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c512c29e936921f2ad8fd937d3100dea310ce9eb | [
"response = await self.client(Operation(operation_type='RUNNER_READ_ALL'))\nself.set_header('Content-Type', 'application/json; charset=UTF-8')\nself.write(response)",
"patch = SchemaParser.parse_patch(self.request.decoded_body, from_string=True)\nfor op in patch:\n operation = op.operation.lower()\n if oper... | <|body_start_0|>
response = await self.client(Operation(operation_type='RUNNER_READ_ALL'))
self.set_header('Content-Type', 'application/json; charset=UTF-8')
self.write(response)
<|end_body_0|>
<|body_start_1|>
patch = SchemaParser.parse_patch(self.request.decoded_body, from_string=True... | RunnerListAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunnerListAPI:
async def get(self):
"""--- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: $ref: '#/definitions/50xError' tags: - Runners"""
<|body_0|>
async def patch(... | stack_v2_sparse_classes_36k_train_007800 | 6,146 | permissive | [
{
"docstring": "--- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: $ref: '#/definitions/50xError' tags: - Runners",
"name": "get",
"signature": "async def get(self)"
},
{
"docstring": "---... | 2 | stack_v2_sparse_classes_30k_train_003305 | Implement the Python class `RunnerListAPI` described below.
Class description:
Implement the RunnerListAPI class.
Method signatures and docstrings:
- async def get(self): --- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404... | Implement the Python class `RunnerListAPI` described below.
Class description:
Implement the RunnerListAPI class.
Method signatures and docstrings:
- async def get(self): --- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404... | a5fd2dcc2444409e243d3fdaa43d86695e5cb142 | <|skeleton|>
class RunnerListAPI:
async def get(self):
"""--- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: $ref: '#/definitions/50xError' tags: - Runners"""
<|body_0|>
async def patch(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunnerListAPI:
async def get(self):
"""--- summary: Retrieve runners responses: 200: description: List of runner states schema: $ref: '#/definitions/Runner' 404: $ref: '#/definitions/404Error' 50x: $ref: '#/definitions/50xError' tags: - Runners"""
response = await self.client(Operation(operati... | the_stack_v2_python_sparse | src/app/beer_garden/api/http/handlers/vbeta/runner.py | beer-garden/beer-garden | train | 254 | |
d21ffde04f29a5cbc938c708913679b3035fe5a9 | [
"self.auto_log_backup = auto_log_backup\nself.dynamic_config = dynamic_config\nself.entity_support = entity_support\nself.full_backup = full_backup\nself.incr_backup = incr_backup\nself.log_backup = log_backup\nself.multi_object_restore = multi_object_restore",
"if dictionary is None:\n return None\nauto_log_b... | <|body_start_0|>
self.auto_log_backup = auto_log_backup
self.dynamic_config = dynamic_config
self.entity_support = entity_support
self.full_backup = full_backup
self.incr_backup = incr_backup
self.log_backup = log_backup
self.multi_object_restore = multi_object_re... | Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configuration' capability. entity_support (bool): Indicates if source has entity capability. full_b... | UdaSourceCapabilities | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UdaSourceCapabilities:
"""Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configuration' capability. entity_support (bool): ... | stack_v2_sparse_classes_36k_train_007801 | 3,068 | permissive | [
{
"docstring": "Constructor for the UdaSourceCapabilities class",
"name": "__init__",
"signature": "def __init__(self, auto_log_backup=None, dynamic_config=None, entity_support=None, full_backup=None, incr_backup=None, log_backup=None, multi_object_restore=None)"
},
{
"docstring": "Creates an in... | 2 | stack_v2_sparse_classes_30k_train_016829 | Implement the Python class `UdaSourceCapabilities` described below.
Class description:
Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configurati... | Implement the Python class `UdaSourceCapabilities` described below.
Class description:
Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configurati... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class UdaSourceCapabilities:
"""Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configuration' capability. entity_support (bool): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UdaSourceCapabilities:
"""Implementation of the 'UdaSourceCapabilities' model. TODO: type description here. Attributes: auto_log_backup (bool): TODO: Type description here. dynamic_config (bool): Specifies whether the source supports the 'Dynamic Configuration' capability. entity_support (bool): Indicates if ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/uda_source_capabilities.py | cohesity/management-sdk-python | train | 24 |
79d23678a5920cced12ab90bb570cd4637464ceb | [
"for rec in self:\n if rec.container_id and rec.billing_type:\n if rec.billing_type == 'weight':\n if rec.container_id.weight < rec.weight:\n raise ValidationError('The weight is must be less than or equal to %s' % rec.container_id.weight)",
"for rec in self:\n if rec.contai... | <|body_start_0|>
for rec in self:
if rec.container_id and rec.billing_type:
if rec.billing_type == 'weight':
if rec.container_id.weight < rec.weight:
raise ValidationError('The weight is must be less than or equal to %s' % rec.container_id.... | FreightOrderLine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FreightOrderLine:
def _check_weight(self):
"""Checking the weight of containers"""
<|body_0|>
def _check_volume(self):
"""Checking the volume of containers"""
<|body_1|>
def onchange_price(self):
"""Calculate the weight and volume of container"""... | stack_v2_sparse_classes_36k_train_007802 | 22,800 | no_license | [
{
"docstring": "Checking the weight of containers",
"name": "_check_weight",
"signature": "def _check_weight(self)"
},
{
"docstring": "Checking the volume of containers",
"name": "_check_volume",
"signature": "def _check_volume(self)"
},
{
"docstring": "Calculate the weight and v... | 4 | stack_v2_sparse_classes_30k_train_009461 | Implement the Python class `FreightOrderLine` described below.
Class description:
Implement the FreightOrderLine class.
Method signatures and docstrings:
- def _check_weight(self): Checking the weight of containers
- def _check_volume(self): Checking the volume of containers
- def onchange_price(self): Calculate the ... | Implement the Python class `FreightOrderLine` described below.
Class description:
Implement the FreightOrderLine class.
Method signatures and docstrings:
- def _check_weight(self): Checking the weight of containers
- def _check_volume(self): Checking the volume of containers
- def onchange_price(self): Calculate the ... | 4b1bcb8f17aad44fe9c80a8180eb0128e6bb2c14 | <|skeleton|>
class FreightOrderLine:
def _check_weight(self):
"""Checking the weight of containers"""
<|body_0|>
def _check_volume(self):
"""Checking the volume of containers"""
<|body_1|>
def onchange_price(self):
"""Calculate the weight and volume of container"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FreightOrderLine:
def _check_weight(self):
"""Checking the weight of containers"""
for rec in self:
if rec.container_id and rec.billing_type:
if rec.billing_type == 'weight':
if rec.container_id.weight < rec.weight:
raise ... | the_stack_v2_python_sparse | freight_management_system/model/freight_order.py | CybroOdoo/CybroAddons | train | 209 | |
7c6fb64589b773c34f34333e6508acfe1dec1fd9 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn LifecycleManagementSettings()",
"from ..email_settings import EmailSettings\nfrom ..entity import Entity\nfrom ..email_settings import EmailSettings\nfrom ..entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'emailSettin... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return LifecycleManagementSettings()
<|end_body_0|>
<|body_start_1|>
from ..email_settings import EmailSettings
from ..entity import Entity
from ..email_settings import EmailSettings
... | LifecycleManagementSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifecycleManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LifecycleManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_36k_train_007803 | 2,715 | 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: LifecycleManagementSettings",
"name": "create_from_discriminator_value",
"signature": "def create_from_discr... | 3 | stack_v2_sparse_classes_30k_val_000144 | Implement the Python class `LifecycleManagementSettings` described below.
Class description:
Implement the LifecycleManagementSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LifecycleManagementSettings: Creates a new instance of the appr... | Implement the Python class `LifecycleManagementSettings` described below.
Class description:
Implement the LifecycleManagementSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LifecycleManagementSettings: Creates a new instance of the appr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class LifecycleManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LifecycleManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LifecycleManagementSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> LifecycleManagementSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the ... | the_stack_v2_python_sparse | msgraph/generated/models/identity_governance/lifecycle_management_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e0c26bfdb27fee2eb9eb2b33840c0005e36987d1 | [
"self.batched_inputs = inputs\nproposals_boxes = proposals[PD_BOXES]\nif self.is_training:\n proposals = self.label_and_sample_proposals(inputs, proposals_boxes)\nfeatures_list = [features[f] for f in self.in_features]\nimg_size = get_img_size_from_batched_inputs(inputs)\nif self.is_training:\n pred_instances... | <|body_start_0|>
self.batched_inputs = inputs
proposals_boxes = proposals[PD_BOXES]
if self.is_training:
proposals = self.label_and_sample_proposals(inputs, proposals_boxes)
features_list = [features[f] for f in self.in_features]
img_size = get_img_size_from_batched_i... | RepeatableROIHeads | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RepeatableROIHeads:
def forward(self, inputs, features, proposals: ProposalsData):
"""See :class:`ROIHeads.forward`."""
<|body_0|>
def forward_with_given_boxes(self, inputs, features, instances, img_size):
"""Use the given boxes in `instances` to produce other (non-b... | stack_v2_sparse_classes_36k_train_007804 | 6,801 | permissive | [
{
"docstring": "See :class:`ROIHeads.forward`.",
"name": "forward",
"signature": "def forward(self, inputs, features, proposals: ProposalsData)"
},
{
"docstring": "Use the given boxes in `instances` to produce other (non-box) per-ROI outputs. This is useful for downstream tasks where a box is kn... | 3 | stack_v2_sparse_classes_30k_train_013757 | Implement the Python class `RepeatableROIHeads` described below.
Class description:
Implement the RepeatableROIHeads class.
Method signatures and docstrings:
- def forward(self, inputs, features, proposals: ProposalsData): See :class:`ROIHeads.forward`.
- def forward_with_given_boxes(self, inputs, features, instances... | Implement the Python class `RepeatableROIHeads` described below.
Class description:
Implement the RepeatableROIHeads class.
Method signatures and docstrings:
- def forward(self, inputs, features, proposals: ProposalsData): See :class:`ROIHeads.forward`.
- def forward_with_given_boxes(self, inputs, features, instances... | 8fbf060088816cd1a366d7cbd5dfe1a0e00f8d79 | <|skeleton|>
class RepeatableROIHeads:
def forward(self, inputs, features, proposals: ProposalsData):
"""See :class:`ROIHeads.forward`."""
<|body_0|>
def forward_with_given_boxes(self, inputs, features, instances, img_size):
"""Use the given boxes in `instances` to produce other (non-b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RepeatableROIHeads:
def forward(self, inputs, features, proposals: ProposalsData):
"""See :class:`ROIHeads.forward`."""
self.batched_inputs = inputs
proposals_boxes = proposals[PD_BOXES]
if self.is_training:
proposals = self.label_and_sample_proposals(inputs, propos... | the_stack_v2_python_sparse | object_detection2/modeling/roi_heads/repeatable_roi_heads.py | seantangtao/wml | train | 0 | |
66617fa2583b9f290ef6cc0b8dfbc3de79e900a8 | [
"print('setUp')\nitem_code = 6546\ndescription = 'Couch'\nmarket_price = 600\nrental_price = 10\nmaterial = 'Fabric'\nsize = 'S'\nself.test_furniture_item = furniture_class.Furniture(item_code, description, market_price, rental_price, material, size)\nself.test_furn_dict = self.test_furniture_item.return_as_diction... | <|body_start_0|>
print('setUp')
item_code = 6546
description = 'Couch'
market_price = 600
rental_price = 10
material = 'Fabric'
size = 'S'
self.test_furniture_item = furniture_class.Furniture(item_code, description, market_price, rental_price, material, si... | Perform tests on furniture_class. module. | FurnitureTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FurnitureTests:
"""Perform tests on furniture_class. module."""
def setUp(self):
"""Define set up characteristics of furniture class tests."""
<|body_0|>
def test_furniture_creation(self):
"""Test creation of furniture item."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_007805 | 10,660 | no_license | [
{
"docstring": "Define set up characteristics of furniture class tests.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test creation of furniture item.",
"name": "test_furniture_creation",
"signature": "def test_furniture_creation(self)"
}
] | 2 | null | Implement the Python class `FurnitureTests` described below.
Class description:
Perform tests on furniture_class. module.
Method signatures and docstrings:
- def setUp(self): Define set up characteristics of furniture class tests.
- def test_furniture_creation(self): Test creation of furniture item. | Implement the Python class `FurnitureTests` described below.
Class description:
Perform tests on furniture_class. module.
Method signatures and docstrings:
- def setUp(self): Define set up characteristics of furniture class tests.
- def test_furniture_creation(self): Test creation of furniture item.
<|skeleton|>
cla... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class FurnitureTests:
"""Perform tests on furniture_class. module."""
def setUp(self):
"""Define set up characteristics of furniture class tests."""
<|body_0|>
def test_furniture_creation(self):
"""Test creation of furniture item."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FurnitureTests:
"""Perform tests on furniture_class. module."""
def setUp(self):
"""Define set up characteristics of furniture class tests."""
print('setUp')
item_code = 6546
description = 'Couch'
market_price = 600
rental_price = 10
material = 'Fab... | the_stack_v2_python_sparse | students/Reem_Alqaysi/Lesson_01/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
b639c08c9685a2228306dcc994609bd14ed0fdeb | [
"self.audit_logs = audit_logs\nself.cluster_id = cluster_id\nself.health = health\nself.iops = iops\nself.job_runs = job_runs\nself.protected_objects = protected_objects\nself.protection = protection\nself.recoveries = recoveries\nself.storage_efficiency = storage_efficiency\nself.throughput = throughput",
"if di... | <|body_start_0|>
self.audit_logs = audit_logs
self.cluster_id = cluster_id
self.health = health
self.iops = iops
self.job_runs = job_runs
self.protected_objects = protected_objects
self.protection = protection
self.recoveries = recoveries
self.stor... | Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (IopsTile): IOPs. job_runs (JobRunsTile): Protection Job Runs. protected_objec... | Dashboard | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dashboard:
"""Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (IopsTile): IOPs. job_runs (JobRunsTile):... | stack_v2_sparse_classes_36k_train_007806 | 5,063 | permissive | [
{
"docstring": "Constructor for the Dashboard class",
"name": "__init__",
"signature": "def __init__(self, audit_logs=None, cluster_id=None, health=None, iops=None, job_runs=None, protected_objects=None, protection=None, recoveries=None, storage_efficiency=None, throughput=None)"
},
{
"docstring... | 2 | null | Implement the Python class `Dashboard` described below.
Class description:
Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (I... | Implement the Python class `Dashboard` described below.
Class description:
Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (I... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class Dashboard:
"""Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (IopsTile): IOPs. job_runs (JobRunsTile):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dashboard:
"""Implementation of the 'Dashboard' model. Data shown on Dashboard. Attributes: audit_logs (AuditLogsTile): Audit Logs. cluster_id (long|int): Id of the cluster for which dashboard is given. health (HealthTile): Cluster Health and alerts. iops (IopsTile): IOPs. job_runs (JobRunsTile): Protection J... | the_stack_v2_python_sparse | cohesity_management_sdk/models/dashboard.py | cohesity/management-sdk-python | train | 24 |
9ce3643d6cff710217ed8aacacbd733cc21717ec | [
"super().__init__(cost_multiplier=cost_multiplier)\nself.forbidden_densities_dagger = conjugate_transpose(forbidden_densities)\nself.density_normalization_constants = np.array([density_forbidden_densities.shape[0] for density_forbidden_densities in forbidden_densities])\nself.hilbert_size = forbidden_densities.shap... | <|body_start_0|>
super().__init__(cost_multiplier=cost_multiplier)
self.forbidden_densities_dagger = conjugate_transpose(forbidden_densities)
self.density_normalization_constants = np.array([density_forbidden_densities.shape[0] for density_forbidden_densities in forbidden_densities])
sel... | This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that each evolving density is forbidden from hilbert_size :: int - the dimension of the hi... | ForbidDensities | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForbidDensities:
"""This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that each evolving density is forbidden from hi... | stack_v2_sparse_classes_36k_train_007807 | 4,874 | permissive | [
{
"docstring": "See class definition for arguments not listed here. Args: forbidden_densities :: ndarray - an array where each entry in the first axis is an array of densities that the corresponding evolving density is forbidden from, that is, each evolving density has its own list of forbidden densities system... | 2 | stack_v2_sparse_classes_30k_train_017101 | Implement the Python class `ForbidDensities` described below.
Class description:
This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that eac... | Implement the Python class `ForbidDensities` described below.
Class description:
This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that eac... | 64c1eed34c9a4200a01a7152932482a29a1fd89e | <|skeleton|>
class ForbidDensities:
"""This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that each evolving density is forbidden from hi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForbidDensities:
"""This class encapsulates a cost function that penalizes the occupation of forbidden densities. Fields: cost_multiplier :: float - the wieght factor for this cost density_normalization_constants :: ndarray - the number of densities that each evolving density is forbidden from hilbert_size ::... | the_stack_v2_python_sparse | qoc/standard/costs/forbiddensities.py | jmbaker94/qoc | train | 0 |
63674f287632baa99b4736c3f1e17aaff0840a6a | [
"args = reqparse.RequestParser().add_argument('random', type=bool, location='args').add_argument('school_id', type=int, location='args', required=True, help='学校id不能为空').add_argument('fullinfo', type=bool, location='args', required=False, default=False).parse_args()\nif args.get('fullinfo', False):\n seller = Sho... | <|body_start_0|>
args = reqparse.RequestParser().add_argument('random', type=bool, location='args').add_argument('school_id', type=int, location='args', required=True, help='学校id不能为空').add_argument('fullinfo', type=bool, location='args', required=False, default=False).parse_args()
if args.get('fullinfo'... | Shop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Shop:
def get(self):
"""根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:"""
<|body_0|>
def post(self):
"""添加商家 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = reqparse.RequestParser().add_argument('random', type=bool, location='args').add_argu... | stack_v2_sparse_classes_36k_train_007808 | 14,722 | no_license | [
{
"docstring": "根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "添加商家 :return:",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004164 | Implement the Python class `Shop` described below.
Class description:
Implement the Shop class.
Method signatures and docstrings:
- def get(self): 根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:
- def post(self): 添加商家 :return: | Implement the Python class `Shop` described below.
Class description:
Implement the Shop class.
Method signatures and docstrings:
- def get(self): 根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:
- def post(self): 添加商家 :return:
<|skeleton|>
class Shop:
def get(self):
"""根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:"""
... | 34a2bf4a51cc40a22dd43cb5eb88af7c2f2c5120 | <|skeleton|>
class Shop:
def get(self):
"""根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:"""
<|body_0|>
def post(self):
"""添加商家 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Shop:
def get(self):
"""根据学校id和商店类别返回符合条件的所有商家或一个随机商家 :return:"""
args = reqparse.RequestParser().add_argument('random', type=bool, location='args').add_argument('school_id', type=int, location='args', required=True, help='学校id不能为空').add_argument('fullinfo', type=bool, location='args', require... | the_stack_v2_python_sparse | App/Shop/Controller/ShopResource.py | Vulcanhy/api.grooo-master | train | 0 | |
f624bddda1ed65fc53decffb560ff6f21b9921e2 | [
"super().__init__(config)\nself.vision_model = CLIPVisionModel(config.vision_config)\nself.visual_projection = nn.Linear(config.vision_config.hidden_size, config.projection_dim, bias=False)\nself.concept_embeds = nn.Parameter(torch.ones(17, config.projection_dim), requires_grad=False)\nself.special_care_embeds = nn... | <|body_start_0|>
super().__init__(config)
self.vision_model = CLIPVisionModel(config.vision_config)
self.visual_projection = nn.Linear(config.vision_config.hidden_size, config.projection_dim, bias=False)
self.concept_embeds = nn.Parameter(torch.ones(17, config.projection_dim), requires_g... | StableDiffusionSafetyChecker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StableDiffusionSafetyChecker:
def __init__(self, config: CLIPConfig):
"""check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig): config for transformers clip."""
<|body_0|>
def forward(self, clip_input, images):
"""return ... | stack_v2_sparse_classes_36k_train_007809 | 7,642 | permissive | [
{
"docstring": "check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig): config for transformers clip.",
"name": "__init__",
"signature": "def __init__(self, config: CLIPConfig)"
},
{
"docstring": "return black image if input image has nsfw content. Ar... | 2 | null | Implement the Python class `StableDiffusionSafetyChecker` described below.
Class description:
Implement the StableDiffusionSafetyChecker class.
Method signatures and docstrings:
- def __init__(self, config: CLIPConfig): check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig... | Implement the Python class `StableDiffusionSafetyChecker` described below.
Class description:
Implement the StableDiffusionSafetyChecker class.
Method signatures and docstrings:
- def __init__(self, config: CLIPConfig): check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig... | a382f143c0fd20d227e1e5524831ba26a568190d | <|skeleton|>
class StableDiffusionSafetyChecker:
def __init__(self, config: CLIPConfig):
"""check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig): config for transformers clip."""
<|body_0|>
def forward(self, clip_input, images):
"""return ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StableDiffusionSafetyChecker:
def __init__(self, config: CLIPConfig):
"""check result image for stable diffusion to prevent NSFW content generated. Args: config(CLIPConfig): config for transformers clip."""
super().__init__(config)
self.vision_model = CLIPVisionModel(config.vision_conf... | the_stack_v2_python_sparse | mmagic/models/editors/stable_diffusion/clip_wrapper.py | open-mmlab/mmagic | train | 1,370 | |
1788ca7326b0e64b945734d3c535aa35f5f0b8bb | [
"self.copy_tasks = copy_tasks\nself.job_id = job_id\nself.job_name = job_name\nself.job_run_id = job_run_id\nself.job_run_start_time_usecs = job_run_start_time_usecs\nself.last_run_end_time_usecs = last_run_end_time_usecs\nself.last_run_start_time_usecs = last_run_start_time_usecs\nself.message = message\nself.num_... | <|body_start_0|>
self.copy_tasks = copy_tasks
self.job_id = job_id
self.job_name = job_name
self.job_run_id = job_run_id
self.job_run_start_time_usecs = job_run_start_time_usecs
self.last_run_end_time_usecs = last_run_end_time_usecs
self.last_run_start_time_usecs ... | Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapshot Copy Tasks. Specifies a list of copy tasks (such as replication and archival tasks). job_id (long|in... | ProtectionSourceSnapshotInformation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectionSourceSnapshotInformation:
"""Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapshot Copy Tasks. Specifies a list of copy ... | stack_v2_sparse_classes_36k_train_007810 | 7,225 | permissive | [
{
"docstring": "Constructor for the ProtectionSourceSnapshotInformation class",
"name": "__init__",
"signature": "def __init__(self, copy_tasks=None, job_id=None, job_name=None, job_run_id=None, job_run_start_time_usecs=None, last_run_end_time_usecs=None, last_run_start_time_usecs=None, message=None, nu... | 2 | stack_v2_sparse_classes_30k_train_015020 | Implement the Python class `ProtectionSourceSnapshotInformation` described below.
Class description:
Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapsho... | Implement the Python class `ProtectionSourceSnapshotInformation` described below.
Class description:
Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapsho... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ProtectionSourceSnapshotInformation:
"""Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapshot Copy Tasks. Specifies a list of copy ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProtectionSourceSnapshotInformation:
"""Implementation of the 'ProtectionSourceSnapshotInformation' model. Specifies details about a Snapshot that backups up a leaf Protection Source Object. Attributes: copy_tasks (list of SnapshotCopyTask): Array of Snapshot Copy Tasks. Specifies a list of copy tasks (such a... | the_stack_v2_python_sparse | cohesity_management_sdk/models/protection_source_snapshot_information.py | cohesity/management-sdk-python | train | 24 |
80b464c07b5c9bc4c87f05365b1e5a3f807fe066 | [
"if s is None or len(s) == 0:\n return 0\nif len(s) == 1:\n return ord(s[0]) - ord('A') + 1\nreturn self.title_to_number_recursive(s[0]) * pow(26, len(s) - 1) + self.title_to_number_recursive(s[1:])",
"if s is None or len(s) == 0:\n return 0\nl = len(s)\nret = 0\nfor c in s:\n d = ord(c) - ord('A') + ... | <|body_start_0|>
if s is None or len(s) == 0:
return 0
if len(s) == 1:
return ord(s[0]) - ord('A') + 1
return self.title_to_number_recursive(s[0]) * pow(26, len(s) - 1) + self.title_to_number_recursive(s[1:])
<|end_body_0|>
<|body_start_1|>
if s is None or len(s)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def title_to_number_recursive(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def title_to_number_iterative(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if s is None or len(s) == 0:
... | stack_v2_sparse_classes_36k_train_007811 | 996 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "title_to_number_recursive",
"signature": "def title_to_number_recursive(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "title_to_number_iterative",
"signature": "def title_to_number_iterative(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def title_to_number_recursive(self, s): :type s: str :rtype: int
- def title_to_number_iterative(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def title_to_number_recursive(self, s): :type s: str :rtype: int
- def title_to_number_iterative(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def title_t... | b7b5d15e6a3c9ab11916550f0ed40ed6a9a2901e | <|skeleton|>
class Solution:
def title_to_number_recursive(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def title_to_number_iterative(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def title_to_number_recursive(self, s):
""":type s: str :rtype: int"""
if s is None or len(s) == 0:
return 0
if len(s) == 1:
return ord(s[0]) - ord('A') + 1
return self.title_to_number_recursive(s[0]) * pow(26, len(s) - 1) + self.title_to_numbe... | the_stack_v2_python_sparse | src/excel_sheet_column_number.py | fifa007/Leetcode | train | 0 | |
6af940cc2225fd3a2fefcb2d105878856acb5e03 | [
"tmp = []\nfor a in arr:\n if a == 0:\n tmp.append(0)\n tmp.append(0)\n else:\n tmp.append(a)\n if len(tmp) == len(arr):\n break\nfor i in range(len(arr)):\n arr[i] = tmp[i]\nreturn",
"possible_dups = 0\nlength_ = len(arr) - 1\nfor left in range(length_ + 1):\n if left >... | <|body_start_0|>
tmp = []
for a in arr:
if a == 0:
tmp.append(0)
tmp.append(0)
else:
tmp.append(a)
if len(tmp) == len(arr):
break
for i in range(len(arr)):
arr[i] = tmp[i]
retu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def duplicateZeros(self, arr: List[int]) -> None:
"""Do not return anything, modify arr in-place instead."""
<|body_0|>
def duplicateZeros2(self, arr: List[int]) -> None:
"""Do not return anything, modify arr in-place instead."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k_train_007812 | 2,706 | no_license | [
{
"docstring": "Do not return anything, modify arr in-place instead.",
"name": "duplicateZeros",
"signature": "def duplicateZeros(self, arr: List[int]) -> None"
},
{
"docstring": "Do not return anything, modify arr in-place instead.",
"name": "duplicateZeros2",
"signature": "def duplicat... | 2 | stack_v2_sparse_classes_30k_train_016876 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def duplicateZeros(self, arr: List[int]) -> None: Do not return anything, modify arr in-place instead.
- def duplicateZeros2(self, arr: List[int]) -> None: Do not return anything... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def duplicateZeros(self, arr: List[int]) -> None: Do not return anything, modify arr in-place instead.
- def duplicateZeros2(self, arr: List[int]) -> None: Do not return anything... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def duplicateZeros(self, arr: List[int]) -> None:
"""Do not return anything, modify arr in-place instead."""
<|body_0|>
def duplicateZeros2(self, arr: List[int]) -> None:
"""Do not return anything, modify arr in-place instead."""
