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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9a5ac4809aa729949070f15cd48cf35504bf9c6f | [
"with codecs.open(file_name, 'r', encoding='utf8') as f:\n recs = json.load(f)\nself.recs = recs",
"if query == None:\n fc = FakeCursor(self.recs)\nelse:\n retur = []\n k = query.keys()[0]\n v = query.values()[0]\n for rec in self.recs:\n if rec[k] == v:\n retur.append(rec)\n ... | <|body_start_0|>
with codecs.open(file_name, 'r', encoding='utf8') as f:
recs = json.load(f)
self.recs = recs
<|end_body_0|>
<|body_start_1|>
if query == None:
fc = FakeCursor(self.recs)
else:
retur = []
k = query.keys()[0]
v =... | Mock Object interface for MongoDB client | FakeMongo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FakeMongo:
"""Mock Object interface for MongoDB client"""
def __init__(self, file_name):
"""Make a FakeMongo Args: file_name (str): name of json file to draw queries from"""
<|body_0|>
def find(self, query=None):
"""perform query on file using mongodb query synta... | stack_v2_sparse_classes_36k_train_028300 | 1,965 | no_license | [
{
"docstring": "Make a FakeMongo Args: file_name (str): name of json file to draw queries from",
"name": "__init__",
"signature": "def __init__(self, file_name)"
},
{
"docstring": "perform query on file using mongodb query syntax (Only partially functional) Kwargs: query (dict): MongoDB style qu... | 2 | stack_v2_sparse_classes_30k_test_000833 | Implement the Python class `FakeMongo` described below.
Class description:
Mock Object interface for MongoDB client
Method signatures and docstrings:
- def __init__(self, file_name): Make a FakeMongo Args: file_name (str): name of json file to draw queries from
- def find(self, query=None): perform query on file usin... | Implement the Python class `FakeMongo` described below.
Class description:
Mock Object interface for MongoDB client
Method signatures and docstrings:
- def __init__(self, file_name): Make a FakeMongo Args: file_name (str): name of json file to draw queries from
- def find(self, query=None): perform query on file usin... | 1da48eba195a6452dee71fa085ee2ffc55d19777 | <|skeleton|>
class FakeMongo:
"""Mock Object interface for MongoDB client"""
def __init__(self, file_name):
"""Make a FakeMongo Args: file_name (str): name of json file to draw queries from"""
<|body_0|>
def find(self, query=None):
"""perform query on file using mongodb query synta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FakeMongo:
"""Mock Object interface for MongoDB client"""
def __init__(self, file_name):
"""Make a FakeMongo Args: file_name (str): name of json file to draw queries from"""
with codecs.open(file_name, 'r', encoding='utf8') as f:
recs = json.load(f)
self.recs = recs
... | the_stack_v2_python_sparse | fruitbowl/cherry/fake_mongo.py | patrick-s-h-lewis/fruitbowl | train | 1 |
a09465adfa5927cc209244e1db8fa01f76b18081 | [
"company = self.env.company\nfor user in self:\n if user.branch_id and user.branch_id.company_id != company:\n raise exceptions.UserError(_(\"Sorry! The selected Branch does not belong to the current Company '%s'\", company.name))",
"if self.property_warehouse_id:\n return self.property_warehouse_id\... | <|body_start_0|>
company = self.env.company
for user in self:
if user.branch_id and user.branch_id.company_id != company:
raise exceptions.UserError(_("Sorry! The selected Branch does not belong to the current Company '%s'", company.name))
<|end_body_0|>
<|body_start_1|>
... | inherited res users | ResUsers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResUsers:
"""inherited res users"""
def branch_constrains(self):
"""branch constrains"""
<|body_0|>
def _get_default_warehouse_id(self):
"""methode to get default warehouse id"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
company = self.env.co... | stack_v2_sparse_classes_36k_train_028301 | 2,986 | no_license | [
{
"docstring": "branch constrains",
"name": "branch_constrains",
"signature": "def branch_constrains(self)"
},
{
"docstring": "methode to get default warehouse id",
"name": "_get_default_warehouse_id",
"signature": "def _get_default_warehouse_id(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019241 | Implement the Python class `ResUsers` described below.
Class description:
inherited res users
Method signatures and docstrings:
- def branch_constrains(self): branch constrains
- def _get_default_warehouse_id(self): methode to get default warehouse id | Implement the Python class `ResUsers` described below.
Class description:
inherited res users
Method signatures and docstrings:
- def branch_constrains(self): branch constrains
- def _get_default_warehouse_id(self): methode to get default warehouse id
<|skeleton|>
class ResUsers:
"""inherited res users"""
d... | 4b1bcb8f17aad44fe9c80a8180eb0128e6bb2c14 | <|skeleton|>
class ResUsers:
"""inherited res users"""
def branch_constrains(self):
"""branch constrains"""
<|body_0|>
def _get_default_warehouse_id(self):
"""methode to get default warehouse id"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResUsers:
"""inherited res users"""
def branch_constrains(self):
"""branch constrains"""
company = self.env.company
for user in self:
if user.branch_id and user.branch_id.company_id != company:
raise exceptions.UserError(_("Sorry! The selected Branch do... | the_stack_v2_python_sparse | multi_branch_base/models/branch_res_users.py | CybroOdoo/CybroAddons | train | 209 |
3ff3a964099cfd0b9c9b9377663e1619e428690b | [
"group_map = {}\nitem_groups = self.item.item_groups\nfor group in item_groups:\n if group.id in group_map:\n msg = \"menu item '%s' has duplicate group '%s'\"\n raise ValueError(msg % (self.path, group.id))\n group_map[group.id] = group\nif u'' not in group_map:\n group = ItemGroup()\n gr... | <|body_start_0|>
group_map = {}
item_groups = self.item.item_groups
for group in item_groups:
if group.id in group_map:
msg = "menu item '%s' has duplicate group '%s'"
raise ValueError(msg % (self.path, group.id))
group_map[group.id] = grou... | A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module. | MenuNode | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MenuNode:
"""A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module."""
def group_data(self):
"""The group map and list of group items for the node. Returns ------- result : tuple A tuple of (dict, list) ... | stack_v2_sparse_classes_36k_train_028302 | 10,191 | permissive | [
{
"docstring": "The group map and list of group items for the node. Returns ------- result : tuple A tuple of (dict, list) which holds the mapping of group id to ItemGroup object, and the flat list of ordered groups.",
"name": "group_data",
"signature": "def group_data(self)"
},
{
"docstring": "... | 5 | stack_v2_sparse_classes_30k_train_010287 | Implement the Python class `MenuNode` described below.
Class description:
A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module.
Method signatures and docstrings:
- def group_data(self): The group map and list of group items for the node... | Implement the Python class `MenuNode` described below.
Class description:
A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module.
Method signatures and docstrings:
- def group_data(self): The group map and list of group items for the node... | 1544e7fb371b8f941cfa2fde682795e479380284 | <|skeleton|>
class MenuNode:
"""A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module."""
def group_data(self):
"""The group map and list of group items for the node. Returns ------- result : tuple A tuple of (dict, list) ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MenuNode:
"""A path node representing a menu item. This class is an implementation detail and should not be consumed by code outside of this module."""
def group_data(self):
"""The group map and list of group items for the node. Returns ------- result : tuple A tuple of (dict, list) which holds t... | the_stack_v2_python_sparse | enaml/workbench/ui/menu_helper.py | MatthieuDartiailh/enaml | train | 26 |
19bf51b9b899aeae3c676e7bc4e292e8a482a107 | [
"c = Counter()\nfor ch in string:\n c[ch] += 1\nfor key in c.keys():\n if key > 1:\n return True\nreturn False",
"if len(string) == 1:\n return True\nfor i in range(len(string)):\n temp = string[i]\n substring = string[:i] + string[i + 1:]\n for temp_ch in substring:\n if temp == t... | <|body_start_0|>
c = Counter()
for ch in string:
c[ch] += 1
for key in c.keys():
if key > 1:
return True
return False
<|end_body_0|>
<|body_start_1|>
if len(string) == 1:
return True
for i in range(len(string)):
... | isUnique | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class isUnique:
def check_hashmap(self, string):
"""Solution uses additional Counter (hashmap) datastructure"""
<|body_0|>
def check_no_ds(self, string):
"""Solution without using any additional datastructures"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_028303 | 798 | no_license | [
{
"docstring": "Solution uses additional Counter (hashmap) datastructure",
"name": "check_hashmap",
"signature": "def check_hashmap(self, string)"
},
{
"docstring": "Solution without using any additional datastructures",
"name": "check_no_ds",
"signature": "def check_no_ds(self, string)"... | 2 | stack_v2_sparse_classes_30k_train_009753 | Implement the Python class `isUnique` described below.
Class description:
Implement the isUnique class.
Method signatures and docstrings:
- def check_hashmap(self, string): Solution uses additional Counter (hashmap) datastructure
- def check_no_ds(self, string): Solution without using any additional datastructures | Implement the Python class `isUnique` described below.
Class description:
Implement the isUnique class.
Method signatures and docstrings:
- def check_hashmap(self, string): Solution uses additional Counter (hashmap) datastructure
- def check_no_ds(self, string): Solution without using any additional datastructures
<... | 09d75e3ec63308d3b8be0b07748043cde79a62a1 | <|skeleton|>
class isUnique:
def check_hashmap(self, string):
"""Solution uses additional Counter (hashmap) datastructure"""
<|body_0|>
def check_no_ds(self, string):
"""Solution without using any additional datastructures"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class isUnique:
def check_hashmap(self, string):
"""Solution uses additional Counter (hashmap) datastructure"""
c = Counter()
for ch in string:
c[ch] += 1
for key in c.keys():
if key > 1:
return True
return False
def check_no_ds(se... | the_stack_v2_python_sparse | ctc/ch01-arrays/1-is-unique.py | skailasa/practice | train | 5 | |
a7596482fd636fb08ad508e926899fd4c82e1eaa | [
"super().__init__(settings, ui_id, job_id)\nself.local_template = 'settings/bilby_local.sh'\nself.job_parameter_file = os.path.join(self.get_working_directory(), 'json_params.json')\nself.job_output_directory = os.path.join(self.get_working_directory(), 'output')",
"params = super().generate_template_dict()\npara... | <|body_start_0|>
super().__init__(settings, ui_id, job_id)
self.local_template = 'settings/bilby_local.sh'
self.job_parameter_file = os.path.join(self.get_working_directory(), 'json_params.json')
self.job_output_directory = os.path.join(self.get_working_directory(), 'output')
<|end_body_... | Bilby | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bilby:
def __init__(self, settings, ui_id, job_id):
"""Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param job_id: The Slurm id of the Job"""
<|body_0|>
def generate_template_dict(self):
... | stack_v2_sparse_classes_36k_train_028304 | 2,162 | permissive | [
{
"docstring": "Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param job_id: The Slurm id of the Job",
"name": "__init__",
"signature": "def __init__(self, settings, ui_id, job_id)"
},
{
"docstring": "Called befo... | 3 | stack_v2_sparse_classes_30k_test_000187 | Implement the Python class `Bilby` described below.
Class description:
Implement the Bilby class.
Method signatures and docstrings:
- def __init__(self, settings, ui_id, job_id): Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param jo... | Implement the Python class `Bilby` described below.
Class description:
Implement the Bilby class.
Method signatures and docstrings:
- def __init__(self, settings, ui_id, job_id): Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param jo... | 68ebdec8dd2fe7a4d1c6ad07783e86ea2056ae67 | <|skeleton|>
class Bilby:
def __init__(self, settings, ui_id, job_id):
"""Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param job_id: The Slurm id of the Job"""
<|body_0|>
def generate_template_dict(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bilby:
def __init__(self, settings, ui_id, job_id):
"""Initialises the local scheduler class for Bilby :param settings: The settings from settings.py :param ui_id: The UI id of the job :param job_id: The Slurm id of the Job"""
super().__init__(settings, ui_id, job_id)
self.local_templa... | the_stack_v2_python_sparse | misc/job_controller_scripts/local/bilby_local.py | ADACS-Australia/SS18B-PLasky | train | 1 | |
6c2f8302b3ecea41ee2db945bacfdfb31bdf3573 | [
"if len(self.variant.alleles) > 2:\n raise ValueError('Additive encoding can only be used with one allele')\nallele_sum = self.allele_idxs.sum(axis=1).astype('float')\nallele_sum[(self.allele_idxs == MISSING_IDX).any(axis=1)] = np.nan\nresult = pd.array(data=allele_sum, dtype='UInt8')\nreturn result",
"if len(... | <|body_start_0|>
if len(self.variant.alleles) > 2:
raise ValueError('Additive encoding can only be used with one allele')
allele_sum = self.allele_idxs.sum(axis=1).astype('float')
allele_sum[(self.allele_idxs == MISSING_IDX).any(axis=1)] = np.nan
result = pd.array(data=allele... | Genotype Mixin containing functions for performing encoding | EncodingMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodingMixin:
"""Genotype Mixin containing functions for performing encoding"""
def encode_additive(self) -> pd.arrays.IntegerArray:
"""Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any alleles are missing Raises ValueError if there is more t... | stack_v2_sparse_classes_36k_train_028305 | 3,710 | permissive | [
{
"docstring": "Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any alleles are missing Raises ValueError if there is more than 1 alternate allele",
"name": "encode_additive",
"signature": "def encode_additive(self) -> pd.arrays.IntegerArray"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_013639 | Implement the Python class `EncodingMixin` described below.
Class description:
Genotype Mixin containing functions for performing encoding
Method signatures and docstrings:
- def encode_additive(self) -> pd.arrays.IntegerArray: Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any... | Implement the Python class `EncodingMixin` described below.
Class description:
Genotype Mixin containing functions for performing encoding
Method signatures and docstrings:
- def encode_additive(self) -> pd.arrays.IntegerArray: Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any... | a4419a5c491567ddfca7fdb2234a1c0d7e396719 | <|skeleton|>
class EncodingMixin:
"""Genotype Mixin containing functions for performing encoding"""
def encode_additive(self) -> pd.arrays.IntegerArray:
"""Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any alleles are missing Raises ValueError if there is more t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncodingMixin:
"""Genotype Mixin containing functions for performing encoding"""
def encode_additive(self) -> pd.arrays.IntegerArray:
"""Returns ------- pd.arrays.IntegerArray Number of copies of the minor allele pd.NA when any alleles are missing Raises ValueError if there is more than 1 alterna... | the_stack_v2_python_sparse | pandas_genomics/arrays/encoding_mixin.py | adbmd/pandas-genomics | train | 0 |
c73e3b8a572c638085919b3aefd202c99b489de8 | [
"try:\n return cls._CODE_MAP[code]\nexcept KeyError as err:\n raise ValueError(f\"Cannot find a region for the code '{code}'\") from err",
"if cls._current_region is None:\n raise ValueError('You must set the active region with `set_region()` before it can be accessed')\nreturn cls._current_region",
"t... | <|body_start_0|>
try:
return cls._CODE_MAP[code]
except KeyError as err:
raise ValueError(f"Cannot find a region for the code '{code}'") from err
<|end_body_0|>
<|body_start_1|>
if cls._current_region is None:
raise ValueError('You must set the active region ... | A collection of all the regions as an enum like object. | Regions | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Regions:
"""A collection of all the regions as an enum like object."""
def from_code(cls, code: str) -> Region:
"""Get a region object based on its code. :raises ValueError: If no valid region can be found."""
<|body_0|>
def get_region(cls) -> Region:
"""Get the ... | stack_v2_sparse_classes_36k_train_028306 | 2,395 | permissive | [
{
"docstring": "Get a region object based on its code. :raises ValueError: If no valid region can be found.",
"name": "from_code",
"signature": "def from_code(cls, code: str) -> Region"
},
{
"docstring": "Get the region this app is running in. :raises ValueError: If the active region has not bee... | 3 | stack_v2_sparse_classes_30k_train_002729 | Implement the Python class `Regions` described below.
Class description:
A collection of all the regions as an enum like object.
Method signatures and docstrings:
- def from_code(cls, code: str) -> Region: Get a region object based on its code. :raises ValueError: If no valid region can be found.
- def get_region(cls... | Implement the Python class `Regions` described below.
Class description:
A collection of all the regions as an enum like object.
Method signatures and docstrings:
- def from_code(cls, code: str) -> Region: Get a region object based on its code. :raises ValueError: If no valid region can be found.
- def get_region(cls... | 86614d8fe690ca52516fef87bfffe9e61dd2c21f | <|skeleton|>
class Regions:
"""A collection of all the regions as an enum like object."""
def from_code(cls, code: str) -> Region:
"""Get a region object based on its code. :raises ValueError: If no valid region can be found."""
<|body_0|>
def get_region(cls) -> Region:
"""Get the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Regions:
"""A collection of all the regions as an enum like object."""
def from_code(cls, code: str) -> Region:
"""Get a region object based on its code. :raises ValueError: If no valid region can be found."""
try:
return cls._CODE_MAP[code]
except KeyError as err:
... | the_stack_v2_python_sparse | lms/models/region.py | hypothesis/lms | train | 44 |
800e89db03c0091e696d9ee58a97ffd90de94cbb | [
"if isinstance(key, int):\n return TransType(key)\nif key not in TransType._member_map_:\n extend_enum(TransType, key, default)\nreturn TransType[key]",
"if not (isinstance(value, int) and 0 <= value <= 255):\n raise ValueError('%r is not a valid %s' % (value, cls.__name__))\nif 144 <= value <= 252:\n ... | <|body_start_0|>
if isinstance(key, int):
return TransType(key)
if key not in TransType._member_map_:
extend_enum(TransType, key, default)
return TransType[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and 0 <= value <= 255):
rai... | [TransType] Transport Layer Protocol Numbers | TransType | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransType:
"""[TransType] Transport Layer Protocol Numbers"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_028307 | 13,924 | permissive | [
{
"docstring": "Backport support for original codes.",
"name": "get",
"signature": "def get(key, default=-1)"
},
{
"docstring": "Lookup function used when value is not found.",
"name": "_missing_",
"signature": "def _missing_(cls, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001483 | Implement the Python class `TransType` described below.
Class description:
[TransType] Transport Layer Protocol Numbers
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found. | Implement the Python class `TransType` described below.
Class description:
[TransType] Transport Layer Protocol Numbers
Method signatures and docstrings:
- def get(key, default=-1): Backport support for original codes.
- def _missing_(cls, value): Lookup function used when value is not found.
<|skeleton|>
class Tran... | 71363d7948003fec88cedcf5bc80b6befa2ba244 | <|skeleton|>
class TransType:
"""[TransType] Transport Layer Protocol Numbers"""
def get(key, default=-1):
"""Backport support for original codes."""
<|body_0|>
def _missing_(cls, value):
"""Lookup function used when value is not found."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransType:
"""[TransType] Transport Layer Protocol Numbers"""
def get(key, default=-1):
"""Backport support for original codes."""
if isinstance(key, int):
return TransType(key)
if key not in TransType._member_map_:
extend_enum(TransType, key, default)
... | the_stack_v2_python_sparse | pcapkit/const/reg/transtype.py | hiok2000/PyPCAPKit | train | 0 |
0066c5bdefb2b716e3202f0c1b809dbbd2eebe69 | [
"self.name = name\nself.time_zone = time_zone\nself.tags = tags\nself.disable_my_meraki_com = disable_my_meraki_com\nself.disable_remote_status_page = disable_remote_status_page\nself.enrollment_string = enrollment_string",
"if dictionary is None:\n return None\nname = dictionary.get('name')\ntime_zone = dicti... | <|body_start_0|>
self.name = name
self.time_zone = time_zone
self.tags = tags
self.disable_my_meraki_com = disable_my_meraki_com
self.disable_remote_status_page = disable_remote_status_page
self.enrollment_string = enrollment_string
<|end_body_0|>
<|body_start_1|>
... | Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' column in the table in <a target='_blank' href='https://en.wikipedia.org/wiki/List_of_t... | UpdateNetworkModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkModel:
"""Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' column in the table in <a target='_blank'... | stack_v2_sparse_classes_36k_train_028308 | 3,938 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkModel class",
"name": "__init__",
"signature": "def __init__(self, name=None, time_zone=None, tags=None, disable_my_meraki_com=None, disable_remote_status_page=None, enrollment_string=None)"
},
{
"docstring": "Creates an instance of this model fro... | 2 | stack_v2_sparse_classes_30k_train_012876 | Implement the Python class `UpdateNetworkModel` described below.
Class description:
Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' co... | Implement the Python class `UpdateNetworkModel` described below.
Class description:
Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' co... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkModel:
"""Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' column in the table in <a target='_blank'... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNetworkModel:
"""Implementation of the 'updateNetwork' model. TODO: type model description here. Attributes: name (string): The name of the network time_zone (string): The timezone of the network. For a list of allowed timezones, please see the 'TZ' column in the table in <a target='_blank' href='https:... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
1303bd42bcca07856cde5011e0d5af7d052a9990 | [
"if n <= 0:\n return False\nfrom math import log10\nreturn log10(n) / log10(3) % 1 == 0",
"if n <= 0:\n return False\nwhile n % 3 == 0:\n n /= 3\nreturn n == 1"
] | <|body_start_0|>
if n <= 0:
return False
from math import log10
return log10(n) / log10(3) % 1 == 0
<|end_body_0|>
<|body_start_1|>
if n <= 0:
return False
while n % 3 == 0:
n /= 3
return n == 1
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfThree(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOfThreeLoop(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n <= 0:
return False
from math imp... | stack_v2_sparse_classes_36k_train_028309 | 581 | no_license | [
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOfThree",
"signature": "def isPowerOfThree(self, n)"
},
{
"docstring": ":type n: int :rtype: bool",
"name": "isPowerOfThreeLoop",
"signature": "def isPowerOfThreeLoop(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfThree(self, n): :type n: int :rtype: bool
- def isPowerOfThreeLoop(self, n): :type n: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfThree(self, n): :type n: int :rtype: bool
- def isPowerOfThreeLoop(self, n): :type n: int :rtype: bool
<|skeleton|>
class Solution:
def isPowerOfThree(self, n)... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def isPowerOfThree(self, n):
""":type n: int :rtype: bool"""
<|body_0|>
def isPowerOfThreeLoop(self, n):
""":type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPowerOfThree(self, n):
""":type n: int :rtype: bool"""
if n <= 0:
return False
from math import log10
return log10(n) / log10(3) % 1 == 0
def isPowerOfThreeLoop(self, n):
""":type n: int :rtype: bool"""
if n <= 0:
ret... | the_stack_v2_python_sparse | top_interview_questions/easy_collection/math/power_of_three.py | hwc1824/LeetCodeSolution | train | 0 | |
0ed90a57827aad9dfb9f88ec422ed420451b0db5 | [
"cwd = os.path.join(os.path.dirname(__file__), config.vosk_model_dir)\nself.model = Model(cwd)\nlogger.info(f'Loaded speech recognition model from {cwd}')",
"logger.info(f'Recognising speech for {file_name}')\nwf = wave.open(file_name, 'rb')\nif wf.getnchannels() != 1 or wf.getsampwidth() != 2 or wf.getcomptype()... | <|body_start_0|>
cwd = os.path.join(os.path.dirname(__file__), config.vosk_model_dir)
self.model = Model(cwd)
logger.info(f'Loaded speech recognition model from {cwd}')
<|end_body_0|>
<|body_start_1|>
logger.info(f'Recognising speech for {file_name}')
wf = wave.open(file_name, '... | Simple class that uses Vosk to process a file for speech recognition | SpeechRecogniser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpeechRecogniser:
"""Simple class that uses Vosk to process a file for speech recognition"""
def __init__(self):
"""Set the log level and load the Vosk model"""
<|body_0|>
def process_file(self, file_name):
"""Run the Vosk model on the input file :param file_name... | stack_v2_sparse_classes_36k_train_028310 | 2,478 | permissive | [
{
"docstring": "Set the log level and load the Vosk model",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run the Vosk model on the input file :param file_name: Input wav or mp3 file :return: List of dictionaries containing: confidence, start time, end time and the pre... | 2 | stack_v2_sparse_classes_30k_train_005970 | Implement the Python class `SpeechRecogniser` described below.
Class description:
Simple class that uses Vosk to process a file for speech recognition
Method signatures and docstrings:
- def __init__(self): Set the log level and load the Vosk model
- def process_file(self, file_name): Run the Vosk model on the input ... | Implement the Python class `SpeechRecogniser` described below.
Class description:
Simple class that uses Vosk to process a file for speech recognition
Method signatures and docstrings:
- def __init__(self): Set the log level and load the Vosk model
- def process_file(self, file_name): Run the Vosk model on the input ... | 4252835bc69ecb54e6d0e0af49f2e77c76fd78ad | <|skeleton|>
class SpeechRecogniser:
"""Simple class that uses Vosk to process a file for speech recognition"""
def __init__(self):
"""Set the log level and load the Vosk model"""
<|body_0|>
def process_file(self, file_name):
"""Run the Vosk model on the input file :param file_name... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpeechRecogniser:
"""Simple class that uses Vosk to process a file for speech recognition"""
def __init__(self):
"""Set the log level and load the Vosk model"""
cwd = os.path.join(os.path.dirname(__file__), config.vosk_model_dir)
self.model = Model(cwd)
logger.info(f'Loade... | the_stack_v2_python_sparse | audio_pipeline/audio_speech/speech_recogniser.py | AlexWimpory/video-caption | train | 0 |
4ebf219bc008ea2b78be25e85304eed2c65ba740 | [
"x = tf.expand_dims(x, axis=0)\ny = tf.expand_dims(y, axis=0)\nself.assertEqual(tf.size(tf.sets.difference(x, y)), 0, msg='Input sets are not equal.')\nself.assertEqual(tf.size(tf.sets.difference(y, x)), 0, msg='Input sets are not equal.')",
"histogram_x = dict(zip(x_keys.numpy(), x_values.numpy()))\nhistogram_y ... | <|body_start_0|>
x = tf.expand_dims(x, axis=0)
y = tf.expand_dims(y, axis=0)
self.assertEqual(tf.size(tf.sets.difference(x, y)), 0, msg='Input sets are not equal.')
self.assertEqual(tf.size(tf.sets.difference(y, x)), 0, msg='Input sets are not equal.')
<|end_body_0|>
<|body_start_1|>
... | TestCase for Heavy Hitters. | HeavyHittersTest | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HeavyHittersTest:
"""TestCase for Heavy Hitters."""
def assertSetAllEqual(self, x, y):
"""Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y: A 1D tf.string Raises: ValueError: If x and y are diffe... | stack_v2_sparse_classes_36k_train_028311 | 2,180 | permissive | [
{
"docstring": "Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y: A 1D tf.string Raises: ValueError: If x and y are different sets.",
"name": "assertSetAllEqual",
"signature": "def assertSetAllEqual(self, x, y)"
}... | 2 | null | Implement the Python class `HeavyHittersTest` described below.
Class description:
TestCase for Heavy Hitters.
Method signatures and docstrings:
- def assertSetAllEqual(self, x, y): Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y... | Implement the Python class `HeavyHittersTest` described below.
Class description:
TestCase for Heavy Hitters.
