init create instruction information
- def execute(self, net_stat: Status): Execute create Instruction
<|skeleton|>
class Create:
def __init__(self, i... | b15d9e8c511c9a78c469e30f597e08504d2969c7 | <|skeleton|>
class Create:
def __init__(self, input):
"""Init create instruction information"""
<|body_0|>
def execute(self, net_stat: Status):
"""Execute create Instruction"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Create:
def __init__(self, input):
"""Init create instruction information"""
Instruction.__init__(self, input)
self.device = input[self.start]
self.device_name = input[self.start + 1]
self.device_info = input[self.start + 1:]
def execute(self, net_stat: Status):
... | the_stack_v2_python_sparse | instructions/create.py | University-Projects-UH/physical-layer | train | 0 | |
56eeab54fb6d4321ce648423f995a933bbec8eda | [
"self.city = city\nself.state = state\nself.country = country\nself.postal_code = postal_code\nself.address_line_1 = address_line_1\nself.address_line_2 = address_line_2\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\ncity = dictionary.get('city')\nstate = dictionar... | <|body_start_0|>
self.city = city
self.state = state
self.country = country
self.postal_code = postal_code
self.address_line_1 = address_line_1
self.address_line_2 = address_line_2
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>... | Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headquarters country (string): The country of the institution’s headquarters postal_code (... | InstitutionAddress | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstitutionAddress:
"""Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headquarters country (string): The country o... | stack_v2_sparse_classes_75kplus_train_006568 | 3,105 | permissive | [
{
"docstring": "Constructor for the InstitutionAddress class",
"name": "__init__",
"signature": "def __init__(self, city=None, state=None, country=None, postal_code=None, address_line_1=None, address_line_2=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model fro... | 2 | stack_v2_sparse_classes_30k_train_013978 | Implement the Python class `InstitutionAddress` described below.
Class description:
Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headq... | Implement the Python class `InstitutionAddress` described below.
Class description:
Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headq... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class InstitutionAddress:
"""Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headquarters country (string): The country o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InstitutionAddress:
"""Implementation of the 'Institution Address' model. The address for the financial institution Attributes: city (string): The city of the institution’s headquarters state (string): Two-letter code for the state of the institution’s headquarters country (string): The country of the institu... | the_stack_v2_python_sparse | finicityapi/models/institution_address.py | monarchmoney/finicity-python | train | 0 |
f5aeacbf3509ee7c4a8ec0445f76c7bd00ac0551 | [
"roman_int = {'I': 1, 'IV': 4, 'V': 5, 'IX': 9, 'X': 10, 'XL': 40, 'L': 50, 'XC': 90, 'C': 100, 'CD': 400, 'D': 500, 'CM': 900, 'M': 1000}\nresult = 0\ni = 0\nn = len(string)\nwhile i < n:\n if i < n - 1 and roman_int[string[i]] < roman_int[string[i + 1]]:\n result += roman_int[string[i:i + 2]]\n i... | <|body_start_0|>
roman_int = {'I': 1, 'IV': 4, 'V': 5, 'IX': 9, 'X': 10, 'XL': 40, 'L': 50, 'XC': 90, 'C': 100, 'CD': 400, 'D': 500, 'CM': 900, 'M': 1000}
result = 0
i = 0
n = len(string)
while i < n:
if i < n - 1 and roman_int[string[i]] < roman_int[string[i + 1]]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to ... | stack_v2_sparse_classes_75kplus_train_006569 | 2,904 | no_license | [
{
"docstring": "Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to take 2 characters to evaluate number. 3) Otherwise, w... | 2 | stack_v2_sparse_classes_30k_train_042082 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def roman_to_int(self, string): Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def roman_to_int(self, string): Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of ... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to take 2 charact... | the_stack_v2_python_sparse | Strings/roman_numerals/roman_to_integer.py | vladn90/Algorithms | train | 0 | |
e40652e01f68372d46216cd20139c4a9b2b49007 | [
"num_of_products_optimized = 0\nnum_of_products_excluded = 0\nself._shopping_exclusion_config = config_parser.get_config_contents(_SHOPPING_EXCLUSION_OPTIMIZER_CONFIG_OVERRIDE_KEY, _SHOPPING_EXCLUSION_OPTIMIZER_CONFIG_FILE_NAME.format(language))\nself.shopping_removal_patterns_exact_match = frozenset(self._shopping... | <|body_start_0|>
num_of_products_optimized = 0
num_of_products_excluded = 0
self._shopping_exclusion_config = config_parser.get_config_contents(_SHOPPING_EXCLUSION_OPTIMIZER_CONFIG_OVERRIDE_KEY, _SHOPPING_EXCLUSION_OPTIMIZER_CONFIG_FILE_NAME.format(language))
self.shopping_removal_patter... | An optimizer that detects and excludes products from Shopping Ads. | ShoppingExclusionOptimizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShoppingExclusionOptimizer:
"""An optimizer that detects and excludes products from Shopping Ads."""
def _optimize(self, product_batch: Dict[str, Any], language: str, country: str, currency: str) -> optimization_result_counts.OptimizationResultCounts:
"""Runs the optimization. Args: ... | stack_v2_sparse_classes_75kplus_train_006570 | 6,253 | permissive | [
{
"docstring": "Runs the optimization. Args: product_batch: A batch of product data. language: The language to use for this optimizer. country: The country to use for this optimizer. currency: The currency to use for this optimizer. Returns: The number of products affected by this optimization.",
"name": "_... | 2 | null | Implement the Python class `ShoppingExclusionOptimizer` described below.
Class description:
An optimizer that detects and excludes products from Shopping Ads.
Method signatures and docstrings:
- def _optimize(self, product_batch: Dict[str, Any], language: str, country: str, currency: str) -> optimization_result_count... | Implement the Python class `ShoppingExclusionOptimizer` described below.
Class description:
An optimizer that detects and excludes products from Shopping Ads.
Method signatures and docstrings:
- def _optimize(self, product_batch: Dict[str, Any], language: str, country: str, currency: str) -> optimization_result_count... | 58588ce54f8ea065fdc7501398b1b2e10f8adc41 | <|skeleton|>
class ShoppingExclusionOptimizer:
"""An optimizer that detects and excludes products from Shopping Ads."""
def _optimize(self, product_batch: Dict[str, Any], language: str, country: str, currency: str) -> optimization_result_counts.OptimizationResultCounts:
"""Runs the optimization. Args: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ShoppingExclusionOptimizer:
"""An optimizer that detects and excludes products from Shopping Ads."""
def _optimize(self, product_batch: Dict[str, Any], language: str, country: str, currency: str) -> optimization_result_counts.OptimizationResultCounts:
"""Runs the optimization. Args: product_batch... | the_stack_v2_python_sparse | shoptimizer_api/optimizers_builtin/shopping_exclusion_optimizer.py | google/shoptimizer | train | 43 |
de9d082a826973ed1716e46a5ca31eecf880bb8d | [
"assert os.path.exists(path)\ndata = np.load(path, allow_pickle=True).tolist()\nreturn data",
"assert isinstance(info1, dict) and isinstance(info2, dict)\ncheck_data(info1, info2)\nself.diff_dict = compute_diff(info1, info2)",
"logger = init_logger(path)\npassed = check_print_diff(self.diff_dict, diff_method=di... | <|body_start_0|>
assert os.path.exists(path)
data = np.load(path, allow_pickle=True).tolist()
return data
<|end_body_0|>
<|body_start_1|>
assert isinstance(info1, dict) and isinstance(info2, dict)
check_data(info1, info2)
self.diff_dict = compute_diff(info1, info2)
<|end... | ReprodDiffHelper | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReprodDiffHelper:
def load_info(self, path: str):
"""加载字典文件 :param path: :return:"""
<|body_0|>
def compare_info(self, info1: dict, info2: dict):
"""对比diff :param info1: :param info2: :return:"""
<|body_1|>
def report(self, diff_method='mean', diff_thres... | stack_v2_sparse_classes_75kplus_train_006571 | 1,970 | permissive | [
{
"docstring": "加载字典文件 :param path: :return:",
"name": "load_info",
"signature": "def load_info(self, path: str)"
},
{
"docstring": "对比diff :param info1: :param info2: :return:",
"name": "compare_info",
"signature": "def compare_info(self, info1: dict, info2: dict)"
},
{
"docstri... | 3 | null | Implement the Python class `ReprodDiffHelper` described below.
Class description:
Implement the ReprodDiffHelper class.
Method signatures and docstrings:
- def load_info(self, path: str): 加载字典文件 :param path: :return:
- def compare_info(self, info1: dict, info2: dict): 对比diff :param info1: :param info2: :return:
- def... | Implement the Python class `ReprodDiffHelper` described below.
Class description:
Implement the ReprodDiffHelper class.