<|body_1|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def duplicateZeros(self, arr: List[int]) -> None:
"""Do not return anything, modify arr in-place instead."""
tmp = []
for a in arr:
if a == 0:
tmp.append(0)
tmp.append(0)
else:
tmp.append(a)
i... | the_stack_v2_python_sparse | D/DuplicateZeros.py | bssrdf/pyleet | train | 2 | |
26841a961821eec14490ca74ee9cdf7d4d9b0d83 | [
"random.shuffle(nums)\nmid_index = len(nums) // 2\nself.quick_select(nums, mid_index)\nmid = nums[mid_index]\ni = 0\nj = 0\nk = len(nums) - 1\nwhile j < k:\n if nums[j] > mid:\n nums[j], nums[k] = (nums[k], nums[j])\n k -= 1\n elif nums[j] < mid:\n nums[i], nums[j] = (nums[j], nums[i])\n ... | <|body_start_0|>
random.shuffle(nums)
mid_index = len(nums) // 2
self.quick_select(nums, mid_index)
mid = nums[mid_index]
i = 0
j = 0
k = len(nums) - 1
while j < k:
if nums[j] > mid:
nums[j], nums[k] = (nums[k], nums[j])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
"""Do not return anything, modify nums in-place instead. Args: nums: list[int]"""
<|body_0|>
def quick_select(self, nums, target):
"""Args: nums: list[int target: int"""
<|body_1|>
def partition(self, nums, left, rig... | stack_v2_sparse_classes_36k_train_007813 | 2,730 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead. Args: nums: list[int]",
"name": "wiggleSort",
"signature": "def wiggleSort(self, nums)"
},
{
"docstring": "Args: nums: list[int target: int",
"name": "quick_select",
"signature": "def quick_select(self, nums, target)"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): Do not return anything, modify nums in-place instead. Args: nums: list[int]
- def quick_select(self, nums, target): Args: nums: list[int target: int
-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleSort(self, nums): Do not return anything, modify nums in-place instead. Args: nums: list[int]
- def quick_select(self, nums, target): Args: nums: list[int target: int
-... | 101bce2fac8b188a4eb2f5e017293d21ad0ecb21 | <|skeleton|>
class Solution:
def wiggleSort(self, nums):
"""Do not return anything, modify nums in-place instead. Args: nums: list[int]"""
<|body_0|>
def quick_select(self, nums, target):
"""Args: nums: list[int target: int"""
<|body_1|>
def partition(self, nums, left, rig... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wiggleSort(self, nums):
"""Do not return anything, modify nums in-place instead. Args: nums: list[int]"""
random.shuffle(nums)
mid_index = len(nums) // 2
self.quick_select(nums, mid_index)
mid = nums[mid_index]
i = 0
j = 0
k = len(n... | the_stack_v2_python_sparse | code/324. 摆动排序 II.py | AiZhanghan/Leetcode | train | 0 | |
545c15a4b6637af0e1342282047d0e3d77d6de37 | [
"if data is not None:\n self.batch_size = len(data)\n self.dataset = dataset\n self.train = train\n for name, field in dataset.fields.items():\n if field is not None:\n setattr(self, name, field.numericalize(field.pad((x.__dict__[name] for x in data)), device=device, train=train))",
... | <|body_start_0|>
if data is not None:
self.batch_size = len(data)
self.dataset = dataset
self.train = train
for name, field in dataset.fields.items():
if field is not None:
setattr(self, name, field.numericalize(field.pad((x.__d... | Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the batch is from a training set. Also stores the Variable for each column in ... | Batch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Batch:
"""Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the batch is from a training set. Also stores... | stack_v2_sparse_classes_36k_train_007814 | 25,729 | permissive | [
{
"docstring": "Create a Batch from a list of examples.",
"name": "__init__",
"signature": "def __init__(self, data=None, dataset=None, device=None, train=True)"
},
{
"docstring": "Create a Batch directly from a number of Variables.",
"name": "fromvars",
"signature": "def fromvars(cls, d... | 2 | stack_v2_sparse_classes_30k_train_008030 | Implement the Python class `Batch` described below.
Class description:
Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the ba... | Implement the Python class `Batch` described below.
Class description:
Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the ba... | 5de55545049fa05b2f47cd7355362fd9f755f19f | <|skeleton|>
class Batch:
"""Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the batch is from a training set. Also stores... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Batch:
"""Defines a batch of examples along with its Fields. Attributes: batch_size: Number of examples in the batch. dataset: A reference to the dataset object the examples come from (which itself contains the dataset's Field objects). train: Whether the batch is from a training set. Also stores the Variable... | the_stack_v2_python_sparse | cnn_text_classification/torchtext/data.py | eriche2016/pytorch_projects_misc | train | 5 |
43831fef13a3936df5194fad1959be2b81879e71 | [
"super(Htaccess, self).__init__(atts)\nself.sections = []\nif 'sections' in atts:\n for sfile in atts['sections']:\n section = HtaccessSection(sfile)\n self.sections.append(section)\nif not self.exists() or not prompt('Use existing htaccess file?'):\n for section in self.sections:\n self.... | <|body_start_0|>
super(Htaccess, self).__init__(atts)
self.sections = []
if 'sections' in atts:
for sfile in atts['sections']:
section = HtaccessSection(sfile)
self.sections.append(section)
if not self.exists() or not prompt('Use existing htacc... | A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment. | Htaccess | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Htaccess:
"""A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment."""
def __init__(self, atts):
"""Initialize an Htaccess class."""
<|body_0|>
def verify(self, repair=False):
"""Verifies the htaccess file and contents... | stack_v2_sparse_classes_36k_train_007815 | 2,521 | permissive | [
{
"docstring": "Initialize an Htaccess class.",
"name": "__init__",
"signature": "def __init__(self, atts)"
},
{
"docstring": "Verifies the htaccess file and contents. This checks to make sure sections exist. It does",
"name": "verify",
"signature": "def verify(self, repair=False)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015729 | Implement the Python class `Htaccess` described below.
Class description:
A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment.
Method signatures and docstrings:
- def __init__(self, atts): Initialize an Htaccess class.
- def verify(self, repair=False): Verifies the htacc... | Implement the Python class `Htaccess` described below.
Class description:
A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment.
Method signatures and docstrings:
- def __init__(self, atts): Initialize an Htaccess class.
- def verify(self, repair=False): Verifies the htacc... | 5a537ab6865fcfb43a253cdb8cf2397a53d940a7 | <|skeleton|>
class Htaccess:
"""A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment."""
def __init__(self, atts):
"""Initialize an Htaccess class."""
<|body_0|>
def verify(self, repair=False):
"""Verifies the htaccess file and contents... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Htaccess:
"""A class that describes an Apache htaccess file. This is primarily a wrapper for htaccess managment."""
def __init__(self, atts):
"""Initialize an Htaccess class."""
super(Htaccess, self).__init__(atts)
self.sections = []
if 'sections' in atts:
for ... | the_stack_v2_python_sparse | ww/htaccess.py | hbradleyiii/ww | train | 0 |
401420b047544e8b038f10f0935649c278b479b5 | [
"self._client = client\nself._is_time_of_use = is_time_of_use\nsuper().__init__(hass, LOGGER, name=DOMAIN, update_interval=MIN_TIME_BETWEEN_UPDATES)",
"LOGGER.debug('async_update_data enter')\nphx_time_zone = dt_util.get_time_zone(PHOENIX_TIME_ZONE)\nend_date = dt_util.now(phx_time_zone)\nstart_date = end_date - ... | <|body_start_0|>
self._client = client
self._is_time_of_use = is_time_of_use
super().__init__(hass, LOGGER, name=DOMAIN, update_interval=MIN_TIME_BETWEEN_UPDATES)
<|end_body_0|>
<|body_start_1|>
LOGGER.debug('async_update_data enter')
phx_time_zone = dt_util.get_time_zone(PHOENI... | A srp_energy Data Update Coordinator. | SRPEnergyDataUpdateCoordinator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SRPEnergyDataUpdateCoordinator:
"""A srp_energy Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None:
"""Initialize the srp_energy data coordinator."""
<|body_0|>
async def _async_update_data(self) -> ... | stack_v2_sparse_classes_36k_train_007816 | 2,450 | permissive | [
{
"docstring": "Initialize the srp_energy data coordinator.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None"
},
{
"docstring": "Fetch data from API endpoint. This is the place to pre-process the data to lookup tab... | 2 | null | Implement the Python class `SRPEnergyDataUpdateCoordinator` described below.
Class description:
A srp_energy Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None: Initialize the srp_energy data coordinator.
- async ... | Implement the Python class `SRPEnergyDataUpdateCoordinator` described below.
Class description:
A srp_energy Data Update Coordinator.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None: Initialize the srp_energy data coordinator.
- async ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class SRPEnergyDataUpdateCoordinator:
"""A srp_energy Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None:
"""Initialize the srp_energy data coordinator."""
<|body_0|>
async def _async_update_data(self) -> ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SRPEnergyDataUpdateCoordinator:
"""A srp_energy Data Update Coordinator."""
def __init__(self, hass: HomeAssistant, client: SrpEnergyClient, is_time_of_use: bool) -> None:
"""Initialize the srp_energy data coordinator."""
self._client = client
self._is_time_of_use = is_time_of_use... | the_stack_v2_python_sparse | homeassistant/components/srp_energy/coordinator.py | home-assistant/core | train | 35,501 |
ff93229ff67b4803028dd06366636ee8ee202387 | [
"andinopy_logger.debug('Terminal starting initialization')\nself.andinoio_instance = andinoio_instance if andinoio_instance is not None else andinoio.andinoio()\nself.display_instance = display_instance if display_instance is not None else display()\nself.rfid_keyboard_instance = rfid_keyboard_instance if rfid_keyb... | <|body_start_0|>
andinopy_logger.debug('Terminal starting initialization')
self.andinoio_instance = andinoio_instance if andinoio_instance is not None else andinoio.andinoio()
self.display_instance = display_instance if display_instance is not None else display()
self.rfid_keyboard_insta... | terminal | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class terminal:
def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None):
"""Create a new Terminal instance Can be passed preconfigured handles"""
<|body_0|>
def start(self):
"""Start the ... | stack_v2_sparse_classes_36k_train_007817 | 8,903 | permissive | [
{
"docstring": "Create a new Terminal instance Can be passed preconfigured handles",
"name": "__init__",
"signature": "def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None)"
},
{
"docstring": "Start the termi... | 3 | stack_v2_sparse_classes_30k_train_014927 | Implement the Python class `terminal` described below.
Class description:
Implement the terminal class.
Method signatures and docstrings:
- def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None): Create a new Terminal instance Can ... | Implement the Python class `terminal` described below.
Class description:
Implement the terminal class.
Method signatures and docstrings:
- def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None): Create a new Terminal instance Can ... | 27f7246933c40b5fca4db5cb0590544d80555d51 | <|skeleton|>
class terminal:
def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None):
"""Create a new Terminal instance Can be passed preconfigured handles"""
<|body_0|>
def start(self):
"""Start the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class terminal:
def __init__(self, andinoio_instance: andinoio.andinoio=None, display_instance: 'display'=None, rfid_keyboard_instance: 'rfid_keyboard'=None):
"""Create a new Terminal instance Can be passed preconfigured handles"""
andinopy_logger.debug('Terminal starting initialization')
se... | the_stack_v2_python_sparse | Andino-Common/src/andinopy/build/lib/andinopy/terminal.py | matt2005/Andino | train | 0 | |
1ffa5814cc5ee2da8d735c79e1674aef1aecfad4 | [
"host = 'foo.com:1234'\npath_info = '/_ah/login'\ncookie_dict = {}\naction = ''\nset_email = ''\nset_admin = False\ncontinue_url = ''\nstatus, location, set_cookie, content_type = self._run_test(host, path_info, cookie_dict, action, set_email, set_admin, continue_url)\nself.assertEqual(302, status)\nself.assertFals... | <|body_start_0|>
host = 'foo.com:1234'
path_info = '/_ah/login'
cookie_dict = {}
action = ''
set_email = ''
set_admin = False
continue_url = ''
status, location, set_cookie, content_type = self._run_test(host, path_info, cookie_dict, action, set_email, set... | Tests the various ways of invoking the login page. | LoginPageTest | [
"Apache-2.0",
"LGPL-2.1-or-later",
"BSD-3-Clause",
"MIT",
"GPL-2.0-or-later",
"MPL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginPageTest:
"""Tests the various ways of invoking the login page."""
def test_no_params(self):
"""Tests just accessing the login URL with no params."""
<|body_0|>
def test_login(self):
"""Tests when setting the user info with and without continue URL."""
... | stack_v2_sparse_classes_36k_train_007818 | 12,436 | permissive | [
{
"docstring": "Tests just accessing the login URL with no params.",
"name": "test_no_params",
"signature": "def test_no_params(self)"
},
{
"docstring": "Tests when setting the user info with and without continue URL.",
"name": "test_login",
"signature": "def test_login(self)"
},
{
... | 5 | stack_v2_sparse_classes_30k_train_006802 | Implement the Python class `LoginPageTest` described below.
Class description:
Tests the various ways of invoking the login page.
Method signatures and docstrings:
- def test_no_params(self): Tests just accessing the login URL with no params.
- def test_login(self): Tests when setting the user info with and without c... | Implement the Python class `LoginPageTest` described below.
Class description:
Tests the various ways of invoking the login page.
Method signatures and docstrings:
- def test_no_params(self): Tests just accessing the login URL with no params.
- def test_login(self): Tests when setting the user info with and without c... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class LoginPageTest:
"""Tests the various ways of invoking the login page."""
def test_no_params(self):
"""Tests just accessing the login URL with no params."""
<|body_0|>
def test_login(self):
"""Tests when setting the user info with and without continue URL."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginPageTest:
"""Tests the various ways of invoking the login page."""
def test_no_params(self):
"""Tests just accessing the login URL with no params."""
host = 'foo.com:1234'
path_info = '/_ah/login'
cookie_dict = {}
action = ''
set_email = ''
set... | the_stack_v2_python_sparse | AppServer/google/appengine/tools/devappserver2/login_test.py | obino/appscale | train | 1 |
0dc0e9f25f358e1a1207b99e048f56e41526df62 | [
"super().__init__()\nself.word_embedding_dim = word_embedding_dim\nself.char_embedding_dim = char_embedding_dim\nself.word_lstm_size = word_lstm_size\nself.char_lstm_size = char_lstm_size\nself.fc_dim = fc_dim\nself.dropout = dropout\nself.embedding = None\nself.use_char = True\nself.use_crf = True\nself.batch_size... | <|body_start_0|>
super().__init__()
self.word_embedding_dim = word_embedding_dim
self.char_embedding_dim = char_embedding_dim
self.word_lstm_size = word_lstm_size
self.char_lstm_size = char_lstm_size
self.fc_dim = fc_dim
self.dropout = dropout
self.embeddi... | BiLstmCrfNER | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiLstmCrfNER:
def __init__(self, word_embedding_dim=100, char_embedding_dim=25, word_lstm_size=100, char_lstm_size=25, fc_dim=100, dropout=0.5, embeddings=None, use_char=True, use_crf=True, batch_size=16, learning_rate=0.001, max_iter=10):
"""Construct a BiLSTM-CRF NER model. Model is au... | stack_v2_sparse_classes_36k_train_007819 | 7,645 | permissive | [
{
"docstring": "Construct a BiLSTM-CRF NER model. Model is augmented with character level embeddings as well as word embeddings by default. Implementation is provided by the Anago project. Parameters ---------- word_embedding_dim : int, optional, default 100 word embedding dimensions. char_embedding_dim : int, ... | 5 | stack_v2_sparse_classes_30k_train_003520 | Implement the Python class `BiLstmCrfNER` described below.
Class description:
Implement the BiLstmCrfNER class.
Method signatures and docstrings:
- def __init__(self, word_embedding_dim=100, char_embedding_dim=25, word_lstm_size=100, char_lstm_size=25, fc_dim=100, dropout=0.5, embeddings=None, use_char=True, use_crf=... | Implement the Python class `BiLstmCrfNER` described below.
Class description:
Implement the BiLstmCrfNER class.
Method signatures and docstrings:
- def __init__(self, word_embedding_dim=100, char_embedding_dim=25, word_lstm_size=100, char_lstm_size=25, fc_dim=100, dropout=0.5, embeddings=None, use_char=True, use_crf=... | 366420b2ec57bf790562de62a79f4973cbd6b3ed | <|skeleton|>
class BiLstmCrfNER:
def __init__(self, word_embedding_dim=100, char_embedding_dim=25, word_lstm_size=100, char_lstm_size=25, fc_dim=100, dropout=0.5, embeddings=None, use_char=True, use_crf=True, batch_size=16, learning_rate=0.001, max_iter=10):
"""Construct a BiLSTM-CRF NER model. Model is au... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BiLstmCrfNER:
def __init__(self, word_embedding_dim=100, char_embedding_dim=25, word_lstm_size=100, char_lstm_size=25, fc_dim=100, dropout=0.5, embeddings=None, use_char=True, use_crf=True, batch_size=16, learning_rate=0.001, max_iter=10):
"""Construct a BiLSTM-CRF NER model. Model is augmented with c... | the_stack_v2_python_sparse | nerds/models/bilstm.py | fyuval/nerds | train | 0 | |
f368e03cbb16215c38e9139fcfb9a5589cf5c7c9 | [
"self.mvid = mvid\nself.logdir = '{}/{}'.format(settings['log_dir'], self.mvid)\nself.mvm = get_model_version(mvid)\nif self.mvm.empty:\n raise RuntimeError(f'Model version for {mvid} is empty.')\nself.run_cv = self.mvm.cross_validate_id.values[0] == 1\nself.meid = self.mvm.modelable_entity_id.values[0]\nif self... | <|body_start_0|>
self.mvid = mvid
self.logdir = '{}/{}'.format(settings['log_dir'], self.mvid)
self.mvm = get_model_version(mvid)
if self.mvm.empty:
raise RuntimeError(f'Model version for {mvid} is empty.')
self.run_cv = self.mvm.cross_validate_id.values[0] == 1
... | Driver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Driver:
def __init__(self, mvid):
"""Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job"""
<|body_0|>
def build_jobmon_workflow(self, identifier=None, extra_arguments=None):
... | stack_v2_sparse_classes_36k_train_007820 | 5,762 | no_license | [
{
"docstring": "Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job",
"name": "__init__",
"signature": "def __init__(self, mvid)"
},
{
"docstring": "Returns jobmon workflow that represents cascade j... | 2 | null | Implement the Python class `Driver` described below.
Class description:
Implement the Driver class.
Method signatures and docstrings:
- def __init__(self, mvid): Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job
- def ... | Implement the Python class `Driver` described below.
Class description:
Implement the Driver class.
Method signatures and docstrings:
- def __init__(self, mvid): Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job
- def ... | 746ea5fb76a9c049c37a8c15aa089c041a90a6d5 | <|skeleton|>
class Driver:
def __init__(self, mvid):
"""Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job"""
<|body_0|>
def build_jobmon_workflow(self, identifier=None, extra_arguments=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Driver:
def __init__(self, mvid):
"""Makes directories in preparation for launching cascade. Then launches jobmon to manage rest of cascade. Args: mvid (int): model version of dismod job"""
self.mvid = mvid
self.logdir = '{}/{}'.format(settings['log_dir'], self.mvid)
self.mvm =... | the_stack_v2_python_sparse | gbd_2019/shared_code/central_comp/nonfatal/dismod/driver.py | Nermin-Ghith/ihme-modeling | train | 0 | |
17b5711bb87a1f078f5827530eae3afb8a4b9077 | [
"self._property1 = property1\nself._operation = operation\nself._property2 = property2",
"name = path if path != None else 'value'\nvalue1 = ObjectReader.get_property(value, self._property1)\nvalue2 = ObjectReader.get_property(value, self._property2)\nif not ObjectComparator.compare(value1, self._operation, value... | <|body_start_0|>
self._property1 = property1
self._operation = operation
self._property2 = property2
<|end_body_0|>
<|body_start_1|>
name = path if path != None else 'value'
value1 = ObjectReader.get_property(value, self._property1)
value2 = ObjectReader.get_property(val... | Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ field1: 1, field2: 1 }) // Result: field1 shall not be equal to field2 schema.validate({}) //... | PropertiesComparisonRule | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropertiesComparisonRule:
"""Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ field1: 1, field2: 1 }) // Result: field1... | stack_v2_sparse_classes_36k_train_007821 | 2,738 | permissive | [
{
"docstring": "Creates a new validation rule and sets its arguments. :param property1: a name of the first property to compare. :param operation: a comparison operation: \"==\" (\"=\", \"EQ\"), \"!= \" (\"<>\", \"NE\"); \"<\"/\">\" (\"LT\"/\"GT\"), \"<=\"/\">=\" (\"LE\"/\"GE\"); \"LIKE\". :param property2: a n... | 2 | stack_v2_sparse_classes_30k_val_000730 | Implement the Python class `PropertiesComparisonRule` described below.
Class description:
Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ fi... | Implement the Python class `PropertiesComparisonRule` described below.
Class description:
Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ fi... | 4be674228adcf447c1579cbeb45b7aee89d4322c | <|skeleton|>
class PropertiesComparisonRule:
"""Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ field1: 1, field2: 1 }) // Result: field1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PropertiesComparisonRule:
"""Validation rule that compares two object properties. Example: schema = ObjectSchema().with_rule(PropertyComparisonRule("field1", "NE", "field2")) schema.validate({ field1: 1, field2: 2 }) // Result: no errors schema.validate({ field1: 1, field2: 1 }) // Result: field1 shall not be... | the_stack_v2_python_sparse | pip_services3_commons/validate/PropertiesComparisonRule.py | banalna/pip-services3-commons-python | train | 0 |
e07859eaa2012b4bdf1ade7e5c92331cf6522ffc | [
"data = self.get_json()\nschema = Telescope.__schema__()\ntry:\n telescope = schema.load(data)\nexcept ValidationError as e:\n return self.error(f'Invalid/missing parameters: {e.normalized_messages()}')\nDBSession().add(telescope)\nself.verify_and_commit()\nself.push_all(action='skyportal/REFRESH_TELESCOPES')... | <|body_start_0|>
data = self.get_json()
schema = Telescope.__schema__()
try:
telescope = schema.load(data)
except ValidationError as e:
return self.error(f'Invalid/missing parameters: {e.normalized_messages()}')
DBSession().add(telescope)
self.veri... | TelescopeHandler | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TelescopeHandler:
def post(self):
"""--- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: type:... | stack_v2_sparse_classes_36k_train_007822 | 5,371 | permissive | [
{
"docstring": "--- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: type: object properties: id: type: integer descrip... | 4 | null | Implement the Python class `TelescopeHandler` described below.
Class description:
Implement the TelescopeHandler class.
Method signatures and docstrings:
- def post(self): --- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: appli... | Implement the Python class `TelescopeHandler` described below.
Class description:
Implement the TelescopeHandler class.
Method signatures and docstrings:
- def post(self): --- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: appli... | 2433d5ae0b2f41faac3c76ed4ae8d9a4da5522fb | <|skeleton|>
class TelescopeHandler:
def post(self):
"""--- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: type:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TelescopeHandler:
def post(self):
"""--- description: Create telescopes tags: - telescopes requestBody: content: application/json: schema: TelescopeNoID responses: 200: content: application/json: schema: allOf: - $ref: '#/components/schemas/Success' - type: object properties: data: type: object proper... | the_stack_v2_python_sparse | skyportal/handlers/api/telescope.py | dmitryduev/skyportal | train | 1 | |
4e9a3fd6f67c4dd82575ad113a453549f56b4d93 | [
"if len(prices) < 2:\n return 0\nminPrice = prices[0]\nmaxPrice = prices[0]\nresArr = list()\nfor i in range(1, len(prices)):\n if prices[i] < minPrice:\n minPrice = prices[i]\n maxPrice = prices[i]\n elif prices[i] > maxPrice:\n maxPrice = prices[i]\n resArr.append(maxPrice - m... | <|body_start_0|>
if len(prices) < 2:
return 0
minPrice = prices[0]
maxPrice = prices[0]
resArr = list()
for i in range(1, len(prices)):
if prices[i] < minPrice:
minPrice = prices[i]
maxPrice = prices[i]
elif pric... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit2(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(prices) < 2:
return ... | stack_v2_sparse_classes_36k_train_007823 | 960 | permissive | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit1",
"signature": "def maxProfit1(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit2",
"signature": "def maxProfit2(self, prices)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020884 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit2(self, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit1(self, prices): :type prices: List[int] :rtype: int
- def maxProfit2(self, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxPr... | 03876232521a20d32f8fa4e7d6d19cf208739a79 | <|skeleton|>
class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit2(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit1(self, prices):
""":type prices: List[int] :rtype: int"""
if len(prices) < 2:
return 0
minPrice = prices[0]
maxPrice = prices[0]
resArr = list()
for i in range(1, len(prices)):
if prices[i] < minPrice:
... | the_stack_v2_python_sparse | Python/best-time-to-buy-and-sell-stock.py | coolryze/LeetCode | train | 4 | |
403b4b9ba23ba10354f7848c7a985f2d35c59b54 | [
"selector = '#ae-appbar-version-id option[selected=\"selected\"]'\nversion_element, = self.doc.cssselect(selector)\nreturn version_element.text.strip()",
"details = []\nselector = '#ae-instances-details-table tbody tr'\nfor element in self.doc.cssselect(selector):\n children = list(element)\n assert len(chi... | <|body_start_0|>
selector = '#ae-appbar-version-id option[selected="selected"]'
version_element, = self.doc.cssselect(selector)
return version_element.text.strip()
<|end_body_0|>
<|body_start_1|>
details = []
selector = '#ae-instances-details-table tbody tr'
for element ... | An API for the contents of /instances as structured data. | Instances | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Instances:
"""An API for the contents of /instances as structured data."""
def version(self):
"""The app version that owns these instances."""
<|body_0|>
def raw_detail_dicts(self):
"""Performance statistics specific to each instance. Returns: A list of dicts wit... | stack_v2_sparse_classes_36k_train_007824 | 15,505 | no_license | [
{
"docstring": "The app version that owns these instances.",
"name": "version",
"signature": "def version(self)"
},
{
"docstring": "Performance statistics specific to each instance. Returns: A list of dicts with (as of App Engine 1.7.2) fields like this: [{'instance_id': '01c61b117c08b2b562c94f2... | 2 | stack_v2_sparse_classes_30k_train_004662 | Implement the Python class `Instances` described below.
Class description:
An API for the contents of /instances as structured data.
Method signatures and docstrings:
- def version(self): The app version that owns these instances.
- def raw_detail_dicts(self): Performance statistics specific to each instance. Returns... | Implement the Python class `Instances` described below.
Class description:
An API for the contents of /instances as structured data.
Method signatures and docstrings:
- def version(self): The app version that owns these instances.
- def raw_detail_dicts(self): Performance statistics specific to each instance. Returns... | c4ad2ad67b497ce411a9e5d6d6db407ee304491f | <|skeleton|>
class Instances:
"""An API for the contents of /instances as structured data."""
def version(self):
"""The app version that owns these instances."""
