blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c7e12d9df2dee2eade1f090e6e027940570e26b9 | [
"self._true_mean = Config.get_param(config, 'true_mean')\nif Config.has_key(config, 'std_deviation'):\n self._std_deviation = Config.get_param(config, 'std_deviation')\nelse:\n self._std_deviation = None\nself._significance_level = Config.get_param(config, 'significance_level')",
"if len(deviation) is not 1... | <|body_start_0|>
self._true_mean = Config.get_param(config, 'true_mean')
if Config.has_key(config, 'std_deviation'):
self._std_deviation = Config.get_param(config, 'std_deviation')
else:
self._std_deviation = None
self._significance_level = Config.get_param(config... | Base class for student t test. | StudentTTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StudentTTest:
"""Base class for student t test."""
def __init__(self, config):
"""Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Configuration from yaml file"""
<|body_0|>
def c... | stack_v2_sparse_classes_36k_train_024700 | 2,054 | permissive | [
{
"docstring": "Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Configuration from yaml file",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Check if the given informat... | 2 | null | Implement the Python class `StudentTTest` described below.
Class description:
Base class for student t test.
Method signatures and docstrings:
- def __init__(self, config): Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Conf... | Implement the Python class `StudentTTest` described below.
Class description:
Base class for student t test.
Method signatures and docstrings:
- def __init__(self, config): Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Conf... | 2f66e226fc335ae357001d07fbc74d30ab469509 | <|skeleton|>
class StudentTTest:
"""Base class for student t test."""
def __init__(self, config):
"""Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Configuration from yaml file"""
<|body_0|>
def c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StudentTTest:
"""Base class for student t test."""
def __init__(self, config):
"""Constructor for a new hypothesis by using the student t test. It includes the value, the deviation and the number of samples. :param config: Configuration from yaml file"""
self._true_mean = Config.get_param... | the_stack_v2_python_sparse | tug_observers/tug_observer_plugins/tug_observer_plugin_utils/scripts/hypothesis_check/single_value_hypothesis_check/student_t_test.py | annarosejohny/Model_based_diagnosis | train | 0 |
e094adcc06d95287efec38b54ea8121981a9f329 | [
"return_data = []\nfor minion_id in minions:\n try:\n history = salt_returns.objects.filter(id=minion_id)\n for job in history:\n full_ret = job.full_ret\n return_data.append({'id': job.id, 'full_ret': full_ret, 'fun': job.fun, 'jid': job.jid, 'comment': job.return_value, 'suc... | <|body_start_0|>
return_data = []
for minion_id in minions:
try:
history = salt_returns.objects.filter(id=minion_id)
for job in history:
full_ret = job.full_ret
return_data.append({'id': job.id, 'full_ret': full_ret, 'fu... | API to retrieve data from salt_returns for a group of minions | JobHistoryListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobHistoryListView:
"""API to retrieve data from salt_returns for a group of minions"""
def get_minion_job_history(self, minions, page_number):
"""Loop through minions and get their job history. Then parse it a bit."""
<|body_0|>
def list(self, request, *args, **kwargs):... | stack_v2_sparse_classes_36k_train_024701 | 47,872 | no_license | [
{
"docstring": "Loop through minions and get their job history. Then parse it a bit.",
"name": "get_minion_job_history",
"signature": "def get_minion_job_history(self, minions, page_number)"
},
{
"docstring": "Since we have two different front ends sending data, we need some awkward logic to see... | 2 | stack_v2_sparse_classes_30k_test_000350 | Implement the Python class `JobHistoryListView` described below.
Class description:
API to retrieve data from salt_returns for a group of minions
Method signatures and docstrings:
- def get_minion_job_history(self, minions, page_number): Loop through minions and get their job history. Then parse it a bit.
- def list(... | Implement the Python class `JobHistoryListView` described below.
Class description:
API to retrieve data from salt_returns for a group of minions
Method signatures and docstrings:
- def get_minion_job_history(self, minions, page_number): Loop through minions and get their job history. Then parse it a bit.
- def list(... | 122a172caea82ef660e81a9dfc6377afd731f9cb | <|skeleton|>
class JobHistoryListView:
"""API to retrieve data from salt_returns for a group of minions"""
def get_minion_job_history(self, minions, page_number):
"""Loop through minions and get their job history. Then parse it a bit."""
<|body_0|>
def list(self, request, *args, **kwargs):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobHistoryListView:
"""API to retrieve data from salt_returns for a group of minions"""
def get_minion_job_history(self, minions, page_number):
"""Loop through minions and get their job history. Then parse it a bit."""
return_data = []
for minion_id in minions:
try:
... | the_stack_v2_python_sparse | sso/files/gui/sse/job/views.py | nofxrok/headless | train | 1 |
747feffffdba33029a438093fb583d517282eed6 | [
"super().__init__(name=name)\nif 'name' in parameters:\n raise ValueError('Cannot have parameter named str(name)')\nself._parameters = dict()\nif parameters:\n self._create_attributes(parameters)",
"for param_name in parameters:\n param_value = parameters[param_name]\n setattr(self, param_name, param_... | <|body_start_0|>
super().__init__(name=name)
if 'name' in parameters:
raise ValueError('Cannot have parameter named str(name)')
self._parameters = dict()
if parameters:
self._create_attributes(parameters)
<|end_body_0|>
<|body_start_1|>
for param_name in ... | Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might even correspond to a model of a physical or simulated system. Typically, all met... | MetaInstrument | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetaInstrument:
"""Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might even correspond to a model of a physic... | stack_v2_sparse_classes_36k_train_024702 | 5,014 | no_license | [
{
"docstring": "Args: name (str): the name of this meta instrument.",
"name": "__init__",
"signature": "def __init__(self, name: str, **parameters)"
},
{
"docstring": "Set every parameter as an attribute. Meant to be called once within the __init__() method. Very useful when initialising objects... | 2 | null | Implement the Python class `MetaInstrument` described below.
Class description:
Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might... | Implement the Python class `MetaInstrument` described below.
Class description:
Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might... | b1f8e742df003f1d4ed7962353f8646740592f7d | <|skeleton|>
class MetaInstrument:
"""Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might even correspond to a model of a physic... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetaInstrument:
"""Abstract class that encapsulates a meta instrument. A meta instrument can take many forms. It may be composed of many physical instruments. It may be an element of an experiment that is controlled by multiple physical instruments. It might even correspond to a model of a physical or simulat... | the_stack_v2_python_sparse | codebase/instruments/instrument.py | qcrew-lab/qcore | train | 1 |
b080de6d27ec1cefd589f4f3af5342efa604fffe | [
"session = create_session()\nif field.data in [phone[0] for phone in session.query(User.phone_number).all()]:\n raise ValidationError('Пользователь с таким номером телефона уже существует')",
"session = create_session()\nif field.data in [email[0] for email in session.query(User.email).all()]:\n raise Valid... | <|body_start_0|>
session = create_session()
if field.data in [phone[0] for phone in session.query(User.phone_number).all()]:
raise ValidationError('Пользователь с таким номером телефона уже существует')
<|end_body_0|>
<|body_start_1|>
session = create_session()
if field.data... | Класс формы регистрации. | RegistrationForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegistrationForm:
"""Класс формы регистрации."""
def validate_phone_number_field(self, field: StringField):
"""Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверить"""
<|body_0|>
def validate_email_field(sel... | stack_v2_sparse_classes_36k_train_024703 | 8,216 | no_license | [
{
"docstring": "Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверить",
"name": "validate_phone_number_field",
"signature": "def validate_phone_number_field(self, field: StringField)"
},
{
"docstring": "Метод, проверяющий уникальнос... | 2 | stack_v2_sparse_classes_30k_train_016445 | Implement the Python class `RegistrationForm` described below.
Class description:
Класс формы регистрации.
Method signatures and docstrings:
- def validate_phone_number_field(self, field: StringField): Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверит... | Implement the Python class `RegistrationForm` described below.
Class description:
Класс формы регистрации.
Method signatures and docstrings:
- def validate_phone_number_field(self, field: StringField): Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверит... | 7227e0fab616086ed895b2d09d1dc247c0048183 | <|skeleton|>
class RegistrationForm:
"""Класс формы регистрации."""
def validate_phone_number_field(self, field: StringField):
"""Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверить"""
<|body_0|>
def validate_email_field(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegistrationForm:
"""Класс формы регистрации."""
def validate_phone_number_field(self, field: StringField):
"""Метод, проверяющий уникальность введенных данных в поле для телефона :param field: поле, которое необходимо проверить"""
session = create_session()
if field.data in [phon... | the_stack_v2_python_sparse | data/forms.py | Nekson228/Webby | train | 0 |
256003bfdf8b1245f83124aa9352628489fa5bd1 | [
"username = kwargs.get('username', None)\nself.pagination_class.page_size_query_param = 'length'\nself.pagination_class.max_page_size = 100\nqueryset = self.filter_queryset(self.get_queryset())\nusername = bleach.clean(username)\nif request.user.is_staff:\n user = get_or_none(User, username=username)\n if use... | <|body_start_0|>
username = kwargs.get('username', None)
self.pagination_class.page_size_query_param = 'length'
self.pagination_class.max_page_size = 100
queryset = self.filter_queryset(self.get_queryset())
username = bleach.clean(username)
if request.user.is_staff:
... | API endpoint that allows users to view their history | UserHistoryViewSet | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserHistoryViewSet:
"""API endpoint that allows users to view their history"""
def list(self, request, *args, **kwargs):
"""Return a list of a users command history"""
<|body_0|>
def retrieve(self, request, *args, **kwargs):
"""Return a specific user's command"""... | stack_v2_sparse_classes_36k_train_024704 | 4,294 | permissive | [
{
"docstring": "Return a list of a users command history",
"name": "list",
"signature": "def list(self, request, *args, **kwargs)"
},
{
"docstring": "Return a specific user's command",
"name": "retrieve",
"signature": "def retrieve(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018745 | Implement the Python class `UserHistoryViewSet` described below.
Class description:
API endpoint that allows users to view their history
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Return a list of a users command history
- def retrieve(self, request, *args, **kwargs): Return a speci... | Implement the Python class `UserHistoryViewSet` described below.
Class description:
API endpoint that allows users to view their history
Method signatures and docstrings:
- def list(self, request, *args, **kwargs): Return a list of a users command history
- def retrieve(self, request, *args, **kwargs): Return a speci... | 85102bb41aa0d558a3fa088e4fd6f51613599ad0 | <|skeleton|>
class UserHistoryViewSet:
"""API endpoint that allows users to view their history"""
def list(self, request, *args, **kwargs):
"""Return a list of a users command history"""
<|body_0|>
def retrieve(self, request, *args, **kwargs):
"""Return a specific user's command"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserHistoryViewSet:
"""API endpoint that allows users to view their history"""
def list(self, request, *args, **kwargs):
"""Return a list of a users command history"""
username = kwargs.get('username', None)
self.pagination_class.page_size_query_param = 'length'
self.pagin... | the_stack_v2_python_sparse | orchestrator/core/orc_server/account/views/viewsets.py | g2-inc/openc2-oif-orchestrator | train | 1 |
bc7867a3e997939292ac0777ed17ead2a75c2a7c | [
"data = self.get_json()\nif 'obj_id' not in data:\n return self.error('Missing required parameter: obj_id')\nwith self.Session() as session:\n try:\n obj_id = post_thumbnail(data, self.associated_user_object.id, session)\n except Exception as e:\n return self.error(f'Thumbnail failed to post:... | <|body_start_0|>
data = self.get_json()
if 'obj_id' not in data:
return self.error('Missing required parameter: obj_id')
with self.Session() as session:
try:
obj_id = post_thumbnail(data, self.associated_user_object.id, session)
except Exceptio... | ThumbnailHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThumbnailHandler:
def post(self):
"""--- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: string description: ID of object associated with thumbnails. data: type: string format: byte description: base... | stack_v2_sparse_classes_36k_train_024705 | 22,926 | permissive | [
{
"docstring": "--- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: string description: ID of object associated with thumbnails. data: type: string format: byte description: base64-encoded PNG image file contents. Image siz... | 4 | null | Implement the Python class `ThumbnailHandler` described below.
Class description:
Implement the ThumbnailHandler class.
Method signatures and docstrings:
- def post(self): --- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: strin... | Implement the Python class `ThumbnailHandler` described below.
Class description:
Implement the ThumbnailHandler class.
Method signatures and docstrings:
- def post(self): --- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: strin... | 161d3532ba3ba059446addcdac58ca96f39e9636 | <|skeleton|>
class ThumbnailHandler:
def post(self):
"""--- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: string description: ID of object associated with thumbnails. data: type: string format: byte description: base... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThumbnailHandler:
def post(self):
"""--- description: Upload thumbnails tags: - thumbnails requestBody: content: application/json: schema: type: object properties: obj_id: type: string description: ID of object associated with thumbnails. data: type: string format: byte description: base64-encoded PNG... | the_stack_v2_python_sparse | skyportal/handlers/api/thumbnail.py | skyportal/skyportal | train | 80 | |
6db837e1bcaea8cf9b304017d511826394e1a2f3 | [
"userdb = CombaUser()\nif userdb.hasPassword(username, password):\n return userdb.getUser(username)\nelse:\n return False",
"valid_user = self.check_auth(username, password)\nif valid_user:\n group = None\n groupcreated = None\n try:\n user = User.objects.get(username=username)\n except U... | <|body_start_0|>
userdb = CombaUser()
if userdb.hasPassword(username, password):
return userdb.getUser(username)
else:
return False
<|end_body_0|>
<|body_start_1|>
valid_user = self.check_auth(username, password)
if valid_user:
group = None
... | Provides authentication via comba_lib | RedisBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
<|body_0|>
def authenticate(self, username=None, password=None):
"""Overwrite ... | stack_v2_sparse_classes_36k_train_024706 | 3,013 | no_license | [
{
"docstring": "check user and password in redis db :param username: :param password: :return:",
"name": "check_auth",
"signature": "def check_auth(self, username, password)"
},
{
"docstring": "Overwrite the parent authenticate method :param username: :param password: :return:",
"name": "aut... | 3 | stack_v2_sparse_classes_30k_test_000417 | Implement the Python class `RedisBackend` described below.
Class description:
Provides authentication via comba_lib
Method signatures and docstrings:
- def check_auth(self, username, password): check user and password in redis db :param username: :param password: :return:
- def authenticate(self, username=None, passw... | Implement the Python class `RedisBackend` described below.
Class description:
Provides authentication via comba_lib
Method signatures and docstrings:
- def check_auth(self, username, password): check user and password in redis db :param username: :param password: :return:
- def authenticate(self, username=None, passw... | eb6b8bca4f782f7aa8fbabd4fddbfddaae769252 | <|skeleton|>
class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
<|body_0|>
def authenticate(self, username=None, password=None):
"""Overwrite ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RedisBackend:
"""Provides authentication via comba_lib"""
def check_auth(self, username, password):
"""check user and password in redis db :param username: :param password: :return:"""
userdb = CombaUser()
if userdb.hasPassword(username, password):
return userdb.getUse... | the_stack_v2_python_sparse | comba_web/redisbackend.py | combaos/comba_web | train | 0 |
8c1348706b58cbc67772329a1d68007a4ec04dfe | [
"self.s = []\nself.m = []\nself.sset = set()\nself.mset = set()\nself.id = 0",
"self.s.append((x, self.id))\nhq.heappush(self.m, (-x, -self.id))\nself.id += 1",
"if self.top() is not None:\n d = self.s.pop()\n id = d[1]\n val = d[0]\n self.sset.add(id)\n return val",
"if self.s:\n while self... | <|body_start_0|>
self.s = []
self.m = []
self.sset = set()
self.mset = set()
self.id = 0
<|end_body_0|>
<|body_start_1|>
self.s.append((x, self.id))
hq.heappush(self.m, (-x, -self.id))
self.id += 1
<|end_body_1|>
<|body_start_2|>
if self.top() is... | MaxStack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaxStack:
def __init__(self):
"""initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int... | stack_v2_sparse_classes_36k_train_024707 | 3,412 | no_license | [
{
"docstring": "initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type x: int :rtype: None",
"name": "push",
"signature": "def push(self, x)"
},
{
... | 6 | null | Implement the Python class `MaxStack` described below.
Class description:
Implement the MaxStack class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態
- def push(self, x): :type x: int :rtype: None
- d... | Implement the Python class `MaxStack` described below.
Class description:
Implement the MaxStack class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態
- def push(self, x): :type x: int :rtype: None
- d... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class MaxStack:
def __init__(self):
"""initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態"""
<|body_0|>
def push(self, x):
""":type x: int :rtype: None"""
<|body_1|>
def pop(self):
""":rtype: int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MaxStack:
def __init__(self):
"""initialize your data structure here. 設計: stack 與 heap 的modification 為獨立事件 各自mark各自的tag 並且在modify時check對方的狀態"""
self.s = []
self.m = []
self.sset = set()
self.mset = set()
self.id = 0
def push(self, x):
""":type x: in... | the_stack_v2_python_sparse | stack/716_Max_Stack.py | vsdrun/lc_public | train | 6 | |
5d7080cfb443ae4a3770e890963b839edf77fb45 | [
"tg_instance = BuiltIn().get_library_instance('resources.libraries.python.TrafficGenerator')\ntg_instance.set_rate_provider_defaults(frame_size, traffic_profile)\nalgorithm = MultipleLossRatioSearch(measurer=tg_instance, final_trial_duration=final_trial_duration, final_relative_width=final_relative_width, number_of... | <|body_start_0|>
tg_instance = BuiltIn().get_library_instance('resources.libraries.python.TrafficGenerator')
tg_instance.set_rate_provider_defaults(frame_size, traffic_profile)
algorithm = MultipleLossRatioSearch(measurer=tg_instance, final_trial_duration=final_trial_duration, final_relative_wid... | Class to be imported as Robot Library, containing a single keyword. | OptimizedSearch | [
"CC-BY-4.0",
"Apache-2.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptimizedSearch:
"""Class to be imported as Robot Library, containing a single keyword."""
def perform_optimized_ndrpdr_search(frame_size, traffic_profile, minimum_transmit_rate, maximum_transmit_rate, packet_loss_ratio=0.005, final_relative_width=0.005, final_trial_duration=30.0, initial_tr... | stack_v2_sparse_classes_36k_train_024708 | 32,463 | permissive | [
{
"docstring": "Setup initialized TG, perform optimized search, return intervals. :param frame_size: Frame size identifier or value [B]. :param traffic_profile: Module name as a traffic profile identifier. See resources/traffic_profiles/trex for implemented modules. :param minimum_transmit_rate: Minimal bidirec... | 2 | null | Implement the Python class `OptimizedSearch` described below.
Class description:
Class to be imported as Robot Library, containing a single keyword.
Method signatures and docstrings:
- def perform_optimized_ndrpdr_search(frame_size, traffic_profile, minimum_transmit_rate, maximum_transmit_rate, packet_loss_ratio=0.00... | Implement the Python class `OptimizedSearch` described below.
Class description:
Class to be imported as Robot Library, containing a single keyword.
Method signatures and docstrings:
- def perform_optimized_ndrpdr_search(frame_size, traffic_profile, minimum_transmit_rate, maximum_transmit_rate, packet_loss_ratio=0.00... | 3151c98618c78e3782e48bbe4d9c8f906c126f69 | <|skeleton|>
class OptimizedSearch:
"""Class to be imported as Robot Library, containing a single keyword."""
def perform_optimized_ndrpdr_search(frame_size, traffic_profile, minimum_transmit_rate, maximum_transmit_rate, packet_loss_ratio=0.005, final_relative_width=0.005, final_trial_duration=30.0, initial_tr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptimizedSearch:
"""Class to be imported as Robot Library, containing a single keyword."""
def perform_optimized_ndrpdr_search(frame_size, traffic_profile, minimum_transmit_rate, maximum_transmit_rate, packet_loss_ratio=0.005, final_relative_width=0.005, final_trial_duration=30.0, initial_trial_duration=... | the_stack_v2_python_sparse | resources/libraries/python/TrafficGenerator.py | preym17/csit | train | 0 |
9996591799edd24e8b51773c0c8d8345e7891da7 | [
"agent = request.user.userinfo.agent\ncompany = request.user.userinfo.company\ndata = models.SSARuleManage.tree(agent, company)\nreturn Response({'data': data, 'status': 200, 'msg': '获取成功'})",
"obj_serializer = serializers.RuleManageSerializers(data=request.data, context={'request': request})\nif obj_serializer.i... | <|body_start_0|>
agent = request.user.userinfo.agent
company = request.user.userinfo.company
data = models.SSARuleManage.tree(agent, company)
return Response({'data': data, 'status': 200, 'msg': '获取成功'})
<|end_body_0|>
<|body_start_1|>
obj_serializer = serializers.RuleManageSeri... | 专家分析系统 | RuleManageList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def post(self, request):
"""添加规则"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
agent = request.user.userinfo.agent
company = request.user.userinfo.company
... | stack_v2_sparse_classes_36k_train_024709 | 4,124 | no_license | [
{
"docstring": "获取规则目录树",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "添加规则",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000590 | Implement the Python class `RuleManageList` described below.
Class description:
专家分析系统
Method signatures and docstrings:
- def get(self, request): 获取规则目录树
- def post(self, request): 添加规则 | Implement the Python class `RuleManageList` described below.
Class description:
专家分析系统
Method signatures and docstrings:
- def get(self, request): 获取规则目录树
- def post(self, request): 添加规则
<|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
<|body_0|>
def post(self, request):
"""添加规则"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RuleManageList:
"""专家分析系统"""
def get(self, request):
"""获取规则目录树"""
agent = request.user.userinfo.agent
company = request.user.userinfo.company
data = models.SSARuleManage.tree(agent, company)
return Response({'data': data, 'status': 200, 'msg': '获取成功'})
def po... | the_stack_v2_python_sparse | soc_ssa/views/experts_analysis.py | sundw2015/841 | train | 4 |
68fb771b41c6984b96e7a2e7418e1ab59169707b | [
"assert type(knots) is tuple\nassert type(order) is tuple\nassert type(boundary_knots) is tuple\nassert len(knots) == len(order)\nassert len(order) == len(boundary_knots)\nspl = []\nfor knts_i, k, knts_b, c in zip(knots, order, boundary_knots, coords):\n spl.append(bSpline(knts_i, k, knts_b))\nself.coords = coor... | <|body_start_0|>
assert type(knots) is tuple
assert type(order) is tuple
assert type(boundary_knots) is tuple
assert len(knots) == len(order)
assert len(order) == len(boundary_knots)
spl = []
for knts_i, k, knts_b, c in zip(knots, order, boundary_knots, coords):
... | TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatment in "Curve and Surface Fittnig with Splines". The algorithms aren't strictly the most... | TensorProductSpline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorProductSpline:
"""TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatment in "Curve and Surface Fittnig with Sp... | stack_v2_sparse_classes_36k_train_024710 | 12,005 | permissive | [
{
"docstring": "Constructor for the tensor product spline Construct the tensor product spline from spline definitions along each axis we're interested in. The tensor product spline is the cartesian product of splines in each dimension. Args: knots: tuple, with one array for each dimension, defined as for bSplin... | 4 | null | Implement the Python class `TensorProductSpline` described below.
Class description:
TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatmen... | Implement the Python class `TensorProductSpline` described below.
Class description:
TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatmen... | 6827886916e36432ce1d806f0a78edef6c9270d9 | <|skeleton|>
class TensorProductSpline:
"""TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatment in "Curve and Surface Fittnig with Sp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TensorProductSpline:
"""TensorProductSpline, a class for working with tensor splines Contains basic routines for evaluating tensor product splines, computing the Vandermonde-like matrix for a spline, and computing derivatives. Based on Paul Diercx's treatment in "Curve and Surface Fittnig with Splines". The a... | the_stack_v2_python_sparse | pybots/src/geometry/basis_spline.py | aivian/robots | train | 0 |
1c7d9b90b4a32c2de1c0f4311716b3cd49e72abc | [
"if matrix is None or len(matrix) == 0 or len(matrix[0]) == 0:\n return\nn = len(matrix)\nfor i in range(n // 2):\n for j in range(i, n - i - 1):\n tmp = matrix[i][j]\n matrix[i][j] = matrix[n - j - 1][i]\n matrix[n - j - 1][i] = matrix[n - i - 1][n - j - 1]\n matrix[n - i - 1][n -... | <|body_start_0|>
if matrix is None or len(matrix) == 0 or len(matrix[0]) == 0:
return
n = len(matrix)
for i in range(n // 2):
for j in range(i, n - i - 1):
tmp = matrix[i][j]
matrix[i][j] = matrix[n - j - 1][i]
matrix[n - j ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate2(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_36k_train_024711 | 1,556 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.",
"name": "rotate",
"signature": "def rotate(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-place instead.",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate2(self, matrix): :type matrix: List[List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix): :type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead.
- def rotate2(self, matrix): :type matrix: List[List[... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
<|body_0|>
def rotate2(self, matrix):
""":type matrix: List[List[int]] :rtype: None Do not return anything, modify matrix in-p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, matrix):
""":type matrix: List[List[int]] :rtype: void Do not return anything, modify matrix in-place instead."""
if matrix is None or len(matrix) == 0 or len(matrix[0]) == 0:
return
n = len(matrix)
for i in range(n // 2):
for ... | the_stack_v2_python_sparse | R/RotateImage.py | bssrdf/pyleet | train | 2 | |
88d39b3fae08bf6d8e2d2f7e663d69078a6ce975 | [
"self._log.debug('init')\nname = os.path.basename(p).split('.')[0]\nself._log.debug('Get logger name = %s', name)\nself.logger = logging.getLogger(name)",
"self._log.debug('get_tag')\nif not tag:\n self._log.debug('not tag')\n return\nelif type(tag) is str:\n self._log.debug('is str')\n return tag\nel... | <|body_start_0|>
self._log.debug('init')
name = os.path.basename(p).split('.')[0]
self._log.debug('Get logger name = %s', name)
self.logger = logging.getLogger(name)
<|end_body_0|>
<|body_start_1|>
self._log.debug('get_tag')
if not tag:
self._log.debug('not t... | Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object): def __init__(self): LOG.debug(self, 'init') @classmethod def class_meth... | Logger | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logger:
"""Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object): def __init__(self): LOG.debug(self, '... | stack_v2_sparse_classes_36k_train_024712 | 15,106 | permissive | [
{
"docstring": "Init logger given a path string like __file__ (or a custom name).",
"name": "__init__",
"signature": "def __init__(self, p)"
},
{
"docstring": "Given a tag (e.g. None, 'tag', cls, self) return None or a string. The returned tag string is determined from the class name or string p... | 3 | stack_v2_sparse_classes_30k_train_000356 | Implement the Python class `Logger` described below.
Class description:
Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object)... | Implement the Python class `Logger` described below.
Class description:
Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object)... | 1b876810cc1a61d70f061fa554b03c5ad54c813c | <|skeleton|>
class Logger:
"""Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object): def __init__(self): LOG.debug(self, '... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logger:
"""Custom logger wrapper. Typical use includes the module (file) and class name in the log output. By creating a module logger with the file name and adding a 'tag' to the message. Usage: # module.py: LOG = Logger(__file__) class ExampleClass(object): def __init__(self): LOG.debug(self, 'init') @class... | the_stack_v2_python_sparse | common.py | gavingc/TuckerSync | train | 0 |
2d581072b8629f9a56c20d08d7b4bc6f2ac77cd9 | [
"user_pref = user_models.UserPref.get_signed_in_user_pref()\nif not user_pref:\n self.abort(403, msg='User must be signed in')\nnew_notify = self.get_bool_param('notify')\nuser_pref.notify_as_starrer = new_notify\nuser_pref.put()\nreturn {'message': 'Done'}",
"user_pref = user_models.UserPref.get_signed_in_use... | <|body_start_0|>
user_pref = user_models.UserPref.get_signed_in_user_pref()
if not user_pref:
self.abort(403, msg='User must be signed in')
new_notify = self.get_bool_param('notify')
user_pref.notify_as_starrer = new_notify
user_pref.put()
return {'message': '... | Users can store their settings preferences such as whether to get notification from the features they starred. | SettingsAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SettingsAPI:
"""Users can store their settings preferences such as whether to get notification from the features they starred."""
def do_post(self, **kwargs):
"""Set the user settings (currently only the notify_as_starrer)"""
<|body_0|>
def do_get(self, **kwargs):
... | stack_v2_sparse_classes_36k_train_024713 | 1,588 | permissive | [
{
"docstring": "Set the user settings (currently only the notify_as_starrer)",
"name": "do_post",
"signature": "def do_post(self, **kwargs)"
},
{
"docstring": "Return the user settings (currently only the notify_as_starrer)",
"name": "do_get",
"signature": "def do_get(self, **kwargs)"
... | 2 | null | Implement the Python class `SettingsAPI` described below.
Class description:
Users can store their settings preferences such as whether to get notification from the features they starred.