Method signatures and docstrings:
- def load_info(self, path: str): 加载字典文件 :param path: :return:
- def compare_info(self, info1: dict, info2: dict): 对比diff :param info1: :param info2: :return:
- def... | 8042c21b690ffc0162095e749a41b94dd38732da | <|skeleton|>
class ReprodDiffHelper:
def load_info(self, path: str):
"""加载字典文件 :param path: :return:"""
<|body_0|>
def compare_info(self, info1: dict, info2: dict):
"""对比diff :param info1: :param info2: :return:"""
<|body_1|>
def report(self, diff_method='mean', diff_thres... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReprodDiffHelper:
def load_info(self, path: str):
"""加载字典文件 :param path: :return:"""
assert os.path.exists(path)
data = np.load(path, allow_pickle=True).tolist()
return data
def compare_info(self, info1: dict, info2: dict):
"""对比diff :param info1: :param info2: :re... | the_stack_v2_python_sparse | tutorials/reprod_log/reprod_log/ReprodDiffHelper.py | PaddlePaddle/models | train | 7,633 | |
fd71f9c39517076c0db12ecd825d1cc34e751ca1 | [
"cli = self.client\nresp = cli.get('/beeswax/report_gen')\nassert_true(resp.status_code, 200)\nresp = cli.post('/beeswax/report_gen', {'columns-next_form_id': '1', 'columns-0-_exists': 'True', 'columns-0-col': '*', 'columns-0-display': 'on', 'columns-0-source': 'table', 'columns-0-table': 'test', 'union.conds-next_... | <|body_start_0|>
cli = self.client
resp = cli.get('/beeswax/report_gen')
assert_true(resp.status_code, 200)
resp = cli.post('/beeswax/report_gen', {'columns-next_form_id': '1', 'columns-0-_exists': 'True', 'columns-0-col': '*', 'columns-0-display': 'on', 'columns-0-source': 'table', 'col... | Tests for report generator that require a running Hadoop | TestReportGenWithHadoop | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestReportGenWithHadoop:
"""Tests for report generator that require a running Hadoop"""
def test_report_gen_view(self):
"""Test report gen view logic and query generation. It requires Hive because report gen automatically gathers all the table names."""
<|body_0|>
def te... | stack_v2_sparse_classes_75kplus_train_006572 | 8,139 | permissive | [
{
"docstring": "Test report gen view logic and query generation. It requires Hive because report gen automatically gathers all the table names.",
"name": "test_report_gen_view",
"signature": "def test_report_gen_view(self)"
},
{
"docstring": "Test report design view and interaction",
"name":... | 2 | null | Implement the Python class `TestReportGenWithHadoop` described below.
Class description:
Tests for report generator that require a running Hadoop
Method signatures and docstrings:
- def test_report_gen_view(self): Test report gen view logic and query generation. It requires Hive because report gen automatically gathe... | Implement the Python class `TestReportGenWithHadoop` described below.
Class description:
Tests for report generator that require a running Hadoop
Method signatures and docstrings:
- def test_report_gen_view(self): Test report gen view logic and query generation. It requires Hive because report gen automatically gathe... | 82f2de44789ff5a981ed725175bae7944832d1e9 | <|skeleton|>
class TestReportGenWithHadoop:
"""Tests for report generator that require a running Hadoop"""
def test_report_gen_view(self):
"""Test report gen view logic and query generation. It requires Hive because report gen automatically gathers all the table names."""
<|body_0|>
def te... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestReportGenWithHadoop:
"""Tests for report generator that require a running Hadoop"""
def test_report_gen_view(self):
"""Test report gen view logic and query generation. It requires Hive because report gen automatically gathers all the table names."""
cli = self.client
resp = cl... | the_stack_v2_python_sparse | apps/beeswax/src/beeswax/report/tests.py | civascu/hue | train | 0 |
d8efa965b2c94d7618bd9fafe511a61f0614a385 | [
"if not filepath:\n raise Exception('ERROR: Invalid dataset path.')\nself.type = type\nself.filepath = filepath\nself.up_sites = up_sites\nself.down_sites = down_sites\nself.donor_site = []\nself.acceptor_site = []\nself.neg_donor_site = []\nself.neg_acceptor_site = []\nif self.type not in {'train', 'test'}:\n ... | <|body_start_0|>
if not filepath:
raise Exception('ERROR: Invalid dataset path.')
self.type = type
self.filepath = filepath
self.up_sites = up_sites
self.down_sites = down_sites
self.donor_site = []
self.acceptor_site = []
self.neg_donor_site =... | Sequence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one seque... | stack_v2_sparse_classes_75kplus_train_006573 | 5,098 | no_license | [
{
"docstring": "All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one sequence each. type: str (one of \"train\", \"test\") Set the data type. Way of reading would be different. up_sites: int, d... | 4 | stack_v2_sparse_classes_30k_train_037771 | Implement the Python class `Sequence` described below.
Class description:
Implement the Sequence class.
Method signatures and docstrings:
- def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None: All kinds of splice site sequences for training. Parameters ---------- filepath:... | Implement the Python class `Sequence` described below.
Class description:
Implement the Sequence class.
Method signatures and docstrings:
- def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None: All kinds of splice site sequences for training. Parameters ---------- filepath:... | 3302ff7222d191f632695f0b9465ec2555f1b0af | <|skeleton|>
class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one seque... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one sequence each. type... | the_stack_v2_python_sparse | Utils/extract.py | Newiz430/SplicePredictor | train | 1 | |
d7d224999ff7b83f88102ec8180b88ff057bb825 | [
"start_row, start_column, number_of_rows, number_of_columns = bounds\nself.array = array\nself.bounds = bounds\nself.start_row = start_row\nself.start_column = start_column\nself.number_of_rows = number_of_rows\nself.number_of_columns = number_of_columns",
"r, c = location\nif not (0 <= r and r < self.number_of_r... | <|body_start_0|>
start_row, start_column, number_of_rows, number_of_columns = bounds
self.array = array
self.bounds = bounds
self.start_row = start_row
self.start_column = start_column
self.number_of_rows = number_of_rows
self.number_of_columns = number_of_columns... | A class representing an instance of a peak-finding problem. | PeakProblem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeakProblem:
"""A class representing an instance of a peak-finding problem."""
def __init__(self, array, bounds):
"""A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating which rows to include. RUNTIME: O(1)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_006574 | 2,953 | permissive | [
{
"docstring": "A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating which rows to include. RUNTIME: O(1)",
"name": "__init__",
"signature": "def __init__(self, array, bounds)"
},
{
"docstring": "@brief Returns value of the array at the given ... | 2 | stack_v2_sparse_classes_30k_train_028026 | Implement the Python class `PeakProblem` described below.
Class description:
A class representing an instance of a peak-finding problem.
Method signatures and docstrings:
- def __init__(self, array, bounds): A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating whic... | Implement the Python class `PeakProblem` described below.
Class description:
A class representing an instance of a peak-finding problem.
Method signatures and docstrings:
- def __init__(self, array, bounds): A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating whic... | ad067fd4e605c230ea87bdc36cc38341e681a1e0 | <|skeleton|>
class PeakProblem:
"""A class representing an instance of a peak-finding problem."""
def __init__(self, array, bounds):
"""A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating which rows to include. RUNTIME: O(1)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PeakProblem:
"""A class representing an instance of a peak-finding problem."""
def __init__(self, array, bounds):
"""A method for initializing an instance of the PeakProblem class. Takes an array and an argument indicating which rows to include. RUNTIME: O(1)"""
start_row, start_column, n... | the_stack_v2_python_sparse | Voltron/Voltron/Algorithms/PeakFinding/PeakProblem.py | ernestyalumni/HrdwCCppCUDA | train | 3 |
4ec37c35833213991d066b04dbe89192f9678f6d | [
"self.year = kwargs.pop('year')\nself.proyectos = []\nself.vol_total_inv_prev_proy = {}\nself.ayudas_prv_proy = {}\nself.financiacion_prv_proy = {}\nself.vpi_retribuible_prv_proy = {}\nself.generated_proy = []\nself.ids = {}\nsuper(PRO, self).__init__(**kwargs)",
"ids_resums = get_resum_any_id(self.connection, se... | <|body_start_0|>
self.year = kwargs.pop('year')
self.proyectos = []
self.vol_total_inv_prev_proy = {}
self.ayudas_prv_proy = {}
self.financiacion_prv_proy = {}
self.vpi_retribuible_prv_proy = {}
self.generated_proy = []
self.ids = {}
super(PRO, sel... | Class to generate proyectos of 4667 | PRO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PRO:
"""Class to generate proyectos of 4667"""
def __init__(self, **kwargs):
"""Class constructor :param kwargs: :type kwargs: dict"""
<|body_0|>
def get_sequence(self):
"""Generates the sequence of ids to make the report :return: List of ids :rtype: list"""
... | stack_v2_sparse_classes_75kplus_train_006575 | 3,866 | no_license | [
{
"docstring": "Class constructor :param kwargs: :type kwargs: dict",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Generates the sequence of ids to make the report :return: List of ids :rtype: list",
"name": "get_sequence",
"signature": "def get_sequ... | 3 | null | Implement the Python class `PRO` described below.