<|body_0|>
def raw_detail_dicts(self):
"""Performance statistics specific to each instance. Returns: A list of dicts wit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Instances:
"""An API for the contents of /instances as structured data."""
def version(self):
"""The app version that owns these instances."""
selector = '#ae-appbar-version-id option[selected="selected"]'
version_element, = self.doc.cssselect(selector)
return version_elem... | the_stack_v2_python_sparse | src/gae_dashboard/parsers.py | summer-liu/analytics | train | 1 |
aef499a01cb90d14f70e7b19f8501bddbce1854c | [
"n = len(nums)\nlo, hi = (0, n - 1)\nwhile lo < hi and nums[lo] <= nums[lo + 1]:\n lo += 1\nwhile lo < hi and nums[hi - 1] <= nums[hi]:\n hi -= 1\nif hi <= lo:\n return 0\nmini = float('inf')\nmaxa = -float('inf')\nfor i in range(lo, hi + 1):\n mini = min(mini, nums[i])\n maxa = max(maxa, nums[i])\nw... | <|body_start_0|>
n = len(nums)
lo, hi = (0, n - 1)
while lo < hi and nums[lo] <= nums[lo + 1]:
lo += 1
while lo < hi and nums[hi - 1] <= nums[hi]:
hi -= 1
if hi <= lo:
return 0
mini = float('inf')
maxa = -float('inf')
fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findUnsortedSubarray(self, nums: List[int]) -> int:
"""Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may over-include, consider 1 2 5 9 4 6 ... need to shrink from 1 2 5 9 to 1 2 according to min value... | stack_v2_sparse_classes_36k_train_007825 | 2,142 | no_license | [
{
"docstring": "Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may over-include, consider 1 2 5 9 4 6 ... need to shrink from 1 2 5 9 to 1 2 according to min value nums[lo - 1] <= min && max <= nums[hi + 1]",
"name": "findUnsortedSubarr... | 2 | stack_v2_sparse_classes_30k_train_010643 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findUnsortedSubarray(self, nums: List[int]) -> int: Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findUnsortedSubarray(self, nums: List[int]) -> int: Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may... | 929dde1723fb2f54870c8a9badc80fc23e8400d3 | <|skeleton|>
class Solution:
def findUnsortedSubarray(self, nums: List[int]) -> int:
"""Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may over-include, consider 1 2 5 9 4 6 ... need to shrink from 1 2 5 9 to 1 2 according to min value... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findUnsortedSubarray(self, nums: List[int]) -> int:
"""Sorted at both ends Then search for the two ends by nums[i+1] > nums[i] on the left side (right side similar) Problem: may over-include, consider 1 2 5 9 4 6 ... need to shrink from 1 2 5 9 to 1 2 according to min value nums[lo - 1] ... | the_stack_v2_python_sparse | _algorithms_challenges/leetcode/LeetCode/581 Shortest Unsorted Continuous Subarray.py | syurskyi/Algorithms_and_Data_Structure | train | 4 | |
cac3ed1bdfb11ffb1e90e27ab15ceb71a7e99c8b | [
"Galkin.__init__(self, kwargs_model=kwargs_model, kwargs_aperture=kwargs_aperture, kwargs_psf=kwargs_psf, kwargs_cosmo=kwargs_cosmo, kwargs_numerics=kwargs_numerics, analytic_kinematics=analytic_kinematics)\nif not self.aperture_type == 'IFU_shells':\n raise ValueError('GalkinShells is not supported with apertur... | <|body_start_0|>
Galkin.__init__(self, kwargs_model=kwargs_model, kwargs_aperture=kwargs_aperture, kwargs_psf=kwargs_psf, kwargs_cosmo=kwargs_cosmo, kwargs_numerics=kwargs_numerics, analytic_kinematics=analytic_kinematics)
if not self.aperture_type == 'IFU_shells':
raise ValueError('GalkinSh... | class to calculate velocity dispersion for radial shells in a fast way | GalkinShells | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GalkinShells:
"""class to calculate velocity dispersion for radial shells in a fast way"""
def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False):
""":param kwargs_model: keyword arguments describing the model comp... | stack_v2_sparse_classes_36k_train_007826 | 3,570 | permissive | [
{
"docstring": ":param kwargs_model: keyword arguments describing the model components :param kwargs_aperture: keyword arguments describing the spectroscopic aperture, see Aperture() class :param kwargs_psf: keyword argument specifying the PSF of the observation :param kwargs_cosmo: keyword arguments that defin... | 2 | null | Implement the Python class `GalkinShells` described below.
Class description:
class to calculate velocity dispersion for radial shells in a fast way
Method signatures and docstrings:
- def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): :param ... | Implement the Python class `GalkinShells` described below.
Class description:
class to calculate velocity dispersion for radial shells in a fast way
Method signatures and docstrings:
- def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False): :param ... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class GalkinShells:
"""class to calculate velocity dispersion for radial shells in a fast way"""
def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False):
""":param kwargs_model: keyword arguments describing the model comp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GalkinShells:
"""class to calculate velocity dispersion for radial shells in a fast way"""
def __init__(self, kwargs_model, kwargs_aperture, kwargs_psf, kwargs_cosmo, kwargs_numerics=None, analytic_kinematics=False):
""":param kwargs_model: keyword arguments describing the model components :param... | the_stack_v2_python_sparse | lenstronomy/GalKin/galkin_shells.py | lenstronomy/lenstronomy | train | 41 |
2b5f0e0897df9c1f5f0d5137c993215bf6d784a1 | [
"try:\n tag_ord = None\n if isinstance(tag, bytes) and len(tag) == 1:\n tag_ord = ord(tag)\n if tag_ord in (ord(self.OK_STATUS), ord(self.DATA_TO_NETWORK), ord(self.DATA_TO_SLS)):\n return True\nexcept TypeError:\n pass\nreturn False",
"if isinstance(data, (bytes, bytearray)):\n tag =... | <|body_start_0|>
try:
tag_ord = None
if isinstance(tag, bytes) and len(tag) == 1:
tag_ord = ord(tag)
if tag_ord in (ord(self.OK_STATUS), ord(self.DATA_TO_NETWORK), ord(self.DATA_TO_SLS)):
return True
except TypeError:
pass
... | Outbound data tag class | TagOutbound | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagOutbound:
"""Outbound data tag class"""
def in_this_scope(self, tag):
"""Check tag is in this scope"""
<|body_0|>
def assemble_for_network(self, data):
"""Assemble data to network"""
<|body_1|>
def assemble_for_sls(self, data):
"""Assemble... | stack_v2_sparse_classes_36k_train_007827 | 8,293 | permissive | [
{
"docstring": "Check tag is in this scope",
"name": "in_this_scope",
"signature": "def in_this_scope(self, tag)"
},
{
"docstring": "Assemble data to network",
"name": "assemble_for_network",
"signature": "def assemble_for_network(self, data)"
},
{
"docstring": "Assemble data to ... | 4 | stack_v2_sparse_classes_30k_train_014680 | Implement the Python class `TagOutbound` described below.
Class description:
Outbound data tag class
Method signatures and docstrings:
- def in_this_scope(self, tag): Check tag is in this scope
- def assemble_for_network(self, data): Assemble data to network
- def assemble_for_sls(self, data): Assemble data to sls
- ... | Implement the Python class `TagOutbound` described below.
Class description:
Outbound data tag class
Method signatures and docstrings:
- def in_this_scope(self, tag): Check tag is in this scope
- def assemble_for_network(self, data): Assemble data to network
- def assemble_for_sls(self, data): Assemble data to sls
- ... | ff4577c321b1ac3439856c98e9ca6d8b88462d7e | <|skeleton|>
class TagOutbound:
"""Outbound data tag class"""
def in_this_scope(self, tag):
"""Check tag is in this scope"""
<|body_0|>
def assemble_for_network(self, data):
"""Assemble data to network"""
<|body_1|>
def assemble_for_sls(self, data):
"""Assemble... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagOutbound:
"""Outbound data tag class"""
def in_this_scope(self, tag):
"""Check tag is in this scope"""
try:
tag_ord = None
if isinstance(tag, bytes) and len(tag) == 1:
tag_ord = ord(tag)
if tag_ord in (ord(self.OK_STATUS), ord(self.DA... | the_stack_v2_python_sparse | uhost/utilities/tag.py | connax-utim/uhost-python | train | 1 |
f4721ca826652c250ee16fd6435ff4437abc407e | [
"super().__init__('efetch.fcgi', tool, email, apikey=apikey, threads=threads, qid=qid)\nself.logger = entrezpy.log.logger.get_class_logger(Efetcher)\nself.logger.debug(json.dumps({'init': self.dump()}))",
"param = entrezpy.efetch.efetch_parameter.EfetchParameter(parameter)\nself.logger.debug(json.dumps({'paramete... | <|body_start_0|>
super().__init__('efetch.fcgi', tool, email, apikey=apikey, threads=threads, qid=qid)
self.logger = entrezpy.log.logger.get_class_logger(Efetcher)
self.logger.debug(json.dumps({'init': self.dump()}))
<|end_body_0|>
<|body_start_1|>
param = entrezpy.efetch.efetch_paramet... | Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm.nih.gov/books/NBK25497/table/ chapter2.T._entrez_unique_identifiers_ui/?re... | Efetcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Efetcher:
"""Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm.nih.gov/books/NBK25497/table/ chapter2... | stack_v2_sparse_classes_36k_train_007828 | 3,185 | no_license | [
{
"docstring": ":ivar result: :class:`entrezpy.base.result.EutilsResult`",
"name": "__init__",
"signature": "def __init__(self, tool, email, apikey=None, apikey_var=None, threads=None, qid=None)"
},
{
"docstring": "Implements :meth:`entrezpy.base.query.EutilsQuery.inquire` and configures fetch. ... | 2 | null | Implement the Python class `Efetcher` described below.
Class description:
Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm... | Implement the Python class `Efetcher` described below.
Class description:
Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm... | be9e22fc41153060da306366b6d3aa26d5f60f23 | <|skeleton|>
class Efetcher:
"""Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm.nih.gov/books/NBK25497/table/ chapter2... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Efetcher:
"""Efetcher implements Efetch E-Utilities queries [0]. It implements :meth:`entrezpy.base.query.EutilsQuery.inquire` to fetch data from NCBI Entrez servers. [0]: https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.EFetch [1]: https://www.ncbi.nlm.nih.gov/books/NBK25497/table/ chapter2.T._entrez_un... | the_stack_v2_python_sparse | venv/Lib/site-packages/entrezpy/efetch/efetcher.py | lvn3668/variantAnnotation | train | 2 |
0890c266b7406f69d3faf5884c15b145a2854976 | [
"rota_tool = getToolByName(self, 'portal_rotatool')\nmembers = rota_tool.getAvailableReporters()\nreturn DisplayList([(m.UID(), m.Title()) for m in members])",
"catalog = getToolByName(self, 'uid_catalog')\nteam_ids = [p.UID for p in catalog(portal_type='DebateRecordOffice')]\nreturn team_ids",
"rota_tool = get... | <|body_start_0|>
rota_tool = getToolByName(self, 'portal_rotatool')
members = rota_tool.getAvailableReporters()
return DisplayList([(m.UID(), m.Title()) for m in members])
<|end_body_0|>
<|body_start_1|>
catalog = getToolByName(self, 'uid_catalog')
team_ids = [p.UID for p in cat... | DebateRecordFolder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DebateRecordFolder:
def getReportersForSittingVocab(self):
"""Get the current parliament's team of reporters, and return the active memberships."""
<|body_0|>
def getSpaceTeamsDefault(self):
"""Used from space_team_edit.pt"""
<|body_1|>
def getNotAddable... | stack_v2_sparse_classes_36k_train_007829 | 5,607 | no_license | [
{
"docstring": "Get the current parliament's team of reporters, and return the active memberships.",
"name": "getReportersForSittingVocab",
"signature": "def getReportersForSittingVocab(self)"
},
{
"docstring": "Used from space_team_edit.pt",
"name": "getSpaceTeamsDefault",
"signature": ... | 4 | null | Implement the Python class `DebateRecordFolder` described below.
Class description:
Implement the DebateRecordFolder class.
Method signatures and docstrings:
- def getReportersForSittingVocab(self): Get the current parliament's team of reporters, and return the active memberships.
- def getSpaceTeamsDefault(self): Us... | Implement the Python class `DebateRecordFolder` described below.
Class description:
Implement the DebateRecordFolder class.
Method signatures and docstrings:
- def getReportersForSittingVocab(self): Get the current parliament's team of reporters, and return the active memberships.
- def getSpaceTeamsDefault(self): Us... | 5cf0ba31dfbff8d2c1b4aa8ab6f69c7a0ae9870d | <|skeleton|>
class DebateRecordFolder:
def getReportersForSittingVocab(self):
"""Get the current parliament's team of reporters, and return the active memberships."""
<|body_0|>
def getSpaceTeamsDefault(self):
"""Used from space_team_edit.pt"""
<|body_1|>
def getNotAddable... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DebateRecordFolder:
def getReportersForSittingVocab(self):
"""Get the current parliament's team of reporters, and return the active memberships."""
rota_tool = getToolByName(self, 'portal_rotatool')
members = rota_tool.getAvailableReporters()
return DisplayList([(m.UID(), m.Tit... | the_stack_v2_python_sparse | archived/Bungeni/branches/ooo2tools-branch/debaterecord/DebateRecordFolder.py | malangalanga/bungeni-portal | train | 0 | |
719d78b5fc72a0524b9c6c21fc50e2df08176e42 | [
"super().__init__()\nself.init_point = init_point\nself.sigma = sigma",
"sq_diff = torch.norm(X - self.init_point, p=2, dim=-1) ** 2\npdf = torch.exp(sq_diff / 2 / self.sigma ** 2)\nregularization_term = pdf.max(dim=-1).values\nreturn regularization_term"
] | <|body_start_0|>
super().__init__()
self.init_point = init_point
self.sigma = sigma
<|end_body_0|>
<|body_start_1|>
sq_diff = torch.norm(X - self.init_point, p=2, dim=-1) ** 2
pdf = torch.exp(sq_diff / 2 / self.sigma ** 2)
regularization_term = pdf.max(dim=-1).values
... | Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction. | GaussianPenalty | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianPenalty:
"""Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction."""
def __init__(self, init_point: Tensor, sigma: float):
"""Initializing Gaussian regularization. Args: init_point: The "1 x dim" reference point ... | stack_v2_sparse_classes_36k_train_007830 | 14,396 | permissive | [
{
"docstring": "Initializing Gaussian regularization. Args: init_point: The \"1 x dim\" reference point against which we want to regularize. sigma: The parameter used in gaussian function.",
"name": "__init__",
"signature": "def __init__(self, init_point: Tensor, sigma: float)"
},
{
"docstring":... | 2 | null | Implement the Python class `GaussianPenalty` described below.
Class description:
Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction.
Method signatures and docstrings:
- def __init__(self, init_point: Tensor, sigma: float): Initializing Gaussian regular... | Implement the Python class `GaussianPenalty` described below.
Class description:
Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction.
Method signatures and docstrings:
- def __init__(self, init_point: Tensor, sigma: float): Initializing Gaussian regular... | 4cc5ed59b2e8a9c780f786830c548e05cc74d53c | <|skeleton|>
class GaussianPenalty:
"""Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction."""
def __init__(self, init_point: Tensor, sigma: float):
"""Initializing Gaussian regularization. Args: init_point: The "1 x dim" reference point ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianPenalty:
"""Gaussian penalty class to be added to any arbitrary acquisition function to construct a PenalizedAcquisitionFunction."""
def __init__(self, init_point: Tensor, sigma: float):
"""Initializing Gaussian regularization. Args: init_point: The "1 x dim" reference point against which... | the_stack_v2_python_sparse | botorch/acquisition/penalized.py | pytorch/botorch | train | 2,891 |
a6d54e3d94d5674435b144b4f4f099c24316cbbe | [
"sub_list = re.findall('.{%s}' % self.word_len, substring)\nsub_dict = self.gen_dict(sub_list)\nif sub_dict == self.word_dic:\n return True\nreturn False",
"word_dic = dict.fromkeys(word_list, 0)\nfor w in word_list:\n word_dic[w] += 1\nreturn word_dic",
"if len(words) == 0:\n return []\nself.word_len ... | <|body_start_0|>
sub_list = re.findall('.{%s}' % self.word_len, substring)
sub_dict = self.gen_dict(sub_list)
if sub_dict == self.word_dic:
return True
return False
<|end_body_0|>
<|body_start_1|>
word_dic = dict.fromkeys(word_list, 0)
for w in word_list:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def check(self, substring):
""":type substring: str :rtype: bool"""
<|body_0|>
def gen_dict(word_list):
""":type word_list: List[str :rtype: dict"""
<|body_1|>
def findSubstring(self, s, words):
""":type s: str :type words: List[str] :r... | stack_v2_sparse_classes_36k_train_007831 | 2,182 | no_license | [
{
"docstring": ":type substring: str :rtype: bool",
"name": "check",
"signature": "def check(self, substring)"
},
{
"docstring": ":type word_list: List[str :rtype: dict",
"name": "gen_dict",
"signature": "def gen_dict(word_list)"
},
{
"docstring": ":type s: str :type words: List[... | 3 | stack_v2_sparse_classes_30k_train_018922 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def check(self, substring): :type substring: str :rtype: bool
- def gen_dict(word_list): :type word_list: List[str :rtype: dict
- def findSubstring(self, s, words): :type s: str ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def check(self, substring): :type substring: str :rtype: bool
- def gen_dict(word_list): :type word_list: List[str :rtype: dict
- def findSubstring(self, s, words): :type s: str ... | f8f3b0cdb47ee6bb4bf9bdc7c2a983f4a882d9dd | <|skeleton|>
class Solution:
def check(self, substring):
""":type substring: str :rtype: bool"""
<|body_0|>
def gen_dict(word_list):
""":type word_list: List[str :rtype: dict"""
<|body_1|>
def findSubstring(self, s, words):
""":type s: str :type words: List[str] :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def check(self, substring):
""":type substring: str :rtype: bool"""
sub_list = re.findall('.{%s}' % self.word_len, substring)
sub_dict = self.gen_dict(sub_list)
if sub_dict == self.word_dic:
return True
return False
def gen_dict(word_list):
... | the_stack_v2_python_sparse | solutions/030-substring-with-concatenation-of-all-words/main.py | CallMeNP/leetcode | train | 0 | |
0101cb4e170a8d168a24134fee231c0d44274d44 | [
"session = db_apis.get_session()\nwith session.begin():\n db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])\namphorae = {amp.id: amp for amp in db_lb.amphorae}\nupdated_ports = {}\nhandle_delta = HandleNetworkDelta()\nfor amp_id, delta in deltas.items():\n ret = handle_de... | <|body_start_0|>
session = db_apis.get_session()
with session.begin():
db_lb = self.loadbalancer_repo.get(session, id=loadbalancer[constants.LOADBALANCER_ID])
amphorae = {amp.id: amp for amp in db_lb.amphorae}
updated_ports = {}
handle_delta = HandleNetworkDelta()
... | Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta | HandleNetworkDeltas | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
<|body_0|>
def revert(self, result, deltas, *args, **kw... | stack_v2_sparse_classes_36k_train_007832 | 44,034 | permissive | [
{
"docstring": "Handle network plugging based off deltas.",
"name": "execute",
"signature": "def execute(self, deltas, loadbalancer)"
},
{
"docstring": "Handle a network plug or unplug failures.",
"name": "revert",
"signature": "def revert(self, result, deltas, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003005 | Implement the Python class `HandleNetworkDeltas` described below.
Class description:
Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta
Method signatures and docstrings:
- def execute(self, deltas, loadbalancer): Handle network plugging based off deltas.
- def revert(s... | Implement the Python class `HandleNetworkDeltas` described below.
Class description:
Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta
Method signatures and docstrings:
- def execute(self, deltas, loadbalancer): Handle network plugging based off deltas.
- def revert(s... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
<|body_0|>
def revert(self, result, deltas, *args, **kw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HandleNetworkDeltas:
"""Task to plug and unplug networks Loop through the deltas and plug or unplug networks based on delta"""
def execute(self, deltas, loadbalancer):
"""Handle network plugging based off deltas."""
session = db_apis.get_session()
with session.begin():
... | the_stack_v2_python_sparse | octavia/controller/worker/v2/tasks/network_tasks.py | openstack/octavia | train | 147 |
36f1f1176ca5b91d8e496019f7b037101f623504 | [
"rval = zeros(len(string), float32)\nrval[:] = nan\n_pwm.score_string(self.values, self.char_to_index, string, rval)\nreturn rval",
"rval = zeros(len(string), float32)\nrval[:] = nan\n_pwm.score_string_with_gaps(self.values, self.char_to_index, string, rval)\nreturn rval"
] | <|body_start_0|>
rval = zeros(len(string), float32)
rval[:] = nan
_pwm.score_string(self.values, self.char_to_index, string, rval)
return rval
<|end_body_0|>
<|body_start_1|>
rval = zeros(len(string), float32)
rval[:] = nan
_pwm.score_string_with_gaps(self.values... | A position specific matrix containing values that are suitable for scoring a sequence. | ScoringMatrix | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScoringMatrix:
"""A position specific matrix containing values that are suitable for scoring a sequence."""
def score_string(self, string):
"""Score each valid position in `string` using this scoring matrix. Positions which were not scored are set to nan."""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_007833 | 5,401 | permissive | [
{
"docstring": "Score each valid position in `string` using this scoring matrix. Positions which were not scored are set to nan.",
"name": "score_string",
"signature": "def score_string(self, string)"
},
{
"docstring": "Score each valid position in `string` using this scoring matrix. Positions w... | 2 | null | Implement the Python class `ScoringMatrix` described below.
Class description:
A position specific matrix containing values that are suitable for scoring a sequence.
Method signatures and docstrings:
- def score_string(self, string): Score each valid position in `string` using this scoring matrix. Positions which wer... | Implement the Python class `ScoringMatrix` described below.
Class description:
A position specific matrix containing values that are suitable for scoring a sequence.
Method signatures and docstrings:
- def score_string(self, string): Score each valid position in `string` using this scoring matrix. Positions which wer... | 7758bc4492626ffdbaa90c8fc5dd7620b1e2f3f8 | <|skeleton|>
class ScoringMatrix:
"""A position specific matrix containing values that are suitable for scoring a sequence."""
def score_string(self, string):
"""Score each valid position in `string` using this scoring matrix. Positions which were not scored are set to nan."""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScoringMatrix:
"""A position specific matrix containing values that are suitable for scoring a sequence."""
def score_string(self, string):
"""Score each valid position in `string` using this scoring matrix. Positions which were not scored are set to nan."""
rval = zeros(len(string), floa... | the_stack_v2_python_sparse | lib/bx/motif/pwm.py | bxlab/bx-python | train | 141 |
42825c29669586cea2c74137ad127ea6773ce7e0 | [
"if not mr.auth.user_id:\n return {'error': 'User is not logged in.'}\njson_data = {}\nwith self.profiler.Phase('page processing'):\n json_data.update(self._GatherHotlists(mr))\nreturn json_data",
"with self.profiler.Phase('GetUserHotlists'):\n user_hotlists = self.services.features.GetHotlistsByUserID(m... | <|body_start_0|>
if not mr.auth.user_id:
return {'error': 'User is not logged in.'}
json_data = {}
with self.profiler.Phase('page processing'):
json_data.update(self._GatherHotlists(mr))
return json_data
<|end_body_0|>
<|body_start_1|>
with self.profiler.... | Servlet to get all of a user's hotlists in JSON format. | HotlistsJsonFeed | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HotlistsJsonFeed:
"""Servlet to get all of a user's hotlists in JSON format."""
def HandleRequest(self, mr):
"""Retrieve list of a user's hotlists for the "My hotlists" menu. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON format"""
... | stack_v2_sparse_classes_36k_train_007834 | 2,958 | permissive | [
{
"docstring": "Retrieve list of a user's hotlists for the \"My hotlists\" menu. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON format",
"name": "HandleRequest",
"signature": "def HandleRequest(self, mr)"
},
{
"docstring": "Return a dict of hotlist... | 2 | null | Implement the Python class `HotlistsJsonFeed` described below.
Class description:
Servlet to get all of a user's hotlists in JSON format.
Method signatures and docstrings:
- def HandleRequest(self, mr): Retrieve list of a user's hotlists for the "My hotlists" menu. Args: mr: common information parsed from the HTTP re... | Implement the Python class `HotlistsJsonFeed` described below.
Class description:
Servlet to get all of a user's hotlists in JSON format.
Method signatures and docstrings:
- def HandleRequest(self, mr): Retrieve list of a user's hotlists for the "My hotlists" menu. Args: mr: common information parsed from the HTTP re... | 09064105713603f7bf75c772e8354800a1bfa256 | <|skeleton|>
class HotlistsJsonFeed:
"""Servlet to get all of a user's hotlists in JSON format."""
def HandleRequest(self, mr):
"""Retrieve list of a user's hotlists for the "My hotlists" menu. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON format"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HotlistsJsonFeed:
"""Servlet to get all of a user's hotlists in JSON format."""
def HandleRequest(self, mr):
"""Retrieve list of a user's hotlists for the "My hotlists" menu. Args: mr: common information parsed from the HTTP request. Returns: Results dictionary in JSON format"""
if not mr... | the_stack_v2_python_sparse | appengine/monorail/sitewide/userhotlistsmenu.py | mcgreevy/chromium-infra | train | 1 |
10ff3efab79c8e7290680587c754d4c7b0f087f9 | [
"def generate(sequence: List[str]) -> None:\n \"\"\"递归生成所有序列，并将有效序列加入结果。\"\"\"\n if len(sequence) == 2 * n:\n if valid(sequence):\n ans.append(''.join(sequence))\n else:\n sequence.append('(')\n generate(sequence)\n sequence.pop()\n sequence.append(')')\n ... | <|body_start_0|>
def generate(sequence: List[str]) -> None:
"""递归生成所有序列，并将有效序列加入结果。"""
if len(sequence) == 2 * n:
if valid(sequence):
ans.append(''.join(sequence))
else:
sequence.append('(')
generate(sequence... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generate_parenthesis(self, n: int) -> List[str]:
"""暴力。"""
<|body_0|>
def generate_parenthesis_2(self, n: int) -> List[str]:
"""回溯法。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def generate(sequence: List[str]) -> None:
... | stack_v2_sparse_classes_36k_train_007835 | 3,775 | no_license | [
{
"docstring": "暴力。",
"name": "generate_parenthesis",
"signature": "def generate_parenthesis(self, n: int) -> List[str]"
},
{
"docstring": "回溯法。",
"name": "generate_parenthesis_2",
"signature": "def generate_parenthesis_2(self, n: int) -> List[str]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate_parenthesis(self, n: int) -> List[str]: 暴力。
- def generate_parenthesis_2(self, n: int) -> List[str]: 回溯法。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generate_parenthesis(self, n: int) -> List[str]: 暴力。
- def generate_parenthesis_2(self, n: int) -> List[str]: 回溯法。
<|skeleton|>
class Solution:
def generate_parenthesis... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def generate_parenthesis(self, n: int) -> List[str]:
"""暴力。"""
<|body_0|>
def generate_parenthesis_2(self, n: int) -> List[str]:
"""回溯法。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generate_parenthesis(self, n: int) -> List[str]:
"""暴力。"""
def generate(sequence: List[str]) -> None:
"""递归生成所有序列，并将有效序列加入结果。"""
if len(sequence) == 2 * n:
if valid(sequence):
ans.append(''.join(sequence))
el... | the_stack_v2_python_sparse | 0022_generate-parentheses.py | Nigirimeshi/leetcode | train | 0 | |
8d2fb863d28d654b66d405c337cf97922b8ada51 | [
"vk_account = user.get_vk_account()\nif vk_account is not None:\n vk_session = VkApi(token=vk_account.access_token)\n self.vk = vk_session.get_api()\n self.vk_id = vk_account.uid\nself.user = user",
"friends_ids: List['User'] = []\nuser_model: 'User' = get_user_model()\nreturn user_model.objects.filter(s... | <|body_start_0|>
vk_account = user.get_vk_account()
if vk_account is not None:
vk_session = VkApi(token=vk_account.access_token)
self.vk = vk_session.get_api()
self.vk_id = vk_account.uid
self.user = user
<|end_body_0|>
<|body_start_1|>
friends_ids: L... | VK. | Vk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vk:
"""VK."""
def __init__(self, user: 'User'):
"""Init."""
<|body_0|>
def get_friends(self) -> QuerySet['User']:
"""Get friends."""
<|body_1|>
def get_data(self, fields: list[str]) -> UntypedObject:
"""Get data."""
<|body_2|>
de... | stack_v2_sparse_classes_36k_train_007836 | 3,092 | no_license | [
{
"docstring": "Init.",
"name": "__init__",
"signature": "def __init__(self, user: 'User')"
},
{
"docstring": "Get friends.",
"name": "get_friends",
"signature": "def get_friends(self) -> QuerySet['User']"
},
{
"docstring": "Get data.",
"name": "get_data",
"signature": "d... | 4 | stack_v2_sparse_classes_30k_train_003558 | Implement the Python class `Vk` described below.
Class description:
VK.
Method signatures and docstrings:
- def __init__(self, user: 'User'): Init.
- def get_friends(self) -> QuerySet['User']: Get friends.
- def get_data(self, fields: list[str]) -> UntypedObject: Get data.
- def get_countries(self, country_codes: lis... | Implement the Python class `Vk` described below.
Class description:
VK.
Method signatures and docstrings:
- def __init__(self, user: 'User'): Init.
- def get_friends(self) -> QuerySet['User']: Get friends.
- def get_data(self, fields: list[str]) -> UntypedObject: Get data.