Method signatures and docstrings:
- def do_post(self, **kwargs): Set the user settings (currently only the notify_as_starrer)
- de... | Implement the Python class `SettingsAPI` described below.
Class description:
Users can store their settings preferences such as whether to get notification from the features they starred.
Method signatures and docstrings:
- def do_post(self, **kwargs): Set the user settings (currently only the notify_as_starrer)
- de... | 17f9886d064da5bda84006d5866077727646fff2 | <|skeleton|>
class SettingsAPI:
"""Users can store their settings preferences such as whether to get notification from the features they starred."""
def do_post(self, **kwargs):
"""Set the user settings (currently only the notify_as_starrer)"""
<|body_0|>
def do_get(self, **kwargs):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SettingsAPI:
"""Users can store their settings preferences such as whether to get notification from the features they starred."""
def do_post(self, **kwargs):
"""Set the user settings (currently only the notify_as_starrer)"""
user_pref = user_models.UserPref.get_signed_in_user_pref()
... | the_stack_v2_python_sparse | api/settings_api.py | GoogleChrome/chromium-dashboard | train | 574 |
e14770f6fb324f8a37e997f57eb98353c5081c99 | [
"super(DecoderBlock, self).__init__()\nself.mha1 = MultiHeadAttention(dm, h)\nself.mha2 = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernor... | <|body_start_0|>
super(DecoderBlock, self).__init__()
self.mha1 = MultiHeadAttention(dm, h)
self.mha2 = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(dm)
self.layernorm1 = tf.keras.... | the Transformer decoder block class | DecoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderBlock:
"""the Transformer decoder block class"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer drop_rate: dropout rate"""
<|body_0|>
def c... | stack_v2_sparse_classes_36k_train_024714 | 2,383 | no_license | [
{
"docstring": "Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer drop_rate: dropout rate",
"name": "__init__",
"signature": "def __init__(self, dm, h, hidden, drop_rate=0.1)"
},
{
"docstring": "the call method for the transfor... | 2 | null | Implement the Python class `DecoderBlock` described below.
Class description:
the Transformer decoder block class
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer... | Implement the Python class `DecoderBlock` described below.
Class description:
the Transformer decoder block class
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer... | d86b0e0cae2dd07c761f84a493abc895007873ee | <|skeleton|>
class DecoderBlock:
"""the Transformer decoder block class"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer drop_rate: dropout rate"""
<|body_0|>
def c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderBlock:
"""the Transformer decoder block class"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""Decoder block initializer dm: in dimensionality of model h: number of heads hidden: number of hidden units in FC layer drop_rate: dropout rate"""
super(DecoderBlock, self).__init__... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/8-transformer_decoder_block.py | mag389/holbertonschool-machine_learning | train | 2 |
ee79346eb9b225e02af30451ec164fb470090525 | [
"self.d = dict()\nfor i in range(len(words)):\n w = words[i]\n if w in self.d:\n self.d[w].append(i)\n else:\n self.d[w] = [i]",
"l1 = self.d[word1]\nl2 = self.d[word2]\nres = float('inf')\nfor i in range(len(l1)):\n nl = list(map(lambda x: abs(x - l1[i]), l2))\n res = min(res, min(nl... | <|body_start_0|>
self.d = dict()
for i in range(len(words)):
w = words[i]
if w in self.d:
self.d[w].append(i)
else:
self.d[w] = [i]
<|end_body_0|>
<|body_start_1|>
l1 = self.d[word1]
l2 = self.d[word2]
res = flo... | WordDistance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.d = dict()
for i in rang... | stack_v2_sparse_classes_36k_train_024715 | 1,448 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005687 | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|skeleton|>
class WordDistance:
... | 29543f8da4881b9b8a08a39e510a77c1036c8386 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
self.d = dict()
for i in range(len(words)):
w = words[i]
if w in self.d:
self.d[w].append(i)
else:
self.d[w] = [i]
def shortest(self, word1, wo... | the_stack_v2_python_sparse | 244-shortest-word-distance-ii/shortest-word-distance-ii.py | Cccmm002/my_leetcode | train | 0 | |
bab16ada7b2c468c25cdc4e6494e17449401c03f | [
"q = db().query(cls.model)\nif lock_for_update:\n q = q.with_lockmode('update')\nres = q.first()\nif not res and fail_if_not_found:\n raise errors.ObjectNotFound(\"Object '{0}' is not found in DB\".format(cls.__name__))\nreturn res",
"data.pop('master_node_uid', None)\nsuper(MasterNodeSettings, cls).update(... | <|body_start_0|>
q = db().query(cls.model)
if lock_for_update:
q = q.with_lockmode('update')
res = q.first()
if not res and fail_if_not_found:
raise errors.ObjectNotFound("Object '{0}' is not found in DB".format(cls.__name__))
return res
<|end_body_0|>
<|... | MasterNodeSettings | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MasterNodeSettings:
def get_one(cls, fail_if_not_found=False, lock_for_update=False):
"""Get one instance from table. :param fail_if_not_found: raise an exception if object is not found :param lock_for_update: lock returned object for update (DB mutex) :return: instance of an object (mod... | stack_v2_sparse_classes_36k_train_024716 | 3,310 | permissive | [
{
"docstring": "Get one instance from table. :param fail_if_not_found: raise an exception if object is not found :param lock_for_update: lock returned object for update (DB mutex) :return: instance of an object (model)",
"name": "get_one",
"signature": "def get_one(cls, fail_if_not_found=False, lock_for... | 3 | null | Implement the Python class `MasterNodeSettings` described below.
Class description:
Implement the MasterNodeSettings class.
Method signatures and docstrings:
- def get_one(cls, fail_if_not_found=False, lock_for_update=False): Get one instance from table. :param fail_if_not_found: raise an exception if object is not f... | Implement the Python class `MasterNodeSettings` described below.
Class description:
Implement the MasterNodeSettings class.
Method signatures and docstrings:
- def get_one(cls, fail_if_not_found=False, lock_for_update=False): Get one instance from table. :param fail_if_not_found: raise an exception if object is not f... | 0e09dce510927f2cc490b898e5fe3f813bd791be | <|skeleton|>
class MasterNodeSettings:
def get_one(cls, fail_if_not_found=False, lock_for_update=False):
"""Get one instance from table. :param fail_if_not_found: raise an exception if object is not found :param lock_for_update: lock returned object for update (DB mutex) :return: instance of an object (mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MasterNodeSettings:
def get_one(cls, fail_if_not_found=False, lock_for_update=False):
"""Get one instance from table. :param fail_if_not_found: raise an exception if object is not found :param lock_for_update: lock returned object for update (DB mutex) :return: instance of an object (model)"""
... | the_stack_v2_python_sparse | nailgun/nailgun/objects/master_node_settings.py | mba811/fuel-web | train | 1 | |
aa046820e8fc249515cce130237f2fc992825129 | [
"super(MyImageNet22K, self).__init__(root, *args, **kwargs)\nself.exclude_imagenet1k = exclude_imagenet1k\nself.shuffle_idxs = False\nself.size = size\nif exclude_imagenet1k:\n self.samples = [s for s in self.samples if not any([idx in s[0] for idx in self.imagenet1k_idxs])]",
"path, target = self.samples[inde... | <|body_start_0|>
super(MyImageNet22K, self).__init__(root, *args, **kwargs)
self.exclude_imagenet1k = exclude_imagenet1k
self.shuffle_idxs = False
self.size = size
if exclude_imagenet1k:
self.samples = [s for s in self.samples if not any([idx in s[0] for idx in self.i... | MyImageNet22K | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyImageNet22K:
def __init__(self, root: str, size: torch.Size, exclude_imagenet1k=True, *args, **kwargs):
"""Implements a torchvision style ImageNet22k dataset. The dataset needs to be downloaded manually and put in the according directory. Since the dataset is very large, it happens tha... | stack_v2_sparse_classes_36k_train_024717 | 13,359 | permissive | [
{
"docstring": "Implements a torchvision style ImageNet22k dataset. The dataset needs to be downloaded manually and put in the according directory. Since the dataset is very large, it happens that some of the image files are broken. In this case, a warning is logged during training and a black image is returned... | 2 | stack_v2_sparse_classes_30k_train_019797 | Implement the Python class `MyImageNet22K` described below.
Class description:
Implement the MyImageNet22K class.
Method signatures and docstrings:
- def __init__(self, root: str, size: torch.Size, exclude_imagenet1k=True, *args, **kwargs): Implements a torchvision style ImageNet22k dataset. The dataset needs to be d... | Implement the Python class `MyImageNet22K` described below.
Class description:
Implement the MyImageNet22K class.
Method signatures and docstrings:
- def __init__(self, root: str, size: torch.Size, exclude_imagenet1k=True, *args, **kwargs): Implements a torchvision style ImageNet22k dataset. The dataset needs to be d... | 7af3d8eadabee81ab8f7db5dea7f8389ef090213 | <|skeleton|>
class MyImageNet22K:
def __init__(self, root: str, size: torch.Size, exclude_imagenet1k=True, *args, **kwargs):
"""Implements a torchvision style ImageNet22k dataset. The dataset needs to be downloaded manually and put in the according directory. Since the dataset is very large, it happens tha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyImageNet22K:
def __init__(self, root: str, size: torch.Size, exclude_imagenet1k=True, *args, **kwargs):
"""Implements a torchvision style ImageNet22k dataset. The dataset needs to be downloaded manually and put in the according directory. Since the dataset is very large, it happens that some of the ... | the_stack_v2_python_sparse | python/fcdd/datasets/outlier_exposure/imagenet.py | hkhaledmohamed/fcdd | train | 0 | |
22a60725b00e3dcdf96c58fae81969a0508687f2 | [
"self.cmd = cmd\nself.environment = os.environ\nprocess = subprocess.Popen(['which', self.cmd[0]], env=self.environment, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\nself.stdout, self.stderr = process.communicate()\nself.exitcode = process.returncode\nif self.exitcode != 0:\n raise ConnectomistConfigurationE... | <|body_start_0|>
self.cmd = cmd
self.environment = os.environ
process = subprocess.Popen(['which', self.cmd[0]], env=self.environment, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
self.stdout, self.stderr = process.communicate()
self.exitcode = process.returncode
if se... | Parent class for the wrapping of Connectomist Ptk functions. | PtkWrapper | [
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PtkWrapper:
"""Parent class for the wrapping of Connectomist Ptk functions."""
def __init__(self, cmd):
"""Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute."""
<|body_0|>
def __call__(self, files_to_ch... | stack_v2_sparse_classes_36k_train_024718 | 8,020 | permissive | [
{
"docstring": "Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute.",
"name": "__init__",
"signature": "def __init__(self, cmd)"
},
{
"docstring": "Run the Connectomist Ptk command. Parameters ---------- files_to_check: list of ... | 2 | stack_v2_sparse_classes_30k_train_001052 | Implement the Python class `PtkWrapper` described below.
Class description:
Parent class for the wrapping of Connectomist Ptk functions.
Method signatures and docstrings:
- def __init__(self, cmd): Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute.
... | Implement the Python class `PtkWrapper` described below.
Class description:
Parent class for the wrapping of Connectomist Ptk functions.
Method signatures and docstrings:
- def __init__(self, cmd): Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute.
... | 3105d2b1e4458c3be398391436be54bf59949a34 | <|skeleton|>
class PtkWrapper:
"""Parent class for the wrapping of Connectomist Ptk functions."""
def __init__(self, cmd):
"""Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute."""
<|body_0|>
def __call__(self, files_to_ch... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PtkWrapper:
"""Parent class for the wrapping of Connectomist Ptk functions."""
def __init__(self, cmd):
"""Initialize the PtkWrapper class Parameters ---------- cmd: list of str (mandatory) the Morphologist command to execute."""
self.cmd = cmd
self.environment = os.environ
... | the_stack_v2_python_sparse | clindmri/extensions/connectomist/wrappers.py | neurospin/caps-clindmri | train | 0 |
0a463924803fd0fd6693929e892b0529410abac5 | [
"self.regex = regex\nm = len(regex)\nself.m = m\nops = Stack()\ngraph = Digraph(m + 1)\nfor i in range(0, m):\n lp = i\n if regex[i] == '(' or regex[i] == '|':\n ops.push(i)\n elif regex[i] == ')':\n or_ = ops.pop()\n if regex[or_] == '|':\n lp = ops.pop()\n graph... | <|body_start_0|>
self.regex = regex
m = len(regex)
self.m = m
ops = Stack()
graph = Digraph(m + 1)
for i in range(0, m):
lp = i
if regex[i] == '(' or regex[i] == '|':
ops.push(i)
elif regex[i] == ')':
or_... | The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, closure, binary or, and parentheses, metacharacters (either in the text... | NFA | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NFA:
"""The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, closure, binary or, and parentheses, met... | stack_v2_sparse_classes_36k_train_024719 | 3,293 | no_license | [
{
"docstring": "Initializes the NFA from the specified regular expression. :param regex: the regular expression",
"name": "__init__",
"signature": "def __init__(self, regex)"
},
{
"docstring": "Returns True if the text is matched by the regular expression. :param txt: the text :returns: True if ... | 2 | stack_v2_sparse_classes_30k_train_021051 | Implement the Python class `NFA` described below.
Class description:
The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, c... | Implement the Python class `NFA` described below.
Class description:
The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, c... | 658e3a42b712fb79a4afc8c3acf24161bd5d6737 | <|skeleton|>
class NFA:
"""The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, closure, binary or, and parentheses, met... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NFA:
"""The NFA class provides a data type for creating a nondeterministic finite state automaton (NFA) from a regular expression and testing whether a given string is matched by that regular expression. It supports the following operations: concatenation, closure, binary or, and parentheses, metacharacters (... | the_stack_v2_python_sparse | algs4/strings/nfa.py | bhavyaagg/python-test | train | 0 |
88260242b8609eb63a87062ea9931c3290e37d3e | [
"if not 0 <= maxBirthProb <= 1:\n raise ValueError\nif not 0 <= clearProb <= 1:\n raise ValueError\nelse:\n self.maxBirthProb = maxBirthProb\n self.clearProb = clearProb",
"potential = random.random()\nif potential <= self.clearProb:\n return True\nreturn False",
"self.popDensity = popDensity\nPo... | <|body_start_0|>
if not 0 <= maxBirthProb <= 1:
raise ValueError
if not 0 <= clearProb <= 1:
raise ValueError
else:
self.maxBirthProb = maxBirthProb
self.clearProb = clearProb
<|end_body_0|>
<|body_start_1|>
potential = random.random()
... | Representation of a simple virus (does not model drug effects/resistance). | SimpleVirus | [
"Giftware"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleVirus:
"""Representation of a simple virus (does not model drug effects/resistance)."""
def __init__(self, maxBirthProb, clearProb):
"""Initialize a SimpleVirus instance, saves all parameters as attributes of the instance. maxBirthProb: Maximum reproduction probability (a float... | stack_v2_sparse_classes_36k_train_024720 | 28,689 | permissive | [
{
"docstring": "Initialize a SimpleVirus instance, saves all parameters as attributes of the instance. maxBirthProb: Maximum reproduction probability (a float between 0-1) clearProb: Maximum clearance probability (a float between 0-1).",
"name": "__init__",
"signature": "def __init__(self, maxBirthProb,... | 3 | stack_v2_sparse_classes_30k_train_001966 | Implement the Python class `SimpleVirus` described below.
Class description:
Representation of a simple virus (does not model drug effects/resistance).
Method signatures and docstrings:
- def __init__(self, maxBirthProb, clearProb): Initialize a SimpleVirus instance, saves all parameters as attributes of the instance... | Implement the Python class `SimpleVirus` described below.
Class description:
Representation of a simple virus (does not model drug effects/resistance).
Method signatures and docstrings:
- def __init__(self, maxBirthProb, clearProb): Initialize a SimpleVirus instance, saves all parameters as attributes of the instance... | 6f7dab3b1ef188b1ace0dba72eed78843879e9e7 | <|skeleton|>
class SimpleVirus:
"""Representation of a simple virus (does not model drug effects/resistance)."""
def __init__(self, maxBirthProb, clearProb):
"""Initialize a SimpleVirus instance, saves all parameters as attributes of the instance. maxBirthProb: Maximum reproduction probability (a float... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SimpleVirus:
"""Representation of a simple virus (does not model drug effects/resistance)."""
def __init__(self, maxBirthProb, clearProb):
"""Initialize a SimpleVirus instance, saves all parameters as attributes of the instance. maxBirthProb: Maximum reproduction probability (a float between 0-1)... | the_stack_v2_python_sparse | MIT/Problem sets/ps12.py | CStage/MIT-Git | train | 0 |
07b6c0c2357ca2ab7198d756806b861fc705b913 | [
"super(DenseLayers, self).__init__(name=name, **kwargs)\nif any((size < 1 for size in hidden_sizes)):\n raise ValueError('All sizes in `hidden_sizes` must be positive.')\nself.hidden_sizes = hidden_sizes\nself.activation = tf.keras.activations.get(activation)\nself.use_bias = use_bias\nself.kernel_initializer = ... | <|body_start_0|>
super(DenseLayers, self).__init__(name=name, **kwargs)
if any((size < 1 for size in hidden_sizes)):
raise ValueError('All sizes in `hidden_sizes` must be positive.')
self.hidden_sizes = hidden_sizes
self.activation = tf.keras.activations.get(activation)
... | Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one, which will not have any activation. | DenseLayers | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DenseLayers:
"""Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one, which will not have any activation.""... | stack_v2_sparse_classes_36k_train_024721 | 4,381 | permissive | [
{
"docstring": "Init. Args: hidden_sizes: List of hidden layer sizes, one for each layer in order. The last integer will be the layer size of the output. activation: Activation function to use. If you don't specify anything, no activation is applied (i.e. \"linear\" activation: a(x) = x). Note that the last lay... | 2 | stack_v2_sparse_classes_30k_train_005108 | Implement the Python class `DenseLayers` described below.
Class description:
Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one... | Implement the Python class `DenseLayers` described below.
Class description:
Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class DenseLayers:
"""Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one, which will not have any activation.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DenseLayers:
"""Convenience class for stacking Dense layers. The result is a simple fully-connected network with `len(hidden_sizes)` layers, the last of which is the output. The given activation function will be applied to every layer except for the last one, which will not have any activation."""
def __... | the_stack_v2_python_sparse | readtwice/layers/helpers.py | Jimmy-INL/google-research | train | 1 |
b91e44f770a2a4dc2566ef805425b59d8b80881d | [
"filters = {}\nfor field in self.lookup_field:\n if self.request.GET.get(field, None):\n if field in self.varchar_fields:\n filters[field] = ast.literal_eval(self.request.GET.get(field, None))\n elif field in self.int_fields:\n filters[field] = int(self.request.GET.get(field, ... | <|body_start_0|>
filters = {}
for field in self.lookup_field:
if self.request.GET.get(field, None):
if field in self.varchar_fields:
filters[field] = ast.literal_eval(self.request.GET.get(field, None))
elif field in self.int_fields:
... | A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data. | ListFilterAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListFilterAPIView:
"""A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data."""
def get_filters(self):
"""Method which creates the filters dict. Matches the given Parameters from the request with the allowed looku... | stack_v2_sparse_classes_36k_train_024722 | 13,273 | permissive | [
{
"docstring": "Method which creates the filters dict. Matches the given Parameters from the request with the allowed lookup_fields, and only maps non-empty fields.",
"name": "get_filters",
"signature": "def get_filters(self)"
},
{
"docstring": "Method which returns the filtered Queryset.",
... | 2 | stack_v2_sparse_classes_30k_train_003645 | Implement the Python class `ListFilterAPIView` described below.
Class description:
A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data.
Method signatures and docstrings:
- def get_filters(self): Method which creates the filters dict. Matches the... | Implement the Python class `ListFilterAPIView` described below.
Class description:
A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data.
Method signatures and docstrings:
- def get_filters(self): Method which creates the filters dict. Matches the... | 8c5bc4c9ba9759b58b52ddf339ccaec40ec5f6ea | <|skeleton|>
class ListFilterAPIView:
"""A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data."""
def get_filters(self):
"""Method which creates the filters dict. Matches the given Parameters from the request with the allowed looku... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListFilterAPIView:
"""A View which creates a filters dict and returns a List of objects matching alle given Filters. View only for Retrieving Data."""
def get_filters(self):
"""Method which creates the filters dict. Matches the given Parameters from the request with the allowed lookup_fields, and... | the_stack_v2_python_sparse | geomat/stein/views.py | GeoMatDigital/django-geomat | train | 3 |
d22b509c66f8f33f775b72f89dc11d123ee56747 | [
"while i < j:\n array[i], array[j] = (array[j], array[i])\n i += 1\n j -= 1",
"for i in range(len(array) - 1, 0, -1):\n if array[i] > array[i - 1]:\n break\nelse:\n array.reverse()\n return\nfor j in range(len(array) - 1, i - 1, -1):\n if array[j] > array[i - 1]:\n array[j], arr... | <|body_start_0|>
while i < j:
array[i], array[j] = (array[j], array[i])
i += 1
j -= 1
<|end_body_0|>
<|body_start_1|>
for i in range(len(array) - 1, 0, -1):
if array[i] > array[i - 1]:
break
else:
array.reverse()
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse_array(self, array, i, j):
"""Reverses array in-place from index i to j."""
<|body_0|>
def next_permutation(self, array):
"""Generates next lexicographical permutation of an array. Modifies array in-place, doesn't return anything."""
<|bo... | stack_v2_sparse_classes_36k_train_024723 | 3,435 | no_license | [
{
"docstring": "Reverses array in-place from index i to j.",
"name": "reverse_array",
"signature": "def reverse_array(self, array, i, j)"
},
{
"docstring": "Generates next lexicographical permutation of an array. Modifies array in-place, doesn't return anything.",
"name": "next_permutation",... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_array(self, array, i, j): Reverses array in-place from index i to j.
- def next_permutation(self, array): Generates next lexicographical permutation of an array. Modi... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse_array(self, array, i, j): Reverses array in-place from index i to j.
- def next_permutation(self, array): Generates next lexicographical permutation of an array. Modi... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def reverse_array(self, array, i, j):
"""Reverses array in-place from index i to j."""
<|body_0|>
def next_permutation(self, array):
"""Generates next lexicographical permutation of an array. Modifies array in-place, doesn't return anything."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse_array(self, array, i, j):
"""Reverses array in-place from index i to j."""
while i < j:
array[i], array[j] = (array[j], array[i])
i += 1
j -= 1
def next_permutation(self, array):
"""Generates next lexicographical permutatio... | the_stack_v2_python_sparse | Backtracking/permutation_sequence.py | vladn90/Algorithms | train | 0 | |
6912719ddd454307106777e35f3e6f03ce3ee769 | [
"self.reuse = False\nself.batch_size = batch_size\nself.num_channels = num_channels\nself.layer_stage_sizes = layer_stage_sizes\nself.name = name\nself.num_classes = num_classes\nself.batch_norm_use = batch_norm_use\nself.inner_layer_depth = inner_layer_depth\nself.strided_dim_reduction = strided_dim_reduction\nsel... | <|body_start_0|>
self.reuse = False
self.batch_size = batch_size
self.num_channels = num_channels
self.layer_stage_sizes = layer_stage_sizes
self.name = name
self.num_classes = num_classes
self.batch_norm_use = batch_norm_use
self.inner_layer_depth = inner... | VGGClassifier | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VGGClassifier:
def __init__(self, batch_size, layer_stage_sizes, name, num_classes, num_channels=1, batch_norm_use=False, inner_layer_depth=2, strided_dim_reduction=True):
"""Initializes a VGG Classifier architecture :param batch_size: The size of the data batch :param layer_stage_sizes:... | stack_v2_sparse_classes_36k_train_024724 | 9,392 | permissive | [
{
"docstring": "Initializes a VGG Classifier architecture :param batch_size: The size of the data batch :param layer_stage_sizes: A list containing the filters for each layer stage, where layer stage is a series of convolutional layers with stride=1 and no max pooling followed by a dimensionality reducing stage... | 2 | null | Implement the Python class `VGGClassifier` described below.
Class description:
Implement the VGGClassifier class.
Method signatures and docstrings:
- def __init__(self, batch_size, layer_stage_sizes, name, num_classes, num_channels=1, batch_norm_use=False, inner_layer_depth=2, strided_dim_reduction=True): Initializes... | Implement the Python class `VGGClassifier` described below.
Class description:
Implement the VGGClassifier class.
Method signatures and docstrings:
- def __init__(self, batch_size, layer_stage_sizes, name, num_classes, num_channels=1, batch_norm_use=False, inner_layer_depth=2, strided_dim_reduction=True): Initializes... | 2831df3ef210cb3e259bbc43dd39159533f4a33e | <|skeleton|>
class VGGClassifier:
def __init__(self, batch_size, layer_stage_sizes, name, num_classes, num_channels=1, batch_norm_use=False, inner_layer_depth=2, strided_dim_reduction=True):
"""Initializes a VGG Classifier architecture :param batch_size: The size of the data batch :param layer_stage_sizes:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VGGClassifier:
def __init__(self, batch_size, layer_stage_sizes, name, num_classes, num_channels=1, batch_norm_use=False, inner_layer_depth=2, strided_dim_reduction=True):
"""Initializes a VGG Classifier architecture :param batch_size: The size of the data batch :param layer_stage_sizes: A list contai... | the_stack_v2_python_sparse | network_architectures.py | comRamona/ACL-2018-Multimodal-Sentiment-Analysis-Multicomp | train | 0 | |
bacde2ae00408dda8f5d833ececa4d3dbc1fd5bc | [
"session_id = super().create_session(user_id)\nif session_id is None:\n return None\nuser_session = UserSession(user_id=user_id, session_id=session_id)\nif user_session is None:\n return None\nuser_session.save()\nUserSession.save_to_file()\nreturn session_id",
"if session_id is None:\n return None\nUser... | <|body_start_0|>
session_id = super().create_session(user_id)
if session_id is None:
return None
user_session = UserSession(user_id=user_id, session_id=session_id)
if user_session is None:
return None
user_session.save()
UserSession.save_to_file()
... | Session in database Class | SessionDBAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionDBAuth:
"""Session in database Class"""
def create_session(self, user_id=None):
"""Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Make user i... | stack_v2_sparse_classes_36k_train_024725 | 2,328 | no_license | [
{
"docstring": "Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "Make user id to session Args: session_id: String of the session Return: User ID if no... | 3 | stack_v2_sparse_classes_30k_val_001092 | Implement the Python class `SessionDBAuth` described below.
Class description:
Session in database Class
Method signatures and docstrings:
- def create_session(self, user_id=None): Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID
- def user_id_for_session_id(self, session_... | Implement the Python class `SessionDBAuth` described below.
Class description:
Session in database Class
Method signatures and docstrings:
- def create_session(self, user_id=None): Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID
- def user_id_for_session_id(self, session_... | fa0b08c37ece2510d450a8ad01d43ce48d18357b | <|skeleton|>
class SessionDBAuth:
"""Session in database Class"""
def create_session(self, user_id=None):
"""Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""Make user i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionDBAuth:
"""Session in database Class"""
def create_session(self, user_id=None):
"""Make a new Session to Database Args: user_id: Identificator of the user_id Return: Session ID"""
session_id = super().create_session(user_id)
if session_id is None:
return None
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_db_auth.py | Zaccheaus90/holbertonschool-web_back_end-1 | train | 0 |
e6526b64c01934a79e23ff7e09453e45b7bf96b2 | [
"self.input = 'AlgoExpert is the best!'\nself.output = 'best! the is AlgoExpert'\nreturn (self.input, self.output)",
"input_str, output_arr = self.setUp()\noutput = reverseWordsInString(input_str)\nself.assertEqual(output, output_arr)"
] | <|body_start_0|>
self.input = 'AlgoExpert is the best!'
self.output = 'best! the is AlgoExpert'
return (self.input, self.output)
<|end_body_0|>
<|body_start_1|>
input_str, output_arr = self.setUp()
output = reverseWordsInString(input_str)
self.assertEqual(output, output_... | Class with unittests for ReverseWordsInString.py | test_ReverseWordsInString | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_ReverseWordsInString:
"""Class with unittests for ReverseWordsInString.py"""
def setUp(self):
"""Sets up input."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_024726 | 898 | no_license | [
{
"docstring": "Sets up input.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Checks if returned output is as expected.",
"name": "test_ExpectedOutput",
"signature": "def test_ExpectedOutput(self)"
}
] | 2 | null | Implement the Python class `test_ReverseWordsInString` described below.
Class description:
Class with unittests for ReverseWordsInString.py
Method signatures and docstrings:
- def setUp(self): Sets up input.
- def test_ExpectedOutput(self): Checks if returned output is as expected. | Implement the Python class `test_ReverseWordsInString` described below.
Class description:
Class with unittests for ReverseWordsInString.py
Method signatures and docstrings:
- def setUp(self): Sets up input.