Method signatures and docstrings:
- def assertSetAllEqual(self, x, y): Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y... | 329e60fa56b87f691303638ceb9dfa1fc5083953 | <|skeleton|>
class HeavyHittersTest:
"""TestCase for Heavy Hitters."""
def assertSetAllEqual(self, x, y):
"""Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y: A 1D tf.string Raises: ValueError: If x and y are diffe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HeavyHittersTest:
"""TestCase for Heavy Hitters."""
def assertSetAllEqual(self, x, y):
"""Assert two tensor lists contain the same set of items. Allow items to be in different order in these two lists. Args: x: A 1D tf.string y: A 1D tf.string Raises: ValueError: If x and y are different sets."""... | the_stack_v2_python_sparse | analytics/heavy_hitters/heavy_hitters_testcase.py | google-research/federated | train | 595 |
ace67e84967a2df346a06ca8869c0ee1e0261187 | [
"super().__init__()\nself.set_XY = set_XY\nself.set_H = set_H\nself.set_D = set_D",
"ovars = []\nif self.set_XY:\n ovars.append(FV.X)\n ovars.append(FV.Y)\nif self.set_H:\n ovars.append(FV.H)\nif self.set_D:\n ovars.append(FV.D)\nreturn ovars",
"n_states = mdata.n_states\nn_turbines = algo.n_turbine... | <|body_start_0|>
super().__init__()
self.set_XY = set_XY
self.set_H = set_H
self.set_D = set_D
<|end_body_0|>
<|body_start_1|>
ovars = []
if self.set_XY:
ovars.append(FV.X)
ovars.append(FV.Y)
if self.set_H:
ovars.append(FV.H)
... | Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models | SetXYHD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SetXYHD:
"""Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models"""
def __init__(self, set_XY=True, set_H=True, set_D=True):
... | stack_v2_sparse_classes_36k_train_028312 | 3,492 | permissive | [
{
"docstring": "Constructor. Parameters ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data",
"name": "__init__",
"signature": "def __init__(self, set_XY=True, set_H=True, set_D=True)"
},
{
"docstring": "The variables which are be... | 3 | stack_v2_sparse_classes_30k_train_005883 | Implement the Python class `SetXYHD` described below.
Class description:
Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models
Method signatures and docst... | Implement the Python class `SetXYHD` described below.
Class description:
Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models
Method signatures and docst... | 65b01a4d33c40065d1b19900d8238b173700653c | <|skeleton|>
class SetXYHD:
"""Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models"""
def __init__(self, set_XY=True, set_H=True, set_D=True):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SetXYHD:
"""Sets basic turbine data, from turbine object to farm data. Attributes ---------- set_XY: bool Flag for (x,y) data set_H: bool Flag for height data set_D: bool Flag for rotor diameter data :group: models.turbine_models"""
def __init__(self, set_XY=True, set_H=True, set_D=True):
"""Cons... | the_stack_v2_python_sparse | foxes/models/turbine_models/set_XYHD.py | FraunhoferIWES/foxes | train | 14 |
d499169c3009524d5e7b99176cbdbdeb6839757b | [
"if not metric_name:\n raise KeyError(\"'metric_name' parameter is required\")\nreturn super(Metadata, cls).get(metric_name)",
"if not metric_name:\n raise KeyError(\"'metric_name' parameter is required\")\nreturn super(Metadata, cls).update(id=metric_name, **params)"
] | <|body_start_0|>
if not metric_name:
raise KeyError("'metric_name' parameter is required")
return super(Metadata, cls).get(metric_name)
<|end_body_0|>
<|body_start_1|>
if not metric_name:
raise KeyError("'metric_name' parameter is required")
return super(Metadata... | A wrapper around Metric Metadata HTTP API | Metadata | [
"Apache-2.0",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Metadata:
"""A wrapper around Metric Metadata HTTP API"""
def get(cls, metric_name):
"""Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representing the API's JSON response"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_028313 | 2,290 | permissive | [
{
"docstring": "Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representing the API's JSON response",
"name": "get",
"signature": "def get(cls, metric_name)"
},
{
"docstring": "Update metadata fields for an existin... | 2 | null | Implement the Python class `Metadata` described below.
Class description:
A wrapper around Metric Metadata HTTP API
Method signatures and docstrings:
- def get(cls, metric_name): Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representi... | Implement the Python class `Metadata` described below.
Class description:
A wrapper around Metric Metadata HTTP API
Method signatures and docstrings:
- def get(cls, metric_name): Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representi... | 11a38d0c8d6b156758e7500500d706b7159d18ed | <|skeleton|>
class Metadata:
"""A wrapper around Metric Metadata HTTP API"""
def get(cls, metric_name):
"""Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representing the API's JSON response"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Metadata:
"""A wrapper around Metric Metadata HTTP API"""
def get(cls, metric_name):
"""Get metadata information on an existing Datadog metric param metric_name: metric name (ex. system.cpu.idle) :returns: Dictionary representing the API's JSON response"""
if not metric_name:
... | the_stack_v2_python_sparse | datadog/api/metadata.py | DataDog/datadogpy | train | 602 |
4a486f329c9014947d1ac47a6f97bb47e9b11bf8 | [
"from pytz import timezone\nfrom os import environ\nconfig = TraderBase.get_config()\ntry:\n return timezone(config['autotrader']['time_zone'])\nexcept (configparser.NoSectionError, configparser.NoOptionError, KeyError, TypeError):\n if environ.get('TZ') is not None:\n return timezone(os.environ['TZ'])... | <|body_start_0|>
from pytz import timezone
from os import environ
config = TraderBase.get_config()
try:
return timezone(config['autotrader']['time_zone'])
except (configparser.NoSectionError, configparser.NoOptionError, KeyError, TypeError):
if environ.get... | Helper class for logging and config parsing | TraderBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TraderBase:
"""Helper class for logging and config parsing"""
def get_timezone():
"""Return configured timezone or europe berlin as default :return:"""
<|body_0|>
def setup_logger(name: str):
"""Setup the autotrader standard logger :param name: name of logger :re... | stack_v2_sparse_classes_36k_train_028314 | 2,924 | no_license | [
{
"docstring": "Return configured timezone or europe berlin as default :return:",
"name": "get_timezone",
"signature": "def get_timezone()"
},
{
"docstring": "Setup the autotrader standard logger :param name: name of logger :return: instance of logger",
"name": "setup_logger",
"signature... | 3 | null | Implement the Python class `TraderBase` described below.
Class description:
Helper class for logging and config parsing
Method signatures and docstrings:
- def get_timezone(): Return configured timezone or europe berlin as default :return:
- def setup_logger(name: str): Setup the autotrader standard logger :param nam... | Implement the Python class `TraderBase` described below.
Class description:
Helper class for logging and config parsing
Method signatures and docstrings:
- def get_timezone(): Return configured timezone or europe berlin as default :return:
- def setup_logger(name: str): Setup the autotrader standard logger :param nam... | a2b486d5941dbee01272c49e6e63e289edcf9966 | <|skeleton|>
class TraderBase:
"""Helper class for logging and config parsing"""
def get_timezone():
"""Return configured timezone or europe berlin as default :return:"""
<|body_0|>
def setup_logger(name: str):
"""Setup the autotrader standard logger :param name: name of logger :re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TraderBase:
"""Helper class for logging and config parsing"""
def get_timezone():
"""Return configured timezone or europe berlin as default :return:"""
from pytz import timezone
from os import environ
config = TraderBase.get_config()
try:
return timezon... | the_stack_v2_python_sparse | autotrader/base/trader_base.py | SlashGordon/autotrader | train | 1 |
93150c9d103e72dec26b3936ef4bb6ac93591dac | [
"self.regularization = regularization\nself.clip_margin = clip_margin\nself.pano_pad = pano_pad\nself.spline_degree = spline_degree",
"aligned_results = bspline_warp(thetas, image, self.spline_degree, regularization=self.regularization, pano_pad=self.pano_pad)\nif self.pano_pad:\n clipped_results = aligned_res... | <|body_start_0|>
self.regularization = regularization
self.clip_margin = clip_margin
self.pano_pad = pano_pad
self.spline_degree = spline_degree
<|end_body_0|>
<|body_start_1|>
aligned_results = bspline_warp(thetas, image, self.spline_degree, regularization=self.regularization, ... | A class for aligning a set of images using bspline warps. | ImageAlignment | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageAlignment:
"""A class for aligning a set of images using bspline warps."""
def __init__(self, regularization=0.3, clip_margin=32, pano_pad=True, spline_degree=3):
"""Initializes a layer that warp images based on alignment parameters. Args: regularization: (float): A regularizati... | stack_v2_sparse_classes_36k_train_028315 | 10,152 | permissive | [
{
"docstring": "Initializes a layer that warp images based on alignment parameters. Args: regularization: (float): A regularization, ranging from [0, 1], for alignment control points clip_margin (int): For non-panoramic padding dimensions, controls how many edge pixels to crop. Useful for removing warping artif... | 2 | null | Implement the Python class `ImageAlignment` described below.
Class description:
A class for aligning a set of images using bspline warps.
Method signatures and docstrings:
- def __init__(self, regularization=0.3, clip_margin=32, pano_pad=True, spline_degree=3): Initializes a layer that warp images based on alignment ... | Implement the Python class `ImageAlignment` described below.
Class description:
A class for aligning a set of images using bspline warps.
Method signatures and docstrings:
- def __init__(self, regularization=0.3, clip_margin=32, pano_pad=True, spline_degree=3): Initializes a layer that warp images based on alignment ... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ImageAlignment:
"""A class for aligning a set of images using bspline warps."""
def __init__(self, regularization=0.3, clip_margin=32, pano_pad=True, spline_degree=3):
"""Initializes a layer that warp images based on alignment parameters. Args: regularization: (float): A regularizati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageAlignment:
"""A class for aligning a set of images using bspline warps."""
def __init__(self, regularization=0.3, clip_margin=32, pano_pad=True, spline_degree=3):
"""Initializes a layer that warp images based on alignment parameters. Args: regularization: (float): A regularization, ranging f... | the_stack_v2_python_sparse | factorize_a_city/libs/image_alignment.py | Jimmy-INL/google-research | train | 1 |
57051fc750b20da7b5ba99135a2ae2881bc00d26 | [
"filepath = cls._convert_filepath(filepath)\nif filepath.suffix == '.pdb':\n return cls._from_pdb_file(filepath)\nelse:\n raise ValueError(f'The {format} format is not supported or invalid.')",
"parser = PDBParser()\nstructure = parser.get_structure('', pdb_file)\nreturn structure"
] | <|body_start_0|>
filepath = cls._convert_filepath(filepath)
if filepath.suffix == '.pdb':
return cls._from_pdb_file(filepath)
else:
raise ValueError(f'The {format} format is not supported or invalid.')
<|end_body_0|>
<|body_start_1|>
parser = PDBParser()
... | Parse a structure as a biopython structure object. | Biopython | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Biopython:
"""Parse a structure as a biopython structure object."""
def from_file(cls, filepath):
"""Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structure file: pdb files only. Returns ------- Bio.PDB.Structure... | stack_v2_sparse_classes_36k_train_028316 | 1,330 | permissive | [
{
"docstring": "Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structure file: pdb files only. Returns ------- Bio.PDB.Structure.Structure Structure as biopython structure object.",
"name": "from_file",
"signature": "def from_file(cl... | 2 | stack_v2_sparse_classes_30k_train_003733 | Implement the Python class `Biopython` described below.
Class description:
Parse a structure as a biopython structure object.
Method signatures and docstrings:
- def from_file(cls, filepath): Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structur... | Implement the Python class `Biopython` described below.
Class description:
Parse a structure as a biopython structure object.
Method signatures and docstrings:
- def from_file(cls, filepath): Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structur... | c76e87c4fdcb822dfc025e6cb87c34c9e17505d2 | <|skeleton|>
class Biopython:
"""Parse a structure as a biopython structure object."""
def from_file(cls, filepath):
"""Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structure file: pdb files only. Returns ------- Bio.PDB.Structure... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Biopython:
"""Parse a structure as a biopython structure object."""
def from_file(cls, filepath):
"""Load structures as biopython structure object from file. Parameters ---------- filepath : str or pathlib.Path Path to structure file: pdb files only. Returns ------- Bio.PDB.Structure.Structure St... | the_stack_v2_python_sparse | opencadd/io/biopython.py | volkamerlab/opencadd | train | 62 |
23050faaaaca4daad88eb1029b3ac34fd2f90920 | [
"attribution_key = metrics_for_slice_pb2.AttributionsKey()\nif self.name:\n attribution_key.name = self.name\nif self.model_name:\n attribution_key.model_name = self.model_name\nif self.output_name:\n attribution_key.output_name = self.output_name\nif self.sub_key:\n attribution_key.sub_key.CopyFrom(sel... | <|body_start_0|>
attribution_key = metrics_for_slice_pb2.AttributionsKey()
if self.name:
attribution_key.name = self.name
if self.model_name:
attribution_key.model_name = self.model_name
if self.output_name:
attribution_key.output_name = self.output_na... | An AttributionsKey is a metric key uniquely identifying attributions. | AttributionsKey | [
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'AttributionsKey... | stack_v2_sparse_classes_36k_train_028317 | 44,385 | permissive | [
{
"docstring": "Converts key to proto.",
"name": "to_proto",
"signature": "def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey"
},
{
"docstring": "Configures class from proto.",
"name": "from_proto",
"signature": "def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'Attr... | 2 | stack_v2_sparse_classes_30k_train_000533 | Implement the Python class `AttributionsKey` described below.
Class description:
An AttributionsKey is a metric key uniquely identifying attributions.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.Attr... | Implement the Python class `AttributionsKey` described below.
Class description:
An AttributionsKey is a metric key uniquely identifying attributions.
Method signatures and docstrings:
- def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey: Converts key to proto.
- def from_proto(pb: metrics_for_slice_pb2.Attr... | ee0d8eff562bfe068a3ffdc4da0472cc90adaf41 | <|skeleton|>
class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
<|body_0|>
def from_proto(pb: metrics_for_slice_pb2.AttributionsKey) -> 'AttributionsKey... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttributionsKey:
"""An AttributionsKey is a metric key uniquely identifying attributions."""
def to_proto(self) -> metrics_for_slice_pb2.AttributionsKey:
"""Converts key to proto."""
attribution_key = metrics_for_slice_pb2.AttributionsKey()
if self.name:
attribution_ke... | the_stack_v2_python_sparse | tensorflow_model_analysis/metrics/metric_types.py | tensorflow/model-analysis | train | 1,200 |
18fbd2fd25c60e0dcfcf90fcab7a2a0d7434493b | [
"self.name = None\nself.training_data = None\nself.test_data = None\nself.entities = None\nself.features_dim = features_dim\nself.feat_normalize = normalize\nself.target_transform = target_transform",
"if self.feat_normalize:\n for i in range(len(self.entities)):\n if isspmatrix_csr(self.entities[i]):\n... | <|body_start_0|>
self.name = None
self.training_data = None
self.test_data = None
self.entities = None
self.features_dim = features_dim
self.feat_normalize = normalize
self.target_transform = target_transform
<|end_body_0|>
<|body_start_1|>
if self.feat_n... | Base class that holds necessary (minimal) information needed | Dataset | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Base class that holds necessary (minimal) information needed"""
def __init__(self, name, features_dim=0, normalize=False, target_transform=''):
"""Initialize parameters Args: name (str): Name of the dataset features_dim (uint): Dimension of the features. If not 0, PCA is ... | stack_v2_sparse_classes_36k_train_028318 | 8,650 | permissive | [
{
"docstring": "Initialize parameters Args: name (str): Name of the dataset features_dim (uint): Dimension of the features. If not 0, PCA is performed on the features as the dimensionality reduction technique normalize (bool): Normalize the features target_transform (str): Transform the target values. Current o... | 4 | stack_v2_sparse_classes_30k_train_016496 | Implement the Python class `Dataset` described below.
Class description:
Base class that holds necessary (minimal) information needed
Method signatures and docstrings:
- def __init__(self, name, features_dim=0, normalize=False, target_transform=''): Initialize parameters Args: name (str): Name of the dataset features... | Implement the Python class `Dataset` described below.
Class description:
Base class that holds necessary (minimal) information needed
Method signatures and docstrings:
- def __init__(self, name, features_dim=0, normalize=False, target_transform=''): Initialize parameters Args: name (str): Name of the dataset features... | 787ae309ec78a9b2b1f58931931cb117affc4ea9 | <|skeleton|>
class Dataset:
"""Base class that holds necessary (minimal) information needed"""
def __init__(self, name, features_dim=0, normalize=False, target_transform=''):
"""Initialize parameters Args: name (str): Name of the dataset features_dim (uint): Dimension of the features. If not 0, PCA is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""Base class that holds necessary (minimal) information needed"""
def __init__(self, name, features_dim=0, normalize=False, target_transform=''):
"""Initialize parameters Args: name (str): Name of the dataset features_dim (uint): Dimension of the features. If not 0, PCA is performed on ... | the_stack_v2_python_sparse | recommenders/models/geoimc/geoimc_data.py | DaniBunny/recommenders | train | 1 |
e0c3d7ae4f53489584f7a75333680534438cc5c1 | [
"self.grid_r = r - 1\nself.grid_c = c - 1\nself.stop_cells = set(stop_cells)",
"path = [(0, 0)]\nwent_right: set = set()\nwent_down: set = set()\nr = 0\nc = 0\nwhile (r, c) != (self.grid_r, self.grid_c):\n if c < self.grid_c and (r, c) not in went_right and ((r, c + 1) not in self.stop_cells):\n went_ri... | <|body_start_0|>
self.grid_r = r - 1
self.grid_c = c - 1
self.stop_cells = set(stop_cells)
<|end_body_0|>
<|body_start_1|>
path = [(0, 0)]
went_right: set = set()
went_down: set = set()
r = 0
c = 0
while (r, c) != (self.grid_r, self.grid_c):
... | 8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. Design an algorithm to find a path for the robot from the top left to the bottom... | RobotInAGrid | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobotInAGrid:
"""8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. Design an algorithm to find a path for t... | stack_v2_sparse_classes_36k_train_028319 | 1,849 | no_license | [
{
"docstring": ":param r: rows in a grid :param c: cells in a grid",
"name": "__init__",
"signature": "def __init__(self, stop_cells, r, c)"
},
{
"docstring": "Algorithm to find a path for the robot from the top left to the bottom right. Algo: step right, if not possible, step left, if not possi... | 2 | null | Implement the Python class `RobotInAGrid` described below.
Class description:
8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. D... | Implement the Python class `RobotInAGrid` described below.
Class description:
8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. D... | 8ae84f276cd07ffdb9b742569a5e32809ecc6b29 | <|skeleton|>
class RobotInAGrid:
"""8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. Design an algorithm to find a path for t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RobotInAGrid:
"""8.2 Robot in a Grid: Imagine a robot sitting on the upper left corner of grid with r rows and c columns. The robot can only move in two directions, right and down, but certain cells are "off limits" such that the robot cannot step on them. Design an algorithm to find a path for the robot from... | the_stack_v2_python_sparse | pyquiz/ctci/dynamic/RobotInAGrid.py | DmitryPukhov/pyquiz | train | 0 |
461d39a26047af0f700a58e6cd1c317e7ce41d00 | [
"header = json.dumps({'typ': 'JWT', 'alg': 'BLK2B'}).encode('utf-8')\nhenc = base58.b58encode_check(header).decode()\npayload = json.dumps(data).encode('utf-8')\npenc = base58.b58encode_check(payload).decode()\nhdata = henc + '.' + penc\nd = hmac.new(key, hdata.encode('utf-8'), digestmod=hashlib.blake2b)\ndig = d.d... | <|body_start_0|>
header = json.dumps({'typ': 'JWT', 'alg': 'BLK2B'}).encode('utf-8')
henc = base58.b58encode_check(header).decode()
payload = json.dumps(data).encode('utf-8')
penc = base58.b58encode_check(payload).decode()
hdata = henc + '.' + penc
d = hmac.new(key, hdata... | JWT | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JWT:
def create_signed_token(cls, key, data):
"""Create a complete JWT token. Exclusively uses blake2b HMAC."""
<|body_0|>
def verify_signed_token(cls, key, token):
"""Decodes the payload in the token and returns a tuple whose first value is a boolean indicating whet... | stack_v2_sparse_classes_36k_train_028320 | 2,771 | permissive | [
{
"docstring": "Create a complete JWT token. Exclusively uses blake2b HMAC.",
"name": "create_signed_token",
"signature": "def create_signed_token(cls, key, data)"
},
{
"docstring": "Decodes the payload in the token and returns a tuple whose first value is a boolean indicating whether the signat... | 2 | stack_v2_sparse_classes_30k_train_002679 | Implement the Python class `JWT` described below.
Class description:
Implement the JWT class.
Method signatures and docstrings:
- def create_signed_token(cls, key, data): Create a complete JWT token. Exclusively uses blake2b HMAC.
- def verify_signed_token(cls, key, token): Decodes the payload in the token and return... | Implement the Python class `JWT` described below.
Class description:
Implement the JWT class.
Method signatures and docstrings:
- def create_signed_token(cls, key, data): Create a complete JWT token. Exclusively uses blake2b HMAC.
- def verify_signed_token(cls, key, token): Decodes the payload in the token and return... | 94597af5ab5736bdb995a97b3bc65182ca38ee51 | <|skeleton|>
class JWT:
def create_signed_token(cls, key, data):
"""Create a complete JWT token. Exclusively uses blake2b HMAC."""
<|body_0|>
def verify_signed_token(cls, key, token):
"""Decodes the payload in the token and returns a tuple whose first value is a boolean indicating whet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JWT:
def create_signed_token(cls, key, data):
"""Create a complete JWT token. Exclusively uses blake2b HMAC."""
header = json.dumps({'typ': 'JWT', 'alg': 'BLK2B'}).encode('utf-8')
henc = base58.b58encode_check(header).decode()
payload = json.dumps(data).encode('utf-8')
... | the_stack_v2_python_sparse | hikka/auth.py | obasys/hikka | train | 0 | |
eddb444106c21e612a6e829d685c52c95d96f67b | [
"super(BinaryRealIndividual, self).__init__(genes, parent, statistic)\nself._phenome = None\nif isinstance(parent, BinaryRealIndividual):\n self.bits_per_value = parent.bits_per_value\n self.lowest = parent.lowest\n self.highest = parent.highest\n self.encoding = parent.encoding\nelse:\n self.bits_pe... | <|body_start_0|>
super(BinaryRealIndividual, self).__init__(genes, parent, statistic)
self._phenome = None
if isinstance(parent, BinaryRealIndividual):
self.bits_per_value = parent.bits_per_value
self.lowest = parent.lowest
self.highest = parent.highest
... | An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled. | BinaryRealIndividual | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryRealIndividual:
"""An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled."""
def __init__(self, genes, parent, bits_per_value=None, lowest=0.0, highest=1.0, encoding=None, statistic=None):
""... | stack_v2_sparse_classes_36k_train_028321 | 14,844 | permissive | [
{
"docstring": "Initialises a new individual. :Parameters: genes : iterable The sequence of genes that make up the new individual. parent : `BinaryRealIndividual` or `BinarySpecies` Either the `BinaryRealIndividual` that was used to generate the new individual, or the `BinarySpecies` descriptor that defines the... | 3 | stack_v2_sparse_classes_30k_train_019187 | Implement the Python class `BinaryRealIndividual` described below.
Class description:
An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled.
Method signatures and docstrings:
- def __init__(self, genes, parent, bits_per_value=None,... | Implement the Python class `BinaryRealIndividual` described below.
Class description:
An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled.
Method signatures and docstrings:
- def __init__(self, genes, parent, bits_per_value=None,... | c1c64237697115ea3137bc854c0dfdf8b456b0dd | <|skeleton|>
class BinaryRealIndividual:
"""An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled."""
def __init__(self, genes, parent, bits_per_value=None, lowest=0.0, highest=1.0, encoding=None, statistic=None):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryRealIndividual:
"""An `Individual` for binary-valued genomes and real-valued phenomes. Binary values are grouped into real-valued parameters, summed and scaled."""
def __init__(self, genes, parent, bits_per_value=None, lowest=0.0, highest=1.0, encoding=None, statistic=None):
"""Initialises ... | the_stack_v2_python_sparse | esec/esec/species/binary_real.py | zooba/esec | train | 1 |
2dfffcb5c5ea916feaf1a1825dba6e8e4ca68d37 | [
"self.assertTrue(utils.IsSubclass(int, int))\nself.assertTrue(utils.IsSubclass(bool, int))\nself.assertTrue(utils.IsSubclass(str, (str, basestring)))\nself.assertFalse(utils.IsSubclass(int, bool))\nself.assertFalse(utils.IsSubclass(int, None))",
"self.assertRaises(AttributeError, utils._DictToTuple, None)\n\nclas... | <|body_start_0|>
self.assertTrue(utils.IsSubclass(int, int))
self.assertTrue(utils.IsSubclass(bool, int))
self.assertTrue(utils.IsSubclass(str, (str, basestring)))
self.assertFalse(utils.IsSubclass(int, bool))
self.assertFalse(utils.IsSubclass(int, None))
<|end_body_0|>
<|body_s... | Comprehensive test for the endpoints_proto_datastore.utils module. | UtilsTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UtilsTests:
"""Comprehensive test for the endpoints_proto_datastore.utils module."""
def testIsSubclass(self):
"""Tests the utils.IsSubclass method."""
<|body_0|>
def testDictToTuple(self):
"""Tests the utils._DictToTuple method."""
<|body_1|>
def te... | stack_v2_sparse_classes_36k_train_028322 | 2,058 | permissive | [
{
"docstring": "Tests the utils.IsSubclass method.",
"name": "testIsSubclass",
"signature": "def testIsSubclass(self)"
},
{
"docstring": "Tests the utils._DictToTuple method.",
"name": "testDictToTuple",
"signature": "def testDictToTuple(self)"
},
{
"docstring": "Tests the utils.... | 3 | stack_v2_sparse_classes_30k_train_008351 | Implement the Python class `UtilsTests` described below.
Class description:
Comprehensive test for the endpoints_proto_datastore.utils module.
Method signatures and docstrings:
- def testIsSubclass(self): Tests the utils.IsSubclass method.
- def testDictToTuple(self): Tests the utils._DictToTuple method.
- def testGe... | Implement the Python class `UtilsTests` described below.
Class description:
Comprehensive test for the endpoints_proto_datastore.utils module.
Method signatures and docstrings:
- def testIsSubclass(self): Tests the utils.IsSubclass method.
- def testDictToTuple(self): Tests the utils._DictToTuple method.
- def testGe... | 37e0136ab61a99a8cd25ef264c2d5f8f024e8f6f | <|skeleton|>
class UtilsTests:
"""Comprehensive test for the endpoints_proto_datastore.utils module."""
def testIsSubclass(self):
"""Tests the utils.IsSubclass method."""
<|body_0|>
def testDictToTuple(self):
"""Tests the utils._DictToTuple method."""