- def get_countries(self, country_codes: lis... | 04141e4cfc885ba6c53328e1222980b85d9828ef | <|skeleton|>
class Vk:
"""VK."""
def __init__(self, user: 'User'):
"""Init."""
<|body_0|>
def get_friends(self) -> QuerySet['User']:
"""Get friends."""
<|body_1|>
def get_data(self, fields: list[str]) -> UntypedObject:
"""Get data."""
<|body_2|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vk:
"""VK."""
def __init__(self, user: 'User'):
"""Init."""
vk_account = user.get_vk_account()
if vk_account is not None:
vk_session = VkApi(token=vk_account.access_token)
self.vk = vk_session.get_api()
self.vk_id = vk_account.uid
self.u... | the_stack_v2_python_sparse | src/moviesapp/vk.py | desecho/movies | train | 14 |
39f37c617dafc865c826b1a37429e32a561afd20 | [
"try:\n return inv(v)\nexcept:\n return None",
"from ambry.build import meta_source_schema, get_specs\nspecs = get_specs(self)\nmeta_source_schema(self, self)"
] | <|body_start_0|>
try:
return inv(v)
except:
return None
<|end_body_0|>
<|body_start_1|>
from ambry.build import meta_source_schema, get_specs
specs = get_specs(self)
meta_source_schema(self, self)
<|end_body_1|>
| Bundle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bundle:
def illegal_to_none(self, v):
"""Converts '4 7' value from hlthcvrg field, on row 127231, to None."""
<|body_0|>
def meta_source_schema(self):
"""Read the spec from the HTML file, and bergest it with the descriptions from the codebook.txt file. Does *not* use... | stack_v2_sparse_classes_36k_train_007837 | 672 | no_license | [
{
"docstring": "Converts '4 7' value from hlthcvrg field, on row 127231, to None.",
"name": "illegal_to_none",
"signature": "def illegal_to_none(self, v)"
},
{
"docstring": "Read the spec from the HTML file, and bergest it with the descriptions from the codebook.txt file. Does *not* use the conv... | 2 | stack_v2_sparse_classes_30k_train_015128 | Implement the Python class `Bundle` described below.
Class description:
Implement the Bundle class.
Method signatures and docstrings:
- def illegal_to_none(self, v): Converts '4 7' value from hlthcvrg field, on row 127231, to None.
- def meta_source_schema(self): Read the spec from the HTML file, and bergest it with ... | Implement the Python class `Bundle` described below.
Class description:
Implement the Bundle class.
Method signatures and docstrings:
- def illegal_to_none(self, v): Converts '4 7' value from hlthcvrg field, on row 127231, to None.
- def meta_source_schema(self): Read the spec from the HTML file, and bergest it with ... | a084bb965cb7b3ff5871a547709bc3975d1fe936 | <|skeleton|>
class Bundle:
def illegal_to_none(self, v):
"""Converts '4 7' value from hlthcvrg field, on row 127231, to None."""
<|body_0|>
def meta_source_schema(self):
"""Read the spec from the HTML file, and bergest it with the descriptions from the codebook.txt file. Does *not* use... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bundle:
def illegal_to_none(self, v):
"""Converts '4 7' value from hlthcvrg field, on row 127231, to None."""
try:
return inv(v)
except:
return None
def meta_source_schema(self):
"""Read the spec from the HTML file, and bergest it with the descripti... | the_stack_v2_python_sparse | cdc.gov/brfss-2013/bundle.py | CivicSpleen/ambry10-bundles | train | 0 | |
cc77c2e54c9cde7f39170d329d288ccd483dd08e | [
"metric_struct_field = StructField('metric', StructType([StructField('dimensions', MapType(StringType(), StringType(), True), True), StructField('value_meta', MapType(StringType(), StringType(), True), True), StructField('name', StringType(), True), StructField('timestamp', StringType(), True), StructField('value',... | <|body_start_0|>
metric_struct_field = StructField('metric', StructType([StructField('dimensions', MapType(StringType(), StringType(), True), True), StructField('value_meta', MapType(StringType(), StringType(), True), True), StructField('name', StringType(), True), StructField('timestamp', StringType(), True), ... | utility methods to transform raw metric. | MonMetricUtils | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonMetricUtils:
"""utility methods to transform raw metric."""
def _get_mon_metric_json_schema():
"""get the schema of the incoming monasca metric."""
<|body_0|>
def create_mon_metrics_df_from_json_rdd(sql_context, jsonrdd):
"""create mon metrics df from json rdd... | stack_v2_sparse_classes_36k_train_007838 | 23,930 | permissive | [
{
"docstring": "get the schema of the incoming monasca metric.",
"name": "_get_mon_metric_json_schema",
"signature": "def _get_mon_metric_json_schema()"
},
{
"docstring": "create mon metrics df from json rdd.",
"name": "create_mon_metrics_df_from_json_rdd",
"signature": "def create_mon_m... | 2 | stack_v2_sparse_classes_30k_train_018886 | Implement the Python class `MonMetricUtils` described below.
Class description:
utility methods to transform raw metric.
Method signatures and docstrings:
- def _get_mon_metric_json_schema(): get the schema of the incoming monasca metric.
- def create_mon_metrics_df_from_json_rdd(sql_context, jsonrdd): create mon met... | Implement the Python class `MonMetricUtils` described below.
Class description:
utility methods to transform raw metric.
Method signatures and docstrings:
- def _get_mon_metric_json_schema(): get the schema of the incoming monasca metric.
- def create_mon_metrics_df_from_json_rdd(sql_context, jsonrdd): create mon met... | 6d76487028926b50d93f70e8dc61dc90ed318256 | <|skeleton|>
class MonMetricUtils:
"""utility methods to transform raw metric."""
def _get_mon_metric_json_schema():
"""get the schema of the incoming monasca metric."""
<|body_0|>
def create_mon_metrics_df_from_json_rdd(sql_context, jsonrdd):
"""create mon metrics df from json rdd... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MonMetricUtils:
"""utility methods to transform raw metric."""
def _get_mon_metric_json_schema():
"""get the schema of the incoming monasca metric."""
metric_struct_field = StructField('metric', StructType([StructField('dimensions', MapType(StringType(), StringType(), True), True), Struct... | the_stack_v2_python_sparse | monasca_transform/transform/transform_utils.py | xiashuijun/monasca-transform | train | 0 |
edca37b31261169336906d806fc37b6d3e0f0266 | [
"print('ouput level = ' + str(ILog.get_output_level()))\nself.__test_output_all('default')\nfor i in range(1, 4):\n ILog.set_output_level(i)\n print('set ouput level = ' + str(i))\n self.__test_output_all('lv = ' + str(i))",
"ILog.error('error message: ' + _postfix)\nILog.warn('warning message: ' + _po... | <|body_start_0|>
print('ouput level = ' + str(ILog.get_output_level()))
self.__test_output_all('default')
for i in range(1, 4):
ILog.set_output_level(i)
print('set ouput level = ' + str(i))
self.__test_output_all('lv = ' + str(i))
<|end_body_0|>
<|body_start_... | test: Logger | TestIFGILogger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestIFGILogger:
"""test: Logger"""
def test_logger(self):
"""test logger."""
<|body_0|>
def __test_output_all(self, _postfix):
"""test subroutine to test all the output level"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print('ouput level = '... | stack_v2_sparse_classes_36k_train_007839 | 1,114 | no_license | [
{
"docstring": "test logger.",
"name": "test_logger",
"signature": "def test_logger(self)"
},
{
"docstring": "test subroutine to test all the output level",
"name": "__test_output_all",
"signature": "def __test_output_all(self, _postfix)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010017 | Implement the Python class `TestIFGILogger` described below.
Class description:
test: Logger
Method signatures and docstrings:
- def test_logger(self): test logger.
- def __test_output_all(self, _postfix): test subroutine to test all the output level | Implement the Python class `TestIFGILogger` described below.
Class description:
test: Logger
Method signatures and docstrings:
- def test_logger(self): test logger.
- def __test_output_all(self, _postfix): test subroutine to test all the output level
<|skeleton|>
class TestIFGILogger:
"""test: Logger"""
def... | f163b6b9e15100d223ddf4e180727a2b63fbae2d | <|skeleton|>
class TestIFGILogger:
"""test: Logger"""
def test_logger(self):
"""test logger."""
<|body_0|>
def __test_output_all(self, _postfix):
"""test subroutine to test all the output level"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestIFGILogger:
"""test: Logger"""
def test_logger(self):
"""test logger."""
print('ouput level = ' + str(ILog.get_output_level()))
self.__test_output_all('default')
for i in range(1, 4):
ILog.set_output_level(i)
print('set ouput level = ' + str(i))... | the_stack_v2_python_sparse | ifgi/base/test_ILog.py | yamauchih/ifgi-path-tracer | train | 0 |
35b856c324cb40ca03d3a6af3f2448ebc3c74975 | [
"self._action_ph = tf.placeholder(tf.float32, (batch_size, action_size))\nself._batch_size = batch_size\nself._action_size = action_size\nself._build_target = build_target\nself._action_space = spaces.Box(low=-1, high=1, shape=(action_size,))\nself._include_timestep = include_timestep\nsuper(CEMActorPolicy, self)._... | <|body_start_0|>
self._action_ph = tf.placeholder(tf.float32, (batch_size, action_size))
self._batch_size = batch_size
self._action_size = action_size
self._build_target = build_target
self._action_space = spaces.Box(low=-1, high=1, shape=(action_size,))
self._include_tim... | Learned policy for grasping (continuous). Uses CEM for selecting actions. | CEMActorPolicy | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CEMActorPolicy:
"""Learned policy for grasping (continuous). Uses CEM for selecting actions."""
def __init__(self, q_func, state_shape, action_size, use_gpu=True, batch_size=64, build_target=False, include_timestep=True, checkpoint=None):
"""Initializes the policy. Args: q_func: Pyth... | stack_v2_sparse_classes_36k_train_007840 | 14,341 | permissive | [
{
"docstring": "Initializes the policy. Args: q_func: Python function that takes in state, action, scope as input and returns Q(state, action) and intermediate endpoints dictionary. state_shape: Tuple of ints describing shape of the state observation. action_size: (int) Size of the vector-encoded action. use_gp... | 3 | stack_v2_sparse_classes_30k_train_000151 | Implement the Python class `CEMActorPolicy` described below.
Class description:
Learned policy for grasping (continuous). Uses CEM for selecting actions.
Method signatures and docstrings:
- def __init__(self, q_func, state_shape, action_size, use_gpu=True, batch_size=64, build_target=False, include_timestep=True, che... | Implement the Python class `CEMActorPolicy` described below.
Class description:
Learned policy for grasping (continuous). Uses CEM for selecting actions.
Method signatures and docstrings:
- def __init__(self, q_func, state_shape, action_size, use_gpu=True, batch_size=64, build_target=False, include_timestep=True, che... | dea327aa9e7ef7f7bca5a6c225dbdca1077a06e9 | <|skeleton|>
class CEMActorPolicy:
"""Learned policy for grasping (continuous). Uses CEM for selecting actions."""
def __init__(self, q_func, state_shape, action_size, use_gpu=True, batch_size=64, build_target=False, include_timestep=True, checkpoint=None):
"""Initializes the policy. Args: q_func: Pyth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CEMActorPolicy:
"""Learned policy for grasping (continuous). Uses CEM for selecting actions."""
def __init__(self, q_func, state_shape, action_size, use_gpu=True, batch_size=64, build_target=False, include_timestep=True, checkpoint=None):
"""Initializes the policy. Args: q_func: Python function t... | the_stack_v2_python_sparse | dql_grasping/policies.py | Tarkiyah/googleResearch | train | 11 |
6b2866f37f7e3dbed3b736b42b75bc701b392ad3 | [
"cache = [v1[::-1], v2[::-1]]\nself.list_all = [i for i in cache if i]\nself.cur = 0",
"if self.cur == -1 or not self.list_all:\n return False\nnext_val = self.list_all[self.cur].pop()\nif self.list_all[self.cur]:\n self.cur = self.cur + 1 if self.cur < len(self.list_all) - 1 else 0\nelse:\n while self.c... | <|body_start_0|>
cache = [v1[::-1], v2[::-1]]
self.list_all = [i for i in cache if i]
self.cur = 0
<|end_body_0|>
<|body_start_1|>
if self.cur == -1 or not self.list_all:
return False
next_val = self.list_all[self.cur].pop()
if self.list_all[self.cur]:
... | ZigzagIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k_train_007841 | 2,162 | no_license | [
{
"docstring": "Initialize your data structure here. :type v1: List[int] :type v2: List[int]",
"name": "__init__",
"signature": "def __init__(self, v1, v2)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name"... | 3 | null | Implement the Python class `ZigzagIterator` described below.
Class description:
Implement the ZigzagIterator class.
Method signatures and docstrings:
- def __init__(self, v1, v2): Initialize your data structure here. :type v1: List[int] :type v2: List[int]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bo... | Implement the Python class `ZigzagIterator` described below.
Class description:
Implement the ZigzagIterator class.
Method signatures and docstrings:
- def __init__(self, v1, v2): Initialize your data structure here. :type v1: List[int] :type v2: List[int]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bo... | 56383c2b07448a9017a7a707afb66e08b403ee76 | <|skeleton|>
class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZigzagIterator:
def __init__(self, v1, v2):
"""Initialize your data structure here. :type v1: List[int] :type v2: List[int]"""
cache = [v1[::-1], v2[::-1]]
self.list_all = [i for i in cache if i]
self.cur = 0
def next(self):
""":rtype: int"""
if self.cur ==... | the_stack_v2_python_sparse | ALL_SOLUTIONS/281_Zigzag_Iterator.py | jamiezeminzhang/Leetcode_Python | train | 2 | |
74287659e00de320b5cca17a048fd0f1914775ec | [
"if value is None:\n return len(values['frequency'])\nreturn value",
"if arg == 'frequency':\n return np.array(self.frequency)\nif arg == 'magnitude':\n return np.array(self.magnitude)\nif arg == 'phase':\n return np.array(self.phase)\nraise ValueError(f\"Unknown arg {arg}, must be: 'frequency', 'magn... | <|body_start_0|>
if value is None:
return len(values['frequency'])
return value
<|end_body_0|>
<|body_start_1|>
if arg == 'frequency':
return np.array(self.frequency)
if arg == 'magnitude':
return np.array(self.magnitude)
if arg == 'phase':
... | Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use case - Phase is in radians | CalibrationData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalibrationData:
"""Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use case - Phase is in radians"""
def... | stack_v2_sparse_classes_36k_train_007842 | 18,607 | permissive | [
{
"docstring": "Validate number of samples",
"name": "validate_n_samples",
"signature": "def validate_n_samples(cls, value: Union[int, None], values: Dict[str, Any]) -> int"
},
{
"docstring": "Get data mainly for the purposes of plotting",
"name": "__getitem__",
"signature": "def __getit... | 4 | stack_v2_sparse_classes_30k_train_012599 | Implement the Python class `CalibrationData` described below.
Class description:
Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use... | Implement the Python class `CalibrationData` described below.
Class description:
Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use... | cba60747803b6c582eaaf1a670a7f455f5724ebd | <|skeleton|>
class CalibrationData:
"""Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use case - Phase is in radians"""
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalibrationData:
"""Class for holding calibration data Calibration is usually the transfer function of the instrument or sensor to be removed from the data. It is expected to be in the frequency domain. Regarding units: - Magnitude units are dependent on use case - Phase is in radians"""
def validate_n_s... | the_stack_v2_python_sparse | resistics/calibrate.py | resistics/resistics | train | 47 |
b059a4fdf533e041f07557755a8dfb1bafbdc92c | [
"i *= 10\nfor j in range(10):\n i2 = i + j\n if i2 > n:\n break\n r.append(i2)\n self.go(n, i2, r)",
"r = []\nfor i in range(1, 10):\n if i > n:\n break\n r.append(i)\n self.go(n, i, r)\nreturn r"
] | <|body_start_0|>
i *= 10
for j in range(10):
i2 = i + j
if i2 > n:
break
r.append(i2)
self.go(n, i2, r)
<|end_body_0|>
<|body_start_1|>
r = []
for i in range(1, 10):
if i > n:
break
r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def go(self, n, i, r):
""":type i: int :type p: int :type r: List[int]"""
<|body_0|>
def lexicalOrder(self, n):
""":type n: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i *= 10
for j in range(10):
... | stack_v2_sparse_classes_36k_train_007843 | 931 | no_license | [
{
"docstring": ":type i: int :type p: int :type r: List[int]",
"name": "go",
"signature": "def go(self, n, i, r)"
},
{
"docstring": ":type n: int :rtype: List[int]",
"name": "lexicalOrder",
"signature": "def lexicalOrder(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def go(self, n, i, r): :type i: int :type p: int :type r: List[int]
- def lexicalOrder(self, n): :type n: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def go(self, n, i, r): :type i: int :type p: int :type r: List[int]
- def lexicalOrder(self, n): :type n: int :rtype: List[int]
<|skeleton|>
class Solution:
def go(self, n,... | f08b8a3f7de7a456a55573f3c4d8920a80f03a1a | <|skeleton|>
class Solution:
def go(self, n, i, r):
""":type i: int :type p: int :type r: List[int]"""
<|body_0|>
def lexicalOrder(self, n):
""":type n: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def go(self, n, i, r):
""":type i: int :type p: int :type r: List[int]"""
i *= 10
for j in range(10):
i2 = i + j
if i2 > n:
break
r.append(i2)
self.go(n, i2, r)
def lexicalOrder(self, n):
""":type n:... | the_stack_v2_python_sparse | py/386.py | pipi32167/LeetCode | train | 1 | |
2c211f1fb3b4ccf847ff2a4dbbe6683c999d96f0 | [
"revoked_token = self._client.revoke_token(token=token)\nif check:\n self.check_token_is_revoked(revoked_token, must_revoked=False)\nreturn revoked_token",
"def predicate():\n try:\n self.get_token_validate(token)\n is_revoked = True\n except exceptions.NotFound:\n is_revoked = False... | <|body_start_0|>
revoked_token = self._client.revoke_token(token=token)
if check:
self.check_token_is_revoked(revoked_token, must_revoked=False)
return revoked_token
<|end_body_0|>
<|body_start_1|>
def predicate():
try:
self.get_token_validate(tok... | Token steps. | TokenSteps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TokenSteps:
"""Token steps."""
def revoke_token(self, token, check=True):
"""Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.AccessInfo: token"""
<|body_0|>
def check_token... | stack_v2_sparse_classes_36k_train_007844 | 4,425 | no_license | [
{
"docstring": "Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.AccessInfo: token",
"name": "revoke_token",
"signature": "def revoke_token(self, token, check=True)"
},
{
"docstring": "Step to check... | 4 | stack_v2_sparse_classes_30k_train_001083 | Implement the Python class `TokenSteps` described below.
Class description:
Token steps.
Method signatures and docstrings:
- def revoke_token(self, token, check=True): Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.Acc... | Implement the Python class `TokenSteps` described below.
Class description:
Token steps.
Method signatures and docstrings:
- def revoke_token(self, token, check=True): Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.Acc... | e7583444cd24893ec6ae237b47db7c605b99b0c5 | <|skeleton|>
class TokenSteps:
"""Token steps."""
def revoke_token(self, token, check=True):
"""Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.AccessInfo: token"""
<|body_0|>
def check_token... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TokenSteps:
"""Token steps."""
def revoke_token(self, token, check=True):
"""Step to revoke a token. Args: token (str): The token to be revoked. check (bool): flag whether to check step or not Returns: keystoneclient.access.AccessInfo: token"""
revoked_token = self._client.revoke_token(to... | the_stack_v2_python_sparse | stepler/keystone/steps/tokens.py | Mirantis/stepler | train | 16 |
37a00cc28e9012c07ef55ced741290f62404f5c8 | [
"classes = [cls]\nparameterschema = {'type': 'object', 'additionalProperties': False}\nwhile len(classes):\n curr_cls = classes.pop(0)\n classes.extend(curr_cls.__bases__)\n if not hasattr(curr_cls, 'arguments_structure'):\n continue\n add_parameterschema_argument(parameterschema, curr_cls.argume... | <|body_start_0|>
classes = [cls]
parameterschema = {'type': 'object', 'additionalProperties': False}
while len(classes):
curr_cls = classes.pop(0)
classes.extend(curr_cls.__bases__)
if not hasattr(curr_cls, 'arguments_structure'):
continue
... | Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line arguments or json config. | ArgumentsHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArgumentsHandler:
"""Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line arguments or json config."""
def for... | stack_v2_sparse_classes_36k_train_007845 | 17,901 | permissive | [
{
"docstring": "Creates parameter schema based on `arguments_structure` of class and its all parent classes. Returns ------- Dict : Parameter schema for the class.",
"name": "form_parameterschema",
"signature": "def form_parameterschema(cls) -> Dict"
},
{
"docstring": "Creates argparse parser ba... | 2 | stack_v2_sparse_classes_30k_train_000439 | Implement the Python class `ArgumentsHandler` described below.
Class description:
Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line ar... | Implement the Python class `ArgumentsHandler` described below.
Class description:
Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line ar... | 9ec31ca0da1ba4d3445b98c08a8de4da45a198a8 | <|skeleton|>
class ArgumentsHandler:
"""Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line arguments or json config."""
def for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArgumentsHandler:
"""Class responsible for creating parsers for arguments from command line or json configs. The child class should define its own `arguments_structure` and from_argparse/from_json methods so that it could be instantiated from command line arguments or json config."""
def form_parametersc... | the_stack_v2_python_sparse | kenning/utils/args_manager.py | antmicro/kenning | train | 55 |
1e99306d2916f977f93567f6069f0638d0fdee8f | [
"if pos_label not in (0, 1):\n raise ValueError('only {0, 1} are accepted for `pos_label`')\ny_true = convert_binary_labels(y_true).ravel()\nscore = _check_binary_score(score, pos_label)\nh = 1.0 - y_true * score\nh[h < 0] = 0.0\nreturn h",
"if pos_label not in (0, 1):\n raise ValueError('only {0, 1} are ac... | <|body_start_0|>
if pos_label not in (0, 1):
raise ValueError('only {0, 1} are accepted for `pos_label`')
y_true = convert_binary_labels(y_true).ravel()
score = _check_binary_score(score, pos_label)
h = 1.0 - y_true * score
h[h < 0] = 0.0
return h
<|end_body_0... | Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector machines. After converting the labels to {-1, +1}, then the hinge loss is def... | CLossHinge | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CLossHinge:
"""Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector machines. After converting the labels t... | stack_v2_sparse_classes_36k_train_007846 | 6,353 | permissive | [
{
"docstring": "Computes the value of the hinge loss function. Parameters ---------- y_true : CArray Ground truth (correct), targets. Vector-like array. score : CArray Outputs (predicted), targets. 2-D array of shape (n_samples, n_classes) or 1-D flat array of shape (n_samples,). If 1-D array, the probabilities... | 2 | null | Implement the Python class `CLossHinge` described below.
Class description:
Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector ... | Implement the Python class `CLossHinge` described below.
Class description:
Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector ... | 431373e65d8cfe2cb7cf042ce1a6c9519ea5a14a | <|skeleton|>
class CLossHinge:
"""Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector machines. After converting the labels t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CLossHinge:
"""Hinge Loss Function. The function computes the average distance between the model and the data using hinge loss, a one-sided metric that considers only prediction errors. Hinge loss is used in maximal margin classifiers such as support vector machines. After converting the labels to {-1, +1}, t... | the_stack_v2_python_sparse | src/secml/ml/classifiers/loss/c_loss_hinge.py | Cinofix/secml | train | 0 |
d01e533c15be3ffa5d7717e6909ec649a258309c | [
"self.__ops = ops\nself.__nops = len(ops)\nfor iop in range(self.__nops):\n if not isinstance(self.__ops[iop], operator):\n raise Exception('Elements of ops list must be of type operator')\nif self.__nops != len(dims):\n raise Exception('Number of dimensions (%d) must equal number of operators (%d)' % ... | <|body_start_0|>
self.__ops = ops
self.__nops = len(ops)
for iop in range(self.__nops):
if not isinstance(self.__ops[iop], operator):
raise Exception('Elements of ops list must be of type operator')
if self.__nops != len(dims):
raise Exception('Num... | A chain operator | chainop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class chainop:
"""A chain operator"""
def __init__(self, ops, dims):
"""chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},.... | stack_v2_sparse_classes_36k_train_007847 | 13,837 | no_license | [
{
"docstring": "chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},...] Note that the operators will be applied in the order they come in the list... | 4 | stack_v2_sparse_classes_30k_train_020130 | Implement the Python class `chainop` described below.
Class description:
A chain operator
Method signatures and docstrings:
- def __init__(self, ops, dims): chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of th... | Implement the Python class `chainop` described below.
Class description:
A chain operator
Method signatures and docstrings:
- def __init__(self, ops, dims): chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of th... | 32a303eddd13385d8778b8bb3b4fbbfbe78bea51 | <|skeleton|>
class chainop:
"""A chain operator"""
def __init__(self, ops, dims):
"""chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class chainop:
"""A chain operator"""
def __init__(self, ops, dims):
"""chainop constructor Parameters: ops - a list of operators to be chained dims - a list of dictionaries that contain the dimensions of the inputs and outputs of the arrays For example dims = [{'nrows': 10, 'ncols': 10},...] Note that... | the_stack_v2_python_sparse | opt/linopt/combops.py | ke0m/scaas | train | 2 |
c731af8fa4328a291e66766b9bf16f9a99a8a052 | [
"if not function:\n raise ArgumentError('No window function provided')\nif window_size < 1:\n raise ArgumentError('Window size should be >= 1')\nif not source_attribute:\n raise ArgumentError('Source attribute not specified')\nif not target_attribute:\n raise ArgumentError('Target attribute not specifie... | <|body_start_0|>
if not function:
raise ArgumentError('No window function provided')
if window_size < 1:
raise ArgumentError('Window size should be >= 1')
if not source_attribute:
raise ArgumentError('Source attribute not specified')
if not target_attr... | WindowFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowFunction:
def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label):
"""Creates a window function."""
<|body_0|>
def __call__(self, record):
"""Collects the source value. If the window for the `window_key` is filled, then ... | stack_v2_sparse_classes_36k_train_007848 | 8,406 | no_license | [
{
"docstring": "Creates a window function.",
"name": "__init__",
"signature": "def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label)"
},
{
"docstring": "Collects the source value. If the window for the `window_key` is filled, then apply the window funct... | 2 | stack_v2_sparse_classes_30k_train_008464 | Implement the Python class `WindowFunction` described below.
Class description:
Implement the WindowFunction class.
Method signatures and docstrings:
- def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label): Creates a window function.
- def __call__(self, record): Collects th... | Implement the Python class `WindowFunction` described below.
Class description:
Implement the WindowFunction class.
Method signatures and docstrings:
- def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label): Creates a window function.
- def __call__(self, record): Collects th... | 067f502154eefc4199ad3f3e0d54fad4acd2d274 | <|skeleton|>
class WindowFunction:
def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label):
"""Creates a window function."""
<|body_0|>
def __call__(self, record):
"""Collects the source value. If the window for the `window_key` is filled, then ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WindowFunction:
def __init__(self, function, window_key, target_attribute, source_attribute, window_size, label):
"""Creates a window function."""
if not function:
raise ArgumentError('No window function provided')
if window_size < 1:
raise ArgumentError('Window... | the_stack_v2_python_sparse | env/Lib/site-packages/cubes/statutils.py | wgiovanni/teg-backend-integration | train | 0 | |
b4ec57017ae83b2a6e36f965081115befbc706c7 | [
"self.assert_parse_received_correct_type(raw_value, str)\nif self.should_strip_input:\n return raw_value.strip()\nreturn raw_value",
"value = self.empty_value\nif raw_value is not UNSET:\n raw_value = self.parse_as_text(raw_value)\nif raw_value:\n value = raw_value\nreturn value"
] | <|body_start_0|>
self.assert_parse_received_correct_type(raw_value, str)
if self.should_strip_input:
return raw_value.strip()
return raw_value
<|end_body_0|>
<|body_start_1|>
value = self.empty_value
if raw_value is not UNSET:
raw_value = self.parse_as_te... | CharField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CharField:
def parse_as_text(self, raw_value):
"""Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `force_text` as an additional safety check. Strip the input based on `.should_strip_input`"""
... | stack_v2_sparse_classes_36k_train_007849 | 16,303 | permissive | [
{
"docstring": "Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `force_text` as an additional safety check. Strip the input based on `.should_strip_input`",
"name": "parse_as_text",
"signature": "def parse_as_text... | 2 | null | Implement the Python class `CharField` described below.