- def test_ExpectedOutput(self): Checks if returned output is as expected.
<|skeleton|>
class test_ReverseWor... | 3aa62ad36c3b06b2a3b05f1f8e2a9e21d68b371f | <|skeleton|>
class test_ReverseWordsInString:
"""Class with unittests for ReverseWordsInString.py"""
def setUp(self):
"""Sets up input."""
<|body_0|>
def test_ExpectedOutput(self):
"""Checks if returned output is as expected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_ReverseWordsInString:
"""Class with unittests for ReverseWordsInString.py"""
def setUp(self):
"""Sets up input."""
self.input = 'AlgoExpert is the best!'
self.output = 'best! the is AlgoExpert'
return (self.input, self.output)
def test_ExpectedOutput(self):
... | the_stack_v2_python_sparse | AlgoExpert_algorithms/Medium/ReverseWordsInString/test_ReverseWordsInString.py | JakubKazimierski/PythonPortfolio | train | 9 |
68773e40edbd3d6b138ede3d676decacb28d558a | [
"hunt_urn = rdfvalue.RDFURN(request.REQ.get('hunt_id'))\nwith aff4.FACTORY.Open(hunt_urn, aff4_type='GRRHunt', token=request.token) as hunt:\n runner = hunt.GetRunner()\n hunt_args = rdfvalue.ModifyHuntFlowArgs(client_limit=runner.args.client_limit, expiry_time=runner.context.expires)\n self.hunt_params_fo... | <|body_start_0|>
hunt_urn = rdfvalue.RDFURN(request.REQ.get('hunt_id'))
with aff4.FACTORY.Open(hunt_urn, aff4_type='GRRHunt', token=request.token) as hunt:
runner = hunt.GetRunner()
hunt_args = rdfvalue.ModifyHuntFlowArgs(client_limit=runner.args.client_limit, expiry_time=runner.... | Dialog that allows user to modify certain hunt parameters. | ModifyHuntDialog | [
"Apache-2.0",
"DOC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifyHuntDialog:
"""Dialog that allows user to modify certain hunt parameters."""
def Layout(self, request, response):
"""Layout handler."""
<|body_0|>
def RenderAjax(self, request, response):
"""Starts ModifyHuntFlow that actually modifies a hunt."""
<|... | stack_v2_sparse_classes_36k_train_024727 | 47,444 | permissive | [
{
"docstring": "Layout handler.",
"name": "Layout",
"signature": "def Layout(self, request, response)"
},
{
"docstring": "Starts ModifyHuntFlow that actually modifies a hunt.",
"name": "RenderAjax",
"signature": "def RenderAjax(self, request, response)"
}
] | 2 | null | Implement the Python class `ModifyHuntDialog` described below.
Class description:
Dialog that allows user to modify certain hunt parameters.
Method signatures and docstrings:
- def Layout(self, request, response): Layout handler.
- def RenderAjax(self, request, response): Starts ModifyHuntFlow that actually modifies ... | Implement the Python class `ModifyHuntDialog` described below.
Class description:
Dialog that allows user to modify certain hunt parameters.
Method signatures and docstrings:
- def Layout(self, request, response): Layout handler.
- def RenderAjax(self, request, response): Starts ModifyHuntFlow that actually modifies ... | ba1648b97a76f844ffb8e1891cc9e2680f9b1c6e | <|skeleton|>
class ModifyHuntDialog:
"""Dialog that allows user to modify certain hunt parameters."""
def Layout(self, request, response):
"""Layout handler."""
<|body_0|>
def RenderAjax(self, request, response):
"""Starts ModifyHuntFlow that actually modifies a hunt."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModifyHuntDialog:
"""Dialog that allows user to modify certain hunt parameters."""
def Layout(self, request, response):
"""Layout handler."""
hunt_urn = rdfvalue.RDFURN(request.REQ.get('hunt_id'))
with aff4.FACTORY.Open(hunt_urn, aff4_type='GRRHunt', token=request.token) as hunt:
... | the_stack_v2_python_sparse | gui/plugins/hunt_view.py | defaultnamehere/grr | train | 3 |
a96ffdcbcb7a08673b65f6039442c24c0868e93e | [
"self.cf = cf\nwf = ListReader(cf, 'whitelist', need_compiled_ix=False)\nwhitelist = wf.srcdict.keys()\nself.whitedict = {'ip': [], 'ip6': []}\nself.havenets = {'ip': False, 'ip6': False}\nself.normalise_addr = NormaliseAddress(cf, error_name='Whitelist')\nfor ipstr in whitelist:\n proto = 'ip'\n if ':' in ip... | <|body_start_0|>
self.cf = cf
wf = ListReader(cf, 'whitelist', need_compiled_ix=False)
whitelist = wf.srcdict.keys()
self.whitedict = {'ip': [], 'ip6': []}
self.havenets = {'ip': False, 'ip6': False}
self.normalise_addr = NormaliseAddress(cf, error_name='Whitelist')
... | Check for IPs in whitelist | WhiteListCheck | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WhiteListCheck:
"""Check for IPs in whitelist"""
def __init__(self, cf):
"""Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes"""
<|body_0|>
def is_white(self, proto, ipaddr):
"""Lookup ipaddr in white ... | stack_v2_sparse_classes_36k_train_024728 | 2,713 | permissive | [
{
"docstring": "Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes",
"name": "__init__",
"signature": "def __init__(self, cf)"
},
{
"docstring": "Lookup ipaddr in white list dict Parameters ---------- proto : {'ip', 'ip6'} ipadddr : st... | 2 | stack_v2_sparse_classes_30k_train_011053 | Implement the Python class `WhiteListCheck` described below.
Class description:
Check for IPs in whitelist
Method signatures and docstrings:
- def __init__(self, cf): Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes
- def is_white(self, proto, ipaddr): Lo... | Implement the Python class `WhiteListCheck` described below.
Class description:
Check for IPs in whitelist
Method signatures and docstrings:
- def __init__(self, cf): Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes
- def is_white(self, proto, ipaddr): Lo... | 43e48d46089113e09c3a267c255d3102f3dddac7 | <|skeleton|>
class WhiteListCheck:
"""Check for IPs in whitelist"""
def __init__(self, cf):
"""Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes"""
<|body_0|>
def is_white(self, proto, ipaddr):
"""Lookup ipaddr in white ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WhiteListCheck:
"""Check for IPs in whitelist"""
def __init__(self, cf):
"""Read whitelist contents from whitelist.d Create whitedict - dict indexed by ip|ip6 values are ipaddress classes"""
self.cf = cf
wf = ListReader(cf, 'whitelist', need_compiled_ix=False)
whitelist = ... | the_stack_v2_python_sparse | nftfw/whitelistcheck.py | pcollinson/nftfw | train | 31 |
7cafc0356301b96505e5f57c2cfab529384dbe38 | [
"ans = 0\ntotalLength = 0\nstack = [(-1, 0)]\nfor p in input.split('\\n'):\n currDepth = p.count('\\t')\n currLength = len(p.replace('\\t', ''))\n depth, length = stack[-1]\n while depth >= currDepth:\n totalLength -= length\n stack.pop()\n depth, length = stack[-1]\n if currDept... | <|body_start_0|>
ans = 0
totalLength = 0
stack = [(-1, 0)]
for p in input.split('\n'):
currDepth = p.count('\t')
currLength = len(p.replace('\t', ''))
depth, length = stack[-1]
while depth >= currDepth:
totalLength -= length... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
<|body_0|>
def lengthLongestPath2(self, input):
""":type input: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = 0
totalLength = 0
... | stack_v2_sparse_classes_36k_train_024729 | 6,317 | no_license | [
{
"docstring": ":type input: str :rtype: int",
"name": "lengthLongestPath",
"signature": "def lengthLongestPath(self, input)"
},
{
"docstring": ":type input: str :rtype: int",
"name": "lengthLongestPath2",
"signature": "def lengthLongestPath2(self, input)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthLongestPath(self, input): :type input: str :rtype: int
- def lengthLongestPath2(self, input): :type input: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthLongestPath(self, input): :type input: str :rtype: int
- def lengthLongestPath2(self, input): :type input: str :rtype: int
<|skeleton|>
class Solution:
def length... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
<|body_0|>
def lengthLongestPath2(self, input):
""":type input: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthLongestPath(self, input):
""":type input: str :rtype: int"""
ans = 0
totalLength = 0
stack = [(-1, 0)]
for p in input.split('\n'):
currDepth = p.count('\t')
currLength = len(p.replace('\t', ''))
depth, length = sta... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00388.Longest_Absolute_File_Path.py | roger6blog/LeetCode | train | 0 | |
0505504dbb08a78ebc45dc0936873653dadc00db | [
"aspect = Aspect.query.get(aspect_id)\nif aspect is None:\n return abort(HTTPStatus.NOT_FOUND, message='Aspect is not found')\nif aspect.image_path is None:\n return abort(HTTPStatus.NOT_FOUND, 'Aspect image is not found')\nreturn file_storage.download(file_storage.FileCategory.AspectImage, aspect.image_path)... | <|body_start_0|>
aspect = Aspect.query.get(aspect_id)
if aspect is None:
return abort(HTTPStatus.NOT_FOUND, message='Aspect is not found')
if aspect.image_path is None:
return abort(HTTPStatus.NOT_FOUND, 'Aspect image is not found')
return file_storage.download(fi... | AspectImageResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AspectImageResource:
def get(self, aspect_id):
"""Get aspect image"""
<|body_0|>
def put(self, aspect_id):
"""Replace aspect image * User can set the aspect image **if it does not exists**. This is done to set the image after creating the aspect * User with permissio... | stack_v2_sparse_classes_36k_train_024730 | 2,266 | permissive | [
{
"docstring": "Get aspect image",
"name": "get",
"signature": "def get(self, aspect_id)"
},
{
"docstring": "Replace aspect image * User can set the aspect image **if it does not exists**. This is done to set the image after creating the aspect * User with permission to **\"edit aspects\"** can ... | 2 | stack_v2_sparse_classes_30k_train_013484 | Implement the Python class `AspectImageResource` described below.
Class description:
Implement the AspectImageResource class.
Method signatures and docstrings:
- def get(self, aspect_id): Get aspect image
- def put(self, aspect_id): Replace aspect image * User can set the aspect image **if it does not exists**. This ... | Implement the Python class `AspectImageResource` described below.
Class description:
Implement the AspectImageResource class.
Method signatures and docstrings:
- def get(self, aspect_id): Get aspect image
- def put(self, aspect_id): Replace aspect image * User can set the aspect image **if it does not exists**. This ... | dce87ffe395ae4bd08b47f28e07594e1889da819 | <|skeleton|>
class AspectImageResource:
def get(self, aspect_id):
"""Get aspect image"""
<|body_0|>
def put(self, aspect_id):
"""Replace aspect image * User can set the aspect image **if it does not exists**. This is done to set the image after creating the aspect * User with permissio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AspectImageResource:
def get(self, aspect_id):
"""Get aspect image"""
aspect = Aspect.query.get(aspect_id)
if aspect is None:
return abort(HTTPStatus.NOT_FOUND, message='Aspect is not found')
if aspect.image_path is None:
return abort(HTTPStatus.NOT_FOUN... | the_stack_v2_python_sparse | src/backend/app/api/public/aspects/aspect/aspect_image.py | aimanow/sft | train | 0 | |
bb963d8389eb4eceea6361d54b661170b3997774 | [
"self._seed = seed\nself.server = server\nself.height = height\nself.width = width\nself.density = density\nself.infected_chance = infected_chance\nself.carrier = 0\nself.infected = 0\nself.susceptible = 0\nself.recovered = 0\nself.total = 0\nself.patient_zero = patient_zero\nself.human_kill_zombie_chance = human_k... | <|body_start_0|>
self._seed = seed
self.server = server
self.height = height
self.width = width
self.density = density
self.infected_chance = infected_chance
self.carrier = 0
self.infected = 0
self.susceptible = 0
self.recovered = 0
... | Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework. | Apocalypse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Apocalypse:
"""Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework."""
def __init__(self, height=50, width=50, density=0.1, infected_chance=0.05, map_id=5, city_id=0, province='', human_kill_agent_chance=0.6, patient_zer... | stack_v2_sparse_classes_36k_train_024731 | 4,644 | no_license | [
{
"docstring": "Initializes the apocalypse object, makes the grid and puts agents on that grid. Args: height (int): Grid height. width (int): Grid width. density (float): Percentage of the amount of agents in an area. infected_chance (float): Percentage of agents in an area to be infected. map_id (int): Index t... | 3 | stack_v2_sparse_classes_30k_train_015407 | Implement the Python class `Apocalypse` described below.
Class description:
Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework.
Method signatures and docstrings:
- def __init__(self, height=50, width=50, density=0.1, infected_chance=0.05, map_id... | Implement the Python class `Apocalypse` described below.
Class description:
Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework.
Method signatures and docstrings:
- def __init__(self, height=50, width=50, density=0.1, infected_chance=0.05, map_id... | 59d645537f3644a451243ae83d6a0288ba6e4123 | <|skeleton|>
class Apocalypse:
"""Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework."""
def __init__(self, height=50, width=50, density=0.1, infected_chance=0.05, map_id=5, city_id=0, province='', human_kill_agent_chance=0.6, patient_zer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Apocalypse:
"""Apocalypse model. Model holds all the data and functions for the simulation to work. It is a subclass of the mesa framework."""
def __init__(self, height=50, width=50, density=0.1, infected_chance=0.05, map_id=5, city_id=0, province='', human_kill_agent_chance=0.6, patient_zero=False, door... | the_stack_v2_python_sparse | apocalypse_sim/model.py | PimPaardekooper/zombie_apocalypse | train | 0 |
fc9d79cd611cd91ed01072956b6add2533666f04 | [
"errors: dict = {}\nif user_input is not None:\n region_identifier = user_input[CONF_REGION_IDENTIFIER]\n if not await self.hass.async_add_executor_job(DwdWeatherWarningsAPI, region_identifier):\n errors['base'] = 'invalid_identifier'\n if not errors:\n await self.async_set_unique_id(region_i... | <|body_start_0|>
errors: dict = {}
if user_input is not None:
region_identifier = user_input[CONF_REGION_IDENTIFIER]
if not await self.hass.async_add_executor_job(DwdWeatherWarningsAPI, region_identifier):
errors['base'] = 'invalid_identifier'
if not e... | Handle the config flow for the dwd_weather_warnings integration. | DwdWeatherWarningsConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DwdWeatherWarningsConfigFlow:
"""Handle the config flow for the dwd_weather_warnings integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
<|body_0|>
async def async_step_import(self, import_... | stack_v2_sparse_classes_36k_train_024732 | 2,654 | permissive | [
{
"docstring": "Handle the initial step.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult"
},
{
"docstring": "Import a config entry from configuration.yaml.",
"name": "async_step_import",
"signature": "async ... | 2 | null | Implement the Python class `DwdWeatherWarningsConfigFlow` described below.
Class description:
Handle the config flow for the dwd_weather_warnings integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle the initial step.
- async def... | Implement the Python class `DwdWeatherWarningsConfigFlow` described below.
Class description:
Handle the config flow for the dwd_weather_warnings integration.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Handle the initial step.
- async def... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class DwdWeatherWarningsConfigFlow:
"""Handle the config flow for the dwd_weather_warnings integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
<|body_0|>
async def async_step_import(self, import_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DwdWeatherWarningsConfigFlow:
"""Handle the config flow for the dwd_weather_warnings integration."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Handle the initial step."""
errors: dict = {}
if user_input is not None:
regio... | the_stack_v2_python_sparse | homeassistant/components/dwd_weather_warnings/config_flow.py | home-assistant/core | train | 35,501 |
90884b41eaf5730f0e863cc4192d527fb2a08603 | [
"if re.search('([^a-zA-Z/._\\\\d+])', username) is None:\n return username\nraise serializers.ValidationError('Username can only contain alphanumeric characters and . or _.')",
"if re.search('(^(?=.*[a-z])(?=.*[A-Z])(?=.*\\\\d)(?=.*[@$!%*?&])[A-Za-z\\\\d@$_!%*?&]{8,}$)', password) is not None:\n return pass... | <|body_start_0|>
if re.search('([^a-zA-Z/._\\d+])', username) is None:
return username
raise serializers.ValidationError('Username can only contain alphanumeric characters and . or _.')
<|end_body_0|>
<|body_start_1|>
if re.search('(^(?=.*[a-z])(?=.*[A-Z])(?=.*\\d)(?=.*[@$!%*?&])[A-... | serializes and validates user's data | UserSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSerializer:
"""serializes and validates user's data"""
def validate_username(self, username):
"""Validate username"""
<|body_0|>
def validate_password(self, password):
"""Validate password"""
<|body_1|>
def create(self, validated_data):
"... | stack_v2_sparse_classes_36k_train_024733 | 3,565 | permissive | [
{
"docstring": "Validate username",
"name": "validate_username",
"signature": "def validate_username(self, username)"
},
{
"docstring": "Validate password",
"name": "validate_password",
"signature": "def validate_password(self, password)"
},
{
"docstring": "creates a user",
"... | 3 | stack_v2_sparse_classes_30k_val_001201 | Implement the Python class `UserSerializer` described below.
Class description:
serializes and validates user's data
Method signatures and docstrings:
- def validate_username(self, username): Validate username
- def validate_password(self, password): Validate password
- def create(self, validated_data): creates a use... | Implement the Python class `UserSerializer` described below.
Class description:
serializes and validates user's data
Method signatures and docstrings:
- def validate_username(self, username): Validate username
- def validate_password(self, password): Validate password
- def create(self, validated_data): creates a use... | 009def5bbaf3066df19ce3f48eacd6c8c055acdf | <|skeleton|>
class UserSerializer:
"""serializes and validates user's data"""
def validate_username(self, username):
"""Validate username"""
<|body_0|>
def validate_password(self, password):
"""Validate password"""
<|body_1|>
def create(self, validated_data):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSerializer:
"""serializes and validates user's data"""
def validate_username(self, username):
"""Validate username"""
if re.search('([^a-zA-Z/._\\d+])', username) is None:
return username
raise serializers.ValidationError('Username can only contain alphanumeric cha... | the_stack_v2_python_sparse | apps/account/serializers.py | sasili-adetunji/flightify | train | 0 |
36544a5bae567d5261aa30dde41cb54d018d9d67 | [
"env.switch[1].ui.create_lag(lag=3800, key=0, lag_type='Static', hash_mode='None')\nlag = {'lagId': 3800, 'name': 'lag3800', 'actorAdminLagKey': 0, 'lagControlType': 'Static', 'hashMode': 'None'}\nlag_table = env.switch[1].ui.get_table_lags()\nassert lag in lag_table, 'LAG has not been added'\nenv.switch[1].ui.dele... | <|body_start_0|>
env.switch[1].ui.create_lag(lag=3800, key=0, lag_type='Static', hash_mode='None')
lag = {'lagId': 3800, 'name': 'lag3800', 'actorAdminLagKey': 0, 'lagControlType': 'Static', 'hashMode': 'None'}
lag_table = env.switch[1].ui.get_table_lags()
assert lag in lag_table, 'LAG h... | @description Suite for LAG testing | TestLagSamples | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLagSamples:
"""@description Suite for LAG testing"""
def test_configure_static_lag(self, env):
"""@brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. -# Delete static LAG. -# Verify static LAG has been delet... | stack_v2_sparse_classes_36k_train_024734 | 6,708 | permissive | [
{
"docstring": "@brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. -# Delete static LAG. -# Verify static LAG has been deleted. @endsteps",
"name": "test_configure_static_lag",
"signature": "def test_configure_static_lag(self, env... | 3 | stack_v2_sparse_classes_30k_train_017283 | Implement the Python class `TestLagSamples` described below.
Class description:
@description Suite for LAG testing
Method signatures and docstrings:
- def test_configure_static_lag(self, env): @brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. ... | Implement the Python class `TestLagSamples` described below.
Class description:
@description Suite for LAG testing
Method signatures and docstrings:
- def test_configure_static_lag(self, env): @brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. ... | 18c532fcea7b98cbeadd68e82bdad78ebaaecf4e | <|skeleton|>
class TestLagSamples:
"""@description Suite for LAG testing"""
def test_configure_static_lag(self, env):
"""@brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. -# Delete static LAG. -# Verify static LAG has been delet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLagSamples:
"""@description Suite for LAG testing"""
def test_configure_static_lag(self, env):
"""@brief Verify that static LAG can be created and deleted @steps -# Create static LAG. -# Verify static LAG has been created. -# Delete static LAG. -# Verify static LAG has been deleted. @endsteps... | the_stack_v2_python_sparse | l2/lag/test_lag_samples.py | ravigupta1989/testcases | train | 0 |
9cba50c729d3f384102b9dc431c55bbf36b7cc8f | [
"self.sc = sc\nself._skl2spark_classes = {SKL_LogisticRegression: ClassNames('org.apache.spark.ml.classification.LogisticRegressionModel', LogisticRegressionModel), SKL_LinearRegression: ClassNames('org.apache.spark.ml.regression.LinearRegressionModel', LinearRegressionModel)}\nself._supported_skl_types = self._skl... | <|body_start_0|>
self.sc = sc
self._skl2spark_classes = {SKL_LogisticRegression: ClassNames('org.apache.spark.ml.classification.LogisticRegressionModel', LogisticRegressionModel), SKL_LinearRegression: ClassNames('org.apache.spark.ml.regression.LinearRegressionModel', LinearRegressionModel)}
sel... | Class for converting between scikit-learn and Spark ML models | Converter | [
"Python-2.0",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Converter:
"""Class for converting between scikit-learn and Spark ML models"""
def __init__(self, sc):
""":param sc: SparkContext"""
<|body_0|>
def toSpark(self, model):
"""Convert a scikit-learn model to a Spark ML model from the Pipelines API (spark.ml). Curren... | stack_v2_sparse_classes_36k_train_024735 | 6,928 | permissive | [
{
"docstring": ":param sc: SparkContext",
"name": "__init__",
"signature": "def __init__(self, sc)"
},
{
"docstring": "Convert a scikit-learn model to a Spark ML model from the Pipelines API (spark.ml). Currently supported models: - sklearn.linear_model.LogisticRegression (binary classification ... | 6 | null | Implement the Python class `Converter` described below.
Class description:
Class for converting between scikit-learn and Spark ML models
Method signatures and docstrings:
- def __init__(self, sc): :param sc: SparkContext
- def toSpark(self, model): Convert a scikit-learn model to a Spark ML model from the Pipelines A... | Implement the Python class `Converter` described below.
Class description:
Class for converting between scikit-learn and Spark ML models
Method signatures and docstrings:
- def __init__(self, sc): :param sc: SparkContext
- def toSpark(self, model): Convert a scikit-learn model to a Spark ML model from the Pipelines A... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class Converter:
"""Class for converting between scikit-learn and Spark ML models"""
def __init__(self, sc):
""":param sc: SparkContext"""
<|body_0|>
def toSpark(self, model):
"""Convert a scikit-learn model to a Spark ML model from the Pipelines API (spark.ml). Curren... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Converter:
"""Class for converting between scikit-learn and Spark ML models"""
def __init__(self, sc):
""":param sc: SparkContext"""
self.sc = sc
self._skl2spark_classes = {SKL_LogisticRegression: ClassNames('org.apache.spark.ml.classification.LogisticRegressionModel', LogisticReg... | the_stack_v2_python_sparse | lib/python2.7/site-packages/spark_sklearn/converter.py | wangyum/Anaconda | train | 11 |
2c1ce9b33fc0b7ac96c0e683692982322e64f2ae | [
"q = quantity.Volume(1.0, 'm^3')\nself.assertAlmostEqual(q.value, 1.0, 6)\nself.assertAlmostEqual(q.value_si, 1.0, delta=1e-06)\nself.assertEqual(q.units, 'm^3')",
"q = quantity.Volume(1.0, 'L')\nself.assertAlmostEqual(q.value, 1.0, 6)\nself.assertAlmostEqual(q.value_si, 0.001, delta=1e-09)\nself.assertEqual(q.un... | <|body_start_0|>
q = quantity.Volume(1.0, 'm^3')
self.assertAlmostEqual(q.value, 1.0, 6)
self.assertAlmostEqual(q.value_si, 1.0, delta=1e-06)
self.assertEqual(q.units, 'm^3')
<|end_body_0|>
<|body_start_1|>
q = quantity.Volume(1.0, 'L')
self.assertAlmostEqual(q.value, 1.... | Contains unit tests of the Volume unit type object. | TestVolume | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestVolume:
"""Contains unit tests of the Volume unit type object."""
def test_m3(self):
"""Test the creation of an volume quantity with units of m^3."""
<|body_0|>
def test_L(self):
"""Test the creation of an volume quantity with units of L."""
<|body_1|... | stack_v2_sparse_classes_36k_train_024736 | 33,010 | permissive | [
{
"docstring": "Test the creation of an volume quantity with units of m^3.",
"name": "test_m3",
"signature": "def test_m3(self)"
},
{
"docstring": "Test the creation of an volume quantity with units of L.",
"name": "test_L",
"signature": "def test_L(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004591 | Implement the Python class `TestVolume` described below.
Class description:
Contains unit tests of the Volume unit type object.
Method signatures and docstrings:
- def test_m3(self): Test the creation of an volume quantity with units of m^3.
- def test_L(self): Test the creation of an volume quantity with units of L. | Implement the Python class `TestVolume` described below.
Class description:
Contains unit tests of the Volume unit type object.
Method signatures and docstrings:
- def test_m3(self): Test the creation of an volume quantity with units of m^3.
- def test_L(self): Test the creation of an volume quantity with units of L.... | 0937b2e0a955dcf21b79674a4e89f43941c0dd85 | <|skeleton|>
class TestVolume:
"""Contains unit tests of the Volume unit type object."""
def test_m3(self):
"""Test the creation of an volume quantity with units of m^3."""
<|body_0|>
def test_L(self):
"""Test the creation of an volume quantity with units of L."""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestVolume:
"""Contains unit tests of the Volume unit type object."""
def test_m3(self):
"""Test the creation of an volume quantity with units of m^3."""
q = quantity.Volume(1.0, 'm^3')
self.assertAlmostEqual(q.value, 1.0, 6)
self.assertAlmostEqual(q.value_si, 1.0, delta=1... | the_stack_v2_python_sparse | rmgpy/quantityTest.py | vrlambert/RMG-Py | train | 1 |
2ed8f673cb00541414cc276099fbf36196ddae00 | [
"self._feature_columns = tuple(feature_columns or [])\nassert self._feature_columns\nchief_hook = None\nif isinstance(optimizer, sdca_optimizer.SDCAOptimizer) and enable_centered_bias:\n enable_centered_bias = False\n logging.warning('centered_bias is not supported with SDCA, please disable it explicitly.')\n... | <|body_start_0|>
self._feature_columns = tuple(feature_columns or [])
assert self._feature_columns
chief_hook = None
if isinstance(optimizer, sdca_optimizer.SDCAOptimizer) and enable_centered_bias:
enable_centered_bias = False
logging.warning('centered_bias is not... | Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(...) sparse_feature_a_x_sparse_feature_b = crossed_column(...) estimator = LinearR... | LinearRegressor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinearRegressor:
"""Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(...) sparse_feature_a_x_sparse_feature_... | stack_v2_sparse_classes_36k_train_024737 | 38,403 | permissive | [
{
"docstring": "Construct a `LinearRegressor` estimator object. Args: feature_columns: An iterable containing all the feature columns used by the model. All items in the set should be instances of classes derived from `FeatureColumn`. model_dir: Directory to save model parameters, graph, etc. This can also be u... | 4 | null | Implement the Python class `LinearRegressor` described below.
Class description:
Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(... | Implement the Python class `LinearRegressor` described below.
Class description:
Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class LinearRegressor:
"""Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(...) sparse_feature_a_x_sparse_feature_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinearRegressor:
"""Linear regressor model. Train a linear regression model to predict label value given observation of feature values. Example: ```python sparse_column_a = sparse_column_with_hash_bucket(...) sparse_column_b = sparse_column_with_hash_bucket(...) sparse_feature_a_x_sparse_feature_b = crossed_c... | the_stack_v2_python_sparse | Tensorflow_OpenCV_Nightly/source/tensorflow/contrib/learn/python/learn/estimators/linear.py | ryfeus/lambda-packs | train | 1,283 |
700c185d9f867c5bf7db8c45c4dc913a7ab04271 | [
"assert isinstance(cone, ConvexConeInPositiveQuadrant), 'incorrect cone type'\nconstraints = []\nname = name or str(id(cone))\nleft_extreme_ray = cone.left_extreme_ray()\nx_coeff = math.tan(math.radians(left_extreme_ray.angle_in_degrees())) if left_extreme_ray.angle_in_degrees() < 90 else 1.0\ny_coeff = 1 if left_e... | <|body_start_0|>
assert isinstance(cone, ConvexConeInPositiveQuadrant), 'incorrect cone type'
constraints = []
name = name or str(id(cone))
left_extreme_ray = cone.left_extreme_ray()
x_coeff = math.tan(math.radians(left_extreme_ray.angle_in_degrees())) if left_extreme_ray.angle_i... | Implements constraint generator utility | ConstraintGenerationUtilities | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConstraintGenerationUtilities:
"""Implements constraint generator utility"""
def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None):
"""Creates and adds the constraints to the model for the given cone, returns the constraints"""
<|bo... | stack_v2_sparse_classes_36k_train_024738 | 41,178 | permissive | [
{
"docstring": "Creates and adds the constraints to the model for the given cone, returns the constraints",
"name": "create_constraints_for_cone_in_positive_quadrant",
"signature": "def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None)"
},
{
"docstring... | 4 | stack_v2_sparse_classes_30k_train_015393 | Implement the Python class `ConstraintGenerationUtilities` described below.