<|body_1|>
def te... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UtilsTests:
"""Comprehensive test for the endpoints_proto_datastore.utils module."""
def testIsSubclass(self):
"""Tests the utils.IsSubclass method."""
self.assertTrue(utils.IsSubclass(int, int))
self.assertTrue(utils.IsSubclass(bool, int))
self.assertTrue(utils.IsSubclass... | the_stack_v2_python_sparse | lib/endpoints_proto_datastore/utils_test.py | uetopia/metagame | train | 2 |
091df8021a7aefc4e82ee59844e89e232a859dac | [
"if k <= 1:\n return 0\nprod = 1\nans = left = 0\nfor right, val in enumerate(nums):\n prod *= val\n while prod >= k:\n prod /= nums[left]\n left += 1\n ans += right - left + 1\nreturn ans",
"count = 0\nlast = 0\nfor i in range(len(nums)):\n if nums[i] >= k:\n last = i\n ... | <|body_start_0|>
if k <= 1:
return 0
prod = 1
ans = left = 0
for right, val in enumerate(nums):
prod *= val
while prod >= k:
prod /= nums[left]
left += 1
ans += right - left + 1
return ans
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def numSubarrayProductLessThanK0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_028323 | 1,743 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "numSubarrayProductLessThanK",
"signature": "def numSubarrayProductLessThanK(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "numSubarrayProductLessThanK0",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_011647 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def numSubarrayProductLessThanK0(self, nums, k): :type nums: List[int] :type k: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSubarrayProductLessThanK(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def numSubarrayProductLessThanK0(self, nums, k): :type nums: List[int] :type k: i... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def numSubarrayProductLessThanK0(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numSubarrayProductLessThanK(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
if k <= 1:
return 0
prod = 1
ans = left = 0
for right, val in enumerate(nums):
prod *= val
while prod >= k:
... | the_stack_v2_python_sparse | 剑指 Offer II 009. 乘积小于 K 的子数组.py | yangyuxiang1996/leetcode | train | 0 | |
575b7c659222099eae5f4e14803230830ac607d1 | [
"attribute_list = ['task_type', 'api_id', 'db_host', 'db_port', 'genapi_version', 'log_level', 'entities', 'api_key']\nself.config = config\nsuper(DeployTask, self).__init__(message, attribute_list, config)",
"self.task_type = self.get_task_type()\nself.api_id = self.message['api_id']\nself.db_host = self.message... | <|body_start_0|>
attribute_list = ['task_type', 'api_id', 'db_host', 'db_port', 'genapi_version', 'log_level', 'entities', 'api_key']
self.config = config
super(DeployTask, self).__init__(message, attribute_list, config)
<|end_body_0|>
<|body_start_1|>
self.task_type = self.get_task_typ... | Deploy task definition | DeployTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployTask:
"""Deploy task definition"""
def __init__(self, message, config):
"""Initialize the Deploy task"""
<|body_0|>
def parse_parameters(self):
"""Read out all parameters needed to run the deploy task { “task_type”: ”DEPLOY”, “api_id”: “88sdhv98shdvlh123”, ... | stack_v2_sparse_classes_36k_train_028324 | 3,395 | no_license | [
{
"docstring": "Initialize the Deploy task",
"name": "__init__",
"signature": "def __init__(self, message, config)"
},
{
"docstring": "Read out all parameters needed to run the deploy task { “task_type”: ”DEPLOY”, “api_id”: “88sdhv98shdvlh123”, “db_host”: “db1.apitrary.net”, “db_port”: 8098, “ge... | 4 | stack_v2_sparse_classes_30k_train_008302 | Implement the Python class `DeployTask` described below.
Class description:
Deploy task definition
Method signatures and docstrings:
- def __init__(self, message, config): Initialize the Deploy task
- def parse_parameters(self): Read out all parameters needed to run the deploy task { “task_type”: ”DEPLOY”, “api_id”: ... | Implement the Python class `DeployTask` described below.
Class description:
Deploy task definition
Method signatures and docstrings:
- def __init__(self, message, config): Initialize the Deploy task
- def parse_parameters(self): Read out all parameters needed to run the deploy task { “task_type”: ”DEPLOY”, “api_id”: ... | 5f45763782a68d1ed755166c4f6bb2e62e7735b6 | <|skeleton|>
class DeployTask:
"""Deploy task definition"""
def __init__(self, message, config):
"""Initialize the Deploy task"""
<|body_0|>
def parse_parameters(self):
"""Read out all parameters needed to run the deploy task { “task_type”: ”DEPLOY”, “api_id”: “88sdhv98shdvlh123”, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeployTask:
"""Deploy task definition"""
def __init__(self, message, config):
"""Initialize the Deploy task"""
attribute_list = ['task_type', 'api_id', 'db_host', 'db_port', 'genapi_version', 'log_level', 'entities', 'api_key']
self.config = config
super(DeployTask, self).... | the_stack_v2_python_sparse | deployr/app_deployr/models/deploy_task.py | otype/deployr | train | 0 |
6263c5241b349ad0bdb2c225fa8c3f058aa31070 | [
"response = self.client.get('/products/')\nself.assertEqual(response.status_code, 302)\nself.assertEqual(response.url, '/accounts/login/?next=/products/')",
"response = self.client.get('/products/Pints/')\nself.assertEqual(response.status_code, 302)\nself.assertEqual(response.url, '/accounts/login/?next=/products... | <|body_start_0|>
response = self.client.get('/products/')
self.assertEqual(response.status_code, 302)
self.assertEqual(response.url, '/accounts/login/?next=/products/')
<|end_body_0|>
<|body_start_1|>
response = self.client.get('/products/Pints/')
self.assertEqual(response.statu... | Test for cart view when user is logged out | TestProductViewsLoggedOut | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestProductViewsLoggedOut:
"""Test for cart view when user is logged out"""
def test_all_products_view_logged_out(self):
"""Check that the all products view redirects to login page when logged out"""
<|body_0|>
def test_filtered_products_view_logged_out(self):
""... | stack_v2_sparse_classes_36k_train_028325 | 2,945 | no_license | [
{
"docstring": "Check that the all products view redirects to login page when logged out",
"name": "test_all_products_view_logged_out",
"signature": "def test_all_products_view_logged_out(self)"
},
{
"docstring": "Check that the filter products views redirects to login page when logged out",
... | 3 | null | Implement the Python class `TestProductViewsLoggedOut` described below.
Class description:
Test for cart view when user is logged out
Method signatures and docstrings:
- def test_all_products_view_logged_out(self): Check that the all products view redirects to login page when logged out
- def test_filtered_products_v... | Implement the Python class `TestProductViewsLoggedOut` described below.
Class description:
Test for cart view when user is logged out
Method signatures and docstrings:
- def test_all_products_view_logged_out(self): Check that the all products view redirects to login page when logged out
- def test_filtered_products_v... | e052a6f95566322b95cc41a3dfd730e382a6863e | <|skeleton|>
class TestProductViewsLoggedOut:
"""Test for cart view when user is logged out"""
def test_all_products_view_logged_out(self):
"""Check that the all products view redirects to login page when logged out"""
<|body_0|>
def test_filtered_products_view_logged_out(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestProductViewsLoggedOut:
"""Test for cart view when user is logged out"""
def test_all_products_view_logged_out(self):
"""Check that the all products view redirects to login page when logged out"""
response = self.client.get('/products/')
self.assertEqual(response.status_code, 3... | the_stack_v2_python_sparse | products/test_views.py | Code-Institute-Submissions/milestone-project-84 | train | 0 |
641545540bcfb7496d5a8ce06bae2ef61738eee0 | [
"tp = type(e)\ntb = e.__traceback__\ntraceback_str = 'Traceback (most recent call last):\\n' + ''.join(traceback.format_tb(tb))\ntry:\n attributes = e.get_attributes()\nexcept AttributeError:\n attributes = {}\nreturn (tp.__name__, traceback_str, sy.serde.msgpack.serde._simplify(worker, attributes))",
"erro... | <|body_start_0|>
tp = type(e)
tb = e.__traceback__
traceback_str = 'Traceback (most recent call last):\n' + ''.join(traceback.format_tb(tb))
try:
attributes = e.get_attributes()
except AttributeError:
attributes = {}
return (tp.__name__, traceback_... | Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high | SendNotPermittedError | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forwa... | stack_v2_sparse_classes_36k_train_028326 | 15,166 | permissive | [
{
"docstring": "Serialize information about an Exception which was raised to forward it",
"name": "simplify",
"signature": "def simplify(worker: 'sy.workers.AbstractWorker', e)"
},
{
"docstring": "Detail and re-raise an Exception forwarded by another worker",
"name": "detail",
"signature... | 2 | stack_v2_sparse_classes_30k_train_018627 | Implement the Python class `SendNotPermittedError` described below.
Class description:
Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high
Method signatures and docstrings:
- def simplify(worker: 'sy.workers.AbstractWorker', e): Serialize... | Implement the Python class `SendNotPermittedError` described below.
Class description:
Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high
Method signatures and docstrings:
- def simplify(worker: 'sy.workers.AbstractWorker', e): Serialize... | cc4765bed880ad38a02505834f63df39e0815328 | <|skeleton|>
class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forwa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SendNotPermittedError:
"""Raised when calling send on a tensor which does not allow send to be called on it. This can happen do to sensitivity being too high"""
def simplify(worker: 'sy.workers.AbstractWorker', e):
"""Serialize information about an Exception which was raised to forward it"""
... | the_stack_v2_python_sparse | syft/exceptions.py | tudorcebere/PySyft | train | 2 |
c67919208ded41ded5abcfa37a400f4eef24a42f | [
"language_list = lq.get_languages()\nif not language_list:\n logging.debug('Empty language list')\n return self.bad_response('Internal error')\nres = [{'id': language.id, 'language': language.name} for language in language_list]\nreturn self.success_response({'languages': res})",
"data = request.get_json()\... | <|body_start_0|>
language_list = lq.get_languages()
if not language_list:
logging.debug('Empty language list')
return self.bad_response('Internal error')
res = [{'id': language.id, 'language': language.name} for language in language_list]
return self.success_respo... | LanguageHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LanguageHandler:
def get(self):
"""Get language list."""
<|body_0|>
def post(self):
"""{ 'name': str }"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
language_list = lq.get_languages()
if not language_list:
logging.debug('Empty ... | stack_v2_sparse_classes_36k_train_028327 | 1,015 | no_license | [
{
"docstring": "Get language list.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "{ 'name': str }",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000709 | Implement the Python class `LanguageHandler` described below.
Class description:
Implement the LanguageHandler class.
Method signatures and docstrings:
- def get(self): Get language list.
- def post(self): { 'name': str } | Implement the Python class `LanguageHandler` described below.
Class description:
Implement the LanguageHandler class.
Method signatures and docstrings:
- def get(self): Get language list.
- def post(self): { 'name': str }
<|skeleton|>
class LanguageHandler:
def get(self):
"""Get language list."""
... | 8d3dfc06e0738e3e9547604d421788b4145fd971 | <|skeleton|>
class LanguageHandler:
def get(self):
"""Get language list."""
<|body_0|>
def post(self):
"""{ 'name': str }"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LanguageHandler:
def get(self):
"""Get language list."""
language_list = lq.get_languages()
if not language_list:
logging.debug('Empty language list')
return self.bad_response('Internal error')
res = [{'id': language.id, 'language': language.name} for la... | the_stack_v2_python_sparse | app/handlers/language.py | AleksandrFrolov/BackofficeSS | train | 0 | |
ca33239d16e723674ac0b47248a63a19bb204b7c | [
"self.redshift = redshift\nself.light_profile_list = light_profile_list\nself.mass_profile_list = mass_profile_list",
"if self.light_profile_list is not None:\n return sum(map(lambda p: p.image_from_grid(grid=grid), self.light_profile_list))\nreturn np.zeros((grid.shape[0],))",
"if self.mass_profile_list is ... | <|body_start_0|>
self.redshift = redshift
self.light_profile_list = light_profile_list
self.mass_profile_list = mass_profile_list
<|end_body_0|>
<|body_start_1|>
if self.light_profile_list is not None:
return sum(map(lambda p: p.image_from_grid(grid=grid), self.light_profile... | Galaxy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list ... | stack_v2_sparse_classes_36k_train_028328 | 2,345 | no_license | [
{
"docstring": "A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list of the galaxy's light profiles. mass_profile_list A list of the galaxy's mass profiles.",
"name": "__init__",
"signature": "def _... | 3 | null | Implement the Python class `Galaxy` described below.
Class description:
Implement the Galaxy class.
Method signatures and docstrings:
- def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None): A galaxy, which contains light and mass profiles at a specified ... | Implement the Python class `Galaxy` described below.
Class description:
Implement the Galaxy class.
Method signatures and docstrings:
- def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None): A galaxy, which contains light and mass profiles at a specified ... | ac76dfef4643189a130ce18d23070bb81272a93c | <|skeleton|>
class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list of the galaxy'... | the_stack_v2_python_sparse | projects/cosmology/src/galaxy.py | Jammy2211/autofit_workspace | train | 6 | |
2f7970d4837197811056d4adc87a2ee3ed1fe5af | [
"try:\n wiki = Wiki.objects.get(slug=slug)\nexcept Wiki.DoesNotExist:\n error_msg = 'Wiki not found.'\n return api_error(status.HTTP_404_NOT_FOUND, error_msg)\nif not wiki.has_read_perm(request.user):\n error_msg = 'Permission denied.'\n return api_error(status.HTTP_403_FORBIDDEN, error_msg)\npage_na... | <|body_start_0|>
try:
wiki = Wiki.objects.get(slug=slug)
except Wiki.DoesNotExist:
error_msg = 'Wiki not found.'
return api_error(status.HTTP_404_NOT_FOUND, error_msg)
if not wiki.has_read_perm(request.user):
error_msg = 'Permission denied.'
... | WikiPageView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WikiPageView:
def get(self, request, slug, page_name='home'):
"""Get content of a wiki"""
<|body_0|>
def delete(self, request, slug, page_name):
"""Delete a page in a wiki"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
wiki = Wiki.... | stack_v2_sparse_classes_36k_train_028329 | 12,107 | permissive | [
{
"docstring": "Get content of a wiki",
"name": "get",
"signature": "def get(self, request, slug, page_name='home')"
},
{
"docstring": "Delete a page in a wiki",
"name": "delete",
"signature": "def delete(self, request, slug, page_name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015225 | Implement the Python class `WikiPageView` described below.
Class description:
Implement the WikiPageView class.
Method signatures and docstrings:
- def get(self, request, slug, page_name='home'): Get content of a wiki
- def delete(self, request, slug, page_name): Delete a page in a wiki | Implement the Python class `WikiPageView` described below.
Class description:
Implement the WikiPageView class.
Method signatures and docstrings:
- def get(self, request, slug, page_name='home'): Get content of a wiki
- def delete(self, request, slug, page_name): Delete a page in a wiki
<|skeleton|>
class WikiPageVi... | 13b3ed26a04248211ef91ca70dccc617be27a3c3 | <|skeleton|>
class WikiPageView:
def get(self, request, slug, page_name='home'):
"""Get content of a wiki"""
<|body_0|>
def delete(self, request, slug, page_name):
"""Delete a page in a wiki"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WikiPageView:
def get(self, request, slug, page_name='home'):
"""Get content of a wiki"""
try:
wiki = Wiki.objects.get(slug=slug)
except Wiki.DoesNotExist:
error_msg = 'Wiki not found.'
return api_error(status.HTTP_404_NOT_FOUND, error_msg)
i... | the_stack_v2_python_sparse | fhs/usr/share/python/syncwerk/restapi/restapi/api2/endpoints/wiki_pages.py | syncwerk/syncwerk-server-restapi | train | 0 | |
d3a431c151d605c82207c6d0c44b1be4ae25cd0d | [
"super(CreateAdcNodeObjects, self).__init__(*args, **kwargs)\nself.node_count = node_count\nself.bigip = bigip\nself.object_counter = 0\nself.context = ContextHelper(__name__)\nself.cfgifc = self.context.get_config()\nself.ip_gen = ipv4_address_generator()",
"LOG.info('Creating {0} node(s) in the BigIQ working co... | <|body_start_0|>
super(CreateAdcNodeObjects, self).__init__(*args, **kwargs)
self.node_count = node_count
self.bigip = bigip
self.object_counter = 0
self.context = ContextHelper(__name__)
self.cfgifc = self.context.get_config()
self.ip_gen = ipv4_address_generator... | Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call. | CreateAdcNodeObjects | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateAdcNodeObjects:
"""Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call."""
def __init__(self, node_count, bigip, *args, **kwargs):... | stack_v2_sparse_classes_36k_train_028330 | 15,401 | permissive | [
{
"docstring": "Object initialization. @param node_count: The number of ADC nodes to create. @param bigip: BIG-IP device, as returned by MachineIdResolver.",
"name": "__init__",
"signature": "def __init__(self, node_count, bigip, *args, **kwargs)"
},
{
"docstring": "Generate the specified number... | 2 | null | Implement the Python class `CreateAdcNodeObjects` described below.
Class description:
Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call.
Method signatures and d... | Implement the Python class `CreateAdcNodeObjects` described below.
Class description:
Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call.
Method signatures and d... | 40264ac83b3f1d2a30ebc1107927044f42c86f8a | <|skeleton|>
class CreateAdcNodeObjects:
"""Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call."""
def __init__(self, node_count, bigip, *args, **kwargs):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateAdcNodeObjects:
"""Create the specified number of ADC Node objects on the BIG-IQ for the specified BIG-IP. Works for BIG-IQ 4.6.0 and later. You must deploy the ADC objects from the BIG-IQ to the BIG-IP(s) with a separate call."""
def __init__(self, node_count, bigip, *args, **kwargs):
"""O... | the_stack_v2_python_sparse | f5test/commands/rest/adc.py | jonozzz/nosest | train | 1 |
ab95cd39abb438207791303ed82eea174967422e | [
"self.master = master\nself.model = HomeModel()\nisReady = self.model.doesScaleExist()\nself.view = HomeView(master, self, isReady, ImageTk.PhotoImage(file='LogoImg.png'))\nself.view.pack(expand=YES, fill=BOTH)",
"self.view.destroy()\nfrom contoursController import ContoursController\nContoursController(self.mast... | <|body_start_0|>
self.master = master
self.model = HomeModel()
isReady = self.model.doesScaleExist()
self.view = HomeView(master, self, isReady, ImageTk.PhotoImage(file='LogoImg.png'))
self.view.pack(expand=YES, fill=BOTH)
<|end_body_0|>
<|body_start_1|>
self.view.destro... | HomeController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HomeController:
def __init__(self, master):
"""The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: master(Tk object): The toplevel widget of Tk which is the main window of an application"""
<|body_0... | stack_v2_sparse_classes_36k_train_028331 | 1,161 | no_license | [
{
"docstring": "The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: master(Tk object): The toplevel widget of Tk which is the main window of an application",
"name": "__init__",
"signature": "def __init__(self, master)"
... | 3 | stack_v2_sparse_classes_30k_train_013533 | Implement the Python class `HomeController` described below.
Class description:
Implement the HomeController class.
Method signatures and docstrings:
- def __init__(self, master): The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: mast... | Implement the Python class `HomeController` described below.
Class description:
Implement the HomeController class.
Method signatures and docstrings:
- def __init__(self, master): The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: mast... | e448c450f6792dbc96e61d7ae4869d27e9e82632 | <|skeleton|>
class HomeController:
def __init__(self, master):
"""The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: master(Tk object): The toplevel widget of Tk which is the main window of an application"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HomeController:
def __init__(self, master):
"""The HomeController if there is no config file will not allow the user to start export, but only to calibrate the various models Args: master(Tk object): The toplevel widget of Tk which is the main window of an application"""
self.master = master
... | the_stack_v2_python_sparse | src/GUI/homeController.py | LaserSaver/LaserSaver | train | 0 | |
7e2642811b17392adf07f375f495fd57aeb24639 | [
"super().__init__()\nself.name: str = name\nself.params: dict = data",
"if self.params == {}:\n return {self.name: None}\nreturn {self.name: self.params}"
] | <|body_start_0|>
super().__init__()
self.name: str = name
self.params: dict = data
<|end_body_0|>
<|body_start_1|>
if self.params == {}:
return {self.name: None}
return {self.name: self.params}
<|end_body_1|>
| Configuration Dataset class. | Dataset | [
"MIT",
"Intel",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Configuration Dataset class."""
def __init__(self, name: str, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataset class."""
<|body_0|>
def serialize(self, serialization_type: str='default') -> Dict[str, Any]:
"""Serialize Dataset cla... | stack_v2_sparse_classes_36k_train_028332 | 4,560 | permissive | [
{
"docstring": "Initialize Configuration Dataset class.",
"name": "__init__",
"signature": "def __init__(self, name: str, data: Dict[str, Any]={}) -> None"
},
{
"docstring": "Serialize Dataset class.",
"name": "serialize",
"signature": "def serialize(self, serialization_type: str='defaul... | 2 | stack_v2_sparse_classes_30k_train_013923 | Implement the Python class `Dataset` described below.
Class description:
Configuration Dataset class.
Method signatures and docstrings:
- def __init__(self, name: str, data: Dict[str, Any]={}) -> None: Initialize Configuration Dataset class.
- def serialize(self, serialization_type: str='default') -> Dict[str, Any]: ... | Implement the Python class `Dataset` described below.
Class description:
Configuration Dataset class.
Method signatures and docstrings:
- def __init__(self, name: str, data: Dict[str, Any]={}) -> None: Initialize Configuration Dataset class.
- def serialize(self, serialization_type: str='default') -> Dict[str, Any]: ... | 3976edc4215398e69ce0213f87ec295f5dc96e0e | <|skeleton|>
class Dataset:
"""Configuration Dataset class."""
def __init__(self, name: str, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataset class."""
<|body_0|>
def serialize(self, serialization_type: str='default') -> Dict[str, Any]:
"""Serialize Dataset cla... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""Configuration Dataset class."""
def __init__(self, name: str, data: Dict[str, Any]={}) -> None:
"""Initialize Configuration Dataset class."""
super().__init__()
self.name: str = name
self.params: dict = data
def serialize(self, serialization_type: str='def... | the_stack_v2_python_sparse | neural_compressor/ux/utils/workload/dataloader.py | Skp80/neural-compressor | train | 0 |
79ea7de4905de49fc1800aec10e44906f9dd73de | [
"for i in range(n_of_tests):\n result = rb.random_color(300)\n self.assertEqual((300, 300, 3), np.shape(result))\n for color in result:\n for line in color:\n for value in line:\n self.assertTrue(value >= 0 and value <= 1.0)",
"for i in range(n_of_tests):\n result = rb... | <|body_start_0|>
for i in range(n_of_tests):
result = rb.random_color(300)
self.assertEqual((300, 300, 3), np.shape(result))
for color in result:
for line in color:
for value in line:
self.assertTrue(value >= 0 and v... | TestResizeImages | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestResizeImages:
def test_random_color(self):
"""Tests that returns a L*L*3 array of values between 0 and1"""
<|body_0|>
def test_random_image(self):
"""Test random_image by checking that the resultant image is size*size*3 array of values between 0 and 2? for now, O... | stack_v2_sparse_classes_36k_train_028333 | 4,020 | permissive | [
{
"docstring": "Tests that returns a L*L*3 array of values between 0 and1",
"name": "test_random_color",
"signature": "def test_random_color(self)"
},
{
"docstring": "Test random_image by checking that the resultant image is size*size*3 array of values between 0 and 2? for now, Ong will solve th... | 5 | null | Implement the Python class `TestResizeImages` described below.
Class description:
Implement the TestResizeImages class.
Method signatures and docstrings:
- def test_random_color(self): Tests that returns a L*L*3 array of values between 0 and1
- def test_random_image(self): Test random_image by checking that the resul... | Implement the Python class `TestResizeImages` described below.
Class description:
Implement the TestResizeImages class.
Method signatures and docstrings:
- def test_random_color(self): Tests that returns a L*L*3 array of values between 0 and1
- def test_random_image(self): Test random_image by checking that the resul... | 73bd44509da3442f0538968fd6f012e14bd2b2c8 | <|skeleton|>
class TestResizeImages:
def test_random_color(self):
"""Tests that returns a L*L*3 array of values between 0 and1"""
<|body_0|>
def test_random_image(self):
"""Test random_image by checking that the resultant image is size*size*3 array of values between 0 and 2? for now, O... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestResizeImages:
def test_random_color(self):
"""Tests that returns a L*L*3 array of values between 0 and1"""
for i in range(n_of_tests):
result = rb.random_color(300)
self.assertEqual((300, 300, 3), np.shape(result))
for color in result:
fo... | the_stack_v2_python_sparse | src/rendering/TestRandomLib/TestRandBack.py | mforcexvi/3D-DL | train | 3 | |
99d4ca8e0e3a1e13e230611864ef6a98dac4c1a6 | [
"inSpec = super(SampleSelector, cls).getInputSpecification()\ninSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringType))\ncriterion = InputData.parameterInputFactory('criterion', contentType=InputTypes.StringType, strictMode=True)\ncriterion.addParam('value', InputTypes.IntegerType)... | <|body_start_0|>
inSpec = super(SampleSelector, cls).getInputSpecification()
inSpec.addSub(InputData.parameterInputFactory('target', contentType=InputTypes.StringType))
criterion = InputData.parameterInputFactory('criterion', contentType=InputTypes.StringType, strictMode=True)
criterion.... | This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return. | SampleSelector | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the ... | stack_v2_sparse_classes_36k_train_028334 | 5,362 | permissive | [
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls.",
"name": "getInputSpecification",
"signatur... | 6 | stack_v2_sparse_classes_30k_train_003526 | Implement the Python class `SampleSelector` described below.
Class description:
This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return.
Method signatures and docstrings:
- def getInputSpecification(cls):... | Implement the Python class `SampleSelector` described below.
Class description:
This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return.
Method signatures and docstrings:
- def getInputSpecification(cls):... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SampleSelector:
"""This postprocessor selects the row in which the minimum or the maximum of a target is found.The postprocessor can act on DataObject, and generates a DataObject in return."""
def getInputSpecification(cls):
"""Method to get a reference to a class that specifies the input data fo... | the_stack_v2_python_sparse | ravenframework/Models/PostProcessors/SampleSelector.py | idaholab/raven | train | 201 |
2bf09c4b10b379fe92623329e28a49ef56a739cb | [
"if verbose:\n print(base_object_query)\nrecord_index = start_record\nresult = run_object_query(self.client, base_object_query, record_index, limit_to, verbose)\nobj_search_result = result['body']['ExecuteMSQLResult']['ResultValue']['ObjectSearchResult']\nif obj_search_result is not None:\n search_results = o... | <|body_start_0|>
if verbose:
print(base_object_query)
record_index = start_record
result = run_object_query(self.client, base_object_query, record_index, limit_to, verbose)
obj_search_result = result['body']['ExecuteMSQLResult']['ResultValue']['ObjectSearchResult']
if... | A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests. | ChunkQueryMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChunkQueryMixin:
"""A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests."""
def get_long_query(self, base_object_... | stack_v2_sparse_classes_36k_train_028335 | 4,089 | permissive | [
{
"docstring": "Takes a base query for all objects and recursively requests them :param str base_object_query: the base query to be executed :param int limit_to: how many rows to query for in each chunk :param int max_calls: the max calls(chunks to request) None is infinite :param int start_record: the first re... | 2 | stack_v2_sparse_classes_30k_train_016823 | Implement the Python class `ChunkQueryMixin` described below.
Class description:
A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests.
Metho... | Implement the Python class `ChunkQueryMixin` described below.
Class description:
A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests.
Metho... | 221f5ed8bc7d4424237a4669c5af9edc11819ee9 | <|skeleton|>
class ChunkQueryMixin:
"""A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests."""
def get_long_query(self, base_object_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChunkQueryMixin:
"""A mixin for API client service classes that makes it easy to consistently request multiple queries from a MemberSuite endpoint. Membersuite will often time out on big queries, so this allows us to break it up into smaller requests."""
def get_long_query(self, base_object_query, limit_... | the_stack_v2_python_sparse | membersuite_api_client/mixins.py | rerb/python-membersuite-api-client | train | 0 |
a3fbdbbd0a271444bc64277451b26f429a8aa77b | [
"if not isinstance(args[0], PolarDiagram):\n super().plot(*args, **kwargs)\n return\npd = args[0]\nlabels, slices, info = pd.get_slices(ws, n_steps, full_info=True)\n_configure_axes(self, labels, colors, show_legend, legend_kw, **kwargs)\n_plot(self, slices, info, False, use_convex_hull, **kwargs)",
"if not... | <|body_start_0|>
if not isinstance(args[0], PolarDiagram):
super().plot(*args, **kwargs)
return
pd = args[0]
labels, slices, info = pd.get_slices(ws, n_steps, full_info=True)
_configure_axes(self, labels, colors, show_legend, legend_kw, **kwargs)
_plot(sel... | Projection to plot given data in a rectilinear plot. | HROFlat | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HROFlat:
"""Projection to plot given data in a rectilinear plot."""
def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False, **kwargs):
"""Plots the given data in a rectilinear plot. Otherwise, it works identical ... | stack_v2_sparse_classes_36k_train_028336 | 23,221 | permissive | [
{
"docstring": "Plots the given data in a rectilinear plot. Otherwise, it works identical to `HROPolar.plot`. See also ---------- `HROPolar.plot`",
"name": "plot",
"signature": "def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False... | 2 | stack_v2_sparse_classes_30k_train_001477 | Implement the Python class `HROFlat` described below.