Class description:
Implement the CharField class.
Method signatures and docstrings:
- def parse_as_text(self, raw_value): Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `... | Implement the Python class `CharField` described below.
Class description:
Implement the CharField class.
Method signatures and docstrings:
- def parse_as_text(self, raw_value): Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `... | 8755e64c13e2b6f9bef9bbee47011253f20e7e0d | <|skeleton|>
class CharField:
def parse_as_text(self, raw_value):
"""Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `force_text` as an additional safety check. Strip the input based on `.should_strip_input`"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CharField:
def parse_as_text(self, raw_value):
"""Responsible for raising an error if the raw extracted value is not a string instance. If it recognizes the input as a string, use Django's `force_text` as an additional safety check. Strip the input based on `.should_strip_input`"""
self.assert... | the_stack_v2_python_sparse | formation/field_types.py | codeforamerica/intake | train | 51 | |
251ad93753c985faa78c2fd3e4807b6fd486ac80 | [
"if not nums:\n return []\ncnt = {}\nfor i in range(len(nums)):\n if nums[i] not in cnt:\n cnt[nums[i]] = 1\n else:\n cnt[nums[i]] += 1\nreturn [key for key, value in sorted(cnt.items(), key=lambda x: x[1], reverse=True)][:k]",
"counts = collections.Counter(nums)\nprint(counts)\nheap = []\n... | <|body_start_0|>
if not nums:
return []
cnt = {}
for i in range(len(nums)):
if nums[i] not in cnt:
cnt[nums[i]] = 1
else:
cnt[nums[i]] += 1
return [key for key, value in sorted(cnt.items(), key=lambda x: x[1], reverse=Tr... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def topKFrequent(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def topKFrequent2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_007850 | 1,371 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "topKFrequent",
"signature": "def topKFrequent(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: List[int]",
"name": "topKFrequent2",
"signature": "def topKFrequent2(self, nums, k)"... | 2 | stack_v2_sparse_classes_30k_train_013935 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def topKFrequent(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def topKFrequent2(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def topKFrequent(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
- def topKFrequent2(self, nums, k): :type nums: List[int] :type k: int :rtype: List[int]
<|... | 4960986edae561c1f9f32f3c97ce144f976d7844 | <|skeleton|>
class Solution:
def topKFrequent(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_0|>
def topKFrequent2(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def topKFrequent(self, nums, k):
""":type nums: List[int] :type k: int :rtype: List[int]"""
if not nums:
return []
cnt = {}
for i in range(len(nums)):
if nums[i] not in cnt:
cnt[nums[i]] = 1
else:
cnt... | the_stack_v2_python_sparse | hash_table/top_k_frequent_elements.py | AlexSchumi/Algorithms | train | 0 | |
c28878f7620d703a5c876272e0403f265ddd2004 | [
"pth = os.path.join(self.root, 'imagenet100.txt')\nif not os.path.isfile(pth):\n url = 'https://raw.githubusercontent.com/HobbitLong/CMC/master/imagenet100.txt'\n try:\n from urllib.request import urlretrieve\n urlretrieve(url, pth)\n except Exception:\n raise FileNotFoundError('File %... | <|body_start_0|>
pth = os.path.join(self.root, 'imagenet100.txt')
if not os.path.isfile(pth):
url = 'https://raw.githubusercontent.com/HobbitLong/CMC/master/imagenet100.txt'
try:
from urllib.request import urlretrieve
urlretrieve(url, pth)
... | ImageNet100Dataset | [
"LicenseRef-scancode-cecill-b-en"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageNet100Dataset:
def _extract_classes(self, all_classes=None):
""":param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 100 class names extracted from 'imagenet100.txt' sorted alphabetically"""
<|body_0|>
def _find_... | stack_v2_sparse_classes_36k_train_007851 | 19,654 | permissive | [
{
"docstring": ":param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 100 class names extracted from 'imagenet100.txt' sorted alphabetically",
"name": "_extract_classes",
"signature": "def _extract_classes(self, all_classes=None)"
},
{
"do... | 2 | null | Implement the Python class `ImageNet100Dataset` described below.
Class description:
Implement the ImageNet100Dataset class.
Method signatures and docstrings:
- def _extract_classes(self, all_classes=None): :param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 1... | Implement the Python class `ImageNet100Dataset` described below.
Class description:
Implement the ImageNet100Dataset class.
Method signatures and docstrings:
- def _extract_classes(self, all_classes=None): :param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 1... | 7a807ed690929563ce36086eaf0998d0e8856aea | <|skeleton|>
class ImageNet100Dataset:
def _extract_classes(self, all_classes=None):
""":param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 100 class names extracted from 'imagenet100.txt' sorted alphabetically"""
<|body_0|>
def _find_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageNet100Dataset:
def _extract_classes(self, all_classes=None):
""":param all_classes: list of all class names used to check if filtered class are inside them :return: a list of 100 class names extracted from 'imagenet100.txt' sorted alphabetically"""
pth = os.path.join(self.root, 'imagenet1... | the_stack_v2_python_sparse | pynet/datasets/imagenet.py | Duplums/pynet | train | 0 | |
3abb49531763c60f4767c32a85c2440ef42740d7 | [
"self.detect_language = detect_language\nself.callback_url = callback_url\nself.callback_method = callback_method\nself.username = username\nself.password = password\nself.tag = tag\nself.callback_timeout = callback_timeout",
"if dictionary is None:\n return None\ndetect_language = dictionary.get('detectLangua... | <|body_start_0|>
self.detect_language = detect_language
self.callback_url = callback_url
self.callback_method = callback_method
self.username = username
self.password = password
self.tag = tag
self.callback_timeout = callback_timeout
<|end_body_0|>
<|body_start_1... | Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to detect the dominant language the recording is in and transcribe accordingly. Current supported l... | TranscribeRecordingRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TranscribeRecordingRequest:
"""Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to detect the dominant language the recording... | stack_v2_sparse_classes_36k_train_007852 | 3,233 | permissive | [
{
"docstring": "Constructor for the TranscribeRecordingRequest class",
"name": "__init__",
"signature": "def __init__(self, detect_language=None, callback_url=None, callback_method=None, username=None, password=None, tag=None, callback_timeout=None)"
},
{
"docstring": "Creates an instance of thi... | 2 | null | Implement the Python class `TranscribeRecordingRequest` described below.
Class description:
Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to det... | Implement the Python class `TranscribeRecordingRequest` described below.
Class description:
Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to det... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class TranscribeRecordingRequest:
"""Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to detect the dominant language the recording... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TranscribeRecordingRequest:
"""Implementation of the 'TranscribeRecordingRequest' model. TODO: type model description here. Attributes: detect_language (bool): Indicates that the recording may not be in English, and the transcription service will need to detect the dominant language the recording is in and tr... | the_stack_v2_python_sparse | bandwidth/voice/models/transcribe_recording_request.py | Bandwidth/python-sdk | train | 10 |
080f763229dc6df2d2a54807ffab2b120f726c4e | [
"self.config = config\nprint(config)\nself.model = TiSASRec(config['model'])\nself.num_batch = config['model']['n_users'] // config['model']['batch_size']\nself.bce_criterion = torch.nn.BCEWithLogitsLoss()\nsuper(TiSASRecEngine, self).__init__(config)",
"assert hasattr(self, 'model'), 'Please specify the exact mo... | <|body_start_0|>
self.config = config
print(config)
self.model = TiSASRec(config['model'])
self.num_batch = config['model']['n_users'] // config['model']['batch_size']
self.bce_criterion = torch.nn.BCEWithLogitsLoss()
super(TiSASRecEngine, self).__init__(config)
<|end_bod... | Engine for training & evaluating TiSASRec model. | TiSASRecEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TiSASRecEngine:
"""Engine for training & evaluating TiSASRec model."""
def __init__(self, config):
"""Initialize TiSASRecEngine Class."""
<|body_0|>
def train_single_batch(self, batch_data, ratings=None):
"""Train the model in a single batch."""
<|body_1|... | stack_v2_sparse_classes_36k_train_007853 | 15,823 | permissive | [
{
"docstring": "Initialize TiSASRecEngine Class.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Train the model in a single batch.",
"name": "train_single_batch",
"signature": "def train_single_batch(self, batch_data, ratings=None)"
},
{
"docst... | 3 | stack_v2_sparse_classes_30k_train_011966 | Implement the Python class `TiSASRecEngine` described below.
Class description:
Engine for training & evaluating TiSASRec model.
Method signatures and docstrings:
- def __init__(self, config): Initialize TiSASRecEngine Class.
- def train_single_batch(self, batch_data, ratings=None): Train the model in a single batch.... | Implement the Python class `TiSASRecEngine` described below.
Class description:
Engine for training & evaluating TiSASRec model.
Method signatures and docstrings:
- def __init__(self, config): Initialize TiSASRecEngine Class.
- def train_single_batch(self, batch_data, ratings=None): Train the model in a single batch.... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class TiSASRecEngine:
"""Engine for training & evaluating TiSASRec model."""
def __init__(self, config):
"""Initialize TiSASRecEngine Class."""
<|body_0|>
def train_single_batch(self, batch_data, ratings=None):
"""Train the model in a single batch."""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TiSASRecEngine:
"""Engine for training & evaluating TiSASRec model."""
def __init__(self, config):
"""Initialize TiSASRecEngine Class."""
self.config = config
print(config)
self.model = TiSASRec(config['model'])
self.num_batch = config['model']['n_users'] // config... | the_stack_v2_python_sparse | beta_rec/models/tisasrec.py | beta-team/beta-recsys | train | 156 |
8276e1b589c31740fca51c035d2c0f21d9683078 | [
"if config is None:\n raise TypeError('Input parameter config is None')\nif not isinstance(config, StubConfiguration):\n raise TypeError('Input parameter config is not a StubConfiguration')\nself._config = config",
"path_split = service_name.split('.')\nmodule_name = '%s_client' % '.'.join(path_split[:-1])\... | <|body_start_0|>
if config is None:
raise TypeError('Input parameter config is None')
if not isinstance(config, StubConfiguration):
raise TypeError('Input parameter config is not a StubConfiguration')
self._config = config
<|end_body_0|>
<|body_start_1|>
path_spl... | Factory for client-side vAPI stubs | StubFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StubFactory:
"""Factory for client-side vAPI stubs"""
def __init__(self, config):
"""Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs"""
<|body_0|>
def create_stub(self, service_name):
"""Create... | stack_v2_sparse_classes_36k_train_007854 | 16,678 | no_license | [
{
"docstring": "Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Create a stub corresponding to the specified service name :type service_name: :... | 2 | null | Implement the Python class `StubFactory` described below.
Class description:
Factory for client-side vAPI stubs
Method signatures and docstrings:
- def __init__(self, config): Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs
- def create_stub(self, ... | Implement the Python class `StubFactory` described below.
Class description:
Factory for client-side vAPI stubs
Method signatures and docstrings:
- def __init__(self, config): Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs
- def create_stub(self, ... | 5d395700ab3d0d1d45b497e48beab8c366fca9f5 | <|skeleton|>
class StubFactory:
"""Factory for client-side vAPI stubs"""
def __init__(self, config):
"""Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs"""
<|body_0|>
def create_stub(self, service_name):
"""Create... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StubFactory:
"""Factory for client-side vAPI stubs"""
def __init__(self, config):
"""Initialize the stub factory :type config: :class:`StubConfiguration` :param config: Configuration data for vAPI stubs"""
if config is None:
raise TypeError('Input parameter config is None')
... | the_stack_v2_python_sparse | alexa-program/vmware/vapi/bindings/stub.py | taromurata/TDP2018_VMCAPI | train | 1 |
ad10a6b19597963f86834e618fa4dd179df85216 | [
"connection = client_object.connection\ncommand = 'get certificate api thumbprint'\npylogger.debug('Command to get manager thumbprint %s' % command)\nexpect_prompt = ['bytes*', '>']\nresult = connection.request(command, expect_prompt)\nstdout_lines = result.response_data.splitlines()\nthumbprint_index_in_output = 0... | <|body_start_0|>
connection = client_object.connection
command = 'get certificate api thumbprint'
pylogger.debug('Command to get manager thumbprint %s' % command)
expect_prompt = ['bytes*', '>']
result = connection.request(command, expect_prompt)
stdout_lines = result.res... | NSX70CRUDImpl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NSX70CRUDImpl:
def get_manager_thumbprint(cls, client_object):
"""Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager> show api certificate thumbprint f71250ab638c9939a91b0db1b89619a43a9cda44a2c8628167ce5327d44bd16f nim... | stack_v2_sparse_classes_36k_train_007855 | 2,819 | no_license | [
{
"docstring": "Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager> show api certificate thumbprint f71250ab638c9939a91b0db1b89619a43a9cda44a2c8628167ce5327d44bd16f nimbus-cloud-nsxmanager>",
"name": "get_manager_thumbprint",
"signatu... | 2 | null | Implement the Python class `NSX70CRUDImpl` described below.
Class description:
Implement the NSX70CRUDImpl class.
Method signatures and docstrings:
- def get_manager_thumbprint(cls, client_object): Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager... | Implement the Python class `NSX70CRUDImpl` described below.
Class description:
Implement the NSX70CRUDImpl class.
Method signatures and docstrings:
- def get_manager_thumbprint(cls, client_object): Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager... | 5b55817c050b637e2747084290f6206d2e622938 | <|skeleton|>
class NSX70CRUDImpl:
def get_manager_thumbprint(cls, client_object):
"""Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager> show api certificate thumbprint f71250ab638c9939a91b0db1b89619a43a9cda44a2c8628167ce5327d44bd16f nim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NSX70CRUDImpl:
def get_manager_thumbprint(cls, client_object):
"""Method to NSX manager thumbprint Sample output of the command 'show api certificate thumbprint': nimbus-cloud-nsxmanager> show api certificate thumbprint f71250ab638c9939a91b0db1b89619a43a9cda44a2c8628167ce5327d44bd16f nimbus-cloud-nsxm... | the_stack_v2_python_sparse | SystemTesting/pylib/vmware/nsx/manager/cli/nsx70_crud_impl.py | Cloudxtreme/MyProject | train | 0 | |
c0ddf5ca0ef1bc8e4b2a8c34e87b8fa2fba8a98b | [
"self.certificate = certificate\nself.exchange = exchange\nself.filer_id = filer_id\nself.password = password\nself.server_ip = server_ip\nself.username = username\nself.virtual_host = virtual_host",
"if dictionary is None:\n return None\ncertificate = dictionary.get('certificate')\nexchange = dictionary.get('... | <|body_start_0|>
self.certificate = certificate
self.exchange = exchange
self.filer_id = filer_id
self.password = password
self.server_ip = server_ip
self.username = username
self.virtual_host = virtual_host
<|end_body_0|>
<|body_start_1|>
if dictionary i... | Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (string): Specifies the password. server_ip (string): Specifies the server ip. userna... | AMQPTargetConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AMQPTargetConfig:
"""Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (string): Specifies the password. server_... | stack_v2_sparse_classes_36k_train_007856 | 2,660 | permissive | [
{
"docstring": "Constructor for the AMQPTargetConfig class",
"name": "__init__",
"signature": "def __init__(self, certificate=None, exchange=None, filer_id=None, password=None, server_ip=None, username=None, virtual_host=None)"
},
{
"docstring": "Creates an instance of this model from a dictiona... | 2 | stack_v2_sparse_classes_30k_train_010696 | Implement the Python class `AMQPTargetConfig` described below.
Class description:
Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (s... | Implement the Python class `AMQPTargetConfig` described below.
Class description:
Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (s... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class AMQPTargetConfig:
"""Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (string): Specifies the password. server_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AMQPTargetConfig:
"""Implementation of the 'AMQPTargetConfig' model. TODO: type description here. Attributes: certificate (string): Specifies the certificate. exchange (string): Specifies the exchange. filer_id (long|int): Specifies the filer id. password (string): Specifies the password. server_ip (string): ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/amqp_target_config.py | cohesity/management-sdk-python | train | 24 |
7102898c76ab92c702557deb0f20aa42967d2770 | [
"with mute_signals(post_save):\n profile = ProfileFactory(address=None)\nassert profile.address1 is None\nassert profile.address2 is None\nassert profile.address3 is None",
"with mute_signals(post_save):\n profile = ProfileFactory(address='')\nassert profile.address1 == ''\nassert profile.address2 == ''\nas... | <|body_start_0|>
with mute_signals(post_save):
profile = ProfileFactory(address=None)
assert profile.address1 is None
assert profile.address2 is None
assert profile.address3 is None
<|end_body_0|>
<|body_start_1|>
with mute_signals(post_save):
profile = P... | Tests for splitting a user's address field | ProfileAddressTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileAddressTests:
"""Tests for splitting a user's address field"""
def test_unset_address(self):
"""Test splitting an unset address"""
<|body_0|>
def test_empty_address(self):
"""Test splitting an empty address"""
<|body_1|>
def test_short_address... | stack_v2_sparse_classes_36k_train_007857 | 10,083 | permissive | [
{
"docstring": "Test splitting an unset address",
"name": "test_unset_address",
"signature": "def test_unset_address(self)"
},
{
"docstring": "Test splitting an empty address",
"name": "test_empty_address",
"signature": "def test_empty_address(self)"
},
{
"docstring": "Test split... | 4 | null | Implement the Python class `ProfileAddressTests` described below.
Class description:
Tests for splitting a user's address field
Method signatures and docstrings:
- def test_unset_address(self): Test splitting an unset address
- def test_empty_address(self): Test splitting an empty address
- def test_short_address(sel... | Implement the Python class `ProfileAddressTests` described below.
Class description:
Tests for splitting a user's address field
Method signatures and docstrings:
- def test_unset_address(self): Test splitting an unset address
- def test_empty_address(self): Test splitting an empty address
- def test_short_address(sel... | d6564caca0b7bbfd31e67a751564107fd17d6eb0 | <|skeleton|>
class ProfileAddressTests:
"""Tests for splitting a user's address field"""
def test_unset_address(self):
"""Test splitting an unset address"""
<|body_0|>
def test_empty_address(self):
"""Test splitting an empty address"""
<|body_1|>
def test_short_address... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileAddressTests:
"""Tests for splitting a user's address field"""
def test_unset_address(self):
"""Test splitting an unset address"""
with mute_signals(post_save):
profile = ProfileFactory(address=None)
assert profile.address1 is None
assert profile.address... | the_stack_v2_python_sparse | profiles/models_test.py | mitodl/micromasters | train | 35 |
a212d9d8608fcfbdfc79ea5c0289d97581e8ba04 | [
"self.__parser = argparse.ArgumentParser(description='Executes a configuration in kombi')\nself.__parser.add_argument('config', help='path for a configuration file or a directory containing configurations files.')\nself.__parser.add_argument('source', metavar='FILE', nargs='*', help='path for a file or directory. I... | <|body_start_0|>
self.__parser = argparse.ArgumentParser(description='Executes a configuration in kombi')
self.__parser.add_argument('config', help='path for a configuration file or a directory containing configurations files.')
self.__parser.add_argument('source', metavar='FILE', nargs='*', hel... | Runs a kombi configuration through command-line. | Cli | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cli:
"""Runs a kombi configuration through command-line."""
def __init__(self):
"""Create a cli object."""
<|body_0|>
def run(self, args, outStream=sys.stdout, errStream=subprocess.STDOUT):
"""Execute the configuration."""
<|body_1|>
def __loadCrawle... | stack_v2_sparse_classes_36k_train_007858 | 3,968 | permissive | [
{
"docstring": "Create a cli object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Execute the configuration.",
"name": "run",
"signature": "def run(self, args, outStream=sys.stdout, errStream=subprocess.STDOUT)"
},
{
"docstring": "Return the source c... | 3 | null | Implement the Python class `Cli` described below.
Class description:
Runs a kombi configuration through command-line.
Method signatures and docstrings:
- def __init__(self): Create a cli object.
- def run(self, args, outStream=sys.stdout, errStream=subprocess.STDOUT): Execute the configuration.
- def __loadCrawlers(s... | Implement the Python class `Cli` described below.
Class description:
Runs a kombi configuration through command-line.
Method signatures and docstrings:
- def __init__(self): Create a cli object.
- def run(self, args, outStream=sys.stdout, errStream=subprocess.STDOUT): Execute the configuration.
- def __loadCrawlers(s... | 046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4 | <|skeleton|>
class Cli:
"""Runs a kombi configuration through command-line."""
def __init__(self):
"""Create a cli object."""
<|body_0|>
def run(self, args, outStream=sys.stdout, errStream=subprocess.STDOUT):
"""Execute the configuration."""
<|body_1|>
def __loadCrawle... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cli:
"""Runs a kombi configuration through command-line."""
def __init__(self):
"""Create a cli object."""
self.__parser = argparse.ArgumentParser(description='Executes a configuration in kombi')
self.__parser.add_argument('config', help='path for a configuration file or a directo... | the_stack_v2_python_sparse | src/lib/kombi/Cli.py | kombiHQ/kombi | train | 2 |
6a0c7d909f128c2d51ec8a42d8d737accf8b91d2 | [
"if options is None:\n options = {}\nroot_dir = options.get('rootDir', os.environ['DEFAULT_CACHE_PATH'])\nif not os.path.isdir(root_dir):\n os.makedirs(root_dir, exist_ok=True)\nself.root_dir = root_dir\nself.ttl = ttl\nself.size = size",
"if not isinstance(key, str):\n raise ValueError('key must be stri... | <|body_start_0|>
if options is None:
options = {}
root_dir = options.get('rootDir', os.environ['DEFAULT_CACHE_PATH'])
if not os.path.isdir(root_dir):
os.makedirs(root_dir, exist_ok=True)
self.root_dir = root_dir
self.ttl = ttl
self.size = size
<|en... | FileSystemCache | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSystemCache:
def __init__(self, options=None, size=1000, ttl=1000):
"""docs"""
<|body_0|>
def set(self, key, value):
"""set or add a key and value to the cache :param key: str or int type of key :param value: pickled value :return:"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k_train_007859 | 2,737 | permissive | [
{
"docstring": "docs",
"name": "__init__",
"signature": "def __init__(self, options=None, size=1000, ttl=1000)"
},
{
"docstring": "set or add a key and value to the cache :param key: str or int type of key :param value: pickled value :return:",
"name": "set",
"signature": "def set(self, ... | 5 | null | Implement the Python class `FileSystemCache` described below.
Class description:
Implement the FileSystemCache class.
Method signatures and docstrings:
- def __init__(self, options=None, size=1000, ttl=1000): docs
- def set(self, key, value): set or add a key and value to the cache :param key: str or int type of key ... | Implement the Python class `FileSystemCache` described below.
Class description:
Implement the FileSystemCache class.
Method signatures and docstrings:
- def __init__(self, options=None, size=1000, ttl=1000): docs
- def set(self, key, value): set or add a key and value to the cache :param key: str or int type of key ... | 54f86662095e74ccd2ba59e928410725ae5bf354 | <|skeleton|>
class FileSystemCache:
def __init__(self, options=None, size=1000, ttl=1000):
"""docs"""
<|body_0|>
def set(self, key, value):
"""set or add a key and value to the cache :param key: str or int type of key :param value: pickled value :return:"""
<|body_1|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileSystemCache:
def __init__(self, options=None, size=1000, ttl=1000):
"""docs"""
if options is None:
options = {}
root_dir = options.get('rootDir', os.environ['DEFAULT_CACHE_PATH'])
if not os.path.isdir(root_dir):
os.makedirs(root_dir, exist_ok=True)
... | the_stack_v2_python_sparse | dtlpy/caches/filesystem_cache.py | dataloop-ai/dtlpy | train | 16 | |
e9d5f911db466574d83bbbdff41d017b178f8281 | [
"if not isinstance(shear_range, (list, tuple)) or len(shear_range) != 2:\n raise ValueError('shear_range argument must be list/tuple with two values!')\nself.shear_range = shear_range\nself.reference = reference\nself.lazy = lazy",
"shear_x = random.gauss(self.shear_range[0], self.shear_range[1])\nshear_y = ra... | <|body_start_0|>
if not isinstance(shear_range, (list, tuple)) or len(shear_range) != 2:
raise ValueError('shear_range argument must be list/tuple with two values!')
self.shear_range = shear_range
self.reference = reference
self.lazy = lazy
<|end_body_0|>
<|body_start_1|>
... | Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss. | RandomShear2D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomShear2D:
"""Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss."""
def __init__(self, shear_range, r... | stack_v2_sparse_classes_36k_train_007860 | 21,674 | permissive | [
{
"docstring": "Initialize a RandomShear2D object Arguments --------- shear_range : list or tuple Lower and Upper bounds on rotation parameter, in degrees. e.g. shear_range = (-10,10) will result in a random draw of the rotation parameters between -10 and 10 degrees reference : ANTsImage (optional but recommend... | 2 | null | Implement the Python class `RandomShear2D` described below.
Class description:
Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss.
M... | Implement the Python class `RandomShear2D` described below.
Class description:
Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss.
M... | 41f2dd3fcf72654f284dac1a9448033e963f0afb | <|skeleton|>
class RandomShear2D:
"""Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss."""
def __init__(self, shear_range, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomShear2D:
"""Apply a Shear2D transform to an image, but with the shear parameters randomly generated from a user-specified range. The range is determined by a mean (first parameter) and standard deviation (second parameter) via calls to random.gauss."""
def __init__(self, shear_range, reference=None... | the_stack_v2_python_sparse | ants/contrib/sampling/affine2d.py | ANTsX/ANTsPy | train | 483 |
28fdbff0af061fcdc4b58a724418db2d027abc6a | [
"recent = self.listRecentPaths()\nif path in recent:\n return\nrecent.append(path)\nif len(recent) > 10:\n recent = recent[-10:]\nrecent = op.pathsep.join(recent)\nfslsettings.write('fsleyes.recentFiles', recent)\nself.notify()",
"recent = fslsettings.read('fsleyes.recentFiles', None)\nif recent is None:\n ... | <|body_start_0|>
recent = self.listRecentPaths()
if path in recent:
return
recent.append(path)
if len(recent) > 10:
recent = recent[-10:]
recent = op.pathsep.join(recent)
fslsettings.write('fsleyes.recentFiles', recent)
self.notify()
<|end_... | The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance. | RecentPathManager | [
"BSD-3-Clause",
"CC-BY-3.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecentPathManager:
"""The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance."""
def recordPath(self, path):
"""Adds the giv... | stack_v2_sparse_classes_36k_train_007861 | 16,912 | permissive | [
{
"docstring": "Adds the given ``path`` to the recent files list.",
"name": "recordPath",
"signature": "def recordPath(self, path)"
},
{
"docstring": "Returns a list of recently loaded files.",
"name": "listRecentPaths",
"signature": "def listRecentPaths(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004124 | Implement the Python class `RecentPathManager` described below.
Class description:
The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance.
Method signatures a... | Implement the Python class `RecentPathManager` described below.
Class description:
The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance.