Class description:
Implements constraint generator utility
Method signatures and docstrings:
- def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None): Creates and adds the constraints to the model fo... | Implement the Python class `ConstraintGenerationUtilities` described below.
Class description:
Implements constraint generator utility
Method signatures and docstrings:
- def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None): Creates and adds the constraints to the model fo... | 465ea7aaa62157411f9f181b994f4d7e6b8a2e33 | <|skeleton|>
class ConstraintGenerationUtilities:
"""Implements constraint generator utility"""
def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None):
"""Creates and adds the constraints to the model for the given cone, returns the constraints"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConstraintGenerationUtilities:
"""Implements constraint generator utility"""
def create_constraints_for_cone_in_positive_quadrant(momilp_model, cone, x_var, y_var, name=None):
"""Creates and adds the constraints to the model for the given cone, returns the constraints"""
assert isinstance... | the_stack_v2_python_sparse | src/momilp/utilities.py | gokhanceyhan/momilp | train | 2 |
e9f4277fd38de1862c6a642f24e2111ba1afefc2 | [
"self.InitAttr(node, bool, c4d.PYLOOKATCAMERA_PITCH)\nnode[c4d.PYLOOKATCAMERA_PITCH] = True\npd = c4d.PriorityData()\nif pd is None:\n raise MemoryError('Failed to create a priority data.')\npd.SetPriorityValue(c4d.PRIORITYVALUE_CAMERADEPENDENT, True)\nnode[c4d.EXPRESSION_PRIORITY] = pd\nreturn True",
"bd = do... | <|body_start_0|>
self.InitAttr(node, bool, c4d.PYLOOKATCAMERA_PITCH)
node[c4d.PYLOOKATCAMERA_PITCH] = True
pd = c4d.PriorityData()
if pd is None:
raise MemoryError('Failed to create a priority data.')
pd.SetPriorityValue(c4d.PRIORITYVALUE_CAMERADEPENDENT, True)
... | Look at Camera | LookAtCamera | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LookAtCamera:
"""Look at Camera"""
def Init(self, node):
"""Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, otherwise False."""
<|body_0|>
def Execute(self,... | stack_v2_sparse_classes_36k_train_024739 | 3,361 | permissive | [
{
"docstring": "Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, otherwise False.",
"name": "Init",
"signature": "def Init(self, node)"
},
{
"docstring": "Called by Cinema 4D at each... | 2 | null | Implement the Python class `LookAtCamera` described below.
Class description:
Look at Camera
Method signatures and docstrings:
- def Init(self, node): Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, othe... | Implement the Python class `LookAtCamera` described below.
Class description:
Look at Camera
Method signatures and docstrings:
- def Init(self, node): Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, othe... | b1ea3fce533df34094bc3d0bd6460dfb84306e53 | <|skeleton|>
class LookAtCamera:
"""Look at Camera"""
def Init(self, node):
"""Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, otherwise False."""
<|body_0|>
def Execute(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LookAtCamera:
"""Look at Camera"""
def Init(self, node):
"""Called when Cinema 4D Initialize the TagData (used to define, default values). Args: node (c4d.GeListNode): The instance of the TagData. Returns: True on success, otherwise False."""
self.InitAttr(node, bool, c4d.PYLOOKATCAMERA_P... | the_stack_v2_python_sparse | plugins/py-look_at_camera_r13/py-look_at_camera_r13.pyp | PluginCafe/cinema4d_py_sdk_extended | train | 112 |
1852adbb56a7c08dc4a4e555c62da35036eddb7c | [
"self.wind = wind\nself.water = water\nsuper(Langmuir, self).__init__(**kwargs)\nself.array_types.update({'fay_area': gat('fay_area'), 'area': gat('area'), 'bulk_init_volume': gat('bulk_init_volume'), 'age': gat('age'), 'positions': gat('positions'), 'spill_num': gat('spill_num'), 'frac_coverage': gat('frac_coverag... | <|body_start_0|>
self.wind = wind
self.water = water
super(Langmuir, self).__init__(**kwargs)
self.array_types.update({'fay_area': gat('fay_area'), 'area': gat('area'), 'bulk_init_volume': gat('bulk_init_volume'), 'age': gat('age'), 'positions': gat('positions'), 'spill_num': gat('spill_... | Easiest to define this as a weathering process that updates 'area' array | Langmuir | [
"LicenseRef-scancode-public-domain",
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Langmuir:
"""Easiest to define this as a weathering process that updates 'area' array"""
def __init__(self, water=None, wind=None, **kwargs):
"""initialize wind to (0, 0) if it is None"""
<|body_0|>
def _get_frac_coverage(self, points, model_time, rel_buoy, thickness):
... | stack_v2_sparse_classes_36k_train_024740 | 38,088 | permissive | [
{
"docstring": "initialize wind to (0, 0) if it is None",
"name": "__init__",
"signature": "def __init__(self, water=None, wind=None, **kwargs)"
},
{
"docstring": "return fractional coverage for a blob of oil with inputs; relative_buoyancy, and thickness Assumes the thickness is the minimum oil ... | 4 | stack_v2_sparse_classes_30k_train_004905 | Implement the Python class `Langmuir` described below.
Class description:
Easiest to define this as a weathering process that updates 'area' array
Method signatures and docstrings:
- def __init__(self, water=None, wind=None, **kwargs): initialize wind to (0, 0) if it is None
- def _get_frac_coverage(self, points, mod... | Implement the Python class `Langmuir` described below.
Class description:
Easiest to define this as a weathering process that updates 'area' array
Method signatures and docstrings:
- def __init__(self, water=None, wind=None, **kwargs): initialize wind to (0, 0) if it is None
- def _get_frac_coverage(self, points, mod... | 97bb561fb8c953c4ee766a3f9d84a41aef93fb28 | <|skeleton|>
class Langmuir:
"""Easiest to define this as a weathering process that updates 'area' array"""
def __init__(self, water=None, wind=None, **kwargs):
"""initialize wind to (0, 0) if it is None"""
<|body_0|>
def _get_frac_coverage(self, points, model_time, rel_buoy, thickness):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Langmuir:
"""Easiest to define this as a weathering process that updates 'area' array"""
def __init__(self, water=None, wind=None, **kwargs):
"""initialize wind to (0, 0) if it is None"""
self.wind = wind
self.water = water
super(Langmuir, self).__init__(**kwargs)
... | the_stack_v2_python_sparse | py_gnome/gnome/weatherers/spreading.py | NOAA-ORR-ERD/PyGnome | train | 45 |
5bdcace672df14724c42ef88461bdc91041be62e | [
"self.lexicon = lexicon\nL_inv = self.lexicon.L_inv.to(device)\nif L_inv.properties & k2.fsa_properties.ARC_SORTED != 0:\n L_inv = k2.arc_sort(L_inv)\nassert L_inv.requires_grad is False\nassert oov in self.lexicon.words\nself.L_inv = L_inv\nself.oov_id = self.lexicon.words[oov]\nself.oov = oov\nself.device = de... | <|body_start_0|>
self.lexicon = lexicon
L_inv = self.lexicon.L_inv.to(device)
if L_inv.properties & k2.fsa_properties.ARC_SORTED != 0:
L_inv = k2.arc_sort(L_inv)
assert L_inv.requires_grad is False
assert oov in self.lexicon.words
self.L_inv = L_inv
se... | MmiTrainingGraphCompiler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MmiTrainingGraphCompiler:
def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>'):
"""Args: L_inv: Its labels are words, while its aux_labels are phones. phones: The phone symbol table. words: The word symbol table. oov: Out of vocabulary word."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_024741 | 6,137 | permissive | [
{
"docstring": "Args: L_inv: Its labels are words, while its aux_labels are phones. phones: The phone symbol table. words: The word symbol table. oov: Out of vocabulary word.",
"name": "__init__",
"signature": "def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>')"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_013647 | Implement the Python class `MmiTrainingGraphCompiler` described below.
Class description:
Implement the MmiTrainingGraphCompiler class.
Method signatures and docstrings:
- def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>'): Args: L_inv: Its labels are words, while its aux_labels are phones. ... | Implement the Python class `MmiTrainingGraphCompiler` described below.
Class description:
Implement the MmiTrainingGraphCompiler class.
Method signatures and docstrings:
- def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>'): Args: L_inv: Its labels are words, while its aux_labels are phones. ... | 2dda31e14039a79b77c89bcd3bb96d52cbf60c8a | <|skeleton|>
class MmiTrainingGraphCompiler:
def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>'):
"""Args: L_inv: Its labels are words, while its aux_labels are phones. phones: The phone symbol table. words: The word symbol table. oov: Out of vocabulary word."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MmiTrainingGraphCompiler:
def __init__(self, lexicon: Lexicon, device: torch.device, oov: str='<UNK>'):
"""Args: L_inv: Its labels are words, while its aux_labels are phones. phones: The phone symbol table. words: The word symbol table. oov: Out of vocabulary word."""
self.lexicon = lexicon
... | the_stack_v2_python_sparse | snowfall/training/mmi_graph.py | csukuangfj/snowfall | train | 0 | |
61013f5d18ffd68ac791127bbbc4978d735ced4a | [
"ins_col = 0\nfor point in self.points:\n time.sleep(2)\n ins_col = ins_col + 1\n self.cut(point)\n trans_img = img_to_str(self.cut_img_name)\n row_content, col_content = trans_img.basicAccurate()\n excel_obj = excel_class(row_content, col_content, ins_col, self.start_row, excel_name=self.excel_na... | <|body_start_0|>
ins_col = 0
for point in self.points:
time.sleep(2)
ins_col = ins_col + 1
self.cut(point)
trans_img = img_to_str(self.cut_img_name)
row_content, col_content = trans_img.basicAccurate()
excel_obj = excel_class(row_co... | handler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class handler:
def pre_cut(self):
"""根据point来将图片截取为多张图片，并识别生成excel"""
<|body_0|>
def handler_img(self):
"""读取文件夹里面的图片，并交给pre_cut()处理"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ins_col = 0
for point in self.points:
time.sleep(2)
... | stack_v2_sparse_classes_36k_train_024742 | 8,802 | no_license | [
{
"docstring": "根据point来将图片截取为多张图片，并识别生成excel",
"name": "pre_cut",
"signature": "def pre_cut(self)"
},
{
"docstring": "读取文件夹里面的图片，并交给pre_cut()处理",
"name": "handler_img",
"signature": "def handler_img(self)"
}
] | 2 | null | Implement the Python class `handler` described below.
Class description:
Implement the handler class.
Method signatures and docstrings:
- def pre_cut(self): 根据point来将图片截取为多张图片，并识别生成excel
- def handler_img(self): 读取文件夹里面的图片，并交给pre_cut()处理 | Implement the Python class `handler` described below.
Class description:
Implement the handler class.
Method signatures and docstrings:
- def pre_cut(self): 根据point来将图片截取为多张图片，并识别生成excel
- def handler_img(self): 读取文件夹里面的图片，并交给pre_cut()处理
<|skeleton|>
class handler:
def pre_cut(self):
"""根据point来将图片截取为多张... | 3c02098163611eaa4a21994cded89912794b9338 | <|skeleton|>
class handler:
def pre_cut(self):
"""根据point来将图片截取为多张图片，并识别生成excel"""
<|body_0|>
def handler_img(self):
"""读取文件夹里面的图片，并交给pre_cut()处理"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class handler:
def pre_cut(self):
"""根据point来将图片截取为多张图片，并识别生成excel"""
ins_col = 0
for point in self.points:
time.sleep(2)
ins_col = ins_col + 1
self.cut(point)
trans_img = img_to_str(self.cut_img_name)
row_content, col_content = tra... | the_stack_v2_python_sparse | other/ocr.py | sunjiebin/s12 | train | 0 | |
eae781e58493abcefc29f5b15efb3bc5bd34b850 | [
"super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())\nself.__start = True\nself.__configure()",
"self.__mic = Microphone()\nself._button.configure(foreground=self.FOREGROUND)\nself._button.configure(background=self.START_COLOR)",
"if self.__start:\n self._button['text'] = self.... | <|body_start_0|>
super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())
self.__start = True
self.__configure()
<|end_body_0|>
<|body_start_1|>
self.__mic = Microphone()
self._button.configure(foreground=self.FOREGROUND)
self._button.configure(... | Class for selecting sound file. | MicButton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
<|body_0|>
def __configure(self):
"""Initialize the look/location of the Button."""
<|body_1|>
def __toggleMic(self):
"""Toggle the microphone ... | stack_v2_sparse_classes_36k_train_024743 | 1,853 | no_license | [
{
"docstring": "Construct object.",
"name": "__init__",
"signature": "def __init__(self, form)"
},
{
"docstring": "Initialize the look/location of the Button.",
"name": "__configure",
"signature": "def __configure(self)"
},
{
"docstring": "Toggle the microphone button to start/st... | 3 | stack_v2_sparse_classes_30k_train_000408 | Implement the Python class `MicButton` described below.
Class description:
Class for selecting sound file.
Method signatures and docstrings:
- def __init__(self, form): Construct object.
- def __configure(self): Initialize the look/location of the Button.
- def __toggleMic(self): Toggle the microphone button to start... | Implement the Python class `MicButton` described below.
Class description:
Class for selecting sound file.
Method signatures and docstrings:
- def __init__(self, form): Construct object.
- def __configure(self): Initialize the look/location of the Button.
- def __toggleMic(self): Toggle the microphone button to start... | 6d29e1e0b2335c90452a832373dcf3058cec33e9 | <|skeleton|>
class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
<|body_0|>
def __configure(self):
"""Initialize the look/location of the Button."""
<|body_1|>
def __toggleMic(self):
"""Toggle the microphone ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MicButton:
"""Class for selecting sound file."""
def __init__(self, form):
"""Construct object."""
super().__init__(form=form, bTxt=self.START_TEXT, bCmd=lambda: self.__toggleMic())
self.__start = True
self.__configure()
def __configure(self):
"""Initialize th... | the_stack_v2_python_sparse | emotionAnalyzer/gui/micButton.py | vkepuska/LivePitchTracking | train | 0 |
231b9c86fcad9a224466518886a8356e98813ff4 | [
"for arg in self.non_number_values:\n self.assertRaises(TypeError, prev1.proper_dividers_list, arg)\nfor arg, val in self.proper_dividers_values:\n self.assertEqual(prev1.proper_dividers_list(arg), val)",
"for arg in self.non_number_values:\n self.assertRaises(TypeError, prev1.proper_dividers_fun, arg)\n... | <|body_start_0|>
for arg in self.non_number_values:
self.assertRaises(TypeError, prev1.proper_dividers_list, arg)
for arg, val in self.proper_dividers_values:
self.assertEqual(prev1.proper_dividers_list(arg), val)
<|end_body_0|>
<|body_start_1|>
for arg in self.non_numbe... | TestProperDividers | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestProperDividers:
def test_proper_dividers_list(self):
"""Testing proper_dividers_list function"""
<|body_0|>
def test_proper_dividers_fun(self):
"""Testing proper_dividers_fun function"""
<|body_1|>
def test_proper_dividers_map(self):
"""Testi... | stack_v2_sparse_classes_36k_train_024744 | 8,451 | no_license | [
{
"docstring": "Testing proper_dividers_list function",
"name": "test_proper_dividers_list",
"signature": "def test_proper_dividers_list(self)"
},
{
"docstring": "Testing proper_dividers_fun function",
"name": "test_proper_dividers_fun",
"signature": "def test_proper_dividers_fun(self)"
... | 4 | stack_v2_sparse_classes_30k_train_002525 | Implement the Python class `TestProperDividers` described below.
Class description:
Implement the TestProperDividers class.
Method signatures and docstrings:
- def test_proper_dividers_list(self): Testing proper_dividers_list function
- def test_proper_dividers_fun(self): Testing proper_dividers_fun function
- def te... | Implement the Python class `TestProperDividers` described below.
Class description:
Implement the TestProperDividers class.
Method signatures and docstrings:
- def test_proper_dividers_list(self): Testing proper_dividers_list function
- def test_proper_dividers_fun(self): Testing proper_dividers_fun function
- def te... | 0cd4bbe3feb63b248d643303433f9fb2fc2def79 | <|skeleton|>
class TestProperDividers:
def test_proper_dividers_list(self):
"""Testing proper_dividers_list function"""
<|body_0|>
def test_proper_dividers_fun(self):
"""Testing proper_dividers_fun function"""
<|body_1|>
def test_proper_dividers_map(self):
"""Testi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestProperDividers:
def test_proper_dividers_list(self):
"""Testing proper_dividers_list function"""
for arg in self.non_number_values:
self.assertRaises(TypeError, prev1.proper_dividers_list, arg)
for arg, val in self.proper_dividers_values:
self.assertEqual(pr... | the_stack_v2_python_sparse | Python - advanced course/Solutions/9/9.1.py | maxymilianz/CS-at-University-of-Wroclaw | train | 0 | |
ad44f625d79e3d60f639d5cbd137c2b7fed42049 | [
"int_n = int(n)\nfor k in range(2, int_n):\n tmp = 0\n i = 0\n while tmp < int_n:\n tmp += k ** i\n i += 1\n if tmp == int_n:\n return str(k)",
"n = int(n)\n\ndef check(k, len):\n tmp = 0\n for i in range(len):\n tmp += k ** i\n return tmp\nfor N in range(len(bin(n... | <|body_start_0|>
int_n = int(n)
for k in range(2, int_n):
tmp = 0
i = 0
while tmp < int_n:
tmp += k ** i
i += 1
if tmp == int_n:
return str(k)
<|end_body_0|>
<|body_start_1|>
n = int(n)
def ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestGoodBase(self, n: str) -> str:
"""k^0+k^1+k^2... n > k >= 2 input = "1000000000000000000" 超时 :param n: :return:"""
<|body_0|>
def smallestGoodBase(self, n: str) -> str:
"""二分查找 bin()求出n的二进制(-2减去符号), 其他进制都小于二进制的长度 if tmp > n: r = mid - 1 if tmp <... | stack_v2_sparse_classes_36k_train_024745 | 2,087 | no_license | [
{
"docstring": "k^0+k^1+k^2... n > k >= 2 input = \"1000000000000000000\" 超时 :param n: :return:",
"name": "smallestGoodBase",
"signature": "def smallestGoodBase(self, n: str) -> str"
},
{
"docstring": "二分查找 bin()求出n的二进制(-2减去符号), 其他进制都小于二进制的长度 if tmp > n: r = mid - 1 if tmp < n: l = mid + 1 [l,r]... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestGoodBase(self, n: str) -> str: k^0+k^1+k^2... n > k >= 2 input = "1000000000000000000" 超时 :param n: :return:
- def smallestGoodBase(self, n: str) -> str: 二分查找 bin()求出... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestGoodBase(self, n: str) -> str: k^0+k^1+k^2... n > k >= 2 input = "1000000000000000000" 超时 :param n: :return:
- def smallestGoodBase(self, n: str) -> str: 二分查找 bin()求出... | b1680014ce3f55ba952a1e64241c0cbb783cc436 | <|skeleton|>
class Solution:
def smallestGoodBase(self, n: str) -> str:
"""k^0+k^1+k^2... n > k >= 2 input = "1000000000000000000" 超时 :param n: :return:"""
<|body_0|>
def smallestGoodBase(self, n: str) -> str:
"""二分查找 bin()求出n的二进制(-2减去符号), 其他进制都小于二进制的长度 if tmp > n: r = mid - 1 if tmp <... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def smallestGoodBase(self, n: str) -> str:
"""k^0+k^1+k^2... n > k >= 2 input = "1000000000000000000" 超时 :param n: :return:"""
int_n = int(n)
for k in range(2, int_n):
tmp = 0
i = 0
while tmp < int_n:
tmp += k ** i
... | the_stack_v2_python_sparse | a_483.py | sun510001/leetcode_jianzhi_offer_2 | train | 0 | |
5adf9955f31264db3543ee2bfb31382d184bbb69 | [
"try:\n ilp.solve(pulp.GLPK())\n assert round(pulp.value(ilp.objective), 0) == 5\nexcept pulp.solvers.PulpSolverError:\n pytest.fail(f'Solver not installed')",
"try:\n ilp.solve(pulp.COIN())\n assert round(pulp.value(ilp.objective), 0) == 5\nexcept pulp.solvers.PulpSolverError:\n pytest.fail(f'S... | <|body_start_0|>
try:
ilp.solve(pulp.GLPK())
assert round(pulp.value(ilp.objective), 0) == 5
except pulp.solvers.PulpSolverError:
pytest.fail(f'Solver not installed')
<|end_body_0|>
<|body_start_1|>
try:
ilp.solve(pulp.COIN())
assert r... | Test Installed Solvers. | TestSolver | [
"LicenseRef-scancode-proprietary-license",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSolver:
"""Test Installed Solvers."""
def test_glpk(self, ilp):
"""Test method for GLPK."""
<|body_0|>
def test_cbc(self, ilp):
"""Test method for CBC."""
<|body_1|>
def test_cplex(self, ilp):
"""Test method for CPLEX."""
<|body_2... | stack_v2_sparse_classes_36k_train_024746 | 1,770 | permissive | [
{
"docstring": "Test method for GLPK.",
"name": "test_glpk",
"signature": "def test_glpk(self, ilp)"
},
{
"docstring": "Test method for CBC.",
"name": "test_cbc",
"signature": "def test_cbc(self, ilp)"
},
{
"docstring": "Test method for CPLEX.",
"name": "test_cplex",
"sig... | 5 | stack_v2_sparse_classes_30k_train_002588 | Implement the Python class `TestSolver` described below.
Class description:
Test Installed Solvers.
Method signatures and docstrings:
- def test_glpk(self, ilp): Test method for GLPK.
- def test_cbc(self, ilp): Test method for CBC.
- def test_cplex(self, ilp): Test method for CPLEX.
- def test_gurobi(self, ilp): Test... | Implement the Python class `TestSolver` described below.
Class description:
Test Installed Solvers.
Method signatures and docstrings:
- def test_glpk(self, ilp): Test method for GLPK.
- def test_cbc(self, ilp): Test method for CBC.
- def test_cplex(self, ilp): Test method for CPLEX.
- def test_gurobi(self, ilp): Test... | 12f696633743825b34556180eed171649a26f05d | <|skeleton|>
class TestSolver:
"""Test Installed Solvers."""
def test_glpk(self, ilp):
"""Test method for GLPK."""
<|body_0|>
def test_cbc(self, ilp):
"""Test method for CBC."""
<|body_1|>
def test_cplex(self, ilp):
"""Test method for CPLEX."""
<|body_2... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSolver:
"""Test Installed Solvers."""
def test_glpk(self, ilp):
"""Test method for GLPK."""
try:
ilp.solve(pulp.GLPK())
assert round(pulp.value(ilp.objective), 0) == 5
except pulp.solvers.PulpSolverError:
pytest.fail(f'Solver not installed')... | the_stack_v2_python_sparse | check_installed_solvers.py | atomassi/mapping_distrinet | train | 2 |
6deea93b94d6b74e2c53f73415426eff47e37a84 | [
"hash1 = generate_password_hash('default')\nhash2 = generate_password_hash(u'default', method='sha1')\nassert hash1 != hash2\nassert check_password_hash(hash1, 'default')\nassert check_password_hash(hash2, 'default')\nassert hash1.startswith('sha1$')\nassert hash2.startswith('sha1$')\nfakehash = generate_password_h... | <|body_start_0|>
hash1 = generate_password_hash('default')
hash2 = generate_password_hash(u'default', method='sha1')
assert hash1 != hash2
assert check_password_hash(hash1, 'default')
assert check_password_hash(hash2, 'default')
assert hash1.startswith('sha1$')
as... | SecurityTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SecurityTestCase:
def test_password_hashing(self):
"""Test the password hashing and password hash checking"""
<|body_0|>
def test_safe_join(self):
"""Test the safe joining helper"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
hash1 = generate_passw... | stack_v2_sparse_classes_36k_train_024747 | 1,838 | permissive | [
{
"docstring": "Test the password hashing and password hash checking",
"name": "test_password_hashing",
"signature": "def test_password_hashing(self)"
},
{
"docstring": "Test the safe joining helper",
"name": "test_safe_join",
"signature": "def test_safe_join(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004629 | Implement the Python class `SecurityTestCase` described below.
Class description:
Implement the SecurityTestCase class.
Method signatures and docstrings:
- def test_password_hashing(self): Test the password hashing and password hash checking
- def test_safe_join(self): Test the safe joining helper | Implement the Python class `SecurityTestCase` described below.
Class description:
Implement the SecurityTestCase class.
Method signatures and docstrings:
- def test_password_hashing(self): Test the password hashing and password hash checking
- def test_safe_join(self): Test the safe joining helper
<|skeleton|>
class... | 6641120dfac24800a25214daaf594b5d534fc9bd | <|skeleton|>
class SecurityTestCase:
def test_password_hashing(self):
"""Test the password hashing and password hash checking"""
<|body_0|>
def test_safe_join(self):
"""Test the safe joining helper"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SecurityTestCase:
def test_password_hashing(self):
"""Test the password hashing and password hash checking"""
hash1 = generate_password_hash('default')
hash2 = generate_password_hash(u'default', method='sha1')
assert hash1 != hash2
assert check_password_hash(hash1, 'def... | the_stack_v2_python_sparse | gcm_flask/werkzeug/testsuite/security.py | BCB-PWA-Team/Barcamp-Bangalore-Android-App | train | 0 | |
5b08bd32f6843c2a5eb398330af3ad1ff11a44e9 | [
"super(PreprocessorSelfSupervised, self).__init__(root_dir=root_dir, patch_size=patch_size, pad_type=pad_type, look_for_labels=look_for_labels, crop=crop, spacing=spacing)\nself.transforms = [{'name': 'Mirroring', 'execution_probability': 0.5}]\nself.type = 'self-supervised'",
"image, _ = super(PreprocessorSelfSu... | <|body_start_0|>
super(PreprocessorSelfSupervised, self).__init__(root_dir=root_dir, patch_size=patch_size, pad_type=pad_type, look_for_labels=look_for_labels, crop=crop, spacing=spacing)
self.transforms = [{'name': 'Mirroring', 'execution_probability': 0.5}]
self.type = 'self-supervised'
<|end_... | PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data. | PreprocessorSelfSupervised | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreprocessorSelfSupervised:
"""PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data."""
def __init__(self, root_dir='../raw', patch_size=(64, 64, 32), crop=2, pad_type='zero_pad', look_for_labels=False, spacing=(0.8, 0.8, 0.8... | stack_v2_sparse_classes_36k_train_024748 | 19,145 | no_license | [
{
"docstring": "PreprocessorSelfSupervised constructor, extending the Preprocessor constructor by defining augumentations and level of supervision. Args: root_dir (string): path to folder containing raw data. Defaults to '../raw'. patch_size (tuple of ints): patch size for padding and croping calculation. Defau... | 2 | stack_v2_sparse_classes_30k_train_011968 | Implement the Python class `PreprocessorSelfSupervised` described below.
Class description:
PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data.
Method signatures and docstrings:
- def __init__(self, root_dir='../raw', patch_size=(64, 64, 32), crop=2... | Implement the Python class `PreprocessorSelfSupervised` described below.
Class description:
PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data.