Class description:
Class to generate proyectos of 4667
Method signatures and docstrings:
- def __init__(self, **kwargs): Class constructor :param kwargs: :type kwargs: dict
- def get_sequence(self): Generates the sequence of ids to make the report :return: List of ids... | Implement the Python class `PRO` described below.
Class description:
Class to generate proyectos of 4667
Method signatures and docstrings:
- def __init__(self, **kwargs): Class constructor :param kwargs: :type kwargs: dict
- def get_sequence(self): Generates the sequence of ids to make the report :return: List of ids... | c8b1ede6cb55dff4385efbe1b8a0afe8c4a4f48d | <|skeleton|>
class PRO:
"""Class to generate proyectos of 4667"""
def __init__(self, **kwargs):
"""Class constructor :param kwargs: :type kwargs: dict"""
<|body_0|>
def get_sequence(self):
"""Generates the sequence of ids to make the report :return: List of ids :rtype: list"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PRO:
"""Class to generate proyectos of 4667"""
def __init__(self, **kwargs):
"""Class constructor :param kwargs: :type kwargs: dict"""
self.year = kwargs.pop('year')
self.proyectos = []
self.vol_total_inv_prev_proy = {}
self.ayudas_prv_proy = {}
self.financ... | the_stack_v2_python_sparse | libcnmc/res_4667/PRO.py | gisce/libCNMC | train | 7 |
1dd8840793332f3881cebaa3f1442f2d61a55931 | [
"self.TIDAL_CLIENT_VERSION = '1.9.1'\nself.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/'\nself.username = username\nself.token = token\nself.unique_id = str(uuid.uuid4()).replace('-', '')[16:]\nself.auth(password)\npassword = None",
"postParams = {'username': self.username, 'password': password, 'token': self.... | <|body_start_0|>
self.TIDAL_CLIENT_VERSION = '1.9.1'
self.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/'
self.username = username
self.token = token
self.unique_id = str(uuid.uuid4()).replace('-', '')[16:]
self.auth(password)
password = None
<|end_body_0|>
<|bo... | Tidal session object which can be used to communicate with Tidal servers | TidalSession | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TidalSession:
"""Tidal session object which can be used to communicate with Tidal servers"""
def __init__(self, username, password, token='4zx46pyr9o8qZNRw'):
"""Initiate a new session"""
<|body_0|>
def auth(self, password):
"""Attempts to authorize and create a ... | stack_v2_sparse_classes_75kplus_train_006576 | 8,327 | permissive | [
{
"docstring": "Initiate a new session",
"name": "__init__",
"signature": "def __init__(self, username, password, token='4zx46pyr9o8qZNRw')"
},
{
"docstring": "Attempts to authorize and create a new valid session",
"name": "auth",
"signature": "def auth(self, password)"
},
{
"doc... | 4 | stack_v2_sparse_classes_30k_val_000360 | Implement the Python class `TidalSession` described below.
Class description:
Tidal session object which can be used to communicate with Tidal servers
Method signatures and docstrings:
- def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): Initiate a new session
- def auth(self, password): Attempts to au... | Implement the Python class `TidalSession` described below.
Class description:
Tidal session object which can be used to communicate with Tidal servers
Method signatures and docstrings:
- def __init__(self, username, password, token='4zx46pyr9o8qZNRw'): Initiate a new session
- def auth(self, password): Attempts to au... | 2a7e339b97f173efa319abc5e4ec8fc9172f1505 | <|skeleton|>
class TidalSession:
"""Tidal session object which can be used to communicate with Tidal servers"""
def __init__(self, username, password, token='4zx46pyr9o8qZNRw'):
"""Initiate a new session"""
<|body_0|>
def auth(self, password):
"""Attempts to authorize and create a ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TidalSession:
"""Tidal session object which can be used to communicate with Tidal servers"""
def __init__(self, username, password, token='4zx46pyr9o8qZNRw'):
"""Initiate a new session"""
self.TIDAL_CLIENT_VERSION = '1.9.1'
self.TIDAL_API_BASE = 'https://api.tidalhifi.com/v1/'
... | the_stack_v2_python_sparse | bin/redsea/tidal_api.py | SultanSGillani/dotfiles | train | 7 |
63595358a0cadb80b9cb932b540e470864ea69d2 | [
"self.zero = LinkedList(0)\nself.one = LinkedList(1)\nself.two = LinkedList(2)\nself.three = LinkedList(3)\nself.four = LinkedList(4)\nself.five = LinkedList(5)\nself.six = LinkedList(6)\nself.seven = LinkedList(7)\nself.eight = LinkedList(8)\nself.nine = LinkedList(9)\nself.zero.next = self.one\nself.one.next = se... | <|body_start_0|>
self.zero = LinkedList(0)
self.one = LinkedList(1)
self.two = LinkedList(2)
self.three = LinkedList(3)
self.four = LinkedList(4)
self.five = LinkedList(5)
self.six = LinkedList(6)
self.seven = LinkedList(7)
self.eight = LinkedList(... | Class with unittests for RemoveKthNodeFromEnd.py | test_RemoveKthNodeFromEnd | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_RemoveKthNodeFromEnd:
"""Class with unittests for RemoveKthNodeFromEnd.py"""
def SetUp(self):
"""Set Up input list."""
<|body_0|>
def test_RemoveKthNodeFromEnd(self):
"""Checks if output is correct."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_006577 | 1,607 | no_license | [
{
"docstring": "Set Up input list.",
"name": "SetUp",
"signature": "def SetUp(self)"
},
{
"docstring": "Checks if output is correct.",
"name": "test_RemoveKthNodeFromEnd",
"signature": "def test_RemoveKthNodeFromEnd(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010898 | Implement the Python class `test_RemoveKthNodeFromEnd` described below.
Class description:
Class with unittests for RemoveKthNodeFromEnd.py
Method signatures and docstrings:
- def SetUp(self): Set Up input list.
- def test_RemoveKthNodeFromEnd(self): Checks if output is correct. | Implement the Python class `test_RemoveKthNodeFromEnd` described below.
Class description:
Class with unittests for RemoveKthNodeFromEnd.py
Method signatures and docstrings:
- def SetUp(self): Set Up input list.
- def test_RemoveKthNodeFromEnd(self): Checks if output is correct.
<|skeleton|>
class test_RemoveKthNode... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class test_RemoveKthNodeFromEnd:
"""Class with unittests for RemoveKthNodeFromEnd.py"""
def SetUp(self):
"""Set Up input list."""
<|body_0|>
def test_RemoveKthNodeFromEnd(self):
"""Checks if output is correct."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class test_RemoveKthNodeFromEnd:
"""Class with unittests for RemoveKthNodeFromEnd.py"""
def SetUp(self):
"""Set Up input list."""
self.zero = LinkedList(0)
self.one = LinkedList(1)
self.two = LinkedList(2)
self.three = LinkedList(3)
self.four = LinkedList(4)
... | the_stack_v2_python_sparse | AlgoExpert_algorithms/Medium/RemoveKthNodeFromEnd/test_RemoveKthNodeFromEnd.py | JakubKazimierski/PythonPortfolio | train | 9 |
475b88a9100055bf82b2084ad2cd78b5ac91437a | [
"assert len(input_list) > 0\nassert number_samples <= len(input_list)\nsuper().__init__(self.PROBLEM_NAME)\nself.input_list = input_list\nself.number_samples = number_samples",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\ni = 0\nreservoir = [0] * self.number_samples\nfor i in range(self.number_samp... | <|body_start_0|>
assert len(input_list) > 0
assert number_samples <= len(input_list)
super().__init__(self.PROBLEM_NAME)
self.input_list = input_list
self.number_samples = number_samples
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_N... | Reservoir Sampling | ReservoirSampling | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReservoirSampling:
"""Reservoir Sampling"""
def __init__(self, input_list, number_samples):
"""Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: None"""
<|body_0|>
def solve(self):
... | stack_v2_sparse_classes_75kplus_train_006578 | 2,073 | no_license | [
{
"docstring": "Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_list, number_samples)"
},
{
"docstring": "Solve the problem Note: O(n) (runtime) s... | 2 | stack_v2_sparse_classes_30k_train_048364 | Implement the Python class `ReservoirSampling` described below.
Class description:
Reservoir Sampling
Method signatures and docstrings:
- def __init__(self, input_list, number_samples): Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: ... | Implement the Python class `ReservoirSampling` described below.