Class description:
Projection to plot given data in a rectilinear plot.
Method signatures and docstrings:
- def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False, **kwargs): Plots the given d... | Implement the Python class `HROFlat` described below.
Class description:
Projection to plot given data in a rectilinear plot.
Method signatures and docstrings:
- def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False, **kwargs): Plots the given d... | 921536e2db7a9635c539a8dc2a97d1411e58c2a1 | <|skeleton|>
class HROFlat:
"""Projection to plot given data in a rectilinear plot."""
def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False, **kwargs):
"""Plots the given data in a rectilinear plot. Otherwise, it works identical ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HROFlat:
"""Projection to plot given data in a rectilinear plot."""
def plot(self, *args, ws=None, n_steps=None, colors=('green', 'red'), show_legend=False, legend_kw=None, use_convex_hull=False, **kwargs):
"""Plots the given data in a rectilinear plot. Otherwise, it works identical to `HROPolar.... | the_stack_v2_python_sparse | hrosailing/plotting/projections.py | hrosailing/hrosailing | train | 17 |
6451bfd1032ed71f60c4806b847ec5462c0ddcb4 | [
"\"\"\"\n Recall \"count smaller number after self\" where we encountered the problem\n\n count[i] = count of nums[j] - nums[i] < 0 with j > i\n \n Here, after we preprocessed the array, we need to solve the problem\n\n count[i] = count of a <= S[j] - S[i] <= b with j > i\n ... | <|body_start_0|>
"""
Recall "count smaller number after self" where we encountered the problem
count[i] = count of nums[j] - nums[i] < 0 with j > i
Here, after we preprocessed the array, we need to solve the problem
count[i] = count of a <= S[j]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countRangeSum(self, nums, lower, upper):
""":type nums: List[int] :type lower: int :type upper: int :rtype: int"""
<|body_0|>
def countRangeSumBIT(self, nums, lower, upper):
""":type nums: List[int] :type lower: int :type upper: int :rtype: int"""
... | stack_v2_sparse_classes_36k_train_028337 | 3,778 | no_license | [
{
"docstring": ":type nums: List[int] :type lower: int :type upper: int :rtype: int",
"name": "countRangeSum",
"signature": "def countRangeSum(self, nums, lower, upper)"
},
{
"docstring": ":type nums: List[int] :type lower: int :type upper: int :rtype: int",
"name": "countRangeSumBIT",
"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countRangeSum(self, nums, lower, upper): :type nums: List[int] :type lower: int :type upper: int :rtype: int
- def countRangeSumBIT(self, nums, lower, upper): :type nums: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countRangeSum(self, nums, lower, upper): :type nums: List[int] :type lower: int :type upper: int :rtype: int
- def countRangeSumBIT(self, nums, lower, upper): :type nums: Lis... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def countRangeSum(self, nums, lower, upper):
""":type nums: List[int] :type lower: int :type upper: int :rtype: int"""
<|body_0|>
def countRangeSumBIT(self, nums, lower, upper):
""":type nums: List[int] :type lower: int :type upper: int :rtype: int"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countRangeSum(self, nums, lower, upper):
""":type nums: List[int] :type lower: int :type upper: int :rtype: int"""
"""
Recall "count smaller number after self" where we encountered the problem
count[i] = count of nums[j] - nums[i] < 0 with j > i
... | the_stack_v2_python_sparse | C/CountofRangeSum.py | bssrdf/pyleet | train | 2 | |
13a2825e1dba546a69beb6a2cda328345ef71920 | [
"n = len(nums)\nif n * k == 0:\n return []\nreturn [max(nums[i:i + k]) for i in range(n - k + 1)]",
"size = len(nums)\nif size * k == 0:\n return []\nif size == 1:\n return nums\nqueue, output, max_idx = (deque(), [], 0)\n\ndef clean_up(index: int):\n if queue and queue[0] == index - k:\n queue... | <|body_start_0|>
n = len(nums)
if n * k == 0:
return []
return [max(nums[i:i + k]) for i in range(n - k + 1)]
<|end_body_0|>
<|body_start_1|>
size = len(nums)
if size * k == 0:
return []
if size == 1:
return nums
queue, output,... | SlidingWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
<|body_0|>
def get_max_in_window_(self, nums: List[int], k: int) -> List[int]:
... | stack_v2_sparse_classes_36k_train_028338 | 2,981 | no_license | [
{
"docstring": "Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:",
"name": "get_max_in_window__",
"signature": "def get_max_in_window__(self, nums: List[int], k: int) -> List[int]"
},
{
"docstring": "Approach: Using Deque Time Complexity: O(N) Spa... | 3 | stack_v2_sparse_classes_30k_train_018054 | Implement the Python class `SlidingWindow` described below.
Class description:
Implement the SlidingWindow class.
Method signatures and docstrings:
- def get_max_in_window__(self, nums: List[int], k: int) -> List[int]: Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:
-... | Implement the Python class `SlidingWindow` described below.
Class description:
Implement the SlidingWindow class.
Method signatures and docstrings:
- def get_max_in_window__(self, nums: List[int], k: int) -> List[int]: Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:
-... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
<|body_0|>
def get_max_in_window_(self, nums: List[int], k: int) -> List[int]:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SlidingWindow:
def get_max_in_window__(self, nums: List[int], k: int) -> List[int]:
"""Approach: Brute Force Time Complexity: O(NK) Space Complexity: O(N - k + 1) :param nums: :return:"""
n = len(nums)
if n * k == 0:
return []
return [max(nums[i:i + k]) for i in ran... | the_stack_v2_python_sparse | revisited/arrays/sliding_window.py | Shiv2157k/leet_code | train | 1 | |
af38cf309f51c557e607a85e57ec13d720223470 | [
"super().__init__(env)\nself._time_delta = 0.1\nself._speed_max = 22.22\nself._dist_max = self._speed_max * self._time_delta",
"limited_actions: Dict[str, np.ndarray] = {}\nfor agent_name, agent_action in action.items():\n limited_actions[agent_name] = self._limit(name=agent_name, action=agent_action)\nout = s... | <|body_start_0|>
super().__init__(env)
self._time_delta = 0.1
self._speed_max = 22.22
self._dist_max = self._speed_max * self._time_delta
<|end_body_0|>
<|body_start_1|>
limited_actions: Dict[str, np.ndarray] = {}
for agent_name, agent_action in action.items():
... | Limits the delta-x and delta-y in the RelativeTargetPose action space. | LimitRelativeTargetPose | [
"LGPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"CC-BY-NC-4.0",
"GPL-1.0-or-later",
"LicenseRef-scancode-generic-exception",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.0-or-later",
"GPL-3.0-or-later",
"BSD-3-Clause",
"MIT",
"LGPL-... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LimitRelativeTargetPose:
"""Limits the delta-x and delta-y in the RelativeTargetPose action space."""
def __init__(self, env: gym.Env):
"""Args: env (gym.Env): Environment to be wrapped."""
<|body_0|>
def step(self, action: Dict[str, np.ndarray]) -> Tuple[Dict[str, Any],... | stack_v2_sparse_classes_36k_train_028339 | 3,732 | permissive | [
{
"docstring": "Args: env (gym.Env): Environment to be wrapped.",
"name": "__init__",
"signature": "def __init__(self, env: gym.Env)"
},
{
"docstring": "Steps the environment. Args: action (Dict[str, np.ndarray]): Action for each agent. Returns: Tuple[ Dict[str, Any], Dict[str, float], Dict[str,... | 3 | stack_v2_sparse_classes_30k_train_001563 | Implement the Python class `LimitRelativeTargetPose` described below.
Class description:
Limits the delta-x and delta-y in the RelativeTargetPose action space.
Method signatures and docstrings:
- def __init__(self, env: gym.Env): Args: env (gym.Env): Environment to be wrapped.
- def step(self, action: Dict[str, np.nd... | Implement the Python class `LimitRelativeTargetPose` described below.
Class description:
Limits the delta-x and delta-y in the RelativeTargetPose action space.
Method signatures and docstrings:
- def __init__(self, env: gym.Env): Args: env (gym.Env): Environment to be wrapped.
- def step(self, action: Dict[str, np.nd... | 2ae8bd76a0b6e4da5699629cec0fefa5aa47ce67 | <|skeleton|>
class LimitRelativeTargetPose:
"""Limits the delta-x and delta-y in the RelativeTargetPose action space."""
def __init__(self, env: gym.Env):
"""Args: env (gym.Env): Environment to be wrapped."""
<|body_0|>
def step(self, action: Dict[str, np.ndarray]) -> Tuple[Dict[str, Any],... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LimitRelativeTargetPose:
"""Limits the delta-x and delta-y in the RelativeTargetPose action space."""
def __init__(self, env: gym.Env):
"""Args: env (gym.Env): Environment to be wrapped."""
super().__init__(env)
self._time_delta = 0.1
self._speed_max = 22.22
self._... | the_stack_v2_python_sparse | smarts/env/gymnasium/wrappers/limit_relative_target_pose.py | huawei-noah/SMARTS | train | 824 |
859c02e964d85374daf80a08961b1e9e38f0cd72 | [
"self.target = target\nif config is not None:\n self.config = config\nelse:\n self.config = get_default_session_config()\nself.graph = graph",
"sess = tf.Session(target=self.target, graph=self.graph, config=self.config)\nsess.run(tf.global_variables_initializer())\nsess.run(tf.local_variables_initializer())... | <|body_start_0|>
self.target = target
if config is not None:
self.config = config
else:
self.config = get_default_session_config()
self.graph = graph
<|end_body_0|>
<|body_start_1|>
sess = tf.Session(target=self.target, graph=self.graph, config=self.confi... | tf.train.SessionCreator for a new session | NewSessionCreator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewSessionCreator:
"""tf.train.SessionCreator for a new session"""
def __init__(self, target='', graph=None, config=None):
"""Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init__()`. graph: same as :meth:`tf.Session.__init__()`. confi... | stack_v2_sparse_classes_36k_train_028340 | 2,209 | permissive | [
{
"docstring": "Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init__()`. graph: same as :meth:`tf.Session.__init__()`. config: same as :meth:`tf.Session.__init__()`. Default to :func:`utils.default.get_default_session_config()`.",
"name": "__init__",
"si... | 2 | stack_v2_sparse_classes_30k_train_018629 | Implement the Python class `NewSessionCreator` described below.
Class description:
tf.train.SessionCreator for a new session
Method signatures and docstrings:
- def __init__(self, target='', graph=None, config=None): Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init_... | Implement the Python class `NewSessionCreator` described below.
Class description:
tf.train.SessionCreator for a new session
Method signatures and docstrings:
- def __init__(self, target='', graph=None, config=None): Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init_... | 0ffc81a62eccf021077019fb59b0e9e7615e8222 | <|skeleton|>
class NewSessionCreator:
"""tf.train.SessionCreator for a new session"""
def __init__(self, target='', graph=None, config=None):
"""Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init__()`. graph: same as :meth:`tf.Session.__init__()`. confi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NewSessionCreator:
"""tf.train.SessionCreator for a new session"""
def __init__(self, target='', graph=None, config=None):
"""Inits NewSessionCreator with targe, graph and config. Args: target: same as :meth:`tf.Session.__init__()`. graph: same as :meth:`tf.Session.__init__()`. config: same as :m... | the_stack_v2_python_sparse | tensorcv/utils/sesscreate.py | conan7882/DeepVision-tensorflow | train | 12 |
fdb9af6308e60b7f913135329713a002b28acc66 | [
"elem = deepcopy(elem)\nyld = elem.find('./YIELD')\nif yld is not None:\n yld.tag = 'YLD'\nreturn super(STOCKINFO, STOCKINFO).groom(elem)",
"elem = deepcopy(elem)\nyld = elem.find('./YLD')\nif yld is not None:\n yld.tag = 'YIELD'\nreturn super(STOCKINFO, STOCKINFO).ungroom(elem)"
] | <|body_start_0|>
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(STOCKINFO, STOCKINFO).groom(elem)
<|end_body_0|>
<|body_start_1|>
elem = deepcopy(elem)
yld = elem.find('./YLD')
if yld is not None:
... | OFX Section 13.8.5.6 | STOCKINFO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YLD"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
elem = deepcop... | stack_v2_sparse_classes_36k_train_028341 | 6,031 | no_license | [
{
"docstring": "Rename all Elements tagged YIELD (reserved Python keyword) to YLD",
"name": "groom",
"signature": "def groom(elem)"
},
{
"docstring": "Rename YLD back to YLD",
"name": "ungroom",
"signature": "def ungroom(elem)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009682 | Implement the Python class `STOCKINFO` described below.
Class description:
OFX Section 13.8.5.6
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YLD | Implement the Python class `STOCKINFO` described below.
Class description:
OFX Section 13.8.5.6
Method signatures and docstrings:
- def groom(elem): Rename all Elements tagged YIELD (reserved Python keyword) to YLD
- def ungroom(elem): Rename YLD back to YLD
<|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"... | 67e688ea6510853657736c3804969d029c672c5c | <|skeleton|>
class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
<|body_0|>
def ungroom(elem):
"""Rename YLD back to YLD"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class STOCKINFO:
"""OFX Section 13.8.5.6"""
def groom(elem):
"""Rename all Elements tagged YIELD (reserved Python keyword) to YLD"""
elem = deepcopy(elem)
yld = elem.find('./YIELD')
if yld is not None:
yld.tag = 'YLD'
return super(STOCKINFO, STOCKINFO).groom(... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/ofxtools/models/invest/securities.py | yetaai/batchaccounting | train | 0 |
08469cb65e3316eca0c1ed79ab17d1948690c970 | [
"user = req.context.get('user')\nuser_id = str(user.id)\nuser_dto = user_to_dto(user)\nuser_dto.posts = [post_to_dto(post, href=PostResource.url_to(req.netloc, post_id=post.id)) for post in get_user_posts(user_id)]\nuser_dto.comments = [comment_to_dto(comment, href=CommentResource.url_to(req.netloc, comment_id=comm... | <|body_start_0|>
user = req.context.get('user')
user_id = str(user.id)
user_dto = user_to_dto(user)
user_dto.posts = [post_to_dto(post, href=PostResource.url_to(req.netloc, post_id=post.id)) for post in get_user_posts(user_id)]
user_dto.comments = [comment_to_dto(comment, href=Co... | UserResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserResource:
def on_get(self, req, resp):
"""Fetch user information for current session."""
<|body_0|>
def on_put(self, req, resp):
"""Updates user resource for current session."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = req.context.get... | stack_v2_sparse_classes_36k_train_028342 | 7,736 | permissive | [
{
"docstring": "Fetch user information for current session.",
"name": "on_get",
"signature": "def on_get(self, req, resp)"
},
{
"docstring": "Updates user resource for current session.",
"name": "on_put",
"signature": "def on_put(self, req, resp)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014015 | Implement the Python class `UserResource` described below.
Class description:
Implement the UserResource class.
Method signatures and docstrings:
- def on_get(self, req, resp): Fetch user information for current session.
- def on_put(self, req, resp): Updates user resource for current session. | Implement the Python class `UserResource` described below.
Class description:
Implement the UserResource class.
Method signatures and docstrings:
- def on_get(self, req, resp): Fetch user information for current session.
- def on_put(self, req, resp): Updates user resource for current session.
<|skeleton|>
class Use... | e507fe0307d1a7ea29d6c3e20be62fa82a8f109f | <|skeleton|>
class UserResource:
def on_get(self, req, resp):
"""Fetch user information for current session."""
<|body_0|>
def on_put(self, req, resp):
"""Updates user resource for current session."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserResource:
def on_get(self, req, resp):
"""Fetch user information for current session."""
user = req.context.get('user')
user_id = str(user.id)
user_dto = user_to_dto(user)
user_dto.posts = [post_to_dto(post, href=PostResource.url_to(req.netloc, post_id=post.id)) for... | the_stack_v2_python_sparse | blog/resources/users.py | neetjn/py-blog | train | 0 | |
f278139af34c96ad50ca8e9008ec1b033ff65147 | [
"res = []\nif not root:\n return res\nfrom collections import deque\nqueue = deque()\nqueue.append(root)\nres.append(root.val)\nwhile queue:\n for _ in range(len(queue)):\n node = queue.popleft()\n if node.left:\n queue.append(node.left)\n res.append(node.left.val)\n ... | <|body_start_0|>
res = []
if not root:
return res
from collections import deque
queue = deque()
queue.append(root)
res.append(root.val)
while queue:
for _ in range(len(queue)):
node = queue.popleft()
if node.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_028343 | 1,761 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 2329898b3653802de287434b5facd09636cc92cf | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
res = []
if not root:
return res
from collections import deque
queue = deque()
queue.append(root)
res.append(root.val)
while q... | the_stack_v2_python_sparse | leetcode/二叉树的序列化与反序列化.py | Bubbleskye/2019summer | train | 0 | |
6e830ccb79c876615cbe075dce5643ff4c5ecd96 | [
"budget_line = []\nline_obj = self.env['crossovered.budget.lines']\nfor confirmation in self:\n position = self.env['account.budget.post']._get_budget_position(confirmation.account_id.id)\n if not position:\n raise UserError(_('Confirmation Has no Budget Position!'))\n else:\n budget_line = l... | <|body_start_0|>
budget_line = []
line_obj = self.env['crossovered.budget.lines']
for confirmation in self:
position = self.env['account.budget.post']._get_budget_position(confirmation.account_id.id)
if not position:
raise UserError(_('Confirmation Has no ... | Inherit to overwrite workflow mothods to reflect confirmation state in voucher line | AccountBudgetConfirmationInvoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountBudgetConfirmationInvoice:
"""Inherit to overwrite workflow mothods to reflect confirmation state in voucher line"""
def check_budget_invoice(self):
"""This method check whether the budget line residual allow to validate this confirmation or not @return: boolean True if budget... | stack_v2_sparse_classes_36k_train_028344 | 25,644 | no_license | [
{
"docstring": "This method check whether the budget line residual allow to validate this confirmation or not @return: boolean True if budget line residual more that confirm amount, or False",
"name": "check_budget_invoice",
"signature": "def check_budget_invoice(self)"
},
{
"docstring": "overwr... | 4 | stack_v2_sparse_classes_30k_train_008147 | Implement the Python class `AccountBudgetConfirmationInvoice` described below.
Class description:
Inherit to overwrite workflow mothods to reflect confirmation state in voucher line
Method signatures and docstrings:
- def check_budget_invoice(self): This method check whether the budget line residual allow to validate... | Implement the Python class `AccountBudgetConfirmationInvoice` described below.
Class description:
Inherit to overwrite workflow mothods to reflect confirmation state in voucher line
Method signatures and docstrings:
- def check_budget_invoice(self): This method check whether the budget line residual allow to validate... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class AccountBudgetConfirmationInvoice:
"""Inherit to overwrite workflow mothods to reflect confirmation state in voucher line"""
def check_budget_invoice(self):
"""This method check whether the budget line residual allow to validate this confirmation or not @return: boolean True if budget... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountBudgetConfirmationInvoice:
"""Inherit to overwrite workflow mothods to reflect confirmation state in voucher line"""
def check_budget_invoice(self):
"""This method check whether the budget line residual allow to validate this confirmation or not @return: boolean True if budget line residua... | the_stack_v2_python_sparse | v_11/EBS-SVN/trunk/account_ebs/models/account.py | musabahmed/baba | train | 0 |
f971f5fe79d150e03ecff1af845cbf26124763ab | [
"assert type(n) == int\nself.HAND_SIZE = n\nself.VOWELS = 'aeiou'\nself.CONSONANTS = 'bcdfghjklmnpqrstvwxyz'\nself.dealNewHand()",
"self.hand = {}\nnumVowels = self.HAND_SIZE // 3\nfor i in range(numVowels):\n x = self.VOWELS[random.randrange(0, len(self.VOWELS))]\n self.hand[x] = self.hand.get(x, 0) + 1\nf... | <|body_start_0|>
assert type(n) == int
self.HAND_SIZE = n
self.VOWELS = 'aeiou'
self.CONSONANTS = 'bcdfghjklmnpqrstvwxyz'
self.dealNewHand()
<|end_body_0|>
<|body_start_1|>
self.hand = {}
numVowels = self.HAND_SIZE // 3
for i in range(numVowels):
... | Hand | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Hand:
def __init__(self, n):
"""Initialize a Hand. n: integer, the size of the hand."""
<|body_0|>
def dealNewHand(self):
"""Deals a new hand, and sets the hand attribute to the new hand."""
<|body_1|>
def setDummyHand(self, handString):
"""Allow... | stack_v2_sparse_classes_36k_train_028345 | 3,675 | no_license | [
{
"docstring": "Initialize a Hand. n: integer, the size of the hand.",
"name": "__init__",
"signature": "def __init__(self, n)"
},
{
"docstring": "Deals a new hand, and sets the hand attribute to the new hand.",
"name": "dealNewHand",
"signature": "def dealNewHand(self)"
},
{
"do... | 6 | null | Implement the Python class `Hand` described below.
Class description:
Implement the Hand class.
Method signatures and docstrings:
- def __init__(self, n): Initialize a Hand. n: integer, the size of the hand.
- def dealNewHand(self): Deals a new hand, and sets the hand attribute to the new hand.
- def setDummyHand(sel... | Implement the Python class `Hand` described below.
Class description:
Implement the Hand class.
Method signatures and docstrings:
- def __init__(self, n): Initialize a Hand. n: integer, the size of the hand.
- def dealNewHand(self): Deals a new hand, and sets the hand attribute to the new hand.
- def setDummyHand(sel... | 4e8727154a24c7a1d05361a559a997c8d076480d | <|skeleton|>
class Hand:
def __init__(self, n):
"""Initialize a Hand. n: integer, the size of the hand."""
<|body_0|>
def dealNewHand(self):
"""Deals a new hand, and sets the hand attribute to the new hand."""
<|body_1|>
def setDummyHand(self, handString):
"""Allow... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Hand:
def __init__(self, n):
"""Initialize a Hand. n: integer, the size of the hand."""
assert type(n) == int
self.HAND_SIZE = n
self.VOWELS = 'aeiou'
self.CONSONANTS = 'bcdfghjklmnpqrstvwxyz'
self.dealNewHand()
def dealNewHand(self):
"""Deals a new... | the_stack_v2_python_sparse | 01_MIT_Learning/week_5/lectures_and_examples/Section 2/exercises/hand.py | daftstar/learn_python | train | 0 | |
62534c46953b64cd752226e5d2d0844b49b08db2 | [
"self.identifier = identifier\nself.name = name if name is not None else 'col_{}'.format(abs(identifier))\nself.data_type = data_type",
"name = self.name\nif not self.data_type is None:\n name += '(' + str(self.data_type) + ')'\nreturn name"
] | <|body_start_0|>
self.identifier = identifier
self.name = name if name is not None else 'col_{}'.format(abs(identifier))
self.data_type = data_type
<|end_body_0|>
<|body_start_1|>
name = self.name
if not self.data_type is None:
name += '(' + str(self.data_type) + ')'... | Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string, optional String representation of the column type in the database. By now the f... | DatasetColumn | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatasetColumn:
"""Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string, optional String representation of the ... | stack_v2_sparse_classes_36k_train_028346 | 17,931 | permissive | [
{
"docstring": "Initialize the column object. Parameters ---------- identifier: int, optional Unique column identifier name: string, optional Column name data_type: string, optional String representation of the column data type.",
"name": "__init__",
"signature": "def __init__(self, identifier: int=-1, ... | 2 | null | Implement the Python class `DatasetColumn` described below.
Class description:
Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string,... | Implement the Python class `DatasetColumn` described below.
Class description:
Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string,... | e99f43df3df80ad5647f57d805c339257336ac73 | <|skeleton|>
class DatasetColumn:
"""Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string, optional String representation of the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatasetColumn:
"""Column in a dataset. Each column has a unique identifier and a column name. Column names are not necessarily unique within a dataset. Attributes ---------- identifier: int Unique column identifier name: string Column name data_type: string, optional String representation of the column type i... | the_stack_v2_python_sparse | vizier/datastore/dataset.py | VizierDB/web-api-async | train | 2 |
c12db7c857d67856acbe1bbe263e661caf2ad3b2 | [
"self._ts = datetime.fromtimestamp(unix_timestamp)\nself._cache_key: Optional[str] = None\nself._cache_str: Optional[str] = None",
"if Conf.log_timestamp_format != self._cache_key:\n self._cache_str = self._ts.strftime(Conf.log_timestamp_format)\nreturn self._cache_str"
] | <|body_start_0|>
self._ts = datetime.fromtimestamp(unix_timestamp)
self._cache_key: Optional[str] = None
self._cache_str: Optional[str] = None
<|end_body_0|>
<|body_start_1|>
if Conf.log_timestamp_format != self._cache_key:
self._cache_str = self._ts.strftime(Conf.log_timest... | A Log timestamp with formatting | LogTimeStamp | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogTimeStamp:
"""A Log timestamp with formatting"""
def __init__(self, unix_timestamp: int):
""":param unix_time: The unix time the timestamp represents"""
<|body_0|>
def __str__(self) -> str:
"""Return the timestamp as a formatted string"""
<|body_1|>
<... | stack_v2_sparse_classes_36k_train_028347 | 2,873 | permissive | [
{
"docstring": ":param unix_time: The unix time the timestamp represents",
"name": "__init__",
"signature": "def __init__(self, unix_timestamp: int)"
},
{
"docstring": "Return the timestamp as a formatted string",
"name": "__str__",
"signature": "def __str__(self) -> str"
}
] | 2 | null | Implement the Python class `LogTimeStamp` described below.
Class description:
A Log timestamp with formatting
Method signatures and docstrings:
- def __init__(self, unix_timestamp: int): :param unix_time: The unix time the timestamp represents
- def __str__(self) -> str: Return the timestamp as a formatted string | Implement the Python class `LogTimeStamp` described below.
Class description:
A Log timestamp with formatting
Method signatures and docstrings:
- def __init__(self, unix_timestamp: int): :param unix_time: The unix time the timestamp represents
- def __str__(self) -> str: Return the timestamp as a formatted string
<|... | f28bfb1c34313c74f99691d0b47de1d90ebfd4ec | <|skeleton|>
class LogTimeStamp:
"""A Log timestamp with formatting"""
def __init__(self, unix_timestamp: int):
""":param unix_time: The unix time the timestamp represents"""
<|body_0|>
def __str__(self) -> str:
"""Return the timestamp as a formatted string"""
<|body_1|>
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogTimeStamp:
"""A Log timestamp with formatting"""
def __init__(self, unix_timestamp: int):
""":param unix_time: The unix time the timestamp represents"""
self._ts = datetime.fromtimestamp(unix_timestamp)
self._cache_key: Optional[str] = None
self._cache_str: Optional[str... | the_stack_v2_python_sparse | angrmanagement/data/log.py | angr/angr-management | train | 727 |
af75b471a6427d070f98b39082caf128095ef1f9 | [
"version = versionutils.convert_version_to_tuple(cls.VERSION)\nif not hasattr(objects, cls.obj_name()):\n setattr(objects, cls.obj_name(), cls)\nelse:\n curr_version = versionutils.convert_version_to_tuple(getattr(objects, cls.obj_name()).VERSION)\n if version >= curr_version:\n setattr(objects, cls... | <|body_start_0|>
version = versionutils.convert_version_to_tuple(cls.VERSION)
if not hasattr(objects, cls.obj_name()):
setattr(objects, cls.obj_name(), cls)
else:
curr_version = versionutils.convert_version_to_tuple(getattr(objects, cls.obj_name()).VERSION)
if... | SenlinObjectRegistry | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SenlinObjectRegistry:
def registration_hook(self, cls, index):
"""Callback for object registration. When an object is registered, this function will be called for maintaining senlin.objects.$OBJECT as the highest-versioned implementation of a given object."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_028348 | 5,694 | permissive | [
{
"docstring": "Callback for object registration. When an object is registered, this function will be called for maintaining senlin.objects.$OBJECT as the highest-versioned implementation of a given object.",
"name": "registration_hook",
"signature": "def registration_hook(self, cls, index)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_004187 | Implement the Python class `SenlinObjectRegistry` described below.