Method signatures and docstrings:
- def __init__(self, root_dir='../raw', patch_size=(64, 64, 32), crop=2... | d89f696a1404f5793b71ca46261055a7f4575497 | <|skeleton|>
class PreprocessorSelfSupervised:
"""PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data."""
def __init__(self, root_dir='../raw', patch_size=(64, 64, 32), crop=2, pad_type='zero_pad', look_for_labels=False, spacing=(0.8, 0.8, 0.8... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PreprocessorSelfSupervised:
"""PreprocessorSelfSupervised class. Extends the original class by not processing the labels and saving the processed data."""
def __init__(self, root_dir='../raw', patch_size=(64, 64, 32), crop=2, pad_type='zero_pad', look_for_labels=False, spacing=(0.8, 0.8, 0.8), **kwargs):... | the_stack_v2_python_sparse | source/dataset/preprocessor.py | BereznyMatej/IBT | train | 0 |
e249a07fb698ae1884ce89db87ee0c0445f581cd | [
"Email = self.cleaned_data.get('Email')\ndominio = Email.split('@')[-1].split('.')\nif dominio[0] in ['gmail', 'hotmail', 'outlook', 'yahoo', 'live'] and dominio[1] in ['com', 'mx', 'live']:\n return Email\nelse:\n raise forms.ValidationError(\"¡Ingresa un correo electrónico valido, ya sea de 'google', 'hotma... | <|body_start_0|>
Email = self.cleaned_data.get('Email')
dominio = Email.split('@')[-1].split('.')
if dominio[0] in ['gmail', 'hotmail', 'outlook', 'yahoo', 'live'] and dominio[1] in ['com', 'mx', 'live']:
return Email
else:
raise forms.ValidationError("¡Ingresa un... | ReservacionForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReservacionForm:
def clean_Email(self):
"""Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo por cliente sin importar el número de reservaciones que esté realice."""
<|body_0|>
def clean... | stack_v2_sparse_classes_36k_train_024749 | 4,491 | no_license | [
{
"docstring": "Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo por cliente sin importar el número de reservaciones que esté realice.",
"name": "clean_Email",
"signature": "def clean_Email(self)"
},
{
"doc... | 2 | stack_v2_sparse_classes_30k_train_004813 | Implement the Python class `ReservacionForm` described below.
Class description:
Implement the ReservacionForm class.
Method signatures and docstrings:
- def clean_Email(self): Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo po... | Implement the Python class `ReservacionForm` described below.
Class description:
Implement the ReservacionForm class.
Method signatures and docstrings:
- def clean_Email(self): Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo po... | d5041229d2ddd223a818020efa2ea4efb4339429 | <|skeleton|>
class ReservacionForm:
def clean_Email(self):
"""Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo por cliente sin importar el número de reservaciones que esté realice."""
<|body_0|>
def clean... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReservacionForm:
def clean_Email(self):
"""Si el Email brindado ya existe en la base de datos, regresamos None para evitar la multiplicidad del mismo correo. Teniendo así, un correo por cliente sin importar el número de reservaciones que esté realice."""
Email = self.cleaned_data.get('Email')
... | the_stack_v2_python_sparse | sitioweb_sasor/reservacion/forms.py | DanielRosasPerez/SitioWeb_Restaurante | train | 0 | |
a072e9bd8e46081428855d315bb777f223028f5f | [
"work_on = self.clean_urls(provider.get('url', []))\nfor url in work_on:\n if self.supports_url(url):\n return True\nreturn False",
"for bu in self.base_urls:\n if self.clean_url(url).startswith(bu):\n return True\nreturn False",
"lic_statements = [{'under the Creative Commons Attribution 3.... | <|body_start_0|>
work_on = self.clean_urls(provider.get('url', []))
for url in work_on:
if self.supports_url(url):
return True
return False
<|end_body_0|>
<|body_start_1|>
for bu in self.base_urls:
if self.clean_url(url).startswith(bu):
... | COPERNICUSPlugin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class COPERNICUSPlugin:
def supports(self, provider):
"""Does this plugin support this provider"""
<|body_0|>
def supports_url(self, url):
"""Same as the supports() function but answers the question for a single URL."""
<|body_1|>
def license_detect(self, reco... | stack_v2_sparse_classes_36k_train_024750 | 2,267 | permissive | [
{
"docstring": "Does this plugin support this provider",
"name": "supports",
"signature": "def supports(self, provider)"
},
{
"docstring": "Same as the supports() function but answers the question for a single URL.",
"name": "supports_url",
"signature": "def supports_url(self, url)"
},... | 3 | stack_v2_sparse_classes_30k_train_000989 | Implement the Python class `COPERNICUSPlugin` described below.
Class description:
Implement the COPERNICUSPlugin class.
Method signatures and docstrings:
- def supports(self, provider): Does this plugin support this provider
- def supports_url(self, url): Same as the supports() function but answers the question for a... | Implement the Python class `COPERNICUSPlugin` described below.
Class description:
Implement the COPERNICUSPlugin class.
Method signatures and docstrings:
- def supports(self, provider): Does this plugin support this provider
- def supports_url(self, url): Same as the supports() function but answers the question for a... | 280ba5dcbc508ec01093b8bc2a76aee5a9793723 | <|skeleton|>
class COPERNICUSPlugin:
def supports(self, provider):
"""Does this plugin support this provider"""
<|body_0|>
def supports_url(self, url):
"""Same as the supports() function but answers the question for a single URL."""
<|body_1|>
def license_detect(self, reco... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class COPERNICUSPlugin:
def supports(self, provider):
"""Does this plugin support this provider"""
work_on = self.clean_urls(provider.get('url', []))
for url in work_on:
if self.supports_url(url):
return True
return False
def supports_url(self, url):
... | the_stack_v2_python_sparse | openarticlegauge/plugins/copernicus.py | cameronneylon/OpenArticleGauge | train | 0 | |
4d6e6102e133611e90b6ea6322d6b12d7d0dd91b | [
"if type(N) is not int:\n raise TypeError('N must be int representing number of blocks in the encoder')\nif type(dm) is not int:\n raise TypeError('dm must be int representing dimensionality of model')\nif type(h) is not int:\n raise TypeError('h must be int representing number of heads')\nif type(hidden) ... | <|body_start_0|>
if type(N) is not int:
raise TypeError('N must be int representing number of blocks in the encoder')
if type(dm) is not int:
raise TypeError('dm must be int representing dimensionality of model')
if type(h) is not int:
raise TypeError('h must ... | Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decoder layer linear: the Dense layer with target_vocab units public instance metho... | Transformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decoder layer linear: the Dense layer with t... | stack_v2_sparse_classes_36k_train_024751 | 4,876 | no_license | [
{
"docstring": "Class constructor parameters: N [int]: represents the number of blocks in the encoder and decoder dm [int]: represents the dimensionality of the model h [int]: represents the number of heads hidden [int]: represents the number of hidden units in fully connected layer input_vocab [int]: represent... | 2 | null | Implement the Python class `Transformer` described below.
Class description:
Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decod... | Implement the Python class `Transformer` described below.
Class description:
Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decod... | 8834b201ca84937365e4dcc0fac978656cdf5293 | <|skeleton|>
class Transformer:
"""Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decoder layer linear: the Dense layer with t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transformer:
"""Class to create the transformer network class constructor: def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1) public instance attributes: encoder: the encoder layer decoder: the decoder layer linear: the Dense layer with target_vocab u... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/11-transformer.py | ejonakodra/holbertonschool-machine_learning-1 | train | 0 |
a55dc6594227a004dd2dff0d2226e071150cc0fe | [
"data = csv.reader(open(path), delimiter='\\t', quoting=csv.QUOTE_NONE)\nrows = []\nfor x, row in enumerate(data):\n score = float(row[4]) / 5.0\n rows.append((x + 1, score, row[5], row[6]))\nreturn rows",
"print('Building model')\nembeddings = Embeddings({'path': Models.vectorPath(vector), 'scoring': score... | <|body_start_0|>
data = csv.reader(open(path), delimiter='\t', quoting=csv.QUOTE_NONE)
rows = []
for x, row in enumerate(data):
score = float(row[4]) / 5.0
rows.append((x + 1, score, row[5], row[6]))
return rows
<|end_body_0|>
<|body_start_1|>
print('Buil... | STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark | STS | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class STS:
"""STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark"""
def read(path):
"""Reads a STS data file. Args: path: full path to file Returns: rows"""
<|body_0|>
def train(vector, score):
"""Trains an Embeddings mod... | stack_v2_sparse_classes_36k_train_024752 | 6,859 | permissive | [
{
"docstring": "Reads a STS data file. Args: path: full path to file Returns: rows",
"name": "read",
"signature": "def read(path)"
},
{
"docstring": "Trains an Embeddings model on STS dev + train data. Args: vector: word vector model path score: scoring method (bm25, sif, tfidf or None for avera... | 4 | stack_v2_sparse_classes_30k_train_019461 | Implement the Python class `STS` described below.
Class description:
STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark
Method signatures and docstrings:
- def read(path): Reads a STS data file. Args: path: full path to file Returns: rows
- def train(vector, score): Tra... | Implement the Python class `STS` described below.
Class description:
STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark
Method signatures and docstrings:
- def read(path): Reads a STS data file. Args: path: full path to file Returns: rows
- def train(vector, score): Tra... | c1fde2fcb3cf830247131385ec5340e6a148e70a | <|skeleton|>
class STS:
"""STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark"""
def read(path):
"""Reads a STS data file. Args: path: full path to file Returns: rows"""
<|body_0|>
def train(vector, score):
"""Trains an Embeddings mod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class STS:
"""STS Benchmark Dataset General text similarity http://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark"""
def read(path):
"""Reads a STS data file. Args: path: full path to file Returns: rows"""
data = csv.reader(open(path), delimiter='\t', quoting=csv.QUOTE_NONE)
rows = []
... | the_stack_v2_python_sparse | src/python/codequestion/evaluate.py | spreck/codequestion | train | 0 |
12f9b4d30774393712a613afe07d1ec9ebf67e1c | [
"super(RedactingPIIFilter, self).__init__()\nself.scrubber = self._get_scrubber()\nself._patterns = patterns",
"scrubber = scrubadub.Scrubber()\nscrubber.remove_detector('email')\nscrubber.remove_detector('name')\nscrubber.remove_detector('phone')\nscrubber.add_detector(TINDetector)\nreturn scrubber",
"record.m... | <|body_start_0|>
super(RedactingPIIFilter, self).__init__()
self.scrubber = self._get_scrubber()
self._patterns = patterns
<|end_body_0|>
<|body_start_1|>
scrubber = scrubadub.Scrubber()
scrubber.remove_detector('email')
scrubber.remove_detector('name')
scrubber.... | Redacting filter to remove PII information. | RedactingPIIFilter | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RedactingPIIFilter:
"""Redacting filter to remove PII information."""
def __init__(self, patterns=[]):
"""Initialize PII filter. New patterns can be given as input."""
<|body_0|>
def _get_scrubber():
"""Initialize a scrubber with phone, skype, ssn, tin and url de... | stack_v2_sparse_classes_36k_train_024753 | 1,926 | permissive | [
{
"docstring": "Initialize PII filter. New patterns can be given as input.",
"name": "__init__",
"signature": "def __init__(self, patterns=[])"
},
{
"docstring": "Initialize a scrubber with phone, skype, ssn, tin and url detector.",
"name": "_get_scrubber",
"signature": "def _get_scrubbe... | 4 | stack_v2_sparse_classes_30k_train_015624 | Implement the Python class `RedactingPIIFilter` described below.
Class description:
Redacting filter to remove PII information.
Method signatures and docstrings:
- def __init__(self, patterns=[]): Initialize PII filter. New patterns can be given as input.
- def _get_scrubber(): Initialize a scrubber with phone, skype... | Implement the Python class `RedactingPIIFilter` described below.
Class description:
Redacting filter to remove PII information.
Method signatures and docstrings:
- def __init__(self, patterns=[]): Initialize PII filter. New patterns can be given as input.
- def _get_scrubber(): Initialize a scrubber with phone, skype... | 1e2da9494faf9e316a17cbe899284db9e61d0902 | <|skeleton|>
class RedactingPIIFilter:
"""Redacting filter to remove PII information."""
def __init__(self, patterns=[]):
"""Initialize PII filter. New patterns can be given as input."""
<|body_0|>
def _get_scrubber():
"""Initialize a scrubber with phone, skype, ssn, tin and url de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RedactingPIIFilter:
"""Redacting filter to remove PII information."""
def __init__(self, patterns=[]):
"""Initialize PII filter. New patterns can be given as input."""
super(RedactingPIIFilter, self).__init__()
self.scrubber = self._get_scrubber()
self._patterns = patterns... | the_stack_v2_python_sparse | claims_to_quality/lib/qpp_logging/pii_scrubber.py | gaybro8777/qpp-claims-to-quality-public | train | 0 |
e382713dbf6209d3d754f3a0e1e13855f155fb67 | [
"request = data_set.get('request')\nuser = data_set.get('user')\nif user:\n username = cls.analyze(user, uuid)\n driver = cls.analyze_class.get_user(username)\n CompatAPPDriver.driver = driver\nelse:\n user = data_set.get('session')\n driver = cls.session_class.get_session(user)\nfor step in request:... | <|body_start_0|>
request = data_set.get('request')
user = data_set.get('user')
if user:
username = cls.analyze(user, uuid)
driver = cls.analyze_class.get_user(username)
CompatAPPDriver.driver = driver
else:
user = data_set.get('session')
... | APPDriver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": ... | stack_v2_sparse_classes_36k_train_024754 | 6,213 | permissive | [
{
"docstring": "Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { \"path\": \"/login\", \"user\": \"user1\", \"version\": 2, \"request\": [ {\"eventName\": \"元素点击\", \"event\": \"click\", \"locations\": [\"css selector\", \"#kw\"], \"input\": \"输入内容\"}, {\"eventName\": \"元素名称\", \"event\": \"click\", \"lo... | 2 | stack_v2_sparse_classes_30k_train_002417 | Implement the Python class `APPDriver` described below.
Class description:
Implement the APPDriver class.
Method signatures and docstrings:
- def run(cls, data_set, uuid, host, **kwargs): Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName"... | Implement the Python class `APPDriver` described below.
Class description:
Implement the APPDriver class.
Method signatures and docstrings:
- def run(cls, data_set, uuid, host, **kwargs): Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName"... | 5ecae8652c9f71aaa78cc0fd181d431cb130cab1 | <|skeleton|>
class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class APPDriver:
def run(cls, data_set, uuid, host, **kwargs):
"""Webdriver驱动执行浏览器元素定位与元素动作操作 :param data_set: 测试用例节点信息 { "path": "/login", "user": "user1", "version": 2, "request": [ {"eventName": "元素点击", "event": "click", "locations": ["css selector", "#kw"], "input": "输入内容"}, {"eventName": "元素名称", "event... | the_stack_v2_python_sparse | giantstar/drivers/appDriver.py | DaoSen-v/giantstar | train | 0 | |
709b7a281bac1f3d1f7541e5bddaa9a7e7cf4786 | [
"super(VeryDeepNieFineCoattention, self).__init__()\nself.n_lt_layers = 2\nwith self.init_scope():\n self.energy_layer = links.Bilinear(hidden_dim, hidden_dim, 1)\n self.attention_layer_1 = GraphLinear(head, 1, nobias=True)\n self.attention_layer_2 = GraphLinear(head, 1, nobias=True)\n self.prev_lt_laye... | <|body_start_0|>
super(VeryDeepNieFineCoattention, self).__init__()
self.n_lt_layers = 2
with self.init_scope():
self.energy_layer = links.Bilinear(hidden_dim, hidden_dim, 1)
self.attention_layer_1 = GraphLinear(head, 1, nobias=True)
self.attention_layer_2 = G... | TODO | VeryDeepNieFineCoattention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VeryDeepNieFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
... | stack_v2_sparse_classes_36k_train_024755 | 25,561 | permissive | [
{
"docstring": ":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism",
"name": "__init__",
"signature": "def __init__(self, hidden_dim, out_dim, head, activation=functions.identity)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_019058 | Implement the Python class `VeryDeepNieFineCoattention` described below.
Class description:
TODO
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, activation=functions.identity): :param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :... | Implement the Python class `VeryDeepNieFineCoattention` described below.
Class description:
TODO
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, activation=functions.identity): :param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :... | 21b64a3c8cc9bc33718ae09c65aa917e575132eb | <|skeleton|>
class VeryDeepNieFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VeryDeepNieFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
super(Ve... | the_stack_v2_python_sparse | models/coattention/nie_coattention.py | Minys233/GCN-BMP | train | 1 |
b81c9bc57bb9ec7b07cf341d71c0afce53294774 | [
"self.args, self.setup = (args, setup)\nself.batch_size = batch_size\nself.augmentations = augmentations\nself.mixing_method = mixing_method\nwith open(args.file.name, 'rb') as handle:\n data_package = pickle.load(handle)\nif 'xtrain' in data_package.keys():\n self.trainset, self.validset, self.poisonset, sel... | <|body_start_0|>
self.args, self.setup = (args, setup)
self.batch_size = batch_size
self.augmentations = augmentations
self.mixing_method = mixing_method
with open(args.file.name, 'rb') as handle:
data_package = pickle.load(handle)
if 'xtrain' in data_package.... | Generate a dataset definition completely from file | KettleExternal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KettleExternal:
"""Generate a dataset definition completely from file"""
def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.float)):
"""Initialize with given specs..."""
<|body_0|... | stack_v2_sparse_classes_36k_train_024756 | 5,772 | no_license | [
{
"docstring": "Initialize with given specs...",
"name": "__init__",
"signature": "def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.float))"
},
{
"docstring": "Load a metapoison package. xtrain: CI... | 2 | stack_v2_sparse_classes_30k_val_000027 | Implement the Python class `KettleExternal` described below.
Class description:
Generate a dataset definition completely from file
Method signatures and docstrings:
- def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.flo... | Implement the Python class `KettleExternal` described below.
Class description:
Generate a dataset definition completely from file
Method signatures and docstrings:
- def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.flo... | cedfa1dab4c7bbd0a2fe350664b4c0a885583c08 | <|skeleton|>
class KettleExternal:
"""Generate a dataset definition completely from file"""
def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.float)):
"""Initialize with given specs..."""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KettleExternal:
"""Generate a dataset definition completely from file"""
def __init__(self, args, batch_size, augmentations, mixing_method=dict(type=None, strength=0.0), setup=dict(device=torch.device('cpu'), dtype=torch.float)):
"""Initialize with given specs..."""
self.args, self.setup ... | the_stack_v2_python_sparse | forest/data/kettle_external.py | hsouri/Sleeper-Agent | train | 51 |
240095c0488be53dfe26b4c0c5b361b176b79cf8 | [
"self.login()\nclient = Clients.objects.first()\nng = NotificationGroups.objects.first()\nresponse = self.client.get(reverse('linkednotifcationgroups'), {'client_id': client.id}, format='json')\nexpected = NotificationGroups.objects.filter(contacts__client_id=client.id)\nserializer = DropDownSerializer(expected, ma... | <|body_start_0|>
self.login()
client = Clients.objects.first()
ng = NotificationGroups.objects.first()
response = self.client.get(reverse('linkednotifcationgroups'), {'client_id': client.id}, format='json')
expected = NotificationGroups.objects.filter(contacts__client_id=client.i... | GetSamplesTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetSamplesTest:
def test_get_linked_notify_groups(self):
"""This test ensures that notification groups attached to the client id are returned"""
<|body_0|>
def test_get_all_samples(self):
"""This test ensures that all samples added in the setUp method exist when loop... | stack_v2_sparse_classes_36k_train_024757 | 19,832 | no_license | [
{
"docstring": "This test ensures that notification groups attached to the client id are returned",
"name": "test_get_linked_notify_groups",
"signature": "def test_get_linked_notify_groups(self)"
},
{
"docstring": "This test ensures that all samples added in the setUp method exist when loop thro... | 3 | stack_v2_sparse_classes_30k_train_003473 | Implement the Python class `GetSamplesTest` described below.
Class description:
Implement the GetSamplesTest class.
Method signatures and docstrings:
- def test_get_linked_notify_groups(self): This test ensures that notification groups attached to the client id are returned
- def test_get_all_samples(self): This test... | Implement the Python class `GetSamplesTest` described below.
Class description:
Implement the GetSamplesTest class.
Method signatures and docstrings:
- def test_get_linked_notify_groups(self): This test ensures that notification groups attached to the client id are returned
- def test_get_all_samples(self): This test... | 1c6e2cf3b0d347e68d4b105e4d2b12824a2ae0fb | <|skeleton|>
class GetSamplesTest:
def test_get_linked_notify_groups(self):
"""This test ensures that notification groups attached to the client id are returned"""
<|body_0|>
def test_get_all_samples(self):
"""This test ensures that all samples added in the setUp method exist when loop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetSamplesTest:
def test_get_linked_notify_groups(self):
"""This test ensures that notification groups attached to the client id are returned"""
self.login()
client = Clients.objects.first()
ng = NotificationGroups.objects.first()
response = self.client.get(reverse('lin... | the_stack_v2_python_sparse | eldashboard/tests.py | ahmedsaatci/lims | train | 0 | |
1cfce9e0c5e5f69a1e1a659548de04ba80ba7bcd | [
"super().__init__()\nself.data = data\nself.noise_map = noise_map",
"xvalues = np.arange(self.data.shape[0])\nmodel_data = instance.model_data_1d_via_xvalues_from(xvalues=xvalues)\nresidual_map = self.data - model_data\nchi_squared_map = (residual_map / self.noise_map) ** 2.0\nchi_squared = sum(chi_squared_map)\n... | <|body_start_0|>
super().__init__()
self.data = data
self.noise_map = noise_map
<|end_body_0|>
<|body_start_1|>
xvalues = np.arange(self.data.shape[0])
model_data = instance.model_data_1d_via_xvalues_from(xvalues=xvalues)
residual_map = self.data - model_data
chi... | Analysis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Analysis:
def __init__(self, data: np.ndarray, noise_map: np.ndarray):
"""Standard Analysis class example used throughout PyAutoFit examples."""
<|body_0|>
def log_likelihood_function(self, instance) -> float:
"""Standard log likelihood function used throughout PyAut... | stack_v2_sparse_classes_36k_train_024758 | 20,890 | no_license | [
{
"docstring": "Standard Analysis class example used throughout PyAutoFit examples.",
"name": "__init__",
"signature": "def __init__(self, data: np.ndarray, noise_map: np.ndarray)"
},
{
"docstring": "Standard log likelihood function used throughout PyAutoFit examples.",
"name": "log_likeliho... | 4 | stack_v2_sparse_classes_30k_test_000089 | Implement the Python class `Analysis` described below.
Class description:
Implement the Analysis class.
Method signatures and docstrings:
- def __init__(self, data: np.ndarray, noise_map: np.ndarray): Standard Analysis class example used throughout PyAutoFit examples.
- def log_likelihood_function(self, instance) -> ... | Implement the Python class `Analysis` described below.
Class description:
Implement the Analysis class.
Method signatures and docstrings:
- def __init__(self, data: np.ndarray, noise_map: np.ndarray): Standard Analysis class example used throughout PyAutoFit examples.
- def log_likelihood_function(self, instance) -> ... | ac76dfef4643189a130ce18d23070bb81272a93c | <|skeleton|>
class Analysis:
def __init__(self, data: np.ndarray, noise_map: np.ndarray):
"""Standard Analysis class example used throughout PyAutoFit examples."""
<|body_0|>
def log_likelihood_function(self, instance) -> float:
"""Standard log likelihood function used throughout PyAut... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Analysis:
def __init__(self, data: np.ndarray, noise_map: np.ndarray):
"""Standard Analysis class example used throughout PyAutoFit examples."""
super().__init__()
self.data = data
self.noise_map = noise_map
def log_likelihood_function(self, instance) -> float:
"""... | the_stack_v2_python_sparse | scripts/cookbooks/database.py | Jammy2211/autofit_workspace | train | 6 | |
60171a16cd96548f1768ae642e4e5494d52933c3 | [
"ret = 0\nif len(A) < 3:\n return ret\nstart, end = (0, 1)\nwhile end < len(A):\n if A[end] <= A[start]:\n start = end\n end += 1\n else:\n peak = end + 1\n while peak < len(A) and A[peak] > A[peak - 1]:\n peak += 1\n peak -= 1\n end = peak + 1\n ... | <|body_start_0|>
ret = 0
if len(A) < 3:
return ret
start, end = (0, 1)
while end < len(A):
if A[end] <= A[start]:
start = end
end += 1
else:
peak = end + 1
while peak < len(A) and A[peak] ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def longestMountain2(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = 0
if len(A) < 3:
retur... | stack_v2_sparse_classes_36k_train_024759 | 2,431 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "longestMountain",
"signature": "def longestMountain(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "longestMountain2",
"signature": "def longestMountain2(self, A)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001772 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestMountain(self, A): :type A: List[int] :rtype: int
- def longestMountain2(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestMountain(self, A): :type A: List[int] :rtype: int
- def longestMountain2(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
def longestMountai... | 9190d3d178f1733aa226973757ee7e045b7bab00 | <|skeleton|>
class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def longestMountain2(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestMountain(self, A):
""":type A: List[int] :rtype: int"""
ret = 0
if len(A) < 3:
return ret
start, end = (0, 1)
while end < len(A):
if A[end] <= A[start]:
start = end
end += 1
else:
... | the_stack_v2_python_sparse | LongestMountainInArray.py | ellinx/LC-python | train | 1 | |
e26a9c412592d46c702218a52e8c251518d952a0 | [
"def dfs(x):\n if x == n:\n res.append(self.removeFirstZero(''.join(num)))\n return\n else:\n for i in range(10):\n num[x] = str(i)\n dfs(x + 1)\nres = []\nnum = ['0'] * n\ndfs(0)\nreturn res",
"if int(num_str) == 0:\n return '0'\ni = 0\ndone = False\nwhile i < ... | <|body_start_0|>
def dfs(x):
if x == n:
res.append(self.removeFirstZero(''.join(num)))
return
else:
for i in range(10):
num[x] = str(i)
dfs(x + 1)
res = []
num = ['0'] * n
dfs(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def printNumbers(self, n: int) -> [int]:
"""打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的问题都可以使用这个代码来写 :param n: :return:"""
<|body_0|>
def removeFirstZero(self, num_str):
... | stack_v2_sparse_classes_36k_train_024760 | 1,653 | no_license | [
{
"docstring": "打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的问题都可以使用这个代码来写 :param n: :return:",
"name": "printNumbers",
"signature": "def printNumbers(self, n: int) -> [int]"
},
{
"docstring": "移除数字字符串前面的... | 2 | stack_v2_sparse_classes_30k_train_012179 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def printNumbers(self, n: int) -> [int]: 打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def printNumbers(self, n: int) -> [int]: 打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的... | 97cc61fefe0bedf5161687aab92fb09b0df990e2 | <|skeleton|>
class Solution:
def printNumbers(self, n: int) -> [int]:
"""打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的问题都可以使用这个代码来写 :param n: :return:"""
<|body_0|>
def removeFirstZero(self, num_str):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def printNumbers(self, n: int) -> [int]:
"""打印 “从 1至最大的 n 位数的列表” 常规思路就是用list(range(1, n))直接打印 但是当n比较大时，它会超出int32整型的取值范围，超出取值范围的字无法正常存储。因此需要考虑大数越界问题。 注意：我们可以观察到该列表是一个n位0-9的全排列，该列全排列的问题都可以使用这个代码来写 :param n: :return:"""
def dfs(x):
if x == n:
res.append(self.... | the_stack_v2_python_sparse | code/other/print_number.py | JiaXingBinggan/For_work | train | 0 | |
c2b2a257f8e6c2ffdd120273ec3a76700f60cdcc | [
"self.assertRaises(ValueError, json_lib.AssertIsInstance, tuple(), list, 'a bad value')\nself.assertRaises(ValueError, json_lib.AssertIsInstance, 1, float, 'a bad value')\nself.assertRaises(ValueError, json_lib.AssertIsInstance, 1, bool, 'a bad value')\njson_lib.AssertIsInstance([1], list, 'good value')\njson_lib.A... | <|body_start_0|>
self.assertRaises(ValueError, json_lib.AssertIsInstance, tuple(), list, 'a bad value')
self.assertRaises(ValueError, json_lib.AssertIsInstance, 1, float, 'a bad value')
self.assertRaises(ValueError, json_lib.AssertIsInstance, 1, bool, 'a bad value')
json_lib.AssertIsInst... | Tests for chromite.lib.json_lib. | JsonHelpersTest | [
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JsonHelpersTest:
"""Tests for chromite.lib.json_lib."""
def testAssertIsInstance(self):
"""Test that AssertIsInstance is correct."""
<|body_0|>
def testGetValueOfType(self):
"""Test that GetValueOfType is correct."""
<|body_1|>
def testPopValueOfType... | stack_v2_sparse_classes_36k_train_024761 | 2,477 | permissive | [
{
"docstring": "Test that AssertIsInstance is correct.",
"name": "testAssertIsInstance",
"signature": "def testAssertIsInstance(self)"
},
{
"docstring": "Test that GetValueOfType is correct.",
"name": "testGetValueOfType",
"signature": "def testGetValueOfType(self)"
},
{
"docstri... | 4 | null | Implement the Python class `JsonHelpersTest` described below.
Class description:
Tests for chromite.lib.json_lib.
Method signatures and docstrings:
- def testAssertIsInstance(self): Test that AssertIsInstance is correct.
- def testGetValueOfType(self): Test that GetValueOfType is correct.