Class description:
Reservoir Sampling
Method signatures and docstrings:
- def __init__(self, input_list, number_samples): Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: ... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class ReservoirSampling:
"""Reservoir Sampling"""
def __init__(self, input_list, number_samples):
"""Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: None"""
<|body_0|>
def solve(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ReservoirSampling:
"""Reservoir Sampling"""
def __init__(self, input_list, number_samples):
"""Reservoir Sampling Args: input_list: Contains a list of integers number_samples: Number of elements to sample Returns: None Raises: None"""
assert len(input_list) > 0
assert number_sampl... | the_stack_v2_python_sparse | python/problems/sampling/reservoir.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
eb1858df1d21c2c47a2677f8d4e9c69460929b95 | [
"self.failure_time_series = failure_time_series\nself.num_failed_runs = num_failed_runs\nself.num_in_progress_runs = num_in_progress_runs\nself.num_queued_runs = num_queued_runs\nself.num_successful_runs = num_successful_runs\nself.success_time_series = success_time_series",
"if dictionary is None:\n return No... | <|body_start_0|>
self.failure_time_series = failure_time_series
self.num_failed_runs = num_failed_runs
self.num_in_progress_runs = num_in_progress_runs
self.num_queued_runs = num_queued_runs
self.num_successful_runs = num_successful_runs
self.success_time_series = success... | Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given time frame. num_failed_runs (long|int): Specifies the number of runs that ended in failure... | VaultRunStatsSummary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VaultRunStatsSummary:
"""Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given time frame. num_failed_runs (long|int): Sp... | stack_v2_sparse_classes_75kplus_train_006579 | 3,977 | permissive | [
{
"docstring": "Constructor for the VaultRunStatsSummary class",
"name": "__init__",
"signature": "def __init__(self, failure_time_series=None, num_failed_runs=None, num_in_progress_runs=None, num_queued_runs=None, num_successful_runs=None, success_time_series=None)"
},
{
"docstring": "Creates a... | 2 | null | Implement the Python class `VaultRunStatsSummary` described below.
Class description:
Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given tim... | Implement the Python class `VaultRunStatsSummary` described below.
Class description:
Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given tim... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VaultRunStatsSummary:
"""Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given time frame. num_failed_runs (long|int): Sp... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VaultRunStatsSummary:
"""Implementation of the 'VaultRunStatsSummary' model. Specifies the stats by run type for each vault run. Attributes: failure_time_series (list of VaultRunInfo): Specifies the time series for the failed runs that ended in the given time frame. num_failed_runs (long|int): Specifies the n... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vault_run_stats_summary.py | cohesity/management-sdk-python | train | 24 |
5ee5989f9c06c31628e40f28e0d52ce62308b1ac | [
"url = [op_config['server'], 'apis/ads/publisher', op_config['version'], self.__class__.__name__]\nself.__service = DfpWebService(headers, config, op_config, '/'.join(url), lock, logger)\nsuper(PublisherQueryLanguageService, self).__init__(headers, config, op_config, url, 'adspygoogle.dfp', lock, logger)",
"metho... | <|body_start_0|>
url = [op_config['server'], 'apis/ads/publisher', op_config['version'], self.__class__.__name__]
self.__service = DfpWebService(headers, config, op_config, '/'.join(url), lock, logger)
super(PublisherQueryLanguageService, self).__init__(headers, config, op_config, url, 'adspygoo... | Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system. | PublisherQueryLanguageService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublisherQueryLanguageService:
"""Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system."""
def __init__(self, headers, config, op_config, lock, logger):
"""Inits Publish... | stack_v2_sparse_classes_75kplus_train_006580 | 3,065 | permissive | [
{
"docstring": "Inits PublisherQueryLanguageService. Args: headers: dict Dictionary object with populated authentication credentials. config: dict Dictionary object with populated configuration values. op_config: dict Dictionary object with additional configuration values for this operation. lock: thread.lock T... | 2 | stack_v2_sparse_classes_30k_train_025584 | Implement the Python class `PublisherQueryLanguageService` described below.
Class description:
Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system.
Method signatures and docstrings:
- def __init__(self,... | Implement the Python class `PublisherQueryLanguageService` described below.
Class description:
Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system.
Method signatures and docstrings:
- def __init__(self,... | efa82a8d85cbdc90f030db9d168790c55bd8b12a | <|skeleton|>
class PublisherQueryLanguageService:
"""Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system."""
def __init__(self, headers, config, op_config, lock, logger):
"""Inits Publish... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PublisherQueryLanguageService:
"""Wrapper for PublisherQueryLanguageService. The PublisherQueryLanguage Service provides operations for executing a PQL statement to retrieve information from the system."""
def __init__(self, headers, config, op_config, lock, logger):
"""Inits PublisherQueryLangua... | the_stack_v2_python_sparse | adspygoogle/dfp/PublisherQueryLanguageService.py | hockeyprincess/google-api-dfp-python | train | 0 |
3c875d131c594ef952aa23bbd6e2681ff12ba75d | [
"r = self.client.put('/api/company/', LOGIN_COMPANY_OBJECT_SUCCESS, content_type='application/json')\nself.assertTrue(r.data['success'])\nself.assertEqual(r.status_code, status.HTTP_202_ACCEPTED)",
"r = self.client.put('/api/company/', LOGIN_COMPANY_OBJECT_FAILURE, content_type='application/json')\nself.assertFal... | <|body_start_0|>
r = self.client.put('/api/company/', LOGIN_COMPANY_OBJECT_SUCCESS, content_type='application/json')
self.assertTrue(r.data['success'])
self.assertEqual(r.status_code, status.HTTP_202_ACCEPTED)
<|end_body_0|>
<|body_start_1|>
r = self.client.put('/api/company/', LOGIN_CO... | This test is for login API | Login | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Login:
"""This test is for login API"""
def test_success(self):
"""Test Success"""
<|body_0|>
def test_failure(self):
"""Test Failure"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
r = self.client.put('/api/company/', LOGIN_COMPANY_OBJECT_SUCCE... | stack_v2_sparse_classes_75kplus_train_006581 | 11,905 | permissive | [
{
"docstring": "Test Success",
"name": "test_success",
"signature": "def test_success(self)"
},
{
"docstring": "Test Failure",
"name": "test_failure",
"signature": "def test_failure(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020909 | Implement the Python class `Login` described below.
Class description:
This test is for login API
Method signatures and docstrings:
- def test_success(self): Test Success
- def test_failure(self): Test Failure | Implement the Python class `Login` described below.
Class description:
This test is for login API
Method signatures and docstrings:
- def test_success(self): Test Success
- def test_failure(self): Test Failure
<|skeleton|>
class Login:
"""This test is for login API"""
def test_success(self):
"""Test... | c667e1bc2163ba49591e367bd5c882fe1b1f8df0 | <|skeleton|>
class Login:
"""This test is for login API"""
def test_success(self):
"""Test Success"""
<|body_0|>
def test_failure(self):
"""Test Failure"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Login:
"""This test is for login API"""
def test_success(self):
"""Test Success"""
r = self.client.put('/api/company/', LOGIN_COMPANY_OBJECT_SUCCESS, content_type='application/json')
self.assertTrue(r.data['success'])
self.assertEqual(r.status_code, status.HTTP_202_ACCEPTE... | the_stack_v2_python_sparse | service_area/tests.py | jinayshah86/service-provider-locator | train | 0 |
338efbda77c256534607e00a3fd209eef6d62c93 | [
"kwargs = self.filter_sk_params(Model.predict, kwargs)\nprobas = self.model.predict(x, **kwargs)\nreturn probas",
"kwargs = self.filter_sk_params(Model.predict, kwargs)\nprobas = self.model.predict(x, **kwargs)\nreturn np.argmax(probas, axis=1)"
] | <|body_start_0|>
kwargs = self.filter_sk_params(Model.predict, kwargs)
probas = self.model.predict(x, **kwargs)
return probas
<|end_body_0|>
<|body_start_1|>
kwargs = self.filter_sk_params(Model.predict, kwargs)
probas = self.model.predict(x, **kwargs)
return np.argmax(p... | Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search methods). | FunctionalKerasClassifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search metho... | stack_v2_sparse_classes_75kplus_train_006582 | 7,877 | permissive | [
{
"docstring": "Predict classes from features. Args: x: np.array or scipy.sparse.*matrix array of features **kwargs: additional keyword arguments Returns: y_pred: np.array 2-D array of class predicted probabilities",
"name": "predict_proba",
"signature": "def predict_proba(self, x, **kwargs)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_017737 | Implement the Python class `FunctionalKerasClassifier` described below.
Class description:
Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the sci... | Implement the Python class `FunctionalKerasClassifier` described below.
Class description:
Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the sci... | dea327aa9e7ef7f7bca5a6c225dbdca1077a06e9 | <|skeleton|>
class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search metho... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search methods)."""