Class description:
Implement the SenlinObjectRegistry class.
Method signatures and docstrings:
- def registration_hook(self, cls, index): Callback for object registration. When an object is registered, this function will be called for maintaining senl... | Implement the Python class `SenlinObjectRegistry` described below.
Class description:
Implement the SenlinObjectRegistry class.
Method signatures and docstrings:
- def registration_hook(self, cls, index): Callback for object registration. When an object is registered, this function will be called for maintaining senl... | 4125b34e0a0dfeb77b8e62f169b41e8b584bb60e | <|skeleton|>
class SenlinObjectRegistry:
def registration_hook(self, cls, index):
"""Callback for object registration. When an object is registered, this function will be called for maintaining senlin.objects.$OBJECT as the highest-versioned implementation of a given object."""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SenlinObjectRegistry:
def registration_hook(self, cls, index):
"""Callback for object registration. When an object is registered, this function will be called for maintaining senlin.objects.$OBJECT as the highest-versioned implementation of a given object."""
version = versionutils.convert_ver... | the_stack_v2_python_sparse | senlin/objects/base.py | openstack/senlin | train | 47 | |
ba93715786f1a6fed25ec3b8d8746d07ccbcefa9 | [
"super(DecoderLayer, self).__init__()\nwith self.init_scope():\n self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)\n self.src_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)\n self.feed_forward... | <|body_start_0|>
super(DecoderLayer, self).__init__()
with self.init_scope():
self.self_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_bias=initial_bias)
self.src_attn = MultiHeadAttention(n_units, h, dropout=dropout, initialW=initialW, initial_... | Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate | DecoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_36k_train_028349 | 2,526 | permissive | [
{
"docstring": "Initialize DecoderLayer.",
"name": "__init__",
"signature": "def __init__(self, n_units, d_units=0, h=8, dropout=0.1, initialW=None, initial_bias=None)"
},
{
"docstring": "Compute Encoder layer. Args: e (chainer.Variable): Batch of padded features. (B, Lmax) s (chainer.Variable):... | 2 | stack_v2_sparse_classes_30k_train_004869 | Implement the Python class `DecoderLayer` described below.
Class description:
Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | Implement the Python class `DecoderLayer` described below.
Class description:
Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout ra... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderLayer:
"""Single decoder layer module. Args: n_units (int): Number of input/output dimension of a FeedForward layer. d_units (int): Number of units of hidden layer in a FeedForward layer. h (int): Number of attention heads. dropout (float): Dropout rate"""
def __init__(self, n_units, d_units=0, h=... | the_stack_v2_python_sparse | espnet/nets/chainer_backend/transformer/decoder_layer.py | espnet/espnet | train | 7,242 |
2e687de7f1bddf9d30ef34bd24d1c217ba2428fb | [
"graph = defaultdict(list)\nfor u, v, w in times:\n graph[u].append((v, w))\ndist = {node: float('inf') for node in range(1, N + 1)}\nprint(dist)\nseen = [False] * (N + 1)\ndist[K] = 0\nwhile True:\n cand_node = -1\n cand_dist = float('inf')\n for i in range(1, N + 1):\n if not seen[i] and dist[i... | <|body_start_0|>
graph = defaultdict(list)
for u, v, w in times:
graph[u].append((v, w))
dist = {node: float('inf') for node in range(1, N + 1)}
print(dist)
seen = [False] * (N + 1)
dist[K] = 0
while True:
cand_node = -1
cand_di... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def networkDelayTime(self, times, N, K):
""":type times: List[List[int]] :type N: int :type K: int :rtype: int"""
<|body_0|>
def networkDelayTime_(self, times, N, K):
""":type times: List[List[int]] :type N: int :type K: int :rtype: int"""
<|body_1|... | stack_v2_sparse_classes_36k_train_028350 | 2,764 | no_license | [
{
"docstring": ":type times: List[List[int]] :type N: int :type K: int :rtype: int",
"name": "networkDelayTime",
"signature": "def networkDelayTime(self, times, N, K)"
},
{
"docstring": ":type times: List[List[int]] :type N: int :type K: int :rtype: int",
"name": "networkDelayTime_",
"si... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def networkDelayTime(self, times, N, K): :type times: List[List[int]] :type N: int :type K: int :rtype: int
- def networkDelayTime_(self, times, N, K): :type times: List[List[int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def networkDelayTime(self, times, N, K): :type times: List[List[int]] :type N: int :type K: int :rtype: int
- def networkDelayTime_(self, times, N, K): :type times: List[List[int... | 786075e0f9f61cf062703bc0b41cc3191d77f033 | <|skeleton|>
class Solution:
def networkDelayTime(self, times, N, K):
""":type times: List[List[int]] :type N: int :type K: int :rtype: int"""
<|body_0|>
def networkDelayTime_(self, times, N, K):
""":type times: List[List[int]] :type N: int :type K: int :rtype: int"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def networkDelayTime(self, times, N, K):
""":type times: List[List[int]] :type N: int :type K: int :rtype: int"""
graph = defaultdict(list)
for u, v, w in times:
graph[u].append((v, w))
dist = {node: float('inf') for node in range(1, N + 1)}
print(... | the_stack_v2_python_sparse | 743_networkDelayTime.py | Anirban2404/LeetCodePractice | train | 1 | |
ccd6f4f54e707fe8aa016c3c6b9407227f3fe0f0 | [
"ENFORCER.enforce_call(action='identity:check_grant', build_target=_build_enforcement_target)\nPROVIDERS.assignment_api.get_grant(role_id, domain_id=domain_id, group_id=group_id, inherited_to_projects=False)\nreturn (None, http_client.NO_CONTENT)",
"ENFORCER.enforce_call(action='identity:create_grant', build_targ... | <|body_start_0|>
ENFORCER.enforce_call(action='identity:check_grant', build_target=_build_enforcement_target)
PROVIDERS.assignment_api.get_grant(role_id, domain_id=domain_id, group_id=group_id, inherited_to_projects=False)
return (None, http_client.NO_CONTENT)
<|end_body_0|>
<|body_start_1|>
... | DomainGroupResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DomainGroupResource:
def get(self, domain_id=None, group_id=None, role_id=None):
"""Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group_id}/roles/{role_id}"""
<|body_0|>
def put(self, domain_id=None, group_id=None, role_id=None):
... | stack_v2_sparse_classes_36k_train_028351 | 19,761 | permissive | [
{
"docstring": "Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group_id}/roles/{role_id}",
"name": "get",
"signature": "def get(self, domain_id=None, group_id=None, role_id=None)"
},
{
"docstring": "Grant a role to a group on a domain. PUT /v3/domains/... | 3 | null | Implement the Python class `DomainGroupResource` described below.
Class description:
Implement the DomainGroupResource class.
Method signatures and docstrings:
- def get(self, domain_id=None, group_id=None, role_id=None): Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group... | Implement the Python class `DomainGroupResource` described below.
Class description:
Implement the DomainGroupResource class.
Method signatures and docstrings:
- def get(self, domain_id=None, group_id=None, role_id=None): Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group... | 03a0a8146a78682ede9eca12a5a7fdacde2035c8 | <|skeleton|>
class DomainGroupResource:
def get(self, domain_id=None, group_id=None, role_id=None):
"""Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group_id}/roles/{role_id}"""
<|body_0|>
def put(self, domain_id=None, group_id=None, role_id=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DomainGroupResource:
def get(self, domain_id=None, group_id=None, role_id=None):
"""Check if a group has a specific role on a domain. GET/HEAD /v3/domains/{domain_id}/groups/{group_id}/roles/{role_id}"""
ENFORCER.enforce_call(action='identity:check_grant', build_target=_build_enforcement_targe... | the_stack_v2_python_sparse | keystone/api/domains.py | sapcc/keystone | train | 0 | |
fe182f6a4259ce6281c8b7ac34da161be491bbc2 | [
"assert len(input_string) > 0\nsuper().__init__(self.PROBLEM_NAME)\nself.input_string = input_string",
"print('Solving {} problem ...'.format(self.PROBLEM_NAME))\njson = self.input_string\nif not json:\n return ''\nresult = []\nmultiplier = 0\ni = 0\nwhile i < len(json):\n if json[i] in self.OPENING_BRACKET... | <|body_start_0|>
assert len(input_string) > 0
super().__init__(self.PROBLEM_NAME)
self.input_string = input_string
<|end_body_0|>
<|body_start_1|>
print('Solving {} problem ...'.format(self.PROBLEM_NAME))
json = self.input_string
if not json:
return ''
... | PrettyPrintJSON | PrettyPrintJSON | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrettyPrintJSON:
"""PrettyPrintJSON"""
def __init__(self, input_string):
"""Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None"""
<|body_0|>
def solve(self):
"""Solve the problem Args: Returns: string Raises: N... | stack_v2_sparse_classes_36k_train_028352 | 2,933 | no_license | [
{
"docstring": "Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_string)"
},
{
"docstring": "Solve the problem Args: Returns: string Raises: None",
"name": "solve",
"signat... | 2 | null | Implement the Python class `PrettyPrintJSON` described below.
Class description:
PrettyPrintJSON
Method signatures and docstrings:
- def __init__(self, input_string): Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None
- def solve(self): Solve the problem Args: Retu... | Implement the Python class `PrettyPrintJSON` described below.
Class description:
PrettyPrintJSON
Method signatures and docstrings:
- def __init__(self, input_string): Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None
- def solve(self): Solve the problem Args: Retu... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class PrettyPrintJSON:
"""PrettyPrintJSON"""
def __init__(self, input_string):
"""Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None"""
<|body_0|>
def solve(self):
"""Solve the problem Args: Returns: string Raises: N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrettyPrintJSON:
"""PrettyPrintJSON"""
def __init__(self, input_string):
"""Pretty Print JSON Note: Args: input_string: JSON string to be pretty-printed Returns: None Raises: None"""
assert len(input_string) > 0
super().__init__(self.PROBLEM_NAME)
self.input_string = input... | the_stack_v2_python_sparse | python/problems/string/pretty_print_json.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
ecf8987c17870b9818691d5a1434b9bb6c143743 | [
"data = {'article': request.data.get('id', None), 'user_id': request._request.uid, 'content': request.data.get('content', None)}\ns = ArticleCommentSerializer(data=data)\ns.is_valid()\nif s.errors:\n return self.error(errorcode.MSG_INVALID_DATA, errorcode.INVALID_DATA)\narticle = s.validated_data['article']\ns.v... | <|body_start_0|>
data = {'article': request.data.get('id', None), 'user_id': request._request.uid, 'content': request.data.get('content', None)}
s = ArticleCommentSerializer(data=data)
s.is_valid()
if s.errors:
return self.error(errorcode.MSG_INVALID_DATA, errorcode.INVALID_D... | CommentView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentView:
def post(self, request):
"""评论文章，必须是已发表的文章"""
<|body_0|>
def delete(self, request):
"""删除本人的评论"""
<|body_1|>
def put(self, request):
"""修改本人的评论"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
data = {'article': requ... | stack_v2_sparse_classes_36k_train_028353 | 12,861 | no_license | [
{
"docstring": "评论文章，必须是已发表的文章",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除本人的评论",
"name": "delete",
"signature": "def delete(self, request)"
},
{
"docstring": "修改本人的评论",
"name": "put",
"signature": "def put(self, request)"
}
] | 3 | stack_v2_sparse_classes_30k_train_002594 | Implement the Python class `CommentView` described below.
Class description:
Implement the CommentView class.
Method signatures and docstrings:
- def post(self, request): 评论文章，必须是已发表的文章
- def delete(self, request): 删除本人的评论
- def put(self, request): 修改本人的评论 | Implement the Python class `CommentView` described below.
Class description:
Implement the CommentView class.
Method signatures and docstrings:
- def post(self, request): 评论文章，必须是已发表的文章
- def delete(self, request): 删除本人的评论
- def put(self, request): 修改本人的评论
<|skeleton|>
class CommentView:
def post(self, request)... | 6a68fb207f43e5ed65299cc08535b35d5e934ead | <|skeleton|>
class CommentView:
def post(self, request):
"""评论文章，必须是已发表的文章"""
<|body_0|>
def delete(self, request):
"""删除本人的评论"""
<|body_1|>
def put(self, request):
"""修改本人的评论"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommentView:
def post(self, request):
"""评论文章，必须是已发表的文章"""
data = {'article': request.data.get('id', None), 'user_id': request._request.uid, 'content': request.data.get('content', None)}
s = ArticleCommentSerializer(data=data)
s.is_valid()
if s.errors:
retur... | the_stack_v2_python_sparse | apps/articles/views.py | Slowhalfframe/fanyijiang-API | train | 0 | |
a0c114483329b253162e84fc8b70f93bd9eaa3e2 | [
"value = None\ncache = None\nprefix = None\nif self.should_cache():\n prefix = '%s:%s:string' % (self.get_cache_version(), self.get_cache_prefix())\n cache = router.router.get_cache(prefix)\n value = cache.get(prefix)\nif not value:\n value = super(CacheView, self).get_as_string(request, *args, **kwargs... | <|body_start_0|>
value = None
cache = None
prefix = None
if self.should_cache():
prefix = '%s:%s:string' % (self.get_cache_version(), self.get_cache_prefix())
cache = router.router.get_cache(prefix)
value = cache.get(prefix)
if not value:
... | A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This gets passed to django middleware and d... | CacheView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This g... | stack_v2_sparse_classes_36k_train_028354 | 7,096 | permissive | [
{
"docstring": "Should only be used when inheriting from cms View. Gets the response as a string and caches it with a separate prefix",
"name": "get_as_string",
"signature": "def get_as_string(self, request, *args, **kwargs)"
},
{
"docstring": "Overrides Django's default dispatch to provide cach... | 2 | stack_v2_sparse_classes_30k_train_014331 | Implement the Python class `CacheView` described below.
Class description:
A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long... | Implement the Python class `CacheView` described below.
Class description:
A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long... | 9f5ac28618059eef99152214c7a90ad78151629e | <|skeleton|>
class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CacheView:
"""A class based view that overrides the default dispatch method to determine the cache_prefix. If the cms view is available this class will inherit from there otherwise it will inherit from django's generic class View. :param cache_time: How long should we cache this attribute. This gets passed to... | the_stack_v2_python_sparse | scarlet/cache/views.py | markmiscavage/scarlet | train | 1 |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.weight, vilt_layer.attention.attention.key.weight, vilt_layer.attention.attention.value.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.bias, vilt_layer.attention... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([vilt_layer.attention.attention.query.weight, vilt_layer.attention.attention.key.weight, vilt_layer.attention.attention.value.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([vilt_layer.attention.attentio... | ViltLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViltLayerBetterTransformer:
def __init__(self, vilt_layer, config):
"""A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved."""
<|body_0|>
def fo... | stack_v2_sparse_classes_36k_train_028355 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, vilt_layer, config)"
},
{
"docstring": "T... | 2 | stack_v2_sparse_classes_30k_train_015342 | Implement the Python class `ViltLayerBetterTransformer` described below.
Class description:
Implement the ViltLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, vilt_layer, config): A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`tor... | Implement the Python class `ViltLayerBetterTransformer` described below.
Class description:
Implement the ViltLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, vilt_layer, config): A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`tor... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ViltLayerBetterTransformer:
def __init__(self, vilt_layer, config):
"""A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved."""
<|body_0|>
def fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViltLayerBetterTransformer:
def __init__(self, vilt_layer, config):
"""A simple conversion of the VilTLayer to its `BetterTransformer` implementation. Args: vilt_layer (`torch.nn.Module`): The original `VilTLayer` where the weights needs to be retrieved."""
super().__init__(config)
sel... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
f355c88e2f97bb9f9f6262b0a99eb2aec8920244 | [
"labels_file = os.path.join(os.path.dirname(__file__), 'imagenet_labels.json.gz')\nwith gzip.open(labels_file, 'rb') as file_obj:\n labels = json.load(file_obj)\nreturn labels",
"files = IOUtils.find_files(folder, '*.JPEG', recursively=True)\nrandom.shuffle(files)\nif num_files > 0 and num_files < len(files):\... | <|body_start_0|>
labels_file = os.path.join(os.path.dirname(__file__), 'imagenet_labels.json.gz')
with gzip.open(labels_file, 'rb') as file_obj:
labels = json.load(file_obj)
return labels
<|end_body_0|>
<|body_start_1|>
files = IOUtils.find_files(folder, '*.JPEG', recursivel... | Filesystem | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Filesystem:
def get_labels():
"""Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class folder ID to an object that contains two fields - 'label' and 'human_labels'. The 'label' is an integer... | stack_v2_sparse_classes_36k_train_028356 | 8,048 | permissive | [
{
"docstring": "Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class folder ID to an object that contains two fields - 'label' and 'human_labels'. The 'label' is an integer index of a label from [0,1000) according... | 2 | stack_v2_sparse_classes_30k_train_009525 | Implement the Python class `Filesystem` described below.
Class description:
Implement the Filesystem class.
Method signatures and docstrings:
- def get_labels(): Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class fold... | Implement the Python class `Filesystem` described below.
Class description:
Implement the Filesystem class.
Method signatures and docstrings:
- def get_labels(): Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class fold... | 834350c81154e48af132b7d27874e30a7b80a78c | <|skeleton|>
class Filesystem:
def get_labels():
"""Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class folder ID to an object that contains two fields - 'label' and 'human_labels'. The 'label' is an integer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Filesystem:
def get_labels():
"""Load labels from 'imagenet_labels.json.gz' that's located in the same directory as this file. :rtype: dict :return: Dictionary that maps ImageNet class folder ID to an object that contains two fields - 'label' and 'human_labels'. The 'label' is an integer index of a la... | the_stack_v2_python_sparse | python/dlbs/data/imagenet/tensorflow_data.py | HewlettPackard/dlcookbook-dlbs | train | 132 | |
6bf7841f022e6ba384158abc4cc218f8be6fb3ed | [
"smrys = [x.tojson() for x in SummaryModel.query.filter_by(surveyid=surveyid)]\nif smrys == []:\n return ({'message': \"no summary found for surveyid '{}' \".format(surveyid)}, 400)\nreturn {'summaries': smrys}",
"data = resources.parsers.ParseSummariesPost.parser.parse_args()\nsmmry = SummaryModel(data['qid']... | <|body_start_0|>
smrys = [x.tojson() for x in SummaryModel.query.filter_by(surveyid=surveyid)]
if smrys == []:
return ({'message': "no summary found for surveyid '{}' ".format(surveyid)}, 400)
return {'summaries': smrys}
<|end_body_0|>
<|body_start_1|>
data = resources.parse... | Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid | Summary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Summary:
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid"""
def get(self, surveyid):
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a lis... | stack_v2_sparse_classes_36k_train_028357 | 3,418 | no_license | [
{
"docstring": "Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid",
"name": "get",
"signature": "def get(self, surveyid)"
},
{
"docstring": "Server REST testing resource: Creates a summary for a spec... | 3 | stack_v2_sparse_classes_30k_train_002751 | Implement the Python class `Summary` described below.
Class description:
Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid
Method signatures and docstrings:
- def get(self, surveyid): Internal REST resource: Returns all s... | Implement the Python class `Summary` described below.
Class description:
Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid
Method signatures and docstrings:
- def get(self, surveyid): Internal REST resource: Returns all s... | 619a7040ab339097b19cf5daccf94c58ee4e2870 | <|skeleton|>
class Summary:
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid"""
def get(self, surveyid):
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a lis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Summary:
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summary of evaluated reports to an surveyid"""
def get(self, surveyid):
"""Internal REST resource: Returns all summaries belonging to a specific survey id. Returns a list with a summ... | the_stack_v2_python_sparse | server/resources/summaries.py | yrtsprmb/zappor | train | 0 |
0510b7b92de218233c6649a7fa3f4ae176eea17b | [
"if arr is None:\n return arr\nn = len(arr)\nif n <= 1:\n return arr\nfor i in range(0, n):\n for j in range(0, n - i - 1):\n if arr[j] > arr[j + 1]:\n arr[j + 1], arr[j] = (arr[j], arr[j + 1])\nreturn arr",
"if arr is None:\n return arr\nn = len(arr)\nif n <= 1:\n return arr\nfor... | <|body_start_0|>
if arr is None:
return arr
n = len(arr)
if n <= 1:
return arr
for i in range(0, n):
for j in range(0, n - i - 1):
if arr[j] > arr[j + 1]:
arr[j + 1], arr[j] = (arr[j], arr[j + 1])
return arr
... | BubbleSort | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BubbleSort:
def bubble_sort(arr):
"""Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list"""
<|body_0|>
def bubble_sort_optimized(arr):
"""Optimized bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list... | stack_v2_sparse_classes_36k_train_028358 | 2,435 | permissive | [
{
"docstring": "Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list",
"name": "bubble_sort",
"signature": "def bubble_sort(arr)"
},
{
"docstring": "Optimized bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list",
"name": "bub... | 2 | stack_v2_sparse_classes_30k_train_017192 | Implement the Python class `BubbleSort` described below.
Class description:
Implement the BubbleSort class.
Method signatures and docstrings:
- def bubble_sort(arr): Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list
- def bubble_sort_optimized(arr): Optimized bubble sort. :param ar... | Implement the Python class `BubbleSort` described below.
Class description:
Implement the BubbleSort class.
Method signatures and docstrings:
- def bubble_sort(arr): Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list
- def bubble_sort_optimized(arr): Optimized bubble sort. :param ar... | 8504db89a3f6a1596c0bb7343a4936884b44e6ea | <|skeleton|>
class BubbleSort:
def bubble_sort(arr):
"""Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list"""
<|body_0|>
def bubble_sort_optimized(arr):
"""Optimized bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BubbleSort:
def bubble_sort(arr):
"""Bubble sort. :param arr: List[int], list to be sorted :return: List[int], sorted list"""
if arr is None:
return arr
n = len(arr)
if n <= 1:
return arr
for i in range(0, n):
for j in range(0, n - i ... | the_stack_v2_python_sparse | sorting/bubble_sort.py | fimh/dsa-py | train | 2 | |
a4600be0a16ad03e0b8c064d10dda43288b92713 | [
"context = super().get_serializer_context()\ncontext.update({'redis': self.redis})\nreturn context",
"if is_remember:\n response.set_cookie('login_id', login_id, max_age=7 * 24 * 3600)\nelse:\n response.delete_cookie('login_id', login_id)",
"serializer = self.get_serializer(data=request.data)\nserializer.... | <|body_start_0|>
context = super().get_serializer_context()
context.update({'redis': self.redis})
return context
<|end_body_0|>
<|body_start_1|>
if is_remember:
response.set_cookie('login_id', login_id, max_age=7 * 24 * 3600)
else:
response.delete_cookie(... | 使用JWT登录 | LoginAPIView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginAPIView:
"""使用JWT登录"""
def get_serializer_context(self):
"""添加redis到额外环境中"""
<|body_0|>
def remember_username(response, is_remember, login_id):
"""设置cookie，本地暂存用户名1周"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""用户登录"""
... | stack_v2_sparse_classes_36k_train_028359 | 6,225 | permissive | [
{
"docstring": "添加redis到额外环境中",
"name": "get_serializer_context",
"signature": "def get_serializer_context(self)"
},
{
"docstring": "设置cookie，本地暂存用户名1周",
"name": "remember_username",
"signature": "def remember_username(response, is_remember, login_id)"
},
{
"docstring": "用户登录",
... | 3 | null | Implement the Python class `LoginAPIView` described below.
Class description:
使用JWT登录
Method signatures and docstrings:
- def get_serializer_context(self): 添加redis到额外环境中
- def remember_username(response, is_remember, login_id): 设置cookie，本地暂存用户名1周
- def post(self, request, *args, **kwargs): 用户登录 | Implement the Python class `LoginAPIView` described below.
Class description:
使用JWT登录
Method signatures and docstrings:
- def get_serializer_context(self): 添加redis到额外环境中
- def remember_username(response, is_remember, login_id): 设置cookie，本地暂存用户名1周
- def post(self, request, *args, **kwargs): 用户登录
<|skeleton|>
class Lo... | 13cb59130d15e782f78bc5148409bef0f1c516e0 | <|skeleton|>
class LoginAPIView:
"""使用JWT登录"""
def get_serializer_context(self):
"""添加redis到额外环境中"""
<|body_0|>
def remember_username(response, is_remember, login_id):
"""设置cookie，本地暂存用户名1周"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""用户登录"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginAPIView:
"""使用JWT登录"""
def get_serializer_context(self):
"""添加redis到额外环境中"""
context = super().get_serializer_context()
context.update({'redis': self.redis})
return context
def remember_username(response, is_remember, login_id):
"""设置cookie，本地暂存用户名1周"""
... | the_stack_v2_python_sparse | user_app/views/login_register_api.py | lmyfzx/Django-Mall | train | 0 |
a87e1a14a40b4284005aea9c105bbf086018622d | [
"if not change:\n obj.created_by = request.user\nreturn super(AbstractBaseAdmin, self).save_model(request, obj, form, change)",
"for form in formset.extra_forms:\n if form.has_changed:\n form.instance.created_by = request.user\nreturn super(AbstractBaseAdmin, self).save_formset(request, form, formset... | <|body_start_0|>
if not change:
obj.created_by = request.user
return super(AbstractBaseAdmin, self).save_model(request, obj, form, change)
<|end_body_0|>
<|body_start_1|>
for form in formset.extra_forms:
if form.has_changed:
form.instance.created_by = req... | AbstractBaseAdmin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbstractBaseAdmin:
def save_model(self, request, obj, form, change):
"""Populate AbstractBase.created_by with the user who submitted the request."""
<|body_0|>
def save_formset(self, request, form, formset, change):
"""Populate AbstractBase.created_by on inlined rela... | stack_v2_sparse_classes_36k_train_028360 | 1,179 | permissive | [
{
"docstring": "Populate AbstractBase.created_by with the user who submitted the request.",
"name": "save_model",
"signature": "def save_model(self, request, obj, form, change)"
},
{
"docstring": "Populate AbstractBase.created_by on inlined relations with the user who submitted the request.",
... | 2 | stack_v2_sparse_classes_30k_train_020629 | Implement the Python class `AbstractBaseAdmin` described below.
Class description:
Implement the AbstractBaseAdmin class.
Method signatures and docstrings:
- def save_model(self, request, obj, form, change): Populate AbstractBase.created_by with the user who submitted the request.
- def save_formset(self, request, fo... | Implement the Python class `AbstractBaseAdmin` described below.
Class description:
Implement the AbstractBaseAdmin class.
Method signatures and docstrings:
- def save_model(self, request, obj, form, change): Populate AbstractBase.created_by with the user who submitted the request.
- def save_formset(self, request, fo... | a271d40922eaad682a76d7700beafc7a5df51fac | <|skeleton|>
class AbstractBaseAdmin:
def save_model(self, request, obj, form, change):
"""Populate AbstractBase.created_by with the user who submitted the request."""