- def testPopValueOfType(sel... | Implement the Python class `JsonHelpersTest` described below.
Class description:
Tests for chromite.lib.json_lib.
Method signatures and docstrings:
- def testAssertIsInstance(self): Test that AssertIsInstance is correct.
- def testGetValueOfType(self): Test that GetValueOfType is correct.
- def testPopValueOfType(sel... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class JsonHelpersTest:
"""Tests for chromite.lib.json_lib."""
def testAssertIsInstance(self):
"""Test that AssertIsInstance is correct."""
<|body_0|>
def testGetValueOfType(self):
"""Test that GetValueOfType is correct."""
<|body_1|>
def testPopValueOfType... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JsonHelpersTest:
"""Tests for chromite.lib.json_lib."""
def testAssertIsInstance(self):
"""Test that AssertIsInstance is correct."""
self.assertRaises(ValueError, json_lib.AssertIsInstance, tuple(), list, 'a bad value')
self.assertRaises(ValueError, json_lib.AssertIsInstance, 1, f... | the_stack_v2_python_sparse | third_party/chromite/lib/json_lib_unittest.py | metux/chromium-suckless | train | 5 |
3be6d75737ef3f383f1f94b37a1e59fa01d47fa7 | [
"if n <= 0:\n return\ndp = [0 for i in range(n + 1)]\ndp[0] = 1\ndp[1] = 1\nfor i in range(2, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\nreturn dp[n]",
"if n <= 2:\n return n\ndp = [1, 1]\nfor i in range(n - 2):\n dp.append(dp[-1] + dp[-2])\nreturn dp[-1]",
"if n <= 0:\n return\ndp = [0 for i in ra... | <|body_start_0|>
if n <= 0:
return
dp = [0 for i in range(n + 1)]
dp[0] = 1
dp[1] = 1
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
<|end_body_0|>
<|body_start_1|>
if n <= 2:
return n
dp = [1, 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_024762 | 1,248 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "climbS... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int
- def climbStairs(self, n): :type n: int :rtype: int
<|skeleton|>
class S... | e718fcb6b83664d3d6413cf9b2bb4a875e62de9c | <|skeleton|>
class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def climbStairs(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n):
""":type n: int :rtype: int"""
if n <= 0:
return
dp = [0 for i in range(n + 1)]
dp[0] = 1
dp[1] = 1
for i in range(2, n + 1):
dp[i] = dp[i - 1] + dp[i - 2]
return dp[n]
def climbStairs(self... | the_stack_v2_python_sparse | climbStair.py | bch6179/Pyn | train | 1 | |
f18fc0fbfc739ef67c3daa42b6e9a54af8169401 | [
"self._facility = facility\nself._option = option\nself._priority = priority",
"title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT)\nsyslog.openlog(title, self._option, self._facility)\nsyslog.syslog(self._priority, message)\nsyslog.closelog()"
] | <|body_start_0|>
self._facility = facility
self._option = option
self._priority = priority
<|end_body_0|>
<|body_start_1|>
title = kwargs.get(ATTR_TITLE, ATTR_TITLE_DEFAULT)
syslog.openlog(title, self._option, self._facility)
syslog.syslog(self._priority, message)
... | Implement the syslog notification service. | SyslogNotificationService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyslogNotificationService:
"""Implement the syslog notification service."""
def __init__(self, facility, option, priority):
"""Initialize the service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to syslog."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_024763 | 2,640 | permissive | [
{
"docstring": "Initialize the service.",
"name": "__init__",
"signature": "def __init__(self, facility, option, priority)"
},
{
"docstring": "Send a message to syslog.",
"name": "send_message",
"signature": "def send_message(self, message='', **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000863 | Implement the Python class `SyslogNotificationService` described below.
Class description:
Implement the syslog notification service.
Method signatures and docstrings:
- def __init__(self, facility, option, priority): Initialize the service.
- def send_message(self, message='', **kwargs): Send a message to syslog. | Implement the Python class `SyslogNotificationService` described below.
Class description:
Implement the syslog notification service.
Method signatures and docstrings:
- def __init__(self, facility, option, priority): Initialize the service.
- def send_message(self, message='', **kwargs): Send a message to syslog.
<... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SyslogNotificationService:
"""Implement the syslog notification service."""
def __init__(self, facility, option, priority):
"""Initialize the service."""
<|body_0|>
def send_message(self, message='', **kwargs):
"""Send a message to syslog."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyslogNotificationService:
"""Implement the syslog notification service."""
def __init__(self, facility, option, priority):
"""Initialize the service."""
self._facility = facility
self._option = option
self._priority = priority
def send_message(self, message='', **kwa... | the_stack_v2_python_sparse | homeassistant/components/syslog/notify.py | home-assistant/core | train | 35,501 |
dcad37a8101e1054ceb0404e5dcec42041a1f2a3 | [
"BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)\nself.veh_id = veh_id\nself.k_1 = k_1\nself.k_2 = k_2\nself.h = h\nself.tau = tau\nself.a = a",
"lead_id = env.k.vehicle.get_leader(self.veh_id)\nlead_vel = env.k.vehicle.get_speed(lead_id)\nthis_vel =... | <|body_start_0|>
BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)
self.veh_id = veh_id
self.k_1 = k_1
self.k_2 = k_2
self.h = h
self.tau = tau
self.a = a
<|end_body_0|>
<|body_start_1|>
lead_i... | Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float design parameter (default: 0.9) h : float desired time gap (default: 1.0) tau : fl... | LACController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LACController:
"""Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float design parameter (default: 0.9) h : float... | stack_v2_sparse_classes_36k_train_024764 | 17,548 | permissive | [
{
"docstring": "Instantiate a Linear Adaptive Cruise controller.",
"name": "__init__",
"signature": "def __init__(self, veh_id, car_following_params, k_1=0.3, k_2=0.4, h=1, tau=0.1, a=0, time_delay=0.0, noise=0, fail_safe=None)"
},
{
"docstring": "See parent class.",
"name": "get_accel",
... | 2 | stack_v2_sparse_classes_30k_test_001127 | Implement the Python class `LACController` described below.
Class description:
Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float de... | Implement the Python class `LACController` described below.
Class description:
Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float de... | badac3da17f04d8d8ae5691ee8ba2af9d56fac35 | <|skeleton|>
class LACController:
"""Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float design parameter (default: 0.9) h : float... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LACController:
"""Linear Adaptive Cruise Control. Attributes ---------- veh_id : str Vehicle ID for SUMO identification car_following_params : flow.core.params.SumoCarFollowingParams see parent class k_1 : float design parameter (default: 0.8) k_2 : float design parameter (default: 0.9) h : float desired time... | the_stack_v2_python_sparse | flow/controllers/car_following_models.py | parthjaggi/flow | train | 6 |
c65980d356c8ef391f94747bf265eba2c0d6a81c | [
"Action.__init__(self, game_state, player)\nassert isinstance(is_right_goal, bool)\nassert isinstance(minimum_distance, (int, float))\nassert isinstance(maximum_distance, (int, float)) or maximum_distance is None\nif maximum_distance is not None:\n assert maximum_distance >= minimum_distance\nif maximum_distance... | <|body_start_0|>
Action.__init__(self, game_state, player)
assert isinstance(is_right_goal, bool)
assert isinstance(minimum_distance, (int, float))
assert isinstance(maximum_distance, (int, float)) or maximum_distance is None
if maximum_distance is not None:
assert ma... | Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendre. Attributs (en plus de ceux de Action): player_id : L'identifiant du gardien... | ProtectGoal | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectGoal:
"""Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendre. Attributs (en plus de ceux de Action... | stack_v2_sparse_classes_36k_train_024765 | 4,322 | permissive | [
{
"docstring": ":param game_state: L'état courant du jeu. :param player: L'instance du joueur qui est le gardien de but. :param is_right_goal: Un booléen indiquant si le but à protéger est celui de droite. :param minimum_distance: La distance minimale qu'il doit y avoir entre le gardien et le centre du but. :pa... | 2 | stack_v2_sparse_classes_30k_train_012368 | Implement the Python class `ProtectGoal` described below.
Class description:
Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendr... | Implement the Python class `ProtectGoal` described below.
Class description:
Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendr... | ea997cad26e9eaec75e32f7490e2819151937d93 | <|skeleton|>
class ProtectGoal:
"""Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendre. Attributs (en plus de ceux de Action... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectGoal:
"""Action ProtectGoal: Action de base pour le gardien de but. Déplace le gardien entre la balle et le centre du but, à une certaine distance de celui-ci, tout en restant dans la zone du gardien. Méthodes: exec(self): Retourne la pose où se rendre. Attributs (en plus de ceux de Action): player_id ... | the_stack_v2_python_sparse | ai/STA/Action/ProtectGoal.py | EtienneLavallee/StrategyAI | train | 0 |
4412086452ba95c15086a7747db1b13c767c4cc8 | [
"result = ['']\ncounts = []\ni = 0\nwhile i < len(s):\n if s[i] in ascii_letters:\n result[-1] += s[i]\n elif s[i] in digits:\n j = s[i:].find('[')\n counts.append(int(s[i:i + j]))\n result.append('')\n i += j\n elif s[i] == ']':\n count = counts.pop()\n sub... | <|body_start_0|>
result = ['']
counts = []
i = 0
while i < len(s):
if s[i] in ascii_letters:
result[-1] += s[i]
elif s[i] in digits:
j = s[i:].find('[')
counts.append(int(s[i:i + j]))
result.append(''... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def decodeString(self, s: str) -> str:
"""20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 1. 每当遇到括号需要进行操作时, 都向栈中压入一个空串, 2. 在操作完成之后, 将处理后的字符串 pop 出来, 拼接到栈顶的字符串中 3. 重复 1, 2 步, 最终栈中只有一个元素, 即... | stack_v2_sparse_classes_36k_train_024766 | 2,765 | no_license | [
{
"docstring": "20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 1. 每当遇到括号需要进行操作时, 都向栈中压入一个空串, 2. 在操作完成之后, 将处理后的字符串 pop 出来, 拼接到栈顶的字符串中 3. 重复 1, 2 步, 最终栈中只有一个元素, 即处理完的字符串",
"name": "decodeString",
"signature": "def ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString(self, s: str) -> str: 20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def decodeString(self, s: str) -> str: 20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 ... | 99a3abf1774933af73a8405f9b59e5e64906bca4 | <|skeleton|>
class Solution:
def decodeString(self, s: str) -> str:
"""20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 1. 每当遇到括号需要进行操作时, 都向栈中压入一个空串, 2. 在操作完成之后, 将处理后的字符串 pop 出来, 拼接到栈顶的字符串中 3. 重复 1, 2 步, 最终栈中只有一个元素, 即... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def decodeString(self, s: str) -> str:
"""20190928 执行用时 :32 ms, 在所有 Python3 提交中击败了99.61% 的用户 内存消耗 :13.6 MB, 在所有 Python3 提交中击败了5.26%的用户 思路借鉴了第 154 场周赛, 一位小哥的解法. 维护了一个栈, 最终结果保存在栈底元素中 1. 每当遇到括号需要进行操作时, 都向栈中压入一个空串, 2. 在操作完成之后, 将处理后的字符串 pop 出来, 拼接到栈顶的字符串中 3. 重复 1, 2 步, 最终栈中只有一个元素, 即处理完的字符串"""
... | the_stack_v2_python_sparse | leetcode/394.decode-string.py | iamkissg/leetcode | train | 0 | |
37e4d973fb36d678eba97b6f2562a25650270e1c | [
"if remote_directory == '/':\n res = self._exec_command('chdir /')\n return res\nif remote_directory == '':\n return\nremote_dirname, basename = osp.split(remote_directory)\nself.mkdir_RECURSIVE(remote_dirname)\ntry:\n cmdargs = self.prepare_sftp_command('chdir ' + remote_directory)\n res = self.mylo... | <|body_start_0|>
if remote_directory == '/':
res = self._exec_command('chdir /')
return res
if remote_directory == '':
return
remote_dirname, basename = osp.split(remote_directory)
self.mkdir_RECURSIVE(remote_dirname)
try:
cmdargs =... | This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.SFTPFilesystemServer protocol_copyfrom : asrun.plugins.sftp_server.SFTPFilesystemServer | SFTPFilesystemServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SFTPFilesystemServer:
"""This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.SFTPFilesystemServer protocol_copyfrom :... | stack_v2_sparse_classes_36k_train_024767 | 7,459 | no_license | [
{
"docstring": "Simulating a \"mkdir -p\" command in sftp",
"name": "mkdir_RECURSIVE",
"signature": "def mkdir_RECURSIVE(self, remote_directory, rights=None)"
},
{
"docstring": "Simulating a rm -R command in sftp",
"name": "rmdir_RECURSIVE",
"signature": "def rmdir_RECURSIVE(self, path)"... | 6 | null | Implement the Python class `SFTPFilesystemServer` described below.
Class description:
This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.S... | Implement the Python class `SFTPFilesystemServer` described below.
Class description:
This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.S... | 62592c0f17be823caad8ea71cd52841acbab6185 | <|skeleton|>
class SFTPFilesystemServer:
"""This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.SFTPFilesystemServer protocol_copyfrom :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SFTPFilesystemServer:
"""This class defines a SFTP server for copying files. It is usually used with a SSH server for shell commands. In server configuration, enter: protocol_exec : asrun.plugins.server.SSHServer protocol_copyto : asrun.plugins.sftp_server.SFTPFilesystemServer protocol_copyfrom : asrun.plugin... | the_stack_v2_python_sparse | asrun/plugins/sftp_server.py | zhanxiangqian/salome | train | 1 |
e2d789f7cf28b747e67913c7712ceaa4a8ef8274 | [
"self.radius = radius\nself.radius2 = radius ** 2\nself.xc = x_center\nself.xmin = x_center - radius\nself.xmax = x_center + radius\nself.yc = y_center\nself.ymin = y_center - radius\nself.ymax = y_center + radius",
"while True:\n x = random.uniform(self.xmin, self.xmax)\n y = random.uniform(self.ymin, self... | <|body_start_0|>
self.radius = radius
self.radius2 = radius ** 2
self.xc = x_center
self.xmin = x_center - radius
self.xmax = x_center + radius
self.yc = y_center
self.ymin = y_center - radius
self.ymax = y_center + radius
<|end_body_0|>
<|body_start_1|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.radius = radi... | stack_v2_sparse_classes_36k_train_024768 | 914 | permissive | [
{
"docstring": ":type radius: float :type x_center: float :type y_center: float",
"name": "__init__",
"signature": "def __init__(self, radius, x_center, y_center)"
},
{
"docstring": ":rtype: List[float]",
"name": "randPoint",
"signature": "def randPoint(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_001110 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, radius, x_center, y_center): :type radius: float :type x_center: float :type y_center: float
- def randPoint(self): :rtype: List[float]
<|skeleton|>
class Sol... | 3719f5cb059eefd66b83eb8ae990652f4b7fd124 | <|skeleton|>
class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
<|body_0|>
def randPoint(self):
""":rtype: List[float]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, radius, x_center, y_center):
""":type radius: float :type x_center: float :type y_center: float"""
self.radius = radius
self.radius2 = radius ** 2
self.xc = x_center
self.xmin = x_center - radius
self.xmax = x_center + radius
... | the_stack_v2_python_sparse | Python3/0478-Generate-Random-Point-in-a-Circle/soln.py | wyaadarsh/LeetCode-Solutions | train | 0 | |
e23c611eef6184227698000f33da0114c9df3191 | [
"try:\n\n def generate(vo):\n for subscription in list_subscriptions(name=name, account=account, vo=vo):\n yield (render_json(**subscription) + '\\n')\n return try_stream(generate(vo=request.environ.get('vo')))\nexcept SubscriptionNotFound as error:\n return generate_http_error_flask(404,... | <|body_start_0|>
try:
def generate(vo):
for subscription in list_subscriptions(name=name, account=account, vo=vo):
yield (render_json(**subscription) + '\n')
return try_stream(generate(vo=request.environ.get('vo')))
except SubscriptionNotFound... | REST APIs for subscriptions. | Subscription | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subscription:
"""REST APIs for subscriptions."""
def get(self, account=None, name=None):
"""--- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: The account name. schema: type: string style: simple - na... | stack_v2_sparse_classes_36k_train_024769 | 24,180 | permissive | [
{
"docstring": "--- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: The account name. schema: type: string style: simple - name: name in: path description: The subscription name. schema: type: string style: simple responses: 200:... | 3 | stack_v2_sparse_classes_30k_train_003841 | Implement the Python class `Subscription` described below.
Class description:
REST APIs for subscriptions.
Method signatures and docstrings:
- def get(self, account=None, name=None): --- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: ... | Implement the Python class `Subscription` described below.
Class description:
REST APIs for subscriptions.
Method signatures and docstrings:
- def get(self, account=None, name=None): --- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: ... | 7f0d229ac0b3bc7dec12c6e158bea2b82d414a3b | <|skeleton|>
class Subscription:
"""REST APIs for subscriptions."""
def get(self, account=None, name=None):
"""--- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: The account name. schema: type: string style: simple - na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Subscription:
"""REST APIs for subscriptions."""
def get(self, account=None, name=None):
"""--- summary: Get Subscription description: Retrieve a subscription. tags: - Replicas parameters: - name: account in: path description: The account name. schema: type: string style: simple - name: name in: ... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/subscriptions.py | rucio/rucio | train | 232 |
b6a1f38bd7c658ef43db5712faa03243d894dc71 | [
"super(Button, self).__init__(image=Button.image, x=x, y=y, dx=0, dy=0)\nself.game = game\nself.parent = parent\nself.counter = 0",
"if self.counter != 0:\n self.counter -= 1\nfor sprite in self.overlapping_sprites:\n if sprite == self.game.player and games.keyboard.is_pressed(games.K_s) and (self.counter =... | <|body_start_0|>
super(Button, self).__init__(image=Button.image, x=x, y=y, dx=0, dy=0)
self.game = game
self.parent = parent
self.counter = 0
<|end_body_0|>
<|body_start_1|>
if self.counter != 0:
self.counter -= 1
for sprite in self.overlapping_sprites:
... | Button object that can be pressed to dispense companion cubes | Button | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Button:
"""Button object that can be pressed to dispense companion cubes"""
def __init__(self, game, parent, x, y):
"""Initialize the sprite."""
<|body_0|>
def update(self):
"""If player is over the button they can press it"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_36k_train_024770 | 943 | no_license | [
{
"docstring": "Initialize the sprite.",
"name": "__init__",
"signature": "def __init__(self, game, parent, x, y)"
},
{
"docstring": "If player is over the button they can press it",
"name": "update",
"signature": "def update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004515 | Implement the Python class `Button` described below.
Class description:
Button object that can be pressed to dispense companion cubes
Method signatures and docstrings:
- def __init__(self, game, parent, x, y): Initialize the sprite.
- def update(self): If player is over the button they can press it | Implement the Python class `Button` described below.
Class description:
Button object that can be pressed to dispense companion cubes
Method signatures and docstrings:
- def __init__(self, game, parent, x, y): Initialize the sprite.
- def update(self): If player is over the button they can press it
<|skeleton|>
clas... | aab3e28ef659b9a62060940e752b22679b344fdf | <|skeleton|>
class Button:
"""Button object that can be pressed to dispense companion cubes"""
def __init__(self, game, parent, x, y):
"""Initialize the sprite."""
<|body_0|>
def update(self):
"""If player is over the button they can press it"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Button:
"""Button object that can be pressed to dispense companion cubes"""
def __init__(self, game, parent, x, y):
"""Initialize the sprite."""
super(Button, self).__init__(image=Button.image, x=x, y=y, dx=0, dy=0)
self.game = game
self.parent = parent
self.counte... | the_stack_v2_python_sparse | bin/button.py | noelano/Portal | train | 0 |
1bebf5d0ceac2ebb9379f272ee52d5b9dac018d6 | [
"serializer = ContentLibraryFilterSerializer(data=request.query_params)\nserializer.is_valid(raise_exception=True)\norg = serializer.validated_data['org']\nlibrary_type = serializer.validated_data['type']\ntext_search = serializer.validated_data['text_search']\npaginator = LibraryApiPagination()\nqueryset = api.get... | <|body_start_0|>
serializer = ContentLibraryFilterSerializer(data=request.query_params)
serializer.is_valid(raise_exception=True)
org = serializer.validated_data['org']
library_type = serializer.validated_data['type']
text_search = serializer.validated_data['text_search']
... | Views to list, search for, and create content libraries. | LibraryRootView | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LibraryRootView:
"""Views to list, search for, and create content libraries."""
def get(self, request):
"""Return a list of all content libraries that the user has permission to view."""
<|body_0|>
def post(self, request):
"""Create a new content library."""
... | stack_v2_sparse_classes_36k_train_024771 | 42,120 | permissive | [
{
"docstring": "Return a list of all content libraries that the user has permission to view.",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Create a new content library.",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `LibraryRootView` described below.
Class description:
Views to list, search for, and create content libraries.
Method signatures and docstrings:
- def get(self, request): Return a list of all content libraries that the user has permission to view.
- def post(self, request): Create a new con... | Implement the Python class `LibraryRootView` described below.
Class description:
Views to list, search for, and create content libraries.
Method signatures and docstrings:
- def get(self, request): Return a list of all content libraries that the user has permission to view.
- def post(self, request): Create a new con... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class LibraryRootView:
"""Views to list, search for, and create content libraries."""
def get(self, request):
"""Return a list of all content libraries that the user has permission to view."""
<|body_0|>
def post(self, request):
"""Create a new content library."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LibraryRootView:
"""Views to list, search for, and create content libraries."""
def get(self, request):
"""Return a list of all content libraries that the user has permission to view."""
serializer = ContentLibraryFilterSerializer(data=request.query_params)
serializer.is_valid(rai... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/content_libraries/views.py | luque/better-ways-of-thinking-about-software | train | 3 |
78221a7ec98e7165723377cc52039e01b80ae10e | [
"self.resource_service = resource_service\nself.client = resource_service.client\nself.messages = self.client.MESSAGES_MODULE\nself.status_enum = self.messages.Operation.StatusValueValuesEnum\nself.target_ref = target_ref",
"if operation.error:\n raise OperationErrors(operation.error.errors)\nreturn operation.... | <|body_start_0|>
self.resource_service = resource_service
self.client = resource_service.client
self.messages = self.client.MESSAGES_MODULE
self.status_enum = self.messages.Operation.StatusValueValuesEnum
self.target_ref = target_ref
<|end_body_0|>
<|body_start_1|>
if op... | Compute operations poller. | Poller | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poller:
"""Compute operations poller."""
def __init__(self, resource_service, target_ref=None):
"""Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representing the target of operation. target_ref: Resource, optional... | stack_v2_sparse_classes_36k_train_024772 | 6,267 | permissive | [
{
"docstring": "Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representing the target of operation. target_ref: Resource, optional reference to the expected target of the operation. If not provided operation.targetLink will be used instead."... | 4 | null | Implement the Python class `Poller` described below.
Class description:
Compute operations poller.
Method signatures and docstrings:
- def __init__(self, resource_service, target_ref=None): Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representin... | Implement the Python class `Poller` described below.
Class description:
Compute operations poller.
Method signatures and docstrings:
- def __init__(self, resource_service, target_ref=None): Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representin... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Poller:
"""Compute operations poller."""
def __init__(self, resource_service, target_ref=None):
"""Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representing the target of operation. target_ref: Resource, optional... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Poller:
"""Compute operations poller."""
def __init__(self, resource_service, target_ref=None):
"""Initializes poller for compute operations. Args: resource_service: apitools.base.py.base_api.BaseApiService, service representing the target of operation. target_ref: Resource, optional reference to... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/googlecloudsdk/api_lib/compute/operations/poller.py | KaranToor/MA450 | train | 1 |
3f4761df442b7c0bd44aab5a80ea353cf9457377 | [
"collection_critic = await FakeUserDocument().objects.find_all()\nrandom.shuffle(collection_critic)\nfake_user_list = {}\nfor document_critic in collection_critic[:10]:\n fake_user_list[str(document_critic._id)] = document_critic.info.name\nraise utils.exceptions.Result(content={'fakeUserList': fake_user_list})"... | <|body_start_0|>
collection_critic = await FakeUserDocument().objects.find_all()
random.shuffle(collection_critic)
fake_user_list = {}
for document_critic in collection_critic[:10]:
fake_user_list[str(document_critic._id)] = document_critic.info.name
raise utils.excep... | FakeStatisticHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FakeStatisticHandler:
async def get(self):
"""Запрос данных по пользователям (случайные 10)."""
<|body_0|>
async def post(self):
"""Расчет статистики. В качестве параметров передавать список необходимых данных: двоих пользователей или фильм. Возвращать данные рассчит... | stack_v2_sparse_classes_36k_train_024773 | 6,265 | no_license | [
{
"docstring": "Запрос данных по пользователям (случайные 10).",
"name": "get",
"signature": "async def get(self)"
},
{
"docstring": "Расчет статистики. В качестве параметров передавать список необходимых данных: двоих пользователей или фильм. Возвращать данные рассчитанные данные.",
"name":... | 2 | stack_v2_sparse_classes_30k_train_007359 | Implement the Python class `FakeStatisticHandler` described below.
Class description:
Implement the FakeStatisticHandler class.
Method signatures and docstrings:
- async def get(self): Запрос данных по пользователям (случайные 10).
- async def post(self): Расчет статистики. В качестве параметров передавать список нео... | Implement the Python class `FakeStatisticHandler` described below.
Class description:
Implement the FakeStatisticHandler class.
Method signatures and docstrings:
- async def get(self): Запрос данных по пользователям (случайные 10).
- async def post(self): Расчет статистики. В качестве параметров передавать список нео... | c22b3bc4c533b2e1508dfbd211ce98e26517d079 | <|skeleton|>
class FakeStatisticHandler:
async def get(self):
"""Запрос данных по пользователям (случайные 10)."""
<|body_0|>
async def post(self):
"""Расчет статистики. В качестве параметров передавать список необходимых данных: двоих пользователей или фильм. Возвращать данные рассчит... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FakeStatisticHandler:
async def get(self):
"""Запрос данных по пользователям (случайные 10)."""
collection_critic = await FakeUserDocument().objects.find_all()
random.shuffle(collection_critic)
fake_user_list = {}
for document_critic in collection_critic[:10]:
... | the_stack_v2_python_sparse | server/modules/recommendation/handlers/fake/statistic.py | Rey8d01/chimera | train | 10 | |
b7fb5916f850092f066f97069ca3f8650d7dae24 | [
"self.locale = locale\nself.participant = participant\nself.utterancetierTypes = utterancetierTypes\nself.wordtierTypes = wordtierTypes\nself.postierTypes = postierTypes\nself.morphemetierTypes = None\nself.glosstierTypes = None\nself.translationtierTypes = translationtierTypes\nself.interlineartype = POS\nself.ann... | <|body_start_0|>
self.locale = locale
self.participant = participant
self.utterancetierTypes = utterancetierTypes
self.wordtierTypes = wordtierTypes
self.postierTypes = postierTypes
self.morphemetierTypes = None
self.glosstierTypes = None
self.translationt... | The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and makes this data accessible through several functions. The data contains "tags", w... | PosCorpusReader | [
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PosCorpusReader:
"""The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and makes this data accessible through sev... | stack_v2_sparse_classes_36k_train_024774 | 20,569 | permissive | [
{
"docstring": "root: is the directory where your .eaf files are stored. Only the files in the given directory are read, there is no recursive reading right now. This parameter is obligatory. files: a regular expression for the filenames to read. The default value is \"*.eaf\" locale: restricts the corpus data ... | 4 | stack_v2_sparse_classes_30k_train_006905 | Implement the Python class `PosCorpusReader` described below.
Class description:
The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and... | Implement the Python class `PosCorpusReader` described below.
Class description:
The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and... | ac2bed9b6e759033d17b6ed9e8fa1e79dad68ae6 | <|skeleton|>
class PosCorpusReader:
"""The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and makes this data accessible through sev... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PosCorpusReader:
"""The class EafPosCorpusReader implements a part of the corpus reader API described in the Natual Language Toolkit (NLTK). The class reads in all the .eaf files (from the linguistics annotation software called Elan) in a given directory and makes this data accessible through several function... | the_stack_v2_python_sparse | src/poioapi/corpusreader.py | IgorBMSTU/poio-api | train | 0 |
f0e60f64684acbdeaa07e12e52d8d27ceb140fb1 | [
"super(OpenDetails, self).__init__(*args, **kwargs)\nself.endpoint = 'reports'\nself.campaign_id = None",
"self.campaign_id = campaign_id\nif get_all:\n return self._iterate(url=self._build_path(campaign_id, 'open-details'), **queryparams)\nelse:\n return self._mc_client._get(url=self._build_path(campaign_i... | <|body_start_0|>
super(OpenDetails, self).__init__(*args, **kwargs)
self.endpoint = 'reports'
self.campaign_id = None
<|end_body_0|>
<|body_start_1|>
self.campaign_id = campaign_id
if get_all:
return self._iterate(url=self._build_path(campaign_id, 'open-details'), **... | Get a detailed report about any emails in a specific campaign that were opened by the recipient. | OpenDetails | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpenDetails:
"""Get a detailed report about any emails in a specific campaign that were opened by the recipient."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
<|body_0|>
def all(self, campaign_id, get_all=False, **queryparams):
"""Get deta... | stack_v2_sparse_classes_36k_train_024775 | 1,734 | permissive | [
{
"docstring": "Initialize the endpoint",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Get detailed information about any campaign emails that were opened by a list member. :param campaign_id: The unique id for the campaign. :type campaign_id: :py:cla... | 2 | stack_v2_sparse_classes_30k_train_007946 | Implement the Python class `OpenDetails` described below.