... | the_stack_v2_python_sparse | sparse_data/exp_framework/dnn.py | Tarkiyah/googleResearch | train | 11 |
f9644d058a74c6fbc4fbda121318a27bd44e21f5 | [
"diff_pro = [[difficulty[i], profit[i]] for i in range(len(difficulty))]\ndiff_pro.sort(key=lambda k: k[0])\nmax_p = 0\nfor i, v in enumerate(diff_pro):\n max_p = max(max_p, v[1])\n diff_pro[i][1] = max_p\nans = 0\ndifficulty = [k[0] for k in diff_pro]\nfor w in worker:\n i = bisect.bisect(difficulty, w) -... | <|body_start_0|>
diff_pro = [[difficulty[i], profit[i]] for i in range(len(difficulty))]
diff_pro.sort(key=lambda k: k[0])
max_p = 0
for i, v in enumerate(diff_pro):
max_p = max(max_p, v[1])
diff_pro[i][1] = max_p
ans = 0
difficulty = [k[0] for k i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfitAssignment_1(self, difficulty, profit, worker):
""":type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int"""
<|body_0|>
def maxProfitAssignment_two_pointer(self, difficulty, profit, worker):
""":type difficulty:... | stack_v2_sparse_classes_75kplus_train_006583 | 2,163 | no_license | [
{
"docstring": ":type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int",
"name": "maxProfitAssignment_1",
"signature": "def maxProfitAssignment_1(self, difficulty, profit, worker)"
},
{
"docstring": ":type difficulty: List[int] :type profit: List[int] :type worke... | 2 | stack_v2_sparse_classes_30k_train_023408 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfitAssignment_1(self, difficulty, profit, worker): :type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int
- def maxProfitAssignment_two... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfitAssignment_1(self, difficulty, profit, worker): :type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int
- def maxProfitAssignment_two... | 0e99f9a5226507706b3ee66fd04bae813755ef40 | <|skeleton|>
class Solution:
def maxProfitAssignment_1(self, difficulty, profit, worker):
""":type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int"""
<|body_0|>
def maxProfitAssignment_two_pointer(self, difficulty, profit, worker):
""":type difficulty:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxProfitAssignment_1(self, difficulty, profit, worker):
""":type difficulty: List[int] :type profit: List[int] :type worker: List[int] :rtype: int"""
diff_pro = [[difficulty[i], profit[i]] for i in range(len(difficulty))]
diff_pro.sort(key=lambda k: k[0])
max_p =... | the_stack_v2_python_sparse | medium/arrayandstring/test_826_Most_Profit_Assigning_Work.py | wuxu1019/leetcode_sophia | train | 1 | |
e749338b98c7e4b7670befecc77b7f99c8ad85b6 | [
"gym.ObservationWrapper.__init__(self, env)\nself.width = 84\nself.height = 84\nself.observation_space = spaces.Box(low=0, high=255, shape=(self.height, self.width, 1), dtype=env.observation_space.dtype)",
"frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)\nframe = cv2.resize(frame, (self.width, self.height), inter... | <|body_start_0|>
gym.ObservationWrapper.__init__(self, env)
self.width = 84
self.height = 84
self.observation_space = spaces.Box(low=0, high=255, shape=(self.height, self.width, 1), dtype=env.observation_space.dtype)
<|end_body_0|>
<|body_start_1|>
frame = cv2.cvtColor(frame, cv... | WarpFrame | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WarpFrame:
def __init__(self, env):
"""Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment"""
<|body_0|>
def observation(self, frame):
"""returns the current observation from a frame :param frame: ([int] or [... | stack_v2_sparse_classes_75kplus_train_006584 | 8,857 | permissive | [
{
"docstring": "Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment",
"name": "__init__",
"signature": "def __init__(self, env)"
},
{
"docstring": "returns the current observation from a frame :param frame: ([int] or [float]) environment... | 2 | stack_v2_sparse_classes_30k_train_005198 | Implement the Python class `WarpFrame` described below.
Class description:
Implement the WarpFrame class.
Method signatures and docstrings:
- def __init__(self, env): Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment
- def observation(self, frame): returns ... | Implement the Python class `WarpFrame` described below.
Class description:
Implement the WarpFrame class.
Method signatures and docstrings:
- def __init__(self, env): Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment
- def observation(self, frame): returns ... | ee6dd27bdbddd2cad32b85981a70a4db0e4cf1ee | <|skeleton|>
class WarpFrame:
def __init__(self, env):
"""Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment"""
<|body_0|>
def observation(self, frame):
"""returns the current observation from a frame :param frame: ([int] or [... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WarpFrame:
def __init__(self, env):
"""Warp frames to 84x84 as done in the Nature paper and later work. :param env: (Gym Environment) the environment"""
gym.ObservationWrapper.__init__(self, env)
self.width = 84
self.height = 84
self.observation_space = spaces.Box(low=0... | the_stack_v2_python_sparse | rl/envs/atari.py | DeepKhantwal/rl | train | 0 | |
e0cfcac258f71173b2928e5b9a051d6277354935 | [
"adgroup_objs = AdGroup.objects.all().order_by('-id')\nserializer = GetAdGroupSerializer(adgroup_objs, many=True)\nreturn Response(create_response(serializer.data))",
"categories = request.data.pop('category', None)\nserializer = AdGroupSerializer(data=request.data)\nif serializer.is_valid():\n data = serializ... | <|body_start_0|>
adgroup_objs = AdGroup.objects.all().order_by('-id')
serializer = GetAdGroupSerializer(adgroup_objs, many=True)
return Response(create_response(serializer.data))
<|end_body_0|>
<|body_start_1|>
categories = request.data.pop('category', None)
serializer = AdGroup... | this view is used to create,update,list and delete AdGroup's | AdGroupView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdGroupView:
"""this view is used to create,update,list and delete AdGroup's"""
def get(self, request):
"""get list of all adgroups"""
<|body_0|>
def post(self, request):
"""create new campaign"""
<|body_1|>
def put(self, request):
"""update ... | stack_v2_sparse_classes_75kplus_train_006585 | 48,154 | permissive | [
{
"docstring": "get list of all adgroups",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "create new campaign",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "update existing adGroup",
"name": "put",
"signature": "def pu... | 3 | stack_v2_sparse_classes_30k_test_001671 | Implement the Python class `AdGroupView` described below.
Class description:
this view is used to create,update,list and delete AdGroup's
Method signatures and docstrings:
- def get(self, request): get list of all adgroups
- def post(self, request): create new campaign
- def put(self, request): update existing adGrou... | Implement the Python class `AdGroupView` described below.
Class description:
this view is used to create,update,list and delete AdGroup's
Method signatures and docstrings:
- def get(self, request): get list of all adgroups
- def post(self, request): create new campaign
- def put(self, request): update existing adGrou... | 590d8f6d597b9bafa1d0263edb95490f16570c37 | <|skeleton|>
class AdGroupView:
"""this view is used to create,update,list and delete AdGroup's"""
def get(self, request):
"""get list of all adgroups"""
<|body_0|>
def post(self, request):
"""create new campaign"""
<|body_1|>
def put(self, request):
"""update ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AdGroupView:
"""this view is used to create,update,list and delete AdGroup's"""
def get(self, request):
"""get list of all adgroups"""
adgroup_objs = AdGroup.objects.all().order_by('-id')
serializer = GetAdGroupSerializer(adgroup_objs, many=True)
return Response(create_res... | the_stack_v2_python_sparse | newscout_web/api/v1/views.py | rsqwerty/newscout_web | train | 0 |
f1c0ad746fccb04199952c4bee8fde4fafa792a4 | [
"self.err = None\nself.out = None\nself.outFile = f'{path.dirname(argv[0])}/.outLogger.txt'\nself.errFile = f'{path.dirname(argv[0])}/.errLogger.txt'",
"if not path.exists(self.outFile):\n open(self.outFile, 'w+').close()\nif not path.exists(self.errFile):\n open(self.errFile, 'w+').close()\ncurrentTime = d... | <|body_start_0|>
self.err = None
self.out = None
self.outFile = f'{path.dirname(argv[0])}/.outLogger.txt'
self.errFile = f'{path.dirname(argv[0])}/.errLogger.txt'
<|end_body_0|>
<|body_start_1|>
if not path.exists(self.outFile):
open(self.outFile, 'w+').close()
... | A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. errFile : string The file location to save the for stderr for this program. ... | logger | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class logger:
"""A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. errFile : string The file location to save... | stack_v2_sparse_classes_75kplus_train_006586 | 2,097 | permissive | [
{
"docstring": "The constructor for the logger class, sets up the needed variables.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Start redirecting all stdout and stderr to logger files for each.",
"name": "open",
"signature": "def open(self)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_013161 | Implement the Python class `logger` described below.
Class description:
A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. err... | Implement the Python class `logger` described below.