Method signatures a... | 46ccb4fe2b2346eb57576247f49714032b61307a | <|skeleton|>
class RecentPathManager:
"""The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance."""
def recordPath(self, path):
"""Adds the giv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecentPathManager:
"""The ``RecentPathManager`` is a simple class which provides access to a list of recently loaded files, and can notify registered listeners when that list changes. See the :attr:`recentPathManager` singleton instance."""
def recordPath(self, path):
"""Adds the given ``path`` t... | the_stack_v2_python_sparse | fsleyes/actions/loadoverlay.py | sanjayankur31/fsleyes | train | 1 |
1609c7618fce4de791b6ff624936bed7cbbc5917 | [
"ref_key_attributes = closest_neighbors(self.synthetic_dict.keys(), key_data)\nref_sensitive_attributes = []\nfor key in ref_key_attributes:\n ref_sensitive_attributes.extend(self.synthetic_dict[key])\nreturn majority(ref_sensitive_attributes)",
"ref_key_attributes = closest_neighbors(self.synthetic_dict.keys(... | <|body_start_0|>
ref_key_attributes = closest_neighbors(self.synthetic_dict.keys(), key_data)
ref_sensitive_attributes = []
for key in ref_key_attributes:
ref_sensitive_attributes.extend(self.synthetic_dict[key])
return majority(ref_sensitive_attributes)
<|end_body_0|>
<|bod... | The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The privacy score for each row in the real table will be calculated as the frequency that the tr... | GeneralizedCAPAttacker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneralizedCAPAttacker:
"""The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The privacy score for each row in the real tab... | stack_v2_sparse_classes_36k_train_007862 | 6,127 | permissive | [
{
"docstring": "Make a prediction of the sensitive data given keys. Args: key_data (tuple): The key data. Returns: tuple: The predicted sensitive data.",
"name": "predict",
"signature": "def predict(self, key_data)"
},
{
"docstring": "Score based on the belief of the attacker, in the form P(sens... | 2 | stack_v2_sparse_classes_30k_train_010532 | Implement the Python class `GeneralizedCAPAttacker` described below.
Class description:
The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The pri... | Implement the Python class `GeneralizedCAPAttacker` described below.
Class description:
The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The pri... | a4e05fd57edc990b716340cffaa969a61144062e | <|skeleton|>
class GeneralizedCAPAttacker:
"""The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The privacy score for each row in the real tab... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeneralizedCAPAttacker:
"""The GeneralizedCAP privacy attacker. It will find out all rows in synthetic table that are closest (in hamming distance) to the target key attributes, and predict the sensitive entry that appears most frequently among them. The privacy score for each row in the real table will be ca... | the_stack_v2_python_sparse | sdmetrics/single_table/privacy/cap.py | sdv-dev/SDMetrics | train | 170 |
46301e88ca00c2414752ddb3e5c5785876cd697b | [
"self.name = name\nif criteria is None:\n self.criteria = []\nelse:\n self.criteria = criteria\nself.color = color",
"all_indices = set()\nself.criteria.sort(key=lambda x: x.and_or, reverse=True)\nfor i, c in enumerate(self.criteria):\n indices = c.select(sca)\n m = c.and_or\n if m == 'and' and i >... | <|body_start_0|>
self.name = name
if criteria is None:
self.criteria = []
else:
self.criteria = criteria
self.color = color
<|end_body_0|>
<|body_start_1|>
all_indices = set()
self.criteria.sort(key=lambda x: x.and_or, reverse=True)
for i,... | this class represents a single label | CustomLabel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomLabel:
"""this class represents a single label"""
def __init__(self, name, criteria=None, color=None):
"""Args: name (str) criteria: list of LabelCriterion objects"""
<|body_0|>
def select_cells(self, sca):
"""Selects cells corresponding to the given label"... | stack_v2_sparse_classes_36k_train_007863 | 6,289 | no_license | [
{
"docstring": "Args: name (str) criteria: list of LabelCriterion objects",
"name": "__init__",
"signature": "def __init__(self, name, criteria=None, color=None)"
},
{
"docstring": "Selects cells corresponding to the given label",
"name": "select_cells",
"signature": "def select_cells(se... | 2 | stack_v2_sparse_classes_30k_train_001388 | Implement the Python class `CustomLabel` described below.
Class description:
this class represents a single label
Method signatures and docstrings:
- def __init__(self, name, criteria=None, color=None): Args: name (str) criteria: list of LabelCriterion objects
- def select_cells(self, sca): Selects cells correspondin... | Implement the Python class `CustomLabel` described below.
Class description:
this class represents a single label
Method signatures and docstrings:
- def __init__(self, name, criteria=None, color=None): Args: name (str) criteria: list of LabelCriterion objects
- def select_cells(self, sca): Selects cells correspondin... | a64425ca5bff57c3fe336e47fddf00fe2bbc1e75 | <|skeleton|>
class CustomLabel:
"""this class represents a single label"""
def __init__(self, name, criteria=None, color=None):
"""Args: name (str) criteria: list of LabelCriterion objects"""
<|body_0|>
def select_cells(self, sca):
"""Selects cells corresponding to the given label"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomLabel:
"""this class represents a single label"""
def __init__(self, name, criteria=None, color=None):
"""Args: name (str) criteria: list of LabelCriterion objects"""
self.name = name
if criteria is None:
self.criteria = []
else:
self.criteria... | the_stack_v2_python_sparse | uncurl_analysis/custom_cell_selection.py | yjzhang/uncurl_analysis | train | 1 |
847c02a4e39af8f9bebd87081d62aceeede77984 | [
"name = None\nif 'name' in kwargs:\n name = kwargs.pop('name')\nsuper().__init__(*args, **kwargs)\nif name:\n self.fields['file'].label = _(f'{name.title()} File')\n self.fields['file'].help_text = _(f'Select {name} file to upload')",
"file = self.cleaned_data['file']\nFileManager.validate(file)\nreturn ... | <|body_start_0|>
name = None
if 'name' in kwargs:
name = kwargs.pop('name')
super().__init__(*args, **kwargs)
if name:
self.fields['file'].label = _(f'{name.title()} File')
self.fields['file'].help_text = _(f'Select {name} file to upload')
<|end_body_0... | Step 1 of FileManagementFormView. | UploadFileForm | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadFileForm:
"""Step 1 of FileManagementFormView."""
def __init__(self, *args, **kwargs):
"""Update label and help_text."""
<|body_0|>
def clean_file(self):
"""Run tabular file validation. If anything is wrong with the file, it will raise ValidationError"""
... | stack_v2_sparse_classes_36k_train_007864 | 6,816 | permissive | [
{
"docstring": "Update label and help_text.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Run tabular file validation. If anything is wrong with the file, it will raise ValidationError",
"name": "clean_file",
"signature": "def clean_file(self... | 2 | stack_v2_sparse_classes_30k_train_015860 | Implement the Python class `UploadFileForm` described below.
Class description:
Step 1 of FileManagementFormView.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Update label and help_text.
- def clean_file(self): Run tabular file validation. If anything is wrong with the file, it will raise ... | Implement the Python class `UploadFileForm` described below.
Class description:
Step 1 of FileManagementFormView.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Update label and help_text.
- def clean_file(self): Run tabular file validation. If anything is wrong with the file, it will raise ... | e88a8e99a5f0b201c67a95cba097c729f090d5e2 | <|skeleton|>
class UploadFileForm:
"""Step 1 of FileManagementFormView."""
def __init__(self, *args, **kwargs):
"""Update label and help_text."""
<|body_0|>
def clean_file(self):
"""Run tabular file validation. If anything is wrong with the file, it will raise ValidationError"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadFileForm:
"""Step 1 of FileManagementFormView."""
def __init__(self, *args, **kwargs):
"""Update label and help_text."""
name = None
if 'name' in kwargs:
name = kwargs.pop('name')
super().__init__(*args, **kwargs)
if name:
self.fields[... | the_stack_v2_python_sparse | InvenTree/common/forms.py | inventree/InvenTree | train | 3,077 |
96e43b3c79f540436db71d0a3b5656f11cf04f70 | [
"self.pid = pid\nself.host = host\nself.port = port\nself.keys = keys\nself._prfs = {}",
"try:\n return self._prfs[bound]\nexcept KeyError:\n self._prfs[bound] = {}\n for subset, key in self.keys.items():\n self._prfs[bound][subset] = thresha.PRF(key, bound)\n return self._prfs[bound]",
"if s... | <|body_start_0|>
self.pid = pid
self.host = host
self.port = port
self.keys = keys
self._prfs = {}
<|end_body_0|>
<|body_start_1|>
try:
return self._prfs[bound]
except KeyError:
self._prfs[bound] = {}
for subset, key in self.ke... | Information about a party in the MPC protocol. | _Party | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Party:
"""Information about a party in the MPC protocol."""
def __init__(self, pid, host=None, port=None, keys=None):
"""Initialize a party with given party identity pid."""
<|body_0|>
def prfs(self, bound):
"""PRFs with codomain range(bound) for pseudorandom se... | stack_v2_sparse_classes_36k_train_007865 | 45,303 | permissive | [
{
"docstring": "Initialize a party with given party identity pid.",
"name": "__init__",
"signature": "def __init__(self, pid, host=None, port=None, keys=None)"
},
{
"docstring": "PRFs with codomain range(bound) for pseudorandom secret sharing. Return a mapping from sets of parties to PRFs.",
... | 3 | stack_v2_sparse_classes_30k_train_005032 | Implement the Python class `_Party` described below.
Class description:
Information about a party in the MPC protocol.
Method signatures and docstrings:
- def __init__(self, pid, host=None, port=None, keys=None): Initialize a party with given party identity pid.
- def prfs(self, bound): PRFs with codomain range(bound... | Implement the Python class `_Party` described below.
Class description:
Information about a party in the MPC protocol.
Method signatures and docstrings:
- def __init__(self, pid, host=None, port=None, keys=None): Initialize a party with given party identity pid.
- def prfs(self, bound): PRFs with codomain range(bound... | ae8e421fb840937ccd7c8d5c35a011e5eb2c63df | <|skeleton|>
class _Party:
"""Information about a party in the MPC protocol."""
def __init__(self, pid, host=None, port=None, keys=None):
"""Initialize a party with given party identity pid."""
<|body_0|>
def prfs(self, bound):
"""PRFs with codomain range(bound) for pseudorandom se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Party:
"""Information about a party in the MPC protocol."""
def __init__(self, pid, host=None, port=None, keys=None):
"""Initialize a party with given party identity pid."""
self.pid = pid
self.host = host
self.port = port
self.keys = keys
self._prfs = {}
... | the_stack_v2_python_sparse | server/mpyc/mpyc/runtime.py | Fluxmux/securefacematching | train | 4 |
01bc6c49b9c70bd1c5e8a6845fca7e5af15239ca | [
"start_index = 0\nend_index = len(filename)\nif filename.endswith('.py'):\n end_index = -3\nif filename[1] == ':':\n start_index = 2\nmodulename = filename[start_index:end_index]\nl = modulename.split(os.path.sep)\nmodulename = '.'.join(l)\nreturn modulename",
"m = self.filename_to_module(self.filename)\nm ... | <|body_start_0|>
start_index = 0
end_index = len(filename)
if filename.endswith('.py'):
end_index = -3
if filename[1] == ':':
start_index = 2
modulename = filename[start_index:end_index]
l = modulename.split(os.path.sep)
modulename = '.'.jo... | Build packages from wralea file Use 'register_package' function | PyPackageReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyPackageReader:
"""Build packages from wralea file Use 'register_package' function"""
def filename_to_module(self, filename):
"""Transform the filename ending with .py to the module name"""
<|body_0|>
def get_pkg_name(self):
"""Return the OpenAlea (uniq) full pa... | stack_v2_sparse_classes_36k_train_007866 | 29,195 | permissive | [
{
"docstring": "Transform the filename ending with .py to the module name",
"name": "filename_to_module",
"signature": "def filename_to_module(self, filename)"
},
{
"docstring": "Return the OpenAlea (uniq) full package name",
"name": "get_pkg_name",
"signature": "def get_pkg_name(self)"
... | 4 | stack_v2_sparse_classes_30k_train_017351 | Implement the Python class `PyPackageReader` described below.
Class description:
Build packages from wralea file Use 'register_package' function
Method signatures and docstrings:
- def filename_to_module(self, filename): Transform the filename ending with .py to the module name
- def get_pkg_name(self): Return the Op... | Implement the Python class `PyPackageReader` described below.
Class description:
Build packages from wralea file Use 'register_package' function
Method signatures and docstrings:
- def filename_to_module(self, filename): Transform the filename ending with .py to the module name
- def get_pkg_name(self): Return the Op... | d8322b1db73677ef821adc319ef578f6bec96a79 | <|skeleton|>
class PyPackageReader:
"""Build packages from wralea file Use 'register_package' function"""
def filename_to_module(self, filename):
"""Transform the filename ending with .py to the module name"""
<|body_0|>
def get_pkg_name(self):
"""Return the OpenAlea (uniq) full pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyPackageReader:
"""Build packages from wralea file Use 'register_package' function"""
def filename_to_module(self, filename):
"""Transform the filename ending with .py to the module name"""
start_index = 0
end_index = len(filename)
if filename.endswith('.py'):
... | the_stack_v2_python_sparse | src/pycropml/package.py | AgriculturalModelExchangeInitiative/PyCrop2ML | train | 10 |
0c0813e31c49d554d24899e597976eb6350f6bd3 | [
"self.acc = acc\nself.frame = frame\nself.app = app\nself.script = script\nself.word_ctx = self._getWordContext(x, y)",
"if not self.script or not self.script.speakWordUnderMouse(self.acc):\n return None\nword, start, end = self.script.getWordAtCoords(self.acc, x, y)\nreturn _WordContext(word, self.acc, start,... | <|body_start_0|>
self.acc = acc
self.frame = frame
self.app = app
self.script = script
self.word_ctx = self._getWordContext(x, y)
<|end_body_0|>
<|body_start_1|>
if not self.script or not self.script.speakWordUnderMouse(self.acc):
return None
word, st... | An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here. | _ItemContext | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ItemContext:
"""An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here."""
def __init__(self, x=0, y=0, acc=None, frame=None, app=None, script=None):
"""Initialize an _ItemCon... | stack_v2_sparse_classes_36k_train_007867 | 12,279 | no_license | [
{
"docstring": "Initialize an _ItemContext with all the information we have. Arguments: - x: The X coordinate of the pointer. - y: The Y coordinate of the pointer. - acc: The end-node accessible at that coordinate. - frame: The top-level frame below the pointer. - app: The application the pointer is hovering ab... | 2 | null | Implement the Python class `_ItemContext` described below.
Class description:
An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here.
Method signatures and docstrings:
- def __init__(self, x=0, y=0, acc=None, f... | Implement the Python class `_ItemContext` described below.
Class description:
An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here.
Method signatures and docstrings:
- def __init__(self, x=0, y=0, acc=None, f... | d08f7bf370a82b6970387bb9f165d374a9d9092b | <|skeleton|>
class _ItemContext:
"""An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here."""
def __init__(self, x=0, y=0, acc=None, frame=None, app=None, script=None):
"""Initialize an _ItemCon... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ItemContext:
"""An _ItemContext holds all the information of the item we are currently hovering above. If the accessible supports word speaking, we also store a word context here."""
def __init__(self, x=0, y=0, acc=None, frame=None, app=None, script=None):
"""Initialize an _ItemContext with all... | the_stack_v2_python_sparse | usr/share/python-support/gnome-orca/orca/mouse_review.py | haniokasai/netwalker-rootfs | train | 2 |
76acccb5facaa79724457ed963b8ee3f82a89c94 | [
"tmpl_context.widget = new_fase_form\nheader_file = 'abstract'\nself.params['title'] = 'Nueva Fase'\nself.params['modelname'] = 'Fase'\nself.params['header_file'] = 'abstract'\nself.params['permiso'] = 'crear_fase'\nself.params['cancelar_url'] = '/miproyecto/ver/' + str(idproyecto)\nreturn dict(value=kw, params=sel... | <|body_start_0|>
tmpl_context.widget = new_fase_form
header_file = 'abstract'
self.params['title'] = 'Nueva Fase'
self.params['modelname'] = 'Fase'
self.params['header_file'] = 'abstract'
self.params['permiso'] = 'crear_fase'
self.params['cancelar_url'] = '/miproy... | Controlador de las fases del proyecto | FaseController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaseController:
"""Controlador de las fases del proyecto"""
def new(self, idproyecto, args={}, **kw):
"""Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de crear @type idproyecto : Integer @param idproyecto : Iden... | stack_v2_sparse_classes_36k_train_007868 | 6,423 | no_license | [
{
"docstring": "Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de crear @type idproyecto : Integer @param idproyecto : Identificador del Proyecto. @type args : Hash @param args : Argumentos de template @type kw : Hash @param kw : Keywords @... | 6 | stack_v2_sparse_classes_30k_train_006533 | Implement the Python class `FaseController` described below.
Class description:
Controlador de las fases del proyecto
Method signatures and docstrings:
- def new(self, idproyecto, args={}, **kw): Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de ... | Implement the Python class `FaseController` described below.
Class description:
Controlador de las fases del proyecto
Method signatures and docstrings:
- def new(self, idproyecto, args={}, **kw): Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de ... | f3da55a822dd45ed577844479c58eea69cdad754 | <|skeleton|>
class FaseController:
"""Controlador de las fases del proyecto"""
def new(self, idproyecto, args={}, **kw):
"""Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de crear @type idproyecto : Integer @param idproyecto : Iden... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FaseController:
"""Controlador de las fases del proyecto"""
def new(self, idproyecto, args={}, **kw):
"""Encargado de cargar el widget para crear nuevas instancias, solo tienen acceso aquellos usuarios que posean el premiso de crear @type idproyecto : Integer @param idproyecto : Identificador del... | the_stack_v2_python_sparse | Tg-SAP/sap/controllers/fase.py | mbaez/SAP | train | 1 |
606b20d61989f236fcd05885436e84495a70d594 | [
"super().__init__()\nself.blocks = nn.ModuleList()\ninput_channels = num_input_channels\nfor output_channels in layer_output_channels:\n self.blocks.append(nn.ModuleList([nn.Sequential(nn.Conv2d(input_channels, output_channels, 3, 1, padding=1, bias=False), nn.BatchNorm2d(output_channels), nn.ReLU(), nn.Conv2d(o... | <|body_start_0|>
super().__init__()
self.blocks = nn.ModuleList()
input_channels = num_input_channels
for output_channels in layer_output_channels:
self.blocks.append(nn.ModuleList([nn.Sequential(nn.Conv2d(input_channels, output_channels, 3, 1, padding=1, bias=False), nn.Batc... | Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Number of channels in the input images. layer_output_channels (list): A list of int... | UnetEncoder | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnetEncoder:
"""Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Number of channels in the input images. laye... | stack_v2_sparse_classes_36k_train_007869 | 14,906 | permissive | [
{
"docstring": "Initialize :class:`UnetEncoder`.",
"name": "__init__",
"signature": "def __init__(self, num_input_channels: int, layer_output_channels: list[int]) -> None"
},
{
"docstring": "Logic for using layers defined in init. This method defines how layers are used in forward operation. Arg... | 2 | stack_v2_sparse_classes_30k_train_003100 | Implement the Python class `UnetEncoder` described below.
Class description:
Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Numbe... | Implement the Python class `UnetEncoder` described below.
Class description:
Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Numbe... | f26387f46f675a7b9a8a48c95dad26e819229f2f | <|skeleton|>
class UnetEncoder:
"""Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Number of channels in the input images. laye... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UnetEncoder:
"""Construct a basic UNet encoder. This class builds a basic UNet encoder with batch normalization. The number of channels in each down-sampling block and the number of down-sampling levels are customisable. Args: num_input_channels (int): Number of channels in the input images. layer_output_chan... | the_stack_v2_python_sparse | tiatoolbox/models/architecture/unet.py | TissueImageAnalytics/tiatoolbox | train | 222 |
ff97b4f78d97d2ef13d21f60b8704045c1f5755c | [
"json_response = []\ncomments_query = self.sess.query(Comment).filter_by(problem_id=problem_id).all()\nif not comments_query:\n self.write(json.dumps(json_response))\n return\nfor comment_query in comments_query:\n user_query = self.sess.query(User).get(comment_query.user_id)\n if comment_query.modified... | <|body_start_0|>
json_response = []
comments_query = self.sess.query(Comment).filter_by(problem_id=problem_id).all()
if not comments_query:
self.write(json.dumps(json_response))
return
for comment_query in comments_query:
user_query = self.sess.query(U... | ProblemCommentsHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProblemCommentsHandler:
def get(self, problem_id):
"""Return comments for current problem. Answer format: .. code-block: json { "count": <count of data elements>, "data": [ { "modified_date": "2015-06-25T22:30:49.000Z", "modified_by": "user_1", "created_by": "user_2", "content": "comment... | stack_v2_sparse_classes_36k_train_007870 | 4,646 | no_license | [
{
"docstring": "Return comments for current problem. Answer format: .. code-block: json { \"count\": <count of data elements>, \"data\": [ { \"modified_date\": \"2015-06-25T22:30:49.000Z\", \"modified_by\": \"user_1\", \"created_by\": \"user_2\", \"content\": \"comment_1_content\", \"created_date\": \"2015-06-2... | 2 | stack_v2_sparse_classes_30k_train_001950 | Implement the Python class `ProblemCommentsHandler` described below.
Class description:
Implement the ProblemCommentsHandler class.
Method signatures and docstrings:
- def get(self, problem_id): Return comments for current problem. Answer format: .. code-block: json { "count": <count of data elements>, "data": [ { "m... | Implement the Python class `ProblemCommentsHandler` described below.
Class description:
Implement the ProblemCommentsHandler class.
Method signatures and docstrings:
- def get(self, problem_id): Return comments for current problem. Answer format: .. code-block: json { "count": <count of data elements>, "data": [ { "m... | e911ce6bcaa73e15248586d40c95beeb1a05da47 | <|skeleton|>
class ProblemCommentsHandler:
def get(self, problem_id):
"""Return comments for current problem. Answer format: .. code-block: json { "count": <count of data elements>, "data": [ { "modified_date": "2015-06-25T22:30:49.000Z", "modified_by": "user_1", "created_by": "user_2", "content": "comment... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProblemCommentsHandler:
def get(self, problem_id):
"""Return comments for current problem. Answer format: .. code-block: json { "count": <count of data elements>, "data": [ { "modified_date": "2015-06-25T22:30:49.000Z", "modified_by": "user_1", "created_by": "user_2", "content": "comment_1_content", "... | the_stack_v2_python_sparse | ecomap/api/v1_0/handlers/comments.py | ITsvetkoFF/Kv-008 | train | 3 | |
e6f852078244dd609b1abaf24f71ee0a0233eb22 | [
"elems = [e for row in matrix for e in row]\n\ndef search():\n left, right = (0, len(elems) - 1)\n while left <= right:\n mid = left + (right - left) / 2\n if elems[mid] == target:\n return True\n elif elems[mid] < target:\n left = mid + 1\n else:\n ... | <|body_start_0|>
elems = [e for row in matrix for e in row]
def search():
left, right = (0, len(elems) - 1)
while left <= right:
mid = left + (right - left) / 2
if elems[mid] == target:
return True
elif elems[mi... | 编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 13 输出: false | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 13 输出: false"""
d... | stack_v2_sparse_classes_36k_train_007871 | 4,231 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool 暴力破解：将二维数组转成一维有序数组，然后使用二分查找判断target是否在其中 时间复杂度：遍历二维数组O(m*n)，二分查找O(log(m*n))，因此最终的时间复杂度为O(m*n) 空间复杂度：O(m*n)",
"name": "search_matrix",
"signature": "def search_matrix(self, matrix, target)"
},
{
"docstring": ":type matri... | 3 | null | Implement the Python class `Solution` described below.
Class description:
编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34... | Implement the Python class `Solution` described below.
Class description:
编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34... | 2c534185854c1a6f5ffdb2698f9db9989f30a25b | <|skeleton|>
class Solution:
"""编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 13 输出: false"""
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""编写一个高效的算法来判断 m x n 矩阵中，是否存在一个目标值。该矩阵具有如下特性： 1. 每行中的整数从左到右按升序排列。 2. 每行的第一个整数大于前一行的最后一个整数。 示例 1: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 3 输出: true 示例 2: 输入: matrix = [ [1, 3, 5, 7], [10, 11, 16, 20], [23, 30, 34, 50] ] target = 13 输出: false"""
def search_mat... | the_stack_v2_python_sparse | Week 03/id_668/leetcode_74_668.py | Carryours/algorithm004-03 | train | 2 |
4173a20e82302795abb156d9058f1fa362e74c82 | [
"urls = super(PhotoFrameAdmin, self).get_urls()\nmy_urls = patterns('', url('^add_fotos/(?P<app>[\\\\w]+)/(?P<model>[\\\\w]+)/(?P<id>\\\\d+)?$', self.admin_site.admin_view(self.add_fotos), name='admin_add_fotos'), url('^ajax_edit_foto/$', self.admin_site.admin_view(self.ajax_edit_foto), name='admin_ajax_edit_foto')... | <|body_start_0|>
urls = super(PhotoFrameAdmin, self).get_urls()
my_urls = patterns('', url('^add_fotos/(?P<app>[\\w]+)/(?P<model>[\\w]+)/(?P<id>\\d+)?$', self.admin_site.admin_view(self.add_fotos), name='admin_add_fotos'), url('^ajax_edit_foto/$', self.admin_site.admin_view(self.ajax_edit_foto), name='a... | Modelo para subir fotos usando el widget en un iframe mediante ajax | PhotoFrameAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PhotoFrameAdmin:
"""Modelo para subir fotos usando el widget en un iframe mediante ajax"""
def get_urls(self):
"""URLs para subir fotos y borrarlas"""
<|body_0|>
def add_fotos(self, request, app, model, id):
"""página que muestra la herramienta para subir y edita... | stack_v2_sparse_classes_36k_train_007872 | 2,780 | no_license | [
{
"docstring": "URLs para subir fotos y borrarlas",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "página que muestra la herramienta para subir y editar fotos",
"name": "add_fotos",
"signature": "def add_fotos(self, request, app, model, id)"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_002961 | Implement the Python class `PhotoFrameAdmin` described below.
Class description:
Modelo para subir fotos usando el widget en un iframe mediante ajax
Method signatures and docstrings:
- def get_urls(self): URLs para subir fotos y borrarlas
- def add_fotos(self, request, app, model, id): página que muestra la herramien... | Implement the Python class `PhotoFrameAdmin` described below.
Class description:
Modelo para subir fotos usando el widget en un iframe mediante ajax
Method signatures and docstrings:
- def get_urls(self): URLs para subir fotos y borrarlas
- def add_fotos(self, request, app, model, id): página que muestra la herramien... | 872e7deca73ccd8417d0d963a043cb2e79d64ffb | <|skeleton|>
class PhotoFrameAdmin:
"""Modelo para subir fotos usando el widget en un iframe mediante ajax"""
def get_urls(self):
"""URLs para subir fotos y borrarlas"""
<|body_0|>
def add_fotos(self, request, app, model, id):
"""página que muestra la herramienta para subir y edita... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PhotoFrameAdmin:
"""Modelo para subir fotos usando el widget en un iframe mediante ajax"""
def get_urls(self):
"""URLs para subir fotos y borrarlas"""
urls = super(PhotoFrameAdmin, self).get_urls()
my_urls = patterns('', url('^add_fotos/(?P<app>[\\w]+)/(?P<model>[\\w]+)/(?P<id>\\d... | the_stack_v2_python_sparse | adminphotoload/models.py | ljarufe/quimerahg | train | 0 |
8f6ed2d4688ce647416f63e216a040a65d7e44a0 | [
"result = Statistics()\nassert result.num_games == 0\nassert len(result.metrics) == 8",
"stat_tracker = Statistics()\nstat_tracker.add_result(example_medium_game_result)\ncorrect = [4, 4, 0, 0, 0, 0, 0, 1]\ntotal = [6, 6, 1, 1, 1, 1, 1, 1]\nassert stat_tracker.num_games == 1\nassert [metric.correct for metric in ... | <|body_start_0|>
result = Statistics()
assert result.num_games == 0
assert len(result.metrics) == 8
<|end_body_0|>
<|body_start_1|>
stat_tracker = Statistics()
stat_tracker.add_result(example_medium_game_result)
correct = [4, 4, 0, 0, 0, 0, 0, 1]
total = [6, 6, 1... | Tests for the Statistics class. | TestStatistics | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestStatistics:
"""Tests for the Statistics class."""
def test_constructor() -> None:
"""Should initialize correctly."""
<|body_0|>
def test_add_result(example_medium_game_result: GameResult) -> None:
"""Should correctly add a single game result to the aggregate.... | stack_v2_sparse_classes_36k_train_007873 | 4,589 | permissive | [
{
"docstring": "Should initialize correctly.",
"name": "test_constructor",
"signature": "def test_constructor() -> None"
},
{
"docstring": "Should correctly add a single game result to the aggregate.",
"name": "test_add_result",
"signature": "def test_add_result(example_medium_game_resul... | 3 | null | Implement the Python class `TestStatistics` described below.