<|body_0|>
def save_formset(self, request, form, formset, change):
"""Populate AbstractBase.created_by on inlined rela... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbstractBaseAdmin:
def save_model(self, request, obj, form, change):
"""Populate AbstractBase.created_by with the user who submitted the request."""
if not change:
obj.created_by = request.user
return super(AbstractBaseAdmin, self).save_model(request, obj, form, change)
... | the_stack_v2_python_sparse | quizard/admin/AbstractBaseAdmin.py | E7ernal/quizwhiz | train | 1 | |
f1ff90793c7bfa2adbf724f453f5b6743233e8a2 | [
"self.terminator = '\\n'\nlogging.Handler.__init__(self)\nif stream is None:\n stream = sys.stderr\nself.stream = stream",
"self.acquire()\ntry:\n if self.stream and hasattr(self.stream, 'flush'):\n self.stream.flush()\nfinally:\n self.release()",
"try:\n msg = self.format(record)\n stream... | <|body_start_0|>
self.terminator = '\n'
logging.Handler.__init__(self)
if stream is None:
stream = sys.stderr
self.stream = stream
<|end_body_0|>
<|body_start_1|>
self.acquire()
try:
if self.stream and hasattr(self.stream, 'flush'):
... | Modified from logging.py | CustomStreamHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomStreamHandler:
"""Modified from logging.py"""
def __init__(self, stream=None):
"""Initialize the handler. If stream is not specified, sys.stderr is used."""
<|body_0|>
def flush(self):
"""Flushes the stream."""
<|body_1|>
def emit(self, record)... | stack_v2_sparse_classes_36k_train_028361 | 20,556 | permissive | [
{
"docstring": "Initialize the handler. If stream is not specified, sys.stderr is used.",
"name": "__init__",
"signature": "def __init__(self, stream=None)"
},
{
"docstring": "Flushes the stream.",
"name": "flush",
"signature": "def flush(self)"
},
{
"docstring": "Emit a record. ... | 3 | stack_v2_sparse_classes_30k_train_017277 | Implement the Python class `CustomStreamHandler` described below.
Class description:
Modified from logging.py
Method signatures and docstrings:
- def __init__(self, stream=None): Initialize the handler. If stream is not specified, sys.stderr is used.
- def flush(self): Flushes the stream.
- def emit(self, record): Em... | Implement the Python class `CustomStreamHandler` described below.
Class description:
Modified from logging.py
Method signatures and docstrings:
- def __init__(self, stream=None): Initialize the handler. If stream is not specified, sys.stderr is used.
- def flush(self): Flushes the stream.
- def emit(self, record): Em... | 6659d953b217748d0b15f0da4cd27fe789e3cd50 | <|skeleton|>
class CustomStreamHandler:
"""Modified from logging.py"""
def __init__(self, stream=None):
"""Initialize the handler. If stream is not specified, sys.stderr is used."""
<|body_0|>
def flush(self):
"""Flushes the stream."""
<|body_1|>
def emit(self, record)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomStreamHandler:
"""Modified from logging.py"""
def __init__(self, stream=None):
"""Initialize the handler. If stream is not specified, sys.stderr is used."""
self.terminator = '\n'
logging.Handler.__init__(self)
if stream is None:
stream = sys.stderr
... | the_stack_v2_python_sparse | utool/util_logging.py | Erotemic/utool | train | 8 |
442149997ec81c3ed94adde7d66c8a5e0d2fe72f | [
"super().__init__(screen)\nself._parameters = (screen, position, title, buttons)\nif not isinstance(position, str) or position not in acceptable_positions:\n raise ValueError('Menu->Constructor: position parameter must be one of following strings: left, right, or middle')\nif not isinstance(title, str):\n rai... | <|body_start_0|>
super().__init__(screen)
self._parameters = (screen, position, title, buttons)
if not isinstance(position, str) or position not in acceptable_positions:
raise ValueError('Menu->Constructor: position parameter must be one of following strings: left, right, or middle')... | Menu | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Menu:
def __init__(self, screen, position, title, buttons):
"""Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons"""
<|body_0|>
def add_button(self, text, callback):
"""Adds a button to the button ... | stack_v2_sparse_classes_36k_train_028362 | 4,542 | no_license | [
{
"docstring": "Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons",
"name": "__init__",
"signature": "def __init__(self, screen, position, title, buttons)"
},
{
"docstring": "Adds a button to the button list on the menu. Take... | 4 | stack_v2_sparse_classes_30k_train_016230 | Implement the Python class `Menu` described below.
Class description:
Implement the Menu class.
Method signatures and docstrings:
- def __init__(self, screen, position, title, buttons): Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons
- def add_b... | Implement the Python class `Menu` described below.
Class description:
Implement the Menu class.
Method signatures and docstrings:
- def __init__(self, screen, position, title, buttons): Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons
- def add_b... | 53f2f04c258051f89bdacf988267bf1cb414d9dd | <|skeleton|>
class Menu:
def __init__(self, screen, position, title, buttons):
"""Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons"""
<|body_0|>
def add_button(self, text, callback):
"""Adds a button to the button ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Menu:
def __init__(self, screen, position, title, buttons):
"""Constructor constructs Menu object, which will setup the font, title, and all variables required for a menu with buttons"""
super().__init__(screen)
self._parameters = (screen, position, title, buttons)
if not isins... | the_stack_v2_python_sparse | lib/modules/gui/menu.py | Jacob-Brink/game | train | 0 | |
06c9f3d4d9930778900caad8f2978278d9ffb0fe | [
"super(SpfModel, self).__init__()\nself.config = config\nif self.config.mode == 'attn':\n self.multi_head_attention = attn.MultiHeadAttentionLayer(num_heads=config.num_heads, attention_class='SelfAttentionLayer', dim_in=2 * config.dim_embedding, dim_out=config.dim_attn_out, dim_hidden=config.dim_attn_hidden)\n ... | <|body_start_0|>
super(SpfModel, self).__init__()
self.config = config
if self.config.mode == 'attn':
self.multi_head_attention = attn.MultiHeadAttentionLayer(num_heads=config.num_heads, attention_class='SelfAttentionLayer', dim_in=2 * config.dim_embedding, dim_out=config.dim_attn_ou... | Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood embedding as keys and values. The output is passed through a sequence of fu... | SpfModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpfModel:
"""Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood embedding as keys and values. The outpu... | stack_v2_sparse_classes_36k_train_028363 | 11,352 | no_license | [
{
"docstring": "Initializes object. Args: config:",
"name": "__init__",
"signature": "def __init__(self, config: SpfConfig)"
},
{
"docstring": "Perform forward pass. Args: queries: Queries of shape (BS, 1, E). others: Values and Keys of shape (BS, T_max, E). mask: Attention mask of shape (BS, T_... | 2 | stack_v2_sparse_classes_30k_train_005081 | Implement the Python class `SpfModel` described below.
Class description:
Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood ... | Implement the Python class `SpfModel` described below.
Class description:
Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood ... | 914e38474a8dea667e239785f84245eefce10db2 | <|skeleton|>
class SpfModel:
"""Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood embedding as keys and values. The outpu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpfModel:
"""Implements a neural network with two inputs: 1) Embeddings of neighbors. 2) Embedding of destination The neighborhood encoding is inserted into a multi-head attention mechanism. The embedding of the destination serves as query. The neighborhood embedding as keys and values. The output is passed t... | the_stack_v2_python_sparse | models/sponly.py | ano-iclr22/mistill | train | 0 |
8d45a3efa38afa94a7bc2263211536f069456f2a | [
"if data is None:\n if lambtha <= 0:\n raise ValueError('lambtha must be a positive value')\n self.lambtha = float(lambtha)\nelif type(data) is not list:\n raise TypeError('data must be a list')\nelif len(data) < 2:\n raise ValueError('data must contain multiple values')\nelse:\n self.lambtha ... | <|body_start_0|>
if data is None:
if lambtha <= 0:
raise ValueError('lambtha must be a positive value')
self.lambtha = float(lambtha)
elif type(data) is not list:
raise TypeError('data must be a list')
elif len(data) < 2:
raise Valu... | Tye class to call methods of Poisson distribution CDF and PDF | Poisson | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poisson:
"""Tye class to call methods of Poisson distribution CDF and PDF"""
def __init__(self, data=None, lambtha=1.0):
"""Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of data"""
<|body_0|>
def pmf(self, k):
""... | stack_v2_sparse_classes_36k_train_028364 | 1,588 | no_license | [
{
"docstring": "Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of data",
"name": "__init__",
"signature": "def __init__(self, data=None, lambtha=1.0)"
},
{
"docstring": "Method Probability Mass Function for Poisson k: integer value of the data re... | 3 | null | Implement the Python class `Poisson` described below.
Class description:
Tye class to call methods of Poisson distribution CDF and PDF
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of dat... | Implement the Python class `Poisson` described below.
Class description:
Tye class to call methods of Poisson distribution CDF and PDF
Method signatures and docstrings:
- def __init__(self, data=None, lambtha=1.0): Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of dat... | 7f9a040f23eda32c5aa154c991c930a01b490f0f | <|skeleton|>
class Poisson:
"""Tye class to call methods of Poisson distribution CDF and PDF"""
def __init__(self, data=None, lambtha=1.0):
"""Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of data"""
<|body_0|>
def pmf(self, k):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Poisson:
"""Tye class to call methods of Poisson distribution CDF and PDF"""
def __init__(self, data=None, lambtha=1.0):
"""Initialize method data: type list of given numbers lambtha: type lambda factor to calculate mean of data"""
if data is None:
if lambtha <= 0:
... | the_stack_v2_python_sparse | math/0x03-probability/poisson.py | dbaroli/holbertonschool-machine_learning | train | 0 |
623b601cc60ddc8c53f32b4acb616684179ef870 | [
"del observation\ndel a\nreturn -1",
"del reward\ndel observation\ndel a\nreturn -1"
] | <|body_start_0|>
del observation
del a
return -1
<|end_body_0|>
<|body_start_1|>
del reward
del observation
del a
return -1
<|end_body_1|>
| A MockExploration class that always returns -1. | MockExploration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
<|body_0|>
def step(self, reward: float, observation: np.ndarray, a: int) -> int:
... | stack_v2_sparse_classes_36k_train_028365 | 11,665 | permissive | [
{
"docstring": "Returns the same action passed by the agent.",
"name": "begin_episode",
"signature": "def begin_episode(self, observation: np.ndarray, a: int) -> int"
},
{
"docstring": "Returns the same action passed by the agent.",
"name": "step",
"signature": "def step(self, reward: fl... | 2 | stack_v2_sparse_classes_30k_val_000797 | Implement the Python class `MockExploration` described below.
Class description:
A MockExploration class that always returns -1.
Method signatures and docstrings:
- def begin_episode(self, observation: np.ndarray, a: int) -> int: Returns the same action passed by the agent.
- def step(self, reward: float, observation... | Implement the Python class `MockExploration` described below.
Class description:
A MockExploration class that always returns -1.
Method signatures and docstrings:
- def begin_episode(self, observation: np.ndarray, a: int) -> int: Returns the same action passed by the agent.
- def step(self, reward: float, observation... | 72082feccf404e5bf946e513e4f6c0ae8fb279ad | <|skeleton|>
class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
<|body_0|>
def step(self, reward: float, observation: np.ndarray, a: int) -> int:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MockExploration:
"""A MockExploration class that always returns -1."""
def begin_episode(self, observation: np.ndarray, a: int) -> int:
"""Returns the same action passed by the agent."""
del observation
del a
return -1
def step(self, reward: float, observation: np.nda... | the_stack_v2_python_sparse | balloon_learning_environment/agents/quantile_agent_test.py | google/balloon-learning-environment | train | 108 |
1310921dc60ff7eec19f424a4298c77c7fc6f917 | [
"self.total = total\nself.solved = solved\nself.others = others\nself.locked = locked\nself.time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())\nself.msg = '# Keep thinking, keep alive\\nUntil {}, I have solved **{}** / **{}** problems while **{}** are still locked.\\n\\nCompletion statistic: \\n1. JavaScri... | <|body_start_0|>
self.total = total
self.solved = solved
self.others = others
self.locked = locked
self.time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())
self.msg = '# Keep thinking, keep alive\nUntil {}, I have solved **{}** / **{}** problems while **{}** are s... | generate folder and markdown file update README.md when you finish one problem by some language | Readme | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
<|body_0... | stack_v2_sparse_classes_36k_train_028366 | 10,467 | permissive | [
{
"docstring": ":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展",
"name": "__init__",
"signature": "def __init__(self, total, solved, locked, others=None)"
},
{
"docstring": "create REAdME.md :return:",
"name": "create_leetcode_readme",
"si... | 2 | stack_v2_sparse_classes_30k_train_021220 | Implement the Python class `Readme` described below.
Class description:
generate folder and markdown file update README.md when you finish one problem by some language
Method signatures and docstrings:
- def __init__(self, total, solved, locked, others=None): :param total: total problems nums :param solved: solved pr... | Implement the Python class `Readme` described below.
Class description:
generate folder and markdown file update README.md when you finish one problem by some language
Method signatures and docstrings:
- def __init__(self, total, solved, locked, others=None): :param total: total problems nums :param solved: solved pr... | f71118e8e05d4bcdcfb2dfc42187c73961b8b926 | <|skeleton|>
class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Readme:
"""generate folder and markdown file update README.md when you finish one problem by some language"""
def __init__(self, total, solved, locked, others=None):
""":param total: total problems nums :param solved: solved problem nums :param others: 暂时还没用，我想做扩展"""
self.total = total
... | the_stack_v2_python_sparse | scripts/readme.py | bbruceyuan/algorithms-and-oj | train | 11 |
6364968a8d0c1cb2c18f1c467261b272386e1e38 | [
"user = get_authentication(self.request)\nqueryset = Favorites.objects.filter(user=user, is_used=True)\nreturn queryset",
"if self.request.method == 'GET':\n serializer_class = FavoriteModelSerializer\nelif self.request.method == 'POST':\n serializer_class = FavoriteCreateSerializer\nelif self.action == 'de... | <|body_start_0|>
user = get_authentication(self.request)
queryset = Favorites.objects.filter(user=user, is_used=True)
return queryset
<|end_body_0|>
<|body_start_1|>
if self.request.method == 'GET':
serializer_class = FavoriteModelSerializer
elif self.request.method ... | Create favorite items and delete them as well. | FavoritesView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FavoritesView:
"""Create favorite items and delete them as well."""
def get_queryset(self):
"""Get the favorite items of the user."""
<|body_0|>
def get_serializer_class(self, *args, **kwargs):
"""Get the serializer class depending of the request method."""
... | stack_v2_sparse_classes_36k_train_028367 | 12,742 | no_license | [
{
"docstring": "Get the favorite items of the user.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Get the serializer class depending of the request method.",
"name": "get_serializer_class",
"signature": "def get_serializer_class(self, *args, **kwargs)... | 6 | stack_v2_sparse_classes_30k_train_007347 | Implement the Python class `FavoritesView` described below.
Class description:
Create favorite items and delete them as well.
Method signatures and docstrings:
- def get_queryset(self): Get the favorite items of the user.
- def get_serializer_class(self, *args, **kwargs): Get the serializer class depending of the req... | Implement the Python class `FavoritesView` described below.
Class description:
Create favorite items and delete them as well.
Method signatures and docstrings:
- def get_queryset(self): Get the favorite items of the user.
- def get_serializer_class(self, *args, **kwargs): Get the serializer class depending of the req... | cd8767b5eeaef3a09d77c936781b4126fd8591de | <|skeleton|>
class FavoritesView:
"""Create favorite items and delete them as well."""
def get_queryset(self):
"""Get the favorite items of the user."""
<|body_0|>
def get_serializer_class(self, *args, **kwargs):
"""Get the serializer class depending of the request method."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FavoritesView:
"""Create favorite items and delete them as well."""
def get_queryset(self):
"""Get the favorite items of the user."""
user = get_authentication(self.request)
queryset = Favorites.objects.filter(user=user, is_used=True)
return queryset
def get_serialize... | the_stack_v2_python_sparse | api/services/views.py | ignite7/backproject | train | 0 |
654b20e76d60557a7104d47149aaff209de3d9d1 | [
"self.big = big\nself.medium = medium\nself.small = small",
"if carType == 1:\n if self.big == 0:\n return False\n else:\n self.big -= 1\n return True\nelif carType == 2:\n if self.medium == 0:\n return False\n else:\n self.medium -= 1\n return True\nelif carT... | <|body_start_0|>
self.big = big
self.medium = medium
self.small = small
<|end_body_0|>
<|body_start_1|>
if carType == 1:
if self.big == 0:
return False
else:
self.big -= 1
return True
elif carType == 2:
... | ParkingSystem | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.big = big
... | stack_v2_sparse_classes_36k_train_028368 | 1,674 | permissive | [
{
"docstring": ":type big: int :type medium: int :type small: int",
"name": "__init__",
"signature": "def __init__(self, big, medium, small)"
},
{
"docstring": ":type carType: int :rtype: bool",
"name": "addCar",
"signature": "def addCar(self, carType)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000476 | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool | Implement the Python class `ParkingSystem` described below.
Class description:
Implement the ParkingSystem class.
Method signatures and docstrings:
- def __init__(self, big, medium, small): :type big: int :type medium: int :type small: int
- def addCar(self, carType): :type carType: int :rtype: bool
<|skeleton|>
cla... | b19ae99715f4b7a0d95e32b128a3679e6a298a6f | <|skeleton|>
class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
<|body_0|>
def addCar(self, carType):
""":type carType: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParkingSystem:
def __init__(self, big, medium, small):
""":type big: int :type medium: int :type small: int"""
self.big = big
self.medium = medium
self.small = small
def addCar(self, carType):
""":type carType: int :rtype: bool"""
if carType == 1:
... | the_stack_v2_python_sparse | 1603_design_parking_system.py | mjtsai/leetcode | train | 0 | |
333747b2aa8ee2f33516b982a945f2998eeae0e3 | [
"a = AssetResolver('pyramid_oereb')\nresolver = a.resolve('lib/renderer/getegrid/templates/xml')\nself.template_dir = resolver.abspath()\nsuper(Renderer, self).__init__(info)",
"response = self.get_response(system)\nif isinstance(response, Response) and response.content_type == response.default_content_type:\n ... | <|body_start_0|>
a = AssetResolver('pyramid_oereb')
resolver = a.resolve('lib/renderer/getegrid/templates/xml')
self.template_dir = resolver.abspath()
super(Renderer, self).__init__(info)
<|end_body_0|>
<|body_start_1|>
response = self.get_response(system)
if isinstance(... | Renderer | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Renderer:
def __init__(self, info):
"""Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object."""
<|body_0|>
def __call__(self, value, system):
"""Returns the XML encoded versions response according to t... | stack_v2_sparse_classes_36k_train_028369 | 1,690 | permissive | [
{
"docstring": "Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object.",
"name": "__init__",
"signature": "def __init__(self, info)"
},
{
"docstring": "Returns the XML encoded versions response according to the specification. Args:... | 2 | stack_v2_sparse_classes_30k_train_015188 | Implement the Python class `Renderer` described below.
Class description:
Implement the Renderer class.
Method signatures and docstrings:
- def __init__(self, info): Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object.
- def __call__(self, value, syst... | Implement the Python class `Renderer` described below.
Class description:
Implement the Renderer class.
Method signatures and docstrings:
- def __init__(self, info): Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object.
- def __call__(self, value, syst... | 767375a4adda4589e12c4257377fc30258cdfcb3 | <|skeleton|>
class Renderer:
def __init__(self, info):
"""Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object."""
<|body_0|>
def __call__(self, value, system):
"""Returns the XML encoded versions response according to t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Renderer:
def __init__(self, info):
"""Creates a new XML renderer instance for versions rendering. Args: info (pyramid.interfaces.IRendererInfo): Info object."""
a = AssetResolver('pyramid_oereb')
resolver = a.resolve('lib/renderer/getegrid/templates/xml')
self.template_dir = r... | the_stack_v2_python_sparse | pyramid_oereb/lib/renderer/getegrid/xml_.py | geo-bl-ch/pyramid_oereb | train | 0 | |
ec64bda35758a1c7da117bb9d1231a9c11a4aae0 | [
"for line in self:\n price = line.price_unit * (1 - (line.discount or 0.0) / 100.0) * (1 - (line.discount2 or 0.0) / 100.0)\n taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shipping_id)\n line.update({'price_tax... | <|body_start_0|>
for line in self:
price = line.price_unit * (1 - (line.discount or 0.0) / 100.0) * (1 - (line.discount2 or 0.0) / 100.0)
taxes = line.tax_id.compute_all(price, line.order_id.currency_id, line.product_uom_qty, product=line.product_id, partner=line.order_id.partner_shippin... | SalesOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SalesOrder:
def _compute_amount(self):
"""Compute the amounts of the SO line."""
<|body_0|>
def _prepare_invoice_line(self, qty):
"""Prepare the dict of values to create the new invoice line for a sales order line. :param qty: float quantity to invoice"""
<|b... | stack_v2_sparse_classes_36k_train_028370 | 3,359 | no_license | [
{
"docstring": "Compute the amounts of the SO line.",
"name": "_compute_amount",
"signature": "def _compute_amount(self)"
},
{
"docstring": "Prepare the dict of values to create the new invoice line for a sales order line. :param qty: float quantity to invoice",
"name": "_prepare_invoice_lin... | 2 | stack_v2_sparse_classes_30k_train_011198 | Implement the Python class `SalesOrder` described below.
Class description:
Implement the SalesOrder class.
Method signatures and docstrings:
- def _compute_amount(self): Compute the amounts of the SO line.
- def _prepare_invoice_line(self, qty): Prepare the dict of values to create the new invoice line for a sales o... | Implement the Python class `SalesOrder` described below.
Class description:
Implement the SalesOrder class.
Method signatures and docstrings:
- def _compute_amount(self): Compute the amounts of the SO line.
- def _prepare_invoice_line(self, qty): Prepare the dict of values to create the new invoice line for a sales o... | 29909a40920ef3b6a8c6a1f311a8ad67cb6a7985 | <|skeleton|>
class SalesOrder:
def _compute_amount(self):
"""Compute the amounts of the SO line."""
<|body_0|>
def _prepare_invoice_line(self, qty):
"""Prepare the dict of values to create the new invoice line for a sales order line. :param qty: float quantity to invoice"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SalesOrder:
def _compute_amount(self):
"""Compute the amounts of the SO line."""
for line in self:
price = line.price_unit * (1 - (line.discount or 0.0) / 100.0) * (1 - (line.discount2 or 0.0) / 100.0)
taxes = line.tax_id.compute_all(price, line.order_id.currency_id, li... | the_stack_v2_python_sparse | custom/sales_order/models/sale_order.py | Rombituon-Resource/TRIMITRA | train | 0 | |
0a6f27ff0884cfe3fa3210adc5d6a3db4eb50b21 | [
"ls_lines = FileUtil.ReadLines(ENF_file)\nls_record = []\nfor line in ls_lines:\n ls_record.append(line[:-1].split(';'))\nls_ENF = []\nfor record in ls_record:\n ls_ENF.append(format(float(record[0]), '.2f'))\njson_ENF = {}\njson_ENF['id'] = ENF_file\njson_ENF['ENF'] = ls_ENF\nreturn json_ENF",
"ls_time_exe... | <|body_start_0|>
ls_lines = FileUtil.ReadLines(ENF_file)
ls_record = []
for line in ls_lines:
ls_record.append(line[:-1].split(';'))
ls_ENF = []
for record in ls_record:
ls_ENF.append(format(float(record[0]), '.2f'))
json_ENF = {}
json_ENF[... | TenderUtils | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenderUtils:
def load_ENF(ENF_file):
"""Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data"""
<|body_0|>
def verify_ENF(ENF_file):
"""Verify ENF value by querying from blockchain Args: ENF_name: ENF file name Returns: Ve... | stack_v2_sparse_classes_36k_train_028371 | 9,913 | no_license | [
{
"docstring": "Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data",
"name": "load_ENF",
"signature": "def load_ENF(ENF_file)"
},
{
"docstring": "Verify ENF value by querying from blockchain Args: ENF_name: ENF file name Returns: Verified result: Tr... | 3 | stack_v2_sparse_classes_30k_train_016821 | Implement the Python class `TenderUtils` described below.
Class description:
Implement the TenderUtils class.
Method signatures and docstrings:
- def load_ENF(ENF_file): Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data
- def verify_ENF(ENF_file): Verify ENF value by qu... | Implement the Python class `TenderUtils` described below.
Class description:
Implement the TenderUtils class.
Method signatures and docstrings:
- def load_ENF(ENF_file): Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data
- def verify_ENF(ENF_file): Verify ENF value by qu... | 03ff57e6fe0114ffd2dd953e79a73a893a6bc0ad | <|skeleton|>
class TenderUtils:
def load_ENF(ENF_file):
"""Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data"""
<|body_0|>
def verify_ENF(ENF_file):
"""Verify ENF value by querying from blockchain Args: ENF_name: ENF file name Returns: Ve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TenderUtils:
def load_ENF(ENF_file):
"""Load ENF data from ENF_file Args: ENF_name: ENF file name Returns: json_ENF: json format ENF data"""
ls_lines = FileUtil.ReadLines(ENF_file)
ls_record = []
for line in ls_lines:
ls_record.append(line[:-1].split(';'))
l... | the_stack_v2_python_sparse | Security/py_dev/BlendSPS/src/service_utils.py | samuelxu999/Research | train | 1 | |
7a45c01e5d8c04ca245da452b3c38e1ef9225b54 | [
"with open(self.location, 'r') as csvfile:\n reader = csv.DictReader(csvfile)\n return reader.fieldnames",
"try:\n with open(self.location, 'r') as csvfile:\n reader = csv.DictReader(csvfile)\n if params is None:\n params = {}\n rows = []\n for row in reader:\n ... | <|body_start_0|>
with open(self.location, 'r') as csvfile:
reader = csv.DictReader(csvfile)
return reader.fieldnames
<|end_body_0|>
<|body_start_1|>
try:
with open(self.location, 'r') as csvfile:
reader = csv.DictReader(csvfile)
if par... | Data connector for retrieving data from CSV files. | CsvConnector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CsvConnector:
"""Data connector for retrieving data from CSV files."""
def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None):
"""Return a JSON response from a CSV file. :param params: Query params - ignored :return: Metadata"""
<|body_0|>
def get... | stack_v2_sparse_classes_36k_train_028372 | 5,585 | permissive | [
{
"docstring": "Return a JSON response from a CSV file. :param params: Query params - ignored :return: Metadata",
"name": "get_metadata",
"signature": "def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None)"
},
{
"docstring": "Return a JSON response from a CSV file. CSV f... | 2 | null | Implement the Python class `CsvConnector` described below.
Class description:
Data connector for retrieving data from CSV files.
Method signatures and docstrings:
- def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None): Return a JSON response from a CSV file. :param params: Query params - ign... | Implement the Python class `CsvConnector` described below.
Class description:
Data connector for retrieving data from CSV files.