Class description:
Get a detailed report about any emails in a specific campaign that were opened by the recipient.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the endpoint
- def all(self, campaign_id, get_all=False, **q... | Implement the Python class `OpenDetails` described below.
Class description:
Get a detailed report about any emails in a specific campaign that were opened by the recipient.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize the endpoint
- def all(self, campaign_id, get_all=False, **q... | bf61cd602dc44cbff32fbf6f6dcdd33cf6f782e8 | <|skeleton|>
class OpenDetails:
"""Get a detailed report about any emails in a specific campaign that were opened by the recipient."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
<|body_0|>
def all(self, campaign_id, get_all=False, **queryparams):
"""Get deta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpenDetails:
"""Get a detailed report about any emails in a specific campaign that were opened by the recipient."""
def __init__(self, *args, **kwargs):
"""Initialize the endpoint"""
super(OpenDetails, self).__init__(*args, **kwargs)
self.endpoint = 'reports'
self.campaign... | the_stack_v2_python_sparse | mailchimp3/entities/reportopendetails.py | VingtCinq/python-mailchimp | train | 190 |
cbad5f2dcc9b7c4552470abe8d0ea8925579f1eb | [
"if not buf or not skt:\n raise ValueError('<send_bytes> invalid socket descriptor or buf')\nif timeout:\n skt.settimeout(timeout)\nelse:\n skt.settimeout(None)\nlength = len(buf)\nsent_total = 0\nwhile sent_total < length:\n sent = skt.send(buf)\n if not sent:\n raise IOError('<send_bytes> co... | <|body_start_0|>
if not buf or not skt:
raise ValueError('<send_bytes> invalid socket descriptor or buf')
if timeout:
skt.settimeout(timeout)
else:
skt.settimeout(None)
length = len(buf)
sent_total = 0
while sent_total < length:
... | SocketHelper | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocketHelper:
def send_bytes(skt, buf, timeout=0):
"""Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception"""
<|body_0|>
def recv_bytes(skt, length, timeout=0):
"""Receive bytes from the socket @raise ValueError, IOError, socket.timeout, Exc... | stack_v2_sparse_classes_36k_train_024776 | 2,505 | permissive | [
{
"docstring": "Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception",
"name": "send_bytes",
"signature": "def send_bytes(skt, buf, timeout=0)"
},
{
"docstring": "Receive bytes from the socket @raise ValueError, IOError, socket.timeout, Exception",
"name": "recv_byt... | 4 | null | Implement the Python class `SocketHelper` described below.
Class description:
Implement the SocketHelper class.
Method signatures and docstrings:
- def send_bytes(skt, buf, timeout=0): Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception
- def recv_bytes(skt, length, timeout=0): Receive byte... | Implement the Python class `SocketHelper` described below.
Class description:
Implement the SocketHelper class.
Method signatures and docstrings:
- def send_bytes(skt, buf, timeout=0): Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception
- def recv_bytes(skt, length, timeout=0): Receive byte... | 9d8220a0925327bddf0e10887e22b57c5d6adb37 | <|skeleton|>
class SocketHelper:
def send_bytes(skt, buf, timeout=0):
"""Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception"""
<|body_0|>
def recv_bytes(skt, length, timeout=0):
"""Receive bytes from the socket @raise ValueError, IOError, socket.timeout, Exc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SocketHelper:
def send_bytes(skt, buf, timeout=0):
"""Send bytes to the socket @raise ValueError, IOError, socket.timeout, Exception"""
if not buf or not skt:
raise ValueError('<send_bytes> invalid socket descriptor or buf')
if timeout:
skt.settimeout(timeout)
... | the_stack_v2_python_sparse | lib/perf_engines/sys_helper.py | couchbase/testrunner | train | 18 | |
dd2e26be4e72fcb5d389e063df358567e9682624 | [
"super().default_login()\nleaguer_level_page = Leaguer_Level_Page(self.base, test_data)\nleaguer_level_page.switch_in_leaguer_level_menu()\nleaguer_level_page.click_add_btn()\nleaguer_level_page.input_add_info()\nleaguer_level_page.click_save_btn()\nleaguer_level_page.assert_add_result()",
"super().default_login(... | <|body_start_0|>
super().default_login()
leaguer_level_page = Leaguer_Level_Page(self.base, test_data)
leaguer_level_page.switch_in_leaguer_level_menu()
leaguer_level_page.click_add_btn()
leaguer_level_page.input_add_info()
leaguer_level_page.click_save_btn()
leag... | Leaguer_Level_Case | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Leaguer_Level_Case:
def test_001_leaguer_level_add(self):
"""新增会员"""
<|body_0|>
def test_002_leaguer_level_query(self):
"""查询会员"""
<|body_1|>
def test_003_leaguer_level_del(self):
"""删除会员"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_024777 | 1,873 | no_license | [
{
"docstring": "新增会员",
"name": "test_001_leaguer_level_add",
"signature": "def test_001_leaguer_level_add(self)"
},
{
"docstring": "查询会员",
"name": "test_002_leaguer_level_query",
"signature": "def test_002_leaguer_level_query(self)"
},
{
"docstring": "删除会员",
"name": "test_003... | 3 | stack_v2_sparse_classes_30k_train_018071 | Implement the Python class `Leaguer_Level_Case` described below.
Class description:
Implement the Leaguer_Level_Case class.
Method signatures and docstrings:
- def test_001_leaguer_level_add(self): 新增会员
- def test_002_leaguer_level_query(self): 查询会员
- def test_003_leaguer_level_del(self): 删除会员 | Implement the Python class `Leaguer_Level_Case` described below.
Class description:
Implement the Leaguer_Level_Case class.
Method signatures and docstrings:
- def test_001_leaguer_level_add(self): 新增会员
- def test_002_leaguer_level_query(self): 查询会员
- def test_003_leaguer_level_del(self): 删除会员
<|skeleton|>
class Lea... | 94875917afb222cadcf6b4fde391e44cfbc9d199 | <|skeleton|>
class Leaguer_Level_Case:
def test_001_leaguer_level_add(self):
"""新增会员"""
<|body_0|>
def test_002_leaguer_level_query(self):
"""查询会员"""
<|body_1|>
def test_003_leaguer_level_del(self):
"""删除会员"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Leaguer_Level_Case:
def test_001_leaguer_level_add(self):
"""新增会员"""
super().default_login()
leaguer_level_page = Leaguer_Level_Page(self.base, test_data)
leaguer_level_page.switch_in_leaguer_level_menu()
leaguer_level_page.click_add_btn()
leaguer_level_page.inp... | the_stack_v2_python_sparse | test_case/leaguer_case/test_leaguer_level_case.py | goodboyxzmkk/youlebao | train | 5 | |
1bb69a91efb77ee151f70f2ba35860b4a4cbaaea | [
"dirpath_start = os.path.join(dirpath_testdata, 'simple_directory_tree', 'branch_01', 'leaf_01')\ndirpath_expected = os.path.join(dirpath_testdata, 'simple_directory_tree')\ndirpath_actual = da.lwc.search.find_ancestor_dir_containing(dirpath_start, 'marker_file')\nassert dirpath_expected == dirpath_actual",
"dirp... | <|body_start_0|>
dirpath_start = os.path.join(dirpath_testdata, 'simple_directory_tree', 'branch_01', 'leaf_01')
dirpath_expected = os.path.join(dirpath_testdata, 'simple_directory_tree')
dirpath_actual = da.lwc.search.find_ancestor_dir_containing(dirpath_start, 'marker_file')
assert dir... | Specify the find_ancestor_dir_containing() function. | SpecifyFindAncestorDirContaining | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpecifyFindAncestorDirContaining:
"""Specify the find_ancestor_dir_containing() function."""
def it_finds_an_ancestor_dir(self, dirpath_testdata):
"""Smoke test for find_ancestor_dir_containing function."""
<|body_0|>
def it_finds_the_starting_dir(self, dirpath_testdata)... | stack_v2_sparse_classes_36k_train_024778 | 29,518 | permissive | [
{
"docstring": "Smoke test for find_ancestor_dir_containing function.",
"name": "it_finds_an_ancestor_dir",
"signature": "def it_finds_an_ancestor_dir(self, dirpath_testdata)"
},
{
"docstring": "Smoke test for find_ancestor_dir_containing function.",
"name": "it_finds_the_starting_dir",
... | 3 | null | Implement the Python class `SpecifyFindAncestorDirContaining` described below.
Class description:
Specify the find_ancestor_dir_containing() function.
Method signatures and docstrings:
- def it_finds_an_ancestor_dir(self, dirpath_testdata): Smoke test for find_ancestor_dir_containing function.
- def it_finds_the_star... | Implement the Python class `SpecifyFindAncestorDirContaining` described below.
Class description:
Specify the find_ancestor_dir_containing() function.
Method signatures and docstrings:
- def it_finds_an_ancestor_dir(self, dirpath_testdata): Smoke test for find_ancestor_dir_containing function.
- def it_finds_the_star... | 04a13be2792323e3f9fdb83fd236a8e9cfe6aa2d | <|skeleton|>
class SpecifyFindAncestorDirContaining:
"""Specify the find_ancestor_dir_containing() function."""
def it_finds_an_ancestor_dir(self, dirpath_testdata):
"""Smoke test for find_ancestor_dir_containing function."""
<|body_0|>
def it_finds_the_starting_dir(self, dirpath_testdata)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpecifyFindAncestorDirContaining:
"""Specify the find_ancestor_dir_containing() function."""
def it_finds_an_ancestor_dir(self, dirpath_testdata):
"""Smoke test for find_ancestor_dir_containing function."""
dirpath_start = os.path.join(dirpath_testdata, 'simple_directory_tree', 'branch_01... | the_stack_v2_python_sparse | a3_src/h70_internal/da/lwc/spec/spec_search.py | wtpayne/hiai | train | 5 |
e661e1b6676516bd4732d842f6b1c93295cf2fac | [
"if LooseVersion(self.from_version) < LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):\n error_message, error_code = Errors.invalid_version_in_layoutscontainer('fromVersion')\n if self.handle_error(error_message, error_code, file_path=self.file_path):\n return False\nreturn True",
"if self.to_version an... | <|body_start_0|>
if LooseVersion(self.from_version) < LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):
error_message, error_code = Errors.invalid_version_in_layoutscontainer('fromVersion')
if self.handle_error(error_message, error_code, file_path=self.file_path):
return Fals... | LayoutsContainerValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayoutsContainerValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
<|body_0|>
def is_valid_to_version(self) -> bool:
"""Checks if to version field is valid. ... | stack_v2_sparse_classes_36k_train_024779 | 4,349 | permissive | [
{
"docstring": "Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.",
"name": "is_valid_from_version",
"signature": "def is_valid_from_version(self) -> bool"
},
{
"docstring": "Checks if to version field is valid. Returns: bool. True if to versi... | 2 | stack_v2_sparse_classes_30k_train_015086 | Implement the Python class `LayoutsContainerValidator` described below.
Class description:
Implement the LayoutsContainerValidator class.
Method signatures and docstrings:
- def is_valid_from_version(self) -> bool: Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.
... | Implement the Python class `LayoutsContainerValidator` described below.
Class description:
Implement the LayoutsContainerValidator class.
Method signatures and docstrings:
- def is_valid_from_version(self) -> bool: Checks if from version field is valid. Returns: bool. True if from version field is valid, else False.
... | a17e868e6fc5153f09e7a329801de85aa60cc752 | <|skeleton|>
class LayoutsContainerValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
<|body_0|>
def is_valid_to_version(self) -> bool:
"""Checks if to version field is valid. ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayoutsContainerValidator:
def is_valid_from_version(self) -> bool:
"""Checks if from version field is valid. Returns: bool. True if from version field is valid, else False."""
if LooseVersion(self.from_version) < LooseVersion(FROM_VERSION_LAYOUTS_CONTAINER):
error_message, error_c... | the_stack_v2_python_sparse | demisto_sdk/commands/common/hook_validations/layout.py | SukhnandanMalhotra/demisto-sdk | train | 0 | |
4520848a6bf14de2dec126de4f9f116330db3ba1 | [
"super().__init__()\nself.mixture_size = mixture_size\ninitial_scalar_parameters = [0.0] * mixture_size\nself.scalar_parameters = ParameterList([Parameter(torch.tensor([initial_scalar_parameters[i]], dtype=torch.float, device=flair.device), requires_grad=trainable) for i in range(mixture_size)])\nself.gamma = Param... | <|body_start_0|>
super().__init__()
self.mixture_size = mixture_size
initial_scalar_parameters = [0.0] * mixture_size
self.scalar_parameters = ParameterList([Parameter(torch.tensor([initial_scalar_parameters[i]], dtype=torch.float, device=flair.device), requires_grad=trainable) for i in ... | Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://arxiv.org/abs/1903.08855) The implementation is copied and slightly modified f... | ScalarMix | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScalarMix:
"""Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://arxiv.org/abs/1903.08855) The implementat... | stack_v2_sparse_classes_36k_train_024780 | 7,952 | permissive | [
{
"docstring": "Inits scalar mix implementation. ``mixture = gamma * sum(s_k * tensor_k)`` where ``s = softmax(w)``, with ``w`` and ``gamma`` scalar parameters. :param mixture_size: size of mixtures (usually the number of layers)",
"name": "__init__",
"signature": "def __init__(self, mixture_size: int, ... | 2 | null | Implement the Python class `ScalarMix` described below.
Class description:
Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://ar... | Implement the Python class `ScalarMix` described below.
Class description:
Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://ar... | 1795ac80da18efadcd56b46374a40190abca07e4 | <|skeleton|>
class ScalarMix:
"""Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://arxiv.org/abs/1903.08855) The implementat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScalarMix:
"""Mixes several tensors by a learned weighting. Computes a parameterised scalar mixture of N tensors. This method was proposed by Liu et al. (2019) in the paper: "Linguistic Knowledge and Transferability of Contextual Representations" (https://arxiv.org/abs/1903.08855) The implementation is copied... | the_stack_v2_python_sparse | flair/embeddings/base.py | flairNLP/flair | train | 5,684 |
8d3767b711a7d7b15486529f21f8ad54453d622a | [
"self.distance = distance\nself.pid_foward = PID(distance, 0.01, 0.0001, 0.01, 500, -500, 0.7, -0.7)\nself.pid_yaw = PID(0, 0.33, 0.0, 0.33, 500, -500, 100, -100)\nself.pid_angle = PID(0.0, 0.01, 0.0, 0.01, 500, -500, 0.3, -0.3)\nself.pid_height = PID(0.0, 0.002, 0.0002, 0.002, 500, -500, 0.3, -0.2)\ncflib.crtp.ini... | <|body_start_0|>
self.distance = distance
self.pid_foward = PID(distance, 0.01, 0.0001, 0.01, 500, -500, 0.7, -0.7)
self.pid_yaw = PID(0, 0.33, 0.0, 0.33, 500, -500, 100, -100)
self.pid_angle = PID(0.0, 0.01, 0.0, 0.01, 500, -500, 0.3, -0.3)
self.pid_height = PID(0.0, 0.002, 0.00... | Aruco_tracker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Aruco_tracker:
def __init__(self, distance):
"""Inicialização dos drivers, parâmetros do controle PID e decolagem do drone."""
<|body_0|>
def search_marker(self):
"""Interrompe o movimento se nao encontrar o marcador por tres frames consecutivos. Após 4 segundos, ini... | stack_v2_sparse_classes_36k_train_024781 | 3,942 | no_license | [
{
"docstring": "Inicialização dos drivers, parâmetros do controle PID e decolagem do drone.",
"name": "__init__",
"signature": "def __init__(self, distance)"
},
{
"docstring": "Interrompe o movimento se nao encontrar o marcador por tres frames consecutivos. Após 4 segundos, inicia movimento de r... | 4 | stack_v2_sparse_classes_30k_train_004566 | Implement the Python class `Aruco_tracker` described below.
Class description:
Implement the Aruco_tracker class.
Method signatures and docstrings:
- def __init__(self, distance): Inicialização dos drivers, parâmetros do controle PID e decolagem do drone.
- def search_marker(self): Interrompe o movimento se nao encon... | Implement the Python class `Aruco_tracker` described below.
Class description:
Implement the Aruco_tracker class.
Method signatures and docstrings:
- def __init__(self, distance): Inicialização dos drivers, parâmetros do controle PID e decolagem do drone.
- def search_marker(self): Interrompe o movimento se nao encon... | 8af0ca6930b326ae7bc0cd7bb9aa2d6aa62bceeb | <|skeleton|>
class Aruco_tracker:
def __init__(self, distance):
"""Inicialização dos drivers, parâmetros do controle PID e decolagem do drone."""
<|body_0|>
def search_marker(self):
"""Interrompe o movimento se nao encontrar o marcador por tres frames consecutivos. Após 4 segundos, ini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Aruco_tracker:
def __init__(self, distance):
"""Inicialização dos drivers, parâmetros do controle PID e decolagem do drone."""
self.distance = distance
self.pid_foward = PID(distance, 0.01, 0.0001, 0.01, 500, -500, 0.7, -0.7)
self.pid_yaw = PID(0, 0.33, 0.0, 0.33, 500, -500, 10... | the_stack_v2_python_sparse | Código-fonte/Esquadrilha/aruco_tracker_pid.py | EvoSystems-com-br/IniciacaoCientifica2018_ProjetoDrones | train | 0 | |
d416e44660facb07879f2d214c0706e9b0ff04d0 | [
"self.number = number\nself.title = title\nself.paragraphs = []\nfor paragraph_lines in paragraphs:\n new_pragraph = Paragraph.Paragraph(paragraph_lines)\n self.paragraphs.append(new_pragraph)",
"if paragraph_idx:\n self.paragraphs[paragraph_idx].read()\nelse:\n for paragraph in self.paragraphs:\n ... | <|body_start_0|>
self.number = number
self.title = title
self.paragraphs = []
for paragraph_lines in paragraphs:
new_pragraph = Paragraph.Paragraph(paragraph_lines)
self.paragraphs.append(new_pragraph)
<|end_body_0|>
<|body_start_1|>
if paragraph_idx:
... | Chapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chapter:
def __init__(self, number, title, paragraphs):
"""A chapter consists of multiple paragraphs."""
<|body_0|>
def read(self, paragraph_idx=None):
"""A paragraph can be read."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.number = number
... | stack_v2_sparse_classes_36k_train_024782 | 676 | no_license | [
{
"docstring": "A chapter consists of multiple paragraphs.",
"name": "__init__",
"signature": "def __init__(self, number, title, paragraphs)"
},
{
"docstring": "A paragraph can be read.",
"name": "read",
"signature": "def read(self, paragraph_idx=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011824 | Implement the Python class `Chapter` described below.
Class description:
Implement the Chapter class.
Method signatures and docstrings:
- def __init__(self, number, title, paragraphs): A chapter consists of multiple paragraphs.
- def read(self, paragraph_idx=None): A paragraph can be read. | Implement the Python class `Chapter` described below.
Class description:
Implement the Chapter class.
Method signatures and docstrings:
- def __init__(self, number, title, paragraphs): A chapter consists of multiple paragraphs.
- def read(self, paragraph_idx=None): A paragraph can be read.
<|skeleton|>
class Chapter... | 70dac5017980c8f30294f2cbd98e5bfd905bfaa7 | <|skeleton|>
class Chapter:
def __init__(self, number, title, paragraphs):
"""A chapter consists of multiple paragraphs."""
<|body_0|>
def read(self, paragraph_idx=None):
"""A paragraph can be read."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chapter:
def __init__(self, number, title, paragraphs):
"""A chapter consists of multiple paragraphs."""
self.number = number
self.title = title
self.paragraphs = []
for paragraph_lines in paragraphs:
new_pragraph = Paragraph.Paragraph(paragraph_lines)
... | the_stack_v2_python_sparse | week2/objectOriented/Chapter.py | MalteMagnussen/PythonProjects | train | 0 | |
409220a3cf8b7ab8209f12d7ac382a7634617d34 | [
"super(TinyTransformer, self).__init__()\nif N_v is None:\n dim_out = dim_ff[-1] * N_head\nelse:\n dim_out = N_v * N_head\ndim_in = dim_ff[0]\nself.linear_link = linear_link\nself.num_layer = num_layer\nself.h = N_head\nself.dim_ff = dim_ff\nself.mlps = []\nself.attn = []\nself.lins = []\nfor l in range(num_l... | <|body_start_0|>
super(TinyTransformer, self).__init__()
if N_v is None:
dim_out = dim_ff[-1] * N_head
else:
dim_out = N_v * N_head
dim_in = dim_ff[0]
self.linear_link = linear_link
self.num_layer = num_layer
self.h = N_head
self.di... | TinyTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TinyTransformer:
def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args):
"""Separate linear maps for the keys, queries, and values are optional"""
<|body_0|>
def forward(self, x, mask=None):
"""t... | stack_v2_sparse_classes_36k_train_024783 | 45,005 | no_license | [
{
"docstring": "Separate linear maps for the keys, queries, and values are optional",
"name": "__init__",
"signature": "def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args)"
},
{
"docstring": "the mask tells you which inpu... | 2 | stack_v2_sparse_classes_30k_train_011447 | Implement the Python class `TinyTransformer` described below.
Class description:
Implement the TinyTransformer class.
Method signatures and docstrings:
- def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args): Separate linear maps for the keys, q... | Implement the Python class `TinyTransformer` described below.
Class description:
Implement the TinyTransformer class.
Method signatures and docstrings:
- def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args): Separate linear maps for the keys, q... | 1d4c76920d50729680305a4e877c30e2b782d9d7 | <|skeleton|>
class TinyTransformer:
def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args):
"""Separate linear maps for the keys, queries, and values are optional"""
<|body_0|>
def forward(self, x, mask=None):
"""t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TinyTransformer:
def __init__(self, dim_ff, num_layer, N_head, N_qk=None, N_v=None, queries=False, linear_link=False, resnorm=True, **mlp_args):
"""Separate linear maps for the keys, queries, and values are optional"""
super(TinyTransformer, self).__init__()
if N_v is None:
... | the_stack_v2_python_sparse | src/students.py | Kelarion/repler | train | 0 | |
0585300ad5394565d03bdcffc6a41484d181e432 | [
"if type(self).batch_insert == BaseSDS.batch_insert:\n raise NotImplementedError('insert or batch_insert need to be overridden')\nself.batch_insert(document[None], [index], *args, **kwargs)\nreturn self",
"if type(self).insert == BaseSDS.insert:\n raise NotImplementedError('insert or batch_insert need to be... | <|body_start_0|>
if type(self).batch_insert == BaseSDS.batch_insert:
raise NotImplementedError('insert or batch_insert need to be overridden')
self.batch_insert(document[None], [index], *args, **kwargs)
return self
<|end_body_0|>
<|body_start_1|>
if type(self).insert == Base... | Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s)) | BaseSDS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseSDS:
"""Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s))"""
def insert(self, document, index, *args, **kwargs):
"""Insert a single documen... | stack_v2_sparse_classes_36k_train_024784 | 6,136 | permissive | [
{
"docstring": "Insert a single document in the data structure by saving the index. The document is not saved for scalability. This is the default implementation that uses batch_insert. See batch_insert documentation. Parameters ---------- document : numpy.ndarray or torch.Tensor The document to by inserted (wi... | 6 | null | Implement the Python class `BaseSDS` described below.
Class description:
Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s))
Method signatures and docstrings:
- def insert(self, d... | Implement the Python class `BaseSDS` described below.
Class description:
Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s))
Method signatures and docstrings:
- def insert(self, d... | 3d9dbad51e1bfc0bbb1a60d0aa03c99340f6930c | <|skeleton|>
class BaseSDS:
"""Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s))"""
def insert(self, document, index, *args, **kwargs):
"""Insert a single documen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseSDS:
"""Base Search Data Structure, need to be instantiate. Maintains an index for documents to be retrieved with query. When queried the appropriate index(es) will be returned (not the document(s))"""
def insert(self, document, index, *args, **kwargs):
"""Insert a single document in the data... | the_stack_v2_python_sparse | radbm/search/base.py | duchesneaumathieu/radbm | train | 0 |
464c96498b8f3d51b88ac52b5a0545d6dd9aae84 | [
"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!')",
"conte... | <|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... | Missing associated documentation comment in .proto file. | CollectorServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectorServicer:
"""Missing associated documentation comment in .proto file."""
def SendEvent(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SendMetric(self, request, context):
"""Missing associated docume... | stack_v2_sparse_classes_36k_train_024785 | 5,307 | permissive | [
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SendEvent",
"signature": "def SendEvent(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "SendMetric",
"signature": "def SendMetric(self, requ... | 3 | stack_v2_sparse_classes_30k_train_003609 | Implement the Python class `CollectorServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def SendEvent(self, request, context): Missing associated documentation comment in .proto file.
- def SendMetric(self, request, context): Miss... | Implement the Python class `CollectorServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def SendEvent(self, request, context): Missing associated documentation comment in .proto file.
- def SendMetric(self, request, context): Miss... | 135b3ac8947c123571bec80c6e2ff579b772f16d | <|skeleton|>
class CollectorServicer:
"""Missing associated documentation comment in .proto file."""
def SendEvent(self, request, context):
"""Missing associated documentation comment in .proto file."""
<|body_0|>
def SendMetric(self, request, context):
"""Missing associated docume... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectorServicer:
"""Missing associated documentation comment in .proto file."""
def SendEvent(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
... | the_stack_v2_python_sparse | python/grpc/service2/service/service_pb2_grpc.py | JoseIbanez/testing | train | 3 |
625bce635506d481adbb5c09ab311a120b7c0634 | [
"metadata_bytes = f.read(16)\ndimension, self.chunk_size, scaler_vector_length = _struct_unpack(endianness + 'LQL', metadata_bytes)\nif dimension != 1:\n raise ValueError('Data dimension is not 1')\nscaler_class = _scaler_classes[scaler_type]\nself.scalers = [scaler_class(f, endianness) for _ in range(scaler_vec... | <|body_start_0|>
metadata_bytes = f.read(16)
dimension, self.chunk_size, scaler_vector_length = _struct_unpack(endianness + 'LQL', metadata_bytes)
if dimension != 1:
raise ValueError('Data dimension is not 1')
scaler_class = _scaler_classes[scaler_type]
self.scalers =... | Describes DAQmx data for a single channel | DaqMxMetadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DaqMxMetadata:
"""Describes DAQmx data for a single channel"""
def __init__(self, f, endianness, scaler_type, channel_data_type):
"""Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw data index."""
<|body_0|>
def __repr__(self):... | stack_v2_sparse_classes_36k_train_024786 | 12,402 | permissive | [
{
"docstring": "Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw data index.",
"name": "__init__",
"signature": "def __init__(self, f, endianness, scaler_type, channel_data_type)"
},
{
"docstring": "Return string representation of DAQmx metadata",
... | 2 | stack_v2_sparse_classes_30k_train_004377 | Implement the Python class `DaqMxMetadata` described below.
Class description:
Describes DAQmx data for a single channel
Method signatures and docstrings:
- def __init__(self, f, endianness, scaler_type, channel_data_type): Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw d... | Implement the Python class `DaqMxMetadata` described below.
Class description:
Describes DAQmx data for a single channel
Method signatures and docstrings:
- def __init__(self, f, endianness, scaler_type, channel_data_type): Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw d... | 66827d3bf32a715ba4b3521d091c43a3f50a1f1f | <|skeleton|>
class DaqMxMetadata:
"""Describes DAQmx data for a single channel"""
def __init__(self, f, endianness, scaler_type, channel_data_type):
"""Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw data index."""