Class description:
Tests for the Statistics class.
Method signatures and docstrings:
- def test_constructor() -> None: Should initialize correctly.
- def test_add_result(example_medium_game_result: GameResult) -> None: Should correctly add a single game res... | Implement the Python class `TestStatistics` described below.
Class description:
Tests for the Statistics class.
Method signatures and docstrings:
- def test_constructor() -> None: Should initialize correctly.
- def test_add_result(example_medium_game_result: GameResult) -> None: Should correctly add a single game res... | 6e91c2f24e72f9374c4f703bd966963ea6626e8e | <|skeleton|>
class TestStatistics:
"""Tests for the Statistics class."""
def test_constructor() -> None:
"""Should initialize correctly."""
<|body_0|>
def test_add_result(example_medium_game_result: GameResult) -> None:
"""Should correctly add a single game result to the aggregate.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestStatistics:
"""Tests for the Statistics class."""
def test_constructor() -> None:
"""Should initialize correctly."""
result = Statistics()
assert result.num_games == 0
assert len(result.metrics) == 8
def test_add_result(example_medium_game_result: GameResult) -> N... | the_stack_v2_python_sparse | unit_test/stats_test.py | srijan-deepsource/wolfbot | train | 0 |
312588e7ffe7dd1fc6b11cd866583e8563f9c34f | [
"if m >= n:\n return head\nparent = None\np = head\nfor _ in range(m - 1):\n parent = p\n p = p.next\nt = p\ntmp = p.next\nchild = tmp\nfor _ in range(n - m):\n child = tmp\n if child:\n tmp = child.next\n child.next = p\n p = child\n else:\n break\nt.next = tmp\nif par... | <|body_start_0|>
if m >= n:
return head
parent = None
p = head
for _ in range(m - 1):
parent = p
p = p.next
t = p
tmp = p.next
child = tmp
for _ in range(n - m):
child = tmp
if child:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
<|body_0|>
def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]:
"""08/08/2021 17:38"""
<|body_1|>
def reverseBetween(self, head: Optional[L... | stack_v2_sparse_classes_36k_train_007874 | 3,687 | no_license | [
{
"docstring": "05/06/2018 01:00",
"name": "reverseBetween",
"signature": "def reverseBetween(self, head, m, n)"
},
{
"docstring": "08/08/2021 17:38",
"name": "reverseBetween",
"signature": "def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]"
... | 3 | stack_v2_sparse_classes_30k_train_015047 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): 05/06/2018 01:00
- def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: 08/08/2021 17:38
- def r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseBetween(self, head, m, n): 05/06/2018 01:00
- def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]: 08/08/2021 17:38
- def r... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
<|body_0|>
def reverseBetween(self, head: Optional[ListNode], left: int, right: int) -> Optional[ListNode]:
"""08/08/2021 17:38"""
<|body_1|>
def reverseBetween(self, head: Optional[L... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseBetween(self, head, m, n):
"""05/06/2018 01:00"""
if m >= n:
return head
parent = None
p = head
for _ in range(m - 1):
parent = p
p = p.next
t = p
tmp = p.next
child = tmp
for _ in ... | the_stack_v2_python_sparse | leetcode/solved/92_Reverse_Linked_List_II/solution.py | sungminoh/algorithms | train | 0 | |
fad7bcfc3cad488dcc8ecfc419219d994157af07 | [
"if not matrix or not matrix[0]:\n return\nrow, col = (len(matrix), len(matrix[0]))\nself.mtx = [[0] * (col + 1) for _ in range(row + 1)]\nfor r in range(row):\n for c in range(col):\n self.mtx[r + 1][c + 1] = self.mtx[r][c + 1] + self.mtx[r + 1][c] - self.mtx[r][c] + matrix[r][c]\nprint(self.mtx)",
... | <|body_start_0|>
if not matrix or not matrix[0]:
return
row, col = (len(matrix), len(matrix[0]))
self.mtx = [[0] * (col + 1) for _ in range(row + 1)]
for r in range(row):
for c in range(col):
self.mtx[r + 1][c + 1] = self.mtx[r][c + 1] + self.mtx[r... | NumMatrix_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix_1:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int 59ms"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_007875 | 2,823 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int 59ms",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col... | 2 | null | Implement the Python class `NumMatrix_1` described below.
Class description:
Implement the NumMatrix_1 class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rt... | Implement the Python class `NumMatrix_1` described below.
Class description:
Implement the NumMatrix_1 class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rt... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class NumMatrix_1:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int 59ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix_1:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if not matrix or not matrix[0]:
return
row, col = (len(matrix), len(matrix[0]))
self.mtx = [[0] * (col + 1) for _ in range(row + 1)]
for r in range(row):
for c in range(... | the_stack_v2_python_sparse | RangeSumQuery2D_Immutable_MID_304.py | 953250587/leetcode-python | train | 2 | |
20e841202d99ae745f8555313623f54e72a9f1fc | [
"payload = cls.payload_for_create(type, value)\nbase_doc = base_document.update(virtual_documents=[payload])\nvirtual_doc = [doc for doc in base_doc.virtual_documents if doc.type == type][0]\nreturn virtual_doc",
"doc = super(VirtualDocument, cls).from_response(response)\nif response.get('status') == 'SUBMITTED|M... | <|body_start_0|>
payload = cls.payload_for_create(type, value)
base_doc = base_document.update(virtual_documents=[payload])
virtual_doc = [doc for doc in base_doc.virtual_documents if doc.type == type][0]
return virtual_doc
<|end_body_0|>
<|body_start_1|>
doc = super(VirtualDocu... | Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types | VirtualDocument | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VirtualDocument:
"""Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types"""
def create(cls, base_document, type=None, value=None):... | stack_v2_sparse_classes_36k_train_007876 | 2,913 | permissive | [
{
"docstring": "Add a VirtualDocument to the BaseDocument. Args: type (str): https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types value (str): SSN or TIN, for example Returns: VirtualDocument: a new VirtualDocument instance",
"name": "create",
"signature": "def create(cls, base... | 4 | stack_v2_sparse_classes_30k_train_011562 | Implement the Python class `VirtualDocument` described below.
Class description:
Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types
Method signatures and ... | Implement the Python class `VirtualDocument` described below.
Class description:
Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types
Method signatures and ... | e7647191b386bdda84c0f2f1eb097569e36c27ae | <|skeleton|>
class VirtualDocument:
"""Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types"""
def create(cls, base_document, type=None, value=None):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VirtualDocument:
"""Object representation of a supporting virtual document. Virtual documents are normally ID numbers that help verify the user's identity. https://docs.synapsepay.com/docs/user-resources#section-virtual-document-types"""
def create(cls, base_document, type=None, value=None):
"""A... | the_stack_v2_python_sparse | synapse_pay_rest/models/users/virtual_document.py | SynapseFI/SynapseFI-Python | train | 4 |
39fa9fa2c3fbc41dfded2200a7a87a423d3dbf93 | [
"try:\n from bigdl.llm.transformers import AutoModel\n from transformers import AutoTokenizer, LlamaTokenizer\nexcept ImportError:\n raise ValueError('Could not import transformers python package. Please install it with `pip install transformers`.')\n_model_kwargs = model_kwargs or {}\ntry:\n tokenizer ... | <|body_start_0|>
try:
from bigdl.llm.transformers import AutoModel
from transformers import AutoTokenizer, LlamaTokenizer
except ImportError:
raise ValueError('Could not import transformers python package. Please install it with `pip install transformers`.')
_... | Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embeddings = TransformersEmbeddings.from_model_id(model_id) | TransformersEmbeddings | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformersEmbeddings:
"""Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embeddings = TransformersEmbeddings.from_mode... | stack_v2_sparse_classes_36k_train_007877 | 5,917 | permissive | [
{
"docstring": "Construct object from model_id",
"name": "from_model_id",
"signature": "def from_model_id(cls, model_id: str, model_kwargs: Optional[dict]=None, **kwargs: Any)"
},
{
"docstring": "Compute doc embeddings using a HuggingFace transformer model. Args: texts: The list of texts to embe... | 4 | null | Implement the Python class `TransformersEmbeddings` described below.
Class description:
Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embedd... | Implement the Python class `TransformersEmbeddings` described below.
Class description:
Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embedd... | 4ffa012a426e0d16ed13b707b03d8787ddca6aa4 | <|skeleton|>
class TransformersEmbeddings:
"""Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embeddings = TransformersEmbeddings.from_mode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformersEmbeddings:
"""Wrapper around bigdl-llm transformers embedding models. To use, you should have the ``transformers`` python package installed. Example: .. code-block:: python from bigdl.llm.langchain.embeddings import TransformersEmbeddings embeddings = TransformersEmbeddings.from_model_id(model_id... | the_stack_v2_python_sparse | python/llm/src/bigdl/llm/langchain/embeddings/transformersembeddings.py | intel-analytics/BigDL | train | 4,913 |
63bbe4ebda6c4ec097ba6b494b067d9bbbfc7a95 | [
"i, j = (len(S) - 1, len(T) - 1)\nwhile True:\n bs = 0\n while i >= 0 and (S[i] == '#' or bs > 0):\n if S[i] == '#':\n bs += 1\n else:\n bs -= 1\n i -= 1\n while j >= 0 and (T[j] == '#' or bs > 0):\n if T[j] == '#':\n bs += 1\n else:\n ... | <|body_start_0|>
i, j = (len(S) - 1, len(T) - 1)
while True:
bs = 0
while i >= 0 and (S[i] == '#' or bs > 0):
if S[i] == '#':
bs += 1
else:
bs -= 1
i -= 1
while j >= 0 and (T[j] ==... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i, j = (len(S) - 1, len(T... | stack_v2_sparse_classes_36k_train_007878 | 1,311 | no_license | [
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare",
"signature": "def backspaceCompare(self, S, T)"
},
{
"docstring": ":type S: str :type T: str :rtype: bool",
"name": "backspaceCompare",
"signature": "def backspaceCompare(self, S, T)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
- def backspaceCompare(self, S, T): :type S: str :type T: str :rtype: bool
<|skeleton|>
class Solution:
... | c27f19fac14b4acef8c631ad5569e1a5c29e9e1f | <|skeleton|>
class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_0|>
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def backspaceCompare(self, S, T):
""":type S: str :type T: str :rtype: bool"""
i, j = (len(S) - 1, len(T) - 1)
while True:
bs = 0
while i >= 0 and (S[i] == '#' or bs > 0):
if S[i] == '#':
bs += 1
else... | the_stack_v2_python_sparse | leetcode/p0844 - Backspace String Compare.py | liseyko/CtCI | train | 0 | |
319b5d45886ad147530a86f5b52e5048ce1a62db | [
"comp = lambda a, b: 1 if a + b > b + a else -1\nnum_to_str = map(str, nums)\nnum_to_str.sort(cmp=comp, reverse=True)\nlargest = ''\nfor i in xrange(len(num_to_str)):\n largest = ''.join([largest, num_to_str[i]])\nif largest[0] == '0':\n return '0'\nprint(largest)\nreturn largest",
"def cmp(a, b):\n if a... | <|body_start_0|>
comp = lambda a, b: 1 if a + b > b + a else -1
num_to_str = map(str, nums)
num_to_str.sort(cmp=comp, reverse=True)
largest = ''
for i in xrange(len(num_to_str)):
largest = ''.join([largest, num_to_str[i]])
if largest[0] == '0':
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_0|>
def largestNumber2(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
comp = lambda a, b: 1 if a + b > b + a e... | stack_v2_sparse_classes_36k_train_007879 | 1,394 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: str",
"name": "largestNumber",
"signature": "def largestNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: str",
"name": "largestNumber2",
"signature": "def largestNumber2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestNumber(self, nums): :type nums: List[int] :rtype: str
- def largestNumber2(self, nums): :type nums: List[int] :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestNumber(self, nums): :type nums: List[int] :rtype: str
- def largestNumber2(self, nums): :type nums: List[int] :rtype: str
<|skeleton|>
class Solution:
def larges... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_0|>
def largestNumber2(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
comp = lambda a, b: 1 if a + b > b + a else -1
num_to_str = map(str, nums)
num_to_str.sort(cmp=comp, reverse=True)
largest = ''
for i in xrange(len(num_to_str)):
largest... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00179.Largest Number.py | roger6blog/LeetCode | train | 0 | |
ebcb97e058c714c3c336aa38be84fa4228d4f6f6 | [
"if not root:\n return []\nres = []\nqueue = [root]\nwhile queue:\n level_node = []\n temp = []\n for i in queue:\n level_node.append(i.val)\n if i.left:\n temp.append(i.left)\n if i.right:\n temp.append(i.right)\n res.append(level_node)\n queue = temp\nr... | <|body_start_0|>
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.append(i.val)
if i.left:
temp.append(i.left)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return []... | stack_v2_sparse_classes_36k_train_007880 | 1,795 | no_license | [
{
"docstring": "bfs 迭代：相对来说用队列就能实现",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "递归",
"name": "levelOrder1",
"signature": "def levelOrder1(self, root: TreeNode) -> List[List[int]]"
}
] | 2 | stack_v2_sparse_classes_30k_train_003916 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root: TreeNode) -> List[List[int]]: bfs 迭代：相对来说用队列就能实现
- def levelOrder1(self, root: TreeNode) -> List[List[int]]: 递归
<|skeleton|>
class Solution:
def ... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
<|body_0|>
def levelOrder1(self, root: TreeNode) -> List[List[int]]:
"""递归"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""bfs 迭代：相对来说用队列就能实现"""
if not root:
return []
res = []
queue = [root]
while queue:
level_node = []
temp = []
for i in queue:
level_node.a... | the_stack_v2_python_sparse | 算法/Week_02/102. 二叉树的层序遍历.py | RichieSong/algorithm | train | 0 | |
60623294a2ea0333045f1d14b7aee33888e8f283 | [
"parser.add_argument('name', help='The name of this cluster.')\nparser.add_argument('--size', required=True, type=int, help='Target number of nodes in the cluster.')\nparser.add_argument('--wait', action='store_true', default=True, help='Poll the operation for completion after issuing an resize request.')",
"adap... | <|body_start_0|>
parser.add_argument('name', help='The name of this cluster.')
parser.add_argument('--size', required=True, type=int, help='Target number of nodes in the cluster.')
parser.add_argument('--wait', action='store_true', default=True, help='Poll the operation for completion after issu... | Resizes an existing cluster for running containers. | Resize | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resize:
"""Resizes an existing cluster for running containers."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|body_0... | stack_v2_sparse_classes_36k_train_007881 | 4,051 | permissive | [
{
"docstring": "Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "This is what gets called when the... | 2 | stack_v2_sparse_classes_30k_train_016715 | Implement the Python class `Resize` described below.
Class description:
Resizes an existing cluster for running containers.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information... | Implement the Python class `Resize` described below.
Class description:
Resizes an existing cluster for running containers.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information... | dcf4886d4ec06b13282143ef795c5f0ff20ffee3 | <|skeleton|>
class Resize:
"""Resizes an existing cluster for running containers."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Resize:
"""Resizes an existing cluster for running containers."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
parser.add_argument('... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/surface/container/clusters/resize.py | MD-Anderson-Bioinformatics/NG-CHM_Galaxy | train | 0 |
f7ac0c24b999710288fa4acd6e663b5b6e71df72 | [
"if app == 'cmdb':\n engine = create_engine(config_name.CMDB_DATABASE_URI)\nelif app == 'earthworm':\n engine = create_engine(config_name.EARTHWORM_DATABASE_URI)\nelif app == 'medusa':\n engine = create_engine(config_name.MEDUSA_DATABASE_URI)\nelif app == 'bigdata':\n engine = create_engine(config_name.... | <|body_start_0|>
if app == 'cmdb':
engine = create_engine(config_name.CMDB_DATABASE_URI)
elif app == 'earthworm':
engine = create_engine(config_name.EARTHWORM_DATABASE_URI)
elif app == 'medusa':
engine = create_engine(config_name.MEDUSA_DATABASE_URI)
e... | Define MySQL_query | MySQL_query | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQL_query:
"""Define MySQL_query"""
def sql_query(self, sql, app):
"""Define sql_query"""
<|body_0|>
def mysql_RowProxy_to_str(self, sql, app):
"""将MySQl Proxy数据转换为字符串数据"""
<|body_1|>
def mysql_RowProxy_to_list(self, sql, fields, app):
"""将... | stack_v2_sparse_classes_36k_train_007882 | 4,991 | no_license | [
{
"docstring": "Define sql_query",
"name": "sql_query",
"signature": "def sql_query(self, sql, app)"
},
{
"docstring": "将MySQl Proxy数据转换为字符串数据",
"name": "mysql_RowProxy_to_str",
"signature": "def mysql_RowProxy_to_str(self, sql, app)"
},
{
"docstring": "将MySQl Proxy数据转换为列表数据",
... | 4 | stack_v2_sparse_classes_30k_train_020394 | Implement the Python class `MySQL_query` described below.
Class description:
Define MySQL_query
Method signatures and docstrings:
- def sql_query(self, sql, app): Define sql_query
- def mysql_RowProxy_to_str(self, sql, app): 将MySQl Proxy数据转换为字符串数据
- def mysql_RowProxy_to_list(self, sql, fields, app): 将MySQl Proxy数据转换... | Implement the Python class `MySQL_query` described below.
Class description:
Define MySQL_query
Method signatures and docstrings:
- def sql_query(self, sql, app): Define sql_query
- def mysql_RowProxy_to_str(self, sql, app): 将MySQl Proxy数据转换为字符串数据
- def mysql_RowProxy_to_list(self, sql, fields, app): 将MySQl Proxy数据转换... | 2de82e898524194b3b735835c044f078cc6ee5ba | <|skeleton|>
class MySQL_query:
"""Define MySQL_query"""
def sql_query(self, sql, app):
"""Define sql_query"""
<|body_0|>
def mysql_RowProxy_to_str(self, sql, app):
"""将MySQl Proxy数据转换为字符串数据"""
<|body_1|>
def mysql_RowProxy_to_list(self, sql, fields, app):
"""将... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MySQL_query:
"""Define MySQL_query"""
def sql_query(self, sql, app):
"""Define sql_query"""
if app == 'cmdb':
engine = create_engine(config_name.CMDB_DATABASE_URI)
elif app == 'earthworm':
engine = create_engine(config_name.EARTHWORM_DATABASE_URI)
e... | the_stack_v2_python_sparse | project/business_0321/app/db.py | visionguo/python | train | 0 |
3f212b9cf18461f4f8b7521317851cebffca86e4 | [
"while low <= high:\n if s[low] == s[high]:\n low += 1\n high -= 1\n else:\n return False\nreturn True",
"for size in range(len(s), -1, -1):\n print(len(s), size)\n for low in range(len(s)):\n high = low + (size - 1)\n if high < len(s):\n if self.shrinkChe... | <|body_start_0|>
while low <= high:
if s[low] == s[high]:
low += 1
high -= 1
else:
return False
return True
<|end_body_0|>
<|body_start_1|>
for size in range(len(s), -1, -1):
print(len(s), size)
for ... | Brute-force暴力求解法 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Brute-force暴力求解法"""
def shrinkCheckPalindrome(self, s, low, high):
"""判断传递的序列是否为回文序列，s[low:high+1]"""
<|body_0|>
def longestPalindrome(self, s):
"""暴力法解回文子串，实际上是滑动窗口，O(n^3)，由于是滑动，因此找的就是最长子串"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_007883 | 5,121 | no_license | [
{
"docstring": "判断传递的序列是否为回文序列，s[low:high+1]",
"name": "shrinkCheckPalindrome",
"signature": "def shrinkCheckPalindrome(self, s, low, high)"
},
{
"docstring": "暴力法解回文子串，实际上是滑动窗口，O(n^3)，由于是滑动，因此找的就是最长子串",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Brute-force暴力求解法
Method signatures and docstrings:
- def shrinkCheckPalindrome(self, s, low, high): 判断传递的序列是否为回文序列，s[low:high+1]
- def longestPalindrome(self, s): 暴力法解回文子串，实际上是滑动窗口，O(n^3)，由于是滑动，因此找的就是最长子串 | Implement the Python class `Solution` described below.
Class description:
Brute-force暴力求解法
Method signatures and docstrings:
- def shrinkCheckPalindrome(self, s, low, high): 判断传递的序列是否为回文序列，s[low:high+1]
- def longestPalindrome(self, s): 暴力法解回文子串，实际上是滑动窗口，O(n^3)，由于是滑动，因此找的就是最长子串
<|skeleton|>
class Solution:
"""Br... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class Solution:
"""Brute-force暴力求解法"""
def shrinkCheckPalindrome(self, s, low, high):
"""判断传递的序列是否为回文序列，s[low:high+1]"""
<|body_0|>
def longestPalindrome(self, s):
"""暴力法解回文子串，实际上是滑动窗口，O(n^3)，由于是滑动，因此找的就是最长子串"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Brute-force暴力求解法"""
def shrinkCheckPalindrome(self, s, low, high):
"""判断传递的序列是否为回文序列，s[low:high+1]"""
while low <= high:
if s[low] == s[high]:
low += 1
high -= 1
else:
return False
return True
... | the_stack_v2_python_sparse | other_code_programe/13、最长回文子串.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 |
e9222265dbb0c5a516e2e8ee11841331c0710897 | [
"args = self.parser.parse_args()\ndata = self.build_data(args=args, collection='github_task')\nreturn data",
"args = self.parse_args(add_github_task_fields)\nname = args.pop('name')\nkeyword = args.pop('keyword')\nkeyword = keyword.strip()\nif not keyword:\n return utils.build_ret(ErrorMsg.GithubKeywordEmpty, ... | <|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='github_task')
return data
<|end_body_0|>
<|body_start_1|>
args = self.parse_args(add_github_task_fields)
name = args.pop('name')
keyword = args.pop('keyword')
keyword =... | ARLGithubTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARLGithubTask:
def get(self):
"""Github 任务信息查询"""
<|body_0|>
def post(self):
"""Github 任务添加"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='github_task')
r... | stack_v2_sparse_classes_36k_train_007884 | 4,825 | no_license | [
{
"docstring": "Github 任务信息查询",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Github 任务添加",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `ARLGithubTask` described below.
Class description:
Implement the ARLGithubTask class.
Method signatures and docstrings:
- def get(self): Github 任务信息查询
- def post(self): Github 任务添加 | Implement the Python class `ARLGithubTask` described below.
Class description:
Implement the ARLGithubTask class.
Method signatures and docstrings:
- def get(self): Github 任务信息查询
- def post(self): Github 任务添加
<|skeleton|>
class ARLGithubTask:
def get(self):
"""Github 任务信息查询"""
<|body_0|>
de... | 5ca64806252b9e7e6d2b31a6bfaeecbfdc4baf06 | <|skeleton|>
class ARLGithubTask:
def get(self):
"""Github 任务信息查询"""
<|body_0|>
def post(self):
"""Github 任务添加"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ARLGithubTask:
def get(self):
"""Github 任务信息查询"""
args = self.parser.parse_args()
data = self.build_data(args=args, collection='github_task')
return data
def post(self):
"""Github 任务添加"""
args = self.parse_args(add_github_task_fields)
name = args.po... | the_stack_v2_python_sparse | app/routes/github_task.py | QmF0c3UK/ARL | train | 0 | |
eb18669ec44bb22f4136f5cbfc51746a4af27340 | [
"super(LinkTask, self).__init__(*args, **kwargs)\nself.setOption('type', self.__defaultLinkType)\nself.setMetadata('dispatch.split', True)\nself.setMetadata('dispatch.splitSize', 20)",
"assert self.option('type') in ('hardlink', 'symlink'), 'Invalid link type {}'.format(self.option())\nfor crawler in self.crawler... | <|body_start_0|>
super(LinkTask, self).__init__(*args, **kwargs)
self.setOption('type', self.__defaultLinkType)
self.setMetadata('dispatch.split', True)
self.setMetadata('dispatch.splitSize', 20)
<|end_body_0|>
<|body_start_1|>
assert self.option('type') in ('hardlink', 'symlink... | Links (hardlink or symlink) a file to the target file path. | LinkTask | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkTask:
"""Links (hardlink or symlink) a file to the target file path."""
def __init__(self, *args, **kwargs):
"""Create a Link task."""
<|body_0|>
def _perform(self):
"""Perform the task."""
<|body_1|>
def __linkOnWindows(self, sourceFilePath, tar... | stack_v2_sparse_classes_36k_train_007885 | 3,884 | permissive | [
{
"docstring": "Create a Link task.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Perform the task.",
"name": "_perform",
"signature": "def _perform(self)"
},
{
"docstring": "Create a link on windows.",
"name": "__linkOnWindows",
... | 4 | stack_v2_sparse_classes_30k_train_011863 | Implement the Python class `LinkTask` described below.
Class description:
Links (hardlink or symlink) a file to the target file path.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a Link task.
- def _perform(self): Perform the task.
- def __linkOnWindows(self, sourceFilePath, targetF... | Implement the Python class `LinkTask` described below.
Class description:
Links (hardlink or symlink) a file to the target file path.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a Link task.
- def _perform(self): Perform the task.
- def __linkOnWindows(self, sourceFilePath, targetF... | 046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4 | <|skeleton|>
class LinkTask:
"""Links (hardlink or symlink) a file to the target file path."""
def __init__(self, *args, **kwargs):
"""Create a Link task."""
<|body_0|>
def _perform(self):
"""Perform the task."""
<|body_1|>
def __linkOnWindows(self, sourceFilePath, tar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkTask:
"""Links (hardlink or symlink) a file to the target file path."""
def __init__(self, *args, **kwargs):
"""Create a Link task."""
super(LinkTask, self).__init__(*args, **kwargs)
self.setOption('type', self.__defaultLinkType)
self.setMetadata('dispatch.split', True... | the_stack_v2_python_sparse | src/lib/kombi/Task/Fs/LinkTask.py | kombiHQ/kombi | train | 2 |
a322709883ba2162eda57f91394f82336c53fa2e | [
"cur = 0\ncount = 1\nwhile cur < len(chars) - 1:\n if chars[cur] == chars[cur + 1]:\n chars.pop(cur + 1)\n count += 1\n elif count > 1:\n tmp = list(str(count))\n for i in range(len(tmp)):\n chars.insert(cur + 1 + i, tmp[i])\n cur += len(tmp) + 1\n count = ... | <|body_start_0|>
cur = 0
count = 1
while cur < len(chars) - 1:
if chars[cur] == chars[cur + 1]:
chars.pop(cur + 1)
count += 1
elif count > 1:
tmp = list(str(count))
for i in range(len(tmp)):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def compress(self, chars):
"""1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int"""
<|body_0|>
def compress2(self, chars):
"""1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_007886 | 2,481 | no_license | [
{
"docstring": "1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int",
"name": "compress",
"signature": "def compress(self, chars)"
},
{
"docstring": "1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int",
"name": "compress2",
"signature": "def compress2(self, chars)"... | 2 | stack_v2_sparse_classes_30k_train_008085 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compress(self, chars): 1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int
- def compress2(self, chars): 1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def compress(self, chars): 1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int
- def compress2(self, chars): 1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype:... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def compress(self, chars):
"""1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int"""
<|body_0|>
def compress2(self, chars):
"""1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def compress(self, chars):
"""1个字符保持不动 2个以上连续字符以字符,出现次数代替 :type chars: List[str] :rtype: int"""
cur = 0
count = 1
while cur < len(chars) - 1:
if chars[cur] == chars[cur + 1]:
chars.pop(cur + 1)
count += 1
elif co... | the_stack_v2_python_sparse | 443_压缩字符串.py | lovehhf/LeetCode | train | 0 | |
75ed678640172f8257fa267e9ee9d61cc00d8d3e | [
"assert isinstance(lambda_lineno, int), f'{repr(lambda_lineno)} not integer.'\nassert lambda_lineno >= 0, f'{lambda_lineno} < 0.'\nsuper().__init__()\nself._lambda_lineno = lambda_lineno\nself.lambdas_code: List[str] = []",
"if node.lineno == self._lambda_lineno:\n self.lambdas_code.append(ast_unparse(node))\n... | <|body_start_0|>
assert isinstance(lambda_lineno, int), f'{repr(lambda_lineno)} not integer.'
assert lambda_lineno >= 0, f'{lambda_lineno} < 0.'
super().__init__()
self._lambda_lineno = lambda_lineno
self.lambdas_code: List[str] = []
<|end_body_0|>
<|body_start_1|>
if no... | **Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those lambda functions by applying the visitor design pattern to an AST parsed from that block... | _LambdaNodeUnparser | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _LambdaNodeUnparser:
"""**Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those lambda functions by applying the visitor ... | stack_v2_sparse_classes_36k_train_007887 | 32,447 | permissive | [
{
"docstring": "Initialize this visitor. Parameters ---------- lambda_lineno : int Caller-specific line number (of the code from which the AST visited by this object was parsed) starting the definition of the lambda functions to be unparsed by this visitor.",
"name": "__init__",
"signature": "def __init... | 2 | null | Implement the Python class `_LambdaNodeUnparser` described below.