Class description:
A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. err... | e65f5aa64919649690059da37f7bd608b823ca6a | <|skeleton|>
class logger:
"""A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. errFile : string The file location to save... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class logger:
"""A class dedicated to loggin the stdout and stderr from the wtc-lms-GUI program. Attributes ---------- err : file descriptor The file descriptor for stderr for this program. out : file descriptor The file descriptor for stdout for this program. errFile : string The file location to save the for stde... | the_stack_v2_python_sparse | logger/loggerClass.py | GingerNinja2962/wtc-lms-GUI | train | 2 |
11bcab4df6cbb6d9aed5c19a2dc4189a5cf1d808 | [
"self._renderer = renderer\nself._width = self._renderer.width\nself._height = self._renderer.height\nself._small = int(self._height / 20)\nself._lines = []",
"nickname = information['nickname']\nprogress = information['progress']\nnumber_of_levels = information['number_of_levels']\nself._lines.append([f'GAME: {n... | <|body_start_0|>
self._renderer = renderer
self._width = self._renderer.width
self._height = self._renderer.height
self._small = int(self._height / 20)
self._lines = []
<|end_body_0|>
<|body_start_1|>
nickname = information['nickname']
progress = information['pro... | A class to represent start view of UI. Attributes: renderer: Renderer object. | StartView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StartView:
"""A class to represent start view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus_train_006587 | 2,905 | no_license | [
{
"docstring": "Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display.",
"name": "__init__",
"signature": "def __init__(self, renderer)"
},
{
"docstring": "Prepares all information to show for the renderer object. Informatio... | 2 | stack_v2_sparse_classes_30k_train_018832 | Implement the Python class `StartView` described below.
Class description:
A class to represent start view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object... | Implement the Python class `StartView` described below.
Class description:
A class to represent start view of UI. Attributes: renderer: Renderer object.
Method signatures and docstrings:
- def __init__(self, renderer): Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object... | 29cd15dddff620de068a479595a5cb9aba855343 | <|skeleton|>
class StartView:
"""A class to represent start view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
<|body_0|>
de... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StartView:
"""A class to represent start view of UI. Attributes: renderer: Renderer object."""
def __init__(self, renderer):
"""Constructs all the necessary attributes for finish view. Args: renderer (Renderer): Renderer object which renders the display."""
self._renderer = renderer
... | the_stack_v2_python_sparse | src/ui/start_view.py | TopiasHarjunpaa/ot-harjoitustyo | train | 0 |
3b2de93dde6067a53a07372b751a86c7c2211d08 | [
"n = len(matrix)\nfor i in range(n // 2):\n for j in range(n):\n matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])\nfor i in range(n):\n for j in range(i):\n matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i][j])",
"n = len(matrix)\nfor i in range(n // 2):\n for j... | <|body_start_0|>
n = len(matrix)
for i in range(n // 2):
for j in range(n):
matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])
for i in range(n):
for j in range(i):
matrix[i][j], matrix[j][i] = (matrix[j][i], matrix[i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
<|body_0|>
def rotateonce(self, matrix: List[List[int]]) -> None:
"""一次旋转"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(matrix)
for i in range(n // 2... | stack_v2_sparse_classes_75kplus_train_006588 | 1,239 | no_license | [
{
"docstring": "两次翻转：水平 + 主对角线",
"name": "rotate",
"signature": "def rotate(self, matrix: List[List[int]]) -> None"
},
{
"docstring": "一次旋转",
"name": "rotateonce",
"signature": "def rotateonce(self, matrix: List[List[int]]) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_045611 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: 两次翻转：水平 + 主对角线
- def rotateonce(self, matrix: List[List[int]]) -> None: 一次旋转 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: 两次翻转：水平 + 主对角线
- def rotateonce(self, matrix: List[List[int]]) -> None: 一次旋转
<|skeleton|>
class Solution:
def rotate(self... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
<|body_0|>
def rotateonce(self, matrix: List[List[int]]) -> None:
"""一次旋转"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""两次翻转：水平 + 主对角线"""
n = len(matrix)
for i in range(n // 2):
for j in range(n):
matrix[i][j], matrix[n - 1 - i][j] = (matrix[n - 1 - i][j], matrix[i][j])
for i in range(n):
for ... | the_stack_v2_python_sparse | 48.旋转图像/solution.py | QtTao/daily_leetcode | train | 0 | |
4c8a10ece7f2349ce117d535e4e7090da2150d20 | [
"fields = OrderedDict()\nvalidator_functions = {}\noptions_members = {}\nfor base in reversed(bases):\n if hasattr(base, '_schema'):\n fields.update(deepcopy(base._schema.fields))\n options_members.update(dict(base._schema.options))\n validator_functions.update(base._schema.validators)\nfor ... | <|body_start_0|>
fields = OrderedDict()
validator_functions = {}
options_members = {}
for base in reversed(bases):
if hasattr(base, '_schema'):
fields.update(deepcopy(base._schema.fields))
options_members.update(dict(base._schema.options))
... | Metaclass for Models. | ModelMeta | [
"BSD-3-Clause",
"BSD-2-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelMeta:
"""Metaclass for Models."""
def __new__(mcs, name, bases, attrs):
"""This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class."""
<|body_0|>
def _read_options(mcs, name, bases, attrs, ... | stack_v2_sparse_classes_75kplus_train_006589 | 15,133 | permissive | [
{
"docstring": "This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class.",
"name": "__new__",
"signature": "def __new__(mcs, name, bases, attrs)"
},
{
"docstring": "Parses model `Options` class into a `SchemaOptions` in... | 2 | stack_v2_sparse_classes_30k_train_026551 | Implement the Python class `ModelMeta` described below.
Class description:
Metaclass for Models.
Method signatures and docstrings:
- def __new__(mcs, name, bases, attrs): This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class.
- def _read_o... | Implement the Python class `ModelMeta` described below.
Class description:
Metaclass for Models.
Method signatures and docstrings:
- def __new__(mcs, name, bases, attrs): This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class.
- def _read_o... | 5c0edaac0bc8b040fda638845f24e39b6c324888 | <|skeleton|>
class ModelMeta:
"""Metaclass for Models."""
def __new__(mcs, name, bases, attrs):
"""This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class."""
<|body_0|>
def _read_options(mcs, name, bases, attrs, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelMeta:
"""Metaclass for Models."""
def __new__(mcs, name, bases, attrs):
"""This metaclass parses the declarative Model into a corresponding Schema, then adding it as the `_schema` attribute to the host class."""
fields = OrderedDict()
validator_functions = {}
options_... | the_stack_v2_python_sparse | bin/jamf_pro_addon_for_splunk/aob_py3/solnlib/packages/schematics/models.py | jamf/SplunkBase | train | 5 |
b5558d4c02340a7240356d68b7833e1dcf71dda0 | [
"self._graph = graph\nself._type = t\nself._batch_size = batch_size\nself._strategy = strategy\nself._client = self._graph.get_client()\nself._node_from = node_from\nif self._node_from == pywrap.NodeFrom.NODE:\n if self._type not in self._graph.get_node_decoders().keys():\n raise ValueError('Graph has no ... | <|body_start_0|>
self._graph = graph
self._type = t
self._batch_size = batch_size
self._strategy = strategy
self._client = self._graph.get_client()
self._node_from = node_from
if self._node_from == pywrap.NodeFrom.NODE:
if self._type not in self._graph... | Sampling nodes from graph. | NodeSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeSampler:
"""Sampling nodes from graph."""
def __init__(self, graph, t, batch_size, strategy='by_order', node_from=pywrap.NodeFrom.NODE):
"""Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample from. t (string): type of node or egde. If t is a type of n... | stack_v2_sparse_classes_75kplus_train_006590 | 4,632 | permissive | [
{
"docstring": "Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample from. t (string): type of node or egde. If t is a type of node, then `NodeSampler` will sample from node source. Else if `t` is a type of edge, then `node_from=EDGE_SRC` indicates that the nodes will be sampled from... | 2 | stack_v2_sparse_classes_30k_train_051701 | Implement the Python class `NodeSampler` described below.
Class description:
Sampling nodes from graph.
Method signatures and docstrings:
- def __init__(self, graph, t, batch_size, strategy='by_order', node_from=pywrap.NodeFrom.NODE): Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample fr... | Implement the Python class `NodeSampler` described below.
Class description:
Sampling nodes from graph.