<|body_0|>
def __repr__(self):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DaqMxMetadata:
"""Describes DAQmx data for a single channel"""
def __init__(self, f, endianness, scaler_type, channel_data_type):
"""Read the metadata for a DAQmx raw segment. This is the raw DAQmx-specific portion of the raw data index."""
metadata_bytes = f.read(16)
dimension, s... | the_stack_v2_python_sparse | nptdms_mod/daqmx.py | fusion-flap/flap_w7x_abes | train | 0 |
a522a9a365b5dc0ed140d6f6d4adb2bf73347791 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn UserExperienceAnalyticsAppHealthOSVersionPerformance()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'activeDeviceCount': lambda n: setattr(self, 'active_device_count', n.get_int... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return UserExperienceAnalyticsAppHealthOSVersionPerformance()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[[Any], Non... | The user experience analytics device OS version performance entity contains OS version performance details. | UserExperienceAnalyticsAppHealthOSVersionPerformance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserExperienceAnalyticsAppHealthOSVersionPerformance:
"""The user experience analytics device OS version performance entity contains OS version performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthOSVersionPerfor... | stack_v2_sparse_classes_36k_train_024787 | 3,897 | 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: UserExperienceAnalyticsAppHealthOSVersionPerformance",
"name": "create_from_discriminator_value",
"signature... | 3 | null | Implement the Python class `UserExperienceAnalyticsAppHealthOSVersionPerformance` described below.
Class description:
The user experience analytics device OS version performance entity contains OS version performance details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional... | Implement the Python class `UserExperienceAnalyticsAppHealthOSVersionPerformance` described below.
Class description:
The user experience analytics device OS version performance entity contains OS version performance details.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class UserExperienceAnalyticsAppHealthOSVersionPerformance:
"""The user experience analytics device OS version performance entity contains OS version performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthOSVersionPerfor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserExperienceAnalyticsAppHealthOSVersionPerformance:
"""The user experience analytics device OS version performance entity contains OS version performance details."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> UserExperienceAnalyticsAppHealthOSVersionPerformance:
... | the_stack_v2_python_sparse | msgraph/generated/models/user_experience_analytics_app_health_o_s_version_performance.py | microsoftgraph/msgraph-sdk-python | train | 135 |
ece6df2ca704c466fa44676ffc47ee7d5c67d417 | [
"if n == 0:\n return [0]\n\ndef gray(code, counter, target):\n if counter == target:\n return code\n rcode = code[::-1]\n for i in range(len(code)):\n code[i] = '0' + code[i]\n for i in range(len(rcode)):\n rcode[i] = '1' + rcode[i]\n return gray(code + rcode, counter + 1, tar... | <|body_start_0|>
if n == 0:
return [0]
def gray(code, counter, target):
if counter == target:
return code
rcode = code[::-1]
for i in range(len(code)):
code[i] = '0' + code[i]
for i in range(len(rcode)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def grayCode(self, n):
""":type n: int :rtype: List[int]"""
<|body_0|>
def grayCode2(self, n):
"""An amazing more efficient solution by a fellow coder"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 0:
return [0]
... | stack_v2_sparse_classes_36k_train_024788 | 1,488 | no_license | [
{
"docstring": ":type n: int :rtype: List[int]",
"name": "grayCode",
"signature": "def grayCode(self, n)"
},
{
"docstring": "An amazing more efficient solution by a fellow coder",
"name": "grayCode2",
"signature": "def grayCode2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def grayCode(self, n): :type n: int :rtype: List[int]
- def grayCode2(self, n): An amazing more efficient solution by a fellow coder | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def grayCode(self, n): :type n: int :rtype: List[int]
- def grayCode2(self, n): An amazing more efficient solution by a fellow coder
<|skeleton|>
class Solution:
def grayCo... | b7e92f9a7c4d6652d4901b189f51063ce5520653 | <|skeleton|>
class Solution:
def grayCode(self, n):
""":type n: int :rtype: List[int]"""
<|body_0|>
def grayCode2(self, n):
"""An amazing more efficient solution by a fellow coder"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def grayCode(self, n):
""":type n: int :rtype: List[int]"""
if n == 0:
return [0]
def gray(code, counter, target):
if counter == target:
return code
rcode = code[::-1]
for i in range(len(code)):
... | the_stack_v2_python_sparse | leetcode/medium/gray_code.py | abkunal/Data-Structures-and-Algorithms | train | 2 | |
a89198cd71be35f99f3929834a08f1c869535cce | [
"input_json = request.data\noutput_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))\ntry:\n json_params = input_json['APIParams']\n json_params['profile_... | <|body_start_0|>
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))
try:
json_params = input_jso... | This API will fetch all notifications for a user | FetchMyNotificationsAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FetchMyNotificationsAPI:
"""This API will fetch all notifications for a user"""
def post(self, request):
"""Post function to crete a notification"""
<|body_0|>
def fetch_my_notifications_json(self, request):
"""This API will fetch all notifications for a user. :p... | stack_v2_sparse_classes_36k_train_024789 | 3,361 | no_license | [
{
"docstring": "Post function to crete a notification",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "This API will fetch all notifications for a user. :param request: { 'profile_id':277 } :return",
"name": "fetch_my_notifications_json",
"signature": "def fetc... | 2 | stack_v2_sparse_classes_30k_train_011875 | Implement the Python class `FetchMyNotificationsAPI` described below.
Class description:
This API will fetch all notifications for a user
Method signatures and docstrings:
- def post(self, request): Post function to crete a notification
- def fetch_my_notifications_json(self, request): This API will fetch all notific... | Implement the Python class `FetchMyNotificationsAPI` described below.
Class description:
This API will fetch all notifications for a user
Method signatures and docstrings:
- def post(self, request): Post function to crete a notification
- def fetch_my_notifications_json(self, request): This API will fetch all notific... | 36eb9931f330e64902354c6fc471be2adf4b7049 | <|skeleton|>
class FetchMyNotificationsAPI:
"""This API will fetch all notifications for a user"""
def post(self, request):
"""Post function to crete a notification"""
<|body_0|>
def fetch_my_notifications_json(self, request):
"""This API will fetch all notifications for a user. :p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FetchMyNotificationsAPI:
"""This API will fetch all notifications for a user"""
def post(self, request):
"""Post function to crete a notification"""
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [inp... | the_stack_v2_python_sparse | Generic/common/notifications_new/api/fetch_my_notifications/views_fetch_my_notifications.py | archiemb303/common_backend_django | train | 0 |
e013bb92a9e26aa4e07c4bf60dbae05284a1b481 | [
"if storage_type == 'sql':\n loader = cls._get_sql_loader(provider, **kwargs)\nelif storage_type == 's3':\n loader = cls._get_s3_loader(provider)\nelse:\n raise ValueError('Storage type %s is not supported' % storage_type)\nreturn loader",
"loader: icdlab.AbstractS3DataLoader\nif provider == 'kibot':\n ... | <|body_start_0|>
if storage_type == 'sql':
loader = cls._get_sql_loader(provider, **kwargs)
elif storage_type == 's3':
loader = cls._get_s3_loader(provider)
else:
raise ValueError('Storage type %s is not supported' % storage_type)
return loader
<|end_b... | Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type). | LoaderFactory | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoaderFactory:
"""Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type)."""
def get_loader(cls, storage_type: str, provider: str, **kwargs: Any) -> icdlab.AbstractDataLoader:
"""Return a data loader for the requested `storage_type` and `provi... | stack_v2_sparse_classes_36k_train_024790 | 3,109 | permissive | [
{
"docstring": "Return a data loader for the requested `storage_type` and `provider`. :param storage_type: load from where (e.g., s3, sql) :param provider: provider (e.g., kibot, ib) :param kwargs: additional parameters for loader instantiation :raises ValueError: `storage_type` loader is not implemented for pr... | 3 | stack_v2_sparse_classes_30k_train_000562 | Implement the Python class `LoaderFactory` described below.
Class description:
Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type).
Method signatures and docstrings:
- def get_loader(cls, storage_type: str, provider: str, **kwargs: Any) -> icdlab.AbstractDataLoader: Return ... | Implement the Python class `LoaderFactory` described below.
Class description:
Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type).
Method signatures and docstrings:
- def get_loader(cls, storage_type: str, provider: str, **kwargs: Any) -> icdlab.AbstractDataLoader: Return ... | 363c59fa29df2ba2719cbad2f8a19ae12cc54a92 | <|skeleton|>
class LoaderFactory:
"""Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type)."""
def get_loader(cls, storage_type: str, provider: str, **kwargs: Any) -> icdlab.AbstractDataLoader:
"""Return a data loader for the requested `storage_type` and `provi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoaderFactory:
"""Builds AbstractDataLoader objects based on different criteria (e.g., provider and storage type)."""
def get_loader(cls, storage_type: str, provider: str, **kwargs: Any) -> icdlab.AbstractDataLoader:
"""Return a data loader for the requested `storage_type` and `provider`. :param ... | the_stack_v2_python_sparse | im/app/services/loader_factory.py | srlindemann/amp | train | 0 |
e56498107c650b8f0078a4c2b42b3c63f5253d9b | [
"if not isinstance(tpl, tuple):\n return False\nif not len(tpl) == 2:\n return False\nif not isinstance(tpl[0], int) or not isinstance(tpl[1], int):\n return False\nif tpl[0] < 0 or tpl[1] < 0:\n return False\nreturn True",
"if not isinstance(array, np.ndarray) or not self.shape(dimensions) or (not se... | <|body_start_0|>
if not isinstance(tpl, tuple):
return False
if not len(tpl) == 2:
return False
if not isinstance(tpl[0], int) or not isinstance(tpl[1], int):
return False
if tpl[0] < 0 or tpl[1] < 0:
return False
return True
<|end_... | Scrapbooker class | ScrapBooker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScrapBooker:
"""Scrapbooker class"""
def shape(self, tpl):
"""Utility to check if object is a valid 'shape' of format (x, y)"""
<|body_0|>
def crop(self, array, dimensions, position=(0, 0)):
"""Crops the image as a rectangle via dim arguments (being the new heigh... | stack_v2_sparse_classes_36k_train_024791 | 3,859 | no_license | [
{
"docstring": "Utility to check if object is a valid 'shape' of format (x, y)",
"name": "shape",
"signature": "def shape(self, tpl)"
},
{
"docstring": "Crops the image as a rectangle via dim arguments (being the new height and width oof the image) from the coordinates given by position argument... | 5 | stack_v2_sparse_classes_30k_train_006661 | Implement the Python class `ScrapBooker` described below.
Class description:
Scrapbooker class
Method signatures and docstrings:
- def shape(self, tpl): Utility to check if object is a valid 'shape' of format (x, y)
- def crop(self, array, dimensions, position=(0, 0)): Crops the image as a rectangle via dim arguments... | Implement the Python class `ScrapBooker` described below.
Class description:
Scrapbooker class
Method signatures and docstrings:
- def shape(self, tpl): Utility to check if object is a valid 'shape' of format (x, y)
- def crop(self, array, dimensions, position=(0, 0)): Crops the image as a rectangle via dim arguments... | d47cab16cbad806a14b1323014dbab8da5a000aa | <|skeleton|>
class ScrapBooker:
"""Scrapbooker class"""
def shape(self, tpl):
"""Utility to check if object is a valid 'shape' of format (x, y)"""
<|body_0|>
def crop(self, array, dimensions, position=(0, 0)):
"""Crops the image as a rectangle via dim arguments (being the new heigh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScrapBooker:
"""Scrapbooker class"""
def shape(self, tpl):
"""Utility to check if object is a valid 'shape' of format (x, y)"""
if not isinstance(tpl, tuple):
return False
if not len(tpl) == 2:
return False
if not isinstance(tpl[0], int) or not isin... | the_stack_v2_python_sparse | day03/ex02/ScrapBooker.py | cclaude42/python_bootcamp | train | 7 |
c080cdf86e43b13bc5852d13a061e33a6e7b2e73 | [
"_check_data_dim(data, dim=2)\nx = data[:, 0]\ny = data[:, 1]\nA = np.zeros((3, data.shape[0]), dtype=np.double)\nA[2, :] = -1\n\ndef dist(xc, yc):\n return np.sqrt((x - xc) ** 2 + (y - yc) ** 2)\n\ndef fun(params):\n xc, yc, r = params\n return dist(xc, yc) - r\n\ndef Dfun(params):\n xc, yc, r = params... | <|body_start_0|>
_check_data_dim(data, dim=2)
x = data[:, 0]
y = data[:, 1]
A = np.zeros((3, data.shape[0]), dtype=np.double)
A[2, :] = -1
def dist(xc, yc):
return np.sqrt((x - xc) ** 2 + (y - yc) ** 2)
def fun(params):
xc, yc, r = params... | Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) } A minimum number of 3 points is required to solve for the paramet... | CircleModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CircleModel:
"""Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) } A minimum number of 3 poin... | stack_v2_sparse_classes_36k_train_024792 | 28,119 | permissive | [
{
"docstring": "Estimate circle model from data using total least squares. Parameters ---------- data : (N, 2) array N points with ``(x, y)`` coordinates, respectively. Returns ------- success : bool True, if model estimation succeeds.",
"name": "estimate",
"signature": "def estimate(self, data)"
},
... | 3 | stack_v2_sparse_classes_30k_train_000093 | Implement the Python class `CircleModel` described below.
Class description:
Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc... | Implement the Python class `CircleModel` described below.
Class description:
Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class CircleModel:
"""Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) } A minimum number of 3 poin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CircleModel:
"""Total least squares estimator for 2D circles. The functional model of the circle is:: r**2 = (x - xc)**2 + (y - yc)**2 This estimator minimizes the squared distances from all points to the circle:: min{ sum((r - sqrt((x_i - xc)**2 + (y_i - yc)**2))**2) } A minimum number of 3 points is require... | the_stack_v2_python_sparse | Skimage_numpy/source/skimage/measure/fit.py | ryfeus/lambda-packs | train | 1,283 |
4bc1c7956d246798c6432acedc08f32fae3b718b | [
"if self._disk_subformat is None:\n with open(self.path, 'rb') as fileobj:\n header = fileobj.read(1000).decode('ascii', 'ignore')\n match = re.search('createType=\"(.*)\"', header)\n if not match:\n raise RuntimeError(\"Could not find VMDK 'createType' in the file header:\\n{0}\".format(head... | <|body_start_0|>
if self._disk_subformat is None:
with open(self.path, 'rb') as fileobj:
header = fileobj.read(1000).decode('ascii', 'ignore')
match = re.search('createType="(.*)"', header)
if not match:
raise RuntimeError("Could not find VMDK ... | VMDK disk image file representation. | VMDK | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VMDK:
"""VMDK disk image file representation."""
def disk_subformat(self):
"""Disk subformat, such as 'streamOptimized'."""
<|body_0|>
def from_other_image(cls, input_image, output_dir, output_subformat='streamOptimized'):
"""Convert the other disk image into an ... | stack_v2_sparse_classes_36k_train_024793 | 7,641 | permissive | [
{
"docstring": "Disk subformat, such as 'streamOptimized'.",
"name": "disk_subformat",
"signature": "def disk_subformat(self)"
},
{
"docstring": "Convert the other disk image into an image of this type. Args: input_image (DiskRepresentation): Existing image representation. output_dir (str): Outp... | 3 | stack_v2_sparse_classes_30k_train_011852 | Implement the Python class `VMDK` described below.
Class description:
VMDK disk image file representation.
Method signatures and docstrings:
- def disk_subformat(self): Disk subformat, such as 'streamOptimized'.
- def from_other_image(cls, input_image, output_dir, output_subformat='streamOptimized'): Convert the othe... | Implement the Python class `VMDK` described below.
Class description:
VMDK disk image file representation.
Method signatures and docstrings:
- def disk_subformat(self): Disk subformat, such as 'streamOptimized'.
- def from_other_image(cls, input_image, output_dir, output_subformat='streamOptimized'): Convert the othe... | 0811b96311881a8293f28f2e300f6bed1b77ee31 | <|skeleton|>
class VMDK:
"""VMDK disk image file representation."""
def disk_subformat(self):
"""Disk subformat, such as 'streamOptimized'."""
<|body_0|>
def from_other_image(cls, input_image, output_dir, output_subformat='streamOptimized'):
"""Convert the other disk image into an ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VMDK:
"""VMDK disk image file representation."""
def disk_subformat(self):
"""Disk subformat, such as 'streamOptimized'."""
if self._disk_subformat is None:
with open(self.path, 'rb') as fileobj:
header = fileobj.read(1000).decode('ascii', 'ignore')
... | the_stack_v2_python_sparse | COT/disks/vmdk.py | glennmatthews/cot | train | 88 |
1bb39d0527726bbab2b79a96b63c677b6f88e5e1 | [
"data = {'token': self.token, 'project_id': project_id}\ndata.update(kwargs)\nfiles = {'file': open(filename, 'r')}\nreturn self.api._post('templates/import_into_project', data=data, files=files)",
"data = {'token': self.token, 'project_id': project_id}\ndata.update(kwargs)\nreturn self.api._post('templates/expor... | <|body_start_0|>
data = {'token': self.token, 'project_id': project_id}
data.update(kwargs)
files = {'file': open(filename, 'r')}
return self.api._post('templates/import_into_project', data=data, files=files)
<|end_body_0|>
<|body_start_1|>
data = {'token': self.token, 'project_... | TemplatesManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplatesManager:
def import_into_project(self, project_id, filename, **kwargs):
"""Imports a template into a project."""
<|body_0|>
def export_as_file(self, project_id, **kwargs):
"""Exports a template as a file."""
<|body_1|>
def export_as_url(self, pr... | stack_v2_sparse_classes_36k_train_024794 | 993 | permissive | [
{
"docstring": "Imports a template into a project.",
"name": "import_into_project",
"signature": "def import_into_project(self, project_id, filename, **kwargs)"
},
{
"docstring": "Exports a template as a file.",
"name": "export_as_file",
"signature": "def export_as_file(self, project_id,... | 3 | stack_v2_sparse_classes_30k_train_007706 | Implement the Python class `TemplatesManager` described below.
Class description:
Implement the TemplatesManager class.
Method signatures and docstrings:
- def import_into_project(self, project_id, filename, **kwargs): Imports a template into a project.
- def export_as_file(self, project_id, **kwargs): Exports a temp... | Implement the Python class `TemplatesManager` described below.
Class description:
Implement the TemplatesManager class.
Method signatures and docstrings:
- def import_into_project(self, project_id, filename, **kwargs): Imports a template into a project.
- def export_as_file(self, project_id, **kwargs): Exports a temp... | 7b85de81619146d3d54fececda068010ae73775b | <|skeleton|>
class TemplatesManager:
def import_into_project(self, project_id, filename, **kwargs):
"""Imports a template into a project."""
<|body_0|>
def export_as_file(self, project_id, **kwargs):
"""Exports a template as a file."""
<|body_1|>
def export_as_url(self, pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemplatesManager:
def import_into_project(self, project_id, filename, **kwargs):
"""Imports a template into a project."""
data = {'token': self.token, 'project_id': project_id}
data.update(kwargs)
files = {'file': open(filename, 'r')}
return self.api._post('templates/im... | the_stack_v2_python_sparse | todoist/managers/templates.py | Doist/todoist-python | train | 627 | |
635f22143c3d162117e618e790d84e4b1921ae3d | [
"self.color = color\nself.color_code = '0xFFFFFF'\nif self.color == 'blue':\n self.color_code = '#1E90FF'\nelif self.color == 'red':\n self.color_code = '#DC143C'\nelif self.color == 'green':\n self.color_code = '#32CD32'\nself.stations = {}",
"logger.info(f'In Line({self.color}), creating station:{json.... | <|body_start_0|>
self.color = color
self.color_code = '0xFFFFFF'
if self.color == 'blue':
self.color_code = '#1E90FF'
elif self.color == 'red':
self.color_code = '#DC143C'
elif self.color == 'green':
self.color_code = '#32CD32'
self.sta... | Defines the Line Model | Line | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Line:
"""Defines the Line Model"""
def __init__(self, color):
"""Creates a line"""
<|body_0|>
def _handle_station(self, value):
"""Adds the station to this Line's data model"""
<|body_1|>
def _handle_arrival(self, message):
"""Updates train l... | stack_v2_sparse_classes_36k_train_024795 | 4,009 | no_license | [
{
"docstring": "Creates a line",
"name": "__init__",
"signature": "def __init__(self, color)"
},
{
"docstring": "Adds the station to this Line's data model",
"name": "_handle_station",
"signature": "def _handle_station(self, value)"
},
{
"docstring": "Updates train locations",
... | 4 | stack_v2_sparse_classes_30k_train_002859 | Implement the Python class `Line` described below.
Class description:
Defines the Line Model
Method signatures and docstrings:
- def __init__(self, color): Creates a line
- def _handle_station(self, value): Adds the station to this Line's data model
- def _handle_arrival(self, message): Updates train locations
- def ... | Implement the Python class `Line` described below.
Class description:
Defines the Line Model
Method signatures and docstrings:
- def __init__(self, color): Creates a line
- def _handle_station(self, value): Adds the station to this Line's data model
- def _handle_arrival(self, message): Updates train locations
- def ... | 6688dfbaac143730e8eec0e0b1540f502a8c00bd | <|skeleton|>
class Line:
"""Defines the Line Model"""
def __init__(self, color):
"""Creates a line"""
<|body_0|>
def _handle_station(self, value):
"""Adds the station to this Line's data model"""
<|body_1|>
def _handle_arrival(self, message):
"""Updates train l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Line:
"""Defines the Line Model"""
def __init__(self, color):
"""Creates a line"""
self.color = color
self.color_code = '0xFFFFFF'
if self.color == 'blue':
self.color_code = '#1E90FF'
elif self.color == 'red':
self.color_code = '#DC143C'
... | the_stack_v2_python_sparse | Optimizing Public Transportation/consumers/models/line.py | gmpatil/DataStreamingND | train | 0 |
854fdb81330fd1292d122a477393c5810e1fff61 | [
"self.name = name\nif isinstance(appNamespace, ModuleType):\n self.appNamespace = appNamespace\nelse:\n raise TypeError('Second argument of ViewRouter constructor must be a python module.')\nif label is not None:\n self.label = label\nelse:\n self.label = self.name\nself.registry[name] = self\nself.page... | <|body_start_0|>
self.name = name
if isinstance(appNamespace, ModuleType):
self.appNamespace = appNamespace
else:
raise TypeError('Second argument of ViewRouter constructor must be a python module.')
if label is not None:
self.label = label
els... | This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages) | ViewRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewRouter:
"""This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages)"""
def __init__(self, name, appNamespace, label=None):
""":param str name: the name of th... | stack_v2_sparse_classes_36k_train_024796 | 1,575 | no_license | [
{
"docstring": ":param str name: the name of the router, used as part of the name for the page URL: http::/hostname/routerName/pageName",
"name": "__init__",
"signature": "def __init__(self, name, appNamespace, label=None)"
},
{
"docstring": "Calls a page view function with name *name* passing t... | 2 | null | Implement the Python class `ViewRouter` described below.
Class description:
This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages)
Method signatures and docstrings:
- def __init__(self, name, a... | Implement the Python class `ViewRouter` described below.
Class description:
This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages)
Method signatures and docstrings:
- def __init__(self, name, a... | 91d2eca1e443c5bca0757c5576e86a227c45288c | <|skeleton|>
class ViewRouter:
"""This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages)"""
def __init__(self, name, appNamespace, label=None):
""":param str name: the name of th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewRouter:
"""This class creates a global registry of pages. Web pages register with an instance (router) using the @registerView decorator, and can be served when requested (from router.pages)"""
def __init__(self, name, appNamespace, label=None):
""":param str name: the name of the router, use... | the_stack_v2_python_sparse | smo/web/router.py | wzzhhh1/SmoWeb | train | 0 |
fc7e7f164d6ac62856bc4f9717c4d73d7301922f | [
"queue = [root] if root else []\nres = ''\nwhile queue:\n node = queue.pop(0)\n if node:\n res += '%d,' % node.val\n queue.append(node.left)\n queue.append(node.right)\n else:\n res += 'N,'\nreturn res[:-1]",
"data_list = data.split(',')\nval = data_list.pop(0)\nif not val:\n ... | <|body_start_0|>
queue = [root] if root else []
res = ''
while queue:
node = queue.pop(0)
if node:
res += '%d,' % node.val
queue.append(node.left)
queue.append(node.right)
else:
res += 'N,'
... | 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_024797 | 2,305 | 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 | stack_v2_sparse_classes_30k_train_007187 | 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:... | 95d5aa4158209ad9ab81017e3bc82ef0680ea6bd | <|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"""
queue = [root] if root else []
res = ''
while queue:
node = queue.pop(0)
if node:
res += '%d,' % node.val
queue.ap... | the_stack_v2_python_sparse | Tree/BinaryTree/297_Serialize_and_Deserialize_Binary_Tree.py | OldFuzzier/Data-Structures-and-Algorithms- | train | 0 | |
6d3f111e512bc82eefbd0e8bec7dfb33148bac1b | [
"hub_status_count = HubStatus.objects.count()\nlamp_status_count = LampCtrlStatus.objects.count()\nthreads_count = 1\nmysql_memory = 0\nif platform.system() == 'Linux':\n process = subprocess.Popen('mysqladmin -uroot -psmartlamp status', shell=True, stdout=subprocess.PIPE)\n ret = process.stdout.readline()\n ... | <|body_start_0|>
hub_status_count = HubStatus.objects.count()
lamp_status_count = LampCtrlStatus.objects.count()
threads_count = 1
mysql_memory = 0
if platform.system() == 'Linux':
process = subprocess.Popen('mysqladmin -uroot -psmartlamp status', shell=True, stdout=s... | 状态 get_database_status: 获取数据库状态 | StatusViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatusViewSet:
"""状态 get_database_status: 获取数据库状态"""
def get_database_status(self, request, *args, **kwargs):
"""获取数据库状态 GET /status/database/ :return { "hub_status_count": hub_status_count, "lamp_status_count": lamp_status_count, "threads_count": threads_count, "database_memory": my... | stack_v2_sparse_classes_36k_train_024798 | 5,381 | no_license | [
{
"docstring": "获取数据库状态 GET /status/database/ :return { \"hub_status_count\": hub_status_count, \"lamp_status_count\": lamp_status_count, \"threads_count\": threads_count, \"database_memory\": mysql_memory }",
"name": "get_database_status",
"signature": "def get_database_status(self, request, *args, **k... | 2 | null | Implement the Python class `StatusViewSet` described below.
Class description:
状态 get_database_status: 获取数据库状态
Method signatures and docstrings:
- def get_database_status(self, request, *args, **kwargs): 获取数据库状态 GET /status/database/ :return { "hub_status_count": hub_status_count, "lamp_status_count": lamp_status_cou... | Implement the Python class `StatusViewSet` described below.
Class description:
状态 get_database_status: 获取数据库状态
Method signatures and docstrings:
- def get_database_status(self, request, *args, **kwargs): 获取数据库状态 GET /status/database/ :return { "hub_status_count": hub_status_count, "lamp_status_count": lamp_status_cou... | e153a5c02cce248bea8412f432c02d5e26f1fdc1 | <|skeleton|>
class StatusViewSet:
"""状态 get_database_status: 获取数据库状态"""
def get_database_status(self, request, *args, **kwargs):
"""获取数据库状态 GET /status/database/ :return { "hub_status_count": hub_status_count, "lamp_status_count": lamp_status_count, "threads_count": threads_count, "database_memory": my... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StatusViewSet:
"""状态 get_database_status: 获取数据库状态"""
def get_database_status(self, request, *args, **kwargs):
"""获取数据库状态 GET /status/database/ :return { "hub_status_count": hub_status_count, "lamp_status_count": lamp_status_count, "threads_count": threads_count, "database_memory": mysql_memory }"... | the_stack_v2_python_sparse | apps/status/views.py | CabbyWang/django-demo | train | 0 |
bf9f1b5d0fe2f1f28c3041d3ed1af49bbf0090d4 | [
"q = Queue.PriorityQueue()\nfor n in nums:\n if q.qsize() == k + 1:\n q.get()\n q.put(n)\nwhile q.qsize() != k:\n q.get()\nreturn q.get()",
"import heapq\nary = []\nfor i in nums:\n heapq.heappush(ary, i)\n if len(ary) > k:\n heapq.heappop(ary)\nreturn heapq.heappop(ary)"
] | <|body_start_0|>
q = Queue.PriorityQueue()
for n in nums:
if q.qsize() == k + 1:
q.get()
q.put(n)
while q.qsize() != k:
q.get()
return q.get()
<|end_body_0|>
<|body_start_1|>
import heapq
ary = []
for i in nums:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def rewrite(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
q = Queue.Prio... | stack_v2_sparse_classes_36k_train_024799 | 1,497 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findKthLargest",
"signature": "def findKthLargest(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, nums, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthLargest(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def rewrite(self, nums, k): :type nums: List[int] :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findKthLargest(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def rewrite(self, nums, k): :type nums: List[int] :type k: int :rtype: int
<|skeleton|>
class... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def rewrite(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 findKthLargest(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
q = Queue.PriorityQueue()
for n in nums:
if q.qsize() == k + 1:
q.get()
q.put(n)
while q.qsize() != k:
q.get()
return q.... | the_stack_v2_python_sparse | co_ms/215_Kth_Largest_Element_in_an_Array.py | vsdrun/lc_public | train | 6 |
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