Class description:
**Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those la... | Implement the Python class `_LambdaNodeUnparser` described below.
Class description:
**Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those la... | 0cfd53391eb4de2f8297a4632aa5895b8d82a5b7 | <|skeleton|>
class _LambdaNodeUnparser:
"""**Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those lambda functions by applying the visitor ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _LambdaNodeUnparser:
"""**Lambda node unparser** (i.e., object decompiling the abstract syntax tree (AST) nodes of *all* pure-Python lambda functions defined in a caller-specified block of source code into the exact substrings of that block defining those lambda functions by applying the visitor design patter... | the_stack_v2_python_sparse | beartype/_util/func/utilfunccode.py | beartype/beartype | train | 1,992 |
60d1c2446d772b0cd36a17b045f1f3f9b432cf6e | [
"super().__init__()\nself.steps = None\nself.dt = None\nself.max_t = None",
"if 'steps' in conf:\n self.steps = conf.getint('steps')\nif 'dt' in conf:\n self.dt = conf.getfloat('dt')\nif 'max_t' in conf:\n self.max_t = conf.getfloat('max_t')"
] | <|body_start_0|>
super().__init__()
self.steps = None
self.dt = None
self.max_t = None
<|end_body_0|>
<|body_start_1|>
if 'steps' in conf:
self.steps = conf.getint('steps')
if 'dt' in conf:
self.dt = conf.getfloat('dt')
if 'max_t' in conf:... | A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until. | TimeParser | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeParser:
"""A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until."""
def __init__(self):
"""Initialiser for the TimePar... | stack_v2_sparse_classes_36k_train_007888 | 1,165 | permissive | [
{
"docstring": "Initialiser for the TimeParser class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Parse the given config section into the relevent time values. Args: conf (configparser section): The config section for the time values.",
"name": "parse",
"si... | 2 | stack_v2_sparse_classes_30k_train_018113 | Implement the Python class `TimeParser` described below.
Class description:
A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until.
Method signatures and docs... | Implement the Python class `TimeParser` described below.
Class description:
A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until.
Method signatures and docs... | cc4e7f7b9abb498893aaa05e2b25416f513905b0 | <|skeleton|>
class TimeParser:
"""A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until."""
def __init__(self):
"""Initialiser for the TimePar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeParser:
"""A parser for the time section of the config file. Attributes: steps (int): The instantiated number of steps for time iteration. dt (float): The value for dt (change in time) max_t (float): The time to iterate until."""
def __init__(self):
"""Initialiser for the TimeParser class."""... | the_stack_v2_python_sparse | TTiP/parsers/time_parser.py | AndrewLister-STFC/TTiP | train | 0 |
e6732ba6a86095764ae879dd4265332e695d1e85 | [
"self.ddve = DDVEManager()\nself.ddboost = DDBoostManager()\nself.parameters = ParameterManager()\nself.database = DatabaseManager()",
"storage_unit = self.database.get_storage_unit_by_id(operation.storage_unit_id)\nself.ddve.clear_results()\nself.parameters.set_parameters(storage_unit.name, operation.parameters)... | <|body_start_0|>
self.ddve = DDVEManager()
self.ddboost = DDBoostManager()
self.parameters = ParameterManager()
self.database = DatabaseManager()
<|end_body_0|>
<|body_start_1|>
storage_unit = self.database.get_storage_unit_by_id(operation.storage_unit_id)
self.ddve.clea... | Maintains the subsystems required for the execution of an operation. | OperationManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OperationManager:
"""Maintains the subsystems required for the execution of an operation."""
def __init__(self):
"""Initializes the subsystems required for the execution of an operation."""
<|body_0|>
def execute_operation(self, operation: Operation) -> None:
"""... | stack_v2_sparse_classes_36k_train_007889 | 1,429 | no_license | [
{
"docstring": "Initializes the subsystems required for the execution of an operation.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Executes an operation by passing it to the subsystems in the proper order. :param operation: operation inputs and storage for outputs ... | 2 | stack_v2_sparse_classes_30k_train_013575 | Implement the Python class `OperationManager` described below.
Class description:
Maintains the subsystems required for the execution of an operation.
Method signatures and docstrings:
- def __init__(self): Initializes the subsystems required for the execution of an operation.
- def execute_operation(self, operation:... | Implement the Python class `OperationManager` described below.
Class description:
Maintains the subsystems required for the execution of an operation.
Method signatures and docstrings:
- def __init__(self): Initializes the subsystems required for the execution of an operation.
- def execute_operation(self, operation:... | d8ee7c1608cad88f7c64410de49a07bf7b621be0 | <|skeleton|>
class OperationManager:
"""Maintains the subsystems required for the execution of an operation."""
def __init__(self):
"""Initializes the subsystems required for the execution of an operation."""
<|body_0|>
def execute_operation(self, operation: Operation) -> None:
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OperationManager:
"""Maintains the subsystems required for the execution of an operation."""
def __init__(self):
"""Initializes the subsystems required for the execution of an operation."""
self.ddve = DDVEManager()
self.ddboost = DDBoostManager()
self.parameters = Paramet... | the_stack_v2_python_sparse | readop/managers/operation.py | wma8/SeniorDesign | train | 0 |
4f5627fc3183b6714c6c39d26d80be832e9f5f16 | [
"self.fileHandle = fileHandle\nself.dagPath = dagPath\nself.fFluid = OpenMayaFX.MFnFluid(dagPath)",
"xPtr = OpenMaya.MScriptUtil().asDoublePtr()\nyPtr = OpenMaya.MScriptUtil().asDoublePtr()\nzPtr = OpenMaya.MScriptUtil().asDoublePtr()\nself.fFluid.getDimensions(xPtr, yPtr, zPtr)\ndimX = OpenMaya.MScriptUtil(xPtr)... | <|body_start_0|>
self.fileHandle = fileHandle
self.dagPath = dagPath
self.fFluid = OpenMayaFX.MFnFluid(dagPath)
<|end_body_0|>
<|body_start_1|>
xPtr = OpenMaya.MScriptUtil().asDoublePtr()
yPtr = OpenMaya.MScriptUtil().asDoublePtr()
zPtr = OpenMaya.MScriptUtil().asDoubleP... | Fluid volume export module | Volume | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Volume:
"""Fluid volume export module"""
def __init__(self, fileHandle, dagPath):
"""Set up the objects we're dealing with"""
<|body_0|>
def getOutput(self):
"""Read Fluid data and export as volumegrid"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_007890 | 2,972 | no_license | [
{
"docstring": "Set up the objects we're dealing with",
"name": "__init__",
"signature": "def __init__(self, fileHandle, dagPath)"
},
{
"docstring": "Read Fluid data and export as volumegrid",
"name": "getOutput",
"signature": "def getOutput(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001198 | Implement the Python class `Volume` described below.
Class description:
Fluid volume export module
Method signatures and docstrings:
- def __init__(self, fileHandle, dagPath): Set up the objects we're dealing with
- def getOutput(self): Read Fluid data and export as volumegrid | Implement the Python class `Volume` described below.
Class description:
Fluid volume export module
Method signatures and docstrings:
- def __init__(self, fileHandle, dagPath): Set up the objects we're dealing with
- def getOutput(self): Read Fluid data and export as volumegrid
<|skeleton|>
class Volume:
"""Fluid... | 3891e40c3c4c3a054e5ff1ff16d051d4e690cc4a | <|skeleton|>
class Volume:
"""Fluid volume export module"""
def __init__(self, fileHandle, dagPath):
"""Set up the objects we're dealing with"""
<|body_0|>
def getOutput(self):
"""Read Fluid data and export as volumegrid"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Volume:
"""Fluid volume export module"""
def __init__(self, fileHandle, dagPath):
"""Set up the objects we're dealing with"""
self.fileHandle = fileHandle
self.dagPath = dagPath
self.fFluid = OpenMayaFX.MFnFluid(dagPath)
def getOutput(self):
"""Read Fluid data... | the_stack_v2_python_sparse | luxPlugin/Lux/LuxExportModules/Volume.py | LuxRender/LuxMaya | train | 0 |
06712df722daef3cad57696b16caa699ca04d773 | [
"self.cap = capacity\nself.cache = {}\nself.freqs = {}\nself.freqstart, self.freqend = new_link()",
"if key not in self.cache:\n return -1\nnode = self.cache[key]\nfreq = self.freqs[node.freq]\nif detach(node):\n detach(freq)\n del self.freqs[node.freq]\nnode.freq += 1\nif node.freq not in self.freqs:\n ... | <|body_start_0|>
self.cap = capacity
self.cache = {}
self.freqs = {}
self.freqstart, self.freqend = new_link()
<|end_body_0|>
<|body_start_1|>
if key not in self.cache:
return -1
node = self.cache[key]
freq = self.freqs[node.freq]
if detach(no... | LFUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_007891 | 2,486 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: void",
"name": "pu... | 3 | stack_v2_sparse_classes_30k_train_020431 | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void | Implement the Python class `LFUCache` described below.
Class description:
Implement the LFUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: void
<|sk... | 882f0223bbc139ef201a777aa2dca6df01cd06ce | <|skeleton|>
class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: void"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LFUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.cap = capacity
self.cache = {}
self.freqs = {}
self.freqstart, self.freqend = new_link()
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.cache:
... | the_stack_v2_python_sparse | 2017/460.py | linmounong/leetcode | train | 0 | |
50c524c38b70846de1e18cbc5a633ccf162dae6a | [
"from ..objects.volumes import VolumeObject\nnode = self.get_object_or_404(objects.Node, node_id)\nnode_volumes = VolumeObject.get_volumes(node)\nreturn DisksFormatConvertor.format_disks_to_simple(node_volumes)",
"from ..objects.volumes import VolumeObject\nnode = self.get_object_or_404(objects.Node, node_id)\nda... | <|body_start_0|>
from ..objects.volumes import VolumeObject
node = self.get_object_or_404(objects.Node, node_id)
node_volumes = VolumeObject.get_volumes(node)
return DisksFormatConvertor.format_disks_to_simple(node_volumes)
<|end_body_0|>
<|body_start_1|>
from ..objects.volumes ... | NodeDisksHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NodeDisksHandler:
def GET(self, node_id):
""":returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)"""
<|body_0|>
def PUT(self, node_id):
""":returns: JSONized node disks. :http: * 200 (OK) * 400 (invalid disks data specified) * 404 (node not f... | stack_v2_sparse_classes_36k_train_007892 | 3,280 | permissive | [
{
"docstring": ":returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)",
"name": "GET",
"signature": "def GET(self, node_id)"
},
{
"docstring": ":returns: JSONized node disks. :http: * 200 (OK) * 400 (invalid disks data specified) * 404 (node not found in db)",
"name":... | 2 | null | Implement the Python class `NodeDisksHandler` described below.
Class description:
Implement the NodeDisksHandler class.
Method signatures and docstrings:
- def GET(self, node_id): :returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)
- def PUT(self, node_id): :returns: JSONized node disks. :ht... | Implement the Python class `NodeDisksHandler` described below.
Class description:
Implement the NodeDisksHandler class.
Method signatures and docstrings:
- def GET(self, node_id): :returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)
- def PUT(self, node_id): :returns: JSONized node disks. :ht... | 0e09dce510927f2cc490b898e5fe3f813bd791be | <|skeleton|>
class NodeDisksHandler:
def GET(self, node_id):
""":returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)"""
<|body_0|>
def PUT(self, node_id):
""":returns: JSONized node disks. :http: * 200 (OK) * 400 (invalid disks data specified) * 404 (node not f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NodeDisksHandler:
def GET(self, node_id):
""":returns: JSONized node disks. :http: * 200 (OK) * 404 (node not found in db)"""
from ..objects.volumes import VolumeObject
node = self.get_object_or_404(objects.Node, node_id)
node_volumes = VolumeObject.get_volumes(node)
re... | the_stack_v2_python_sparse | nailgun/nailgun/extensions/volume_manager/handlers/disks.py | mba811/fuel-web | train | 1 | |
479f18f93a6cdadd8747296c789277857a1cde25 | [
"if datasrc is None:\n args = parser.parse_args()\n datasrc = args.datasrc\nsuper().__init__(id_=id_, original_id=original_id, env_knl=env_knl, connection=connection, agts_addrs=agts_addrs, variant=variant, depth=depth, gpu=gpu, interaction=interaction, datasrc=datasrc)",
"vtx = self.pos[0]\nscalar_ngbs = g... | <|body_start_0|>
if datasrc is None:
args = parser.parse_args()
datasrc = args.datasrc
super().__init__(id_=id_, original_id=original_id, env_knl=env_knl, connection=connection, agts_addrs=agts_addrs, variant=variant, depth=depth, gpu=gpu, interaction=interaction, datasrc=datasrc... | RNNLSTMPathMaker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNLSTMPathMaker:
def __init__(self, id_: int, original_id: str, env_knl: EnvironmentKnowledge, connection: Connection, agts_addrs: list, variant: str='', gpu: bool=False, depth: float=3.0, interaction: bool=True, datasrc: str=None):
"""Args: id_ (int): original_id (str): env_knl (Enviro... | stack_v2_sparse_classes_36k_train_007893 | 2,604 | permissive | [
{
"docstring": "Args: id_ (int): original_id (str): env_knl (EnvironmentKnowledge): connection (Connection): agts_addrs (list): variant (str): gpu (bool): depth (float): interaction (bool): datasrc (str):",
"name": "__init__",
"signature": "def __init__(self, id_: int, original_id: str, env_knl: Environ... | 2 | stack_v2_sparse_classes_30k_train_003392 | Implement the Python class `RNNLSTMPathMaker` described below.
Class description:
Implement the RNNLSTMPathMaker class.
Method signatures and docstrings:
- def __init__(self, id_: int, original_id: str, env_knl: EnvironmentKnowledge, connection: Connection, agts_addrs: list, variant: str='', gpu: bool=False, depth: f... | Implement the Python class `RNNLSTMPathMaker` described below.
Class description:
Implement the RNNLSTMPathMaker class.
Method signatures and docstrings:
- def __init__(self, id_: int, original_id: str, env_knl: EnvironmentKnowledge, connection: Connection, agts_addrs: list, variant: str='', gpu: bool=False, depth: f... | 1b9634fb97e77407b4c609399c27663396a8d7e3 | <|skeleton|>
class RNNLSTMPathMaker:
def __init__(self, id_: int, original_id: str, env_knl: EnvironmentKnowledge, connection: Connection, agts_addrs: list, variant: str='', gpu: bool=False, depth: float=3.0, interaction: bool=True, datasrc: str=None):
"""Args: id_ (int): original_id (str): env_knl (Enviro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNLSTMPathMaker:
def __init__(self, id_: int, original_id: str, env_knl: EnvironmentKnowledge, connection: Connection, agts_addrs: list, variant: str='', gpu: bool=False, depth: float=3.0, interaction: bool=True, datasrc: str=None):
"""Args: id_ (int): original_id (str): env_knl (EnvironmentKnowledge... | the_stack_v2_python_sparse | pytrol/control/agent/RNNLSTMPathMaker.py | mothguib/pytrol | train | 0 | |
2abaee166f1a4df5b395d72c015ba69770a13432 | [
"self.flow_hash = flow_hash\nself.classified = 0\nself.classification_tag = ''\nself.classification_time = 0\nself.actions = {}\nself.clsfn = clsfn\nself.time_limit = time_limit\nself.logger = logger\ndb_data = {'flow_hash': self.flow_hash}\ndb_data['classification_time'] = {'$gte': datetime.datetime.now() - self.t... | <|body_start_0|>
self.flow_hash = flow_hash
self.classified = 0
self.classification_tag = ''
self.classification_time = 0
self.actions = {}
self.clsfn = clsfn
self.time_limit = time_limit
self.logger = logger
db_data = {'flow_hash': self.flow_hash}... | An object that represents an individual traffic classification | Classification | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backw... | stack_v2_sparse_classes_36k_train_007894 | 44,404 | permissive | [
{
"docstring": "Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backwards by number of seconds defined in config for classification_time_limit Setting test returns database query execution statistics",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_test_000092 | Implement the Python class `Classification` described below.
Class description:
An object that represents an individual traffic classification
Method signatures and docstrings:
- def __init__(self, flow_hash, clsfn, time_limit, logger): Retrieve classification data from MongoDB collection for a particular flow hash w... | Implement the Python class `Classification` described below.
Class description:
An object that represents an individual traffic classification
Method signatures and docstrings:
- def __init__(self, flow_hash, clsfn, time_limit, logger): Retrieve classification data from MongoDB collection for a particular flow hash w... | 55cc27e81defc42775ff563bfbef31800e089b14 | <|skeleton|>
class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backw... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Classification:
"""An object that represents an individual traffic classification"""
def __init__(self, flow_hash, clsfn, time_limit, logger):
"""Retrieve classification data from MongoDB collection for a particular flow hash within a time range. time range is from current time backwards by numbe... | the_stack_v2_python_sparse | nmeta/flows.py | awesome-nfv/nmeta | train | 0 |
8dc8a8158830ee2d541d9f69a388c4de03808826 | [
"self.subsampling_factor = subsampling_factor\nself.ignore_id = -1\nself.dtype = dtype\nself.load_aux_input = load_aux_input\nself.load_aux_output = load_aux_output",
"assert len(batch) == 1\ndata, utts = batch[0]\nxs_data, ys_data = ([], [])\nfor ud in data:\n if ud[0].ndim > 1:\n xs_data.append(ud)\n ... | <|body_start_0|>
self.subsampling_factor = subsampling_factor
self.ignore_id = -1
self.dtype = dtype
self.load_aux_input = load_aux_input
self.load_aux_output = load_aux_output
<|end_body_0|>
<|body_start_1|>
assert len(batch) == 1
data, utts = batch[0]
x... | Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert. | CustomConverter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomConverter:
"""Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert."""
def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, load_aux_output=False):
"""Construct a CustomConverter objec... | stack_v2_sparse_classes_36k_train_007895 | 3,438 | permissive | [
{
"docstring": "Construct a CustomConverter object.",
"name": "__init__",
"signature": "def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, load_aux_output=False)"
},
{
"docstring": "Transform a batch and send it to a device. Args: batch (list): The batch to transfor... | 2 | null | Implement the Python class `CustomConverter` described below.
Class description:
Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert.
Method signatures and docstrings:
- def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, ... | Implement the Python class `CustomConverter` described below.
Class description:
Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert.
Method signatures and docstrings:
- def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, ... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class CustomConverter:
"""Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert."""
def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, load_aux_output=False):
"""Construct a CustomConverter objec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomConverter:
"""Custom batch converter. Args: subsampling_factor (int): The subsampling factor. dtype (np.dtype): Data type to convert."""
def __init__(self, subsampling_factor=1, dtype=np.float32, load_aux_input=False, load_aux_output=False):
"""Construct a CustomConverter object."""
... | the_stack_v2_python_sparse | paddlespeech/s2t/io/converter.py | anniyanvr/DeepSpeech-1 | train | 0 |
6e088a415b74b4137737d4446c87067d7db42359 | [
"if not num_rows:\n return []\npascal = [1] * (num_rows + 1)\nfor i in range(2, num_rows + 1):\n for j in range(1, i):\n pascal[i - j] += pascal[i - j - 1]\nreturn pascal",
"if not num_rows:\n return []\ntriangle = []\nfor row_num in range(num_rows):\n row = [None for _ in range(row_num + 1)]\n... | <|body_start_0|>
if not num_rows:
return []
pascal = [1] * (num_rows + 1)
for i in range(2, num_rows + 1):
for j in range(1, i):
pascal[i - j] += pascal[i - j - 1]
return pascal
<|end_body_0|>
<|body_start_1|>
if not num_rows:
... | PascalTriangle | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PascalTriangle:
def get_nth_row(self, num_rows: int) -> List[List[int]]:
"""Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:"""
<|body_0|>
def generate(self, num_rows: int) -> List[List[int]]:
"""Approach: DP Time Com... | stack_v2_sparse_classes_36k_train_007896 | 1,473 | no_license | [
{
"docstring": "Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:",
"name": "get_nth_row",
"signature": "def get_nth_row(self, num_rows: int) -> List[List[int]]"
},
{
"docstring": "Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(nu... | 2 | null | Implement the Python class `PascalTriangle` described below.
Class description:
Implement the PascalTriangle class.
Method signatures and docstrings:
- def get_nth_row(self, num_rows: int) -> List[List[int]]: Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:
- def gene... | Implement the Python class `PascalTriangle` described below.
Class description:
Implement the PascalTriangle class.
Method signatures and docstrings:
- def get_nth_row(self, num_rows: int) -> List[List[int]]: Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:
- def gene... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class PascalTriangle:
def get_nth_row(self, num_rows: int) -> List[List[int]]:
"""Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:"""
<|body_0|>
def generate(self, num_rows: int) -> List[List[int]]:
"""Approach: DP Time Com... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PascalTriangle:
def get_nth_row(self, num_rows: int) -> List[List[int]]:
"""Approach: DP Time Complexity: O(num_rows^2) Space Complexity: O(num_row) :param num_rows: :return:"""
if not num_rows:
return []
pascal = [1] * (num_rows + 1)
for i in range(2, num_rows + 1)... | the_stack_v2_python_sparse | revisited/2d_arrays/pascal_triangle.py | Shiv2157k/leet_code | train | 1 | |
e89ef6f86e716dba631971f85e881459eb8d18a2 | [
"super().__init__('custom_unitary', children, None)\nself.id = children[0]\nself.name = self.id.name\nif len(children) == 3:\n self.arguments = children[1]\n self.bitlist = children[2]\nelse:\n self.arguments = None\n self.bitlist = children[1]",
"string = self.name\nif self.arguments is not None:\n ... | <|body_start_0|>
super().__init__('custom_unitary', children, None)
self.id = children[0]
self.name = self.id.name
if len(children) == 3:
self.arguments = children[1]
self.bitlist = children[2]
else:
self.arguments = None
self.bitli... | Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary_list node | CustomUnitary | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary... | stack_v2_sparse_classes_36k_train_007897 | 1,663 | permissive | [
{
"docstring": "Create the custom gate node.",
"name": "__init__",
"signature": "def __init__(self, children)"
},
{
"docstring": "Return the corresponding OPENQASM string.",
"name": "qasm",
"signature": "def qasm(self, prec=15)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010655 | Implement the Python class `CustomUnitary` described below.
Class description:
Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = N... | Implement the Python class `CustomUnitary` described below.
Class description:
Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = N... | abf6c23d4ab6c63f9c01c7434fb46321e6a69200 | <|skeleton|>
class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomUnitary:
"""Node for an OPENQASM custom gate statement. children[0] is an id node. children[1] is an exp_list (if len==3) or primary_list. children[2], if present, is a primary_list. Has properties: .id = id node .name = gate name string .arguments = None or exp_list node .bitlist = primary_list node"""... | the_stack_v2_python_sparse | qiskit/qasm/node/customunitary.py | indian-institute-of-science-qc/qiskit-aakash | train | 37 |
bd84700fa22473710204eab2fb0a9af8cadc356f | [
"assert isinstance(path_and_filename, str)\nassert width > 0 and height > 0\nassert output_format in [self.PNG, self.SVG, self.JPG, self.GIF]\nself.path_and_filename = path_and_filename\nself.plot_obj = plot_obj\nself.width = width\nself.height = height\nself.output_format = output_format",
"header = '#!/usr/bin/... | <|body_start_0|>
assert isinstance(path_and_filename, str)
assert width > 0 and height > 0
assert output_format in [self.PNG, self.SVG, self.JPG, self.GIF]
self.path_and_filename = path_and_filename
self.plot_obj = plot_obj
self.width = width
self.height = height
... | The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png). | script | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class script:
"""The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png)."""
def __init__(self, path_and_filename, plot_obj, width=640, height=480, output_format=PNG):
"""Init script and assert ... | stack_v2_sparse_classes_36k_train_007898 | 3,546 | permissive | [
{
"docstring": "Init script and assert parameters. :param path_and_filename: location to write script and where also to generate image. :param plot_obj: instance of a plot (or a multiplot) :param width: width of the final image (default 640) :param height: height of the final image (default 480) :param output_f... | 3 | stack_v2_sparse_classes_30k_train_003824 | Implement the Python class `script` described below.
Class description:
The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png).
Method signatures and docstrings:
- def __init__(self, path_and_filename, plot_obj, width=640... | Implement the Python class `script` described below.
Class description:
The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png).
Method signatures and docstrings:
- def __init__(self, path_and_filename, plot_obj, width=640... | 64e1f82de144f959cdf3c6dcf0f692bbc0ceb20f | <|skeleton|>
class script:
"""The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png)."""
def __init__(self, path_and_filename, plot_obj, width=640, height=480, output_format=PNG):
"""Init script and assert ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class script:
"""The scripts represents a whole gnuplot script. The main intention is to define the format, the file and to run gnuplot to generate the image (like png)."""
def __init__(self, path_and_filename, plot_obj, width=640, height=480, output_format=PNG):
"""Init script and assert parameters. :... | the_stack_v2_python_sparse | concept/graph/gnuplot/script.py | Nachtfeuer/concept-py | train | 2 |
46cbd726862a2c1d26e2813f68439fa48c908e69 | [
"self._config = config\nself._config_entry = config_entry\nself.device_id = device_id\nself.discovery_data = discovery_data\nself.hass = hass\nself._mqtt_data = get_mqtt_data(hass)\nMqttDiscoveryDeviceUpdate.__init__(self, hass, discovery_data, device_id, config_entry, LOG_NAME)",
"discovery_hash = self.discovery... | <|body_start_0|>
self._config = config
self._config_entry = config_entry
self.device_id = device_id
self.discovery_data = discovery_data
self.hass = hass
self._mqtt_data = get_mqtt_data(hass)
MqttDiscoveryDeviceUpdate.__init__(self, hass, discovery_data, device_id... | Setup a MQTT device trigger with auto discovery. | MqttDeviceTrigger | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MqttDeviceTrigger:
"""Setup a MQTT device trigger with auto discovery."""
def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None:
"""Initialize."""
<|body_0|>
async def async_setup... | stack_v2_sparse_classes_36k_train_007899 | 11,475 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None"
},
{
"docstring": "Initialize the device trigger.",
"name": "async_setup",
"s... | 4 | null | Implement the Python class `MqttDeviceTrigger` described below.
Class description:
Setup a MQTT device trigger with auto discovery.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None: Ini... | Implement the Python class `MqttDeviceTrigger` described below.
Class description:
Setup a MQTT device trigger with auto discovery.
Method signatures and docstrings:
- def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None: Ini... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class MqttDeviceTrigger:
"""Setup a MQTT device trigger with auto discovery."""
def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None:
"""Initialize."""
<|body_0|>
async def async_setup... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MqttDeviceTrigger:
"""Setup a MQTT device trigger with auto discovery."""
def __init__(self, hass: HomeAssistant, config: ConfigType, device_id: str, discovery_data: DiscoveryInfoType, config_entry: ConfigEntry) -> None:
"""Initialize."""
self._config = config
self._config_entry =... | the_stack_v2_python_sparse | homeassistant/components/mqtt/device_trigger.py | home-assistant/core | train | 35,501 |
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