Method signatures and docstrings:
- def __init__(self, graph, t, batch_size, strategy='by_order', node_from=pywrap.NodeFrom.NODE): Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample fr... | 1827c28c570c355e513f24b6a61a88457cfecdaf | <|skeleton|>
class NodeSampler:
"""Sampling nodes from graph."""
def __init__(self, graph, t, batch_size, strategy='by_order', node_from=pywrap.NodeFrom.NODE):
"""Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample from. t (string): type of node or egde. If t is a type of n... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NodeSampler:
"""Sampling nodes from graph."""
def __init__(self, graph, t, batch_size, strategy='by_order', node_from=pywrap.NodeFrom.NODE):
"""Create a Base NodeSampler.. Args: graph (`Graph` object): The graph which sample from. t (string): type of node or egde. If t is a type of node, then `No... | the_stack_v2_python_sparse | graphlearn/python/sampler/node_sampler.py | lorinlee/graph-learn | train | 0 |
9512ac65ee120de771f37f2dc6182ea6f5e88231 | [
"similarity_calc = region_similarity_calculator.IouSimilarity()\nmatcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=match_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)\nbox_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()\nself._target_assigner = target_as... | <|body_start_0|>
similarity_calc = region_similarity_calculator.IouSimilarity()
matcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=match_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)
box_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()
... | Labeler for multiscale anchor boxes. | AnchorLabeler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes i... | stack_v2_sparse_classes_75kplus_train_006591 | 10,735 | permissive | [
{
"docstring": "Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes in the dataset. match_threshold: float number between 0 and 1 representing the threshold to assign positive labels for anchors.",
"na... | 3 | stack_v2_sparse_classes_30k_train_031724 | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.5): Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num... | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.5): Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num... | a5388a45f71a949639b35cc5b990bd130d2d8164 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes in the dataset... | the_stack_v2_python_sparse | TensorFlow2/Detection/Efficientdet/model/anchors.py | NVIDIA/DeepLearningExamples | train | 11,838 |
70886b5a9bf15a63b83284bd395a3ece9eed85e7 | [
"self.projectFileName_ = projectFileName\nself.resultProjectFileName_ = resultProjectFileName\nself.projectExtension_ = projectExtension\nself.braCustomProjectInfo_ = myBraCustomProjectInfo",
"projTokenizer = ProjTokenizerFactory.createProjectsTokenizer(self.projectExtension_)\nwith open(self.resultProjectFileNam... | <|body_start_0|>
self.projectFileName_ = projectFileName
self.resultProjectFileName_ = resultProjectFileName
self.projectExtension_ = projectExtension
self.braCustomProjectInfo_ = myBraCustomProjectInfo
<|end_body_0|>
<|body_start_1|>
projTokenizer = ProjTokenizerFactory.createP... | Project parser to add BRA custom information. This is the class to be called from client code. | ProjectParser | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectParser:
"""Project parser to add BRA custom information. This is the class to be called from client code."""
def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo):
"""Constructor."""
<|body_0|>
def parseProject(self):... | stack_v2_sparse_classes_75kplus_train_006592 | 30,925 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo)"
},
{
"docstring": "Parse the project indicated in the constructor, adding BRA custom info in the result file.",
"name": "pars... | 2 | null | Implement the Python class `ProjectParser` described below.
Class description:
Project parser to add BRA custom information. This is the class to be called from client code.
Method signatures and docstrings:
- def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo): Constr... | Implement the Python class `ProjectParser` described below.
Class description:
Project parser to add BRA custom information. This is the class to be called from client code.
Method signatures and docstrings:
- def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo): Constr... | a29aaa36b73292c14f3f0c83598c0d8991b0295a | <|skeleton|>
class ProjectParser:
"""Project parser to add BRA custom information. This is the class to be called from client code."""
def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo):
"""Constructor."""
<|body_0|>
def parseProject(self):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProjectParser:
"""Project parser to add BRA custom information. This is the class to be called from client code."""
def __init__(self, projectFileName, resultProjectFileName, projectExtension, myBraCustomProjectInfo):
"""Constructor."""
self.projectFileName_ = projectFileName
self... | the_stack_v2_python_sparse | Python/gui/parse_project.py | GervasioCalderon/bug-reproducer-assistant | train | 1 |
ae6b2b217988405a4e08f87d6d05e3e78946531a | [
"try:\n if not token:\n return False\n if token['server_nonce'] != nonce:\n return False\n now = int(time.mktime(time.gmtime()))\n return now <= token['valid_until']\nexcept:\n return False",
"if Token.is_valid():\n return token['token']\nelse:\n return None",
"if not token:\n... | <|body_start_0|>
try:
if not token:
return False
if token['server_nonce'] != nonce:
return False
now = int(time.mktime(time.gmtime()))
return now <= token['valid_until']
except:
return False
<|end_body_0|>
<|bod... | Secure token which is used for authentication and authorization purposes | Token | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Token:
"""Secure token which is used for authentication and authorization purposes"""
def is_valid(token):
"""Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in configuration file (ii) Checks wether the validity time in ... | stack_v2_sparse_classes_75kplus_train_006593 | 2,725 | no_license | [
{
"docstring": "Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in configuration file (ii) Checks wether the validity time in token grater than the current system time For the correct operation of the token verification the system clock MUST be syn... | 5 | null | Implement the Python class `Token` described below.
Class description:
Secure token which is used for authentication and authorization purposes
Method signatures and docstrings:
- def is_valid(token): Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in co... | Implement the Python class `Token` described below.
Class description:
Secure token which is used for authentication and authorization purposes
Method signatures and docstrings:
- def is_valid(token): Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in co... | 75ec52a4d002215a67cefc9c83ad98b5f9e1487c | <|skeleton|>
class Token:
"""Secure token which is used for authentication and authorization purposes"""
def is_valid(token):
"""Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in configuration file (ii) Checks wether the validity time in ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Token:
"""Secure token which is used for authentication and authorization purposes"""
def is_valid(token):
"""Verifies whether the token is valid: (i) Checks whether the server nonce which is found in token is the same as in configuration file (ii) Checks wether the validity time in token grater ... | the_stack_v2_python_sparse | backend/tokens.py | dmitriykuptsov/radwi | train | 0 |
57fcbee6fcb7903b6bc15062ddcea300c5b89a3b | [
"SphericalPotential.__init__(self, amp=amp, ro=ro, vo=vo, amp_units='mass')\na = conversion.parse_length(a, ro=self._ro)\nself.a = a\nself.a2 = a ** 2\nif normalize or (isinstance(normalize, (int, float)) and (not isinstance(normalize, bool))):\n if self.a > 1.0:\n raise ValueError('SphericalShellPotentia... | <|body_start_0|>
SphericalPotential.__init__(self, amp=amp, ro=ro, vo=vo, amp_units='mass')
a = conversion.parse_length(a, ro=self._ro)
self.a = a
self.a2 = a ** 2
if normalize or (isinstance(normalize, (int, float)) and (not isinstance(normalize, bool))):
if self.a >... | Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell. | SphericalShellPotential | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SphericalShellPotential:
"""Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell."""
def __init__(self, amp=1.0, a=0.75, normalize=False, ro... | stack_v2_sparse_classes_75kplus_train_006594 | 3,427 | permissive | [
{
"docstring": "NAME: __init__ PURPOSE: initialize a spherical shell potential INPUT: amp - mass of the shell (default: 1); can be a Quantity with units of mass or Gxmass a= (0.75) radius of the shell (can be Quantity) normalize - if True, normalize such that vc(1.,0.)=1., or, if given as a number, such that th... | 6 | stack_v2_sparse_classes_30k_train_014001 | Implement the Python class `SphericalShellPotential` described below.
Class description:
Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell.
Method signatures and d... | Implement the Python class `SphericalShellPotential` described below.
Class description:
Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell.
Method signatures and d... | 9654e2e181d26abaac4a4fba49375887fb290d36 | <|skeleton|>
class SphericalShellPotential:
"""Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell."""
def __init__(self, amp=1.0, a=0.75, normalize=False, ro... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SphericalShellPotential:
"""Class that implements the potential of an infinitesimally-thin, spherical shell .. math:: \\rho(r) = \\frac{\\mathrm{amp}}{4\\pi\\,a^2}\\,\\delta(r-a) with :math:`\\mathrm{amp} = GM` the mass of the shell."""
def __init__(self, amp=1.0, a=0.75, normalize=False, ro=None, vo=Non... | the_stack_v2_python_sparse | galpy/potential/SphericalShellPotential.py | davidhendel/galpy | train | 0 |
04df1bcc0f6aafc6c8ddccff3a222b7e0bac594e | [
"super(BrowserProxyGrid, self).__init__()\nself._capabilities = capabilities\nself._grid_url = grid_url",
"proxy_ip = self._get_browsermobproxy_docker_ip()\nproxy_port = '9090'\nself._client = Client('{0}:{1}'.format(proxy_ip, proxy_port))",
"proxy_container = os.popen(\"docker ps --format {{.Names}} | grep 'pr... | <|body_start_0|>
super(BrowserProxyGrid, self).__init__()
self._capabilities = capabilities
self._grid_url = grid_url
<|end_body_0|>
<|body_start_1|>
proxy_ip = self._get_browsermobproxy_docker_ip()
proxy_port = '9090'
self._client = Client('{0}:{1}'.format(proxy_ip, pro... | Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserName": "chrome", "platform": 'LINUX', "version": '', "javascriptEnabled": True } bprox... | BrowserProxyGrid | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BrowserProxyGrid:
"""Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserName": "chrome", "platform": 'LINUX', "ver... | stack_v2_sparse_classes_75kplus_train_006595 | 9,587 | permissive | [
{
"docstring": "Initialises Browsermob-proxy grid instance :param dict capabilities: Browser/Device capabilities :param str grid_url: Selenium grid url",
"name": "__init__",
"signature": "def __init__(self, capabilities, grid_url='http://localhost:4444/wd/hub')"
},
{
"docstring": "Assumes browse... | 5 | null | Implement the Python class `BrowserProxyGrid` described below.