Method signatures and docstrings:
- def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None): Return a JSON response from a CSV file. :param params: Query params - ign... | 25a111ac7cf4b23fee50ad8eac6ea21564954859 | <|skeleton|>
class CsvConnector:
"""Data connector for retrieving data from CSV files."""
def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None):
"""Return a JSON response from a CSV file. :param params: Query params - ignored :return: Metadata"""
<|body_0|>
def get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CsvConnector:
"""Data connector for retrieving data from CSV files."""
def get_metadata(self, params: typing.Optional[typing.Mapping[str, str]]=None):
"""Return a JSON response from a CSV file. :param params: Query params - ignored :return: Metadata"""
with open(self.location, 'r') as csv... | the_stack_v2_python_sparse | datasources/connectors/csv.py | PEDASI/PEDASI | train | 0 |
dc8603948e13bba6de24566639f318c78b85c9cb | [
"queryset = get_user_model().objects.all()\nserializer = ProfileSerializer(queryset, many=True)\nreturn Response(serializer.data)",
"data = request.data.get('profile')\nif not data:\n return Response({'response': 'error', 'message': 'profile 파라미터가 없습니다.'})\nserializer = ProfileSerializer(data=data)\nif seriali... | <|body_start_0|>
queryset = get_user_model().objects.all()
serializer = ProfileSerializer(queryset, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
data = request.data.get('profile')
if not data:
return Response({'response': 'error', 'mess... | CreateProfileView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateProfileView:
def get(self, request, *args, **kwargs):
"""# 기능 전체 유저 조회"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""# 기능 회원 가입 # example { "profile": { "username": "rkdalstjd1", "password": "password1", "email": "rkdalstjd9@naver.com", "nickname":... | stack_v2_sparse_classes_36k_train_028373 | 13,056 | no_license | [
{
"docstring": "# 기능 전체 유저 조회",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "# 기능 회원 가입 # example { \"profile\": { \"username\": \"rkdalstjd1\", \"password\": \"password1\", \"email\": \"rkdalstjd9@naver.com\", \"nickname\": \"사장님2\", \"address\": \"서울... | 2 | stack_v2_sparse_classes_30k_train_003045 | Implement the Python class `CreateProfileView` described below.
Class description:
Implement the CreateProfileView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): # 기능 전체 유저 조회
- def post(self, request, *args, **kwargs): # 기능 회원 가입 # example { "profile": { "username": "rkdalstjd1",... | Implement the Python class `CreateProfileView` described below.
Class description:
Implement the CreateProfileView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): # 기능 전체 유저 조회
- def post(self, request, *args, **kwargs): # 기능 회원 가입 # example { "profile": { "username": "rkdalstjd1",... | e7b1638a15a804faf513e25da57c4a2202b5cc0d | <|skeleton|>
class CreateProfileView:
def get(self, request, *args, **kwargs):
"""# 기능 전체 유저 조회"""
<|body_0|>
def post(self, request, *args, **kwargs):
"""# 기능 회원 가입 # example { "profile": { "username": "rkdalstjd1", "password": "password1", "email": "rkdalstjd9@naver.com", "nickname":... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateProfileView:
def get(self, request, *args, **kwargs):
"""# 기능 전체 유저 조회"""
queryset = get_user_model().objects.all()
serializer = ProfileSerializer(queryset, many=True)
return Response(serializer.data)
def post(self, request, *args, **kwargs):
"""# 기능 회원 가입 # ... | the_stack_v2_python_sparse | laundry_guest/backend/src/project/myauth/views.py | serverdevcamp/camp4_ing | train | 2 | |
3659d158856a2feeb2e0680b0bf2eb2142f1c3a5 | [
"k = None\ngo = True\nfor i in range(len(nums) - 1, -1, -1):\n for j in range(i + 1, len(nums)):\n if nums[i] < nums[j] and (k is None or nums[j] < nums[k]):\n k = j\n if k is not None:\n nums[i], nums[k] = (nums[k], nums[i])\n nums[i + 1:] = sorted(nums[i + 1:])\n break... | <|body_start_0|>
k = None
go = True
for i in range(len(nums) - 1, -1, -1):
for j in range(i + 1, len(nums)):
if nums[i] < nums[j] and (k is None or nums[j] < nums[k]):
k = j
if k is not None:
nums[i], nums[k] = (nums[k],... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_028374 | 2,067 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.",
"name": "nextPermutation",
"signature": "def nextPermutation(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permuteUnique",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_013959 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def permuteUnique(self, nums): :type nums: List[int] :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextPermutation(self, nums): :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead.
- def permuteUnique(self, nums): :type nums: List[int] :... | c026f2969c784827fac702b34b07a9268b70b62a | <|skeleton|>
class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def nextPermutation(self, nums):
""":type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead."""
k = None
go = True
for i in range(len(nums) - 1, -1, -1):
for j in range(i + 1, len(nums)):
if nums[i] < nums[j]... | the_stack_v2_python_sparse | codes/contest/leetcode/permutations-ii.py | jiluhu/dirtysalt.github.io | train | 0 | |
e56ef8154e810b318a2c122efcf9df289d6bd2a6 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline. | AssetServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssetServiceServicer:
"""Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline."""
def GetAsset(self, request, context):
"""Ret... | stack_v2_sparse_classes_36k_train_028375 | 5,542 | permissive | [
{
"docstring": "Returns the requested asset in full detail.",
"name": "GetAsset",
"signature": "def GetAsset(self, request, context)"
},
{
"docstring": "Creates assets. Operation statuses are returned.",
"name": "MutateAssets",
"signature": "def MutateAssets(self, request, context)"
}
... | 2 | stack_v2_sparse_classes_30k_train_020666 | Implement the Python class `AssetServiceServicer` described below.
Class description:
Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline.
Method signatures an... | Implement the Python class `AssetServiceServicer` described below.
Class description:
Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline.
Method signatures an... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class AssetServiceServicer:
"""Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline."""
def GetAsset(self, request, context):
"""Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssetServiceServicer:
"""Proto file describing the Asset service. Service to manage assets. Asset types can be created with AssetService are YoutubeVideoAsset, MediaBundleAsset and ImageAsset. TextAsset should be created with Ad inline."""
def GetAsset(self, request, context):
"""Returns the requ... | the_stack_v2_python_sparse | google/ads/google_ads/v5/proto/services/asset_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
1bf36e0a628b420712ed774573a5788398be10fb | [
"self.data_dir = data_dir\nself.batch_size = batch_size\nself.image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms_face_recog[x]) for x in ['train', 'val']}\nself.dataloaders = {x: torch.utils.data.DataLoader(self.image_datasets[x], batch_size=self.batch_size, shuffle=True, num_worke... | <|body_start_0|>
self.data_dir = data_dir
self.batch_size = batch_size
self.image_datasets = {x: datasets.ImageFolder(os.path.join(data_dir, x), data_transforms_face_recog[x]) for x in ['train', 'val']}
self.dataloaders = {x: torch.utils.data.DataLoader(self.image_datasets[x], batch_size... | A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verification of dataloaders | LoadFaceDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoadFaceDataset:
"""A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verification of dataloaders"""
def __init... | stack_v2_sparse_classes_36k_train_028376 | 9,192 | permissive | [
{
"docstring": "Initialize the class object. Dataset class ojbect",
"name": "__init__",
"signature": "def __init__(self, data_dir, batch_size)"
},
{
"docstring": "Show five sample images for verification of dataloaders. Get item internal fuction",
"name": "show_batch",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_014224 | Implement the Python class `LoadFaceDataset` described below.
Class description:
A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verific... | Implement the Python class `LoadFaceDataset` described below.
Class description:
A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verific... | 7c551e3894979cc425dd51baeddbfa5a51b7878d | <|skeleton|>
class LoadFaceDataset:
"""A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verification of dataloaders"""
def __init... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoadFaceDataset:
"""A class to dataset with its loader. ... Attributes ---------- dataloaders : torch dataloader dataset_sizes : length of train and validation dataset class_names : class names Methods ------- show_batch: Shows five sample images for verification of dataloaders"""
def __init__(self, data... | the_stack_v2_python_sparse | Modules/data_loader.py | EVA4-RS-Group/Phase2 | train | 0 |
6f4cb55a74da7b43fc3207dbc5a2f8ed41a29270 | [
"self.p = p\nself.k = k\nself.dat = dat",
"J = V.shape[0]\nX = self.dat.data()\nn, d = X.shape\nfssd = FSSD(self.p, self.k, V, null_sim=None, alpha=None)\nblock_rows = util.constrain(50000 // (d * J), 10, 5000)\navg_rows = []\nfor f, t in util.ChunkIterable(start=0, end=n, chunk_size=block_rows):\n assert f < ... | <|body_start_0|>
self.p = p
self.k = k
self.dat = dat
<|end_body_0|>
<|body_start_1|>
J = V.shape[0]
X = self.dat.data()
n, d = X.shape
fssd = FSSD(self.p, self.k, V, null_sim=None, alpha=None)
block_rows = util.constrain(50000 // (d * J), 10, 5000)
... | Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS 2017 The witness function requires taking an expectation over the sample gener... | SteinWitness | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SteinWitness:
"""Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS 2017 The witness function requires tak... | stack_v2_sparse_classes_36k_train_028377 | 41,550 | permissive | [
{
"docstring": ":params p: an UnnormalizedDensity object :params k: a DifferentiableKernel :params dat: a kgof.data.Data",
"name": "__init__",
"signature": "def __init__(self, p, k, dat)"
},
{
"docstring": ":params V: a numpy array of size J x d (data matrix) :returns (J x d) numpy array represe... | 2 | stack_v2_sparse_classes_30k_train_006106 | Implement the Python class `SteinWitness` described below.
Class description:
Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS... | Implement the Python class `SteinWitness` described below.
Class description:
Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS... | 039a95ed9d8062e283da6bd051b7161a190b4876 | <|skeleton|>
class SteinWitness:
"""Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS 2017 The witness function requires tak... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SteinWitness:
"""Construct a callable object representing the Stein witness function. The witness function g is defined as in Eq. 1 of A Linear-Time Kernel Goodness-of-Fit Test Wittawat Jitkrittum, Wenkai Xu, Zoltan Szabo, Kenji Fukumizu, Arthur Gretton NIPS 2017 The witness function requires taking an expect... | the_stack_v2_python_sparse | kgof/goftest.py | wittawatj/kernel-gof | train | 69 |
5fcbf9e26312bdeb82d6991a2b3d7997501675eb | [
"src_type, src_path = cls.identify_path_type(src)\ndest_type, dest_path = cls.identify_path_type(dest)\nformat_table = {'s3': cls.format_s3_path, 'local': cls.format_local_path}\nsrc_path = format_table[src_type](src_path)[0]\ndest_path, use_src_name = format_table[dest_type](dest_path)\nreturn {'dest': {'path': de... | <|body_start_0|>
src_type, src_path = cls.identify_path_type(src)
dest_type, dest_path = cls.identify_path_type(dest)
format_table = {'s3': cls.format_s3_path, 'local': cls.format_local_path}
src_path = format_table[src_type](src_path)[0]
dest_path, use_src_name = format_table[de... | Path format base class. | FormatPath | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
<|body_0|>
def format_local_path(path: str, dir_op: bool=True) -> Tuple[str, bool]:
"""Format ... | stack_v2_sparse_classes_36k_train_028378 | 4,460 | permissive | [
{
"docstring": "Format the source and destination for use in the file factory.",
"name": "format",
"signature": "def format(cls, src: str, dest: str) -> FormatPathResult"
},
{
"docstring": "Format the path of local files. Returns whether the destination will keep its own name or take the source'... | 4 | stack_v2_sparse_classes_30k_train_020115 | Implement the Python class `FormatPath` described below.
Class description:
Path format base class.
Method signatures and docstrings:
- def format(cls, src: str, dest: str) -> FormatPathResult: Format the source and destination for use in the file factory.
- def format_local_path(path: str, dir_op: bool=True) -> Tupl... | Implement the Python class `FormatPath` described below.
Class description:
Path format base class.
Method signatures and docstrings:
- def format(cls, src: str, dest: str) -> FormatPathResult: Format the source and destination for use in the file factory.
- def format_local_path(path: str, dir_op: bool=True) -> Tupl... | 0763b06aee07d2cf3f037a49ca0cb81a048c5deb | <|skeleton|>
class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
<|body_0|>
def format_local_path(path: str, dir_op: bool=True) -> Tuple[str, bool]:
"""Format ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FormatPath:
"""Path format base class."""
def format(cls, src: str, dest: str) -> FormatPathResult:
"""Format the source and destination for use in the file factory."""
src_type, src_path = cls.identify_path_type(src)
dest_type, dest_path = cls.identify_path_type(dest)
for... | the_stack_v2_python_sparse | runway/core/providers/aws/s3/_helpers/format_path.py | onicagroup/runway | train | 156 |
62f96a6d2ff09586914263ebfbdb2827d8ad5e38 | [
"view = cls.as_view('annual_expenses')\napp.add_url_rule('/api/budgets/<int:budget_id>/annual-expenses', defaults={'expense_id': None}, view_func=view, methods=['GET'])\napp.add_url_rule('/api/budgets/<int:budget_id>/annual-expenses', view_func=view, methods=['POST'])\napp.add_url_rule('/api/budget-annual-expenses/... | <|body_start_0|>
view = cls.as_view('annual_expenses')
app.add_url_rule('/api/budgets/<int:budget_id>/annual-expenses', defaults={'expense_id': None}, view_func=view, methods=['GET'])
app.add_url_rule('/api/budgets/<int:budget_id>/annual-expenses', view_func=view, methods=['POST'])
app.a... | Annual expense REST resource view | AnnualExpensesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnnualExpensesView:
"""Annual expense REST resource view"""
def register(cls, app: Flask):
"""Registers routes for this view"""
<|body_0|>
def get(budget_id: Optional[int], expense_id: Optional[int]):
"""Gets a specific annual expense or all expenses in the speci... | stack_v2_sparse_classes_36k_train_028379 | 17,779 | permissive | [
{
"docstring": "Registers routes for this view",
"name": "register",
"signature": "def register(cls, app: Flask)"
},
{
"docstring": "Gets a specific annual expense or all expenses in the specified budget",
"name": "get",
"signature": "def get(budget_id: Optional[int], expense_id: Optiona... | 5 | stack_v2_sparse_classes_30k_train_012066 | Implement the Python class `AnnualExpensesView` described below.
Class description:
Annual expense REST resource view
Method signatures and docstrings:
- def register(cls, app: Flask): Registers routes for this view
- def get(budget_id: Optional[int], expense_id: Optional[int]): Gets a specific annual expense or all ... | Implement the Python class `AnnualExpensesView` described below.
Class description:
Annual expense REST resource view
Method signatures and docstrings:
- def register(cls, app: Flask): Registers routes for this view
- def get(budget_id: Optional[int], expense_id: Optional[int]): Gets a specific annual expense or all ... | 20d992356952542fd79aab69849a04129fa22de2 | <|skeleton|>
class AnnualExpensesView:
"""Annual expense REST resource view"""
def register(cls, app: Flask):
"""Registers routes for this view"""
<|body_0|>
def get(budget_id: Optional[int], expense_id: Optional[int]):
"""Gets a specific annual expense or all expenses in the speci... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnnualExpensesView:
"""Annual expense REST resource view"""
def register(cls, app: Flask):
"""Registers routes for this view"""
view = cls.as_view('annual_expenses')
app.add_url_rule('/api/budgets/<int:budget_id>/annual-expenses', defaults={'expense_id': None}, view_func=view, met... | the_stack_v2_python_sparse | backend/underbudget/views/budgets.py | vimofthevine/underbudget4 | train | 0 |
075e78da05c720e4cfb0370919761dff851a46be | [
"if not root:\n return 0\nchildren = [root.left, root.right]\nif not any(children):\n return 1\nmin_depth = float('inf')\nfor x in children:\n if x:\n min_depth = min(self.minDepth_BFS_recursion(x), min_depth)\nreturn min_depth + 1\npass",
"if not root:\n return 0\nstack = deque([(root, 1)])\nw... | <|body_start_0|>
if not root:
return 0
children = [root.left, root.right]
if not any(children):
return 1
min_depth = float('inf')
for x in children:
if x:
min_depth = min(self.minDepth_BFS_recursion(x), min_depth)
return... | 1.栈 2.递归 return: 返回数字代表二叉树的深度。 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""1.栈 2.递归 return: 返回数字代表二叉树的深度。"""
def minDepth_DFS_recursion(self, root: TreeNode):
"""递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :return:"""
<|body_0|>
def minDepth_BFS_queue(... | stack_v2_sparse_classes_36k_train_028380 | 2,378 | no_license | [
{
"docstring": "递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :return:",
"name": "minDepth_DFS_recursion",
"signature": "def minDepth_DFS_recursion(self, root: TreeNode)"
},
{
"docstring": ":param root: :return:",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
1.栈 2.递归 return: 返回数字代表二叉树的深度。
Method signatures and docstrings:
- def minDepth_DFS_recursion(self, root: TreeNode): 递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :r... | Implement the Python class `Solution` described below.
Class description:
1.栈 2.递归 return: 返回数字代表二叉树的深度。
Method signatures and docstrings:
- def minDepth_DFS_recursion(self, root: TreeNode): 递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :r... | 62ad010a992c031e8c0fe4d1a9b6f9364f96ed4c | <|skeleton|>
class Solution:
"""1.栈 2.递归 return: 返回数字代表二叉树的深度。"""
def minDepth_DFS_recursion(self, root: TreeNode):
"""递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :return:"""
<|body_0|>
def minDepth_BFS_queue(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""1.栈 2.递归 return: 返回数字代表二叉树的深度。"""
def minDepth_DFS_recursion(self, root: TreeNode):
"""递归遍历，找出最小深度 复杂度分析 N - 节点数量 时间复杂度：O(N) 访问所有节点一次 空间复杂度： 最坏情况下，树是非平衡树，O(N) 最好情况下，完全平衡树，高度只有log(N)，这时复杂度只有O(log(N)) :param root: :return:"""
if not root:
return 0
children =... | the_stack_v2_python_sparse | leetcode/solved/111_.py | usnnu/python_foundation | train | 0 |
5ab1ef018811ab2e46fbd5412ac2ca820e9a5588 | [
"try:\n setattr(type(self), '__optimize_not_implemented__', True)\n out = self.self_optimize_with_info(dataset, **kwargs)[0]\n delattr(type(self), '__optimize_not_implemented__')\nexcept NotImplementedError as e:\n raise NotImplementedError() from e\nreturn out",
"try:\n if getattr(type(self), '__o... | <|body_start_0|>
try:
setattr(type(self), '__optimize_not_implemented__', True)
out = self.self_optimize_with_info(dataset, **kwargs)[0]
delattr(type(self), '__optimize_not_implemented__')
except NotImplementedError as e:
raise NotImplementedError() from e... | Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp.pipelines.GridSearch` should be used directly.... | OptimizablePipeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp... | stack_v2_sparse_classes_36k_train_028381 | 7,840 | permissive | [
{
"docstring": "Optimize the input parameters of the pipeline or algorithm using any logic. This method can be used to adapt the input parameters (values provided in the init) based on any data driven heuristic. .. note:: The optimizations must only modify the input parameters (aka `self.clone` should retain th... | 2 | stack_v2_sparse_classes_30k_train_013845 | Implement the Python class `OptimizablePipeline` described below.
Class description:
Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or... | Implement the Python class `OptimizablePipeline` described below.
Class description:
Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or... | 75b958ee691d6d5b0eee070c1eb20d1017ec619b | <|skeleton|>
class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp.pipelines.Gr... | the_stack_v2_python_sparse | tpcp/_pipeline.py | mad-lab-fau/tpcp | train | 11 |
3ebe466b39a087faf193e6e556191f7af318a320 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AuthenticationMethodsPolicy()",
"from .authentication_method_configuration import AuthenticationMethodConfiguration\nfrom .authentication_methods_policy_migration_state import AuthenticationMethodsPolicyMigrationState\nfrom .entity imp... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AuthenticationMethodsPolicy()
<|end_body_0|>
<|body_start_1|>
from .authentication_method_configuration import AuthenticationMethodConfiguration
from .authentication_methods_policy_migra... | AuthenticationMethodsPolicy | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationMethodsPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationMethodsPolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_36k_train_028382 | 5,875 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AuthenticationMethodsPolicy",
"name": "create_from_discriminator_value",
"signature": "def create_from_discr... | 3 | null | Implement the Python class `AuthenticationMethodsPolicy` described below.
Class description:
Implement the AuthenticationMethodsPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationMethodsPolicy: Creates a new instance of the appr... | Implement the Python class `AuthenticationMethodsPolicy` described below.
Class description:
Implement the AuthenticationMethodsPolicy class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationMethodsPolicy: Creates a new instance of the appr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AuthenticationMethodsPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationMethodsPolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthenticationMethodsPolicy:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AuthenticationMethodsPolicy:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | the_stack_v2_python_sparse | msgraph/generated/models/authentication_methods_policy.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
74e3565f82b2a7eb54cdf3d676b33f0c4d62fc49 | [
"self.screen_width = 1200\nself.screen_height = 800\nself.bg_color = (230, 230, 230)\nself.ship_limit = 3\nself.bullet_width = 10\nself.bullet_height = 15\nself.bullet_color = (60, 60, 60)\nself.bullets_allowed = 6\nself.fleet_drop_speed = 20\nself.speedup_scale = 1.1\nself.score_scale = 1.5\nself.initialize_dynami... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = 15
self.bullet_color = (60, 60, 60)
self.bullets_allowed = 6
self.fleet_drop_speed = ... | 存储《外星人入侵》的所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随着游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_028383 | 1,704 | no_license | [
{
"docstring": "初始化游戏的静态设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随着游戏进行而变化的设置",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"docstring": "提高速度设置",
"name": "increase_speed",
"signa... | 3 | stack_v2_sparse_classes_30k_train_002956 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的静态设置
- def initialize_dynamic_settings(self): 初始化随着游戏进行而变化的设置
- def increase_speed(self): 提高速度设置 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的静态设置
- def initialize_dynamic_settings(self): 初始化随着游戏进行而变化的设置
- def increase_speed(self): 提高速度设置
<|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __... | 61e92d51227962d361123109d5d4a2b460175069 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随着游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的静态设置"""
self.screen_width = 1200
self.screen_height = 800
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 10
self.bullet_height = 15
self.bullet_color = (6... | the_stack_v2_python_sparse | aliens/settings.py | yangrencong/pythonstudy | train | 0 |
94d722f388d674c4b4bb8fdf9a1434a2c73d061e | [
"super(AgeFilter, self).__init__(order)\nself.age = age\nself.ageField = ageField\nself.ageTolerance = ageTolerance\nif self.ageTolerance < 0:\n self.ageTolerance = 0\nself.minAgeField = minAgeField\nself.maxAgeField = maxAgeField\nself.rejectUnclassified = rejectUnclassified",
"for result in results:\n if ... | <|body_start_0|>
super(AgeFilter, self).__init__(order)
self.age = age
self.ageField = ageField
self.ageTolerance = ageTolerance
if self.ageTolerance < 0:
self.ageTolerance = 0
self.minAgeField = minAgeField
self.maxAgeField = maxAgeField
self.... | Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age (integer) : the age of t... | AgeFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_36k_train_028384 | 2,776 | permissive | [
{
"docstring": "Constructor for AgeFilter",
"name": "__init__",
"signature": "def __init__(self, age, ageField=None, ageTolerance=3, minAgeField='minAge', maxAgeField='maxAge', order=0, rejectUnclassified=False)"
},
{
"docstring": "Filters the results according to a given range in which the resu... | 2 | stack_v2_sparse_classes_30k_train_013863 | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | Implement the Python class `AgeFilter` described below.
Class description:
Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using ... | ed72aee466649bd834d5b4459eb6e0173df6e2ec | <|skeleton|>
class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter prec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AgeFilter:
"""Filters search results based on either a specific age or if the age is within an age range defined by the result. Note: there is no default value for 'age' it must be passed to this filter so that it can be customised for the application using it. Options: * order (int): filter precedence * age ... | the_stack_v2_python_sparse | reference-code/puppy/result/filter/ageFilter.py | Granvanoeli/ifind | train | 0 |
8c69076d6771f495c32aedeb40fa7c6e1815beae | [
"assert next is Node.empty or isinstance(next, Node)\nself.item = item\nself.next = next",
"if self.next:\n next_str = ', ' + repr(self.next)\nelse:\n next_str = ''\nreturn 'Node({0}{1})'.format(self.item, next_str)"
] | <|body_start_0|>
assert next is Node.empty or isinstance(next, Node)
self.item = item
self.next = next
<|end_body_0|>
<|body_start_1|>
if self.next:
next_str = ', ' + repr(self.next)
else:
next_str = ''
return 'Node({0}{1})'.format(self.item, next... | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
def __init__(self, item, next=empty):
"""init a node"""
<|body_0|>
def __repr__(self):
"""它实现Node类的repr()函数"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert next is Node.empty or isinstance(next, Node)
self.item = item
se... | stack_v2_sparse_classes_36k_train_028385 | 3,171 | no_license | [
{
"docstring": "init a node",
"name": "__init__",
"signature": "def __init__(self, item, next=empty)"
},
{
"docstring": "它实现Node类的repr()函数",
"name": "__repr__",
"signature": "def __repr__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019671 | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, item, next=empty): init a node
- def __repr__(self): 它实现Node类的repr()函数 | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, item, next=empty): init a node
- def __repr__(self): 它实现Node类的repr()函数
<|skeleton|>
class Node:
def __init__(self, item, next=empty):
"""init a node"""
... | c431569ae08fb77c67e948f5ded75c306af20ba2 | <|skeleton|>
class Node:
def __init__(self, item, next=empty):
"""init a node"""
<|body_0|>
def __repr__(self):
"""它实现Node类的repr()函数"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
def __init__(self, item, next=empty):
"""init a node"""
assert next is Node.empty or isinstance(next, Node)
self.item = item
self.next = next
def __repr__(self):
"""它实现Node类的repr()函数"""
if self.next:
next_str = ', ' + repr(self.next)
... | the_stack_v2_python_sparse | algo-lib/1_basic/Python/LinkedQueue.py | itrowa/arsenal | train | 0 | |
197829184cb24021170fa3b05836ea0ef845c0dc | [
"self.type = type\nself.name = name\nself.width = width\nself.cls = cls",
"assert elem.tag in ['input', 'output', 'clock'], elem.tag\nport = Port(type=PortType.from_string(elem.tag), name=elem.attrib['name'], width=int(elem.get('num_pins', '1')), cls=elem.get('port_class', None))\nreturn port",
"if range_spec i... | <|body_start_0|>
self.type = type
self.name = name
self.width = width
self.cls = cls
<|end_body_0|>
<|body_start_1|>
assert elem.tag in ['input', 'output', 'clock'], elem.tag
port = Port(type=PortType.from_string(elem.tag), name=elem.attrib['name'], width=int(elem.get('n... | A port of pb_type | Port | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Port:
"""A port of pb_type"""
def __init__(self, type, name, width=1, cls=None):
"""Basic constructor"""
<|body_0|>
def from_etree(elem):
"""Create the object from its ElementTree representation"""
<|body_1|>
def yield_pins(self, range_spec=None):
... | stack_v2_sparse_classes_36k_train_028386 | 11,880 | permissive | [
{
"docstring": "Basic constructor",
"name": "__init__",
"signature": "def __init__(self, type, name, width=1, cls=None)"
},
{
"docstring": "Create the object from its ElementTree representation",
"name": "from_etree",
"signature": "def from_etree(elem)"
},
{
"docstring": "Yields ... | 3 | stack_v2_sparse_classes_30k_train_018450 | Implement the Python class `Port` described below.
Class description:
A port of pb_type
Method signatures and docstrings:
- def __init__(self, type, name, width=1, cls=None): Basic constructor
- def from_etree(elem): Create the object from its ElementTree representation
- def yield_pins(self, range_spec=None): Yields... | Implement the Python class `Port` described below.