Class description:
Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserNam... | Implement the Python class `BrowserProxyGrid` described below.
Class description:
Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserNam... | 7175edbf625e46ce1489c97f171a8717eaf0be7e | <|skeleton|>
class BrowserProxyGrid:
"""Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserName": "chrome", "platform": 'LINUX', "ver... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BrowserProxyGrid:
"""Run browsermob-proxy and browser instance in docker mode first. Use to capture and analyse traffic. Useful for a CI setup Please refer to https://hub.docker.com/r/qautomatron/docker-browsermob-proxy/ Example: capabilities = { "browserName": "chrome", "platform": 'LINUX', "version": '', "j... | the_stack_v2_python_sparse | nzme_skynet/core/proxy/browserproxy.py | MilindThakur/nzme-skynet | train | 4 |
4dc9a0bbf7a145253bd145f8e3010881bacc9016 | [
"if max(idf.values()) > documents:\n raise ValueError(f'The number of documents ({documents}) must be greater or equal to the most common term ({max(idf.values())})')\nif min(idf.values()) < 0:\n raise ValueError('The IDF values must be non-negative')\nif documents < 0:\n raise ValueError('The number of do... | <|body_start_0|>
if max(idf.values()) > documents:
raise ValueError(f'The number of documents ({documents}) must be greater or equal to the most common term ({max(idf.values())})')
if min(idf.values()) < 0:
raise ValueError('The IDF values must be non-negative')
if docume... | The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :ivar ~.idf: The IDF table used in conjunction with term weighting. The keys ar... | TFIDFScorer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFIDFScorer:
"""The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :ivar ~.idf: The IDF table used in conju... | stack_v2_sparse_classes_75kplus_train_006596 | 4,002 | no_license | [
{
"docstring": "Create the term-weighting scheme with the IDF table and the number of documents in that scheme. :param idf: The IDF table used in conjunction with term weighting. The keys are the terms, and the corresponding values are the number of documents in which they appear. :type idf: dict :param documen... | 3 | null | Implement the Python class `TFIDFScorer` described below.
Class description:
The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :... | Implement the Python class `TFIDFScorer` described below.
Class description:
The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :... | 6320913c6adf31347d4b1f8d398bd65b61428cfb | <|skeleton|>
class TFIDFScorer:
"""The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :ivar ~.idf: The IDF table used in conju... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TFIDFScorer:
"""The TF-IDF scorer assigns a score the candidate participants similarly to the :class:`~nlp.weighting.tfidf.TFIDF` term-weighting scheme. Therefore the scorer depends on an IDF table, given as a dictionary, and the number of documents in it. :ivar ~.idf: The IDF table used in conjunction with t... | the_stack_v2_python_sparse | lib/apd/scorers/local/tfidf_scorer.py | TianhaoFu/eld-data | train | 0 |
0fbd5d643901bf376d0ad3778ea2531bdc618f33 | [
"obj = self._get_by_name(name)\nif obj is not None:\n raise ValueError('l4 mapping with name {0} already exists'.format(name))\nself.data.append({'name': name, 'uri': uri})",
"obj = self._get_by_name(name)\nif obj is not None:\n self.data.remove(obj)\nelse:\n raise ValueError('The rule with name {0} does... | <|body_start_0|>
obj = self._get_by_name(name)
if obj is not None:
raise ValueError('l4 mapping with name {0} already exists'.format(name))
self.data.append({'name': name, 'uri': uri})
<|end_body_0|>
<|body_start_1|>
obj = self._get_by_name(name)
if obj is not None:
... | Wrapper class around custom application definitions. | CustomApplications | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomApplications:
"""Wrapper class around custom application definitions."""
def add(self, name, uri):
"""Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri"""
<|body_0|>
def remove(self, name):
"""Re... | stack_v2_sparse_classes_75kplus_train_006597 | 13,335 | permissive | [
{
"docstring": "Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri",
"name": "add",
"signature": "def add(self, name, uri)"
},
{
"docstring": "Remove a custom application rule :param str name: the name of the rule",
"name": "remove... | 2 | stack_v2_sparse_classes_30k_train_022488 | Implement the Python class `CustomApplications` described below.
Class description:
Wrapper class around custom application definitions.
Method signatures and docstrings:
- def add(self, name, uri): Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri
- def r... | Implement the Python class `CustomApplications` described below.
Class description:
Wrapper class around custom application definitions.
Method signatures and docstrings:
- def add(self, name, uri): Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri
- def r... | a944f18ad79c775ab6c072924b0bbb613d7462d2 | <|skeleton|>
class CustomApplications:
"""Wrapper class around custom application definitions."""
def add(self, name, uri):
"""Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri"""
<|body_0|>
def remove(self, name):
"""Re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CustomApplications:
"""Wrapper class around custom application definitions."""
def add(self, name, uri):
"""Add a custom application rule :param str name: the name of the rule :param str uri: a string representing a uri"""
obj = self._get_by_name(name)
if obj is not None:
... | the_stack_v2_python_sparse | steelscript/netshark/core/_settings5.py | riverbed/steelscript-netshark | train | 0 |
b4fd9bffee583db8cc45237db4c0604fa3a2c574 | [
"super(StopVehicle, self).__init__(name)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nself._control, self._type = get_actor_control(actor)\nif self._type == 'walker':\n self._control.speed = 0\nself._actor = actor\nself._brake_value = brake_value",
"new_status = py_trees.common.Status.RUNNING... | <|body_start_0|>
super(StopVehicle, self).__init__(name)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
self._control, self._type = get_actor_control(actor)
if self._type == 'walker':
self._control.speed = 0
self._actor = actor
self._brake_value ... | This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in [0,1] applied The behavior terminates when the actor stopped moving | StopVehicle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StopVehicle:
"""This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in [0,1] applied The behavior terminates ... | stack_v2_sparse_classes_75kplus_train_006598 | 39,839 | permissive | [
{
"docstring": "Setup _actor and maximum braking value",
"name": "__init__",
"signature": "def __init__(self, actor, brake_value, name='Stopping')"
},
{
"docstring": "Set brake to brake_value until reaching full stop",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_038762 | Implement the Python class `StopVehicle` described below.
Class description:
This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in... | Implement the Python class `StopVehicle` described below.
Class description:
This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class StopVehicle:
"""This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in [0,1] applied The behavior terminates ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StopVehicle:
"""This class contains an atomic stopping behavior. The controlled traffic participant will decelerate with _bake_value_ until reaching a full stop. Important parameters: - actor: CARLA actor to execute the behavior - brake_value: Brake value in [0,1] applied The behavior terminates when the acto... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_behaviors.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
a7d373b2abeaa9c74fa7dea5b67d3117692bc2ce | [
"return_type = WorkbookFunctionResult(self.context)\npayload = {'number': number}\nqry = ServiceOperationQuery(self, 'abs', None, payload, None, return_type)\nself.context.add_query(qry)\nreturn return_type",
"return_type = WorkbookFunctionResult(self.context)\npayload = {'issue': issue, 'firstInterest': first_in... | <|body_start_0|>
return_type = WorkbookFunctionResult(self.context)
payload = {'number': number}
qry = ServiceOperationQuery(self, 'abs', None, payload, None, return_type)
self.context.add_query(qry)
return return_type
<|end_body_0|>
<|body_start_1|>
return_type = Workbo... | Used as a container for Microsoft Excel worksheet function | WorkbookFunctions | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkbookFunctions:
"""Used as a container for Microsoft Excel worksheet function"""
def abs(self, number):
"""Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float number: The real number of which you want the absolute valu... | stack_v2_sparse_classes_75kplus_train_006599 | 2,700 | permissive | [
{
"docstring": "Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float number: The real number of which you want the absolute value.",
"name": "abs",
"signature": "def abs(self, number)"
},
{
"docstring": "Returns the accrued interest f... | 3 | stack_v2_sparse_classes_30k_train_013297 | Implement the Python class `WorkbookFunctions` described below.
Class description:
Used as a container for Microsoft Excel worksheet function
Method signatures and docstrings:
- def abs(self, number): Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float nu... | Implement the Python class `WorkbookFunctions` described below.
Class description:
Used as a container for Microsoft Excel worksheet function
Method signatures and docstrings:
- def abs(self, number): Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float nu... | cbd245d1af8d69e013c469cfc2a9851f51c91417 | <|skeleton|>
class WorkbookFunctions:
"""Used as a container for Microsoft Excel worksheet function"""
def abs(self, number):
"""Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float number: The real number of which you want the absolute valu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WorkbookFunctions:
"""Used as a container for Microsoft Excel worksheet function"""
def abs(self, number):
"""Returns the absolute value of a number. The absolute value of a number is the number without its sign :param float number: The real number of which you want the absolute value."""
... | the_stack_v2_python_sparse | office365/onedrive/workbooks/functions/functions.py | vgrem/Office365-REST-Python-Client | train | 1,006 |
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