Class description:
A port of pb_type
Method signatures and docstrings:
- def __init__(self, type, name, width=1, cls=None): Basic constructor
- def from_etree(elem): Create the object from its ElementTree representation
- def yield_pins(self, range_spec=None): Yields... | 835a40534f9efd70770d74f56f25fef6cfc6ebc6 | <|skeleton|>
class Port:
"""A port of pb_type"""
def __init__(self, type, name, width=1, cls=None):
"""Basic constructor"""
<|body_0|>
def from_etree(elem):
"""Create the object from its ElementTree representation"""
<|body_1|>
def yield_pins(self, range_spec=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Port:
"""A port of pb_type"""
def __init__(self, type, name, width=1, cls=None):
"""Basic constructor"""
self.type = type
self.name = name
self.width = width
self.cls = cls
def from_etree(elem):
"""Create the object from its ElementTree representation"... | the_stack_v2_python_sparse | f4pga/utils/quicklogic/repacker/pb_type.py | f4pga/f4pga | train | 19 |
f81f8f325de4d2b29662b70777cf97b8fc5957d1 | [
"Parametre.__init__(self, 'vitesse', 'speed')\nself.schema = '<vitesse_rames>'\nself.aide_courte = 'change la vitesse des rames'\nself.aide_longue = \"Cette commande permet de modifier la vitesse des rames que vous tenez en main. Les vitesses disponibles sont |cmd|arrière|ff| (pour aller en marche arrière), |cmd|im... | <|body_start_0|>
Parametre.__init__(self, 'vitesse', 'speed')
self.schema = '<vitesse_rames>'
self.aide_courte = 'change la vitesse des rames'
self.aide_longue = "Cette commande permet de modifier la vitesse des rames que vous tenez en main. Les vitesses disponibles sont |cmd|arrière|ff|... | Commande 'rames vitesse'. | PrmVitesse | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmVitesse:
"""Commande 'rames vitesse'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre._... | stack_v2_sparse_classes_36k_train_028387 | 3,270 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008797 | Implement the Python class `PrmVitesse` described below.
Class description:
Commande 'rames vitesse'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmVitesse` described below.
Class description:
Commande 'rames vitesse'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmVitesse:
"""Commande 'rames v... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmVitesse:
"""Commande 'rames vitesse'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmVitesse:
"""Commande 'rames vitesse'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'vitesse', 'speed')
self.schema = '<vitesse_rames>'
self.aide_courte = 'change la vitesse des rames'
self.aide_longue = "Cette commande permet d... | the_stack_v2_python_sparse | src/secondaires/navigation/commandes/rames/vitesse.py | vincent-lg/tsunami | train | 5 |
7f33c54c5db11af6c66d07aa6980ebd34bdda34e | [
"super().__init__()\nself._securities_cache: Optional[pd.DataFrame] = None\nself._cache_lock = asyncio.Lock()",
"name = self._log_and_validate_group(table_name, outer.SECURITIES)\nif name != outer.SECURITIES:\n raise outer.DataError(f'Некорректное имя таблицы для обновления {table_name}')\nasync with self._cac... | <|body_start_0|>
super().__init__()
self._securities_cache: Optional[pd.DataFrame] = None
self._cache_lock = asyncio.Lock()
<|end_body_0|>
<|body_start_1|>
name = self._log_and_validate_group(table_name, outer.SECURITIES)
if name != outer.SECURITIES:
raise outer.Data... | Информация о всех торгующихся акциях. | SecuritiesLoader | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecuritiesLoader:
"""Информация о всех торгующихся акциях."""
def __init__(self) -> None:
"""Кэшируются данные, чтобы сократить количество обращений к серверу MOEX."""
<|body_0|>
async def get(self, table_name: outer.TableName) -> pd.DataFrame:
"""Получение списк... | stack_v2_sparse_classes_36k_train_028388 | 6,612 | permissive | [
{
"docstring": "Кэшируются данные, чтобы сократить количество обращений к серверу MOEX.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Получение списка торгуемых акций с регистрационным номером и размером лота.",
"name": "get",
"signature": "async def ... | 2 | stack_v2_sparse_classes_30k_train_015611 | Implement the Python class `SecuritiesLoader` described below.
Class description:
Информация о всех торгующихся акциях.
Method signatures and docstrings:
- def __init__(self) -> None: Кэшируются данные, чтобы сократить количество обращений к серверу MOEX.
- async def get(self, table_name: outer.TableName) -> pd.DataF... | Implement the Python class `SecuritiesLoader` described below.
Class description:
Информация о всех торгующихся акциях.
Method signatures and docstrings:
- def __init__(self) -> None: Кэшируются данные, чтобы сократить количество обращений к серверу MOEX.
- async def get(self, table_name: outer.TableName) -> pd.DataF... | e5d0f2c28de25568e4515b63aaad4aa337e2e522 | <|skeleton|>
class SecuritiesLoader:
"""Информация о всех торгующихся акциях."""
def __init__(self) -> None:
"""Кэшируются данные, чтобы сократить количество обращений к серверу MOEX."""
<|body_0|>
async def get(self, table_name: outer.TableName) -> pd.DataFrame:
"""Получение списк... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecuritiesLoader:
"""Информация о всех торгующихся акциях."""
def __init__(self) -> None:
"""Кэшируются данные, чтобы сократить количество обращений к серверу MOEX."""
super().__init__()
self._securities_cache: Optional[pd.DataFrame] = None
self._cache_lock = asyncio.Lock(... | the_stack_v2_python_sparse | poptimizer/data/adapters/loaders/moex.py | chekanskiy/poptimizer | train | 0 |
b544a372cea723344477e32bd93eb56a61f278dc | [
"i = 0\nj = len(height) - 1\nres = 0\nwhile i < j:\n tmp = min(height[j], height[i]) * (j - i)\n if tmp > res:\n res = tmp\n if height[i] < height[j]:\n i += 1\n else:\n j -= 1\nreturn res",
"i, j, max_v = (0, len(height) - 1, 0)\nwhile i < j:\n if height[i] < height[j]:\n ... | <|body_start_0|>
i = 0
j = len(height) - 1
res = 0
while i < j:
tmp = min(height[j], height[i]) * (j - i)
if tmp > res:
res = tmp
if height[i] < height[j]:
i += 1
else:
j -= 1
return r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea0(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
j = len(height) - 1
re... | stack_v2_sparse_classes_36k_train_028389 | 1,039 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea",
"signature": "def maxArea(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "maxArea0",
"signature": "def maxArea0(self, height)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012716 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea0(self, height): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxArea(self, height): :type height: List[int] :rtype: int
- def maxArea0(self, height): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxArea(se... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def maxArea0(self, height):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxArea(self, height):
""":type height: List[int] :rtype: int"""
i = 0
j = len(height) - 1
res = 0
while i < j:
tmp = min(height[j], height[i]) * (j - i)
if tmp > res:
res = tmp
if height[i] < height[j]:
... | the_stack_v2_python_sparse | PythonCode/src/0011_Container_With_Most_Water.py | oneyuan/CodeforFun | train | 0 | |
34987daad6f9d8bf613f54da8ab0978568c8ace2 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.appleManagedIdentityProvider'.casefold():\n... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | IdentityProviderBase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IdentityProviderBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IdentityProviderBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k_train_028390 | 4,982 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: IdentityProviderBase",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminato... | 3 | null | Implement the Python class `IdentityProviderBase` described below.
Class description:
Implement the IdentityProviderBase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IdentityProviderBase: Creates a new instance of the appropriate class based o... | Implement the Python class `IdentityProviderBase` described below.
Class description:
Implement the IdentityProviderBase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IdentityProviderBase: Creates a new instance of the appropriate class based o... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IdentityProviderBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IdentityProviderBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IdentityProviderBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IdentityProviderBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | the_stack_v2_python_sparse | msgraph/generated/models/identity_provider_base.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
6f07312fa13518413ccaa6d8a4b00f67d49a1d93 | [
"self._check_access(request)\nawait self._change_password(data[ATTR_USERNAME], data[ATTR_PASSWORD])\nreturn web.Response(status=HTTP_OK)",
"provider = self._get_provider()\ntry:\n await self.hass.async_add_executor_job(provider.data.change_password, username, password)\n await provider.data.async_save()\nex... | <|body_start_0|>
self._check_access(request)
await self._change_password(data[ATTR_USERNAME], data[ATTR_PASSWORD])
return web.Response(status=HTTP_OK)
<|end_body_0|>
<|body_start_1|>
provider = self._get_provider()
try:
await self.hass.async_add_executor_job(provider... | Hass.io view to handle password reset requests. | HassIOPasswordReset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HassIOPasswordReset:
"""Hass.io view to handle password reset requests."""
async def post(self, request, data):
"""Handle password reset requests."""
<|body_0|>
async def _change_password(self, username, password):
"""Check User credentials."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_028391 | 4,251 | permissive | [
{
"docstring": "Handle password reset requests.",
"name": "post",
"signature": "async def post(self, request, data)"
},
{
"docstring": "Check User credentials.",
"name": "_change_password",
"signature": "async def _change_password(self, username, password)"
}
] | 2 | null | Implement the Python class `HassIOPasswordReset` described below.
Class description:
Hass.io view to handle password reset requests.
Method signatures and docstrings:
- async def post(self, request, data): Handle password reset requests.
- async def _change_password(self, username, password): Check User credentials. | Implement the Python class `HassIOPasswordReset` described below.
Class description:
Hass.io view to handle password reset requests.
Method signatures and docstrings:
- async def post(self, request, data): Handle password reset requests.
- async def _change_password(self, username, password): Check User credentials.
... | ba55b4b8338a2dc0ba3f1d750efea49d86571291 | <|skeleton|>
class HassIOPasswordReset:
"""Hass.io view to handle password reset requests."""
async def post(self, request, data):
"""Handle password reset requests."""
<|body_0|>
async def _change_password(self, username, password):
"""Check User credentials."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HassIOPasswordReset:
"""Hass.io view to handle password reset requests."""
async def post(self, request, data):
"""Handle password reset requests."""
self._check_access(request)
await self._change_password(data[ATTR_USERNAME], data[ATTR_PASSWORD])
return web.Response(statu... | the_stack_v2_python_sparse | homeassistant/components/hassio/auth.py | basnijholt/home-assistant | train | 5 |
ceb4452c1d2962045cef531f5f74ea60a19c819d | [
"super(CustomBatchNormManualModule, self).__init__()\nself.n_neurons = n_neurons\nself.eps = eps\nself.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})",
"_n_batch, n_neurons = input.shape\nassert n_neurons == self.n_neurons\np = self.params\n... | <|body_start_0|>
super(CustomBatchNormManualModule, self).__init__()
self.n_neurons = n_neurons
self.eps = eps
self.params = nn.ParameterDict({'gamma': nn.Parameter(torch.ones(n_neurons)), 'beta': nn.Parameter(torch.zeros(n_neurons))})
<|end_body_0|>
<|body_start_1|>
_n_batch, n... | This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backward method of this function in the backward pass. | CustomBatchNormManualModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomBatchNormManualModule:
"""This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backward method of this function in the backw... | stack_v2_sparse_classes_36k_train_028392 | 7,737 | no_license | [
{
"docstring": "Initializes CustomBatchNormManualModule object. Args: n_neurons: int specifying the number of neurons eps: small float to be added to the variance for stability",
"name": "__init__",
"signature": "def __init__(self, n_neurons, eps=1e-05)"
},
{
"docstring": "Compute the batch norm... | 2 | stack_v2_sparse_classes_30k_train_006549 | Implement the Python class `CustomBatchNormManualModule` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backwa... | Implement the Python class `CustomBatchNormManualModule` described below.
Class description:
This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backwa... | b2cd0d67337b101f3e204e519625e1aaf3cea43b | <|skeleton|>
class CustomBatchNormManualModule:
"""This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backward method of this function in the backw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomBatchNormManualModule:
"""This nn.module implements a custom version of the batch norm operation for MLPs. In self.forward the functional version CustomBatchNormManualFunction.forward is called. The automatic differentiation of PyTorch calls the backward method of this function in the backward pass."""
... | the_stack_v2_python_sparse | assignment_1/code/custom_batchnorm.py | Ivan-Yovchev/uvadlc_practicals_2019 | train | 0 |
05003744d55b715b69a9d752c97af9a6ed80b796 | [
"if energy_modes is None:\n energy_modes = [1, 2, 3, 4]\nsuper().__init__((npart, None, np.dtype('float64')))\nself._makeAttributeAndRegister('npart', 'alpha', 'k', 'energy_modes', localVars=locals(), readOnly=True)\nself.dx = self.npart / 32 / (self.npart + 1)\nself.xvalues = np.array([(i + 1) * self.dx for i i... | <|body_start_0|>
if energy_modes is None:
energy_modes = [1, 2, 3, 4]
super().__init__((npart, None, np.dtype('float64')))
self._makeAttributeAndRegister('npart', 'alpha', 'k', 'energy_modes', localVars=locals(), readOnly=True)
self.dx = self.npart / 32 / (self.npart + 1)
... | Example implementing the outer solar system problem TODO : doku | fermi_pasta_ulam_tsingou | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class fermi_pasta_ulam_tsingou:
"""Example implementing the outer solar system problem TODO : doku"""
def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None):
"""Initialization routine"""
<|body_0|>
def eval_f(self, u, t):
"""Routine to compute the right-h... | stack_v2_sparse_classes_36k_train_028393 | 4,420 | permissive | [
{
"docstring": "Initialization routine",
"name": "__init__",
"signature": "def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None)"
},
{
"docstring": "Routine to compute the right-hand side of the problem. Parameters ---------- u : dtype_u Current values of the numerical solution. t... | 5 | null | Implement the Python class `fermi_pasta_ulam_tsingou` described below.
Class description:
Example implementing the outer solar system problem TODO : doku
Method signatures and docstrings:
- def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None): Initialization routine
- def eval_f(self, u, t): Routine t... | Implement the Python class `fermi_pasta_ulam_tsingou` described below.
Class description:
Example implementing the outer solar system problem TODO : doku
Method signatures and docstrings:
- def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None): Initialization routine
- def eval_f(self, u, t): Routine t... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class fermi_pasta_ulam_tsingou:
"""Example implementing the outer solar system problem TODO : doku"""
def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None):
"""Initialization routine"""
<|body_0|>
def eval_f(self, u, t):
"""Routine to compute the right-h... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class fermi_pasta_ulam_tsingou:
"""Example implementing the outer solar system problem TODO : doku"""
def __init__(self, npart=2048, alpha=0.25, k=1.0, energy_modes=None):
"""Initialization routine"""
if energy_modes is None:
energy_modes = [1, 2, 3, 4]
super().__init__((npa... | the_stack_v2_python_sparse | pySDC/implementations/problem_classes/FermiPastaUlamTsingou.py | Parallel-in-Time/pySDC | train | 30 |
09edf147777f1ff5956cb528ee35ae9c7e033b25 | [
"super(DeviceTarget, self).__init__()\nself.region = region\nself.role = role\nself.network = network\nself.hostname = hostname\nself.realm = 'ACQ_CHROME'\nself.alertable = True\nself._fields = ('region', 'role', 'network', 'hostname')",
"collection.network_device.metro = self.region\ncollection.network_device.ro... | <|body_start_0|>
super(DeviceTarget, self).__init__()
self.region = region
self.role = role
self.network = network
self.hostname = hostname
self.realm = 'ACQ_CHROME'
self.alertable = True
self._fields = ('region', 'role', 'network', 'hostname')
<|end_body_... | Monitoring interface class for monitoring specific hosts or devices. | DeviceTarget | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeviceTarget:
"""Monitoring interface class for monitoring specific hosts or devices."""
def __init__(self, region, role, network, hostname):
"""Create a Target object exporting info about a specific device. Args: region (str): physical region in which the device is located. role (st... | stack_v2_sparse_classes_36k_train_028394 | 4,448 | permissive | [
{
"docstring": "Create a Target object exporting info about a specific device. Args: region (str): physical region in which the device is located. role (str): role of the device. network (str): virtual network on which the device is located. hostname (str): name by which the device self-identifies.",
"name"... | 2 | null | Implement the Python class `DeviceTarget` described below.
Class description:
Monitoring interface class for monitoring specific hosts or devices.
Method signatures and docstrings:
- def __init__(self, region, role, network, hostname): Create a Target object exporting info about a specific device. Args: region (str):... | Implement the Python class `DeviceTarget` described below.
Class description:
Monitoring interface class for monitoring specific hosts or devices.
Method signatures and docstrings:
- def __init__(self, region, role, network, hostname): Create a Target object exporting info about a specific device. Args: region (str):... | 53102de187a48ac2cfc241fef54dcbc29c453a8e | <|skeleton|>
class DeviceTarget:
"""Monitoring interface class for monitoring specific hosts or devices."""
def __init__(self, region, role, network, hostname):
"""Create a Target object exporting info about a specific device. Args: region (str): physical region in which the device is located. role (st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeviceTarget:
"""Monitoring interface class for monitoring specific hosts or devices."""
def __init__(self, region, role, network, hostname):
"""Create a Target object exporting info about a specific device. Args: region (str): physical region in which the device is located. role (str): role of t... | the_stack_v2_python_sparse | third_party/gae_ts_mon/gae_ts_mon/common/targets.py | catapult-project/catapult | train | 2,032 |
a031cf07188b030fd2f62a91a875c51551611af2 | [
"self = object.__new__(cls)\nself.entity_id = entity_id\nself.max_level = max_level\nself.expires_at = 0.0\nKOKORO.call_after(SEX_RESET_AFTER, self)\nreturn self",
"expires_at = self.expires_at\nif expires_at:\n KOKORO.call_at(expires_at + SEX_RESET_AFTER, self)\nelse:\n try:\n del SEX_SPAM_LOCK[self... | <|body_start_0|>
self = object.__new__(cls)
self.entity_id = entity_id
self.max_level = max_level
self.expires_at = 0.0
KOKORO.call_after(SEX_RESET_AFTER, self)
return self
<|end_body_0|>
<|body_start_1|>
expires_at = self.expires_at
if expires_at:
... | Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The max allowed sex rarity level. | SexSpamLock | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SexSpamLock:
"""Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The max allowed sex rarity level."""
de... | stack_v2_sparse_classes_36k_train_028395 | 2,651 | no_license | [
{
"docstring": "Creates a new sex spam lock. Parameters ---------- entity_id : `int` The locked entity's identifier. max_level : `int` The max allowed sex rarity level.",
"name": "__new__",
"signature": "def __new__(cls, entity_id, max_level)"
},
{
"docstring": "Called when sex lock expires. Set... | 3 | null | Implement the Python class `SexSpamLock` described below.
Class description:
Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The m... | Implement the Python class `SexSpamLock` described below.
Class description:
Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The m... | 74f92b598e86606ea3a269311316cddd84a5215f | <|skeleton|>
class SexSpamLock:
"""Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The max allowed sex rarity level."""
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SexSpamLock:
"""Sex spam lock used to avoid sex spam. Or you could say to promote it by not giving. Attributes ----------- entity_id : `int` The locked entity's identifier. expires_at : `float` When the lock expires in monotonic time. max_level : `int` The max allowed sex rarity level."""
def __new__(cls... | the_stack_v2_python_sparse | koishi/plugins/sex/lock.py | HuyaneMatsu/Koishi | train | 17 |
823bc1e89d231d64d9d94568134e5d365a373315 | [
"list_of_links = response.xpath('//*/a[@class=\"exhibitorName\"]/@href').extract()\nfor link in list_of_links:\n yield scrapy.Request(response.urljoin(link), callback=self.parse_data)",
"url = 'https://retailx.a2zinc.net/RetailX2020/Public/Exhibitors.aspx?ID=23735'\nitem = RetailXItem()\nitem['url'] = url\nnam... | <|body_start_0|>
list_of_links = response.xpath('//*/a[@class="exhibitorName"]/@href').extract()
for link in list_of_links:
yield scrapy.Request(response.urljoin(link), callback=self.parse_data)
<|end_body_0|>
<|body_start_1|>
url = 'https://retailx.a2zinc.net/RetailX2020/Public/Exh... | Spider to get the data from the online.marketing | RetailX | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RetailX:
"""Spider to get the data from the online.marketing"""
def parse(self, response):
"""Method checks for the shops :param response: the fully downloaded webpagage :return:"""
<|body_0|>
def parse_data(self, response):
"""Method get the the data of the tool... | stack_v2_sparse_classes_36k_train_028396 | 2,112 | no_license | [
{
"docstring": "Method checks for the shops :param response: the fully downloaded webpagage :return:",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Method get the the data of the tools :param response: :return:",
"name": "parse_data",
"signature": "def par... | 2 | stack_v2_sparse_classes_30k_train_003149 | Implement the Python class `RetailX` described below.
Class description:
Spider to get the data from the online.marketing
Method signatures and docstrings:
- def parse(self, response): Method checks for the shops :param response: the fully downloaded webpagage :return:
- def parse_data(self, response): Method get the... | Implement the Python class `RetailX` described below.
Class description:
Spider to get the data from the online.marketing
Method signatures and docstrings:
- def parse(self, response): Method checks for the shops :param response: the fully downloaded webpagage :return:
- def parse_data(self, response): Method get the... | 64a7ec204166532fc653f7001f288179e45d1046 | <|skeleton|>
class RetailX:
"""Spider to get the data from the online.marketing"""
def parse(self, response):
"""Method checks for the shops :param response: the fully downloaded webpagage :return:"""
<|body_0|>
def parse_data(self, response):
"""Method get the the data of the tool... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RetailX:
"""Spider to get the data from the online.marketing"""
def parse(self, response):
"""Method checks for the shops :param response: the fully downloaded webpagage :return:"""
list_of_links = response.xpath('//*/a[@class="exhibitorName"]/@href').extract()
for link in list_of... | the_stack_v2_python_sparse | AutoScrapy/spiders/retailx.py | SpaceZZ/AutoScrapyProject2 | train | 0 |
57b1e04975007a3ef7f568210e2df10349342df9 | [
"super().__init__(name, 's')\nself.n_points_per_dim = n_points_per_dim\nself.predictions_dict = dict()\nself.hidden_outputs_dict = dict()\nself.x_unique = np.linspace(dataset.test.x.min(axis=1), dataset.test.x.max(axis=1), num=n_points_per_dim, axis=1)\nx_mesh = np.meshgrid(*self.x_unique)\nself.x_pred = np.stack([... | <|body_start_0|>
super().__init__(name, 's')
self.n_points_per_dim = n_points_per_dim
self.predictions_dict = dict()
self.hidden_outputs_dict = dict()
self.x_unique = np.linspace(dataset.test.x.min(axis=1), dataset.test.x.max(axis=1), num=n_points_per_dim, axis=1)
x_mesh ... | This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_column function in the Tests/test_columns.py module for a usage example of this... | Predictions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Predictions:
"""This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_column function in the Tests/test_column... | stack_v2_sparse_classes_36k_train_028397 | 20,983 | no_license | [
{
"docstring": "Initialise this Predictions column. Inputs: - dataset: dataset that the model is about to be trained on. The training set from this dataset is used to calculate the upper and lower limits of the prediction inputs used by this object - n_points_per_dim: the number of unique prediction inputs to u... | 2 | stack_v2_sparse_classes_30k_val_000118 | Implement the Python class `Predictions` described below.
Class description:
This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_c... | Implement the Python class `Predictions` described below.
Class description:
This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_c... | 389dbb3c4f84f8498ea879980b82e2cf543e5441 | <|skeleton|>
class Predictions:
"""This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_column function in the Tests/test_column... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Predictions:
"""This column is for storing predictions of the model during training. Once training is complete, this object can be passed to the plot_predictions_gif object to plot a gif of the predictions evolving during training. See the test_predictions_column function in the Tests/test_columns.py module f... | the_stack_v2_python_sparse | optimisers/columns.py | jakelevi1996/backprop2 | train | 0 |
2430e6b9239b54be7ebc8e7eb20c27916e59751f | [
"self.column_index = column_index\nself.range_start = range_start if not range_start is None else 0\nself.range_end = range_end\nself.cast_to_number = cast_to_number\nself.values: List[Any] = list()\nself.values_caveats: List[bool] = list()",
"if row_index >= self.range_start and (self.range_end is None or row_in... | <|body_start_0|>
self.column_index = column_index
self.range_start = range_start if not range_start is None else 0
self.range_end = range_end
self.cast_to_number = cast_to_number
self.values: List[Any] = list()
self.values_caveats: List[bool] = list()
<|end_body_0|>
<|bo... | Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list List of values in the resulting data series | DataStreamConsumer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataStreamConsumer:
"""Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list List of values in the resulting data ser... | stack_v2_sparse_classes_36k_train_028398 | 7,684 | permissive | [
{
"docstring": "Initialize the index position for the column in the dataset schema that is being consumed and the range interval of row indexes. If range_start is None the considered interval of rows starts at 0. If range_end is None all rows until the end of the dataset are being consumed. Parameters ---------... | 2 | stack_v2_sparse_classes_30k_train_011765 | Implement the Python class `DataStreamConsumer` described below.
Class description:
Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list L... | Implement the Python class `DataStreamConsumer` described below.
Class description:
Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list L... | e99f43df3df80ad5647f57d805c339257336ac73 | <|skeleton|>
class DataStreamConsumer:
"""Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list List of values in the resulting data ser... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataStreamConsumer:
"""Consumer for data rows. The row consumers are used to filter cell values for a given column and a range interval of rows. The result is a list of values that represent a data series in a chart plot. Attributes ---------- values: list List of values in the resulting data series"""
d... | the_stack_v2_python_sparse | vizier/engine/packages/plot/query.py | VizierDB/web-api-async | train | 2 |
b03336620a74a6518aecba253737eb2d8fbdbc62 | [
"super(SlideT, self).__init__()\nself.a = array_check(a, 1)\nself.n_1 = int_check(n_1, 1)\nself.n_2 = int_check(n_2, 1)",
"t = np.zeros(shape=self.a.shape)\nfor i, in np.ndindex(self.a.shape):\n if self.n_1 <= i <= self.a.size - self.n_2 - 1:\n x_forward = self.a[i - self.n_1:i]\n x_backward = se... | <|body_start_0|>
super(SlideT, self).__init__()
self.a = array_check(a, 1)
self.n_1 = int_check(n_1, 1)
self.n_2 = int_check(n_2, 1)
<|end_body_0|>
<|body_start_1|>
t = np.zeros(shape=self.a.shape)
for i, in np.ndindex(self.a.shape):
if self.n_1 <= i <= self.... | Slide T method. | SlideT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SlideT:
"""Slide T method."""
def __init__(self, a: array_like, n_1: int, n_2: int) -> None:
""":param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length"""
<|body_0|>
def testing(self):
"""Slide and test. :return: class... | stack_v2_sparse_classes_36k_train_028399 | 8,892 | no_license | [
{
"docstring": ":param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length",
"name": "__init__",
"signature": "def __init__(self, a: array_like, n_1: int, n_2: int) -> None"
},
{
"docstring": "Slide and test. :return: class self",
"name": "testing",
... | 3 | stack_v2_sparse_classes_30k_train_004302 | Implement the Python class `SlideT` described below.
Class description:
Slide T method.
Method signatures and docstrings:
- def __init__(self, a: array_like, n_1: int, n_2: int) -> None: :param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length
- def testing(self): Slide and... | Implement the Python class `SlideT` described below.
Class description:
Slide T method.
Method signatures and docstrings:
- def __init__(self, a: array_like, n_1: int, n_2: int) -> None: :param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length
- def testing(self): Slide and... | 1c8d5fbf3676dc81e9f143e93ee2564359519b11 | <|skeleton|>
class SlideT:
"""Slide T method."""
def __init__(self, a: array_like, n_1: int, n_2: int) -> None:
""":param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length"""
<|body_0|>
def testing(self):
"""Slide and test. :return: class... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SlideT:
"""Slide T method."""
def __init__(self, a: array_like, n_1: int, n_2: int) -> None:
""":param a: array_like 1-D array :param n_1: int left testing length :param n_2: int right test length"""
super(SlideT, self).__init__()
self.a = array_check(a, 1)
self.n_1 = int_... | the_stack_v2_python_sparse | statistics/mutation.py | qliu0/PythonInAirSeaScience | train | 0 |
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